Category: 8. Health

PROVIDENCE, R.I. [Brown University] — Triclosan is an antimicrobial chemical that was for decades added to everyday items like soap, toothpaste, cosmetics and even kitchen utensils and athletic wear, until concerns about potential health risks led manufacturers to phase it out of some products.

New research suggests there may be even more reason for concern. 

A study led by scientists at Brown University and the University of Massachusetts Amherst found that children with higher levels of triclosan in their bodies were more likely to have allergy-related health issues, with young boys appearing most affected.      

Published in Environmental Health Perspectives, the study followed 347 mothers and their children from pregnancy through the kids’ 12th birthdays. As part of the Cincinnati-based Health Outcomes and Measures of the Environment Study, researchers analyzed urine samples collected up to 10 times over that period to assess triclosan exposure in children. 

They found that children with higher levels of the chemical were more likely to develop allergic conditions like eczema and hay fever, a common allergy that causes sneezing, congestion and itchy eyes.

“The research showed a clear connection between this chemical and the allergic conditions we looked at,” said study senior author Joseph Braun, a professor of epidemiology and director of the Center for Climate, Environment and Health at Brown University’s School of Public Health. “What that all means is antimicrobial chemical exposure during susceptible periods of life, childhood in this case, might increase the risk of allergic disease.” 

The study found that children with twice the level of triclosan in their urine were 23% more likely to report eczema symptoms. This risk increased to nearly 40% by the time they were 8 to 12 years old. Similarly, children with twice the level of triclosan were 12% more likely to have symptoms of hay fever. Boys whose mothers had higher levels of triclosan during pregnancy were more likely than girls to show allergy symptoms.

The same reasons that make triclosan a health concern are in part what made it popular, said Hannah Laue, lead author of the study and an assistant epidemiology professor at UMass Amherst.

“Triclosan is effective at killing many bacteria, fungi and viruses,” Laue said. “While that’s useful for extending product shelf life or reducing odors in athletic wear, it can be harmful to humans. Our bodies rely on beneficial microbes to aid digestion and protect against pathogens. Exposure to triclosan may disrupt that healthy balance, leaving us more vulnerable to disease.”

Laue added that triclosan can also interfere with hormonal systems. 

“Some chemicals, including triclosan, can mimic or block hormones, potentially throwing essential systems into overdrive or shutting them down,” she said. “Triclosan has also been linked to reduced thyroid hormone levels, which are critical for healthy growth and development.”

A persistent antimicrobial

The U.S. Food and Drug Administration banned triclosan from over-the-counter hand soaps in 2016. Since then, many companies have voluntarily removed it from toothpaste and other products. Yet the chemical is still found in some consumer goods, including antimicrobial cutting boards, personal care items and clothing. Manufacturers are not required to list triclosan on product labels. 

The new study is part of an effort by Braun’s team to understand how antimicrobial chemicals affect children’s health. Working with Laue and others, the group has focused on the health effects of triclosan for the last three years, and they plan to track the young study participants into adulthood. The researchers are especially interested in how triclosan might disrupt the gut microbiome, which helps regulate immune responses, and what that means for adolescent and long-term health outcomes.

Braun and Laue hope this body of research will encourage both consumers and manufacturers to make safer choices.

“People can reduce their triclosan exposure by doing what they can to avoid products that contain it,” Braun said. “We also hope that this will prompt companies to consider using safer antimicrobial chemicals or avoiding them altogether in their products.”

The study was supported by the National Institute of Environmental Health Sciences and the National Center for Advancing Translational Sciences. Additional Brown University authors included Elvira Fleury, who earned a master of public health from Brown in 2024 and is now a doctoral student at Harvard University. 

This transcript has been edited for clarity. 

Hello, everyone. I’m Dr Bishal Gyawali, associate professor of oncology at Queens University, Kingston, Canada. I’m very happy to share with you some of the most exciting data that I just saw at the plenary session at ASCO 2025. 

Before that, I’m going to talk to you about a fantastic new drug called exercisumab. I’m joking, of course. Exercise has been shown to improve the lives of patients with colon cancer. I’m joking that if there were a drug called exercisumab, the data would be so compelling that we’d all want to use it and fund it today. 

Because this is not a drug and it’s about exercise, I see some challenges in implementation. I hope that I’m able to convince you that the data are really compelling and we should make an effort so that our health systems will integrate this as a part of cancer care for patients with high-risk stage II and stage III colon cancer who receive adjuvant chemotherapy. 

The trial I’m talking about is called the CHALLENGE trial, which was not presented at the plenary but should have been. In this trial, patients who had high-risk stage II and stage III colon cancer, after they completed their adjuvant chemotherapy, were randomized to receive a structured exercise program vs the standard-of-care arm. 

The standard-of-care arm patients received health education but did not receive a structured exercise program. The goal of the structured exercise program was to improve physical activity by at least 10 MET-hours compared to the baseline of these patients. 

The primary endpoint was disease-free survival. Disease-free survival was significantly improved, and overall survival was also significantly improved. The 5-year disease-free survival rates improved by almost 7%, and the 8-year overall survival rates also improved by a similar amount. The hazard ratio for disease-free survival was 0.72, and the hazard ratio for overall survival was 0.63. 

These are very compelling results. If you compare these results with results from other trials, you’ll see that this is a no-brainer. If this were a drug, you would want to use it today. 

There are some nuances about this trial that I want to highlight. When we talk about the results, some of the comments were, “Oh yes, I have been asking my patients to exercise anyway.” Exercise improves quality of life, it’ll reduce weight, and these are all known to benefit patients. 

I have been telling my patients to exercise, but this trial is not about telling patients to exercise. This trial is about having a formal, structured exercise program. There are particular details.

Patients need to have an in-person visit with a therapist every 2 weeks for the first year and then every month for the next 2 years, so it’s a 3-year therapy program. It’s a scientifically designed and tailored program. It’s not just saying, oh, you should exercise. In fact, saying you should exercise and giving some health education was the control arm of this treatment, not the interventional arm.

The control arm patients were told about this trial, the potential benefits of the exercise, why they should enroll in this trial, and they were given health education materials. An interesting observation is that even the control arm patients had improvements in their physical functioning, VO₂, and all those parameters from baseline to subsequent visits. 

One limitation is the adherence rate to exercise. We see that the adherence rate kept falling with time. I think that by the end of 3 years, the adherence rate to the exercise program was around 60%-65% in that ballpark, which is a limitation. Having said that, the analysis accounts for all of that.

Despite that limitation, we are seeing this substantial benefit. If you want to compare that with the ATOMIC trial, which was a plenary presentation of immunotherapy plus FOLFOX for patients who needed adjuvant FOLFOX in stage III colon cancer patients, of course, the addition of atezolizumab to FOLFOX improved disease-free survival rates. The primary endpoint here was 3-year disease-free survival, and it improved significantly. It was a plenary, and people were making the argument that this should immediately change practice. 

If you compare that with this exercise trial that I just discussed: A, think about the added toxicities; B, think about the added cost; and C, think about how feasible it is to implement. I think it’s a no-brainer that we need to start having health systems funds for a structured exercise program for our patients with colon cancer. 

Yes, the atezolizumab data and the ATOMIC trial data look very interesting and this is one of the first advances in treatment of adjuvant colon cancer in a long time. This is for patients with microsatellite instability-high status. We don’t have overall survival results yet. Disease-free survival is a much more reliable predictor of overall survival in this particular setting. I believe that overall survival might be positive, but we also need to know what percentage of these patients got immunotherapy when they relapsed, because immunotherapy is already standard of care for these patients when they relapse. 

The other point about this trial is, do they all actually need 1 year of atezolizumab? Probably not. As the discussant highlighted in her talk, in many settings, we are now using neoadjuvant strategies. Using two or three cycles might be enough.

The broader point that I’m trying to make is contrasting these two studies and inviting you to think about how different these are, even in terms of magnitude of benefit. The exercise trial has overall survival, not just disease-free survival, at an 8-year time point. 

When I asked Dr Booth about the cost of this intervention, he said for the whole 3-year time point, it might be around $3000 Canadian dollars. This trial was conducted mostly in Canada and in Australia. As opposed to atezolizumab, where a month of atezolizumab alone is going to cost $15,000, so that’s just a perspective I wanted to put forward. 

One more thing I wanted to talk about today is the SERENA-6 trial, which was discussed at the plenary session. This is a trial for patients with estrogen receptor-positive, HER2-negative metastatic breast cancer who have been on a CDK4/6 inhibitor plus aromatase inhibitor for 6 months. They were then tested with ctDNA to detect ESR1 mutations early, and if this was detected, then they were randomized to either follow the same treatment, which is the control arm, or get the new drug.

The primary endpoint here was progression-free survival. This was debated often during the season. We have so many debates about progression-free and overall survival, but for this particular trial, progression-free survival makes no sense because this is just detecting relapse early. Detecting relapse early does not always mean that you need to intervene early.

Of course, if you are intervening early, then you are going to prolong time to tumor progression. The progression-free survival in this sense is more like time on treatment with this drug rather than true progression-free survival. You’re just changing treatment early, and the control arm patients are not getting that treatment when they progress.

Measuring progression-free survival alone here felt similar to measuring CA-125, or whatever tumor markers we measure, then instituting treatment early and claiming that patients have a longer time on treatment, when in fact, it’s just lead time bias or intervening early without knowing that it’s going to improve outcomes.

A final trial from the plenary session was the MATTERHORN trial. I want to bring that up as well because this trial was investigating durvalumab plus perioperative FLOT in patients with esophageal cancers. This trial had a significant improvement in event-free survival, but has not improved overall survival yet. It may or may not translate into an overall survival improvement. 

The discussant did not cover the limitations of this trial well, and that’s why I wanted to bring it up. There are several factors to consider here. There are other trials in similar settings, where event-free or disease-free survival have improved, but overall survival has not. There is no point in getting super excited about this because it may not translate to overall survival, just like other immunotherapy trials in this space. 

The other thing is, we need to make sure what treatments patients are getting at the time of progression or at the time of relapse. Are they getting the right treatment?If they’re not getting the right treatment, then any survival difference can be simply a function of the control arm patients not getting the right treatment at the time of relapse. 

If we compare these results with results of other immunotherapy trials, I don’t think the results are substantially different. Yes, an event-free survival improvement is important, but especially in this setting, in this disease, we have seen other trials where disease-free or event-free survival have not necessarily led to an overall survival improvement. We need to be asking ourselves, can we claim that it is already practice changing without having those results? I don’t think that’s the case. 

Those are some of my thoughts from this year’s plenary session at ASCO 2025. Thank you.

Investigators have found that two common types of hormone therapy may alter breast cancer risk in women before age 55. Women treated with unopposed estrogen hormone therapy (E-HT) were less likely to develop the disease than those who did not use this type of hormone therapy. Additionally, women treated with estrogen plus progestin hormone therapy (EP-HT) were more likely to develop breast cancer than women who did not use this type of hormone therapy. Together, these results—published by O’Brien et al in The Lancet Oncology—may help to guide clinical recommendations for hormone therapy use among younger women.

The two hormone therapies analyzed in the study are often used to manage symptoms related to menopause or following hysterectomy or oophorectomy. Unopposed estrogen therapy is recommended only for women who have had a hysterectomy because of its known association with uterine cancer risk.

“Hormone therapy can greatly improve the quality of life for women experiencing severe menopausal symptoms or those who have had surgeries that affect their hormone levels,” said lead author Katie O’Brien, PhD, of the National Institutes of Health’s (NIH) National Institute of Environmental Health Sciences (NIEHS). “Our study provides greater understanding of the risks associated with different types of hormone therapy, which we hope will help patients and their doctors develop more informed treatment plans.”

Key Results

The researchers conducted a large-scale analysis that included data from more than 459,000 women younger than age 55 across North America, Europe, Asia, and Australia. Women who used E-HT had a 14% reduction in breast cancer incidence compared with those who never used this type of hormone therapy. Of note, this protective effect was more pronounced in women who started E-HT at younger ages or who used it longer. In contrast, women using EP-HT experienced a 10% higher rate of breast cancer compared with nonusers, with an 18% higher rate seen among women using EP-HT for more than 2 years relative to those who never used this type of therapy.

According to the authors, this suggests that for EP-HT users, the cumulative risk of breast cancer before age 55 could be about 4.5%, compared with a 4.1% risk for women who never used this type of hormone therapy and a 3.6% risk for those who used E-HT. Further, the association between EP-HT and breast cancer was particularly elevated among women who had not undergone hysterectomy or oophorectomy. That highlights the importance of considering gynecologic surgery status when evaluating the risks of starting hormone therapy, the researchers noted.

“These findings underscore the need for personalized medical advice when considering hormone therapy,” said NIEHS scientist and senior author Dale Sandler, PhD. “Women and their health-care providers should weigh the benefits of symptom relief against the potential risks associated with hormone therapy, especially EP-HT. For women with an intact uterus and ovaries, the increased risk of breast cancer with EP-HT should prompt careful deliberation.”

The authors noted that their study is consistent with previous large studies that documented similar associations between hormone therapy and breast cancer risk among older and postmenopausal women. This new study extends those findings to younger women, providing essential evidence to help guide decision-making for women as they go through menopause.

Disclosure: For full disclosures of the study authors, visit thelancet.com.

Uterine cancer is the fourth most common cancer diagnosed in women in the United States, with about 69,120 new cases and nearly 14,000 deaths from the disease expected this year. Black women experience a twice as high mortality rate compared with women of other races and ethnicities, and that number is expected to rise sharply over the coming decades.

According to a study by Wright et al published in Cancer Epidemiology, Biomarkers & Prevention, the incidence and mortality rates of uterine cancer in the United States are projected to increase significantly over the next 3 decades, with incidence-based mortality expected to be nearly three times higher in Black women compared with White women.

Study Methodology

The researchers developed the Columbia University Uterine Cancer Model (CU-UTMO) as part of the National Cancer Institute’s Cancer Intervention and Surveillance Modeling Network (CISNET). This state-transition microsimulation model simulates the trajectories for uterine cancer incidence and mortality based on characteristics from a sample population, taking into account age (between 18 and 84 years); Black and White race; birth cohort grouped in 10-year intervals starting in 1910 to 1920; cancer stage, as determined by the American Joint Committee on Cancer; and separately modeled endometrioid and nonendometrioid tumors, which usually have a worse prognosis.

To validate the model, the researchers used CU-UTMO to predict the median age of diagnosis, survival rate, and distribution of diagnosis by stage for uterine cancer in 2018; they found those projections were comparable to the actual Surveillance, Epidemiology, and End Results data from that year. Then the researchers estimated the future rates of the cancer based on publicly available sources through 2018.

Key Results

The researchers found that the model closely fit population-based incidence and mortality data of uterine cancer. They determined that from 2020 to 2050, the incidence of uterine cancer is projected to increase in White women to 74.2 cases per 100,000 (compared with 57.7 cases per 100,000 in 2018) and to increase to 86.9 cases per 100,000 (compared with 56.8 cases per 100,000 in 2018) in Black women.

Among White women, incidence-based mortality will increase from 6.1 per 100,000 in 2018 to 11.2 per 100,000 in 2050, and incidence-based mortality in Black women will increase from 14.1 per 100,000 to 27.9 per 100,000. In addition, the incidence of endometrioid tumors is expected to increase considerably in both White and Black women. However, although White women will experience only a slight increase in nonendometrioid tumors, the incidence of these tumors in Black women will increase substantially.

“These population-level trends support the urgent need to develop and implement novel primary and secondary prevention strategies for uterine cancer,” concluded the study authors.

Understanding Disease Disparities

“There are likely a number of factors that are associated with the increased burden of uterine cancer in Black women,” said lead study author Jason D. Wright, MD, the Sol Goldman Professor of Gynecologic Oncology at Columbia University Vegelos College of Physicians and Surgeons. “They more commonly have aggressive types of uterine cancer, face delayed diagnosis resulting in later-stage disease at diagnosis, and there are often delays in their treatment.”

Reducing Burden of Disease

In addition to building this state-transition microsimulation model of uterine cancer, Dr. Wright and his colleagues also performed a stress test of the model by incorporating hypothetical screening and intervention methods that could detect uterine cancer and precancerous changes prior to a clinical diagnosis. They found that the screening and intervention methods were most effective when introduced at age 55, with declines in cancer incidence that lasted up to 15 years in White women and up to 16 years in Black women.

“The stress testing suggests that if there was an effective screening test, we may be able to substantially reduce the burden of disease. While there is presently no screening or prevention that is routinely used for uterine cancer, we are currently examining the potential impact of integrating screening for this cancer into practice,” said Dr. Wright.

Disclosure: Funding for this study was provided by the National Cancer Institute. For full disclosures of the study authors, visit aacrjournals.org/cebp.

Let’s be honest—deciding to raise your child vegan can feel like a deeply meaningful and intentional choice. You’ve done the research. You’ve had the debates (some louder than others). You’ve stocked your pantry with lentils, B12 supplements, and maybe a few “cheese” options that taste more like regret than dairy replacement.

But here’s what most people don’t tell you.

Raising vegan kids isn’t just about nutrition or ethics—it’s also about navigating tricky social dynamics, your own doubts, and other people’s projections. A lot of projections.

So if you’re considering this path—or already deep into it—here are seven things I wish someone had warned me about from the start.

1. You’ll second-guess yourself more than you expected

Even if you’re confident in your decision, there will be moments that shake you.

A birthday party where your kid stares longingly at a cupcake. A pediatrician visit that ends in side-eyes. A relative who says, “But don’t children need meat to grow?”

And suddenly, you find yourself lying awake at 2 a.m. Googling “Do vegan kids get enough protein?” even though you’ve read 12 articles confirming they do.

This doesn’t mean you’re doing anything wrong. It means you’re a thoughtful parent. But the self-doubt can be exhausting.

Here’s what helped me: grounding in facts (like the American Dietetic Association’s position that well-planned vegan diets are appropriate for all life stages), connecting with other plant-based families, and reminding myself that every parent questions themselves—whether their kid eats chicken nuggets or chickpea nuggets.

2. Other parents might treat you like you’re judging them

I can’t count how many times I’ve said, “We’re raising them vegan, but we really don’t expect other people to do the same,” only to be met with defensiveness.

You’d be amazed at how quickly “Oh, we don’t eat animal products” turns into “So you think I’m a bad mom?”

This is the psychological phenomenon of moral discomfort at work. As noted by Dr. Melanie Joy, author of Why We Love Dogs, Eat Pigs, and Wear Cows, “When people perceive a challenge to their beliefs, even if indirect, they often experience defensiveness—even if no one’s actually judging them.”

I’ve learned to lead with curiosity, not conviction. If someone asks why our family is vegan, I’ll share—but I don’t try to convert. That helps defuse tension and keeps the focus where it should be: on the kids’ well-being.

3. School lunchrooms can be emotional minefields

Let’s talk about the moment your kid opens their lunchbox at school and hears, “Ew, what’s that?”

It’s not just about being different—it’s about being visibly different during one of the most socially sensitive parts of the day. And kids can be brutally honest.

My son once came home asking if I could pack him something “normal,” like Lunchables. Not because he wanted meat—but because he didn’t want to be the odd one out.

This is where resilience-building comes in.

We started role-playing responses. Practicing how to explain his food choices without sounding defensive. Making lunches that look fun and familiar (thank you, cookie cutter sandwiches and cute fruit skewers).

Helping your child feel proud of who they are—and what they eat—is part of the job description.

4. You’ll get surprisingly emotional about “firsts”

First steps. First words. First ice cream cone.

But when you’re raising a vegan kid, these moments take on extra layers.

I cried the first time we found a fully vegan cupcake at a bakery. Not because it tasted amazing (it did), but because I didn’t have to say “no.” For once, my kid could just be a kid.

You’ll also feel an odd sense of grief when they miss out on certain traditions—like roasting marshmallows at camp or decorating eggs at Easter. It’s not about the food. It’s about the memories.

But here’s the upside: you’ll get creative. We toast vegan marshmallows over tealight candles. We dye wooden eggs. You find ways to make new traditions that feel just as magical.

5. Doctors and dietitians are hit or miss

Some will cheer you on. Others will raise an eyebrow and ask if your child is iron-deficient—even if their labs are fine.

I once had a pediatrician suggest “just adding a little fish” to my daughter’s diet because “kids need DHA.” Never mind that she was already getting DHA from algal oil supplements.

This is where it pays to be politely assertive. Bring data. Ask questions. Be open, but also trust yourself.

As registered dietitian Reed Mangels has said, “A vegan diet can meet nutrient needs during pregnancy, infancy, and childhood when properly planned.”

If a healthcare provider doesn’t support that—or makes you feel shamed for your choices—it’s okay to find a new one. Seriously.

6. Your kid will ask questions you’re not always ready for

“Why don’t we eat what my friends eat?”
“Does the cow get sad?”
“Will Grandpa stop eating animals someday, too?”

Whew.

These are not yes-or-no questions. They’re big, philosophical inquiries wrapped in little voices. And they deserve thoughtful answers.

But they also hit you when you least expect them—like in the car line at school or while brushing teeth.

I’ve learned not to overcomplicate it. I keep explanations honest, age-appropriate, and rooted in our family values.

And when I don’t know how to answer, I say so. Then we figure it out together.

7. It’s not just about food—it’s about identity

One of the most unexpected things I’ve realized is how deeply food ties into a child’s sense of self.

When your child says, “I’m vegan,” they’re not just describing a dietary choice—they’re claiming a value system. One that might make them feel different from their peers.

And that’s both beautiful and complicated.

I’ve seen my daughter explain to her classmates that we don’t go to the zoo because we care about animals’ freedom. I’ve watched her ask if her soccer shoes are made from leather. She’s 8.

That kind of awareness can be powerful—but it can also feel heavy.

So we make space to talk about it. To explore what it means to live with integrity and openness. To stand up for your beliefs without putting others down.

That’s the long game, isn’t it? Not just raising vegan kids—but raising thoughtful, kind, critically-thinking humans.

Final thoughts

No one has all the answers. There will be slip-ups. Questions you didn’t prepare for. Snacks eaten at a friend’s house you didn’t approve of.

And that’s okay.

Raising vegan kids isn’t about perfection—it’s about intention. It’s about showing up, staying curious, and leading with values that matter to you.

If you’re navigating this path too, just know: you’re not alone. And you’re doing better than you think.

Turkey said on Wednesday it will shut down all livestock marketplaces to control the spread of highly contagious foot and mouth disease, reported Reuters. 

The agriculture ministry said it detected a new serotype of the disease that heightened the outbreak, due to animal movement after the Muslim religious holiday of Eid al Adha, which is typically marked by slaughtering livestock.

The decision was taken to prevent further spread as teams continue to vaccinate animals against the disease, the ministry said. It will gradually lift the restrictions once the entirelivestock population is vaccinated.

The ministry also said the temporary closure will not disrupt supply and demand for meat and dairy products in Turkey.

Introduction

Sarcopenia is a progressive disorder characterized by the loss of muscle mass and strength. And it is particularly prevalent among older adults, it might affect up to half of people aged 80 years and older, posing a significant public health challenge. In older adults with type 2 diabetes mellitus (T2DM), the prevalence of sarcopenia is 2–3 times higher than in non-diabetic peers.¹ This dual burden not only impairs physical performance and quality of life but also increases the risk of falls, frailty, and mortality.² In recent years, growing concerns have arisen regarding the potential impact of glucose-lowering medications on muscle health, generating significant clinical debate. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) are commonly used hypoglycemic agents. They work through several mechanisms, including increasing glucose-dependent insulin secretion, inhibiting glucagon secretion during hyperglycemia, delaying gastric emptying, and reducing caloric intake. Semaglutide, a long-acting GLP-1RA, can be administered subcutaneously once weekly. It effectively lowers glucose levels and promotes significant weight loss, making it widely adopted for the treatment of diabetes and obesity.^3,4 Additionally, it has shown therapeutic effects on sarcopenic obesity.⁵ However, concerns have been raised about the potential for muscle loss due to long-term Semaglutide use. Some studies indicate that elevated GLP-1 levels may have a detrimental effect on muscle mass.⁶ Given that elderly patients are at a higher risk for sarcopenia, it is essential to further investigate how Semaglutide treatment affects skeletal muscle in this population. In this study, we examined changes in muscle mass and strength among elderly type 2 diabetes patients using Semaglutide, aiming to provide evidence-based guidance for its clinical application.

Methods

Study Design and Participants

This retrospective cohort study investigated older patients (≥65 years) with T2DM who initiated Semaglutide therapy at our hospital between January 2022 and December 2022. Propensity score matching (1:1 ratio) was performed based on age, sex, baseline BMI, diabetes duration, and comorbidities. The resulting control group had comparable baseline characteristics but was not exposed to GLP-1RAs or DPP-4 inhibitors. All participants were monitored for 24 months, with data collected at baseline (0 months), 6 months, 12 months, 18 months, and 24 months. Inclusion criteria were as follows: Age ≥65 years with T2DM (according to ADA guidelines), Body mass index (BMI) ≥24kg/m², with no prior use of GLP-1RA or DPP-4 inhibitors. The study had certain criteria that excluded individuals who had severe liver or renal impairment (defined as serum alanine transaminase (ALT) ≥ 3-fold the upper limit of normal; estimated glomerular filtration rate (eGFR)<15mL/ min/1.73 m²) and cancer. Study subjects meeting the eligibility criteria were included after comprehensive validation of data completeness via the electronic health records system, with exclusion of any cases lacking essential variables. All participants received individualized glucose-lowering regimens supervised by endocrinology specialists. Semaglutide dosage was adjusted based on both glycemic monitoring and hemoglobin A1c levels. This study was approved by the Ethics Committee of Shijiazhuang People’s Hospital (Approval No: 2025075) and conducted by the Declaration of Helsinki. All participants provided written informed consent prior to data collection. Patient confidentiality was protected by anonymizing all personal identifiers in the dataset. The reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Data Collection

Demographic and clinical parameters were systematically extracted from electronic medical records. This data included age, sex, BMI, muscle parameters, duration of diabetes, and comorbidities. The chronic diseases considered included cerebrovascular disease, coronary heart disease, kidney disease, hypertension, and chronic obstructive pulmonary disease (COPD). Due to the retrospective study design, standardized assessments of lifestyle factors (dietary intake and physical activity) were unavailable in the source dataset.

Muscle parameters were assessed through measurements of muscle mass and function. Skeletal muscle mass was estimated using bioelectrical impedance analysis (BCA-1C, Tongfang Health Technology, Beijing). Upper extremity muscle strength was evaluated through handgrip strength measurements, taken with an electronic hand dynamometer (CAMRY EH101, Guangdong). Lower limb muscle strength was evaluated using a 4-meter gait speed test, calculated as gait speed (m/s) = 4 (m) ÷ time (s).

The appendicular skeletal muscle mass index (ASMI) was calculated by dividing the appendicular lean mass of the arms and legs by the square of height (kg/m²). Sarcopenia diagnosis followed 2019 Asian Working Group for Sarcopenia (AWGS) criteria,⁷ requiring both low muscle mass (ASMI <7.0 kg/m² males, <5.7 kg/m² females) and reduced muscle strength (handgrip strength <28 kg males, <18 kg females).

Statistical Analysis

Data were statistically analyzed using IBM SPSS 27.0 and GraphPad 9.0. Continuous variables with normal distribution were expressed as mean ± standard deviation (Mean ± SD). Between-group comparisons used independent samples t-tests, while intra-group longitudinal changes were analyzed with paired t-tests. Categorical variables were compared via chi-square tests. Multivariable linear regression models were constructed to identify clinical predictors of accelerated muscle loss during Semaglutide treatment, adjusting for potential confounders. A two-tailed p-value <0.05 defined statistical significance.

Results

The analysis included 220 Semaglutide-treated patients and 212 matched controls. The baseline information of the Semaglutide treatment group is shown in Table 1. Sarcopenia prevalence was 27.73% in the study population. No significant differences were observed in baseline characteristics between the two groups. However, at the 24-month follow-up, the Semaglutide-treated group exhibited significantly lower values for BMI, ASMI, handgrip strength, and gait speed compared to the control group (p< 0.05). Detailed results are presented in Table 2.

Table 1 Baseline Characteristics of Semaglutide-Treated Patients

Table 2 Comparison of Anthropometric and Muscle Parameters Between Semaglutide-Treated and Control Patients

Longitudinal Changes in Anthropometric and Muscle Parameters

Weight and Muscle Mass Dynamics

All subjects treated with Semaglutide showed a continuous reduction in BMI throughout the study period (p<0.001). A non-significant downward trend in ASMI emerged at 6 months, with significant reductions observed from month 12 onward. Cumulative ASMI loss reached 0.39 kg/m² in females and 0.26 kg/m² in males by study end. While the control group also showed sustained ASMI decline, the magnitude was markedly smaller than in the treatment group (Figure 1).

Figure 1 Longitudinal changes in BMI and muscle parameters during the study period. (a) BMI trajectories. (b) AMSI changes. (c) Handgrip strength variations. (d) Gait speed dynamics. Compare of Semaglutide group: male #<0.05, ##<0.01, ###<0.001; female #<0.05, ##<0.01, ###<0.001. Compare of control group: male *<0.05, **<0.01, ***<0.001; female *<0.05, **<0.01, ***<0.001.

Muscle Strength Trajectories

Handgrip strength: Males displayed a transient improvement at 6 months, followed by a progressive decline. Female participants, while showing no statistically significant change at 6 months, exhibited an upward trend that was subsequently followed by significant deterioration. Gait speed: Both genders exhibited similar patterns, with non-significant declines in intermediate phases but statistically significant overall reductions. Refer to Figure 2 for more information. Semaglutide-treated patients showed significantly greater reductions in ASMI, handgrip strength and gait speed compared to controls (see Table 2).

Figure 2 Multivariable regression analysis of predictors for muscle mass loss following semaglutide treatment. Semaglutide dosage, ASMI, and Gait speed were significant influences. Muscle mass loss (kg/m2) =1.536 + 0.096 × Semaglutide dosage ‒ 0.076 × ASMI + 0.004 × Hand grip strength ‒ 0.892 × Gait speed (R2=0.337).

Influential Factors of Semaglutide-Associated Muscle Loss

To identify determinants of muscle loss, we performed correlation analysis followed by multiple linear regression. The initial correlation analysis revealed that gender, age, baseline body mass index, diabetes duration, and chronic comorbidities showed no significant association with muscle mass loss. However, significant correlations were found with Semaglutide dosage, baseline ASMI, handgrip strength, and gait speed. As shown in Table 3.

Table 3 Correlation Analysis of the Variables with Muscle Loss

Subsequent multiple linear regression analysis, using muscle mass loss as the dependent variable and Semaglutide dosage, baseline ASMI, handgrip strength, and gait speed as independent variables, confirmed independent associations for semaglutide dosage, baseline ASMI, and gait speed, whereas handgrip strength lost statistical significance. The regression model (R² = 0.337) predicted muscle mass loss as: Muscle mass loss (kg/m²) =1.536+0.096×Semaglutide dosage-0.076× ASMI+0.004×Hand grip strength-0.892×Gait speed, R²=0.337. As displayed in Figure 2.

Discussion

Sarcopenia is an age-related condition characterized by the progressive loss of skeletal muscle mass and strength. It typically begins after the age of 30, at a rate of 0.1% to 0.5% annually, and accelerates beyond the age of 65 due to physiological and metabolic changes in aging populations.⁸ In this study, we investigated the effects of Semaglutide on muscle health in elderly patients with T2DM. Our analysis reveals that while Semaglutide effectively reduces body weight in elderly T2DM patients, it paradoxically accelerates this physiological muscle decline, particularly at higher doses and in individuals with pre-existing low muscle mass and function.

The weight-loss effects of Semaglutide, a long-acting GLP-1RA, are well-established,⁹ and this was confirmed in our elderly cohort. This weight loss may be linked to its ability to suppress appetite, delay gastric emptying, and regulate satiety signaling in the central nervous system.¹⁰ In older patients with T2DM, weight loss not only improves glycemic control but also reduces the risk of cardiovascular disease,¹¹ which is especially important in this population. However, despite the metabolic benefits of weight loss, it is crucial to consider the components of that weight loss. Our study found that weight loss was accompanied by a reduction in muscle mass and a decline in muscle function, which could negatively affect the long-term health of elderly patients. This finding contrasts with results from previous studies,¹² possibly because our follow-up population consisted entirely of elderly individuals. Skeletal muscle is the largest organ system in adults, accounting for approximately 30–45% of body weight in young adults, and it plays a vital role in protein homeostasis, as it contains the largest amount of body protein. Maintaining protein homeostasis, or net protein balance, is essential for muscle health. Under certain conditions, such as prolonged fasting, starvation, or inadequate protein intake, skeletal muscle can break down its proteins to mobilize amino acids.¹³ Semaglutide reduces body weight by suppressing appetite and decreasing energy intake; this diminished protein intake may lead to the body breaking down muscle proteins to provide necessary amino acids.¹⁰ Thus, using Semaglutide in older patients with T2DM may exacerbate the development of sarcopenia due to negative energy balance. Moreover, high doses of Semaglutide may more robustly suppress appetite and energy intake,¹⁴ leading to exacerbated muscle mass loss. The precise molecular mechanisms underlying this phenomenon require further investigation. These findings prompt critical inquiry into whether targeted protein supplementation may attenuate these effects in older populations – a promising avenue for future investigation.

Interestingly, we observed that Semaglutide initially improved muscle function, although in female participants this improvement only manifested as an upward trend. This effect may be mediated through the reduction of intramuscular fat infiltration, which is characteristically elevated in obese individuals. The accumulation of lipids and their metabolic byproducts within and between muscle cells can lead to mitochondrial dysfunction and subsequent declines in muscle strength and function.¹⁵ Previous studies have confirmed that GLP-1RA treatment significantly reduces this pathological fat infiltration.¹⁶ However, our data demonstrate that long-term administration results in gradual muscle mass loss, ultimately attenuating the initial functional improvements.

Our regression analysis identified baseline ASMI and gait speed as independent predictors of muscle loss, without significant gender or age differences. This suggests that reduced physical activity, resulting from declining muscle function, may create a vicious cycle of further muscle deterioration.¹⁷ Current research has shown that physical activity, particularly resistance training, has therapeutic effects on sarcopenia.¹⁸ Whether muscle loss can be prevented in Semaglutide users by increasing exercise participation needs further investigation.

The findings of this study have significant implications for clinical practice. While Semaglutide has notable benefits in improving glycemic control and promoting weight loss, its adverse effects on muscle mass should not be overlooked, especially in elderly patients. Clinicians should consider the following points when prescribing Semaglutide: (1) Patient selection: Carefully evaluate the risks and benefits of Semaglutide in elderly patients or those with pre-existing sarcopenia. (2) Dose adjustment: Start elderly patients on a low dose and gradually adjust according to their tolerance and response, avoiding high doses. (3) Monitoring and intervention: Regularly monitor muscle mass, physical function, and quality of life during Semaglutide treatment. This could be combined with moderate resistance training and optimized protein intake,¹⁹ if needed, to help slow muscle loss.

This study has several limitations. The relatively small sample size may limit the generalizability of the findings. While we accounted for major known confounders, we were unable to assess nutritional intake and physical activity patterns, which could influence muscle outcomes. Additionally, the observational nature of the study prevents causal conclusions. These limitations highlight the need for future prospective studies with standardized assessments of diet and exercise.

Conclusion

The use of Semaglutide is associated with muscle loss and functional decline in older adults with type 2 diabetes, particularly at higher doses. This effect is especially significant in patients with sarcopenia. Consequently, it is crucial to assess the risks and benefits for each elderly patient individually and to implement appropriate monitoring and interventions. The potential for nutritional supplementation and targeted exercise regimens to counteract semaglutide-associated muscle decline merits systematic investigation.

Data Sharing Statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Ethics Approval and Consent to Participate

The study was approved by the Ethics Committee of Shijiazhuang People’s Hospital (Approval No: 2025075). All methods were performed by the Declaration of Helsinki, and the reporting followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.

Acknowledgments

We are grateful to all the patients who accepted to participate in this study.

Funding

There is no funding to report.

Disclosure

The authors declare that they have no competing interests in this work.

References

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2. Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet. 2019;393(10191):2636–2646. doi:10.1016/S0140-6736(19)31138-9

3. Yao H, Zhang A, Li D, et al. Comparative effectiveness of GLP-1 receptor agonists on glycaemic control, body weight, and lipid profile for type 2 diabetes: systematic review and network meta-analysis. BMJ. 2024;384:e076410. doi:10.1136/bmj-2023-076410

4. Chao AM, Tronieri JS, Amaro A, Wadden TA. Semaglutide for the treatment of obesity. Trends Cardiovasc Med. 2023;33(3):159–166. doi:10.1016/j.tcm.2021.12.008

5. Ren Q, Chen S, Chen X, et al. An effective glucagon-like peptide-1 receptor agonists, semaglutide, improves sarcopenic obesity in obese mice by modulating skeletal muscle metabolism. Drug Des Devel Ther. 2022;16:3723–3735. doi:10.2147/DDDT.S381546

6. Huang HH, Wang YJ, Jiang HY, et al. Sarcopenia-related changes in serum GLP-1 level affect myogenic differentiation. J Cachexia Sarcopenia Muscle. 2024;15(5):1708–1721. doi:10.1002/jcsm.13524

7. Chen LK, Woo J, Assantachai P, et al. Asian working group for sarcopenia: 2019 consensus update on sarcopenia diagnosis and treatment. J Am Med Dir Assoc. 2020;21(3):300–307.e2. doi:10.1016/j.jamda.2019.12.012

8. Fry CS, Rasmussen BB. Skeletal muscle protein balance and metabolism in the elderly. Curr Aging Sci. 2011;4(3):260–268. doi:10.2174/1874609811104030260

9. Wilding J, Batterham RL, Calanna S, et al. Once-weekly semaglutide in adults with overweight or obesity. N Engl J Med. 2021;384(11):989–1002. doi:10.1056/NEJMoa2032183

10. Drucker DJ. Mechanisms of action and therapeutic application of glucagon-like peptide-1. Cell Metab. 2018;27(4):740–756. doi:10.1016/j.cmet.2018.03.001

11. Marso SP, Bain SC, Consoli A, et al. Semaglutide and cardiovascular outcomes in patients with type 2 diabetes. N Engl J Med. 2016;375(19):1834–1844. doi:10.1056/NEJMoa1607141

12. Xiang J, Ding XY, Zhang W, et al. Clinical effectiveness of semaglutide on weight loss, body composition, and muscle strength in Chinese adults. Eur Rev Med Pharmacol Sci. 2023;27(20):9908–9915. doi:10.26355/eurrev_202310_34169

13. Thalacker-Mercer A, Riddle E, Barre L. Protein and amino acids for skeletal muscle health in aging. Adv Food Nutr Res. 2020;91:29–64.

14. Smits MM, Van Raalte DH. Safety of semaglutide. Front Endocrinol. 2021;12:645563. doi:10.3389/fendo.2021.645563

15. Li CW, Yu K, Shyh-Chang N, et al. Pathogenesis of sarcopenia and the relationship with fat mass: descriptive review. J Cachexia Sarcopenia Muscle. 2022;13(2):781–794. doi:10.1002/jcsm.12901

16. Pandey A, Patel KV, Segar MW, et al. Effect of liraglutide on thigh muscle fat and muscle composition in adults with overweight or obesity: results from a randomized clinical trial. J Cachexia Sarcopenia Muscle. 2024;15(3):1072–1083. doi:10.1002/jcsm.13445

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Introduction

Somatic symptom disorder (SSD) refers to a psychiatric condition marked by an intense preoccupation with bodily symptoms.¹ These symptoms cause significant distress or disruption to daily life, evident through exaggerated and maladaptive cognitive, emotional, and behavioral reactions. For instance, an individual with SSD might exhibit chronic pain, gastrointestinal disturbances, or fatigue, alongside anxiety, catastrophizing thoughts, and avoidance behaviors.² Estimates of the prevalence of SSD in the general population range from 6.7% to 17.4%, with an average frequency of 12.9%.¹ Despite SSD’s elevated prevalence and strong association with detrimental functional consequences, such as diminished quality of life and increased healthcare utilization, research on interventions for its treatment and management remains sparse.³ As a result, healthcare providers continue to face challenges in providing adequate treatment for SSD.

Pharmacotherapy is one of the important approaches in the treatment of SSD. Pharmacological treatment for SSD includes non-psychotropic medications (such as β-blockers, non-steroidal anti-inflammatory drugs, and muscle relaxants for alleviating somatic symptoms), psychotropic medications, and herbal remedies (such as St. John’s wort). Psychotropic medications have been proven effective in treating some somatic symptoms, including selective serotonin reuptake inhibitors (SSRI) (eg, escitalopram, fluoxetine), serotonin and norepinephrine reuptake inhibitors (SNRI) (eg, venlafaxine), atypical antidepressants (eg, mirtazapine), and tricyclic antidepressants (eg, amitriptyline).⁴ However, a significant number of individuals suffering from SSD do not attain a treatment response, which is characterized by a reduction in severity exceeding 50%, following treatment with antidepressant monotherapy administered at adequate doses and for an adequate duration.⁵ Additionally, antidepressants mainly improve mood and relieve somatic symptoms by regulating neurotransmitters such as 5-hydroxytryptamine (5-HT) and norepinephrine.^5,6 However, patients with SSD may have more extensive neurotransmitter imbalances, including the dopamine (DA) system.⁷ Antipsychotic medications can regulate DA.⁸ Typical antipsychotic medications include chlorpromazine, trifluoperazine, and pimozide. These drugs, among the earliest developed in the field of antipsychotic medications, primarily exert their effects by targeting DA D2 receptors but may also interact with other receptors.⁹ In the 1990s, new antipsychotic medications are developed, known as second-generation or “atypical” antipsychotic medications, such as quetiapine, aripiprazole, and risperidone.¹⁰ Risperidone, classified as an atypical antipsychotic, exhibits robust antagonistic effects on DA D2, 5-HT2A, 5-HT2C, 5-HT1D, α1-, and α2-adrenergic receptors. It serves as an effective augmenting therapy for SSRI-resistant major depressive disorder. Furthermore, risperidone has the capability to counteract the SSRI-induced suppression of norepinephrine activity through its 5-HT2A antagonism.⁵ Paliperidone, which is the principal metabolite of risperidone, has demonstrated notable therapeutic benefits when used as an adjunctive treatment alongside citalopram in patients diagnosed with somatoform disorder.⁵ Compared with other second-generation antipsychotic medications, risperidone has relatively fewer adverse reactions.⁵ However, currently, antipsychotic medications are usually not used as monotherapy for SSD but are part of combination therapy, combined with other treatment methods to improve therapeutic efficacy.⁵

In recent years, the combined application of neuromodulation techniques and pharmacotherapy has provided new ideas for the treatment of SSD.¹¹ Repetitive transcranial magnetic stimulation (rTMS), a form of noninvasive brain stimulation, has the capability to modulate the neural excitability of specific brain regions, which has been applied in the treatment of various neurological and psychiatric disorders.¹² It has few side effects and is considered a promising intervention for improving symptoms in patients with SSD.¹³ rTMS has good efficacy in modulating targeted neural activity and further alleviating symptoms, so an increasing number of studies are focusing on examining the effects of rTMS on negative symptoms and cognitive deficits in patients with SSD.¹³ Xue Li et al report that rTMS combined with family intervention and risperidone has a synergistic effect in the treatment of schizophrenia, especially in improving positive symptoms, negative symptoms, and cognitive function.¹⁴ Additionally, data from Rui Li et al show that rTMS combined with risperidone treatment may affect the brain-gut-microbiota axis by regulating the gut microbiota in patients with chronic schizophrenia, thereby participating in the therapeutic effect.¹¹ Given this, this study aimed to explore the application effect of rTMS combined with low-dose antipsychotic medication (risperidone) in SSD.

It is worth noting that patients with SSD often have comorbid symptoms such as anxiety and depression and may have central nervous system dysfunction.^2,15 Neurotransmitter imbalance may be one of the mechanisms leading to symptoms and requires further study. It is well known that DA receptors are widely expressed in the body and function in both peripheral and central nervous systems.¹⁶ Their dysfunction is associated with anxiety and obsessive-compulsive symptoms.¹⁷ Furthermore, high levels of γ-aminobutyric acid (GABA) in the medial prefrontal cortex play an important pathophysiological role in the generation of somatic symptom disorders.¹⁸ Meanwhile, 5-HT abnormalities are also considered a key biological cause of somatic symptoms.⁵ On the other hand, data from Bumhee et al showed that patients with SSD have higher levels of interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α) compared with healthy controls, and hypersensitive C-reactive protein (hs-CRP) and IL-6 have a complete mediating inhibitory effect on the relationship between the functional connectivity strength of the default mode network and depression levels.¹⁹ Against this background, we included studies on neurotransmitters and inflammatory markers to comprehensively evaluate the biological effects of rTMS combined with risperidone on SSD. By analyzing changes in neurotransmitters such as DA, GABA, 5-HT, and inflammatory markers, we can reveal the potential mechanisms of combination therapy and provide a scientific basis for the treatment of SSD.

Materials and Methods

Ethics Statement

All experimental procedures were approved by the Medical Ethics Committee of The First Affiliated Hospital of Harbin Medical University, and patients or their families provided informed consent and signed an informed consent form. This study adhered to the Declaration of Helsinki.

Subjects and Grouping

Ninety patients with SSD admitted to The First Affiliated Hospital of Harbin Medical University from May 2023 to May 2024 were selected as the study subjects. Inclusion criteria: Patients who met the diagnostic criteria for SSD in the International Classification of Diseases, 10th Edition²⁰ and the Chinese Classification and Diagnostic Criteria for Mental Disorders, 3rd Edition, and had a Patient Health Questionnaire-15 score ≥ 5; patients aged 18–75 years; patients who had not received antipsychotic medication or rTMS within the past 6 months; patients on the 17-Item Hamilton Rating Scale for Depression (HAMD)²¹ score ≥ 17 points before treatment. Exclusion criteria: Patients with severe physical diseases (including stroke, malignant tumors, chronic obstructive pulmonary disease, end-stage renal disease, liver cirrhosis, myocardial infarction, etc) or brain organic diseases; patients with a history of schizophrenia, mania, and depression associated with various types of organic lesions; patients with epilepsy, acute-phase cerebrovascular accidents, intracranial infections, and intracranial presence of metal or other foreign bodies; patients with suicidal behavior or suicidal ideation; patients with allergies or sensitivities to all the medications used in the study; and women who were pregnant or breastfeeding.

Depending on the treatment regimen, the enrolled patients were divided into the medication and combination groups, with 45 cases each. The medication group was treated with low-dose antipsychotic medication, while the combination group received low-dose antipsychotic medication combined with rTMS.

Treatments

Patients in the medication group were treated with low-dose antipsychotic medication, specifically risperidone (Janssen Pharmaceutical Co., Ltd., Xi ‘an, China; State Drug Administration H20010309), administered orally at an initial dose of 0.5 mg twice daily, with the dose adjustable to 1.5 mg within one week, for a treatment cycle of 8 weeks. The combination group received low-dose antipsychotic medication combined with rTMS. Specific methods: The antipsychotic medication regimen was identical to that of the medication group. YRDCCY-1 transcranial magnetic stimulator (Yi Ruide Medical Equipment New Technology Co., Ltd., Wuhan, China) was used for the treatment, with an output pulse frequency range of 0–100 Hz and a peak stimulation intensity range of 1.5–6 Tesla. Specific operations: The patient was laid on the magnetic therapy bed, relaxed systemically, with the “8”-shaped coil placed on the right dorsolateral prefrontal cortex. The treatment was stimulated with an intensity of 1Hz frequency and 80% motor threshold, delivering 800 pulses per session, lasting 20 minutes per session, once daily for 5 consecutive days, followed by a 2-day break. This cycle was continued for 8 weeks.

Observation Parameters

General data: General demographic information such as gender, age, years of education, ethnicity, marital occupation, and place of residence of the study subjects were collected through a retrospective case system.

Anxiety and depression: The Hamilton Anxiety Rating Scale (HAMA)²² was used to assess patients’ psychological states. The scale includes 14 items, such as anxious mood, fear, and cognitive function, scored on a 0–4 scale (0 = none, 1 = mild, 2 = moderate, 3 = severe, 4 = very severe), with a maximum score of 56. The HAMD-17 scale was used to assess the depressive symptoms in both groups of patients. This scale consists of 17 items covering aspects such as depressed mood, guilt, and suicidal thoughts, and is divided into five factors: anxiety somatization, weight, cognitive disturbance, retardation, and sleep disturbances. Each question has a different scoring standard, and the corresponding score is selected based on the patient’s response. The total score is then calculated.

Clinical efficacy: HAMD-17 was utilized to evaluate the treatment response. A reduction rate of ≥ 75% before and after treatment was considered clinical remission, 25–74% was considered effective, and < 25% was considered ineffective. The total effective rate was calculated as [(number of clinical remissions + effective cases) / total number of cases × 100%]. The reduction rate was calculated as [(pre-treatment HAMD-17 score – post-treatment HAMD-17 score) / pre-treatment HAMD-17 score × 100%].

Quality of life: The Medical Outcomes Study 36-Item Short Form Health Survey (SF-36) (SF-36)²³ was used for assessment. The survey included four functional domains: physical, social, psychological, and daily living. Each domain is scored out of 100, with higher scores indicating better quality of life for the patient.

Adverse reactions: The occurrence of adverse reactions including fatigue, drowsiness, anorexia, nausea, xerostomia, and dizziness, were compared.

Neurotransmitters levels: Before treatment (admission day 2) and after treatment (8 weeks of treatment), 5 mL of cubital vein blood was collected with an EDTA blood collection tube. Blood samples should be processed within 2 hours; otherwise, they must be stored at −80°C, with strict avoidance of multiple freeze–thaw cycles. The levels of GABA, 5-HT, and DA were measured using the enzyme-linked immunosorbent assay (ELISA).²⁴ ELISA kits for GABA (CB10292-Hu), 5-HT (CB10030-Hu), and DA (CB10524-Hu) were purchased from Coibo Biotechnology (Shanghai, China).

Inflammatory factor levels: Levels of CRP, IL-1β, and IL-10 were measured using ELISA. ELISA kits for CRP (CB10116-Hu), IL-1β (CB10347-Hu), and IL-10 (CB13566-Hu) were available from Coibo.

Statistical Processing

Data were processed using SPSS 26.0 software. The normality of measurement data was tested using the Shapiro–Wilk method, and all data conformed to a normal distribution. Additionally, the measurement data were expressed as mean ± standard deviation (Mean ± SD). Comparisons between groups used independent sample t-tests, and within-group comparisons used paired sample t-tests. Numeration data were expressed as [number of cases (n)], and analyzed using chi-square tests, with Yates’ correction applied to small sample sizes. A P-value < 0.05 was considered statistically significant.

Results

General Data

Baseline data differences between the two groups were analyzed, revealing no statistically significant differences in age, gender, disease duration, marital status, ethnicity, residence, or education level (P > 0.05), indicating comparability (Table 1).

Table 1 Comparison of General Data in the Two Groups

HAMA and HAMD Scores

There was no notable difference in HAMA and HAMD scores between the two groups before treatment (P > 0.05). After treatment, HAMA and HAMD scores in both groups decreased compared to pre-treatment levels (P < 0.05). Post-treatment improvements in HAMA and HAMD scores were better in the combination group than in the medication group (Table 2).

Table 2 Comparison of HAMA and HAMD Scores Before and After Treatment in the Two Groups

SF-36 Scores

There was no significant difference in SF-36 scores between the two groups before treatment (P > 0.05). After treatment, SF-36 dimension scores in both groups increased (P < 0.05), with the combination group’s scores higher than the control group’s (P < 0.05) (Table 3).

Table 3 Comparison of SF-36 Scores Before and After Treatment Between the Two Groups

Clinical Efficacy

The total effective rate in the medication group was 84.44% (38/45), while the total effective rate in the combination group was 97.78% (44/45). According to the chi-square test, the total effective rate in the combination group was higher than that in the medication group (P = 0.026) (Table 4).

Table 4 Comparison of Clinical Efficacy Between the Two Groups

Occurrence of Adverse Reactions

The medication group and the combination group showed no significant difference in the incidence of adverse reactions such as fatigue, drowsiness, anorexia, xerostomia, nausea, and dizziness (all P > 0.05) (Table 5).

Table 5 Comparison of the Incidence of Adverse Reactions Between the Two Groups

Neurotransmitters Levels

There was no significant difference in GABA, 5-HT, and DA levels between the two groups before treatment (P > 0.05). After treatment, GABA and 5-HT levels in both groups increased compared to pre-treatment levels, while DA levels decreased, with the combination group’s levels higher/lower than the medication group’s (Table 6).

Table 6 Comparison of Neurotransmitters Levels Between the Two Groups Before and After Treatment

Inflammatory Factor Levels

There was no remarkable difference between the pre-treatment levels of CRP, IL-1β, and IL-10 between the two groups (P > 0.05). After treatment, CRP and IL-1β levels in both groups decreased compared to pre-treatment levels, while IL-10 levels increased, with the combination group’s levels lower/higher than the medication group’s (Table 7).

Table 7 Comparison of Inflammatory Factor Levels Between the Two Groups Before and After Treatment

Discussion

SSD is common in primary health care institutions, and diagnosis and treatment are often challenging.¹ Therefore, this study evaluated the therapeutic effects of rTMS combined with low-dose antipsychotic medication in patients with SSD. The results showed that rTMS combined with low-dose antipsychotic medication has significant advantages in improving anxiety and depression, enhancing quality of life, and regulating neurotransmitter levels, and inflammatory factors in the treatment of SSD.

Specifically, the improvement in HAMA and HAMD scores in the combination group was better than that in the medication group, indicating that rTMS combined with low-dose antipsychotic medication is more effective in improving anxiety and depressive symptoms. Additionally, the SF-36 scores in the combination group were higher than those in the medication group, indicating that combination therapy is more effective in improving quality of life. Meanwhile, the total effective rate in the combination group was higher than that in the medication group, and there was no significant difference in the incidence of adverse reactions between the two groups, revealing that rTMS combined with low-dose antipsychotic medication is superior to monotherapy in overall efficacy and does not increase the risk of adverse reactions. Studies have reported that rTMS leads to a greater reduction in depressive symptoms than medication, which is further reflected in higher rates of response and remission. Additionally, rTMS results in a more substantial decrease in anxiety and anhedonia symptoms compared to switching antidepressants.²⁵ Furthermore, in the study of Ren et al, intermittent theta burst-rTMS (iTBS-rTMS) demonstrates a favorable therapeutic effect in patients with methamphetamine use disorder, with improvements in both depression and impulsivity. These enhancements are strongly associated with the therapeutic efficacy of iTBS-rTMS.²⁶

In addition, this study highlighted that the levels of GABA and 5-HT in the combination group were higher than those in the medication group, and the level of DA was lower than that in the medication group, indicating that rTMS combined with low-dose antipsychotic medication is more effective in regulating neurotransmitter levels. According to previous results, the serum levels of 5-HT in both the acupuncture + rTMS combination group and the rTMS-only group are found to be higher post-treatment compared to their pre-treatment levels.²⁷ In the study by Feng et al, after rTMS treatment, the GABA levels are notably elevated.²⁸ A study reveals that antipsychotic medications such as risperidone may regulate N-methyl-D-aspartate receptors through the glycogen synthase kinase 3β-β-catenin signaling pathway and/or the activation of cyclic adenosine monophosphate response element-binding protein 1, and the regulation of GABAₐR may also be related to these signaling pathways.²⁹ Thomas et al’s study shows that risperidone affects motor activity and neural activity in mice, especially having a significant impact on neural oscillations in the prefrontal cortex and hippocampus, by blocking DA receptor D₂R and regulating the activity of serotonin receptors (5-HT₁AR and 5-HT₂AR).³⁰ Based on the results of this study, there is a synergistic mechanism in neurotransmitter regulation when risperidone is combined with rTMS. Risperidone, as a D2 receptor antagonist, can block excessive DA activity in the mesolimbic system to alleviate positive symptoms,¹⁴ while rTMS activates glutamatergic neurons in the prefrontal cortex through high-frequency stimulation, promoting DA release and enhancing prefrontal-striatal circuit function. The combined treatment may partially counteract the inhibitory effect of risperidone on DA, thereby optimizing DA metabolic balance. Additionally, risperidone indirectly increases synaptic 5-HT levels by blocking 5-HT2A receptors, and rTMS stimulates the dorsolateral prefrontal cortex to increase 5-HT release into the limbic system. The synergy of the two may increase 5-HT concentrations in relevant brain regions, thereby improving anxiety and depressive symptoms. On the other hand, rTMS can enhance GABAergic interneuron activity to inhibit prefrontal cortex hyperactivity, and risperidone can indirectly regulate DA-GABA interactions to enhance GABAergic inhibition. The combined treatment can more effectively reduce prefrontal cortex excitability and reduce anxiety and obsessive-compulsive symptoms.

Meanwhile, this study also observed that the levels of CRP and IL-1β in the combination group were lower than those in the medication group, and the level of IL-10 was higher than that in the medication group, indicating that rTMS combined with low-dose antipsychotic medication is more effective in regulating inflammatory marker levels. In line with the results of the present study, in the study of Yang et al, deep rTMS reduced microglial activation at the lesion sites and normalized cytokine levels (IL-1β, IL-6, and IL-10) in regions affected by cuprizone.³¹ Based on the results of this study, rTMS may activate the vagus nerve-cholinergic anti-inflammatory pathway, inhibit microglial activation, and reduce the release of pro-inflammatory cytokines (such as IL-1β). Although risperidone does not directly have anti-inflammatory effects, it may inhibit microglial M1 polarization by regulating the DA signaling pathway. When combined, the two may synergistically reduce peripheral blood CRP and IL-1β levels and increase the level of the anti-inflammatory cytokine IL-10.

Limitation

This study preliminarily revealed the efficacy of rTMS combined with risperidone in the treatment of SSD in improving anxiety and depression, enhancing quality of life, regulating neurotransmitter levels, and inflammatory factors. However, this study also has some limitations. For example, we did not perform sample size calculation, and the sample size was small, which may affect the generalizability of the findings. Additionally, the 8-week observation period in this study may not be sufficient to assess the long-term efficacy and potential delayed effects of rTMS combined with risperidone treatment. The lack of long-term follow-up may not allow for the assessment of symptom recurrence rates and drug dependence after treatment.

Conclusion

In conclusion, this study confirms that rTMS combined with low-dose antipsychotic medication is superior to monotherapy in improving anxiety and depression, enhancing the quality of life, regulating neurotransmitter levels, and inflammatory factors in the treatment of somatic symptom disorder, with fewer side effects and significant clinical efficacy. This study provides a new direction for the treatment of SSD, and it is hoped that the treatment regimen can be further optimized to benefit more patients in the future. Importantly, future research should further verify the mechanisms and long-term safety of combination therapy by expanding the sample size, extending the follow-up period, and controlling confounding factors (such as treatment adherence, social support systems, etc). Additionally, the treatment of SSD requires multidisciplinary collaboration, including psychiatry, neurology, and psychology. The multidisciplinary collaborative treatment model can integrate the advantageous resources of various disciplines to provide patients with more personalized and comprehensive treatment plans and improve the overall treatment level of SSD.

Ethical Statement

All experimental procedures were approved by the Medical Ethics Committee of The First Affiliated Hospital of Harbin Medical University, and informed consent was signed by patients’ families.

Consent to Participate

Informed consent was obtained from all individual participants included in the study.

Funding

No funds, grants, or other support was received.

Disclosure

The authors declare that they have no conflicts of interest for this work.

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Introduction

The prevalence of diabetes, particularly type 2 diabetes (T2D), is rising globally, posing a significant public health challenge due to its various acute and chronic complications.¹ Among these complications, cardiovascular diseases (CVDs) stand out as the leading cause of death in patients with T2D.² Vascular dysfunctions, including arterial stiffness (AS) and impaired vasodilation, can emerge before the onset of severe CVDs symptoms.³ Therefore, early assessment of AS is particularly important in the management of T2D. The brachial-ankle pulse wave velocity (baPWV) is a simple, effective and non-invasive method for evaluating AS,⁴ and can independently predict cardiovascular risk, providing important evidence for assessing the development of CVDs in individuals.⁵

Insulin resistance (IR) is considered a significant factor to AS and the progression of CVDs.⁶ While the euglycemic hyperinsulinemic clamp (EHC) is considered the gold standard for assessing IR,⁷ its invasive nature, time consuming and requirement for hospitalization limit its practical applicability. The homeostasis model assessment index (HOMA-IR) offers a simpler approach to assessing IR.⁸ However, it presents specific challenges for patients undergoing insulin therapy. Recently, a growing number of non-insulin-based IR surrogate markers have been proposed, including the triglyceride-glucose (TyG) index, triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-c) ratio, and metabolic score for insulin resistance (METS-IR).^9–11 These markers have been associated with various metabolic diseases. One of our previous studies examined their relationship with nonalcoholic fatty liver disease (NAFLD) in patients with T2D, highlighting their clinical relevance in this context.¹² Building on this foundation, our current study shifts the focus toward AS, a distinct yet critical cardiovascular complication in T2D. A more recent development is the natural log transformation of the glucose disposal rate (log_e GDR), a non-insulin-based model to assess insulin sensitivity (IS) in T2D patients.¹³ The log_e GDR is calculated based on body mass index (BMI), triglycerides (TG), the urinary albumin to creatinine ratio (UACR) and γ-glutamyl transferase (GGT), and it has been validated and demonstrated a strong association with CVDs and mortality rates.¹³ Despite these advances, no studies to date have specifically investigated the relationship between the log_e GDR and AS in T2D. Based on the groundwork laid by our earlier research, this study aims to explore the novel association between log_e GDR and AS, offering fresh insights into the complex interplay between IS and vascular health.

The prevalence of non-obese T2D is gradually increasing, particularly in Asian countries.^14,15 Although CVDs and other conditions have traditionally been associated with obesity and being overweight, recent evidence suggests that non-obese T2D patients may have higher all-cause and cardiovascular mortality rates.^16,17 This could be attributed to factors such as increased visceral fat, impaired IS, and heightened inflammatory responses despite a normal BMI.¹⁸ Furthermore, recent studies have reported non-obese T2D patients have a comparable or even higher prevalence of AS compared to their obese counterparts¹⁸ Due to significant differences in metabolic characteristics between obese and non-obese diabetic patients, particularly regarding IS.¹⁹ And research exploring the relationship between IR surrogate markers and AS in non-obese patients with T2D remains limited. Therefore, we aim to analyze the relationship between the log_e GDR and AS in this population.

Methods

Study Design and Population

We retrospectively reviewed the medical records of patients aged ≥ 18 years with T2D from the Department Endocrinology of Linyi People’s Hospital, from January 2020 to March 2023. The exclusion criteria were (1) subjects missing key anthropometric measurements (height and weight); (2) subjects who had severe liver and kidney dysfunctions; (3) subjects with a history of angina, myocardial infarction and cerebrovascular accident; (4) subjects who had not undergone the baPWV tests or whose clinical data were incomplete, including GGT, TG and UACR; (5) subjects with BMI ≥ 24 kg/m². Ultimately, a total of 790 non-obese patients with T2D were eventually included (Figure 1).

Figure 1 The flow chart of study participants selection.

It is important to note that a portion of the participants included in the current study were also part of our previous work, which primarily investigated the association between IR markers and NAFLD in the overall T2D population. In terms of exclusion criteria, the previous study mainly excluded confounding factors that could affect the diagnosis and analysis of fatty liver disease.¹² For the overlapping populations, we further compared differences in baseline characteristics and various IR indices between the two studies, and the results did not show significant differences, suggesting that the results of this study are relatively stable and have some replication.

Demographic Information

The sex, age, diabetes duration and self-reported current cigarette smoking and drinking status were collected.

Physical Examinations

According to unified standards, the height, weight, systolic blood pressure (SBP) and diastolic blood pressure (DBP) were measured and collected. The bioelectrical impedance analysis (Omron DUALSCAN HDS-2000, Kyoto, Japan) was used to measure the visceral fat area (VFA) and subcutaneous fat area (SFA).

Each participant’s baPWV was measured using the automated system BP-203RPE III (Omron Healthcare Co., Japan) by trained technicians. The device simultaneously recorded pulse waveforms from the brachial and tibial arteries and automatically calculated baPWV values. Before measurement, participants were required to rest in a supine position for at least 5 minutes to ensure hemodynamic stability. Subsequently, appropriately sized cuffs were placed on both upper arms and ankles, and the device was operated according to standard protocols to obtain waveform signals and compute baPWV values.²⁰ To enhance measurement accuracy, this study analyzed data in cases where there was a significant difference between left and right baPWV values and assessed each side’s baPWV separately. AS was defined as baPWV ≥1800 cm/s.

Laboratory Measurements

Following an overnight fast, blood samples were collected and analyzed in the morning for alanine aminotransferase (ALT), aspartate aminotransferase (AST), GGT, TG, HDL-c, total cholesterol (TC), low density lipoprotein-cholesterol (LDL-c), serum creatinine (Scr), uric acid (UA), Cystatin C (Cys C), hemoglobin (Hb), fasting blood glucose (FBG) and glycosylated haemoglobin (HbA1c), fasting insulin (FINS) and UACR. A comprehensive overview of the tools and methods utilized in this research is available in our earlier publication.¹² Non-obese was defined as BMI < 24 kg/m².

Parameter Calculation

1. BMI = weight (kg) / height² (m²);
2. eGFR = 175 * Scr (mg/dL) ^−1.234 * age ^−0.179 * (0.79, if female);²¹
3. HOMA-IR = FBG (mmol/L) * FINS (µU/mL)/22.5;⁸
4. TyG index = ln [TG (mg/dL) × FBG (mg/dL)/2];¹⁰
5. TG/HDL-c ratio = TG (mmol/L)/HDL-c (mmol/L);¹¹
6. METS-IR = ln [(2*FBG (mg/dL)) + TG (mg/dL)] *BMI)/(Ln [HDL-c (mg/dL)]);⁹
7. Log_e GDR = 5.3505–0.3697 * log_e (GGT, IU/L) – 0.2591 * log_e (TG, mg/dL) – 0.1169 * log_e (UACR, mg/g) – (0.0279*BMI, kg/m²).¹³

Statistical Analysis

Statistical analysis was performed using SPSS 26.0 (SPSS Inc, Chicago, USA) and R (version 4.3.2). Data were presented as means ± SD for normally distributed variables and as medians (interquartile ranges) for non-normally distributed variables. Independent-Samples T test and Mann–Whitney U-test were used for comparisons of normally and abnormally distributed continuous variables between two groups, respectively. Categorical variables were presented as percentage (%) and were compared by Chi-square test. For normally distributed data, an Analysis of Variance (ANOVA) and Student-Newman-Keuls tests were used for multiple and pairwise comparisons between the log_e GDR tertiles groups, while the Kruskal–Wallis one-way ANOVA test was used for abnormally distributed data. Pearson correlation and multiple linear stepwise regression analyses were used to evaluate the independent correlations of baPWV. Univariate logistic regression analysis and directed acyclic graphs (DAG) were used to guide the selection of covariates for AS. The DAG was constructed using the dagitty package. And the identified minimal adjustment set includes age, BMI, diabetes duration, FBG, TG, HOMA-IR, METS-IR, TG/HDL-c ratio and TyG index. Logistic regression analysis was used to analyze the independent correlates of AS. Net reclassification improvement (NRI) analysis was performed using the survIDINRI package in R to assess the incremental predictive value of log_e GDR compared with other IR markers for identifying AS. Statistical differences were defined by P-value (two-tailed) less than 0.05.

Results

Clinical and Biochemical Characteristics

The clinical and biochemical characteristics of the participants are shown in Table 1. A total of 790 non-obese patients with T2D were enrolled in our study. The subjects were divided into two groups including non-AS group (baPWV < 1800cm/s) and AS group (baPWV ≥ 1800cm/s). Compared with the non-AS group, the age, diabetes duration, VFA, SFA, SBP, DBP, AST, GGT, UA, Scr, UACR and Cys C were increased in AS group, but the HbA1c, eGFR, Hb and log_e GDR were markedly reduced (all P < 0.05). There were no obvious differences in BMI, TC, LDL-c, HDL-c, TG, FBG, FINS, ALT, HOMA-IR, TG/HDL-c ratio, TyG index, METS-IR and the percentages of males, smoking and drinking between the two groups (all P > 0.05).

Table 1 Clinical and Biochemical Characteristics by Presence of AS

Then, according to tertiles of log_e GDR, the participants were divided into three groups: T1 (0.25–1.98), T2 (1.98–2.28) and T3 (2.28–3.12) (Table 2). As the log_e GDR tertiles increased, the age, diabetes duration, BMI, VFA, SFA, SBP, DBP, TC, LDL-c, TG, FINS, HbA1c, ALT, AST, GGT, UA, Scr, UACR, Cys C, HOMA-IR, TyG index, TG/HDL-c ratio, METS-IR, baPWV, the percentages of smoking, drinking and AS were gradually decreased, while the HDL-c, Hb and eGFR were gradually elevated (all P < 0.05). The FBG and the percentages of males were no significant different between the three groups (both P > 0.05).

Table 2 Comparison of Variables According to the Tertiles of Loge GDR

Correlation Between baPWV or AS and Each Variable by Univariate Analysis

As shown in Table 3, a Pearson correlation analysis was performed to analyze the association between baPWV and each variable. The results displayed that the baPWV was positively related to age, diabetes duration, VFA, SFA, SBP, DBP, TG, FINS, GGT, UA, UACR, Cys C and TG/HDL-c ratio, while negatively to the Hb, HbA1c, eGFR and log_e GDR (all P < 0.05). BMI, TC, LDL-c, HDL-c, FBG, ALT, AST, HOMA-IR, TyG index and METS-IR were not correlated with baPWV (all P > 0.05).

Table 3 The Correlation Between baPWV or AS and Different Variables by Univariate Analysis

Moreover, univariate regression analysis was conducted to identify the factors associated with AS. The results showed that AS was positively related to the age, diabetes duration, VFA, SFA, SBP, DBP, FINS, AST, UA, UACR, Cys C, and negatively to the Hb, HbA1c, eGFR and log_e GDR (all P < 0.05). No significant relationships existed between AS and BMI, TC, LDL-c, TG, HDL-c, FBG, ALT, GGT, HOMA-IR, TyG index, TG/HDL-c ratio, METS-IR and the percentages of males, smoking and drinking (all P > 0.05).

Independent Variables of baPWV by Multiple Linear Stepwise Regression Analysis

The covariates for multivariate linear regression analysis were determined based on the results of Pearson correlation analysis and previous literature reports. A multiple linear stepwise regression analysis was conducted to analyze the independent correlations of baPWV (Table 4). The age, diabetes duration, VFA, SFA, SBP, DBP, TG, FINS, GGT, UA, UACR, Cys C, TG/HDL-c ratio, Hb, HbA1c, eGFR and log_e GDR were set as the dependent variables based on the results of Pearson correlation analysis, and the results displayed that the age, SBP and log_e GDR fit a regression model (all P < 0.05).

Table 4 Multivariate Linear Regression Analysis with baPWV as the Dependent Variable

Independent Correlations of AS by Logistic Regression Analysis

Finally, AS was served as the dependent variable, and based on the results of univariate logistic regression analysis, the DAG diagram (Figure 2), and previous literature, the following variables were included as independent variables: age, diabetes duration, VFA, SFA, SBP, DBP, FINS, HbA1c, AST, UA, eGFR, UACR, Cys C, Hb, BMI, FBG, TG, HOMA-IR, TG/HDL-c ratio, TyG index, METS-IR, log_e GDR and the percentages of smoking and drinking. A logistic regression analysis was performed to analyze the independent correlates of AS (Table 5), and the results found that after adjusting for the other variables, the log_e GDR (OR: 0.286, 95.0% CI for OR: 0.110–0.743), age (OR: 1.196, 95.0% CI for OR: 1.138–1.258), SBP (OR: 1.053, 95.0% CI for OR: 1.031–1.075) and FBG (OR: 0.886, 95.0% CI for OR: 0.792–0.990) were independently related to AS.

Table 5 The Independent Variables for AS

Figure 2 The DAG of identifying confounding variables.

Predictive Value of IR Markers for AS

To assess the incremental predictive value of various IR markers for AS, NRI analysis was performed based on logistic regression models (Table 6). All models were adjusted for potential confounders, including age, diabetes duration, VFA, SFA, SBP, DBP, FINS, HbA1c, AST, UA, eGFR, UACR, Cys C, Hb, BMI, FBG, TG, smoking and drinking. Building upon the base model without any IR marker, integrating log_e GDR yielded a modest improvement in the model’s ability to reclassify patients with AS (NRI:0.043, 95% CI 0.009–0.079, P = 0.011). In contrast, building upon the base model, integrating other IR markers such as HOMA-IR (NRI:0.007, P = 0.697), TyG index (NRI:0.011, P = 0.356), TG/HDL-c ratio (NRI:0.006, P = 0.317), and METS-IR (NRI: −0.004, P = 0.568) did not significantly improve the predictive performance.

Table 6 Analysis of the NRI for Predicting AS

Discussion

This cross-sectional study of non-obese patients with T2D revealed a significant negative association between the log_e GDR and both baPWV and AS. Increased log_e GDR tertiles corresponded with a significant reduction in baPWV and AS incidence. Furthermore, after adjusting for confounding factors, the log_e GDR was independently associated with baPWV and AS.

IR is common among diabetic patients, leading to endothelial dysfunction and inflammatory responses that contribute to AS and atherosclerosis.²² Although the EHC is considered the gold standard for assessing IS, its complexity, time consuming, and requirement for specialized personnel limit its use in large-scale clinical studies. HOMA-IR is a commonly used and simpler indicator of IR, but it relies on FINS. Previous studies have shown that fluctuations in insulin levels can be significantly influenced by an individual’s glucose tolerance and the effects of treatment. Therefore, FINS levels may not be entirely accurate for patients with T2D undergoing treatment.^23,24 Recently, an increasing number of studies have explored the close association between non-insulin-based IR surrogate indicators and AS across various populations. For instance, a study in a healthy Japanese cohort found a significant correlation between the METS-IR and AS.²⁵ A study involving 1895 participants showed a close correlation between the TyG index and the TG/HDL-c ratio with AS in hypertensive patients, while no such relationship was observed in patients with prehypertension.²⁶ Furthermore, research on patients with T2D had indicated that the TyG index was independently and more strongly associated with the prevalence of increased AS compared to HOMA-IR.²⁰ The relationship between non-insulin-based IR surrogate indicators with AS had also been validated in lean postmenopausal women, Chinese non-hypertensive and older subjects.^27–29

The log_e GDR is a newly developed model for assessing IS in T2D, and it has been validated as a reliable EHC-based surrogate capable of capturing the variability of IS in patients with T2D well.¹³ The inclusion of metabolic components (GGT, UACR, BMI and TG) allows log_e GDR to reflect a more comprehensive metabolic profile and potentially capturing a broader range of pathogenic mechanisms. In our study, we found that it was closely associated with IR markers as well. As the tertiles of log_e GDR increased, significant reductions were observed in other IR markers, suggesting a consistent relationship between log_e GDR and IS. Notably, we found that the log_e GDR was independently related to baPWV and AS. This relationship remains important even after adjusting for other confounding factors including IR markers (HOMA-IR, TG/HDL-c ratio, TyG index, and METS-IR).

The mechanisms potentially linking log_e GDR to AS are likely multifactorial and may involve several key pathways. The components included in the calculation of log_e GDR, including GGT, UACR, BMI and TG, may have been suggested as part of circadian syndrome.³⁰ Recent studies indicate that circadian syndrome may be a better predictor of CVDs risk than metabolic syndrome,³⁰ suggesting that log_e GDR might reflect a disruption in circadian rhythms, potentially influencing cardiovascular health. GGT is a key marker of oxidative stress, promoting endothelial dysfunction by reducing nitric oxide bioavailability and increasing vascular inflammation, both of which contribute to arterial stiffening. TG facilitates lipid accumulation in the vascular wall, leading to foam cell formation and atherosclerosis progression. Elevated TG levels are also associated with increased production of small, dense LDL particles, which enhance oxidative stress and vascular inflammation. UACR reflects endothelial dysfunction and vascular damage, as albuminuria is linked to increased vascular permeability and low-grade inflammation, both contributing to arterial remodeling. Additionally, BMI, particularly in the context of visceral adiposity, is associated with chronic low-grade inflammation and activation of the renin-angiotensin-aldosterone system, further promoting vascular stiffness. These components effectively represent the key metabolic pathways leading to AS, supporting the close relationship between log_e GDR and AS.^31–33

Additionally, AS is a degenerative vascular process that increases with age.³⁴ High SBP levels may damage endothelial function, leading to progressively stiffer arteries.³⁵ Be consistent with the above findings, we found a strong relationship between age and SBP with AS in non-obese patients with T2D. This underscores the importance of managing SBP as a modifiable risk factor for AS, particularly in this population. Interestingly, we observed a negative correlation between AS and FBG, which was inconsistent with most studies that suggested elevated FBG was a significant risk factor for AS.³⁶ The multifaceted influencing factors of AS may help explain this phenomenon. As mentioned earlier, the average age in the AS group was significantly higher than that in the non-AS group, and some studies have suggested that older diabetic patients tend to have better blood glucose control.³⁷

The relationship between the novel IS index log_e GDR and AS has not been extensively studied in the context of non-obese T2D. Our study is the first to observe a strong association between log_e GDR and AS in non-obese patients with T2D, highlighting its potential clinical significance. Although non-obese individuals with T2D may have normal body weight, they can still exhibit significant vascular changes. Since log_e GDR incorporates metabolic parameters including BMI, TG, UACR and GGT, it may reflect a broader metabolic disorder amenable to intervention than other IR markers. Importantly, logₑ GDR demonstrated the highest NRI among the evaluated IR indicators, indicating relatively better discriminatory capacity for AS. However, the overall improvement in risk prediction was modest, suggesting that its incremental value in risk stratification may be limited. Therefore, while logₑ GDR shows potential as a complementary tool for early identification of cardiovascular risk in non-obese T2D patients, its clinical utility should be interpreted with caution. Further prospective studies with larger, diverse cohorts are needed to confirm these findings and to clarify the role of logₑ GDR in improving cardiovascular risk prediction models.

Several limitations of this study should be acknowledged. First, as with all cross-sectional studies, we cannot establish causality between log_e GDR and AS. Longitudinal studies are essential to determine the temporal relationship and causal pathways between these variables. Second, using BMI < 24 kg/m² to define “non-obese” may not perfectly capture individuals with increased visceral adiposity, which is a key driver of metabolic dysfunction. Future studies could consider including measures such as waist circumference or waist-to-hip ratio, which provide more direct insight into visceral fat distribution. Lastly, this study is single-center and based on a small sample size, which may limit the generalizability of the results. Future prospective multi-center studies involving larger populations are needed to confirm these findings and further investigate the underlying mechanisms.

Conclusion

In conclusion, the log_e GDR, as a new simple index of IS, is independently associated with AS in non-obese patients with T2D. Its inclusion in existing risk models modestly improved the identification of arterial stiffness. The potential utility of log_e GDR in cardiovascular risk assessment warrants further investigation and validation in future studies.

Ethics Approval and Consent to Participate

The study was approved by the Human Ethics Committee of the Linyi People’s Hospital. All procedures were performed in accordance with ethical standards laid out in the Declaration of Helsinki. Informed consent was obtained from the patients.

Acknowledgments

Shuwei Shi is currently Department of Endocrinology, Linyi People’s Hospital Affiliated to Shandong Second Medical University, Linyi, China. This study was conducted while she was affiliated with the School of Clinical Medicine, Shandong Second Medical University, Weifang, Shandong, China. Baolan Ji and Guanqi Gao are co-corresponding authors for this study.

Funding

This study was supported by grants from the Postdoctoral Program of Affiliated Hospital of Jining Medical University (JYFY322152).

Disclosure

All authors declare that they have no competing interests in this study.

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Introduction

The advancement of medical technology and evolving healthcare concepts has led to the widespread adoption of day surgery, a new medical service model.¹ Anaesthetic techniques are the cornerstone of day surgery. Therefore, improving anaesthesia concepts and methods is essential to ensure safe and effective outcomes in this setting.

In clinical practice, drugs with complementary effects are often used together. The combination of sedatives and opioids is a standard practice for procedural sedation and general anaesthesia. For example, the combination of propofol with fentanyl, midazolam with fentanyl, and propofol with remifentanil improved efficacy, reducing the dosage of both drugs, and reducing adverse effects.^2–5 However, drug interactions can alter pharmacological outcomes,⁶ making it essential to understand the characteristics of these interactions. Remimazolam, a novel, ultrafast, and short-acting benzodiazepine, gained approval for use in both procedural sedation and general anaesthesia.^7–9 Alfentanil, a fentanyl derivative, is a short-acting μ-opioid analgesic widely used in various clinical settings, including endoscopy, abortion, and general anaesthesia.^10–13

Given the rapid onset and offset of remimazolam and alfentanil, their combination could be an ideal anaesthetic regimen for day surgeries. Despite this potential, only a few studies have explored the remimazolam-alfentanil interaction. Our hypothesis is that alfentanil may enhance the sedative effects of remimazolam during anaesthesia induction in patients undergoing urological day surgery.

Methods

Study Design and Participants

This study was a single-centre, single-blinded, randomised clinical trial. Ethical approval was granted by the Medical Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (identifier: 2022-KY-E-302; Chairperson: Prof. Songqing He) on 13 September 2022 and was registered with the Chinese Clinical Trial Registry (https://www.chictr.org.cn; registration number: ChiCTR2200064130, principal investigator: Xuehai Guan; date of registration: 27 September 2022). Written informed consent was obtained from all patients before enrolment. This trial was performed at the First Affiliated Hospital of Guangxi Medical University in accordance with the Declaration of Helsinki and CONSORT guidelines.

A total of 114 patients, aged 18–65 years, with an American Society of Anaesthesiologists (ASA)physical status I–III, undergoing elective urological day surgery under general anaesthesia, were enrolled. Patients with a history of difficult airway (modified Mallampati class 3–4), asthma, severe hypertension (systolic blood pressure ≥ 180 mmHg or diastolic blood pressure ≥ 110 mmHg), pulmonary heart disease, pulmonary arterial hypertension, cardiac insufficiency, hyperthyroidism, epilepsy, or psychosis were excluded. Further exclusion criteria included allergic reactions to drugs, obesity (body mass index, BMI ≥ 30 kg.m⁻²), pregnancy, and analgesic abuse.

Randomisation and Masking

Enrolled patients were randomly assigned to either the RMZ-AF or AF-RMZ group using a computer-generated randomisation code (EpiCalc 2000 software) in a 1:1 ratio. Randomisation was performed by an independent anaesthesiologist who was only involved in patient assignment and drug preparation. Group assignments were concealed in sealed envelopes. Patients, surgeons, and data collectors were blinded to the group allocation throughout the process, with the allocation only revealed after data collection and analysis were completed.

Anaesthesia Management and Intervention

All patients fasted for 8 h before surgery, with no premedication administered. Upon arrival in the operating room, standard monitoring was initiated, including non-invasive blood pressure measurement, electrocardiography, capnography, pulse oximetry (SpO₂), and bispectral index (BIS). All patients inhaled 100% oxygen through a mask for 3 min before anaesthesia induction. In the RMZ-AF group, anaesthesia was induced using remimazolam tosilate (RMZ; Jiangsu Hengrui Medicine Co., Lianyungang, China; diluted with normal saline to 1 mg mL⁻¹), starting at 6 mg kg⁻¹ h⁻¹ until the BIS reached 40–60 and was maintained between 0.2–2 mg kg⁻¹ h⁻¹. When BIS was within 40–60, alfentanil (AF; 30 µg kg⁻¹ IV; Yichang Humanwell Pharmaceutical Co., Yichang, China) and rocuronium (0.6 mg kg⁻¹ IV; Sinopharm Chemical Reagent Co., Shanghai, China) were administered. In the AF-RMZ group, anaesthesia was induced by using alfentanil (30µg kg⁻¹ IV), followed by remimazolam tosilate, starting at 6 mg kg⁻¹ h⁻¹ until BIS reached 40–60 and was maintained between 0.2–2 mg kg⁻¹ h⁻¹. When BIS was within 40–60, rocuronium (0.6 mg kg⁻¹ IV) was administered. In both groups, a laryngeal mask airway (LMA) was inserted 1 min after rocuronium administration. Anaesthesia was maintained using a combination of remimazolam (0.2–2 mg kg⁻¹ h⁻¹) and alfentanil (1–2 µg kg⁻¹ min⁻¹), adjusted based on the clinical signs and symptoms, BIS values (maintained at a range of 40–60), and the patient’s overall condition. Rocuronium was administered as a repeated bolus dose of 0.1–0.2 mg kg⁻¹ when needed. All patients underwent mechanical ventilation (tidal volume, 8 mL kg⁻¹; respiratory rate: 8–12 breaths min⁻¹; oxygen concentration, 60%; and fresh gas flow, 2 L min⁻¹). All patients with hypotension (a 30% decrease in mean arterial blood pressure (MBP) compared with baseline) were treated with ephedrine at the discretion of the attending anaesthesiologist.

If signs of intraoperative awakening (BIS > 60) were detected, the remimazolam infusion rate was adjusted to 10 mg kg⁻¹ h ⁻¹ for up to 1 min. If awakening signs persisted, remimazolam was discontinued and replaced with propofol. All drugs were discontinued at the end of the surgery, and patients were transferred to the post-anaesthesia care unit (PACU) for recovery.

Outcomes

The primary outcome was the time from remimazolam administration to loss of consciousness (LOC) during anaesthesia induction. The consciousness was assessed by using Modified Observer`s Assessment Alertness/Sedation Scale (MOAA/S; 0, no response after painful trapezius squeeze, defined as LOC; 1, responds only after painful trapezius squeeze; 2, responds only after mild prodding or shaking; 3, response to name spoken loudly and/or repeatedly; 4, response to name spoken in normal tone; 5, response readily to name spoken in normal tone) with 10s interval during anaesthesia induction.

Secondary outcomes included anaesthetic and surgical characteristics, vital signs, and adverse events. The durations of surgery, anaesthesia, and PACU stay, as well as the time of eyes-opening and extubation, were recorded. We recorded the administration of remimazolam and alfentanil at the following time points: from administration to LOC, at BIS ≤ 60, and at the end of surgery. Total administration of rocuronium, ephedrine, and crystalloid infusion volumes were also recorded. Vital signs (mean arterial blood pressure [MBP], heart rate, SpO₂, and BIS) were recorded at the following time points: 5 min before anaesthesia (baseline), at LOC, at BIS ≤ 60, at intubation, at 1 and 5 min after intubation, at the beginning of surgery, at 5 min after surgery, at time of eyes-opening, at time of extubation, and at discharge from the PACU. Adverse events such as hypertension (≥ 30% increase in MBP from baseline), hypotension (≥ 30% decrease in MBP from baseline), bradycardia (<50 beats min⁻¹), tachycardia (>100 beats min⁻¹), injection pain, dysphoria, nausea/vomiting, awareness, delirium, and hiccups were also recorded.

Statistical Analyses

Statistical analyses were performed using GraphPad Prism 9.0 (Dotmatics, Boston, MA, USA). The normality and equality of variances for continuous variables were tested using the Kolmogorov–Smirnov and sphericity tests, respectively. Continuous values with normal distribution and equal variance are presented as means (SD) and were analysed using an unpaired t-test or repeated-measures two-way analysis of variance (ANOVA), followed by Bonferroni’s multiple comparison test. Continuous values with non-normal distribution and unequal variance are presented as medians (interquartile range [IQR]) and were analysed using the Mann–Whitney U-test. Categorical values are presented as numbers (%) and were analysed using Fisher’s exact test. A P-value of <0.05 was considered statistically significant.

This study was designed as a superiority trial. PASS software (version 11.0; NCCS, Utah, USA) was used to calculate the sample size. Preliminary tests showed that the time from remimazolam administration to LOC (mean [SD]) was 106.0 (30.0) s and 123.0 (32) s in the AF-RMZ and RMZ-AF groups, respectively. We calculated that 54 patients per group were required to achieve 80% power at a two-sided alpha of 0.05 to detect a significant difference in the primary outcome. To account for a potential 5% dropout rate, we enrolled 57 patients in each group.

Results

Between September 2022 and December 2023, 171 patients were screened for eligibility. Of these, 30 did not meet the inclusion criteria, 27 declined to participate, while 114 were successfully recruited and randomised into either the RMZ-AF or AF-RMZ group (n=57 per group). A total of 114 patients were included in the analysis (Figure 1). Table 1 presents the patient demographic data. No statistically significant differences were observed between the groups.

Table 1 Baseline Characteristics of Patients

Figure 1 CONSORT diagram for the trial. CONSORT indicates Consolidated Standards for Reporting of Trials.

The time from remimazolam administration to LOC during anaesthesia induction was significantly shorter in the AF-RMZ group than in the RMZ-AF group (87.3 [25.7] s vs 132.3 [32.3] s, P<0.0001, Table 2). Similarly, the time from remimazolam administration to BIS ≤ 60 was significantly shorter in the AF-RMZ group than in the RMZ-AF group (168.2 [58.1] s vs 207.8 [61.6] s, P=0.0006, Table 2).

Table 2 Sedation Characteristics of Patients Receiving Remimazolam Combined with or Without Alfentanil for Anaesthesia Induction

No significant differences were found between groups in terms of anaesthesia duration, surgery duration, eyes-opening time, extubation time, or PACU stay (Table 2). The total administration of remimazolam did not differ significantly between groups (Table 3). However, remimazolam doses were more in the RMZ-AF group than in the AF-RMZ group at LOC (14.7 [12.3, 16.4] mg vs 9.9 [8.5, 11.0] mg, P<0.0001) and at BIS ≤ 60 (21.3 [17.5, 25.1] mg vs 18.4 [13.1, 22.6] mg, P=0.0058). No differences were found between the groups in terms of the total administration of alfentanil, ephedrine, rocuronium, or crystalloid infusion volume.

Table 3 Characteristics of Anaesthesia and Surgery in Patients Receiving Remimazolam Combined with or Without Alfentanil for Anaesthesia Induction

Table 4 presents the incidence of adverse events. Hypotension was the most common adverse event, but no difference was found between the RMZ-AF and AF-RMZ groups (28 [49.1%] vs 22 [38.6%], 95% CI: 1.3 [0.84–2.0], P=0.3454). The incidence of hypertension was 10.5% (n=6) in the RMZ-AF group and 15.8% (n=9) in the AF-RMZ group (95% CI: 1.5 [0.59–3.8], P=0.5808). Tachycardia occurred in 12.3% of patients in both groups. No patients in either group experienced bradycardia, injection pain, dysphoria, nausea/vomiting, awareness, delirium, or hiccups.

Table 4 Incidence of Adverse Event in Patients Receiving Remimazolam Combined with or Without Alfentanil for Anaesthesia Induction

No significant differences were observed in MBP, heart rate, SpO₂, or BIS values at any time point (Figure 2).

Figure 2 Changes in vital signs of patients receiving remimazolam combined with or without alfentanil for anaesthesia induction. Data are displayed as means (SD) (A–C) or medians (D). Data were compared using repeated-measures two-way analysis of variance (ANOVA) with Geisser-Greenhouse correction, followed by Bonferroni`s multiple comparisons test. (A) Drug: F (1, 112) = 0.8040, p=0.3718; Time: F (11, 1232) = 127.5, p<0.0001; Drug Ⅹ Time: F (11, 1232) = 1.597, p=0.0936; Subject: F (112.1232) = 8.416, p<0.0001. (B) Drug: F (1, 112) = 0.0362, p=0.8494; Time: F (11, 1232) = 11.92, p<0.0001; Drug Ⅹ Time: F (11, 1232) = 7.392, p<0.0001; Subject: F (112.1232) = 14.33, p<0.0001. (C) Drug: F (1, 112) = 1.045, p=0.3088; Time: F (11, 1232) = 11.43, p<0.0001; Drug Ⅹ Time: F (11, 1232) = 0.5367, p=0.8793; Subject: F (112.1232) = 4.385, p<0.0001. (D) Drug: F (1, 112) = 0.7292, p=0.3950; Time: F (8, 896) = 639.0, p<0.0001; Drug Ⅹ Time: F (8, 896) = 1.627, p=0.1131; Subject: F (112.896) = 3.800, p<0.0001. Abbreviations: RMZ, remimazolam; AF, alfentanil; MBP, mean arterial blood pressure; HR, heart rate; SpO2, pulse oximetry; LOC, loss of consciousness; BIS, bispectral index; PACU, post-anaesthesia care unit.

Discussion

This is the first reported randomised controlled trial investigating the interaction between remimazolam and alfentanil. The main finding of our results showed that the time to LOC and the doses of remimazolam required to reach LOC and BIS ≤ 60 during anaesthesia induction were shorter and lower, respectively, in the AF-RMZ group than in the RMZ-AF group. These results confirm our hypothesis that alfentanil enhances the sedative effects of remimazolam during anaesthesia induction in patients undergoing urological day surgery.

Drug interactions can be classified as synergism, additivity, or antagonism, regardless of whether one drug exerts an effect on its own.^14–17 During anaesthesia induction and maintenance, it is a common practice to use two or more drugs either successively or simultaneously. Combining sedatives and opioids has a synergistic effect, enhancing anaesthesia, reducing the dosage of both drugs, and minimising adverse events.¹⁸ For instance, the combination of propofol and alfentanil changed alfentanil’s pharmacokinetics by decreasing elimination clearance by 15%, rapid distribution clearance by 68%, slow distribution clearance by 51%, and lag time by 62%.⁶ Although we did not conduct pharmacokinetic assessments in this study, we speculate that pretreatment with alfentanil can also affect the pharmacokinetics of remimazolam by decreasing elimination clearance and slowing distribution clearance, thereby enhancing the sedative effect of remimazolam.

Drug interactions may occur through the modulation of the action site.¹⁹ Therefore, understanding the mechanisms underlying these interactions is critical. The combination of propofol and alfentanil produced synergistic antinociceptive effects²⁰ through the inhibition of phosphorylated extracellular signal-regulated kinase 1/2, c-Fos protein²¹ and the adenylyl cyclase pathway.²² Propofol exerts sedative effects by potentiating GABA responses and activating GABA type A receptors (GABAARs).²³ Similarly, remimazolam exerts sedative effects by also acting on GABAARs.⁷ Alfentanil exerts its analgesic effect by acting on mu-opioid receptors (MOR). Since both GABAARs and MOR are co-expressed in some primary afferent neurons, it is plausible that propofol–alfentanil and remimazolam-alfentanil administration may activate the same neural pathways, thereby enhancing their sedative effects.

Alfentanil has been used as a sedative regimen in intensive care without causing prolonged respiratory depression.²⁴ Given that the time to LOC or BIS ≤ 60 and the doses of remimazolam required were significantly shorter or lower, respectively, in the AF-RMZ group compared with the RMZ-AF group, we concluded that alfentanil enhances the sedative effect of remimazolam. The peak effect of a bolus injection of alfentanil occurs at approximately 3–4 min,²⁵ while remimazolam reaches a peak effect at 2–3 min. By administering alfentanil immediately before remimazolam, the peak effect of both drugs overlaps, maximising remimazolam’s sedative efficacy. As the exact nature of their interaction – whether synergistic or additive – remains unclear, further investigation is required to elucidate the underlying mechanisms.

Combining alfentanil and midazolam is recommended in different clinical practices. The combination of remimazolam with alfentanil for anaesthesia during endoscopic retrograde cholangiopancreatography (ERCP), colonoscopy, and gastroscopy procedures showed fewer respiratory depression events and haemodynamic advantages than the propofol-alfentanil combination.^26–28 Hypertension, hypotension, and tachycardia were the major adverse events among the two groups; however, no differences were found between the groups in our trial. The awakening time was slightly longer, and the incidence of adverse events (nausea, abdominal pain, fatigue, dizziness, and abdominal distension) were lower in remimazolam-alfentanil group than that in the propofol-alfentanil group during gastroscopy.²⁷ The postoperative 15-item quality of recovery questionnaire score was higher, and the abdominal pain was lower in the remimazolam-alfentanil group than in the propofol-alfentanil group during ERCP procedure.²⁶ Thus, combining remimazolam and alfentanil may be a safe option for anaesthesia.

Sedative-hypnotic drugs and opioids are risk factors for post-operative nausea and vomiting (PONV), which can prolong recovery. None of the patients developed PONV during our trial. Consistent with a previous report, alfentanil reduced the incidence of PONV than fentanyl.²⁹ The use of rapidly metabolic sedative-hypnotic drugs and opioids for anaesthesia is effective in reducing the risk of PONV.³⁰

None of the patients developed emergence delirium (ED) during our trial. Intranasal alfentanil, in addition to oral midazolam, did not decrease sevoflurane-induced ED.³¹ Intravenous alfentanil decreased the incidence of ED in the PACU.³² Compared with intravenous injection, the bioavailability of intranasal alfentanil was reduced to 64.7%.³³ We infer that the different bio-availabilities of alfentanil result in this discrepancy in preventing ED.

Hiccups are a troublesome adverse event associated with remimazolam. Although remimazolam-induced hiccups are generally self-limiting, they are associated with the risk of regurgitation and aspiration, particularly in patients with a full stomach. No patients developed hiccups during this trial. The incidence of hiccups depends on the bolus rate of remimazolam administered during sedation induction.³⁴ We believe that remimazolam administration at a rate of 6 mg kg⁻¹ h⁻¹ during anaesthesia induction would be appropriate. No patients in our trial experienced injection pain, dysphoria, or increased awareness.

Although there was no significant difference in the incidence of adverse events between the two groups in this study, which differed from those of other studies,^26,27 the reasons may be differences in the study population, differences in drug dosage and administration methods, and the study sample size.

This study had several limitations. First, the trial focused exclusively on patients undergoing urological day surgery, limiting the generalisability of the findings to other populations. Further studies are needed to validate these conclusions in other contexts. Second, this was a single-blinded trial. Although the patients, surgeons, and data collectors were blinded to the group assignment throughout the process, the possibility of bias cannot be entirely excluded. Third, all patients were drawn from a single centre, and genetic and racial factors may limit the applicability of our findings to other populations. Further multi-centre clinical trials are required to confirm this conclusion.

Conclusion

In conclusion, alfentanil enhances the sedative effects of remimazolam during anaesthesia induction in patients undergoing urological day surgery. The combination of remimazolam and alfentanil for general anaesthesia would improve efficacy, reducing the adverse effects and dosage of drug. But the potential mechanisms need further study.

Abbreviations

MBP, mean arterial blood pressure; CI, confidence interval; GABA_A, gamma-aminobutyric acid receptor subunit A; ASA, American Society of Anaesthesiologist; PACU, post-anaesthesia care unit; SpO₂, pulse oximetry; BIS, bispectral index; LOC, loss of consciousness; IQR, interquartile range; ASD, absolute standardized difference; ANOVA, analysis of variance; RMZ, remimazolam; AF, alfentanil.

Data Sharing Statement

The data generated during the current study are available from the corresponding author on reasonable request.

Ethic Approval

This study was approved by the Medical Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (identifier: 2022-KY-E-302; Chairperson: Prof. Songqing He) on 13 September 2022 and was registered with the Chinese Clinical Trial Registry (https://www.chictr.org.cn; registration number: ChiCTR2200064130, principal investigator: Xuehai Guan; date of registration: 27 September 2022). Written informed consent was obtained from all patients before enrolment. This trial was performed at the First Affiliated Hospital of Guangxi Medical University in accordance with the Declaration of Helsinki and CONSORT guidelines.

Acknowledgments

This study was supported by the Natural Science Foundation of Guangxi Zhuang Autonomous Region (2022GXNSFAA035628, 2024GXNSFAA010222), the Clinical Research “Climbing” Program of the First Affiliated Hospital of Guangxi Medical University (YYZS2022005), the Guangxi Zhuang Autonomous Region Health Commission’s Self-Fund Research Project on Western Medicine (Z-A20230492), and the Guangxi Zhuang Autonomous Region Traditional Chinese Medicine Appropriate Technology Development and Promotion Project (GZSY22-59). The funder had no role in the concept, patient recruitment, data collection, analysis, interpretation, trial design, or making the decision to submit for publication.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

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