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What is perimenopause?

Perimenopause is defined as the transitional phase that can last anywhere from 8 to 10 years before menopause, which is marked by 12 consecutive months without a menstrual period. During this time, fluctuations in estrogen and progesterone levels create hormonal chaos that triggers various symptoms. Unfortunately, many women misattribute these symptoms to stress, overwork, or mental health issues, as per the National Institute of Mental Health.

How do you know if it is PMS or perimenopause?

The key difference between PMS and PMM lies in duration and unpredictability. PMS usually arises predictably, following ovulation and is alleviated by menstruation. PMM, however, often feels like an ongoing battle with no apparent cause or solution, radically altering women’s lives, as per Harvard Health.

How does mood change during perimenopause?

The hormonal shifts of perimenopause impact neurotransmitters like serotonin and dopamine, which influence mood, focus, and motivation, as per the Journal of Midlife Health. As a result, many women experience heightened emotions such as irritability, anxiety, and sadness.

These emotional fluctuations can be invisible to others, leading women to feel misunderstood and unappreciated. They may be dismissed as “overreacting” or “too sensitive.” “The impact on relationships and work productivity can be profound, while medical professionals sometimes fail to connect the symptoms to hormonal changes, prescribing antidepressants or sleep aids instead. This dismissive attitude can foster feelings of shame, frustration, and isolation,” menopause coach Tammana Singh tells Health Shots.

What are the symptoms of hormonal changes in women?

Recognising the signs of perimenopause can help you take control of your health and overall well-being. Menopause coach Tammana Singh shares seven key indicators:

1. Heightened anxiety or depressive spells: Unexplained emotional lows and anxiety attacks may become more frequent.
2. New or worsening PMS symptoms: If your PMS seems to be intensifying or changing, it might be a sign of perimenopause.
3. Night sweats and insomnia: Experiencing sudden sweating during the night or difficulty sleeping can significantly disrupt rest.
4. Brain fog or forgetfulness: Mental clarity may decrease, resulting in forgetfulness or difficulty concentrating.
5. Sudden weight gain: Weight gain, particularly around the abdomen, can signal hormonal changes.
6. Migraines or joint pain: Increased headaches or joint discomfort may indicate shifts in hormone levels.
7. Irregular or heavier periods: Changes in menstrual cycle regularity or flow can be a telling sign.

How to manage hormonal changes during perimenopause?

Awareness is crucial when navigating this transitional phase. Understanding that hormonal changes drive these symptoms allows women to seek appropriate help rather than blaming themselves.

Here are some methods to consider:

1. Track your hormonal patterns: Using apps, journals, or simple calendar notes can help you connect mood changes with variations in your menstrual cycle, as per the Journal of Medical Internet Research. Look for patterns that emerge over time.
2. Rethink self-care: The approach to self-care during this phase requires more than just surface-level solutions, as per the American Psychological Association. Focus on restorative practices such as:

• Deep breathing exercises
• Journaling
• Professional therapy
• Gentle movements like yoga or tai chi can help regulate cortisol and estrogen levels.

3. Build a menopause-ready lifestyle: Healthy lifestyle choices can alleviate some perimenopausal symptoms. Consider:

• Introducing foods rich in phytoestrogens (flaxseeds, sesame seeds, tofu).
• Maintaining good sleep hygiene—consistent sleep schedules, a comfortable sleep environment, and practices that promote relaxation.
• Starting a strength-training regimen to support muscle and bone health.

4. Get informed support: Seek out professionals well-versed in hormonal health, such as:

• Functional medicine practitioners
• Integrative gynaecologists
• Specialists knowledgeable about Ayurveda
• Therapists who can guide you through lifestyle shifts based on current research

Hormonal changes may challenge us, but they also open the door to deeper body awareness and self-acceptance.

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Introduction

Chronic obstructive pulmonary disease (COPD) is a debilitating condition that is characterized by poorly reversible airflow limitation, difficulty breathing during physical activities^1–4 decreased exercise capacity,⁵ and limitations in daily activities.^6–9 According to the Italian National Statistics Institute (ISTAT) and the Global Burden of Diseases initiative,^10–12 in Italy, approximately 3.5 million adults are affected by COPD and 2.5% of all Disease Adjusted Life Years lost were attributable to COPD in 2021.¹³ However, these figures may underestimate the actual prevalence of COPD because the disease is often diagnosed only in its advanced stages.^11,14 According to the Medicines Utilization Monitoring Center report recently published by the Italian Medicines Agency, some patients discontinue treatment early after initiating maintenance therapy,¹¹ emphasizing the need for improved COPD management in terms of appropriate diagnosis, pharmacological treatment, and treatment adherence.¹⁵ The management of COPD presents several challenges, including misdiagnosis, delayed diagnosis, failure to implement fundamental measures to slow disease progression (eg, tobacco cessation, vaccinations, and lifestyle changes), uncertainty in selecting the most appropriate drug for treatment, and poor adherence to therapy.^16,17 The Global Initiative for Chronic Obstructive Lung Disease (GOLD 2023–2025) recommend a comprehensive approach to COPD management, including accurate diagnosis and severity assessment, smoking cessation, and individualized pharmacological and non-pharmacological interventions, with a focus on managing exacerbations.^15,18 An e-Delphi study of 600 general practitioners (GPs) in Italy reported that although most GPs were familiar with the GOLD 2023 report and COPD reimbursement requirements, only 34% had access to spirometry. There was no consensus on the initial treatment options, and re-evaluation of triple therapy necessitated a specialist referral.¹⁹

Effective COPD management cannot be limited to expert care alone, especially when prevention and long-term monitoring are essential for optimal outcomes. To address the challenges in COPD management, the Italian Medicines Agency (AIFA) introduced Nota 99, which conforms to the GOLD report 2022 and confers GPs the responsibility of diagnosing and prescribing appropriate medication for mild to moderate COPD. Given the considerable prevalence of COPD, this act recognizes the critical role of GPs in managing COPD. Nota 99 allows GPs to prescribe any inhaled therapy, except for the single-device inhaler triple therapies, while maintaining specialist care for individuals with severe pulmonary obstruction or recurrent exacerbations.¹¹

Given this new scenario, ASTER, an Italian observational prospective multicenter trial, was designed to provide the first meaningful insights into COPD management by GPs following the Nota 99, describing the characteristics of patients, treatment patterns (primary outcome), and clinical outcomes (secondary outcome) over a 6-month observation period.

Materials and Methods

Trial Design and Oversight

ASTER was an observational, multicenter, prospective cohort study conducted in Italy that focused on patients with COPD who were managed by GPs following standard protocols of clinical practice. Consecutive patients at each participation center who provided the written informed consent and privacy form and met the eligibility criteria were enrolled in the study. The study was conducted in 30 centres distributed throughout Italy in order to obtain results reasonably albeit not formally representative of the management of COPD in general medicine in Italy according to the Nota 99. This study was conducted in compliance with the Guidelines for Good Pharmacoepidemiology Practice (GPP)²⁰ and the regulatory elements of observational research in Italy.²¹

Eligible patients were aged 40–80 years and had spirometry-confirmed COPD (post-bronchodilator Forced Expiratory Volume in one second (FEV₁) to Forced Vital Capacity (FVC) ratio <0.70) with an FEV₁ of ≥50% of the predicted value. Patients were enrolled if they had ≤1 exacerbation requiring antibiotics and/or oral corticosteroids; had no emergency room (ER) visits or hospitalizations for COPD in the past year; and, according to the prescription limits for GPs before Nota 99, they could have been treated in the last 3 months before enrollment exclusively with a short or long-acting bronchodilator or an ICS/LABA; and had a COPD Assessment Test (CAT) score ≥10 at the enrollment appointment. Patients were excluded if they were unable to undergo spirometry according to Nota 99, had received LABA/LAMA combinations within the previous 3 months, had low treatment adherence as judged by the clinician, inability to properly use an inhaler, were pregnant or breastfeeding, had a current asthma diagnosis, could not read or write in Italian, or were already enrolled in another clinical trial.

Each patient was assessed during the enrollment visit, which coincided with the reconfirmation of diagnosis and therapy prescription. Patients were then followed up with specific visits at 3 and 6 months, as outlined by standard clinical practice. During the enrollment visit, the GP collected the patient’s history of respiratory disease and symptoms including those within the previous year, occupational and tobacco smoke exposure, COPD anamnesis, and previously prescribed COPD therapies as well as comorbidities and related therapies. The GPs provided the COPD Assessment Test (CAT)²² to the patients and completed the modified Medical Research Council Dyspnea Scale (mMRC)²³ questionnaires. At the 3- and 6-month follow-up visits, the GP collected data on the incidence, severity, and treatment of exacerbations and adjusted the treatment as needed. Additionally, at the 6-month visit, the GP collected information on functional parameters if spirometry was performed according to clinical practice, provided the CAT questionnaire to the patient, and completed the mMRC questionnaire.

Primary and Secondary Effectiveness Analyses

The primary endpoint of the study was to describe treatment patterns during the 6-month observation period, including the proportion of patients taking different COPD medications and any changes in treatment patterns. The secondary endpoints were demographic and clinical features, FEV₁ at enrollment and after 6 months, patient-reported outcomes (CAT and mMRC scores) at enrollment and after 6 months, and the number of COPD exacerbations and exacerbations per patient during the observation period.

Statistical Consideration

The sample size was determined based on feasibility considerations, including the duration of the enrollment period and the number of participating centers. It was estimated that approximately 400 patients can be enrolled over an 8-month period from 40 Italian study centers. Given an expected drop-out rate of approximately 20% over the 6-month observation period, 320 patients were expected to be available for the primary analysis; accordingly, simulations were performed to estimate the achievable precision of the 95% confidence interval (95% CI) of the expected proportions for 320 evaluable patients. This descriptive study had no defined formal hypotheses and no statistical significance testing was performed; data was analyzed using epidemiological methods. Descriptive statistics were provided for all variables and endpoints. All analyses were performed using the SAS software (SAS Institute, Cary, North Carolina, USA).

Results

Participant Disposition and Characteristics

Initially, 385 patients were enrolled in the ASTER study, and 41 of these who did not meet the eligibility criteria were excluded (Figure 1), resulting in 344 (89.4%) eligible patients. Of these eligible patients, 332 (96.5%) completed the study, whereas 12 (3.5%) were lost to follow-up (n = 10) or excluded due to consent withdrawal (n = 2).

The majority of the eligible patients were men (61.9%) and predominantly Caucasian (98.8%) (Table 1). Most patients had either primary (18.9%) or secondary education (71.7%) and were unemployed or retired (73.6%). At enrollment, 49.3% of the patients were active smokers, 41.7% had previously smoked, and 9.0% had never smoked. The majority of patients (83.7%) had comorbidities at enrollment, with arterial hypertension (58.3%), diabetes (24.0%), and cardiac ischemic disease (16.7%) being the most common (Table 1). Moreover, 50% of patients were regularly treated with ≥3 medications for concomitant diseases. The most prevalent COPD symptoms were cough (82.6%), shortness of breath (66.3%), and phlegm (48.0%). More than half of the patients (54.1%) had mild to moderate dyspnea (mMRC grade ≤2) at enrollment (Table 2). Further, 77.6% of the patients reported experiencing the same COPD symptoms in the year before enrollment as they did at the time of diagnosis.

Table 1 Characteristics of the Patients at Enrollment

Table 2 Disease Characteristics at Enrollment (Eligible Patients)

Of the eligible patients, 196 (57%) were classified as incident patients—symptomatic individuals not previously diagnosed with COPD by spirometry but likely prescribed treatments such as LAMA, LABA, or ICS/LABA by their GP without a confirmed diagnosis—while 148 (43%) were classified as prevalent patients with a prior COPD diagnosis (Table S1). Incident patients had a higher FEV₁ (mean, 2.0 vs 1.7), were slightly younger (mean age, 67.2 vs 69.2 years), were more likely to be employed (25.4% vs 17.4%) and had fewer comorbidities (80.6% vs 87.8%) than prevalent patients. In addition, incident patients experienced severe dyspnea less frequently (mMRC grade ≥2: 40.3% vs 53.4%) and had a lower incidence of poor quality of life (CAT score of 21–30: 14.3% vs.19.6%) than prevalent patients.

Primary Endpoint results

At enrollment, 20.9% of patients were treated with LAMA, 13.7% with an ICS/LABA combination, 2.9% with LABA, and 62.5% (30 prevalent and 185 incident patients) were not receiving any treatment (Figure 2). At the 3-month follow-up, 56.7% of patients were being treated with LABA/LAMA, 21.2% with LAMA, and 12.2% with ICS/LABA (Table S2). At the 6-month follow-up, 53.5% of the patients were being treated with a LABA/LAMA combination, 19.2% with LAMA, and 11.3% with an ICS/LABA combination. Current therapy at 6 months was not notably different between prevalent and incident patients, with the only exception of the ICS/LABA combination was being used more frequently in prevalent patients than in incident patients (16.2% vs 7.7%) (Table S3).

Figure 2 Treatment pattern of COPD medications for eligible patients at enrollment (baseline) and at the 6-month follow-up. Abbreviations: ICS, inhaled corticosteroid; LAMA, long-acting muscarinic antagonist; LABA, long-acting beta-agonist; N, total number of patients at each visit; n = number of patients in each category.

Secondary Endpoint results

Overall, lung function improved over the 6-month observational period, as evidenced by the increase in pre-bronchodilator FEV₁ (Table 3). When the pre-bronchodilator FEV₁ at 6 months was compared with that at enrollment in 206 patients, a mean increase of 140 mL was observed (Table 3), and one-quarter of the patients exhibited an increase of at least 300 mL.

Table 3 Summary of Secondary Endpoint Results for Eligible Patients at Enrollment and at the 6-month Follow-up

At enrollment, 45.9% of patients with COPD reported a significant level of dyspnea, with an mMRC score ≥2. At the 6-month follow-up, this value was reduced to 23.5% (Table 3). The mMRC scores at enrollment and at the 6-month follow-up are summarized in Table S4. Overall, the mMRC score decreased by at least one point in 40% of the patients and remained unchanged in 53.9%.

In terms of the impact of COPD on patients’ lives, the patients’ health status and quality of life improved noticeably over the 6-month study period, as evidenced by a mean decrease of 3.6 points in the CAT score (Table 3). Notably, the CAT score decreased by at least 6 points in one-quarter of the patients.

During the observation period, 3.9% (n = 13/332) of the patients experienced 14 exacerbations (10 mild and 4 moderate), resulting in an approximate annualized exacerbation rate of 7.8%. This represents a meaningful drop from the 23.2% incidence rate in the year before recruitment, indicating an absolute reduction of 15.4% and a 34% reduction in the annualized relative risk over the 6-month period (Table 3). Notably, none of these reported exacerbations required admission to the ER or hospitalization.

Discussion

To the best of our knowledge, the ASTER study was the first COPD study conducted in a GP setting in Italy, providing real-world evidence of clinical practice for patients with COPD managed according to Nota 99, which confers GP with a critical responsibility in the COPD management. The study findings highlight the importance of treatment pathways, and the public health implications of appropriate COPD management.

The findings of the ASTER study provide a detailed overview of the evolving treatment patterns for patients with COPD. Over the course of the study, there was a noticeable shift towards combination therapy, with a substantial number of patients switching from monotherapy with LABA or LAMA to LABA/LAMA combination therapy. Similarly, the majority of patients who were initially treated with ICS/LABA combination therapy, switched to LABA/LAMA therapy. This shift towards LABA/LAMA therapy as well as the observed improvements in the CAT and mMRC scores suggests the effectiveness of these treatments in managing symptoms and improving the quality of life of patients with COPD. These real-world results are consistent with prior randomized controlled studies that demonstrated the effectiveness of LAMA/LABA therapy for patients with COPD.^24,25 Overall, the results of the ASTER study suggest that the implementation of Nota 99 may positively influence clinical practices on COPD treatment. The absence of severe exacerbations requiring hospitalization suggests that enhanced patient management and treatment regimens are effective in preventing severe episodes. This is also consistent with previous research indicating that treatment with LABA/LAMA therapy is more effective than monotherapy in preventing all COPD exacerbations.²⁶ Although no formal hypothesis was established, our findings indicate that intervention according to Nota 99, as implemented in the ASTER study, has the potential to avoid an exacerbation episode for every six patients correctly diagnosed and treated over a year.

The ASTER study emphasizes the pivotal role played by Italian GPs in COPD management. With resources and clear guidelines, GPs can effectively diagnose, treat, and monitor patients with COPD, reducing the disease’s impact and improving long-term outcomes. Continuous training and resources are essential for GPs to provide optimal care. Comparative analyses with practices in other countries^27–29 reveal that Nota 99 promotes structured COPD management, allowing for a proactive rather than reactive strategy by providing clear guidance on the correct diagnostic process, prevention, and management of COPD. According to the ASTER study, 94.4% of newly diagnosed patients with COPD were untreated at the time of enrollment, highlighting that COPD is often overlooked. Improved diagnostic procedures in primary care are essential. Active research and surveillance by GPs can help develop precise diagnostic tools and protocols, ensuring accurate and prompt treatment. Routine case findings and early detection strategies are critical to improve COPD management outcomes.

Although the ASTER study provides valuable insights, it has the following limitations. As a real-life, non-interventional study with prospective data collection, there are inherent biases to consider. Information and selection biases may have influenced the outcome as respondents may have been influenced by GPs or their own beliefs about meeting GP expectations. Additionally, the inclusion criteria required patients to be able to read and write in Italian and fill out questionnaires on their own, which may have disqualified some patients and reduced the generalizability of the findings. Furthermore, GPs’ participation in the trial may have encouraged them to adhere more rigorously to treatment recommendations, potentially diverging from “real-world” treatment practices (known as the Hawthorne effect). However, efforts were made to mitigate these biases, including consecutive patient enrollment and regional diversity in site selection.

The study’s findings may have limited applicability to the broader Italian patient population with COPD because of the study’s recruitment strategies and specific eligibility criteria. Despite the efforts taken to choose locations from various geographic regions and ensure representative sampling, the enrolled patients may not fully represent Italy’s COPD patient community. As a result, the findings should be interpreted with caution, taking into account potential selection bias.

Conclusion

The proactive identification of patients with COPD in a general practice setting may allow for early detection, effective treatment, and better clinical outcomes. In ASTER study, the application of AIFA’s Nota 99, which empowers GPs to initiate the most effective therapy when needed, was associated with meaningful improvements in patient outcomes in this study. This suggests that GPs in Italy should actively identify patients with COPD, especially those who may not pay attention to their symptoms because of lack of awareness. Such a proactive approach could result in earlier interventions, more effective disease management, and, eventually, improved patient outcomes. However, future studies using public health system administrative registries or large clinical databases could confirm the ASTER results, accurately define their dimensions, and reduce potential biases, verifying if the promising outcomes are consistent in general medical practice in Italy.

Abbreviations

AIFA, Italian Medicines Agency; ASTER, Italian observational prospective multicenter study; CAT, COPD Assessment Test; CI, Confidence Interval; COPD, Chronic obstructive pulmonary disease; GPP, Good Pharmacoepidemiology Practice; ER, Emergency room; FEV₁, Forced expiratory volume in 1 second; FVC, Forced vital capacity; GOLD, Global Initiative for Chronic Obstructive Lung Disease; GP, General practitioner; ICS, Inhaled corticosteroids; ISTAT, Italian Institute of Statistics; LABA, Long-acting beta-agonists; LAMA, Long-acting muscarinic antagonists; mMRC, modified Medical Research Council; SABA, Short-acting beta-agonists; SAMA, Short-acting muscarinic antagonists; Nota 99, Italian Medicine Agency’s guideline for managing mild-to-moderate COPD by GPs.

Data Sharing Statement

Anonymized individual participant data and study documents can be requested for further research from https://www.gsk-studyregister.com/en/.

Ethics Approval and Informed Consent

This study complies with the Declaration of Helsinki. Informed consent was obtained before initiating this study. The ethics committee of each participating study center has received approval through the Coordinator Research Ethics Committee (Comitato Etico Lazio 1, Rome, Italy), and the individual study centers have received approval from the following ethical committees: Comitato Etico Interaziendale – ASL Alessandria; Comitato Etico Area Vasta Centro – USL Toscana Centro; Comitato Etico Area Vasta Sud Est – USL Toscana Sud Est; Comitato Etico Interprovinciale Area 1 ASL BT; CESC delle Province di Verona e Rovigo; Comitato Etico di Brescia; CET Regione Abruzzo; Comitato Etico – ARES Sardegna; CET Regionale dell’Umbria; Comitato Etico Regione Marche; Comitato Etico Lazio 1; Comitato Indipendente di Etica Medica – ASL Brindisi; Comitato Etico Regione Calabria Area Centro; Comitato Etico Campania Centro; Comitato Etico di Messina; Comitato Etico Indipendente – ASL Bari; CET Marche – AOU delle Marche.

Acknowledgments

The authors gratefully acknowledge the contributions of all the 30 Italian general practitioners (GPs) who participated as principal investigators and sub-investigators in this study. The authors also extend their sincere thanks to Alessandra Dal Collo for support in administrative matters. The authors would like to express their gratitude to the General Medicines Medical Science Liaisons (MSLs) team for their scientific support provided to the GPs. In addition, the authors thank IQVIA Solutions Italy SRL for their contributions to the conduct of clinical operations, data management, and statistical analysis. The authors also thank Dr. Rakesh Ojha, PhD, a medical writer and an employee of GSK, India, for his manuscript writing and project management support.

Author Contributions

All authors contributed to the study conception or design and/or data analysis and interpretation. All authors were involved in the writing, reviewing, and final approval of the manuscript and agreed to be accountable for all aspects of the work.

Funding

This analysis was funded by GSK (study number 217466). GSK also funded all expenses related to the development and publication of this manuscript.

Disclosure

M.V., C.S., D.C., and B.G. are employees of GSK and hold stock options. G.G. and U.A. have no conflicts of interest to declare. R.P. has received consulting fees from GSK Italy and holds stock options from GSK SpA. The authors report no other conflicts of interest in this work.

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Introduction

Nontuberculous mycobacteria (NTM) are environmental pathogens with over 190 identified species,¹ primarily affecting individuals with preexisting lung disease or immunodeficiency.² There is a rising trend in incidence of infection and mortality globally, including among younger populations. Among children, the infection may occur with or without pre-existing lung disease.³ Risk factors among adults have been well studied, but there are fewer pediatric studies in this area of study.⁴ Past research has found that immunodeficiency, the developing immune system, and chronic lung disease heighten the risk of NTM infections in the pediatric population.⁵ NTM infections are especially prevalent because of their ability to inhabit common soil and water sources such as water distribution systems, allowing repeated environmental exposures to invade the lungs through bioaerosols.⁵ It is also thought that different species and subspecies of mycobacteria containing genetic differences manifest themselves differently in infection and clinical response.⁶ For example, two of the most common NTM species Mycobacterium avium and Mycobacterium abscessus differ in their infections with the former being characterized by slow growth, greater general prevalence, and weaker biofilm formation,⁷ while the latter is associated with significant morbidity/mortality, is clinically resistant to most antibiotics, and shows greater general immune responses throughout the course of infection.⁸ Infections from different types of these bacteria can vary by geographic location⁵ with Mycobacterium abscessus being commonly observed in East Asia and Mycobacterium avium complex and Mycobacterium kansasii occurring most commonly in many parts of the US. In Europe, Asia, and partially in Australia, increases in latitude generally see higher rates of Mycobacterium avium complex.

NTM pulmonary disease is frequently misdiagnosed as tuberculosis due to similar symptoms, leading to delays in appropriate treatment. One of the most common signs of NTM infection in healthy children is cervical lymphadenitis, but its clinical presentation is indistinguishable from that of cervical lymphadenitis in regular tuberculosis.⁹ Pulmonary infection, while less commonly associated may be more difficult to treat. This is especially problematic in countries with high tuberculosis rates, where NTM testing methods are resource limited.^10–12 Industrialized nations often report higher NTM incidence than tuberculosis, although pediatric prevalence globally is not well studied.^13,14

This study was conducted to investigate pediatric pulmonary NTM infections among the non-cystic fibrosis population. The global incidence of NTM infections is increasing, and more studies are needed to better understand the disease among the pediatric population.¹⁵ Unlike Cystic Fibrosis patients, who are known to have higher susceptibility to pulmonary infections,¹⁶ the risk factors and clinical manifestations in non-cystic fibrosis pediatric population remains poorly understood. This study aims to investigate the epidemiology, clinical comorbid condition, and five year clinical outcomes of non CF pulmonary NTM infections in distinct pediatric age groups. We hypothesize that there are important differences in these key areas among pediatric age groups. This may lead to the identification of characteristics that could guide clinical decision-making and potentially improve patient outcomes.

The study further hypothesizes that: i) BMI percentiles mediate susceptibility to NTM infections in children, ii) common comorbidities are expected to be significant risk factors for pediatric pulmonary NTM infections, iii) pediatric pulmonary NTM may predispose patients to future lung disease.

Methods

The TriNetX Clinical Data Platform

We utilized the TriNetX research platform to select our patient cohorts from a total of 152,714,105 collected, de-identified patient records on the Global Collaborative Network containing 127 health-care organizations from the following 17 countries: United States, Canada, United Kingdom, Germany, France, Italy, Spain, Netherlands, Denmark, Australia, Singapore, Japan, Brazil, Mexico, Israel, South Korea, and Switzerland. TriNetX deidentifies and aggregates electronic health record (EHR) data from health-care systems, primarily drawing from large academic medical institutions across the USA. It organizes diagnoses under specific ICD codes and stores information such as demographics, medications, lab results, procedures, and vital signs. The platform provides a secure, web-based access to patient-level analyses and interpretation. It reports updated population-level data while ensuring Health Insurance Portability and Accountability Act (HIPAA) compliance.

Data Collection and Stratification

From the TriNetX Global Collaborative Network, the pediatric patient population was stratified into four groups: i) 0–2 years, ii) 3–5 years, iii) 6–12 years, and iv) 13–18 years based on age. The inclusion criteria were: i) subjects with pulmonary NTM infection, and ii) ages 0–18 years. The exclusion criteria were: i) Cystic Fibrosis, ii) Tuberculosis, iii) smoking history, iv) cutaneous non-mycobacterial infections, and v) adult patients. The total cohort (0–18 years) consisted of 2,344 NTM cases from a larger population base of over 23 million pediatric patients collected on July 13, 2024. The distribution among the four groups was expressed both numerically and as a percent of patients in each respective age group with NTM.

Data Analysis

Data analysis focused on patient demographics, clinical characteristics, comorbidities, and outcomes of the 2,344 NTM cases, with particular attention to odds ratios and lab values associated with these infections. Descriptive analysis for this data included prevalence, mean values, and standard deviation within the age cohorts. Demographic information included age, sex, ethnicity, and race. Comorbidities were identified in our analysis. Clinical data were collected including mean values for BMI and oxygen saturation.

Statistical analysis was performed to compare the prevalence and outcomes of NTM across the different age groups, and to evaluate the different comorbidities experienced by each age group. Specifically, the six most common five-year outcomes were compared across the cohorts, assessing risk difference, confidence interval, risk ratio, odds ratio, and statistical significance to determine risk levels between pairs of groups. The analysis was conducted through the built-in analytics tools in the TriNetX software where a p value of <0.05 was defined as statistically significant. Our patients were selected using the inclusion and exclusion criteria outlined in Table 1. Descriptive statistics (mean, SD, proportion) were reported for demographics and clinical features. Comparative analysis across age groups was conducted using Chi-square tests for categorical variables and Student’s t-test or ANOVA for continuous variables. To evaluate associations between NTM and clinical outcomes across age groups, we conducted: Logistic regression analysis for binary outcomes to generate odds ratios (OR), Binomial regression to estimate risk ratios (RR) when appropriate. All models were adjusted for key covariates including age, sex, race, and comorbidity burden. Point estimates were reported with 95% CI.

Ethics

The University of California, Riverside IRB determined that the current study was exempt from further ethics review as it did not fit under the federal definition of human subjects research [DHHS 45 CFR46.102(e), 46.102(l)] or clinical investigation [FDA 21 CFR 50.3(c), 56.102(c)].

Results

Demographics

The demographic data provided insight into the prevalence and distribution of pediatric pulmonary NTM infections among the age cohorts, and with respect to sex, race and ethnicity. The study cohort comprised 2,344 cases stratified across four age groups: 0–2 years, 3–5 years, 6–12 years, and 13–18 years. The majority of NTM cases were observed in the 6–12 year age group at 1074 (734/100,000), followed closely by the 13–18 year age group at 760 (848/100,000). The 3–5 year age group had 401 patients (1261/100,000) and the 0–2 group had 109 patients (689/100,000) (Table 2). There were gender differences in the prevalence of pediatric pulmonary NTM lung infections (Table 3). There was a higher mean prevalence of NTM infections amongfemales compared to males 53.31% vs 46.29% among all age groups. There was no identified gender for 4.17% of the cohort. The majority of the cohort was identified as white 57.8%, followed by Black/African American, 8.88%, Asian, 4.49%, Native American, 2.83%, Native Hawaiian, 1.19%, another race, 8.52%, and unspecified race 21.6%. BMI percentiles were above the 50th percentile for all age groups, and this was statistically significant (p < 0.05) (Table 4).

Table 2 Age Demographics of Our Study Cohort, Including the Number of Patients in Each Age Cohort

Table 3 Sex Demographics of Our Study Cohort, Stratified by Age

Table 4 BMI Percentiles of Each Age Cohort

Laboratory Findings

The data indicated a varying prevalence of NTM infections across the age groups, with the highest prevalence observed in children aged 6–12 years at 1,074 cases (0.007339%). Lab values, particularly those related to immune function, revealed a trend towards higher inflammatory markers among older children, possibly reflecting a more robust immune response or delayed diagnosis. There was an elevated mean white blood cell count in the 13–18 age group at 18.5×10³/μL compared to the expected range of 4.0×10³/μL to 11.0×10³/μL (Table 5). Similarly, CRP mean levels for this age group were significantly above the expected value of 1 mg/L at 26.8 mg/L. In the 3–5 year and 13–18 year cohorts, basophil levels were above the expected 0–1% at 2.68% and 1.83%, respectively. Ferritin levels were higher in the 6–12 year and 13–18 year groups at 546 ng/mL and 1758 ng/mL, respectively, compared to the normal range of 10–200 ng/mL. Among younger children, there were lower levels of inflammatory markers, which may suggest an underdeveloped immune response or early-stage infection.

Table 5 Comparison of Selected Inflammatory Markers by Age Cohort

Comorbid Conditions

Comorbidities such as acute pharyngitis, pneumonia, asthma, malignancy, and immunodeficiency were identified. (Table 6 and Figure 1). The most common comorbidity among the groups was acute pharyngitis in the 13–18 age group at 30% of the cohort. There was a higher burden of NTM infections among the older pediatric group, ages 13 to 18 years. This group also had the highest proportion of each comorbidity: 18% pneumonia, 22% asthma, 12% malignancy, and 11% immunodeficiency. The overall proportion of individuals with comorbidities was lower in the 6–12 year age group, still with acute pharyngitis leading at 19%, pneumonia at 12%, asthma at 13%, malignancy at 6%, and immunodeficiency at 7%. The 3–5 year old cohort had the following comorbid conditions: 11% acute pharyngitis, 7% pneumonia, 11% asthma, 5% malignancy, and 4% immunodeficiency. The 0–2 age groups saw a notable increase in acute pharyngitis, pneumonia, and malignancy at 18%, 9%, and 13%, respectively. The age 0–2 year old group had the highest percent of malignancy. Asthma and immunodeficiency data was not recorded for this age group likely due to reduced diagnosis of these issues at such ages. The most prevalent comorbidity was acute pharyngitis at 78% across all age groups, and no other comorbidity rose above 46%.

Table 6 Comparison of the Top Five Most Common Comorbidities by Age Cohort

Figure 1 The five most common comorbidities associated with NTM infection as a percent of each age cohort. *indicates P < 0.05.

Discussion

The findings of this study demonstrates an age-based differential presentation of Pulmonary NTM infection among the cohort studied. This study highlights the need for age-specific approaches to the diagnosis and management of pediatric pulmonary NTM infections. Our study adds novel data regarding the global prevalence of NTM pulmonary infections among a Pediatric population. The varying prevalence and outcomes across age groups suggest that different factors, such as immune development and environmental exposure, play significant roles in the susceptibility to and progression of these infections. It is important to understand the mechanisms of these differences. Further studies will be completed to better understand the age based differential of disease prevalence.¹⁷ The top five comorbidities we identified were acute pharyngitis, unspecified pneumonia, asthma, malignancy and immunodeficiency. The presence of these comorbidities also correlated with a higher burden of NTM infection in the older pediatric groups, suggesting that these children might have prolonged exposure to risk factors or delayed diagnosis.¹⁸ This increased susceptibility is thought to be related to damaged respiratory mucosa, promoting NTM attachment and infection.¹⁹ Our observed comorbidity of asthma drew our attention to the fact that children with underlying chronic lung diseases may have a higher likelihood of severe outcomes, including prolonged hospitalizations and the need for intensive care.²⁰ There was a higher odds ratio (OR) of developing more severe lung disease, such as pneumonia, pulmonary fibrosis, lung abscess, bronchiectasis, interstitial lung disease upon NTM infection among 0–2 year olds compared to older age groups (Table 7). This is also supported by several reports of some of these outcomes occurring in various age groups.^21,22 Immunodeficiency, whether congenital or acquired, tends to be associated with a more complicated clinical course and higher mortality rates, and we also observed it as a comorbidity.²³ Specifically, this immunosuppression allows for extrapulmonary NTM disease to develop and spread by escaping the body’s immune cells and entering the lymphatic system and bloodstream.²⁴ The finding of lung or mediastinal abscess as a five year outcome heightens our clinical concern among this cohort, especially when considering clinical uncertainty in treatment of NTM.²⁵ The analysis of racial and ethnic data was limited in this study due to potential incomplete availability of documentation of some demographics in the electronic health records, which may have introduced bias in the interpretation of these variables. However, our demographic data supports our initial hypothesis that even a mildly elevated BMI may increase susceptibility for pediatric NTM.²⁶ While current literature supports lower BMI as a significant risk factor for NTM infection,²⁷ one possible explanation is the susceptibility of the host in states of malnutrition. Individuals with higher BMI are more likely to be diagnosed with chronic inflammatory or autoimmune conditions²⁸ which are commonly treated using immunosuppressive corticosteroids,²⁹ potentially increasing the risk for NTM infection.^30,31 In addition to BMI, other physical conditions and comorbidities, particularly chronic lung diseases and immunodeficiency, underscore the need for vigilant screening and management in at-risk populations. The significant odds ratios associated with future 5-year outcomes in older children (Table 7) suggest that more aggressive diagnostic and therapeutic strategies may be warranted in these age groups.³² Our findings show that the majority of NTM cases were observed in the 6–12 year age group and the highest percent of cases were observed in the 3–5 year age group. This finding shows that school-aged children and adolescents are more likely to be diagnosed with NTM infections, potentially due to increased exposure to environmental reservoirs of NTM, such as water and soil, and higher rates of outdoor activities compared to toddlers.³³ Abnormal inflammatory marker values among the 13–18 age group were also a notable age cohort-based finding. Particularly, the elevated white blood cell count, ferritin levels, and CRP in older children suggest a more pronounced inflammatory response in the adolescent age group with NTM infections. These findings are distinct from the data that has been found from a previous study done in Wisconsin. In the Wisconsin study, the isolates were based on statewide data, rather than a global database, and this study included non Pulmonary infections. Our study is the first to our knowledge to analyze a global database, with a focus on Pediatric non CF Pulmonary infections. The data in the Wisconsin study included Cystic Fibrosis patients. Since CF is a known risk factor for Pulmonary NTM, our study design focused on non CF patients.³² From our demographic data, we also found that there were significant differences in the gender of infected patients. This trend aligns with existing adult literature that suggests females may have a higher susceptibility to pulmonary infections due to differences in immune response, hormonal influences, or behavioral factors, such as a greater likelihood of engaging in activities that increase exposure to NTM.³⁴ There were statistically significant differences in NTM infection rates among different racial groups, which has to our knowledge not been studied utilizing a global EHR database. The available data from diverse populations shows that certain racial and ethnic groups might be disproportionately affected by NTM infections, potentially due to disparities in healthcare access, environmental exposures, or genetic predispositions.³⁵ This finding highlights the need for more comprehensive data collection and medical record documentation in future studies to better understand the role of race and ethnicity in the epidemiology of pediatric pulmonary NTM infections.

Table 7 Pulmonary Health Outcomes by Age Cohort

Limitations

This study has several limitations, including its retrospective nature and reliance on data from the TriNetX platform, which may introduce selection bias. Additionally, the reliance on electronic health record data may result in incomplete or inaccurate documentation of clinical characteristics and outcomes. The platform’s retrospective nature may introduce selection bias, affecting the generalizability of the results. Additionally, differences in cohort sizes can impact comparison results. TriNetX also anonymizes data by replacing counts of 1–10 with “10” to protect patient privacy, which limits the statistical analysis of rare outcomes. Furthermore, patients who move to non-TriNetX facilities are lost and not included in the outcome comparisons. There may also be comorbidities that were documented in patients’ records in institutions not participating in TriNetX. The study also did not account for the potential impact of socio-economic factors, geographic location, or variations in healthcare access, which could influence the prevalence and outcomes of NTM infections.^36,37 Despite these limitations, our study has provided an extensive analysis of global data in this area of study, utilizing a novel EHR based database.^38,39 Additionally, more advocacy is needed to ensure that NTM is properly documented, species-wise in the EHR to ensure that future epidemiological studies can be done effectively.

Conclusions

Our study uniquely provides an analysis of global prevalence of non CF Pediatric Pulmonary NTM infections. The study contributes to current knowledge in the field and identifies selected future five year outcomes. We also compared the associated risk for the specific age cohorts studied. This study thus adds to current understanding of the incidence and characteristics of Pediatric NTM non CF pulmonary disease. Future studies to develop treatment strategies and age based considerations are therefore important in the management of Pediatric pulmonary NTM infection.

Disclosure

The authors report no conflicts of interest in this work.

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