As the earning power of women keeps growing, more are seeking financial protection before they get married. ‘It’s a massive generational shift,’ says one legal expert.
Travis Kelce, left, and Taylor Swift are engaged – and a prenup is pretty much a given. It’s becoming the norm for more Americans when they get married, particularly millennial women.
Should Taylor Swift seek a prenuptial agreement, she’ll have plenty of company among American women.
The pop megastar announced her engagement earlier this week to pro football player Travis Kelce, leading to rampant speculation that she might want such an arrangement to safeguard her estimated $1.6 billion net worth. But legal experts say it really doesn’t matter whether you have billions of dollars or pennies to your name – you should consider a prenup in any case to ensure some financial protection should your marriage go awry.
And they say many women, especially of the millennial generation, are indeed heeding that message, given their growing economic power. It’s the flipping of a decades-old playbook in which men typically had more money – or greater earning potential – and were the ones who insisted upon the prenup.
“It’s a massive generational shift,” said Libby Leffler, founder and chief executive of First, an online legal platform that helps people prepare prenups.
Leffler notes that women constitute 50% of First’s clients for prenups in opposite-sex marriages. Similarly, HelloPrenup, another online platform, says 52% of its clients are women.
That “tells us that women are no longer waiting for their partners to bring up the topic – they’re taking the lead,” said Julia Rodgers, HelloPrenup’s founder and CEO.
But a different set of numbers tells us what’s behind the trend, experts note – ones that speak to women’s increasing financial might. Consider that 45% of American women are now considered the household breadwinners, be they single working mothers or married mothers earning at least half of their family’s total income, according to a recent analysis from the Center for American Progress. By contrast, in 1967, that figure was 14%.
Another study, from the Pew Research Center, noted that over the past half-century, the share of women who earn as much as or significantly more than their husband has about tripled.
Added to all this is simply the fact that prenups are becoming more common, regardless of whether they’re initiated by men or women. A 2022 Harris Poll found that 15% of those who have been married or are presently engaged have signed a prenup. In 2020, that figure was merely 3%.
Monica Mazzei, an attorney who chairs the family-law group for Buchalter, a national law firm, says prenups used to have a stigma attached to them – as if they signaled that one person in the marriage didn’t truly love the other. But that’s no longer the case with the younger generation, which has become accustomed to hearing about celebrity prenups, she adds.
“I call it the Kardashian effect,” said Mazzei – referring to Kim Kardashian, the social-media icon who’s not been shy in addressing the importance of a prenup.
Leah Weinberg, a New York City resident, is among those who saw the value in a prenup. She signed one before she got married to her husband in 2012. She says it’s not about how much you love someone, but rather how practical you want to be, given the reality that some marriages naturally end in divorce.
“I think people are smart just to plan for the future,” she said.
As for Swift and Kelce, there’s no word as to what they will do. But Michele Locke, a family-law attorney based in Austin, Texas, says that despite Swift’s riches, the singer may not need to pursue a prenup. That’s because Swift has likely worked with a team of lawyers over the years to secure her assets.
“Women in Taylor’s position have a ton of financial mechanisms in place,” Locke said.
-Charles Passy
This content was created by MarketWatch, which is operated by Dow Jones & Co. MarketWatch is published independently from Dow Jones Newswires and The Wall Street Journal.
Twenty years after Hurricane Katrina ravaged his home town of New Orleans, Jon Batiste has released a new song imploring people to take action against climate change “by raising your voice, and insisting, and voting the right people into office”.
“As an artist, you have to make a statement,” the global star said in an interview on Tuesday with the international media collaboration Covering Climate Now. “You got to bring people together. People power is the way that you can change things in the world.”
“It’s a warning, set to a dance beat,” Batiste said about the song, Petrichor, which appears on his new album Big Money. The Oscar- and multiple Grammy-winning composer and his band performed Petrichor live during Tuesday’s interview; that performance can be heard here [insert VEVO link].
The word “petrichor” refers to “the scent of the earth after the rain”, Batiste said, “when there’s been warm, dry soil for a long time, and then things come back into balance. And right now, we’re out of balance … the natural life support systems of the planet are under threat.”
With a refrain that repeatedly declares “they burning the planet down,” Petrichor does not sugarcoat the dangers of climate change, yet Batiste remains optimistic. “When you make a song, you want to inspire people, but you also want to let them know what they can do,” he said. “And the things that we can do [are] really very simple. It’s clean energy technology, right now, that we can switch to. We can make the world be powered by things that don’t destroy the planet.
“There’s a blanket of pollution around the Earth,” Batiste added, referring to the planet-warming gases released by burning fossil fuels such as oil, gas and coal and by cutting down forests. “The summers feel hot, everything is hot, the weather patterns are shifting. Nobody wants that. And we know what the solution is. There’s an overwhelming majority of people that believe in clean energy … and switching to these new technologies.”
The Guardian and other Covering Climate Now partners earlier this year launched the 89 Percent Project, reporting that 80 to 89% of the world’s people want their governments to take stronger climate action, according to numerous scientific studies. Batiste confirmed that he is part of that 89% climate majority – as is his mother, Katherine Batiste, who did environmental work for the state of Louisiana for most of Jon’s childhood and sat next to him throughout the Covering Climate Now interview.
“We believe in science,” Katherine Batiste said.
“There you go,” Jon said, smiling. “You heard it.”
Many people know that Jon Batiste comes from a storied musical family in New Orleans – his uncle Lionel Batiste was a mainstay of the Treme Brass Band, and his cousin Russell Batiste Jr was a celebrated jazz drummer – but Jon also comes from a family of activists. His mother’s father, David Gauthier, a leader of the Louisiana Postal Workers Union, supported the sanitation workers’ strike in 1968 that drew Martin Luther King Jr to Memphis, where King was assassinated. Among other causes, Jon has been active in the Black Lives Matter protests, a stance his mother saw as a continuation of her father’s legacy. Her dad “believed in standing up for what’s right”, said Katherine Batiste, “and that kind of rolled over on me some, and I passed it on to Jon.”
Jon Batiste and his band perform during a Black Lives Matter protest in New York City, in June 2020. Photograph: Lev Radin/Pacific Press/REX/Shutterstock
“I was raised by incredible people,” said Jon, who spent seven years as bandleader on The Late Show With Stephen Colbert up to 2022. “I saw my grandfather, I saw my father, I saw all these people who were in my immediate environment doing the work and not getting down about it. The key is to keep it going, not to look at yourself and pity the situation, but to find a way to do something with what you have and where you are.”
The Petrichor song illustrates the larger themes of his Big Money album, he added, because the pursuit of money at all costs is putting the climate at risk. And not only the climate. “We’re in the wealthiest time in human history,” he said. “There’s no shortage of resources. Yet there are [people] who don’t have clean water, clean food, basic healthcare. And it’s disproportionately affecting those in low-income communities, people of color. [When] the majority of the wealth is in the hands of only a small percentage of people, it will inevitably corrupt the policies that can change these things. That’s who the song is really geared toward. There’s a pollution blanket around the planet, but it’s the result of a pollution blanket around our souls.
“It’s fitting that we’re here in this place of worship,” Batiste said about the setting of the interview – New York’s Middle church, whose double-meaning motto is “Just love” – because “as Pope Francis said, the Earth is our common home, a sacred planet, and [we need to live] up to our responsibility as stewards of the planet.”
When Hurricane Katrina struck New Orleans on 29 August 2005, the storm and the breach of protective levees put 80% of the city underwater, killed at least 1,800 people and drove countless others to leave town, never to return. While outsiders experienced the storm on television, as a media event, the Batiste family lived it. Jon, with his mother, father, sister and grandmother, evacuated to Texas before the storm hit. But the family home where Katherine Batiste grew up, in the Carrolton neighborhood of New Orleans was destroyed, she said. “All my sisters, brothers, my family, their homes were destroyed … They lost everything … It was devastating.”
Devastation caused by high winds and heavy flooding in the greater New Orleans area following Hurricane Katrina, on 30 August 2005. Photograph: Vincent Laforet/EPA
“New Orleans, to me, is the soul of America,” Jon Batiste said, adding thatthe city was “a warning” that climate-driven disasters “can happen anywhere, and there’s many places where this has happened”.
The role of the artist in the face of such danger and injustice is to “point people to the solutions with rhythm and poetry”, Batiste said. “It’s like [the jazz drummer] Art Blakey said, ‘music can wash away the dust of everyday life,’ and make somebody’s apathy turn into care into action. As an artist, you can connect right to the person – still also entertaining them, but uplifting them and their voice, so that then they know, ‘Oh, I have something to say, and it’s meaningful and it’s powerful. I’m going to sing it at the concert, and I’m going to leave here and it’s going to be in my heart, and I’m going to go into the voting booth and push it, I’m going to go into my communities and push it, and I’m going to live my life in ways that are aligned with it.’ And that is infectious. It moves to the next person, and the next person, the next person, and soon it’s our reality.”
Although the version of Petrichor on the Big Money album is a sort of talking blues foot-tapper that lasts 2 minutes and 38 seconds, the version Batiste and his band played a week earlier in New York’s Central Park was a raucous 11 minutes that had the standing-room crowd dancing with joy. Batiste, who has just begun a 50-date North American tour, said he planned to release a live album that will feature a similarly up-tempo version of Petrichor drawn from upcoming performances at the Grand Ole Opry in Nashville and the Red Rocks Amphitheater in Colorado.
“It’s important when you’re changing the world to have a good time while you’re doing it,” he said. “I really want people to keep dancing and stay optimistic – but know that we gotta, we gotta, move.”
This article is part of the 89 Percent Project of the international media collaboration Covering Climate Now.
Scientists in China have unveiled a supercomputer built on brain-like architecture — specifically, that of a monkey.
Called Darwin Monkey or “Wukong”, the system features over 2 billion artificial neurons and more than 100 billion synapses, putting it roughly on par with the neural structure of a macaque.
The researchers hope it will serve as a simulation tool for neuroscientists while also providing a stepping stone toward artificial general intelligence (AGI) — an artificial intelligence (AI) system that possesses human-like intelligence and reasoning.
Br(AI)n power
Unlike traditional artificial neural networks, which follow classical computing principles and process data via continuously changing binary values, neuromorphic systems like Darwin Monkey are driven by spiking neural networks (SNNs).
SNNs mimic how signals are transmitted between neurons in the brains of mammals, responding to electrical signals to process and transmit data through on-and-off bursts (or spikes) of activity.
Related: China develops new light-based chiplet that could power artificial general intelligence — where AI is smarter than humans
A biological neuron fires an electrical pulse when the signals it receives from other neurons reach a level strong enough to trigger a response. Artificial neurons in SNNs mimic this mechanism, firing only when they’ve built up enough electrical input.
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Where software-based neural networks are a collection of machine learning algorithms arranged to emulate the human brain, SNNs physically replicate the way information moves between biological neurons. This configuration allows SNNs to process data in parallel, potentially making them more powerful than conventional supercomputer architectures.
It may also be more energy efficient: artificial neurons enter a brief rest period after each spike, during which they can’t respond to new inputs. This limits how often they fire, helping to reduce overall power consumption.
Researchers say Darwin Monkey consumes just 2,000 watts of power — roughly the equivalent of an electric kettle or hairdryer — despite being powered by 960 Darwin III neuromorphic chips, each of which supports up to 2.35 million spiking neurons.
Other neuromorphic computers
The previous record-holder in neuromorphic computing was Intel’s Hala Point system, which comprises 1.15 billion artificial neurons and 128 billion artificial synapses distributed over 140,544 processing cores.
Intel claims its system is capable of performing 20 quadrillion operations per second — or 20 petaops. But as there are very few neuromorphic computers currently in existence, and as they process data differently from supercomputers, it’s difficult to compare them on a like-for-like basis.
In a statement, translated into English using Google Translate, the team behind Darwin Monkey said the platform had already demonstrated its capabilities in cognitive tasks such as logical reasoning, content generation and mathematical problem-solving, using an AI model developed by Chinese AI startup DeepSeek.
The system is also being used to simulate the brains of animals with varying levels of neural complexity, including zebrafish and mice, as part of broader efforts to support brain science research.
Darwin Monkey was designed by researchers from Zhejiang University and Zhejiang Lab, a research institute jointly established by the Zhejiang provincial government and Alibaba Group, a Chinese technology conglomerate.
It follows the launch of Darwin Mouse (“Mickey”) in September 2020, which contains 120 million artificial neurons — the equivalent of a mouse’s brain.
Percutaneous coronary intervention (PCI), which involves placing stents or balloons in the closed or obstructed coronary arteries, is a lifesaving treatment for patients with acute myocardial infarction. However, major adverse cardiovascular events, including mortality, myocardial reinfarction, and ischaemia-driven target vessel revascularization remain problems.1
Traditional factors such as diabetes mellitus, hypertension disease, hyperlipidemia and smoking partially contribute to poor prognosis. Furthermore, psychological factors such as depression and anxiety are well-established risk factors for the occurrence of adverse events.2 In 2008, the American Heart Association issued an advisory to screen patients with coronary artery diseases for depression.3 In particular, PCI patients who had undergone surgery were more likely to experience depression and anxiety symptoms. After PCI, approximately 23.5–66.5% of patients develop anxiety4,5, and 20–30% develop depression.2,6 The presence of depression and anxiety symptoms was associated with 2.70-fold and 2.56-fold increases in the risk of adverse events, respectively.6 Hence, it is critical to identify individuals at risk of depression and anxiety symptoms early and implement interventions in a timely manner. Currently, screening for post-PCI depression and anxiety symptoms mainly relies on various assessment scales, given the subjective nature of assessment scales, there was a need for more objective predictive indicators and models to be explored.
Ranucci et al were the first to develop the age, creatinine, and ejection fraction (ACEF) score, which is based on the law of parsimony, to assess mortality risk in elective cardiac operations.7 Despite having only 3 variables, the ACEF score has comparable predictive power to complex scoring models.8 The ACEF score has since been validated in a variety of other clinical practices and populations. Lee et al9 reported that the ACEF was a good predictor of 1-year post-PCI mortality in patients with acute myocardial infarction. However, researches of the ACEF score have been restricted to the prognostic assessment of certain cardiac diseases. There have been no studies applying the ACEF score to the prediction of post-PCI depression and anxiety symptoms. Previous studies have shown that age and left ventricular ejection fraction were associated with post-PCI depressive and anxiety symptoms.10,11 Accordingly, we proposed the hypothesis that ACEF score would have predictive value of post-PCI depression and anxiety symptoms.
Materials and Methods
Participants
In this cross-sectional study, we prospectively enrolled 265 consecutive patients between December 2023 and April 2024 at the Department of Cardiology, the Fifth Affiliated Hospital of Xinjiang Medical University. Patients aged 18 years or older who were diagnosed with acute coronary syndrome and underwent emergency or selective PCI were included. The exclusion criteria were as follows: (1) had a history of depression disorders, anxiety disorders or other mental illnesses, such as schizophrenia, obsessive-compulsive disorder, substance abuse or serious suicidal tendencies; (2) disagreed with the Hospital Anxiety and Depression Scale (HADS); (3) were unable to communicate in Mandarin; and (4) had incomplete demographic characteristics and clinical information. Informed consent was obtained from each patient and the study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the Fifth Affiliated Hospital of Xinjiang Medical University ethics committee (XYDWFYLSk-2024-52).
Measures
Demographics
The following data were collected through the medical records, including age, sex, marital status, educational level, medical history, number of stents, culprit vessel, emergency or elective PCI, personal history of smoking, and postoperative medications used for at least 1 week continuously: aspirin, clopidogrel, ticagrelor, statins, β receptor blockers, angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs) and diuretics.
Laboratory Analyses
Peripheral venous blood samples were collected before PCI. The concentrations of serum creatinine were measured and recorded. As for left ventricular ejection fraction, patients received a conventional 2-dimensional echocardiography examination before revascularization. Echocardiography was performed and measurements included at least 3 consecutive beats for patients with sinus rhythm. The modified biplane Simpson’s rule was applied to calculate.
Depression and Anxiety
After PCI, patients were asked to complete the HADS before they were discharged. As a self-report questionnaire, the HADS comprises two subscales (ie, the HADS-D and HADS-A), covering 14 items in total, and each subscale comprises seven multiple-choice items, with a score ranging from 0 to 21 for both subscales. A cut-off score of ≥8 points on each subscale is considered to indicate clinically relevant levels of depression and anxiety symptoms. The internal consistency of the HADS has been demonstrated previously, with a Cronbach’s alpha of 0.83 for the anxiety subscale (HADS-A) and 0.82 for the depression subscale (HADS-D).12
ACEF Score Calculation
The ACEF score was calculated: ACEF = age/left ventricle ejection fraction +1 (if creatinine was >2.0 mg/dL).7
Covariables
In this study, we controlled for variables that, according to previous studies, might bias the results: age, sex, diabetes mellitus status, hypertension status and smoking status.
Statistical Analysis
SPSS (V.26.0) and R software (V.4.4.2) were used for the statistical analysis of the collected data. All tests for statistical significance were two-sided, and P< 0.05 was considered to indicate statistical significance.
First, according to the normality of the distribution assessed by the Shapiro‒Wilk test, continuous variables are described as the mean ± standard deviation (SD) or the median and interquartile range. Categorical variables are described as frequencies (percentages). One-way analysis of variance (ANOVA) or the Kruskal–Wallis was used to compare continuous variables and Pearson’s chi-square test and Fisher’s exact test was used to compare categorical variables among groups, Benjamini–Hochberg correction was used for multiple comparisons.
Second, multivariable logistic regression analyses were performed to assess the relationship between ACEF score categorized into quartile groups and presence of anxiety, depression symptoms. Meanwhile, linear trend tests across quartiles were examined using ordinal values in separate models. Linear regression analyses and smooth curves fitting (based on the penalized spline method) were utilized to examine the relationships of ACEF score with anxiety, depression symptoms. The models were adjusted for variables with P< 0.05 in the univariate analysis and conventional confounding factors.
Third, the discrimination of the ACEF score for post-PCI anxiety, depression, comorbid anxiety and depression symptoms was assessed by receiver operating characteristic (ROC) curves.
Results
A total of 265 patients who underwent PCI were included in this study, and 43 of these patients were excluded, including 2 patients who could not communicate in Mandarin, 6 patients who refused to complete the HADS, 35 patients who were discharged from the hospital before the investigation. After exclusions, 222 patients were included in the final analysis (Figure 1). The sample included 183 (82.4%) males and 39 (17.6%) females, with an average age of 60.36±11.07 years. Overall, 123 (55.4%) underwent emergency PCI within 24 hours of symptom onset, while the remaining 99 (44.6%) patients received elective PCI. Only 3(1.4%) patients’ creatinine >2.0 mg/dL, 16 (7.2%) patients were diagnosed with post-PCI anxiety symptoms, 33 (14.9%) patients were diagnosed with post-PCI depression symptoms and 37 (16.7%) patients were diagnosed with post-PCI comorbid anxiety and depression symptoms.
Figure 1 Flow chart of the study.
Descriptive Analysis
Table 1 summarizes the demographic characteristics of participants in the four groups, all P value were adjusted by Benjamini–Hochberg correction. It showed statistical significance (all P< 0.05) among groups in oral aspirin, oral diuretics, LVEF and ACEF score. There were no statistically significant differences in the remaining variables.
Table 1 The Demographic Characteristics of Patients According to Anxiety and Depression Symptoms
In Table 2, the patients were divided into four subgroups according to the quartiles of ACEF score at admission: Quartile 1 (n = 56):0.515–0.923, Quartile 2 (n = 55): 0.923–1.116, Quartile 3 (n = 56): 1.116–1.259, Quartile 4 (n = 55): 1.259–3.160. After adjusted by Benjamini–Hochberg correction, age, sex, education levels, smoking, oral aspirin, oral diuretics, LVEF, ACEF score among the patients with different quartiles were statistical significantly different (all P < 0.05). Other characteristics had no statistically significant differences according to the quartiles.
Table 2 Baseline Characteristics of Post-PCI Patients in ACEF Quartiles
In addition, we compared the proportions of post-PCI anxiety, depression and comorbid anxiety and depression symptoms among patients stratified by ACEF quartiles. The ratios of post-PCI anxiety, depression and comorbid anxiety and depression symptoms increased with ascending quartiles of ACEF score (P for trend <0.001). The numbers of patients with post-PCI anxiety symptoms were 2(3.6%) in Q1, 3(5.5%) in Q2, 5(9.1%) in Q3 and 6(10.7%) in Q4. Numbers of patients with post-PCI depression symptoms were 6(10.7%) in Q1, 8(14.5%) in Q2, 8(14.5%) in Q3 and 11 (19.6%) in Q4. Post-PCI comorbid anxiety and depression symptoms were 4(7.1%) in Q1, 3(5.5%) in Q2, 8(14.5%) in Q3 and 22 (39.3%) in Q4 (Figure 2).
Figure 2 The proportion of post-PCI anxiety, depression and comorbid anxiety and depression symptoms for the quartiles of ACEF score.
Logistic Regression Between ACEF Score Levels and Post-PCI Anxiety, Depression Symptoms
As shown in Table 3, elevated ACEF score levels were dose-dependently associated with higher risks of post-PCI anxiety and depression symptoms across progressively adjusted models. In the fully adjusted Model 3, patients in the highest ACEF quartile (Q4) had 7.7-fold increased odds of anxiety symptoms (OR = 7.70; 95% CI: 1.61–36.77) and 6.2-fold increased odds of depression symptoms (OR = 6.17; 95% CI: 1.61–28.03) compared to the lowest quartile (Q1). Statistically significant positive trends were observed for both outcomes (Pfor trend < 0.008 for anxiety symptoms and <0.009 for depression symptoms).
Table 3 Multivariate Adjusted Odds Ratios for the Association Between ACEF Levels and Post-PCI Anxiety and Depression Symptoms
Linear Regression Between ACEF Score and Post-PCI Anxiety, Depression Score
In Table 4, higher ACEF scores were statistically significant associated with increased anxiety score and depression score after PCI. In fully adjusted models (Model 3), each 1-unit elevation in the ACEF score corresponded to a 3.50-point increase in anxiety score (95% CI: 1.36–5.64; P = 0.001) and a 3.45-point increase in depression score (95% CI: 0.93–5.99; P = 0.008). These associations remained statistically robust across progressively adjusted models, indicating a linear relationship between ACEF score and psychological symptom burden.
Table 4 Multivariate Linear Analysis for the Association Among ACEF Score and Post-PCI Anxiety, Depression Score
From a non-linear perspective, the positive correlations between ACEF score and anxiety score and depression score were further corroborated by smooth curve fitting (based on the penalized spline method) (Figure 3).
Figure 3 The fitted smooth curve between ACEF score, anxiety score and depression score.
ROC Curve of ACEF Score in Predicting Post-PCI Anxiety, Depression and Comorbid Anxiety and Depression Symptoms
The ROC curve analysis demonstrated that ACEF score presented ideal accuracy as predictors of in-hospital post-PCI anxiety, depression and comorbid anxiety and depression symptoms (Figure 4). For anxiety symptoms, the AUC of ACEF score was 0.666 (95% CI: 0.578–0.753, P < 0.001). For depression symptoms, the AUC of ACEF score was 0.662, (95% CI: 0.584–0.740, P < 0.001) and for comorbid anxiety and depression symptoms, it was 0.701 (95% CI: 0.608–0.794, P < 0.001) (Table 5).
Table 5 Characteristics of ROC Curve
Figure 4 ROC curves for post-PCI anxiety, depression and comorbid anxiety and depression symptoms.
Discussion
This work, originally reporting on the association between ACEF score and post-PCI anxiety and depression symptoms, has the following findings: a) the incidences of post-PCI anxiety, depression and comorbid anxiety and depression symptoms were 16 (7.2%), 33 (14.9%) and 37 (16.7%); b) higher levels of ACEF score were significantly related to post-PCI anxiety and depression symptoms even adjusting for potential confounders; c) ACEF score has an ideal accuracy in predicting the anxiety and depression symptoms of patients after PCI.
Our study revealed that the ACEF score could predict the occurrence of anxiety and depression symptoms. Previously, the ACEF score was mainly used for risk assessment in cardiac patients. To our knowledge, this is the first study to explore the associations between ACEF scores and the risk of experiencing post-PCI anxiety and depression symptoms.
The underlying mechanism between the ACEF score and post-PCI depression and anxiety symptoms might involve the following aspects. First, regarding age, in our study, the participants in the anxiety, depression and comorbid anxiety and depression symptoms groups were older, and this age-related vulnerability to depression and anxiety might be explained by dysfunction of the hypothalamic‒pituitary‒adrenal (HPA) axis. The HPA axis is an essential modulator of endocrine and behavioural responses to stress. Thus, malfunction of the HPA axis, mainly characterized by the abnormal secretion of glucocorticoids (GCs), could lead to the development of a variety of stress-dependent and age-related diseases. With ageing, the amplitude of the diurnal rhythmic activity of the HPA axis dampens,13,14 and evening and night cortisol (CORT) secretion might increase in humans and primates.13,15 The activities of the HPA axis both under basal conditions and in response to stress exposure are dependent on circadian rhythms.16 Thus, numerous publications have demonstrated that circadian dysregulation increases the risk of various ageing-related diseases, especially anxiety, depression and cardiovascular diseases.13,17,18 The research by Goncharova et al19 used young adult and aged female rhesus monkeys as models to characterize the HPA axis in response to acute stress exposure under chronic constant light conditions, and a significant decrease in the increase in CORT levels in response to acute stress exposure was observed, with an age-dependent mechanism. In addition, CORT levels were also associated with cardiovascular risk. Degroote et al20 reported that reductions in total daytime CORT production independently predict increased cardiovascular risk, as evidenced by increased levels of biomarkers of atherothrombotic risk. Therefore, in light of the above mechanisms and experiments, it could be speculated that older patients with coronary artery diseases are more likely to have mental disorders.
Second, the relationships between creatinine and depression and anxiety are controversial. Previous studies have confirmed that depression and anxiety are linked to metabolic abnormalities of peripheral body systems, such as lipid, fatty acid and fluid balance abnormalities.21,22 Bernhardsen et al23 reported on prospective data from the Finnish Depression and Metabolic Syndrome in Adults (FDMSA) Study comparing serum metabolic biomarkers in depression and control groups and revealed that creatinine was positively correlated with subsequent depression symptoms. The West China Health and Ageing Trend (WCHAT) study, a large multiethnic sample, divided participants into four groups according to comorbid anxiety and depression, anxiety only, depression only and neither, and significantly differed in creatinine compared with the healthy group.24 A meta-analysis of 23 distinctly distributed metabolites from 46 studies in individuals with major depressive disorder (MDD) and controls suggested that MDD patients had lower creatinine levels.25 Rather, another study based on data from the Korea National Health and Nutrition Examination Survey demonstrated that creatinine levels were greater in females in the depression group.26 However, in other metabolomic profile studies, no associations existed,27,28 which is in accordance with this study. In our study, the creatinine component was rarely triggered (>2.0 mg/dL in only 1.4%), making it a non-contributing factor in most cases. We further added a linear regression analysis comparing the performance of the full ACEF score versus a modified score excluding creatinine. In the fully adjusted model, modified ACEF score outperformed the full ACEF score (Supplement 2). But its inclusion in ACEF retains clinical relevance for following reasons: Even subthreshold creatinine values may reflect early renal dysfunction, which synergizes with age and LVEF to amplify cardiovascular risk. In populations with higher renal impairment prevalence (eg, advanced heart failure), creatinine’s contribution to ACEF may be more pronounced. Future validation in cohorts with broader renal function profiles to dissect the relative contributions of ACEF components was needed.
Third, in terms of LVEF, Van Melle et al11 assessed 1989 patients from the Myocardial Infarction and Depression-Intervention Trial (MIND-IT) and demonstrated that there was a significant relationship between LV dysfunction and depression symptoms, both during hospitalization and at 3, 6, 9, and 12 months of follow-up in post-MI patients (ie, the lower the LVEF was, the greater the proportion of depression symptoms). Frasure-Smith et al29 enrolled 896 patients and dichotomized the LVEF with a cut-off of 35%, showing a marked association between LVEF and depression scores. A meta-analysis of 10,175 MI patients reached the same conclusion, but such a correlation existed only in male patients.30 However, in contrast to the above large-sample studies, statistically significant differences were observed among the 222 patients in this study, which might be explained by the fact that the study explored the state of depression and anxiety symptoms during hospitalization and that the patients might still be in a state of acute stress.
Overall, it is reasonable to believe that the ACEF score is a reliable predictor of anxiety and depression symptoms after PCI. Previously there have also been composite objective parameters to predict post-PCI depression and anxiety symptoms. Li et al based on the theory that the inflammatory system was a potential pathological mechanism for the development of depression symptoms, they found that NLR index might be useful inflammatory markers to predict post-PCI depressive symptoms at 1 month (AUC: 0.716, 95% CI: 0.641–0.791).31 Recently, a nomogram based on the 2005–2018 National Health and Nutrition Examination Surveys (NHANES) database was constructed to accurately and objectively predict post-PCI depression, the simplified model variables including age, smoking, poverty to income ratio, and insomnia (AUC: 0.772,95% CI: 0.732–0.812).32 Another nomogram predicting the occurrence of post-PCI depression in acute coronary syndrome patients included female, hypertension history, Gensini score, neutrophil to lymphocyte ratio ≥ 3.24, palate to lymphocyte ratio ≥ 147.74 (AUC: 0.881,95% CI: 0.824–0.938).33 The ACEF score in present study was as accurate a predictor of post-PCI anxiety and depression symptoms as the predictive models described above, with an AUC and 0.666 (95% CI: 0.578–0.753) and 0.662 (95% CI: 0.584–0.740), respectively. And, after multivariable adjusting, individuals in the highest quartile of ACEF score had a 7.701-fold and 6.173-fold higher risk of post-PCI anxiety and depression than those with the lowest quartile.
What’s more, although we have excluded patients who had a history of depression disorders, anxiety disorders or other mental illnesses, it is important to note that anxiety and depression symptoms may have existed prior to PCI in some patients. Given the well-established association between psychological disorders and cardiovascular risk, pre-existing anxiety and depression may exacerbate cardiovascular damage through multiple pathophysiological pathways (eg, chronic inflammation, autonomic dysfunction, or endothelial dysfunction), thereby influencing components of the ACEF score (such as age-related HPA axis dysregulation, abnormal creatinine metabolism, or reduced left ventricular function). Thus, these psychological conditions could act both as triggers for cardiovascular diseases and as contributing factors to elevated ACEF scores, forming a bidirectional association with postoperative psychological symptoms. Future studies should systematically assess patients’ psychological status at baseline to further clarify the interplay between pre-procedural anxiety/depression and the ACEF score.
Clinical Implications
The ACEF score, derived from routinely collected clinical parameters (age, creatinine, and ejection fraction), offers a pragmatic advantage over dedicated psychological screening tools like HADS. Specifically, ACEF does not require additional patient-reported data or dedicated staff time, making it inherently scalable in resource-constrained settings. Clinicians could leverage this score to flag high-risk patients for targeted mental health assessments, particularly in populations where formal anxiety/depression screening is underutilized.
Limitations
This study has several limitations. First, this is a heterogenous population with a relatively small cohort of patients. The heterogeneity reflects real-world clinical diversity, as our study aimed to capture a broad spectrum of patients undergoing PCI in routine practice. This approach enhances ecological validity but may introduce variability. Larger, multicenter validation studies were needed. And our study included a predominantly male cohort (82.4%), with only 17.6% female participants. This imbalance limits the statistical power to detect meaningful gender differences in outcomes. Future studies with balanced gender representation are needed to explore potential sex-specific associations between ACEF scores and psychological morbidity.
Second, in this study, ACEF score was only used to predict post-PCI anxiety and depression status during hospitalization, given that anxiety and depression are considered state indicators and may change over time and conditions. Future studies incorporating serial assessments at 1-month, 6-month and 1-year intervals are needed to evaluate whether ACEF scores predict sustained psychological morbidity or serve as dynamic markers of mental health trajectories.
Third, we included all comers who underwent PCI, whereas psychological preparation might be different for patients undergoing emergency vs elective PCI. In our study, emergency PCI patients exhibited higher anxiety scores, and statistically significant was observed. While depression scores were numerically higher in acute PCI patients, the difference between the two groups did not reach statistical significance, which may be attributed to factors such as the time window of assessment, measurement tools and sample size limitations (Supplement 1).
Finally, the use of the Hospital Anxiety and Depression Scale (HADS) to assess anxiety and depressive symptoms. Although HADS is widely adopted in clinical practice, the validity of its two-factor structure remains controversial, which may compromise the independent distinction between anxiety and depression symptoms. Future research could employ multidimensional psychological assessment tools (eg, PHQ-9 and GAD-7, or combined clinical interviews) to further validate the current findings and enhance the robustness of the results. Additionally, exploring the consistency of associations between ACEF scores and psychological symptoms across different scales would help clarify the generalizability of its predictive value.
Conclusion
ACEF, a simple and objective score, can be a valid predictor of anxiety and depression symptoms during hospitalization after PCI, and higher ACEF score is positively correlated with the prevalences of depression and anxiety symptoms.
Funding
This study was supported by Natural Science Fund of Hubei (grant no. 2021CFB4408) and Natural Science Foundation of Xinjiang Uygur Autonomous Region (grant no.2021D01C445).
Disclosure
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Formula 1 returns to action following the summer break with the Dutch Grand Prix at Zandvoort. But who are the favourites to get back up and running the quickest? Here are what the odds tell us…
Odds are provided by F1’s Official Betting Data Supplier ALT Sports Data, are subject to change and are presented in decimal form: for every $1 wagered you would win the figure represented by the odds; so, if Verstappen is favourite at 1.50, you would win $1.50 for every dollar bet.
The odds for the win
Championship leader Oscar Piastri enters the Dutch Grand Prix weekend as the favourite for success. With six wins this term, the Australian tops the win charts and has missed out on a podium only twice in 14 starts.
On the other side of the McLaren garage, however, Lando Norris was the victorious driver at Zandvoort in 2024, and is the in-form driver with three wins from the last four events to close the points gap.
With three previous wins at the coastal venue, home hero Max Verstappen should not be written off. But with only two wins this season and a Red Bull that has struggled to match McLaren’s pace on Sundays, this could be an uphill battle.
The odds for a podium finish
With the McLaren drivers each failing to feature on the podium just twice this season, the pair are heavy favourites to feature in the top three on Sunday afternoon.
Just behind Verstappen is Charles Leclerc, who has finished third twice in the last three years at Zandvoort, and has recently found form, with podiums in Austria and Belgium.
George Russell will look to go back-to-back following a top-three result last time out in Hungary, while Lewis Hamilton continues his search for a first Grand Prix podium for Ferrari.
The odds for a top-six finish
Hamilton will be keen to return to the top six after two races outside of this bracket, most recently finishing in 12th. Before this, he had been a regular in the higher end of the points, finishing in the top six in six consecutive races from Imola to Silverstone.
Fernando Alonso was able to make the most of a strong weekend for Aston Martin in Hungary to reach the top six for the first time this term, but questions remain as to whether the team can repeat this level of performance.
Gabriel Bortoleto has shown consistent improvement across his rookie season, and achieved a career-best sixth place at the Hungaroring. He has also scored points in three of the last four races for Sauber.
The odds for a top-10 finish
Nico Hulkenberg and Isack Hadjar have taken the chequered flag in the top 10 places on five occasions this year. While Sauber driver Hulkenberg has scored in four of the last six races, Hadjar last scored at the Spanish Grand Prix for Racing Bulls.
In the other Racing Bulls entry, Liam Lawson has found recent form, with points in Austria followed by back-to-back eighth-place finishes in Belgium and Hungary.
Finishing seventh in two of the last three weekends, Lance Stroll could add to his Aston Martin points total.
The odds for who will be fastest in Qualifying
Piastri and Norris remain the favourites to take pole position for McLaren, but the margins have been fine in Qualifying this term.
Leclerc claimed his first pole position of the season in Hungary, while Verstappen is tied with the McLaren pair on four for the campaign. Russell is the only other pole-sitter so far in 2025.
McLaren have only once failed to take pole position at consecutive races this year – this coming when Verstappen headed the grid in Saudi Arabia and Miami.
The odds for the winning team
After 14 rounds, McLaren have been victorious 11 times, with Piastri contributing six to the cause, and Norris five. This total includes six of the last seven rounds. The team is dominating the Teams’ Championship, with 559 points to Ferrari’s 260.
Through Verstappen, Red Bull has topped the podium twice, while Mercedes has a single victory, courtesy of Russell.
Tesla sales slumped 40% across Europe in July compared with a year earlier, as the electric car company run by Elon Musk faces increasingly tough competition from its Chinese rival BYD.
There were 8,837 sales of Tesla cars last month across the EU, the European Free Trade Association and the UK, according to figures from the European Automobile Manufacturers’ Association (ACEA). That compared with 14,769 at the same point last year.
Meanwhile, new car registrations for BYD more than tripled across Europe last month to 13,503, compared with 4,151 last year. BYD’s now has 1.2% market share, the ACEA found. Tesla’s share stood at 0.8%.
Chinese car brands, which often have relatively cheaper models, have been expanding aggressively in Europe. BYD outsold Tesla in Europe for the first time this spring, according to a report from the market research company JATO Dynamics.
In the UK the government said on Thursday that the US car brand Ford would be the first manufacturer to receive the maximum £3,750 subsidy on two models: the Gen-E and the e-Tourneo Courier. A further 26 other models will be eligible for grants of £1,500 under the government’s new electric car grant scheme.
The grants only apply to vehicles with a list price of £37,000 or below, and the discount is applied automatically at the point of sale.
The transport secretary, Heidi Alexander, said: “We’re putting money back in people’s pockets and making it easier and cheaper for families to make the switch to electric, by delivering discounts of up to £3,750 on EVs.
“Our measures are driving competition in the UK EV market, boosting economic growth and supporting jobs and skills as part of our plan for change.”
Separately the Society of Motor Manufacturers and Traders said UK car production rose for a second month in a row in July, by 5.6%.
However, the SMMT chief executive, Mike Hawes, said it was a turbulent time in the market, with “consumer confidence weak, trade flows volatile and massive investment in new technologies under way both here and abroad”.
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ACEA also reported that in the first seven months of 2025, 1,011,903 new battery-electric cars were registered, accounting for 15.6% of the EU market share.
Hybrid-electric car registrations proved more popular, with 2,255,080 units sold across the EU so far this year. This was driven by growth in the four biggest markets: France, up 30.5%, Spain, up 30.2%, Germany, up 10.7, and Italy, up 9.4%.
Sigrid de Vries, the director general of ACEA, said that to accelerate uptake, Europe “must continue to expand public recharging infrastructure, secure lower recharging prices, and ensure well-coordinated purchase incentives schemes”.
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