共找到 20 条结果
The 2023 iteration of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) estimated prevalence, incidence, and health burden for 375 diseases and injuries, including 12 mental disorders. We assess past, current, and emerging trends in the prevalence and burden of mental disorders across sexes and age groups, for 21 regions, 204 countries and territories, and by Socio-demographic Index (SDI) quintile, from 1990 to 2023. Mental disorders included in GBD 2023 were anxiety disorders, major depressive disorder, dysthymia, bipolar disorder, schizophrenia, autism spectrum disorders, conduct disorder, attention-deficit hyperactivity disorder, anorexia nervosa, bulimia nervosa, idiopathic developmental intellectual disability, and a residual category of other mental disorders. A literature review identified epidemiological data for each disorder. These were analysed via a Bayesian meta-regression to estimate prevalence by disorder, sex, age, location, and year. Disorder-specific prevalence was multiplied by disability weights representing the severity of health loss associated with each disorder to estimate years lived with disability (YLDs). Deaths due to anorexia nervosa were assessed with a Cause of Death Ensemble modelling strategy to estimate deaths by sex, age, location, and year, and then multiplied by the standard life expectancy at age of death to estimate years of life lost (YLLs). YLDs equalled disability-adjusted life-years (DALYs) for all mental disorders except anorexia nervosa (the only mental disorder considered as an underlying cause of death in GBD), for which DALYs represented the sum of YLDs and YLLs. We presented prevalence, deaths, YLDs, YLLs, and DALYs as counts, age-specific rates per 100 000 population, and age-standardised rates per 100 000 population. We estimated 1·17 billion (95% uncertainty interval 1·06-1·31) prevalent cases of mental disorders globally in 2023, equivalent to an age-standardised prevalence rate of 14 210·7 cases (12 849·5-15 940·1) per 100 000 population. These estimates represented a 95·5% (75·0-121·2) increase in prevalent cases and 24·2% (11·4-41·4) increase in age-standardised prevalence rate between 1990 and 2023. All mental disorders showed increases in prevalent cases between 1990 and 2023, while notable increases were seen in age-standardised prevalence rates for anxiety disorders, major depressive disorder, dysthymia, anorexia nervosa, bulimia nervosa, schizophrenia, and conduct disorder. There were an estimated 171 million (127-228) DALYs due to mental disorders globally across sex and age in 2023, equivalent to an age-standardised DALY rate of 2070·5 DALYs (1519·1-2750·5) per 100 000 population. Mental disorders contributed to 6·1% (4·8-7·6) of all-cause DALYs in 2023, making them the fifth leading cause of global DALYs (up from 12th in 1990). DALYs were almost entirely composed of YLDs. Mental disorders were the leading cause of YLDs in 2023 (up from second in 1990), explaining 17·3% (14·8-20·6) of all-cause global YLDs. Leading causes of mental disorder DALYs were anxiety disorders (ranked 11th among the 304 diseases and injuries at Level 4 of the GBD cause hierarchy), major depressive disorder (15th), and schizophrenia (41st). Globally in 2023, mental disorder age-standardised DALY rates were higher among females (2239·6 [1643·7-3014·1] per 100 000) than among males (1900·2 [1399·8-2510·8] per 100 000), and peaked in the 15-19 years age group (2617·3 [1850·6-3696·8] per 100 000). All locations showed increased mental disorder DALY rates in 2023 compared with 1990, ranging across countries and territories from 1302·4 (952·7-1683·7) per 100 000 in Viet Nam to 3555·8 (2661·9-4715·0) per 100 000 in the Netherlands. Across SDI quintiles, DALY rates ranged from 1853·0 (1352·1-2469·3) per 100 000 for middle SDI to 2184·1 (1606·1-2890·3) per 100 000 for high SDI. A significant health burden was imposed by mental disorders in all countries and territories in 2023, irrespective of the health resources available. In some instances, this burden has increased over time and is unevenly distributed across populations. Stronger surveillance systems, particularly in low-income and middle-income countries, are required. Additionally, we need more coordinated and inclusive policies to reduce the burden through early treatment and prevention, tailored to sex and age differences across locations. Responding to the mental health needs of our global population, especially those most vulnerable, is an obligation, not a choice. Gates Foundation, Queensland Health, and University of Queensland.
Cardiovascular diseases (CVD) continue to be the leading cause of global mortality. Despite the alarming statistics, effective prevention of CVD remains a significant challenge in practice. The available risk stratification tools have critical limitations in the early detection of CVD. To address these gaps, it is crucial to integrate additional risk detection methods for more accurate identification of at-risk patients. This article addresses the limitations of conventional CVD risk factors and emphasizes the need for individualized risk evaluation. Additionally, it evaluates the role of imaging techniques in the early detection of CVD and the personalized use of aspirin therapy when subclinical atherosclerosis becomes advanced. This article is based on an expert literature review and reflects the outcomes of a medical advisory board meeting that was held in the Middle East (ME) region. A multidisciplinary group of experts discussed the "cardiac risk continuum" concept and the importance of advanced subclinical atherosclerosis detection beyond traditional binary CVD classification. Experts evaluated the clinical feasibility of utilizing carotid ultrasound and coronary artery calcium (CAC) scoring, and assessed the role of aspirin in primary prevention for at-risk patients. The need for tailored risk assessment strategies and individualized preventive measures was highlighted. The experts agreed on the practical use of CAC scoring and/or carotid ultrasound to identify at-risk patients and quantify subclinical atherosclerosis. Data suggest that aspirin estimated benefit increases proportionally with atherosclerosis burden and becomes a net-positive at CAC > 100 or carotid plaque score above 2. The experts emphasized the importance of individualized screening strategies tailored to the Middle Eastern population, considering the challenges and resource limitations in the region. They recommended selective use of CAC and carotid ultrasound to improve risk stratification and to guide a more personalized approach to managing CVD. The experts stressed the need for standardized protocols, healthcare providers' education, and infrastructure development to ensure the effective implementation of these approaches.
The association between breast cancer diagnosis and treatment and the risk of incident ischemic stroke remains unclear. We investigated ischemic stroke risk among breast cancer survivors and evaluated associations by age, follow-up duration, and type of cancer treatment. We conducted a nationwide, retrospective, matched cohort study using the Korean National Health Insurance Service database. Women aged 18 years and older with newly diagnosed breast cancer who underwent breast cancer surgery between January 2010 and December 2016 and had no prior stroke were identified. Each was matched 1:3 by birth year to cancer-free women. The primary outcome was first ischemic stroke, defined as hospitalization with International Classification of Disease, Tenth Revision codes I63/I64 plus inpatient brain CT or MRI. Subdistribution hazard ratios (sHRs) and 95% CIs were estimated using Fine-Gray models that accounted for death as a competing risk and adjusted for sociodemographic factors and cardiovascular and non-CV comorbidities. We analyzed 107,606 breast cancer surgery survivors (mean age, 50.0 years) and 322,818 matched cancer-free women. Over a mean 7.2-year follow-up, ischemic stroke occurred in 1,155 survivors (1.07%). Stroke risk was elevated shortly after breast cancer diagnosis (1-year sHR 1.59; 95% CI 1.34-1.89; 3-year sHR 1.17; 95% CI 1.05-1.30) compared with cancer-free women, with stronger associations at 3 and 6 months after diagnosis across all age groups. Over the long term, survivors had a slightly lower risk of stroke (sHR 0.94; 95% CI 0.88-1.00), and in a 1-year landmark analysis including only event-free individuals, the risk was lower (sHR 0.87, 95% CI 0.81-0.93). Among survivors, anthracycline use (sHR 1.25) and combined tamoxifen-aromatase inhibitor therapy (sHR 1.49) were associated with increased risk of stroke, whereas radiation therapy was associated with decreased risk (sHR 0.84). These associations attenuated and became nonsignificant beyond 1 year. Stroke risk was also higher among survivors with low income, hypertension, diabetes, or current smoking. The association between breast cancer and ischemic stroke risk is time dependent, with a short-term increase after diagnosis and treatment followed by a gradual decline over time. These findings highlight the need for proactive stroke risk management, including early CV assessment and ongoing monitoring for thromboembolic events during survivorship.
Adults aged 75 years and older carry the highest absolute risk of cardiovascular disease (CVD) yet remain substantially underrepresented in randomized trials evaluating statin therapy for primary prevention. This evidence gap creates uncertainty regarding the appropriateness of initiating lipid-lowering therapy in this population. We conducted a narrative review of randomized controlled trials, meta-analyses, and large observational studies evaluating statin therapy for primary CVD prevention in adults aged 75 years and older. We searched PubMed and reference lists of relevant articles through December 2024. Direct randomized evidence for primary prevention in adults over 75 years is limited. The PROSPER trial included a mixed population of primary and secondary prevention patients aged 70-82 years. Post-hoc analyses of ALLHAT-LLT showed no benefit and a trend toward harm in patients aged 75 years and older. Meta-analyses of observational data suggest mortality reductions of 12-14% associated with statin use, though subject to confounding. The time to benefit for cardiovascular event reduction is approximately 2.5 years, which must be weighed against individual life expectancy. Current evidence does not support routine statin initiation for primary prevention in all adults over 75 years. Treatment decisions should be individualized based on cardiovascular risk, life expectancy, frailty status, patient preferences, and competing health priorities. Results from the STAREE and PREVENTABLE trials, expected in 2025-2027, will provide definitive guidance.
Albuminuria has emerged as a key marker for cardiovascular (CV) and renal risk. Despite its clinical relevance, its role as a continuous and stratified predictor of ischemic CV events remains underexplored in Latin American populations, further evidence is needed to assess the prognostic value of urinary albumin-creatinine ratio (UACR) in this context. A retrospective cohort of Mexican adults with UACR measured in 2019 and 5-year follow-up was conducted. UACR levels were classified per 2024 CKD Prognosis Consortium and KDIGO guidelines. Cox model regressions were used to analyze CV events-including myocardial infarction, ischemic stroke, heart failure, unstable angina, and transient ischemic attack -along with overall mortality and associated variables. Among 809 patients [mean (SD) age 55·2(12·5) years; 413 (51·1) males] followed over five years, those in the A3 albuminuria category (UACR ≥300 mg/g) had a significantly increased risk of ischemic CV events (HR ∼3·0) and all-cause mortality (HR > 4·5). Prior history of CV events, smoking, older age, and higher number of medical visits were also associated with CV events. An increase in mortality was seen since A1.2 albuminuria category. HbA1c, age, and male sex emerged as predictors of all-cause mortality. Higher levels of UACR, starting from A1 category, were independently associated with increased risk of CV events and mortality. These findings support the use of UACR as a continuous and stratified marker for CV and renal risk in high-risk populations, even beyond the context of diabetes.
Peripheral artery disease (PAD) is a condition in which atherosclerosis causes narrowing or blockage of the peripheral arteries, leading to insufficient blood supply to the limbs. Although accelerated biological aging has been recognized as a driving factor in the development and progression of many age-related diseases, its exact role in the risk of developing PAD remains unclear. This study investigated the relationship of biological aging and genetic susceptibility with the risk of incident PAD. This prospective study included 403,780 UK Biobank participants free of PAD at baseline. Biological age was estimated from routine clinical biomarkers using the Klemera-Doubal method (KDM-BA) and PhenoAge algorithms. BAA was defined as the residual from regression of biological age on chronological age. Multivariable Cox proportional hazards models were used to estimate hazard ratios (HRs) for incident PAD after adjustment for demographic, socioeconomic, lifestyle, and clinical covariates. A polygenic risk score (PRS) was constructed to evaluate genetic predisposition to PAD. We also examined the interaction between genetic susceptibility and accelerated biological aging in relation to PAD risk. Our findings indicated that accelerated biological aging was significantly associated with an increased risk of PAD, whether assessed by the KDM residual (HR 1.21, 95% CI 1.18-1.24) or the PhenoAge residual (HR 1.34, 95% CI 1.31-1.37). Furthermore, joint association analysis showed that participants with both accelerated biological aging and high genetic risk had the greatest risk of PAD (KDMAge: HR 2.07, 95% CI 1.83-2.34; PhenoAge: HR 6.14, 95% CI 5.30-7.12). A significant additive interaction was also observed between high genetic risk and accelerated biological aging as measured by PhenoAge. Accelerated biological ageing were independently and jointly associated with incident PAD. This finding support the potential value of integrating biological ageing metrics into PAD risk assessment.
Information on childhood cancer burden is crucial for effective cancer policy planning. Unfortunately, observed paediatric cancer data are not available in every country, and previous global burden estimates have not discretely reported several common cancers of childhood. We aimed to inform efforts to address childhood cancer burden globally by analysing results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, which now include nine additional cancer causes compared with previous GBD analyses. GBD 2023 data sources for cancer estimation included population-based cancer registries, vital registration systems, and verbal autopsies. For childhood cancers (defined as those occurring at ages 0-19 years), mortality was estimated using cancer-specific ensemble models and incidence was estimated using mortality estimates and modelled mortality-to-incidence ratios (MIRs). Years of life lost (YLLs) were estimated by multiplying age-specific cancer deaths by the standard life expectancy at the age of death. Prevalence was estimated using survival estimates modelled from MIRs and multiplied by sequelae-specific disability weights to estimate years lived with disability (YLDs). Disability-adjusted life-years (DALYs) were estimated as the sum of YLLs and YLDs. Estimates are presented globally and by geographical and resource groupings, and all estimates are presented with 95% uncertainty intervals (UIs). Globally, in 2023, there were an estimated 377 000 incident childhood cancer cases (95% UI 288 000-489 000), 144 000 deaths (131 000-162 000), and 11·7 million (10·7-13·2) DALYs due to childhood cancer. Deaths due to childhood cancer decreased by 27·0% (15·5-36·1) globally, from 197 000 (173 000-218 000) in 1990, but increased in the WHO African region by 55·6% (25·5-92·4), from 31 500 (24 900-38 500) to 49 000 (42 600-58 200) between 1990 and 2023. In 2023, age-standardised YLLs due to childhood cancer were inversely correlated with country-level Socio-demographic Index. Childhood cancer was the eighth-leading cause of childhood deaths and the ninth-leading cause of DALYs among all cancers in 2023. The percentage of DALYs due to uncategorised childhood cancers was reduced from 26·5% (26·5-26·5) in GBD 2017 to 10·5% (8·1-13·1) with the addition of the nine new cancer causes. Target cancers for the WHO Global Initiative for Childhood Cancer (GICC) comprised 47·3% (42·2-52·0) of global childhood cancer deaths in 2023. Global childhood cancer burden remains a substantial contributor to global childhood disease and cancer burden and is disproportionately weighted towards resource-limited settings. The estimation of additional cancer types relevant in childhood provides a step towards alignment with WHO GICC targets. Efforts to decrease global childhood cancer burden should focus on addressing the inequities in burden worldwide and support comprehensive improvements along the childhood cancer diagnosis and care continuum. St Jude Children's Research Hospital, Gates Foundation, and St Baldrick's Foundation.
To investigate the association of caffeinated and decaffeinated coffee consumption with the risk of diabetes mellitus and gestational diabetes mellitus (GDM). This is a cross-sectional study included 6311 women(1313 with diabetes mellitus, 574 with GDM) using NHANES data (2007-2018). Logistic regression models were used to evaluate the associations between coffee/caffeine intake and diabetes mellitus/GDM risk. Subgroup analyses were done to test results robustness. Higher caffeinated coffee intake was associated with a decreased risk of diabetes mellitus, with ORs of 0.80 (95%CI, 0.66-0.99) for ≤1 cup/day, 0.73 (95%CI, 0.60-0.88) for 1-2 cups/day, 0.86 (95%CI, 0.69-1.07) for 2-3 cups/day, and 0.74 (95%CI, 0.57-0.96) for >3 cups/day. There were dose-response associations of caffeine consumption and the risk of diabetes mellitus. Stratified analyses highlighted obvious relationships of higher caffeine intake with decreased diabetes mellitus in individuals with a BMI ≥30 kg/m2 and those with lower physical activity levels. No significant association was found between coffee intake and GDM risk. Coffee consumption, particularly caffeinated coffee, is associated with a decreased risk of diabetes mellitus but not with GDM. These findings suggest potential metabolic benefits of coffee.
Short or long sleep duration is associated with hypertension in middle-aged populations. However, this association, and its possible effect on cardiovascular outcomes, is not established in older adults, despite age-related changes in the role of systolic (SBP) and diastolic (DBP) blood pressure as cardiovascular risk factors, and the increased predictive role of pulse pressure (PP) in the elderly. We investigated the association of sleep duration with BP levels by 24-h ambulatory BP monitoring (ABPM) and with incident cardiovascular outcomes. 828 participants (mean age 71 years, 60% women) were evaluated. Self-reported short sleep was defined as the lowest quintile (≤7 h) and long sleep as the highest quintile (>10 h); intermediate duration was reference. Outcomes were ischemic stroke, myocardial infarction, cardiovascular death, and composite outcome (any of the 3). Long sleepers had substantially higher daytime and 24-h PP than the reference group (both P < 0.05). There were no differences in SBP and DBP values. Over 11.3 years of follow-up, 214 (25.8%) participants developed cardiovascular events. Long sleep was independently associated with ischemic stroke (adjusted hazard ratios [aHR] 1.76, 95% confidence interval [CI], 1.02-3.04; p = 0.044), cardiovascular death (aHR 1.56, 95% CI, 1.03-2.37; p = 0.035) and composite outcome (aHR 1.41, 95% CI, 1.01-1.98; p = 0.046). PP was also independently associated with cardiovascular events. Short sleep was associated with increased PP in the elderly. Long sleep duration was associated with increased PP and subsequent cardiovascular events, suggesting the importance of PP for cardiovascular risk in the middle-aged and elderly long sleepers.
Atrial fibrillation (AF) and cardiovascular (CV) comorbidities are prevalent in acute pancreatitis (AP) and may compromise hemodynamic tolerance of systemic inflammation. Their independent contributions to in-hospital mortality in AP have not been quantified nationally. We analyzed discharge data from the National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP), Agency for Healthcare Research and Quality (AHRQ), 2016-2022. Adult AP hospitalizations were identified by primary ICD-10-CM diagnosis. Twelve CV risk factors were examined. Survey-weighted logistic regression generated unadjusted, adjusted, and fully adjusted odds ratios (ORs) for in-hospital mortality. A cumulative risk factor count was constructed. Among 1,919,159 weighted AP hospitalizations, overall mortality was 0.59%. On full multivariable adjustment, cerebrovascular disease (OR 2.83, 95% CI 2.33-3.44), AF (2.10, 1.85-2.37), CKD (1.89, 1.68-2.12), MI (1.86, 1.56-2.23), and heart failure (1.79, 1.56-2.05) were the strongest independent CV-comorbidity predictors of in-hospital death. Weighted mortality rose progressively from 0.21% at zero to 3.03% at seven cumulative risk factors; per additional risk factor the crude OR was 1.47 (1.45-1.50, p < 0.001). The dose-response gradient persisted after full adjustment, with integer-level adjusted ORs rising from 1.25 at one risk factor to 5.05 at seven, and a binary cutoff at three or more versus two or fewer risk factors carrying an adjusted OR of 2.01 (1.80-2.25, p < 0.001). Cerebrovascular disease, AF, CKD, MI, and heart failure independently predict in-hospital mortality in AP, with a robust adjusted dose-response by cumulative CV burden. These associative findings are hypothesis-generating; prospective studies are needed to determine whether structured cardiovascular risk assessment improves outcomes in this population.
MicroRNAs (miRNAs) are critical regulators of vascular biology and have been implicated in the pathogenesis of abdominal aortic aneurysm (AAA). However, the diversity of study designs and heterogeneous findings has limited their clinical translation. This study aimed to systematically review available evidence on miRNA expression in AAA, both in aortic tissue and circulating blood, and to explore their potential regulatory pathways. We conducted a comprehensive literature search across five databases -PubMed, Scopus, Embase, Web of Science (WoS), and EBSCO - up to June 2025, following the PRISMA guidelines. Eligible studies included those reporting differential miRNA expression in human AAA samples, whether tissue or blood, with validated results. Data on expression direction, sample type, pathways, and target genes were extracted and synthesized. A total of 39 studies were included reported diagnostic performance varied substantially across studies. Circulating miRNAs in AAA patients exhibited distinct dysregulation patterns, reflecting disease-associated vascular and inflammatory processes. Key Up-regulated miRNAs included miR-21, miR-146a, miR-155, miR-1281, and miR-34a, while prominent Down-regulated candidates comprised miR-15a, miR-29, miR-150-5p, miR-27a-3p, and let-7 family members. These alterations were observed in plasma, serum, and specific cell types, suggesting possible utility as non-invasive biomarker candidates for AAA detection and disease monitoring, although external validation remains limited. Our systematic review highlights a panel of consistently dysregulated miRNAs in AAA, with roles in inflammation, extracellular matrix remodeling, and vascular cell regulation, and they may represent promising candidates for future screening and diagnostic evaluation, pending standardization and prospective validation.
Coronary angiography (CA) and percutaneous coronary intervention (PCI) are widely used for diagnosing and treating coronary artery disease (CAD) but may cause bleeding-related in-hospital complications, especially with femoral access. This study evaluated the incidence and predictors of access-site bleeding events and related outcomes in central Iran. In this retrospective cohort, 1369 patients underwent CA and PCI at Afshar Hospital, Yazd, between 2020 and 2022. Demographic, clinical, and procedural data were collected. Bleeding events were classified using the Bleeding Academic Research Consortium (BARC) criteria, and high bleeding risk was defined according to the Academic Research Consortium for High Bleeding Risk (ARC-HBR). Logistic regression identified independent predictors. Bleeding-related in-hospital complications occurred in 143 patients (10.4%), most commonly inguinal hematoma (8.4%), major bleeding (1.6%), and mortality (0.6%). BARC Type 2 bleeding was most frequent (8.4%), followed by Type 3a (1.6%) and 3b (0.3%). Based on ARC-HBR, 13.5% of patients met at least one major or two minor high bleeding risk criteria. Multivariate analysis showed that elevated international normalized ratio (INR) (OR = 2.15; 95% CI: 1.22-3.72; P = 0.006) and anticoagulant use (OR = 1.8; 95% CI: 1.14-2.85; P = 0.011) were significantly associated with complications. Bleeding-related complications, particularly hematoma, major bleeding, and procedure-related mortality, occurred in over 10% of patients undergoing CA and PCI. Anticoagulant therapy and elevated INR were key predictors, highlighting the importance of individualized risk assessment and bleeding risk stratification using tools like BARC and ARC-HBR.
Artificial intelligence-enabled quantitative coronary computed tomography angiography (AI-QCCTA) offers automated assessment of coronary plaque burden and morphology. Although AI-QCCTA has improved diagnostic consistency and downstream testing efficiency, its prognostic value for major adverse cardiovascular events (MACE) has not been comprehensively quantified. We systematically searched PubMed, Embase, and Cochrane through October 2025 for studies evaluating AI-based plaque analysis in patients without prior MACE undergoing CCTA. Outcomes of interest were pooled using random-effects GLMM models, and prognostic associations were synthesized using inverse-variance random-effects meta-analysis of hazard ratios (HRs). The primary endpoint was MACE; secondary outcomes included myocardial infarction (MI), revascularization, angina, stroke, and mortality. Subgroup analysis was done to identify the association of different plaque characteristics in predicting MACE/MI/Death. Ten studies (n = 20,195) were included. Across six cohorts (n = 18,804), pooled rates were: all-cause mortality 1.20% (95% CI 0.38-3.77%), cardiovascular mortality 0.32% (0.21-0.48%), MACE 5.07% (1.25-18.46%), MI 1.30% (0.41-3.99%), and revascularization 13.09% (6.57-24.40%). AI-enabled plaque burden predicted MACE (HR 1.95, 95% CI 1.29-2.94; I2 = 99%), consistent in sensitivity analysis as per same AI platform use (HR 1.88, 95% CI 1.15-3.07). Low-attenuation plaque showed the strongest association (HR 2.95, 95% CI 1.95-4.45). AI-QCCTA provides prognostic value beyond stenosis severity, with vulnerable plaque characteristics-particularly low-attenuation and non-calcified plaque most strongly predicting adverse cardiovascular outcomes. These findings support the integration of AI-enabled plaque analysis into contemporary risk stratification.
Accurate assessment of mitral regurgitation (MR) severity is crucial for guiding clinical management, but is often limited by the subjectivity and variability of traditional echocardiographic evaluations. Machine learning (ML) models offer potential for automated, objective MR grading, yet their diagnostic performance remains underexplored. This systematic review and meta-analysis aim to evaluate the diagnostic accuracy of ML-based models for assessing MR severity. We searched five different databases for studies evaluating ML algorithms (deep learning or traditional ML) for MR severity assessment in adults. Data were extracted and the risk of bias was assessed using the PROBAST + AI tool. A bivariate random-effects model was used to pool diagnostic metrics, with heterogeneity quantified via I2 statistics and explored through meta-regression and subgroup analyses. Publication bias was evaluated using Deeks' test and funnel plot. Nine studies met inclusion criteria, demonstrating strong ML performance with a pooled AUROC of 0.97 (95% CI: 0.96-0.98), sensitivity of 0.93 (95% CI: 0.83-0.97), and specificity of 0.96 (95% CI: 0.92-0.98). High heterogeneity (I2 > 70%) was observed, partly explained by variations in validation methods and sample size. No significant publication bias was detected (Deeks' p = 0.64). The certainty of the evidence was moderate due to heterogeneity and the retrospective study design. ML models demonstrate good diagnostic accuracy for assessing MR severity, with the potential to enhance clinical decision-making by reducing subjectivity. However, high heterogeneity and limited external validation necessitate prospective, standardized trials to ensure generalizability and clinical adoption.
New-onset atrial fibrillation (NOAF) is a common cardiovascular complication in critically ill patients and is consistently associated with adverse outcomes. However, substantial heterogeneity exists in its clinical presentation and prognosis. This study aimed to identify distinct clinical subtypes of NOAF and evaluate their prognostic and management-related implications. Adult NOAF patients were extracted from the MIMIC-IV database. Demographic and laboratory data within 24 h of ICU admission were analyzed. Consensus k-means clustering was used for identifying subtypes. Survival differences were compared using Kaplan-Meier and log-rank tests, and multivariable Cox models assessed mortality risk and pharmacologic treatment associations. Key variables identified by SHAP analysis were incorporated into a simplified six-variable model, validated externally in MIMIC-III. Among 8472 NOAF patients, four distinct subtypes were identified from the MIMIC-IV cohort (n = 5554), showing progressively increased severity and mortality. Subtype A (30.28%) included mainly post-cardiac surgery patients with preserved homeostasis and the lowest 28-day mortality (4.9%). Subtype B (34.52%) was characterized by marked hypomagnesemia and a moderate burden of comorbid malignancy (28-day mortality 15.5%). Subtype C (19.70%) featured anemia, hypoxemia, and inflammation (28-day mortality 30.2%). Subtype D (15.50%) presented with organ failure and the highest 28-day mortality (42.7%). 28-day mortality risk increased stepwise across subtypes (HR 4.24-5.98; all P < 0.001). Pharmacologic responses, including heart rate control, sedation, and electrolyte therapy, varied across different subtypes. The simplified six-variable model demonstrated high predictive performance (AUC 0.89-0.96) in external validation. Unsupervised clustering revealed four distinct NOAF subtypes in ICU patients, characterized by heterogeneous clinical trajectories. The simplified six-variable model enabled practical bedside classification, supporting precision risk assessment and potentially informing phenotype-oriented management of NOAF in the ICU.
We evaluated trends in prevalence and incidence of heart failure (HF) hospitalizations in Lombardy, and the characteristics of patients starting optimal medical treatment (O-HF-T: almost three among: diuretics, mineralocorticoid receptor antagonist, beta-blockers, ACE-inhibitors, Angiotensin Receptor Blockers). We analysed hospital discharge data with HF-related ICD9-CM recorded in the regional healthcare service from 2000 to 2023. Age-gender standardized HF prevalence and incidence rates were calculated from 2005 to 2023. Determinants of starting O-HF-T, in the three months after discharge, were investigated by Log-Binomial model. HF incidence rates decreased from 790 per 100,000 years-person in 2005 to 564 per 100,000 in 2023; males had higher rates. Standardized prevalence rate increased until 2010, followed by a decrement peaking in the SARS-CoV2 pandemic year 2020. We investigated starting of O-HF-T, and its determinants, in a cohort of incident HF hospitalized patients from January 2010 to September 2019 to avoid the pandemic period (54022 patients, mean age 70 years, 60% males; 55% started O-HF-T within 90-days after discharge. The likelihood of starting O-HF-T was higher in younger males and in patients already treated with lipid-lowering, antidiabetic and antihypertensive drugs before the HF hospitalization. The likelihood of receiving O-HF-T decreased with age, in patients treated with antidepressants and in those with previous CV hospitalizations. The reduction of hospitalisations after 2010 can be explained by a combination of improved disease prevention and better care. Optimal medical treatment was achieved in about half of patients, mainly in younger males.
Multimorbidity, the co-occurrence of two or more non-communicable diseases (NCDs), is common and has been linked to venous thromboembolism (VTE). Whether multimorbidity diagnosed in primary-care is associated with incident VTE remains unclear. We aimed to examine this association. Multimorbidity was defined using Swedish primary-care data. Individuals without prior VTE were included, and incident VTE was identified through the Swedish National Patient Register. Primary-care multimorbidity was defined as two or more NCDs. Subdistribution hazard ratios (subHRs) for VTE were estimated adjusting for sociodemographic factors and acquired and inherited VTE risk factors. The VTE risk of nine disease clusters were investigated. Among 8,170,329 included individuals, 2,183,236 (26.72%) had primary care-diagnosed multimorbidity. Adjusted subHR for VTE among individuals with multimorbidity was 1.36 (95%CI 1.34-1.39). A dose-response association was observed, a subHR of 1.62 (95%CI 1.57-1.67) for individuals with ≥5 NCDs. There were significant interactions between multimorbidity and sex and country of birth. Seven of nine multimorbidity clusters were associated with increased VTE risk. Primary care-diagnosed multimorbidity is an independent, dose-dependent risk factor for VTE. The association between several disease-clusters and VTE suggests potential value in cluster-based risk prediction.
Cardiovascular disease remains the leading global cause of death, and the need for accurate, event-specific risk prediction is particularly critical in regions where long-horizon models perform poorly. We developed and internally validated a probabilistic model to estimate 6- and 12-month risk of acute myocardial infarction, with exploratory 5- and 10-year horizons, using routinely collected electronic health record data from an integrated cardiovascular cohort in Colombia. The study followed TRIPOD + AI guidance and analysed 382,589 patients contributing 3.9 million encounters. The modelling strategy combined a calibrated gradient-boosting classifier with an interpretable survival ensemble incorporating Cox regression, random survival forests, and discrete-time hazards. Primary outcomes were prediction accuracy, discrimination, calibration, and concordance with legacy score scales. The classifier achieved an AUC of 0.869, while 6- and 12-month survival models reached C-indices of 0.836 and 0.846. Calibration was strong, with predicted vs observed AMI counts nearly identical (O/E = 0.998). Concordance analyses demonstrated only moderate alignment with Framingham and PROCAM, indicating substantial re-ranking at short horizons compared with legacy long-term models. External, label-delayed validation (n = 5602) showed monotonic risk separation across predefined priority bands. This model provides a practical population-health stratification tool for short-term AMI risk, with particular value in resource-constrained settings. Recalibration to local incidence rates is recommended before deployment. Prospective evaluation is warranted to assess real-world clinical and operational impact.
Hypertensive disorders of pregnancy (HDP) are established precursors to future cardiovascular disease. Current guidelines endorse labetalol, nifedipine, and methyldopa as first-line antihypertensive therapies, but data on long-term maternal cardiovascular risk are limited. We evaluated five-year postpartum outcomes of HDP patients who were exposed to nifedipine or labetalol during pregnancy. We conducted a retrospective cohort study using the TriNetX US Collaborative Network. Patients were identified using ICD-10-CM codes for HDP-excluding those with pre-existing hypertension-and categorized by treatment with labetalol or nifedipine. Patients exposed to amlodipine or methyldopa were excluded. After 1:1 propensity score matching, we compared cardiovascular and renal outcomes over five years. Results are reported as adjusted odds ratios (aOR) with 95% confidence intervals (CI) and as hazard ratios (HR) from Kaplan-Meier survival analysis. After matching, 11,764 patients remained in each cohort (23,528 total). Nifedipine exposure was associated with lower odds of chronic hypertension (CH, aOR 0.835, 95% CI [0.778, 0.896], p < 0.001), heart failure (HF, aOR 0.699, 95% CI [0.527, 0.926], p = 0.012), HF with reduced ejection fraction (HFrEF, aOR 0.608, 95% CI [0.418, 0.886], p = 0.009), and chronic kidney disease (CKD, aOR 0.653, 95% CI [0.492, 0.867], p = 0.003) compared to labetalol. Time-to-event analysis confirmed these findings. Among HDP patients, nifedipine exposure during the index pregnancy was associated with lower five-year risks of CH, HF, HFrEF, and CKD compared with labetalol. These findings suggest that antihypertensive choice in pregnancy may differentially affect long-term maternal cardiovascular health.
South Asians experience premature acute myocardial infarction (AMI) at disproportionately high rates compared with Western populations, often despite modest LDL-cholesterol levels and contemporary lipid-lowering therapy. Lipoprotein(a) [Lp(a)], a genetically determined and causally implicated atherosclerotic cardiovascular disease risk factor, may contribute through proatherogenic and prothrombotic mechanisms. We evaluated associations between Lp(a), premature AMI, coronary angiographic severity, and percutaneous coronary intervention (PCI) outcomes, with emphasis on South Asian populations. A structured scoping review with quantitative meta-analytic components was conducted in accordance with PRISMA-ScR and PRISMA 2020 guidelines. PubMed, Scopus, and Web of Science were searched from inception through [Month Year]. Eligible studies included adult AMI or PCI cohorts reporting quantitative Lp(a) levels and relevant outcomes. Seventeen studies met inclusion criteria; three provided extractable data for exploratory random-effects meta-analysis using the DerSimonian-Laird method. Elevated Lp(a) showed a pooled risk ratio of 1.16 (95% CI 0.93-1.43; I2 = 24%) for major adverse cardiovascular events, with a consistent direction of effect. Qualitative synthesis linked higher Lp(a) to multivessel disease, higher SYNTAX score, greater thrombus burden, and recurrent post-PCI events. Mechanistic evidence supports roles in oxidized phospholipid transport and impaired fibrinolysis. South Asian cohorts showed higher Lp(a) levels and earlier disease onset. Elevated Lp(a) may contribute to angiographic severity and adverse PCI-era outcomes in premature AMI, supporting risk assessment in high-risk South Asian populations.