Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health pla...Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.展开更多
Rowlands et al.1present an analysis of accelerometer data from the UK Biobank cohort,examining variations in the duration,intensity,and accumulation of moderate-intensity physical activity(MPA)and vigorous-intensity p...Rowlands et al.1present an analysis of accelerometer data from the UK Biobank cohort,examining variations in the duration,intensity,and accumulation of moderate-intensity physical activity(MPA)and vigorous-intensity physical activity(VPA)sufficient to reduce the risk of all-cause mortality.In this study,the authors questioned if shorter durations(i.e.,1,2,3,4,5,10,15,and 20 min/day)of MPA and VPA performed continuously or accumulated throughout the day would equally reduce the risks of all-cause mortality as longer duration MPA and VPA recommended in the physical activity(PA)guidelines.展开更多
Objective This study aims to investigate the joint associations of sarcopenia and social isolation with mortality risk.Methods Using data from the Chinese Longitudinal Healthy Longevity Survey(CLHLS)and the UK Biobank...Objective This study aims to investigate the joint associations of sarcopenia and social isolation with mortality risk.Methods Using data from the Chinese Longitudinal Healthy Longevity Survey(CLHLS)and the UK Biobank,sarcopenia was diagnosed according to European and Asian Working Groups for Sarcopenia criteria.Social isolation was assessed using standardized questionnaires,including questions on solitude,frequency of social activities,contact with others,and marital status(for the CLHLS only).Results During the follow-up period,8,249 deaths occurred in the CLHLS and 26,670 deaths in the UK Biobank groups.While no significant interaction was observed between sarcopenia and social isolation in predicting all-cause mortality in the CLHLS cohort,the association between social isolation and mortality was stronger among individuals with sarcopenia in the UK Biobank(P-interaction=0.03,relative risk due to interaction:0.23,95%confidence interval[CI]:0.06–0.41).Further joint analyses showed that participants with sarcopenia and high levels of social isolation had the highest mortality risk(hazard ration[HR]:1.99;95%CI:[1.74–2.28]in the CLHLS and 1.69[1.55–1.85]in the UK Biobank)compared to those without either condition.Conclusion The combination of social isolation and sarcopenia synergistically increases the risk of mortality in middle-aged and older adults across diverse populations.展开更多
Objective:Early sepsis can be treated if recognised early,but progression to severe sepsis and septic shock and multiple organ dysfunction syndrome substantially increases mortality.The objectives of our study were to...Objective:Early sepsis can be treated if recognised early,but progression to severe sepsis and septic shock and multiple organ dysfunction syndrome substantially increases mortality.The objectives of our study were to assess morbidity and mortality of patients with sepsis and to compare the effectiveness of a simple bedside satisfiable Quick Sequential Organ Failure Assessment(qSOFA)score with National Early Warning Score(NEWS)in prognosticating sepsis.Methods:This prospective observational study was conducted among patients>18 years old presenting with sepsis at B.J.Medical College.The SOFA,qSOFA and NEWS scores were calculated.The effectiveness in predicting mortality was evaluated using receiver operating characteristic curve analysis.Results:A total of 200 patients were evaluated(56%male)with a mean age of 51.7 years.The mortality rate was 23%.Patients categorized under high risk according to SOFA score>8,qSOFA score of 2-3 and NEWS>7 had a mortality rate of 33.3%,27.5%and 28.4%,respectively.AUC for mortality prediction was 0.695 using SOFA score,0.665 using qSOFA and 0.725 using NEWS.At a cut off of 7.50,NEWS demonstrated a sensitivity of 97.8%with a specificity of 28.0%and outperformed both SOFA and qSOFA which yielded a sensitivity of 43.5%and 91.3%and a specificity of 77.9%and 27.9%,respectively.Conclusions:The NEWS score outperforms SOFA and qSOFA in predicting mortality among sepsis patients.However,qSOFA is more helpful in identifying high risk patients and performs better in intensive care setting.展开更多
BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suita...BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suitable for rapid clinical application.METHODS:In this multi-center retrospective cohort study,AAS patient data from three hospitals were analyzed.The modeling cohort included data from the First Affiliated Hospital of Zhengzhou University and the People’s Hospital of Xinjiang Uygur Autonomous Region,with Peking University Third Hospital data serving as the external test set.Four machine learning algorithms—logistic regression(LR),multilayer perceptron(MLP),Gaussian naive Bayes(GNB),and random forest(RF)—were used to develop predictive models based on 34 early-accessible clinical variables.A simplifi ed model was then derived based on fi ve key variables(Stanford type,pericardial eff usion,asymmetric peripheral arterial pulsation,decreased bowel sounds,and dyspnea)via Least Absolute Shrinkage and Selection Operator(LASSO)regression to improve ED applicability.RESULTS:A total of 929 patients were included in the modeling cohort,and 210 were included in the external test set.Four machine learning models based on 34 clinical variables were developed,achieving internal and external validation AUCs of 0.85-0.90 and 0.73-0.85,respectively.The simplifi ed model incorporating fi ve key variables demonstrated internal and external validation AUCs of 0.71-0.86 and 0.75-0.78,respectively.Both models showed robust calibration and predictive stability across datasets.CONCLUSION:Both kinds of models were built based on machine learning tools,and proved to have certain prediction performance and extrapolation.展开更多
Background:Sudden cardiac death(SCD)accounts for more than half of all sudden death cases,posing a significant health burden in China.However,epidemiological data on SCD are scarce due to the lack of a central data re...Background:Sudden cardiac death(SCD)accounts for more than half of all sudden death cases,posing a significant health burden in China.However,epidemiological data on SCD are scarce due to the lack of a central data registry and the heterogeneity of case definitions.This study aims to provide reliable estimates of the incidence and risk factors of SCD in China at the national and regional levels from 2013 to 2021,as well as the current status of prevention.Methods:The multi-cause mortality data from 2013 to 2021 were obtained from the National Mortality Surveillance System of China.Deaths related to cardiac arrest were identified.Crude and age-standardized mortality rates(ASMR)were calculated by time,and region.Joint point regression was applied to identify significant changes during the study period.Subgroup analyses and multilevel negative binomial analysis were performed to understand the SCD risk factors.The first-line prevention measures and their current implementation in China and developed countries were also determined from published articles.Results:From 2013 to 2021,the crude mortality rate of sudden cardiac arrest increased markedly from 8.36 deaths per 100,000 population in 2013 to 18.59 deaths per 100,000 population in 2021.There were considerable differences among regions.Subgroup analysis and negative binomial regression results indicated that males and the elderly were at higher risk of SCD.SCD may be associated with poor medical conditions.More than half of SCDs occurred outside hospitals,and approximately 60%of SCDs were related to ischemic heart disease as the underlying cause.Currently,developed countries have widely adopted primary prevention and emergency treatment measures;however,the utilization rate of such measures in China is relatively low and should be improved.Conclusions:With the continuous rise in the prevalence of cardiovascular diseases and their related risk factors in China,the burden of SCD is expected to increase.In addition to strengthening the clinical pathways for sudden cardiac arrest cases in pre-hospital and hospital settings,it is also necessary to enhance public awareness,knowledge and first-line practical training through large-scale policies for governmental and community-based projects.展开更多
Objective To determine whether frailty is a risk factor for hospitalization and mortality in older adults enrolled in the "Chronic Heart Failure Program" at a hospital in Lima, Peru, between 2018–2021.Metho...Objective To determine whether frailty is a risk factor for hospitalization and mortality in older adults enrolled in the "Chronic Heart Failure Program" at a hospital in Lima, Peru, between 2018–2021.Methods This was an ambispective cohort study. A total of 85 older adults participating in the Chronic Heart Failure Program at Guillermo Almenara National Hospital were included. Each had an initial frailty assessment, forming two cohorts: frail and non-frail older adults. Medical records were reviewed, and patients were followed for one year to track events of interest(hospitalization and mortality). Overall survival and risk factors for hospitalization and death were determined.Results During follow-up, 15.3% of the older adults died, and frailty was identified in 58.8% of the patients. Overall survival using the Kaplan-Meier method was 96.5% at 3 months after entering the Chronic Heart Failure Program;92.9% at 6 months;and85.9% at one year. Multivariate analysis using Poisson regression found that frailty was not a risk factor for hospitalization(a RR =0.92;95% CI: 0.42–2.03). Survival analysis using the Cox proportional hazards model showed that frailty was also not a risk factor for mortality after one year of follow-up(a HR = 1.32;95% CI: 0.27–6.53).Conclusions Our research does not confirm frailty as a risk factor for hospitalization or mortality in older adults enrolled in the“Chronic Heart Failure Program” after one year of follow-up.展开更多
Sepsis poses a serious threat to patient survival,making timely risk assessment crucial.Predicting in-hospital mortality based on clinical indicators can aid in making better clinical decisions.Previous studies have f...Sepsis poses a serious threat to patient survival,making timely risk assessment crucial.Predicting in-hospital mortality based on clinical indicators can aid in making better clinical decisions.Previous studies have focused on classifier selection but lacked a comprehensive analysis of feature selection and data preprocessing.This study optimized machine learning models for sepsis mortality prediction by:(1)comprehensively comparing feature selection and classification methods to identify the best combination,(2)building a high-performing model with fewer features,and(3)identifying key clinically relevant indicators.Methods:Using the MIMIC-III sepsis cohort,we conducted a comprehensive analysis to determine the optimal model,including data preprocessing,data balance,classifier selection,and feature selection.Feature importance was further analyzed to identify the key predictors of in-hospital mortality.Results:The proposed Synthetic Minority Oversampling Technique-Random Forest Recursive Feature Elimination-Extreme Gradient Boosting(SMOTE-(RF-RFE)-XGB)model achieved high predictive performance with a mean Area Under the Curve(AUC)of 0.8507,while reducing the number of features from 78 to 39.Compared to other feature selection methods evaluated in this study and those reported in related literature,Random Forest Recursive Feature Elimination(RF-RFE)offers the best trade-off between accuracy,feature compactness,and stability.Additionally,feature importance rankings consistently identified Acute Physiology Score Ⅲ(APS Ⅲ),Ventilation on First Day,and Depression as the top three most influential predictors,besides the Length of Stay in ICU and Hospital.Conclusions:This study addresses key gaps by conducting a comprehensive evaluation of classifiers and feature selection methods for predicting in-hospital mortality in patients with sepsis.The proposed SMOTE-(RFRFE)-XGB model achieved a high predictive performance and stability with a compact feature set.APS III,Ventilation on First Day,and Depression were consistently identified as key predictors besides Length of Stay in ICU and Hospital.展开更多
Objective:Heart failure(HF)is a complex clinical syndrome that affects nearly 64 million individuals globally.Frequent hospital readmissions lead to poor health outcomes,impact quality of life(QoL),and are associated ...Objective:Heart failure(HF)is a complex clinical syndrome that affects nearly 64 million individuals globally.Frequent hospital readmissions lead to poor health outcomes,impact quality of life(QoL),and are associated with high mortality rates.This study assessed readmissions,mortality,and QoL outcomes in patients with HF in a tertiary care hospital setting.Methods:Patients aged≥18 years with HF,who visited the tertiary care hospital in Karad,India were included in the study(November2019 to October 2021).Demographics,disease characteristics,and condition at discharge were recorded using the medical records of patients.The quantitative data included readmission rates and mortality rates.The qualitative aspects describing patients'QoL were assessed using a patient-reported 21-question QoL questionnaire.Results:A total of 98 patients,predominantly male(63.3%),with a mean age of 62.9 years were included.The majority of the patients(80.6%)required<15 days of hospitalization.The 2-year readmission rate was 24.4%,while the mortality rate was 43.9%.Self-care pattern showed that patients seemed to be taking mild to average care while taking good care was rare.The QoL data showed that 22.4% were living a good quality life,44.9% average,while 32.7% were living a low-quality life.Better education and better self-care were associated with a low rate of readmission.Conclusions:We were able to assess the incidence of readmission,mortality,and QoL in patients with HF in a tertiary care hospital setting.The study showed that HF impacts patients'physical,emotional,and psychological wellbeing.展开更多
BACKGROUND:Rapid identification of patients at risk of clinical deterioration(in-hospital mortality) in emergency settings is essential for timely and appropriate care.Existing prognostic scores,such as the Acute Phys...BACKGROUND:Rapid identification of patients at risk of clinical deterioration(in-hospital mortality) in emergency settings is essential for timely and appropriate care.Existing prognostic scores,such as the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),Simplified Acute Physiology Score 3(SAPS 3),Sequential Organ Failure Assessment(SOFA),and National Early Warning Score 2(NEWS 2),have limitations in emergency scenarios,particularly in resource-limited settings.We aimed to develop a simple and efficient tool tailored to the Brazilian healthcare system.METHODS:This retrospective,multicenter,cohort study analyzed data from 50,709 adult patients admitted to 12 hospitals in southern and southeastern Brazil between 2019 and 2020.The BRASIL score(Brazilian Risk Assessment Severity Index and Length of stay) was constructed using demographic and clinical variables available at admission.Logistic regression was used to determine the weight of each variable,and each variable was assigned a point value based on its β-coefficient and clinical relevance,with thresholds defined according to established medical cutoffs and statistical performance.The score's predictive accuracy was validated using the area under the receiver operating characteristic curve(AUC) with comparative analysis against NEWS 2.RESULTS:The BRASIL score,including age,sex,respiratory rate,heart rate,oxygen saturation,blood pressure,and body temperature,was derived through variables independently associated with in-hospital mortality in a multicenter cohort.The total score was stratified into three risk categories — low(0–3 points),moderate(4–7 points),and high(>7 points) — using observed inflection points in mortality distribution to optimize discrimination.This stratification demonstrated a stepwise increase in mortality rates across categories and the discriminatory performance,with an overall AUC of 0.743(95% CI:0.726–0.761).Compared to NEWS 2(AUC 0.697,95% CI:0.683–0.711),the BRASIL score offered superior early risk identification,supporting timely clinical decisionmaking and resource allocation in the emergency setting.CONCLUSION:The BRASIL score is a novel tool for predicting in-hospital mortality in emergency departments.Its predictive performance and ease of use suggest that it has the potential to improve patient outcomes.展开更多
Background:Although light-intensity physical activity(LPA)has been suggested to be associated with a lower risk of mortality,the minimal and optimal volumes of LPA remain unclear.We aimed to examine the minimal and op...Background:Although light-intensity physical activity(LPA)has been suggested to be associated with a lower risk of mortality,the minimal and optimal volumes of LPA remain unclear.We aimed to examine the minimal and optimal volumes of LPA associated with the risks of mortality and disease incidence(i.e.,cardiovascular diseases and cancer).Methods:Data were derived from the population-based UK Biobank cohort study,including 69,492 adults aged 43-78 years.Accelerometermeasured LPA was defined using a validated,published machine learning-based Random Forest activity method,which was categorized into 4 quartile groups.All-cause and cause-specific mortality(cardiovascular disease-and cancer-specific)were determined according to the International Classification of Diseases,10th version codes.Disease incidence was defined based on primary care,hospitalization,or death records.Results:During a median follow-up period of 8.04 years,2024 adults died from all causes,539 from cardiovascular disease,and 1175 from cancer.For all-cause mortality,compared with participants in the lowest quartile of LPA(<3.9 h/day),the hazard ratios(HRs)and 95%confidence intervals(95%CIs)were 0.82(95%CI:0.73-0.93)for those with 3.9 to<5.0 h/day,0.75(95%CI:0.66-0.85)for those with 5.0 to<6.1 h/day,and 0.77(95%CI:0.68-0.88)for those with≥6.1 h/day,respectively.There was an inverse non-linear dose-response association between LPA and all-cause mortality,with an optimal dose of 5.72 h/day(95%CI:5.45-6.41;HR=0.63,95%CI:0.56-0.71)and a minimal dose of 3.59 h/day(95%CI:3.53-8.56;HR=0.81,95%CI:0.78-0.86),with the 5th percentile as the reference.Similar patterns were observed for cause-specific mortality and disease incidence(cardiovascular disease and cancer).Conclusion:Engaging in LPA for~3.5 h/day was conservatively associated with lower risk of mortality and disease incidence,with further risk reductions observed up to an optimal dose of~6.0 h/day.These findings suggest that sufficient LPA offers important health benefits,which can inform the development of future PA guidelines.展开更多
BACKGROUND:Serum osmolality is a prognostic indicator in critically ill patients.This study aimed to evaluate the association between high osmolality and 28-day mortality in patients with cardiac arrest(CA)admitted to...BACKGROUND:Serum osmolality is a prognostic indicator in critically ill patients.This study aimed to evaluate the association between high osmolality and 28-day mortality in patients with cardiac arrest(CA)admitted to the intensive care unit(ICU).METHODS:Baseline data of adult patients with CA who were admitted to the ICU from 2008 to 2019 were collected from the Medical Information Mart for Intensive Care(MIMIC)-IV.Patients were divided into survivor and non-survivor groups according to the 28-day prognosis.Serum concentrations of sodium,potassium,glucose,and urea nitrogen on the fi rst day of ICU admission were used to determine serum osmolarity.The primary endpoint of this study was 28-day all-cause mortality.Propensity score matching(PSM)analysis was performed to reduce bias between the survivor and nonsurvivor groups.RESULTS:Among the 798 included CA patients,the high osmolarity on the first day of ICU admission remained significantly associated with increased 28-day mortality(62.0%vs.35.5%,P<0.001)and reduced cumulative survival(log-rank P<0.05)after PSM.Cox regression identifi ed the high osmolarity on the fi rst day of ICU admission as an independent predictor.High serum osmolarity on the fi rst day of ICU admission eff ectively predicted 1-,3-,7-,and 28-day all-cause mortality,with the strongest predictive performance for 1-day mortality both before and after PSM(all P<0.05).CONCLUSION:In this study,elevated serum osmolarity on the first day of ICU admission was independently associated with increased 28-day mortality in CA patients and could serve as a prognostic marker.展开更多
BACKGROUND Acute pancreatitis(AP)is a severe condition,and abdominal effusion is a significant predictor of its severity and prognosis.However,the relationship between ascites characteristics and AP outcomes remains u...BACKGROUND Acute pancreatitis(AP)is a severe condition,and abdominal effusion is a significant predictor of its severity and prognosis.However,the relationship between ascites characteristics and AP outcomes remains undefined.AIM To assess the correlation between ascites characteristics and clinical prognosis in AP patients by comparing color depth and turbidity of early ascites.METHODS This study included 667 AP patients with ascites,categorized by color and turbidity into yellow clear(n=54),yellow turbid(n=293),red brown(n=320).The trendχ2 test was employed to analyze the incidence of organ failure(OF),infected pancreatic necrosis(IPN),and mortality across groups.Receiver operating charac teristic(ROC)curves were used to evaluate the predictive value of ascites cell count,amylase,protein,and lactate dehydrogenase(LDH)for abdominal compartment syndrome(ACS)and intra-abdominal hemorrhage.RESULTS AP patients with ascites exhibited higher scores of scoring systems(such as Bedside index for severity in AP,Acute Physiology and Chronic Health Examination II,etc.)and increased complications and mortality rates(all P<0.05)compared to those without ascites.A linear association was observed between ascites color depth and turbidity and the incidence of OF,pancreatic necrosis,IPN,and mortality(P<0.05).LDH in ascites demonstrated high accuracy in predicting ACS and intra-abdominal hemorrhage,with areas under the ROC curve of 0.77 and 0.79,respectively.CONCLUSION Early in AP,ascites correlates with OF,IPN,and mortality,showing linear associations with color depth and turbidity.Ascitic LDH reliably predicts ACS and intra-abdominal hemorrhage in AP patients.展开更多
BACKGROUND:Electrolyte imbalance is common following traumatic brain injury(TBI)and can significantly impact patient outcomes.We aimed to explore the occurrence,patterns,and consequences of electrolyte imbalance in ad...BACKGROUND:Electrolyte imbalance is common following traumatic brain injury(TBI)and can significantly impact patient outcomes.We aimed to explore the occurrence,patterns,and consequences of electrolyte imbalance in adult patients with TBI.METHODS:A retrospective study was conducted from 2016 to 2021 at a level 1 trauma center among hospitalized TBI patients.On admission,the levels of serum electrolytes,including sodium,potassium,calcium,magnesium,and phosphate,were analyzed.Demographics,injury characteristics,and interventions were assessed.The primary outcome was the in-hospital mortality.Multivariate logistic regression analysis was performed to identify independent predictors of mortality in TBI patients.RESULTS:A total of 922 TBI patients were included in the analysis,of whom 902(98%)had electrolyte imbalance.The mean age of patients with electrolyte imbalance was 32.0±15.0 years.Most patients were males(94%).The most common electrolyte abnormalities were hypocalcemia,hypophosphatemia,and hypokalemia.The overall in-hospital mortality rate was 22%in the entire cohort.In multivariate logistic analysis,the predictors of mortality included age(odds ratio[OR]=1.029,95%confidence intervals[CI]:1.013-1.046,P<0.001),low GCS(OR=0.883,95%CI:0.816-0.956,P=0.002),high Injury Severity Score(ISS)scale(OR=1.051,95%CI:1.026-1.078,P<0.001),hypernatremia(OR=2.175,95%CI:1.196-3.955,P=0.011),hyperkalemia(OR=4.862,95%CI:1.222-19.347;P=0.025),low serum bicarbonate levels(OR=0.926,95%CI:0.868-0.988,P=0.020),high serum lactate levels(OR=1.128,95%CI:1.022-1.244,P=0.017),high glucose levels(OR=1.072,95%CI:1.014-1.133,P=0.015),a longer activated partial thromboplastin time(OR=1.054,95%CI:1.024-1.084,P<0.001)and higer international normalized ratio(INR)(OR=3.825,95%CI:1.592-9.188,P=0.003).CONCLUSION:Electrolyte imbalance is common in TBI patients,with the significant prevalence of hypocalcemia,hypophosphatemia,and hypokalemia.However,hypernatremia and hyperkalemia were associated with the risk of mortality,emphasizing the need for further research to comprehend electrolyte dynamics in TBI patients.展开更多
Climate change has significantly increased the frequency and severity of droughts and risk of tree death worldwide.Differences in leaf habit,plant size,and species diversity are associated with differences in the risk...Climate change has significantly increased the frequency and severity of droughts and risk of tree death worldwide.Differences in leaf habit,plant size,and species diversity are associated with differences in the risk of drought-induced mortality,but the relative contributions of these factors to the risk of mortality are unclear.In a study of the mortality of tree and shrub species during the extreme drought of 2019 in a savanna ecosystem in Southwest China,we assessed the relative contributions of evergreen and deciduous leaf habit,plant size,and species richness and diversity to the mortality of shrubs and trees after the 2019 extreme drought.The deciduous species had significantly lower hydraulic safety margins than the coexisting evergreen species,resulting in a higher mortality risk.Additionally,species and individuals with taller canopies tended to have deeper root systems,an advantage during extreme drought that reduced mortality risk.Notably,mortality risk was largely independent of stand species richness and diversity.Overall,leaf habit and plant height were better predictors of mortality risk than species richness and diversity.These novel insights provide a better understanding of the mechanisms driving drought-induced mortality in the ecosystems with a low canopy and weak interspecific and intraspecific competition for shared resources.Leaf habit and tree size should be incorporated into hypotheses on the mechanisms underlying drought-induced tree mortality.展开更多
BACKGROUND The non-high-density lipoprotein cholesterol(non-HDL-C)/HDL-C ratio(NHHR)is linked to cardiovascular event risk,but its prognostic value in diabetes mellitus(DM)patients remains unclear.AIM To explore the a...BACKGROUND The non-high-density lipoprotein cholesterol(non-HDL-C)/HDL-C ratio(NHHR)is linked to cardiovascular event risk,but its prognostic value in diabetes mellitus(DM)patients remains unclear.AIM To explore the association of NHHR and cardiovascular mortality in patients with DM and generate predictive model.METHODS This cohort study analyzed data from 8425 DM patients in National Health and Nutrition Examination Survey.NHHR was calculated as(total cholesterol-HDLC)/HDL-C.Cardiovascular mortality was determined via the National Death Index.Feature selection was performed using the Boruta algorithm and least absolute shrinkage and selection operator regression,followed by Cox proportional hazards models to evaluate NHHR’s relationship with cardiovascular mortality.Stratified and sensitivity analyses assessed the findings’robustness.A nomogram was developed to predict cardiovascular mortality,with model performance evaluated using receiver operating characteristic curves and calibration plots.RESULTS Over an average follow-up of 94.2 months,671 cardiovascular deaths(8.0%)occurred.Six key features including age,education,ethnicity,poverty-income ratio,history of heart failure,and NHHR,were selected.A non-linear association was found,with the highest NHHR quartile showing a 39%higher risk of cardiovascular death compared to the lowest quartile(Q4,hazard ratio:1.39,95%confidence interval:1.11-1.73).Stratified analyses confirmed the increased risk across all subgroups.Sensitivity analyses supported the stability of the results.The nomogram for predicting cardiovascular mortality demonstrated high accuracy.CONCLUSION Elevated NHHR is associated with increased cardiovascular mortality risk in DM patients.NHHR could be a valuable prognostic marker,aiding in identifying high-risk patients and guiding targeted lipid management strategies.展开更多
OBJECTIVE To investigate possible associations between physical function assessment scales,such as Short Physical Performance Battery(SPPB)and Berg Balance Scale(BBS),with all-cause mortality in acute decompensated he...OBJECTIVE To investigate possible associations between physical function assessment scales,such as Short Physical Performance Battery(SPPB)and Berg Balance Scale(BBS),with all-cause mortality in acute decompensated heart failure(ADHF)patients.METHODS A total of 108 ADHF patients were analyzed from October 2020 to October 2022,and followed up to May 2023.The association between baseline clinical characteristics and all-cause mortality was analyzed by univariate Cox regression analysis,while for SPPB and BBS,univariate Cox regression analysis was followed by receiver operating characteristic curves,in which the area under the curve represented their predictive accuracy for all-cause mortality.Incremental predictive values for both physical function assessments were measured by calculating net reclassification index and integrated discrimination improvement scores.Optimal cutoff value for BBS was then identified using restricted cubic spline plots,and survival differences below and above that cut-off were compared using Kaplan-Meier survival curves and the log-rank test.The clinical utility of BBS was measured using decision curve analysis.RESULTS For baseline characteristics,age,female,blood urea nitrogen,as well as statins,angiotensin-converting enzyme inhibitors,angiotensin II receptor blockers,or angiotensin receptor-neprilysin inhibitors,were predictive for all-cause mortality for ADHF patients.With respect to SPPB and BBS,higher scores were associated with lower all-cause mortality rates for both assessments;similar area under the curves were measured for both(0.774 for SPPB and 0.776 for BBS).Furthermore,BBS≤36.5 was associated with significantly higher mortality,which was still applicable even adjusting for confounding factors;BBS was also found to have great clinical utility under decision curve analysis.CONCLUSIONS BBS or SPPB could be used as tools to assess physical function in ageing ADHF patients,as well as prognosticate on all-cause mortality.Moreover,prioritizing the improvement of balance capabilities of ADHF patients in cardiac rehabilitation regimens could aid in lowering mortality risk.展开更多
BACKGROUND Proton pump inhibitors(PPIs)are widely used,including among cancer patients,to manage gastroesophageal reflux and other gastric acid-related disorders.Recent evidence suggests associations between long-term...BACKGROUND Proton pump inhibitors(PPIs)are widely used,including among cancer patients,to manage gastroesophageal reflux and other gastric acid-related disorders.Recent evidence suggests associations between long-term PPI use and higher risks for various adverse health outcomes,including greater mortality.AIM To investigate the association between PPI use and all-cause mortality among cancer patients by a comprehensive analysis after adjustment for various confounders and a robust methodological approach to minimize bias.METHODS This retrospective cohort study used data from the TriNetX research network,with electronic health records from multiple healthcare organizations.The study employed a new-user,active comparator design,which compared newly treated PPI users with non-users and newly treated histamine2 receptor antagonists(H2RA)users among adult cancer patients.Newly prescribed PPIs(esomeprazole,lansoprazole,omeprazole,pantoprazole,or rabeprazole)users were compared to non-users or newly prescribed H2RAs(cimetidine,famotidine,nizatidine,or ranitidine)users.The primary outcome was all-cause mortality.Each patient in the main group was matched to a patient in the control group using 1:1 propensity score matching to reduce confounding effects.Multivariable Cox regression models were used to estimate hazard ratios(HRs)and 95% confidence interval(CI).RESULTS During the follow-up period(median 5.4±1.8 years for PPI users and 6.5±1.0 years for non-users),PPI users demonstrated a higher all-cause mortality rate than non-users after 1 year,2 years,and at the end of follow up(HRs:2.34-2.72).Compared with H2RA users,PPI users demonstrated a higher rate of all-cause mortality HR:1.51(95%CI:1.41-1.69).Similar results were observed across sensitivity analyses by excluding deaths from the first 9 months and 1-year post-exposure,confirming the robustness of these findings.In a sensitivity analysis,we analyzed all-cause mortality outcomes between former PPI users and individuals who have never used PPIs,providing insights into the long-term effects of past PPI use.In addition,at 1-year follow-up,the analysis revealed a significant difference in mortality rates between former PPI users and non-users(HR:1.84;95%CI:1.82-1.96).CONCLUSION PPI use among cancer patients was associated with a higher risk of all-cause mortality compared to non-users or H2RA users.These findings emphasize the need for cautious use of PPIs in cancer patients and suggest that alternative treatments should be considered when clinically feasible.However,further studies are needed to corroborate our findings,given the significant adverse outcomes in cancer patients.展开更多
This editorial comments on the article by Desai et al,which investigates the impact of coronavirus disease 2019(COVID-19)on in-hospital mortality among patients with recurrent stroke using data from the 2020 National ...This editorial comments on the article by Desai et al,which investigates the impact of coronavirus disease 2019(COVID-19)on in-hospital mortality among patients with recurrent stroke using data from the 2020 National Inpatient Sample.The findings reveal significantly higher mortality rates in COVID-19-positive patients compared to non-COVID-19 patients,particularly among middle-aged individuals,males,and ethnic minorities.This editorial explores the underlying mechanisms contributing to these outcomes and discusses the clinical implications for targeted management strategies in high-risk groups.The results emphasize the need for comprehensive approaches to mitigate the heightened risks faced by recurrent stroke patients during the COVID-19 pandemic.展开更多
BACKGROUND Ovarian carcinoma has the highest mortality rate among all gynecological cancers.Several reproductive and hormonal risk factors,including early menarche,late menopause,limited use of oral contraceptives,and...BACKGROUND Ovarian carcinoma has the highest mortality rate among all gynecological cancers.Several reproductive and hormonal risk factors,including early menarche,late menopause,limited use of oral contraceptives,and a low pregnancy rate,have been identified as contributors to the increased susceptibility to ovarian cancer.Advancements in cancer therapy over the past century,including the emergence of precision oncology,underscore the importance of early detection and tailored interventions,factors particularly critical in ovarian cancer,where late-stage diagnosis remains a persistent barrier to survival.This challenge is compounded by the lack of a universally endorsed screening program,resulting in late-stage identification and widespread metastasis.AIM To evaluate demographic differences in ovarian cancer-related mortality from 1999 to 2020 among adult females aged≥25 years within the United States.METHODS Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database was used to collect de-identified death certificate data for malignant neoplasm of the ovaries related deaths in female adults aged 25 years and older from the year 1999 to 2020.Crude mortality rates and age-adjusted mortality rates(AAMRs)per 100000 people were calculated.Join point regression program was used to assess annual percent changes in mortality trends,with statistical significance set at P value<0.05.RESULTS Between 1999 and 2020,337619 deaths due to ovarian cancer occurred among United States females aged 25 to>85.The AAMR decreased from 14.62 in 1999 to 10.15 in 2020,with significant declines across various demographics.The AAMRs were highest among non-Hispanic White women,i.e.,13.53.Based on region,they were the highest in the Northeast(13.06)and Midwest(12.94).The steepest decline was observed in metropolitan areas as compared to nonmetropolitan ones.The study highlights significant progress in reducing ovarian cancer mortality across age,race/ethnicity,and geographic regions during this period.CONCLUSION The mortality trends for ovarian carcinoma patients showed an overall decrease,with the highest mortality rates observed among older individuals(65 to>85 years)and non-Hispanic Whites.These disparities underscore the need for equitable healthcare access and targeted policy interventions.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.42225104)CAS Project for Young Scientists in Basic Research(Grant No.YSBR-086).
文摘Urban populations are increasingly exposed to extreme heat due to climate change and rapid urbanization,heightening health risks in cities worldwide.Accurate heat exposure assessment is essential for public health planning and risk reduction.Most existing approaches rely on a single threshold temperature(e.g.,35℃of daily max temperature),applied uniformly to the entire population.However,this one-size-fits-all assumption overlooks substantial differences in heat sensitivity across population subgroups.In this study,we address this limitation by quantifying subgroup-specific temperature-mortality relationships and using corresponding minimum mortality temperatures(MMTs)to assess heat exposure.Results show that the population-wide MMT was 27.5℃,but it varied greatly across population subgroups.The elderly population(≥65)had an MMT of 24.6℃,much lower than the 28.6℃observed in younger individuals(<65).Females also exhibited a lower MMT that males(25℃versus 28.2℃).However,educational attainment did not significantly affect MMT.Using a uniform MMT resulted in substantial underestimation of heat exposure,ranging from 25.3%in 1990 to 13.9%in 2020,reflecting demographic shifts over time.Spatially,nearly half of the city experienced underestimated heat risk,especially in central and northeastern regions where heat-vulnerable populations are concentrated.These findings underscore the need for more nuanced heat exposure assessments that account for demographic and spatial variability,paving the way for targeted public health interventions to protect the most vulnerable urban populations.
文摘Rowlands et al.1present an analysis of accelerometer data from the UK Biobank cohort,examining variations in the duration,intensity,and accumulation of moderate-intensity physical activity(MPA)and vigorous-intensity physical activity(VPA)sufficient to reduce the risk of all-cause mortality.In this study,the authors questioned if shorter durations(i.e.,1,2,3,4,5,10,15,and 20 min/day)of MPA and VPA performed continuously or accumulated throughout the day would equally reduce the risks of all-cause mortality as longer duration MPA and VPA recommended in the physical activity(PA)guidelines.
基金supported by grants from the National Key Research and Development Program of China(No.2023YFC3606300,No.2022YFC3600300)the National Natural Science Foundation of China(No.82325043)the National Key Research and Development Program of Hubei Province(2022BCA036)。
文摘Objective This study aims to investigate the joint associations of sarcopenia and social isolation with mortality risk.Methods Using data from the Chinese Longitudinal Healthy Longevity Survey(CLHLS)and the UK Biobank,sarcopenia was diagnosed according to European and Asian Working Groups for Sarcopenia criteria.Social isolation was assessed using standardized questionnaires,including questions on solitude,frequency of social activities,contact with others,and marital status(for the CLHLS only).Results During the follow-up period,8,249 deaths occurred in the CLHLS and 26,670 deaths in the UK Biobank groups.While no significant interaction was observed between sarcopenia and social isolation in predicting all-cause mortality in the CLHLS cohort,the association between social isolation and mortality was stronger among individuals with sarcopenia in the UK Biobank(P-interaction=0.03,relative risk due to interaction:0.23,95%confidence interval[CI]:0.06–0.41).Further joint analyses showed that participants with sarcopenia and high levels of social isolation had the highest mortality risk(hazard ration[HR]:1.99;95%CI:[1.74–2.28]in the CLHLS and 1.69[1.55–1.85]in the UK Biobank)compared to those without either condition.Conclusion The combination of social isolation and sarcopenia synergistically increases the risk of mortality in middle-aged and older adults across diverse populations.
文摘Objective:Early sepsis can be treated if recognised early,but progression to severe sepsis and septic shock and multiple organ dysfunction syndrome substantially increases mortality.The objectives of our study were to assess morbidity and mortality of patients with sepsis and to compare the effectiveness of a simple bedside satisfiable Quick Sequential Organ Failure Assessment(qSOFA)score with National Early Warning Score(NEWS)in prognosticating sepsis.Methods:This prospective observational study was conducted among patients>18 years old presenting with sepsis at B.J.Medical College.The SOFA,qSOFA and NEWS scores were calculated.The effectiveness in predicting mortality was evaluated using receiver operating characteristic curve analysis.Results:A total of 200 patients were evaluated(56%male)with a mean age of 51.7 years.The mortality rate was 23%.Patients categorized under high risk according to SOFA score>8,qSOFA score of 2-3 and NEWS>7 had a mortality rate of 33.3%,27.5%and 28.4%,respectively.AUC for mortality prediction was 0.695 using SOFA score,0.665 using qSOFA and 0.725 using NEWS.At a cut off of 7.50,NEWS demonstrated a sensitivity of 97.8%with a specificity of 28.0%and outperformed both SOFA and qSOFA which yielded a sensitivity of 43.5%and 91.3%and a specificity of 77.9%and 27.9%,respectively.Conclusions:The NEWS score outperforms SOFA and qSOFA in predicting mortality among sepsis patients.However,qSOFA is more helpful in identifying high risk patients and performs better in intensive care setting.
基金supported by the special fund of the National Clinical Key Specialty Construction Program[(2022)301-2305].
文摘BACKGROUND:This study aims to develop and validate a machine learning-based in-hospital mortality predictive model for acute aortic syndrome(AAS)in the emergency department(ED)and to derive a simplifi ed version suitable for rapid clinical application.METHODS:In this multi-center retrospective cohort study,AAS patient data from three hospitals were analyzed.The modeling cohort included data from the First Affiliated Hospital of Zhengzhou University and the People’s Hospital of Xinjiang Uygur Autonomous Region,with Peking University Third Hospital data serving as the external test set.Four machine learning algorithms—logistic regression(LR),multilayer perceptron(MLP),Gaussian naive Bayes(GNB),and random forest(RF)—were used to develop predictive models based on 34 early-accessible clinical variables.A simplifi ed model was then derived based on fi ve key variables(Stanford type,pericardial eff usion,asymmetric peripheral arterial pulsation,decreased bowel sounds,and dyspnea)via Least Absolute Shrinkage and Selection Operator(LASSO)regression to improve ED applicability.RESULTS:A total of 929 patients were included in the modeling cohort,and 210 were included in the external test set.Four machine learning models based on 34 clinical variables were developed,achieving internal and external validation AUCs of 0.85-0.90 and 0.73-0.85,respectively.The simplifi ed model incorporating fi ve key variables demonstrated internal and external validation AUCs of 0.71-0.86 and 0.75-0.78,respectively.Both models showed robust calibration and predictive stability across datasets.CONCLUSION:Both kinds of models were built based on machine learning tools,and proved to have certain prediction performance and extrapolation.
基金supported by the Sci-Tech Innovation 2030 Agenda(2023ZD0503900,2023ZD0503901)the Provincial Natural Science Foundation of Hunan(2024JJ8118)the Central South University Innovation-Driven Research Program(2023CXQD007).
文摘Background:Sudden cardiac death(SCD)accounts for more than half of all sudden death cases,posing a significant health burden in China.However,epidemiological data on SCD are scarce due to the lack of a central data registry and the heterogeneity of case definitions.This study aims to provide reliable estimates of the incidence and risk factors of SCD in China at the national and regional levels from 2013 to 2021,as well as the current status of prevention.Methods:The multi-cause mortality data from 2013 to 2021 were obtained from the National Mortality Surveillance System of China.Deaths related to cardiac arrest were identified.Crude and age-standardized mortality rates(ASMR)were calculated by time,and region.Joint point regression was applied to identify significant changes during the study period.Subgroup analyses and multilevel negative binomial analysis were performed to understand the SCD risk factors.The first-line prevention measures and their current implementation in China and developed countries were also determined from published articles.Results:From 2013 to 2021,the crude mortality rate of sudden cardiac arrest increased markedly from 8.36 deaths per 100,000 population in 2013 to 18.59 deaths per 100,000 population in 2021.There were considerable differences among regions.Subgroup analysis and negative binomial regression results indicated that males and the elderly were at higher risk of SCD.SCD may be associated with poor medical conditions.More than half of SCDs occurred outside hospitals,and approximately 60%of SCDs were related to ischemic heart disease as the underlying cause.Currently,developed countries have widely adopted primary prevention and emergency treatment measures;however,the utilization rate of such measures in China is relatively low and should be improved.Conclusions:With the continuous rise in the prevalence of cardiovascular diseases and their related risk factors in China,the burden of SCD is expected to increase.In addition to strengthening the clinical pathways for sudden cardiac arrest cases in pre-hospital and hospital settings,it is also necessary to enhance public awareness,knowledge and first-line practical training through large-scale policies for governmental and community-based projects.
文摘Objective To determine whether frailty is a risk factor for hospitalization and mortality in older adults enrolled in the "Chronic Heart Failure Program" at a hospital in Lima, Peru, between 2018–2021.Methods This was an ambispective cohort study. A total of 85 older adults participating in the Chronic Heart Failure Program at Guillermo Almenara National Hospital were included. Each had an initial frailty assessment, forming two cohorts: frail and non-frail older adults. Medical records were reviewed, and patients were followed for one year to track events of interest(hospitalization and mortality). Overall survival and risk factors for hospitalization and death were determined.Results During follow-up, 15.3% of the older adults died, and frailty was identified in 58.8% of the patients. Overall survival using the Kaplan-Meier method was 96.5% at 3 months after entering the Chronic Heart Failure Program;92.9% at 6 months;and85.9% at one year. Multivariate analysis using Poisson regression found that frailty was not a risk factor for hospitalization(a RR =0.92;95% CI: 0.42–2.03). Survival analysis using the Cox proportional hazards model showed that frailty was also not a risk factor for mortality after one year of follow-up(a HR = 1.32;95% CI: 0.27–6.53).Conclusions Our research does not confirm frailty as a risk factor for hospitalization or mortality in older adults enrolled in the“Chronic Heart Failure Program” after one year of follow-up.
文摘Sepsis poses a serious threat to patient survival,making timely risk assessment crucial.Predicting in-hospital mortality based on clinical indicators can aid in making better clinical decisions.Previous studies have focused on classifier selection but lacked a comprehensive analysis of feature selection and data preprocessing.This study optimized machine learning models for sepsis mortality prediction by:(1)comprehensively comparing feature selection and classification methods to identify the best combination,(2)building a high-performing model with fewer features,and(3)identifying key clinically relevant indicators.Methods:Using the MIMIC-III sepsis cohort,we conducted a comprehensive analysis to determine the optimal model,including data preprocessing,data balance,classifier selection,and feature selection.Feature importance was further analyzed to identify the key predictors of in-hospital mortality.Results:The proposed Synthetic Minority Oversampling Technique-Random Forest Recursive Feature Elimination-Extreme Gradient Boosting(SMOTE-(RF-RFE)-XGB)model achieved high predictive performance with a mean Area Under the Curve(AUC)of 0.8507,while reducing the number of features from 78 to 39.Compared to other feature selection methods evaluated in this study and those reported in related literature,Random Forest Recursive Feature Elimination(RF-RFE)offers the best trade-off between accuracy,feature compactness,and stability.Additionally,feature importance rankings consistently identified Acute Physiology Score Ⅲ(APS Ⅲ),Ventilation on First Day,and Depression as the top three most influential predictors,besides the Length of Stay in ICU and Hospital.Conclusions:This study addresses key gaps by conducting a comprehensive evaluation of classifiers and feature selection methods for predicting in-hospital mortality in patients with sepsis.The proposed SMOTE-(RFRFE)-XGB model achieved a high predictive performance and stability with a compact feature set.APS III,Ventilation on First Day,and Depression were consistently identified as key predictors besides Length of Stay in ICU and Hospital.
文摘Objective:Heart failure(HF)is a complex clinical syndrome that affects nearly 64 million individuals globally.Frequent hospital readmissions lead to poor health outcomes,impact quality of life(QoL),and are associated with high mortality rates.This study assessed readmissions,mortality,and QoL outcomes in patients with HF in a tertiary care hospital setting.Methods:Patients aged≥18 years with HF,who visited the tertiary care hospital in Karad,India were included in the study(November2019 to October 2021).Demographics,disease characteristics,and condition at discharge were recorded using the medical records of patients.The quantitative data included readmission rates and mortality rates.The qualitative aspects describing patients'QoL were assessed using a patient-reported 21-question QoL questionnaire.Results:A total of 98 patients,predominantly male(63.3%),with a mean age of 62.9 years were included.The majority of the patients(80.6%)required<15 days of hospitalization.The 2-year readmission rate was 24.4%,while the mortality rate was 43.9%.Self-care pattern showed that patients seemed to be taking mild to average care while taking good care was rare.The QoL data showed that 22.4% were living a good quality life,44.9% average,while 32.7% were living a low-quality life.Better education and better self-care were associated with a low rate of readmission.Conclusions:We were able to assess the incidence of readmission,mortality,and QoL in patients with HF in a tertiary care hospital setting.The study showed that HF impacts patients'physical,emotional,and psychological wellbeing.
文摘BACKGROUND:Rapid identification of patients at risk of clinical deterioration(in-hospital mortality) in emergency settings is essential for timely and appropriate care.Existing prognostic scores,such as the Acute Physiology and Chronic Health Evaluation IV(APACHE IV),Simplified Acute Physiology Score 3(SAPS 3),Sequential Organ Failure Assessment(SOFA),and National Early Warning Score 2(NEWS 2),have limitations in emergency scenarios,particularly in resource-limited settings.We aimed to develop a simple and efficient tool tailored to the Brazilian healthcare system.METHODS:This retrospective,multicenter,cohort study analyzed data from 50,709 adult patients admitted to 12 hospitals in southern and southeastern Brazil between 2019 and 2020.The BRASIL score(Brazilian Risk Assessment Severity Index and Length of stay) was constructed using demographic and clinical variables available at admission.Logistic regression was used to determine the weight of each variable,and each variable was assigned a point value based on its β-coefficient and clinical relevance,with thresholds defined according to established medical cutoffs and statistical performance.The score's predictive accuracy was validated using the area under the receiver operating characteristic curve(AUC) with comparative analysis against NEWS 2.RESULTS:The BRASIL score,including age,sex,respiratory rate,heart rate,oxygen saturation,blood pressure,and body temperature,was derived through variables independently associated with in-hospital mortality in a multicenter cohort.The total score was stratified into three risk categories — low(0–3 points),moderate(4–7 points),and high(>7 points) — using observed inflection points in mortality distribution to optimize discrimination.This stratification demonstrated a stepwise increase in mortality rates across categories and the discriminatory performance,with an overall AUC of 0.743(95% CI:0.726–0.761).Compared to NEWS 2(AUC 0.697,95% CI:0.683–0.711),the BRASIL score offered superior early risk identification,supporting timely clinical decisionmaking and resource allocation in the emergency setting.CONCLUSION:The BRASIL score is a novel tool for predicting in-hospital mortality in emergency departments.Its predictive performance and ease of use suggest that it has the potential to improve patient outcomes.
基金supported by the National Key Research and Development Plan:Real-Time Intelligent Active Intervention on Integration of Ten Important Chronic Diseases(2020YFC2003504-2,to BX)。
文摘Background:Although light-intensity physical activity(LPA)has been suggested to be associated with a lower risk of mortality,the minimal and optimal volumes of LPA remain unclear.We aimed to examine the minimal and optimal volumes of LPA associated with the risks of mortality and disease incidence(i.e.,cardiovascular diseases and cancer).Methods:Data were derived from the population-based UK Biobank cohort study,including 69,492 adults aged 43-78 years.Accelerometermeasured LPA was defined using a validated,published machine learning-based Random Forest activity method,which was categorized into 4 quartile groups.All-cause and cause-specific mortality(cardiovascular disease-and cancer-specific)were determined according to the International Classification of Diseases,10th version codes.Disease incidence was defined based on primary care,hospitalization,or death records.Results:During a median follow-up period of 8.04 years,2024 adults died from all causes,539 from cardiovascular disease,and 1175 from cancer.For all-cause mortality,compared with participants in the lowest quartile of LPA(<3.9 h/day),the hazard ratios(HRs)and 95%confidence intervals(95%CIs)were 0.82(95%CI:0.73-0.93)for those with 3.9 to<5.0 h/day,0.75(95%CI:0.66-0.85)for those with 5.0 to<6.1 h/day,and 0.77(95%CI:0.68-0.88)for those with≥6.1 h/day,respectively.There was an inverse non-linear dose-response association between LPA and all-cause mortality,with an optimal dose of 5.72 h/day(95%CI:5.45-6.41;HR=0.63,95%CI:0.56-0.71)and a minimal dose of 3.59 h/day(95%CI:3.53-8.56;HR=0.81,95%CI:0.78-0.86),with the 5th percentile as the reference.Similar patterns were observed for cause-specific mortality and disease incidence(cardiovascular disease and cancer).Conclusion:Engaging in LPA for~3.5 h/day was conservatively associated with lower risk of mortality and disease incidence,with further risk reductions observed up to an optimal dose of~6.0 h/day.These findings suggest that sufficient LPA offers important health benefits,which can inform the development of future PA guidelines.
基金funded by the Shenzhen Science and Technology Program(JCYJ20230807112007014 to PG)the Shenzhen Key Medical Discipline Construction Fund(SZXK046 to PG).
文摘BACKGROUND:Serum osmolality is a prognostic indicator in critically ill patients.This study aimed to evaluate the association between high osmolality and 28-day mortality in patients with cardiac arrest(CA)admitted to the intensive care unit(ICU).METHODS:Baseline data of adult patients with CA who were admitted to the ICU from 2008 to 2019 were collected from the Medical Information Mart for Intensive Care(MIMIC)-IV.Patients were divided into survivor and non-survivor groups according to the 28-day prognosis.Serum concentrations of sodium,potassium,glucose,and urea nitrogen on the fi rst day of ICU admission were used to determine serum osmolarity.The primary endpoint of this study was 28-day all-cause mortality.Propensity score matching(PSM)analysis was performed to reduce bias between the survivor and nonsurvivor groups.RESULTS:Among the 798 included CA patients,the high osmolarity on the first day of ICU admission remained significantly associated with increased 28-day mortality(62.0%vs.35.5%,P<0.001)and reduced cumulative survival(log-rank P<0.05)after PSM.Cox regression identifi ed the high osmolarity on the fi rst day of ICU admission as an independent predictor.High serum osmolarity on the fi rst day of ICU admission eff ectively predicted 1-,3-,7-,and 28-day all-cause mortality,with the strongest predictive performance for 1-day mortality both before and after PSM(all P<0.05).CONCLUSION:In this study,elevated serum osmolarity on the first day of ICU admission was independently associated with increased 28-day mortality in CA patients and could serve as a prognostic marker.
基金Supported by National Natural Science Foundation of China,No.82360136Jiangxi Clinical Research Center for Gastroenterology,No.20223BCG74011.
文摘BACKGROUND Acute pancreatitis(AP)is a severe condition,and abdominal effusion is a significant predictor of its severity and prognosis.However,the relationship between ascites characteristics and AP outcomes remains undefined.AIM To assess the correlation between ascites characteristics and clinical prognosis in AP patients by comparing color depth and turbidity of early ascites.METHODS This study included 667 AP patients with ascites,categorized by color and turbidity into yellow clear(n=54),yellow turbid(n=293),red brown(n=320).The trendχ2 test was employed to analyze the incidence of organ failure(OF),infected pancreatic necrosis(IPN),and mortality across groups.Receiver operating charac teristic(ROC)curves were used to evaluate the predictive value of ascites cell count,amylase,protein,and lactate dehydrogenase(LDH)for abdominal compartment syndrome(ACS)and intra-abdominal hemorrhage.RESULTS AP patients with ascites exhibited higher scores of scoring systems(such as Bedside index for severity in AP,Acute Physiology and Chronic Health Examination II,etc.)and increased complications and mortality rates(all P<0.05)compared to those without ascites.A linear association was observed between ascites color depth and turbidity and the incidence of OF,pancreatic necrosis,IPN,and mortality(P<0.05).LDH in ascites demonstrated high accuracy in predicting ACS and intra-abdominal hemorrhage,with areas under the ROC curve of 0.77 and 0.79,respectively.CONCLUSION Early in AP,ascites correlates with OF,IPN,and mortality,showing linear associations with color depth and turbidity.Ascitic LDH reliably predicts ACS and intra-abdominal hemorrhage in AP patients.
文摘BACKGROUND:Electrolyte imbalance is common following traumatic brain injury(TBI)and can significantly impact patient outcomes.We aimed to explore the occurrence,patterns,and consequences of electrolyte imbalance in adult patients with TBI.METHODS:A retrospective study was conducted from 2016 to 2021 at a level 1 trauma center among hospitalized TBI patients.On admission,the levels of serum electrolytes,including sodium,potassium,calcium,magnesium,and phosphate,were analyzed.Demographics,injury characteristics,and interventions were assessed.The primary outcome was the in-hospital mortality.Multivariate logistic regression analysis was performed to identify independent predictors of mortality in TBI patients.RESULTS:A total of 922 TBI patients were included in the analysis,of whom 902(98%)had electrolyte imbalance.The mean age of patients with electrolyte imbalance was 32.0±15.0 years.Most patients were males(94%).The most common electrolyte abnormalities were hypocalcemia,hypophosphatemia,and hypokalemia.The overall in-hospital mortality rate was 22%in the entire cohort.In multivariate logistic analysis,the predictors of mortality included age(odds ratio[OR]=1.029,95%confidence intervals[CI]:1.013-1.046,P<0.001),low GCS(OR=0.883,95%CI:0.816-0.956,P=0.002),high Injury Severity Score(ISS)scale(OR=1.051,95%CI:1.026-1.078,P<0.001),hypernatremia(OR=2.175,95%CI:1.196-3.955,P=0.011),hyperkalemia(OR=4.862,95%CI:1.222-19.347;P=0.025),low serum bicarbonate levels(OR=0.926,95%CI:0.868-0.988,P=0.020),high serum lactate levels(OR=1.128,95%CI:1.022-1.244,P=0.017),high glucose levels(OR=1.072,95%CI:1.014-1.133,P=0.015),a longer activated partial thromboplastin time(OR=1.054,95%CI:1.024-1.084,P<0.001)and higer international normalized ratio(INR)(OR=3.825,95%CI:1.592-9.188,P=0.003).CONCLUSION:Electrolyte imbalance is common in TBI patients,with the significant prevalence of hypocalcemia,hypophosphatemia,and hypokalemia.However,hypernatremia and hyperkalemia were associated with the risk of mortality,emphasizing the need for further research to comprehend electrolyte dynamics in TBI patients.
基金supported by the National Natural Science Foundation of China(31600479,32371576)the Key R&D Program of Yunnan Province(202403AC100028)+1 种基金the Youth Academic and Technical Leading Talent Reserve Program in Yunnan Province(202405AC350012)the 14th Five-Year Plans of Xishuangbanna Tropical Botanical Garden,Chinese Academy of Sciences(XTBG-1450101,E3ZKFF2B01).
文摘Climate change has significantly increased the frequency and severity of droughts and risk of tree death worldwide.Differences in leaf habit,plant size,and species diversity are associated with differences in the risk of drought-induced mortality,but the relative contributions of these factors to the risk of mortality are unclear.In a study of the mortality of tree and shrub species during the extreme drought of 2019 in a savanna ecosystem in Southwest China,we assessed the relative contributions of evergreen and deciduous leaf habit,plant size,and species richness and diversity to the mortality of shrubs and trees after the 2019 extreme drought.The deciduous species had significantly lower hydraulic safety margins than the coexisting evergreen species,resulting in a higher mortality risk.Additionally,species and individuals with taller canopies tended to have deeper root systems,an advantage during extreme drought that reduced mortality risk.Notably,mortality risk was largely independent of stand species richness and diversity.Overall,leaf habit and plant height were better predictors of mortality risk than species richness and diversity.These novel insights provide a better understanding of the mechanisms driving drought-induced mortality in the ecosystems with a low canopy and weak interspecific and intraspecific competition for shared resources.Leaf habit and tree size should be incorporated into hypotheses on the mechanisms underlying drought-induced tree mortality.
基金Supported by Hospital Capability Enhancement Project of Xiyuan Hospital,China Academy of Chinese Medical Sciences,No.XYZX0404-15Zhejiang Provincial Medical Association Clinical Medical Research Special Funding Projects,No.2023ZYC-A13.
文摘BACKGROUND The non-high-density lipoprotein cholesterol(non-HDL-C)/HDL-C ratio(NHHR)is linked to cardiovascular event risk,but its prognostic value in diabetes mellitus(DM)patients remains unclear.AIM To explore the association of NHHR and cardiovascular mortality in patients with DM and generate predictive model.METHODS This cohort study analyzed data from 8425 DM patients in National Health and Nutrition Examination Survey.NHHR was calculated as(total cholesterol-HDLC)/HDL-C.Cardiovascular mortality was determined via the National Death Index.Feature selection was performed using the Boruta algorithm and least absolute shrinkage and selection operator regression,followed by Cox proportional hazards models to evaluate NHHR’s relationship with cardiovascular mortality.Stratified and sensitivity analyses assessed the findings’robustness.A nomogram was developed to predict cardiovascular mortality,with model performance evaluated using receiver operating characteristic curves and calibration plots.RESULTS Over an average follow-up of 94.2 months,671 cardiovascular deaths(8.0%)occurred.Six key features including age,education,ethnicity,poverty-income ratio,history of heart failure,and NHHR,were selected.A non-linear association was found,with the highest NHHR quartile showing a 39%higher risk of cardiovascular death compared to the lowest quartile(Q4,hazard ratio:1.39,95%confidence interval:1.11-1.73).Stratified analyses confirmed the increased risk across all subgroups.Sensitivity analyses supported the stability of the results.The nomogram for predicting cardiovascular mortality demonstrated high accuracy.CONCLUSION Elevated NHHR is associated with increased cardiovascular mortality risk in DM patients.NHHR could be a valuable prognostic marker,aiding in identifying high-risk patients and guiding targeted lipid management strategies.
基金supported by the Key Research and Development Special Project of the Autonomous Region(No.2022B03023-3)the Key Supported Discipline of Health System in Shanghai(No.2023ZDFC0302)。
文摘OBJECTIVE To investigate possible associations between physical function assessment scales,such as Short Physical Performance Battery(SPPB)and Berg Balance Scale(BBS),with all-cause mortality in acute decompensated heart failure(ADHF)patients.METHODS A total of 108 ADHF patients were analyzed from October 2020 to October 2022,and followed up to May 2023.The association between baseline clinical characteristics and all-cause mortality was analyzed by univariate Cox regression analysis,while for SPPB and BBS,univariate Cox regression analysis was followed by receiver operating characteristic curves,in which the area under the curve represented their predictive accuracy for all-cause mortality.Incremental predictive values for both physical function assessments were measured by calculating net reclassification index and integrated discrimination improvement scores.Optimal cutoff value for BBS was then identified using restricted cubic spline plots,and survival differences below and above that cut-off were compared using Kaplan-Meier survival curves and the log-rank test.The clinical utility of BBS was measured using decision curve analysis.RESULTS For baseline characteristics,age,female,blood urea nitrogen,as well as statins,angiotensin-converting enzyme inhibitors,angiotensin II receptor blockers,or angiotensin receptor-neprilysin inhibitors,were predictive for all-cause mortality for ADHF patients.With respect to SPPB and BBS,higher scores were associated with lower all-cause mortality rates for both assessments;similar area under the curves were measured for both(0.774 for SPPB and 0.776 for BBS).Furthermore,BBS≤36.5 was associated with significantly higher mortality,which was still applicable even adjusting for confounding factors;BBS was also found to have great clinical utility under decision curve analysis.CONCLUSIONS BBS or SPPB could be used as tools to assess physical function in ageing ADHF patients,as well as prognosticate on all-cause mortality.Moreover,prioritizing the improvement of balance capabilities of ADHF patients in cardiac rehabilitation regimens could aid in lowering mortality risk.
文摘BACKGROUND Proton pump inhibitors(PPIs)are widely used,including among cancer patients,to manage gastroesophageal reflux and other gastric acid-related disorders.Recent evidence suggests associations between long-term PPI use and higher risks for various adverse health outcomes,including greater mortality.AIM To investigate the association between PPI use and all-cause mortality among cancer patients by a comprehensive analysis after adjustment for various confounders and a robust methodological approach to minimize bias.METHODS This retrospective cohort study used data from the TriNetX research network,with electronic health records from multiple healthcare organizations.The study employed a new-user,active comparator design,which compared newly treated PPI users with non-users and newly treated histamine2 receptor antagonists(H2RA)users among adult cancer patients.Newly prescribed PPIs(esomeprazole,lansoprazole,omeprazole,pantoprazole,or rabeprazole)users were compared to non-users or newly prescribed H2RAs(cimetidine,famotidine,nizatidine,or ranitidine)users.The primary outcome was all-cause mortality.Each patient in the main group was matched to a patient in the control group using 1:1 propensity score matching to reduce confounding effects.Multivariable Cox regression models were used to estimate hazard ratios(HRs)and 95% confidence interval(CI).RESULTS During the follow-up period(median 5.4±1.8 years for PPI users and 6.5±1.0 years for non-users),PPI users demonstrated a higher all-cause mortality rate than non-users after 1 year,2 years,and at the end of follow up(HRs:2.34-2.72).Compared with H2RA users,PPI users demonstrated a higher rate of all-cause mortality HR:1.51(95%CI:1.41-1.69).Similar results were observed across sensitivity analyses by excluding deaths from the first 9 months and 1-year post-exposure,confirming the robustness of these findings.In a sensitivity analysis,we analyzed all-cause mortality outcomes between former PPI users and individuals who have never used PPIs,providing insights into the long-term effects of past PPI use.In addition,at 1-year follow-up,the analysis revealed a significant difference in mortality rates between former PPI users and non-users(HR:1.84;95%CI:1.82-1.96).CONCLUSION PPI use among cancer patients was associated with a higher risk of all-cause mortality compared to non-users or H2RA users.These findings emphasize the need for cautious use of PPIs in cancer patients and suggest that alternative treatments should be considered when clinically feasible.However,further studies are needed to corroborate our findings,given the significant adverse outcomes in cancer patients.
文摘This editorial comments on the article by Desai et al,which investigates the impact of coronavirus disease 2019(COVID-19)on in-hospital mortality among patients with recurrent stroke using data from the 2020 National Inpatient Sample.The findings reveal significantly higher mortality rates in COVID-19-positive patients compared to non-COVID-19 patients,particularly among middle-aged individuals,males,and ethnic minorities.This editorial explores the underlying mechanisms contributing to these outcomes and discusses the clinical implications for targeted management strategies in high-risk groups.The results emphasize the need for comprehensive approaches to mitigate the heightened risks faced by recurrent stroke patients during the COVID-19 pandemic.
文摘BACKGROUND Ovarian carcinoma has the highest mortality rate among all gynecological cancers.Several reproductive and hormonal risk factors,including early menarche,late menopause,limited use of oral contraceptives,and a low pregnancy rate,have been identified as contributors to the increased susceptibility to ovarian cancer.Advancements in cancer therapy over the past century,including the emergence of precision oncology,underscore the importance of early detection and tailored interventions,factors particularly critical in ovarian cancer,where late-stage diagnosis remains a persistent barrier to survival.This challenge is compounded by the lack of a universally endorsed screening program,resulting in late-stage identification and widespread metastasis.AIM To evaluate demographic differences in ovarian cancer-related mortality from 1999 to 2020 among adult females aged≥25 years within the United States.METHODS Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database was used to collect de-identified death certificate data for malignant neoplasm of the ovaries related deaths in female adults aged 25 years and older from the year 1999 to 2020.Crude mortality rates and age-adjusted mortality rates(AAMRs)per 100000 people were calculated.Join point regression program was used to assess annual percent changes in mortality trends,with statistical significance set at P value<0.05.RESULTS Between 1999 and 2020,337619 deaths due to ovarian cancer occurred among United States females aged 25 to>85.The AAMR decreased from 14.62 in 1999 to 10.15 in 2020,with significant declines across various demographics.The AAMRs were highest among non-Hispanic White women,i.e.,13.53.Based on region,they were the highest in the Northeast(13.06)and Midwest(12.94).The steepest decline was observed in metropolitan areas as compared to nonmetropolitan ones.The study highlights significant progress in reducing ovarian cancer mortality across age,race/ethnicity,and geographic regions during this period.CONCLUSION The mortality trends for ovarian carcinoma patients showed an overall decrease,with the highest mortality rates observed among older individuals(65 to>85 years)and non-Hispanic Whites.These disparities underscore the need for equitable healthcare access and targeted policy interventions.
