Stroke is a critical health issue in China, and carotid artery stenosis and plaque play key roles in its prevalence. Despite the acknowledged significance of this condition, detailed information regarding the prevalence of carotid artery stenosis and plaque across the Chinese population has been scarce. This study analyzed data from the China Stroke High-risk Population Screening and Intervention Program for 2020-2021, focusing on 194 878 Chinese adults aged 40 years and above. It assessed the prevalence of carotid artery stenosis and plaque and identified their associated risk factors. Results revealed a standardized prevalence of 0.40% for carotid artery stenosis and 36.27% for carotid plaque. Notably, the highest rates of stenosis were observed in north and south China at 0.61%, while southwestern China exhibited the highest plaque prevalence at 43.17%. Key risk factors included older age, male gender, hypertension, diabetes, stroke, smoking, and atrial fibrillation. This study highlights significant geographical and demographic disparities in the prevalence of these conditions, underlining the urgent need for targeted interventions and policy reforms. These measures are essential for reducing the incidence of stroke and improving patient outcomes, addressing this significant health challenge in China.
Humans ; China/epidemiology* ; Male ; Female ; Prevalence ; Middle Aged ; Carotid Stenosis/epidemiology* ; Risk Factors ; Aged ; Adult ; Plaque, Atherosclerotic/epidemiology* ; Stroke/epidemiology* ; Aged, 80 and over

The quest to decipher the determinants of human longevity has intensified with the rise in global life expectancy. Long-lived individuals (LLIs), who exceed the average life expectancy while delaying age-related diseases, serve as a unique model for studying human healthy aging and longevity. Longevity is a complex phenotype influenced by both genetic and non-genetic factors. This review paper delves into the genetic, epigenetic, metabolic, immune, and environmental factors underpinning the phenomenon of human longevity, with a particular focus on LLIs, such as centenarians. By integrating findings from human longevity studies, this review highlights a diverse array of factors influencing longevity, ranging from genetic polymorphisms and epigenetic modifications to the impacts of diet and physical activity. As life expectancy grows, understanding these factors is crucial for developing strategies that promote a healthier and longer life.
Humans ; Healthy Aging/physiology* ; Longevity/physiology* ; Epigenesis, Genetic ; Life Expectancy ; Exercise ; Aging/genetics* ; Diet ; Aged, 80 and over

OBJECTIVE: To analyze the clinical characteristics of elderly patients with sepsis, identify the key factors affecting their clinical outcomes, construct a death risk assessment scale for elderly patients with sepsis, and evaluate its predictive value. METHODS: A retrospective case-control study was conducted. The clinical data of sepsis patients admitted to intensive care unit (ICU) of the First Affiliated Hospital of Wenzhou Medical University from September 2021 to September 2023 were collected, including basic information, clinical characteristics, and clinical outcomes. The patients were divided into non-elderly group (age ≥ 65 years old) and elderly group (age < 65 years old) based on age. Additionally, the elderly patients were divided into survival group and death group based on their 30-day survival status. The clinical characteristics of elderly patients with sepsis were analyzed. Univariate and multivariate Logistic regression analyses were used to screen the independent risk factors for 30-day death in elderly patients with sepsis, and the regression equation was constructed. The regression equation was simplified, and the death risk assessment scale was established. The predictive value of different scores for the prognosis of elderly patients with sepsis was compared. RESULTS: (1) A total of 833 patients with sepsis were finally enrolled, including 485 in the elderly group and 348 in the non-elderly group. Compared with the non-elderly group, the elderly group showed significantly lower counts of lymphocyte, T cell, CD8⁺ T cell, and the ratio of T cells and CD8⁺ T cells [lymphocyte count (×10⁹/L): 0.71 (0.43, 1.06) vs. 0.83 (0.53, 1.26), T cell count (cells/μL): 394.0 (216.0, 648.0) vs. 490.5 (270.5, 793.0), CD8⁺ T cell count (cells/μL): 126.0 (62.0, 223.5) vs. 180.0 (101.0, 312.0), T cell ratio: 0.60 (0.48, 0.70) vs. 0.64 (0.51, 0.75), CD8⁺ T cell ratio: 0.19 (0.13, 0.28) vs. 0.24 (0.16, 0.34), all P < 0.01], higher natural killer cell (NK cell) count, acute physiology and chronic health evaluation II (APACHE II) score, ratio of invasive mechanical ventilation (IMV) during hospitalization, and 30-day mortality [NK cell count (cells/μL): 112.0 (61.0, 187.5) vs. 95.0 (53.0, 151.0), APACHE II score: 16.00 (12.00, 21.00) vs. 13.00 (8.00, 17.00), IMV ratio: 40.6% (197/485) vs. 31.9% (111/348), 30-day mortality: 28.9% (140/485) vs. 19.5% (68/348), all P < 0.05], and longer length of ICU stay [days: 5.5 (3.0, 10.0) vs. 5.0 (3.0, 8.0), P < 0.05]. There were no statistically significant differences in the levels of inflammatory markers such as C-reactive protein (CRP), procalcitonin (PCT), tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), and interleukins (IL-2, IL-4, IL-6, IL-10) between the two groups. (2) In 485 elderly patients with sepsis, 345 survived in 30 days, and 140 died with the 30-day mortality of 28.9%. Compared with the survival group, the patients in the death group were older, and had lower body mass index (BMI), white blood cell count (WBC), PCT, platelet count (PLT) and higher IL-6, IL-10, N-terminal pro-brain natriuretic peptide (NT-proBNP), total bilirubin (TBil), blood lactic acid (Lac), and ratio of in-hospital IMV and continuous renal replacement therapy (CRRT). Multivariate Logistic regression analysis indicated that BMI [odds ratio (OR) = 0.783, 95% confidence interval (95%CI) was 0.678-0.905, P = 0.001], IL-6 (OR = 1.073, 95%CI was 1.004-1.146, P = 0.036), TBil (OR = 1.009, 95%CI was 1.000-1.018, P = 0.045), Lac (OR = 1.211, 95%CI was 1.072-1.367, P = 0.002), and IMV during hospitalization (OR = 6.181, 95%CI was 2.214-17.256, P = 0.001) were independent risk factors for 30-day death in elderly patients with sepsis, and the regression equation was constructed (Logit P = 1.012-0.244×BMI+0.070×IL-6+0.009×TBil+0.190×Lac+1.822×IMV). The regression equation was simplified to construct a death risk assessment scale, namely BITLI score. Receiver operator characteristic curve (ROC curve) analysis showed that the area under the ROC curve (AUC) of BITLI score for predicting death risk was 0.852 (95%CI was 0.769-0.935), and it was higher than APACHE II score (AUC = 0.714, 95%CI was 0.623-0.805) and sequential organ failure assessment (SOFA) score (AUC = 0.685, 95%CI was 0.578-0.793). The determined cut-off value of BITLI score was 1.50, while achieving a sensitivity of 83.3% and specificity of 74.0%. CONCLUSIONS Elderly patients with sepsis often have reduced lymphocyte counts, severe conditions, and poor prognosis. BMI, IL-6, TBil, Lac, and IMV during hospitalization were independent risk factors for 30-day death in elderly patients with sepsis. The BITLI score constructed based above risk factors is more precise and reliable than traditional APACHE II and SOFA scores in predicting the outcomes of elderly patients with sepsis.
Humans ; Sepsis/mortality* ; Aged ; Retrospective Studies ; Risk Assessment ; Case-Control Studies ; Prognosis ; Male ; Female ; Intensive Care Units ; Risk Factors ; Aged, 80 and over ; Logistic Models ; Middle Aged

OBJECTIVE: To elucidate the predictive value of norepinephrine equivalence (NEE) score on the 28-day death risk in patients with sepsis and provide evidence for its application in the diagnosis and treatment of sepsis and septic shock. METHODS: A retrospective cohort study was conducted based on the data of patients with sepsis from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). The patients who received vasoactive agents within 6 hours after the diagnosis of sepsis or septic shock were enrolled, and they were divided into survival and non-survival groups based on their 28-day outcomes. The baseline characteristics, vital signs, and treatment data were collected. Multivariate Cox regression analysis was performed to identify factors influencing the 28-day death risk. Receiver operator characteristic curve (ROC curve) was drawn to analyze the predictive value of various parameters on the 28-day death risk of septic patients. Kaplan-Meier survival curve was used to evaluate cumulative survival rate in patients classified by different quantitative parameters based on the cut-off values obtained from ROC curve analysis. RESULTS: A total of 7 744 patients who met the Sepsis-3 diagnostic criteria and received vasopressor treatment within 6 hours post-diagnosis were enrolled, of which 5 997 cases survived and 1 747 died, with the 28-day mortality of 22.6%. Significant differences were observed between the two groups regarding age, gender, height, body weight, race, type of intensive care unit (ICU), acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, Charlson comorbidity index (CCI) score, underlying comorbidities, and vital signs. Compared with the survival group, the non-survival group had poorer blood routine, liver and kidney function, coagulation function, blood gas analysis and other indicators. Multivariate Cox regression analysis revealed that age > 65 years old [hazard ratio (HR) = 0.892, 95% confidence interval (95%CI) was 0.801-0.994, P = 0.039] and male (HR = 0.735, 95%CI was 0.669-0.808, P < 0.001) were protective factors for 28-day death in patients with sepsis, and NEE score (HR = 1.040, 95%CI was 1.021-1.060, P < 0.001), shock index (HR = 1.840, 95%CI was 1.675-2.022, P < 0.001), APACHE II score (HR = 1.076, 95%CI was 1.069-1.083, P < 0.001), SOFA score (HR = 1.035, 95%CI was 1.015-1.056, P < 0.001), and CCI score (HR = 1.135, 95%CI was 1.115-1.155, P < 0.001) were independent risk factors for 28-day death in septic patients. ROC curve analysis showed that the area under the ROC curve (AUC) of NEE score for predicting the 28-day death risk of septic patients was 0.743 (95%CI was 0.730-0.756), which was comparable to the predictive value of APACHE II score (AUC = 0.742, 95%CI was 0.729-0.755) and ratio of mean arterial pressure (MAP)/NEE score (MAP/NEE; AUC = 0.738, 95%CI was 0.725-0.751, both P > 0.05), and better than SOFA score (AUC = 0.609, 95%CI was 0.594-0.624), CCI score (AUC = 0.658, 95%CI was 0.644-0.673), shock index (AUC = 0.613, 95%CI was 0.597-0.629) and ratio of diastolic blood pressure (DBP)/NEE score (DBP/NEE; AUC = 0.735, 95%CI was 0.721-0.748, all P < 0.05). According to the cut-off values of APACHE II and NEE scores obtained from ROC curve analysis, the patients were stratified for Kaplan-Meier survival curve analysis, and the results showed that the 28-day cumulative survival rate in the septic patients with an APACHE II score ≤ 22.5 was significantly higher than that in those with an APACHE II > 22.5 (Log-Rank test: χ² = 848.600, P < 0.001), and the 28-day cumulative survival rate in the septic patients with an NEE score ≤0.120 was significantly higher than that in those with an NEE score > 0.120 (Log-Rank test: χ² = 832.449, P < 0.001). CONCLUSIONS NEE score is an independent risk factor for 28-day death in septic patients who received vasoactive treatment within 6 hours of diagnosis and possesses significant predictive value. It can be used for severity stratification in sepsis management.
Humans ; Retrospective Studies ; Sepsis/diagnosis* ; Male ; Female ; Norepinephrine/therapeutic use* ; Middle Aged ; Aged ; Prognosis ; Predictive Value of Tests ; Shock, Septic/mortality* ; Adult ; ROC Curve ; Risk Factors ; Survival Rate ; Aged, 80 and over

OBJECTIVE: Xuebijing injection has been recommended as a therapeutic approach for individuals with severe and critical COVID-19. This study aims to explore the correlation of neutrophil to lymphocyte platelet ratio (NLPR) with the severity and prognosis of COVID-19, and the effect of XBJ on the prognosis of patients with COVID-19 in different inflammatory states. METHODS: This was a retrospective study conducted at Wuhan Union Hospital in China. COVID-19 patients admitted between November 1, 2022 and February 1, 2023 were included. In predicting prognosis for individuals with COVID-19, new inflammatory indicators were used, and their prognostic value was assessed by using Cox regression models and receiver operating characteristic curves. Furthermore, a calculation was made to determine the cutoff value for NLPR. Relative risk and Cox regression models were used to examine the effects of Xuebijing injection on prognosis in patient cohorts that had been stratified by the NLPR cutoff. RESULTS: This research included 455 participants with COVID-19, with a mean age of 72 years. Several inflammatory indicators were found to be strongly correlated with prognosis, and NLPR shows the greatest predictive power. Patients with NLPR > 3.29 exhibited a mortality rate of 17.3%, which was 6.2 times higher than in patients with NLPR ≤ 3.29. Importantly, providing Xuebijing injection to patients with NLPR > 3.29 was associated with a lower risk of 60-day all-cause mortality. However, there was no discernible improvement in survival among patients with NLPR ≤ 3.29 who received Xuebijing injection. CONCLUSION NLPR is the most reliable inflammatory marker for predicting prognosis among individuals with COVID-19, and can accurately identify individuals who may benefit from Xuebijing injection. Please cite this article as: Liao M, Zhang LT, Bai LJ, Wang RY, Liu Y, Han J, Liu LH, Qi BL. Xuebijing injection reduces COVID-19 patients mortality as influenced by the neutrophil to lymphocyte platelet ratio. J Integr Med. 2025; 23(3): 282-288.
Humans ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Female ; Retrospective Studies ; Aged ; Neutrophils ; COVID-19 Drug Treatment ; COVID-19/blood* ; Middle Aged ; Prognosis ; Lymphocytes ; Blood Platelets ; Platelet Count ; SARS-CoV-2 ; Aged, 80 and over ; Adult

OBJECTIVE: As an age-related neurodegenerative disease, the prevalence of mild cognitive impairment (MCI) increases with age. Within the framework of traditional Chinese medicine, spleen-kidney deficiency syndrome (SKDS) is recognized as the most frequent MCI subtype. Due to the covert and gradual onset of MCI, in community settings it poses a significant challenge for patients and their families to discern between typical aging and pathological changes. There exists an urgent need to devise a preliminary diagnostic tool designed for community-residing older adults with MCI attributed to SKDS (MCI-SKDS). METHODS: This investigation enrolled 312 elderly individuals diagnosed with MCI, who were randomly distributed into training and test datasets at a 3:1 ratio. Five machine learning methods, including logistic regression (LR), decision tree (DT), naive Bayes (NB), support vector machine (SVM), and gradient boosting (GB), were used to build a diagnostic prediction model for MCI-SKDS. Accuracy, sensitivity, specificity, precision, F1 score, and area under the curve were used to evaluate model performance. Furthermore, the clinical applicability of the model was evaluated through decision curve analysis (DCA). RESULTS: The accuracy, precision, specificity and F1 score of the DT model performed best in the training set (test set), with scores of 0.904 (0.845), 0.875 (0.795), 0.973 (0.875) and 0.973 (0.875). The sensitivity of the training set (test set) of the SVM model performed best among the five models with a score of 0.865 (0.821). The area under the curve of all five models was greater than 0.9 for the training dataset and greater than 0.8 for the test dataset. The DCA of all models showed good clinical application value. The study identified ten indicators that were significant predictors of MCI-SKDS. CONCLUSION The risk prediction index derived from machine learning for the MCI-SKDS prediction model is simple and practical; the model demonstrates good predictive value and clinical applicability, and the DT model had the best performance. Please cite this article as: Ai YT, Zhou S, Wang M, Zheng TY, Hu H, Wang YC, Li YC, Wang XT, Zhou PJ. Development of a machine learning-based risk prediction model for mild cognitive impairment with spleen-kidney deficiency syndrome in the elderly. J Integr Med. 2025; 23(4): 390-397.
Humans ; Cognitive Dysfunction/diagnosis* ; Aged ; Male ; Female ; Machine Learning ; Spleen ; Aged, 80 and over ; Kidney ; Medicine, Chinese Traditional

OBJECTIVE: The results of limited studies on the relationship between environmental pollution and dementia have been contradictory. We analyzed the combined effects of PM _2.5 and smoking on the prevalence of dementia and cognitive impairment in an elderly community-dwelling Chinese population. METHODS: We assessed 24,117 individuals along with the annual average PM _2.5 concentrations from 2012 to 2016. Dementia was confirmed in the baseline survey at a qualified clinical facility, and newly suspected dementia was assessed in 2017, after excluding cases of suspected dementia in 2015. National census data were used to weight the sample data to reflect the entire population in China, with multiple logistic regression performed to analyze the combined effects of PM _2.5 and smoking frequency on dementia and cognitive impairment. RESULTS: Individuals exposed to the highest PM _2.5 concentration and smoked daily were at higher risk of dementia than those in the lowest PM _2.5 concentration group ( OR, 1.603; 95% CI [1.626-1.635], P < 0.0001) and in the nonsmoking group ( OR, 1.248; 95% CI [1.244-1.252]; P < 0.0001). Moderate PM _2.5 exposure and occasional smoking together increased the short-term risk of cognitive impairment. High-level PM _2.5 exposure and smoking were associated with an increased risk of dementia, so more efforts are needed to reduce this risk through environmental protection and antismoking campaigns. CONCLUSION High-level PM _2.5 exposure and smoking were associated with an increased risk of dementia. Lowering the ambient PM _2.5, and smoking cessation are recommended to promote health.
Humans ; Dementia/etiology* ; Male ; Aged ; Female ; Cognitive Dysfunction/etiology* ; China/epidemiology* ; Particulate Matter/analysis* ; Smoking/epidemiology* ; Air Pollutants/analysis* ; Aged, 80 and over ; Environmental Exposure/adverse effects* ; Prevalence ; Middle Aged

OBJECTIVE: This study examines utilizes the advantages of machine learning algorithms to discern key determinants in prognosticate postoperative circulatory complications (PCCs) for older patients. METHODS: This secondary analysis of data from a randomized controlled trial involved 1,720 elderly participants in five tertiary hospitals in Beijing, China. Participants aged 60-90 years undergoing major non-cardiac surgery under general anesthesia. The primary outcome metric of the study was the occurrence of PCCs, according to the European Society of Cardiology and the European Society of Anaesthesiology diagnostic criteria. The analysis metrics contained 67 candidate variables, including baseline characteristics, laboratory tests, and scale assessments. RESULTS: Our feature selection process identified key variables that significantly impact patient outcomes, including the duration of ICU stay, surgery, and anesthesia; APACHE-II score; intraoperative average heart rate and blood loss; cumulative opioid use during surgery; patient age; VAS-Move-Median score on the 1st to 3rd day; Charlson comorbidity score; volumes of intraoperative plasma, crystalloid, and colloid fluids; cumulative red blood cell transfusion during surgery; and endotracheal intubation duration. Notably, our Random Forest model demonstrated exceptional performance with an accuracy of 0.9872. CONCLUSION We have developed and validated an algorithm for predicting PCCs in elderly patients by identifying key risk factors.
Aged ; Aged, 80 and over ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; Machine Learning ; Postoperative Complications/etiology* ; Risk Factors ; Randomized Controlled Trials as Topic ; Secondary Data Analysis

OBJECTIVE: Asthma imposes a significant global health burden. This study examines changes in the asthma-related disease burden from 1990 to 2021 and projects future burdens for 2050 under different scenarios. METHODS: Using data from the Global Burden of Disease 2021 study, we analyzed asthma incidence, prevalence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2021. We projected the disease burden for 2050 based on current trends and hypothetical scenarios in which all risk factors are controlled. Temporal trends in age-standardized incidence, prevalence, mortality, and DALY rates were explored using Annual Percent Change. RESULTS: In 2021, the age-standardized rates for asthma incidence, prevalence, mortality, and DALYs in China were 364.17 per 100,000 (95% uncertainty interval [ UI]: 283.22-494.10), 1,956.49 per 100,000 (95% UI: 1,566.68-2,491.87), 1.47 per 100,000 (95% UI: 1.15-1.79), and 103.76 per 100,000 (95% UI: 72.50-145.46), respectively. A higher disease burden was observed among Chinese men and individuals aged 70 years or older. Compared to the current trend, a combined scenario involving improvements in environmental factors, behavioral and metabolic health, child nutrition, and vaccination resulted in a greater reduction in the disease burden caused by asthma. CONCLUSION Addressing modifiable risk factors is essential for further reducing the asthma-related disease burden.
Humans ; Asthma/mortality* ; China/epidemiology* ; Male ; Female ; Adult ; Middle Aged ; Aged ; Child ; Adolescent ; Global Burden of Disease/trends* ; Child, Preschool ; Young Adult ; Infant ; Cost of Illness ; Disability-Adjusted Life Years ; Prevalence ; Incidence ; Infant, Newborn ; Aged, 80 and over ; Risk Factors

OBJECTIVE: This study aims to analyze the burden of lower respiratory infections in Chinese elderly people aged 70 and above. METHODS: This study utilized Global Burden of Disease (GBD) 1990-2050 prediction data to analyze changes in mortality rates and disability-adjusted life year (DALY) rates for lower respiratory infections in the elderly population (aged 70 and above) in China from 1990 to 2050. It also discusses future trends in the burden of lower respiratory infections (LRI) in China under different scenarios. RESULTS: According to GBD predictions, the burden of lower respiratory infections in the elderly aged 70 years and above in China is lower than the global average. The burden has been decreasing from 1990 to 2020, but is projected to increase from 2020 to 2050. Scenario-based predictions suggest that, under scenarios involving improvements in nutrition and vaccination, the burden of lower respiratory infections in the elderly in China is expected to be the lowest in 2050. CONCLUSION This study indicates that the burden of lower respiratory infections in elderly people aged 70 years and above in China remains a significant public health issue and may worsen. The government should consider strengthening the preventive measures and management strategies for respiratory infections in the elderly population.
Humans ; China/epidemiology* ; Aged ; Respiratory Tract Infections/mortality* ; Aged, 80 and over ; Male ; Female ; Forecasting ; Disability-Adjusted Life Years ; Global Burden of Disease ; Cost of Illness