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

Mitochondria play a pivotal role in spermatogenesis and sperm activation in Caenorhabditis elegans, serving as the primary ATP supplier for cell division and differentiation while also acting as a key regulator of zinc ion homeostasis, membrane dynamics, and apoptotic signaling. This review systematically summarizes the essential mitochondrial mechanisms at different stages of sperm development, highlighting their multifaceted contributions beyond energy metabolism. Mitochondria are crucial for maintaining the health and stability of the gonads by regulating key apoptotic execution proteins that facilitate the proper elimination of damaged or unnecessary germ cells. Additionally, mitochondria dynamically adjust their energy supply to meet the metabolic demands of different stages of germline development. During early spermatogenesis, mitochondria provide ATP to fuel mitotic and meiotic divisions, support cellular differentiation, and regulate H⁺ and Zn²⁺ exchange to maintain cytoplasmic homeostasis, thereby ensuring the proper maturation and functionality of sperm cells. As spermatogenesis progresses, mitochondria participate in processing and sorting essential sperm proteins, such as major sperm protein (MSP), and contribute to the formation of membranous organelles (MOs), which are critical for subsequent activation events. During sperm activation, mitochondria play a dual role in ensuring a successful transition from immotile spermatids to fully functional spermatozoa. First, they provide ATP to facilitate pseudopod formation, MO fusion, and ion channel regulation, all of which are essential for sperm motility and fertilization potential. Second, mitochondria regulate the quality and quantity of functional mitochondria within sperm cells through mitopherogenesis—a recently discovered process in which mitochondrial vesicles are selectively released, ensuring that only healthy mitochondria are retained. This quality-control mechanism optimizes mitochondrial function, which is crucial for sustaining sperm motility and longevity. Beyond their traditional role in energy metabolism, mitochondria may also contribute to protein synthesis during spermatogenesis and activation. Recent evidence suggests that mitochondrial ribosomes actively translate specific proteins required for sperm function, challenging the long-standing belief that spermatozoa do not engage in de novo protein synthesis after differentiation. This emerging perspective raises important questions about the role of mitochondria in regulating sperm activation at the molecular level, particularly in modulating oxidative phosphorylation (OXPHOS) protein composition to optimize ATP production. In summary, mitochondria serve as both the central energy hub and a crucial regulatory factor in sperm activation, metabolic homeostasis, and reproductive success. Their involvement extends beyond ATP generation to include apoptotic regulation, ion homeostasis, vesicle-mediated mitochondrial quality control, and potential contributions to protein synthesis. Understanding these mitochondrial functions in C. elegans not only deepens our knowledge of nematode reproductive biology, but also provides valuable insights into broader mechanisms governing mitochondrial regulation in germline cells across species. These findings open new avenues for future research into the interplay between mitochondria, energy metabolism, and sperm function, with potential implications for reproductive health and fertility studies.

Objective:To explore the effect of empagliflozin combined with levosimendan on plasma levels of type Ⅰcollagen(Collagen Ⅰ),connective tissue growth factor(CTGF),and α-smooth muscle actin(α-SMA)in patients with coronary heart disease(CHD)and heart failure(HF).Methods:This randomized controlled study enrolled 106 CHD+HF patients admitted to Linfen Central Hospital between June 2022 and June 2023.Patients were divid-ed into control group(n=53,treated with levosimendan)and combined treatment group(n=53,received addition-al empagliflozin).Both groups were treated for 12 weeks.The total effective rate,exercise endurance,cardiac function,levels of HF biomarkers,inflammatory factors,myocardial fibrosis indexes and incidence of adverse reac-tions were compared between two groups.Results:The total effective rate of combined treatment group was signif-icantly higher than that in the control group(94.34％vs.81.13％,P＜0.001).Compared with patients in the con-trol group,those in the combined treatment group had significant higher cardiac output(CO)[(4.62±0.89)L/min vs.(3.90±0.75)L/min],left ventricular ejection fraction(LVEF)[(55.42±6.09)％vs.(48.97±5.74)％]and 6-minute walking distance(6MWD)[(405.69±56.47)m vs.(295.65±41.32)m](P＜0.001 all),and signifi-cant lower levels of N-terminal pro B-type natriuretic peptide(NT-proBNP)[(192.06±29.02)pg/ml vs.(313.58±20.98)pg/ml],soluble suppression of tumorigenicity 2(sST2)[(53.33±5.79)μg/L vs.(60.04±6.88)μg/L],interleukin-1β(IL-1β)[(18.16±5.42)ng/L vs.(21.07±6.31)ng/L],high-sensitive C-reactive protein(hsCRP)[(1.69±0.41)mg/L vs.(1.98±0.56)mg/L],tumor necrosis factor α(TNF-α)[(0.87±0.26)ng/L vs.(1.19±0.32)ng/L],Collagen Ⅰ[(162.58±30.55)μg/L vs.(189.98±41.32)μg/L],CTGF[(114.26±14.89)μg/L vs.(125.87±19.47)μg/L]andα-SMA[(90.63±19.57)μg/L vs.(101.39±23.62)μg/L](P＜0.05 or＜0.01).There was no significant difference in the incidence of adverse reactions between two groups(15.09％vs.16.98％,P=0.791).Conclusion:Empagliflozin combined with levosimendan has a significant therapeutic effect in patients with coronary heart disease and heart failure,which calld significantly improve cardiac function,exercise endurance,reduce levels of heart failure biomarkers and inflammatory factors,and inhibit myo-cardial fibrosis.

Objective:To explore the impact of the two-way referral model on compliance and prognosis in patients with heart failure.Methods:This bidirectional cohort study enrolled chronic heart failure (CHF) patients treated at Qilu Hospital of Shandong University or designated primary hospitals between March 2018 and March 2022. Patients were categorized into two groups based on referral status: two-way referral group (participating in the referral model with≥1 follow-up visit at primary hospitals) and the core hospital group (receiving treatment and follow-up exclusively at Qilu Hospital). Baseline clinical characteristics were collected and compared between groups. Patients underwent followed-up, with primary endpoints including follow-up rate, drug (β-blockers, angiotension converting enzyme inhibitor (ACEI)/angiotensin Ⅱ receptor blockers (ARB)/angiotensin receptor-neprilysin inhibitor (ARNI), sodium-glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists) utilization rate and target dose achievement rate. Secondary endpoints encompassed changes from baseline in left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), and N-terminal pro-brain natriuretic peptide (NT-proBNP), plus cardiovascular mortality and heart failure rehospitalization. Generalized linear mixed models analyzed longitudinal trends in LVEF, LVEDd, and NT-proBNP levels. Kaplan-Meier curves and Cox regression evaluated LVEF recovery rates, supplemented by subgroup analyses. Multivariate logistic regression was used to identify factors influencing target dose achievement rate for β-blockers and ACEI/ARB/ARNI therapies in CHF patients.Results:A total of 357 patients were enrolled, aged 53 (41, 63) years, including 256 males (71.7%). 157 patients were in the two-way referral group and 200 patients in the core hospital-treated group. Compared with the core hospital-treated group, the two-way referral group had lower baseline LVEF (28 (22, 34)% vs. 31 (23, 36)%, P=0.021) and systolic blood pressure (116 (104, 125) mmHg vs. 121 (109, 134) mmHg (1 mmHg=0.133 kPa), P=0.010). The 12-month follow-up rate of the two-way referral group was higher than the core hospital-treated group (73.8% vs. 56.0%, P=0.004). No significant between-group differences were observed in drug utilization rate of β-blockers, ACEI/ARB/ARNI, or sodium-glucose cotransporter 2 inhibitors during follow-up (all P>0.05), while mineralocorticoid receptor antagonists use showed a declining trend in both groups. Although the core hospital-treated group had higher target dose achievement rates for β-blockers (65.4% vs. 49.3%, P=0.042) and ACEI/ARB/ARNI (79.8% vs. 65.8%, P=0.046) than the two-way referral group, multivariate logistic regression indicated that the two-way referral model was not a negative predictor for these outcomes (all P>0.05). Both groups showed improved NT-proBNP, LVEDd, and LVEF from baseline (all P<0.001) with no significant difference in trends between groups (all P>0.05). There was no significant difference in the composite incidence (7.6% vs. 6.5%, P=0.674) and cumulative incidence (log-rank P=0.684) of cardiovascular death and heart failure rehospitalization at 12 months between two groups. Conclusion:The two-way referral model demonstrates advantages in improving medication adherence, drug utilization rates, and targetdoseachievement rates among CHF patients. This model not only promotes cardiac functional recovery but also reduces risks of cardiovascular mortality and heart failure rehospitalization, achieving comparable therapeutic and management outcomes to those observed in core hospital-treated patients.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective:To explore the effect of empagliflozin combined with levosimendan on plasma levels of type Ⅰcollagen(Collagen Ⅰ),connective tissue growth factor(CTGF),and α-smooth muscle actin(α-SMA)in patients with coronary heart disease(CHD)and heart failure(HF).Methods:This randomized controlled study enrolled 106 CHD+HF patients admitted to Linfen Central Hospital between June 2022 and June 2023.Patients were divid-ed into control group(n=53,treated with levosimendan)and combined treatment group(n=53,received addition-al empagliflozin).Both groups were treated for 12 weeks.The total effective rate,exercise endurance,cardiac function,levels of HF biomarkers,inflammatory factors,myocardial fibrosis indexes and incidence of adverse reac-tions were compared between two groups.Results:The total effective rate of combined treatment group was signif-icantly higher than that in the control group(94.34％vs.81.13％,P＜0.001).Compared with patients in the con-trol group,those in the combined treatment group had significant higher cardiac output(CO)[(4.62±0.89)L/min vs.(3.90±0.75)L/min],left ventricular ejection fraction(LVEF)[(55.42±6.09)％vs.(48.97±5.74)％]and 6-minute walking distance(6MWD)[(405.69±56.47)m vs.(295.65±41.32)m](P＜0.001 all),and signifi-cant lower levels of N-terminal pro B-type natriuretic peptide(NT-proBNP)[(192.06±29.02)pg/ml vs.(313.58±20.98)pg/ml],soluble suppression of tumorigenicity 2(sST2)[(53.33±5.79)μg/L vs.(60.04±6.88)μg/L],interleukin-1β(IL-1β)[(18.16±5.42)ng/L vs.(21.07±6.31)ng/L],high-sensitive C-reactive protein(hsCRP)[(1.69±0.41)mg/L vs.(1.98±0.56)mg/L],tumor necrosis factor α(TNF-α)[(0.87±0.26)ng/L vs.(1.19±0.32)ng/L],Collagen Ⅰ[(162.58±30.55)μg/L vs.(189.98±41.32)μg/L],CTGF[(114.26±14.89)μg/L vs.(125.87±19.47)μg/L]andα-SMA[(90.63±19.57)μg/L vs.(101.39±23.62)μg/L](P＜0.05 or＜0.01).There was no significant difference in the incidence of adverse reactions between two groups(15.09％vs.16.98％,P=0.791).Conclusion:Empagliflozin combined with levosimendan has a significant therapeutic effect in patients with coronary heart disease and heart failure,which calld significantly improve cardiac function,exercise endurance,reduce levels of heart failure biomarkers and inflammatory factors,and inhibit myo-cardial fibrosis.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To explore the impact of the two-way referral model on compliance and prognosis in patients with heart failure.Methods:This bidirectional cohort study enrolled chronic heart failure (CHF) patients treated at Qilu Hospital of Shandong University or designated primary hospitals between March 2018 and March 2022. Patients were categorized into two groups based on referral status: two-way referral group (participating in the referral model with≥1 follow-up visit at primary hospitals) and the core hospital group (receiving treatment and follow-up exclusively at Qilu Hospital). Baseline clinical characteristics were collected and compared between groups. Patients underwent followed-up, with primary endpoints including follow-up rate, drug (β-blockers, angiotension converting enzyme inhibitor (ACEI)/angiotensin Ⅱ receptor blockers (ARB)/angiotensin receptor-neprilysin inhibitor (ARNI), sodium-glucose cotransporter 2 inhibitors and mineralocorticoid receptor antagonists) utilization rate and target dose achievement rate. Secondary endpoints encompassed changes from baseline in left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVEDd), and N-terminal pro-brain natriuretic peptide (NT-proBNP), plus cardiovascular mortality and heart failure rehospitalization. Generalized linear mixed models analyzed longitudinal trends in LVEF, LVEDd, and NT-proBNP levels. Kaplan-Meier curves and Cox regression evaluated LVEF recovery rates, supplemented by subgroup analyses. Multivariate logistic regression was used to identify factors influencing target dose achievement rate for β-blockers and ACEI/ARB/ARNI therapies in CHF patients.Results:A total of 357 patients were enrolled, aged 53 (41, 63) years, including 256 males (71.7%). 157 patients were in the two-way referral group and 200 patients in the core hospital-treated group. Compared with the core hospital-treated group, the two-way referral group had lower baseline LVEF (28 (22, 34)% vs. 31 (23, 36)%, P=0.021) and systolic blood pressure (116 (104, 125) mmHg vs. 121 (109, 134) mmHg (1 mmHg=0.133 kPa), P=0.010). The 12-month follow-up rate of the two-way referral group was higher than the core hospital-treated group (73.8% vs. 56.0%, P=0.004). No significant between-group differences were observed in drug utilization rate of β-blockers, ACEI/ARB/ARNI, or sodium-glucose cotransporter 2 inhibitors during follow-up (all P>0.05), while mineralocorticoid receptor antagonists use showed a declining trend in both groups. Although the core hospital-treated group had higher target dose achievement rates for β-blockers (65.4% vs. 49.3%, P=0.042) and ACEI/ARB/ARNI (79.8% vs. 65.8%, P=0.046) than the two-way referral group, multivariate logistic regression indicated that the two-way referral model was not a negative predictor for these outcomes (all P>0.05). Both groups showed improved NT-proBNP, LVEDd, and LVEF from baseline (all P<0.001) with no significant difference in trends between groups (all P>0.05). There was no significant difference in the composite incidence (7.6% vs. 6.5%, P=0.674) and cumulative incidence (log-rank P=0.684) of cardiovascular death and heart failure rehospitalization at 12 months between two groups. Conclusion:The two-way referral model demonstrates advantages in improving medication adherence, drug utilization rates, and targetdoseachievement rates among CHF patients. This model not only promotes cardiac functional recovery but also reduces risks of cardiovascular mortality and heart failure rehospitalization, achieving comparable therapeutic and management outcomes to those observed in core hospital-treated patients.