Objective To explore the effects of the Otago Exercise Program(OEP)on activities of daily living,muscle strength,balance,and physical function in older adults with sarcopenia,to compare OEP with conventional exercise training,and to provide a basis for clinical rehabilitation programs for older adults with sarcopenia.Methods In this randomized controlled trial,120 older adults clinically diagnosed with sarcopenia were enrolled.The participants were randomly assigned to the OEP intervention group(experimental group)and the conventional exercise intervention group(control group),with 60 in each group.The experimental group underwent 12 weeks of OEP training,three times a week,with each session lasting 45 minutes.The control group underwent conventional exercise training following the same schedule.The Modified Barthel Index was used as the primary outcome measure to assess activities of daily living.Secondary outcome measures included muscle strength,gait stability,dynamic balance,and physical function status,evaluated using grip strength,6-meter walking speed,the Timed Up and Go Test(TUGT),and the Short Physical Performance Battery(SPPB).Results A total of 120 older adults with sarcopenia were included.The mean age of the participants was(80.17±8.48)years.Baseline data before treatment showed no statistically significant differences between the two groups.Both groups completed the treatment within 12 weeks without experiencing any adverse events.The baseline data for the experimental group were as follows,MBI at(67.00±22.76)points,hand grip strength at(15.29±4.94)kg,gait speed at(0.61±0.26)m/s,TUGT time at(15.05±6.74)s,and SPPB score at(6.17±1.40)points,while the corresponding post-intervention findings were as follows,(78.72±15.83)points,(17.67±5.83)kg,(0.77±0.28)m/s,(13.49±6.16)s,and(9.25±1.71)points,respectively.The experimental group showed improvements in all measures from baseline to post-intervention(P＜0.05 for all measures).As for the control group,the baseline data for the corresponding measures were as follows,(67.20±22.12)points,(15.00±5.35)kg,(0.58±0.23)m/s,(17.29±6.90)s,and(6.00±1.24)points,respectively.The post-intervention findings increased to(71.13±20.28)points,(15.47±5.72)kg,(0.64±0.28)m/s,(16.50±6.99)s,and(6.73±1.61)points,respectively,but the changes were not statistically significant(P＞0.05).Furthermore,an intergroup comparison of intervention effects(post-intervention minus preintervention)revealed significant differences in mean changes from baseline.The experimental group demonstrated improvements of(+11.72±6.32)points in modified Barthel Index,(+11.72±6.32)kg in grip strength,(+0.16±0.09)m/s in gait speed,(—1.56±1.32)s in TUGT time,and(—1.56±1.32)points in SPPB score.In contrast,the control group showed smaller changes of(+3.93±5.65)points,(+0.47±1.37)kg,(+0.06±0.07)m/s,(—0.79±1.54)s,and(+0.73±1.12)points,respectively(all P＜0.05).Intergroup comparisons revealed superior outcomes in the experimental group across all measures.Conclusion OEP significantly enhances activities of daily living,improves muscle strength,balance,and physical function in older adults,and is more effective than conventional rehabilitation exercise programs,making it suitable for extensive clinical application.

Objective To investigate plasma protein expression changes in heatstroke patients using proteomics technology and to identify reliable prognostic biomarkers.Methods A retrospective analysis was conducted on 20 heatstroke patients hospitalized at the 908th Hospital of the Chinese PLA Joint Logistics Support Force from July 2022 to February 2024.Patients were divided into survival(n=16)and death groups(n=4)based on 28-day outcomes.Fasting venous blood samples were collected from both groups for proteomic analysis.Liquid chromatography-mass spectrometry(LC-MS/MS)was used to identify and screen differentially expressed proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)enrichment analyses were performed.LASSO regression was applied to screen key prognostic biomarkers,and receiver operating characteristic(ROC)curve analysis was used to evaluate their predictive value.Results A total of 27 upregulated and 90 downregulated proteins were identified between the two groups.These proteins were primarily involved in biological processes such as immune responses,complement activation,and metabolic processes.LASSO regression analysis indicated that actin-related protein 2(ARP2),cysteine-rich scavenger receptor type 1 M130(CD163),and catalase(CAT)could serve as effective biomarkers for evaluating heatstroke prognosis.ROC curve analysis demonstrated that ARP2 had higher diagnostic efficacy(AUC=0.98,sensitivity=0.80,specificity=1.00)compared to CD163(AUC=0.94,sensitivity=0.76,specificity=1.00),CAT(AUC=0.96,sensitivity=0.67,specificity=1.00),and acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(AUC=0.79,sensitivity=0.44,specificity=1.00).Conclusion Elevated plasma ARP2 level has good clinical value for predicting poor prognosis in heatstroke patients.

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

Objective To comprehensively evaluate the multidimensional impact of the"Tianjin Experience"of Chest Pain Center(CPC)development on in-hospital mortality,optimization of treatment workflows,and regional coordination of care for patients with acute myocardial infarction(AMI),with the aim of providing scientific evidence to further improve the model and enhance AMI treatment outcomes.Methods This study analyzed data from the"Cardiovascular and Cerebrovascular Acute Events Surveillance System"maintained by the Tianjin Center for Disease Control and Prevention from 2013 to 2024.A segmented regression model was applied to assess the long-term trends in in-hospital mortality from acute myocardial infarction(AMI),with a particular focus on evaluating the impact of the chest pain center program on treatment outcomes.Additionally,supplementary analyses were conducted using surveillance data from the Tianjin Chest Pain Center Quality Control Team between 2017 and 2024.To verify the effectiveness of treatment process optimization,temporal trends in key time-based process indicators were assessed,including Door-in-Door-out(DIDO)time at non-PCI hospitals,Door-to-Wire(D-to-W)time,and First Medical Contact to Wire(FMC-to-W)to wire time.Results According to the data from the Tianjin Center for Disease Control and Prevention,the average 28-day AMI mortality rate in the overall patient population was 9.85％.Between 01/2013 and 12/2014,the mortality rate showed a significant upward trend(P＜0.01),followed by a downward trend from 01/2015 to 12/2024,although the latter did not reach statistical significance(P＞0.05).From 2013 to 2024,a total of 27 633 AMI cases with complete clinical records were collected from Tianjin Chest Hospital,with an average 28-day mortality rate of 4.55％.The mortality rate exhibited a decreasing trend from 01/2013 to 12/2016,with an annual percent change(APC)of-7.56(P＜0.05).From 01/2017 to 12/2024,the trend stabilized,with an APC of 0.39(P＞0.05).Conclusions The development of the CPC system in Tianjin significantly reduced key treatment times and improved the overall efficiency of AMI management.While population-level AMI mortality rates began to decline after 2015,the rate of improvement has slowed,indicating a continued need for optimizing the regional coordinated care system to further enhance patient outcomes.

Aim To explore the antioxidative effect of the Chinese medicine Baitouweng(BTW)on treating ulcerative colitis(UC).Methods Sixty male mice were randomly divided into six groups:control,dextran sulfate sodium(DSS)(3 g·105 L-1),BTW(20,10,and 5 g·kg-1),and 5-aminosalicylic acid(5-ASA)(800 mg·kg-1).UC model was constructed by 3％DSS for seven days,and the UC model was given by ga-vage once daily from the 5 th day of modeling for seven days.Results BTW effectively reduced the symptoms and histopathological scores of UC mice.Additionally,it downregulated the inflammatory factors,interleukin(IL)-6 and IL-1 β,the immunoglobulins vascular cell adhesion molecule 1 and intercellular adhesion mole-cule 1,and metalloprotease matrix metallopeptidase 9.Moreover,it downregulated high mobility group box 1 protein.Furthermore,it inhibited the nuclear factor er-ythroid 2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)pathway.Conclusions BTW improves the general condition,inflammatory indexes and oxidative stress level,and its mechanism may be related to inhib-iting the level of HMGB1 to regulate the Nrf-2/HO-1 signaling pathway and rescue intestinal barrier-related protein expression.

Aim To explore the antioxidative effect of the Chinese medicine Baitouweng(BTW)on treating ulcerative colitis(UC).Methods Sixty male mice were randomly divided into six groups:control,dextran sulfate sodium(DSS)(3 g·105 L-1),BTW(20,10,and 5 g·kg-1),and 5-aminosalicylic acid(5-ASA)(800 mg·kg-1).UC model was constructed by 3％DSS for seven days,and the UC model was given by ga-vage once daily from the 5 th day of modeling for seven days.Results BTW effectively reduced the symptoms and histopathological scores of UC mice.Additionally,it downregulated the inflammatory factors,interleukin(IL)-6 and IL-1 β,the immunoglobulins vascular cell adhesion molecule 1 and intercellular adhesion mole-cule 1,and metalloprotease matrix metallopeptidase 9.Moreover,it downregulated high mobility group box 1 protein.Furthermore,it inhibited the nuclear factor er-ythroid 2-related factor 2(Nrf2)/heme oxygenase-1(HO-1)pathway.Conclusions BTW improves the general condition,inflammatory indexes and oxidative stress level,and its mechanism may be related to inhib-iting the level of HMGB1 to regulate the Nrf-2/HO-1 signaling pathway and rescue intestinal barrier-related protein expression.

Objective To comprehensively evaluate the multidimensional impact of the"Tianjin Experience"of Chest Pain Center(CPC)development on in-hospital mortality,optimization of treatment workflows,and regional coordination of care for patients with acute myocardial infarction(AMI),with the aim of providing scientific evidence to further improve the model and enhance AMI treatment outcomes.Methods This study analyzed data from the"Cardiovascular and Cerebrovascular Acute Events Surveillance System"maintained by the Tianjin Center for Disease Control and Prevention from 2013 to 2024.A segmented regression model was applied to assess the long-term trends in in-hospital mortality from acute myocardial infarction(AMI),with a particular focus on evaluating the impact of the chest pain center program on treatment outcomes.Additionally,supplementary analyses were conducted using surveillance data from the Tianjin Chest Pain Center Quality Control Team between 2017 and 2024.To verify the effectiveness of treatment process optimization,temporal trends in key time-based process indicators were assessed,including Door-in-Door-out(DIDO)time at non-PCI hospitals,Door-to-Wire(D-to-W)time,and First Medical Contact to Wire(FMC-to-W)to wire time.Results According to the data from the Tianjin Center for Disease Control and Prevention,the average 28-day AMI mortality rate in the overall patient population was 9.85％.Between 01/2013 and 12/2014,the mortality rate showed a significant upward trend(P＜0.01),followed by a downward trend from 01/2015 to 12/2024,although the latter did not reach statistical significance(P＞0.05).From 2013 to 2024,a total of 27 633 AMI cases with complete clinical records were collected from Tianjin Chest Hospital,with an average 28-day mortality rate of 4.55％.The mortality rate exhibited a decreasing trend from 01/2013 to 12/2016,with an annual percent change(APC)of-7.56(P＜0.05).From 01/2017 to 12/2024,the trend stabilized,with an APC of 0.39(P＞0.05).Conclusions The development of the CPC system in Tianjin significantly reduced key treatment times and improved the overall efficiency of AMI management.While population-level AMI mortality rates began to decline after 2015,the rate of improvement has slowed,indicating a continued need for optimizing the regional coordinated care system to further enhance patient outcomes.

Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Background/Aims: Chronic hepatitis C (CHC) patients who failed antiviral therapy are at increased risk for hepatocellular carcinoma (HCC). This study assessed the potential role of metformin and statins, medications for diabetes mellitus (DM) and hyperlipidemia (HLP), in reducing HCC risk among these patients. Methods: We included CHC patients from the T-COACH study who failed antiviral therapy. We tracked the onset of HCC 1.5 years post-therapy by linking to Taiwan’s cancer registry data from 2003 to 2019. We accounted for death and liver transplantation as competing risks and employed Gray’s cumulative incidence and Cox subdistribution hazards models to analyze HCC development. Results: Out of 2,779 patients, 480 (17.3%) developed HCC post-therapy. DM patients not using metformin had a 51% increased risk of HCC compared to non-DM patients, while HLP patients on statins had a 50% reduced risk compared to those without HLP. The 5-year HCC incidence was significantly higher for metformin non-users (16.5%) versus non-DM patients (11.3%; adjusted sub-distribution hazard ratio [aSHR]=1.51; P=0.007) and metformin users (3.1%; aSHR=1.59; P=0.022). Statin use in HLP patients correlated with a lower HCC risk (3.8%) compared to non-HLP patients (12.5%; aSHR=0.50; P<0.001). Notably, the increased HCC risk associated with non-use of metformin was primarily seen in non-cirrhotic patients, whereas statins decreased HCC risk in both cirrhotic and non-cirrhotic patients. Conclusions Metformin and statins may have a chemopreventive effect against HCC in CHC patients who failed antiviral therapy. These results support the need for personalized preventive strategies in managing HCC risk.