ObjectiveTo investigate the current status of assistive device use and unmet needs among persons with disabilities in Sichuan-Chongqing region, and to identify the key factors associated with satisfaction with these devices. MethodsFrom October, 2024 to February, 2025, quota sampling was adopted to recruit 1 040 persons with disabilities in Sichuan and 260 persons with disabilities in Chongqing. Telephone and online questionnaires were used to collect data on demographic characteristics, status of assistive device utilization and unmet assistive device needs, as well as satisfaction with assistive device use. Correlation analysis, multiple linear regression analysis and structural equation modeling were performed to identify key factors associated with satisfaction. ResultsA total of 1 186 valid responses were collected, of which 942 were from Sichuan Province and 244 from Chongqing Municipality. The utilization rate of assistive devices among persons with disabilities in Sichuan-Chongqing region was 61.9%, and the rate of unmet assistive device needs was 30.6%. The assistive device utilization rate of participants with agricultural household registration (57.98%) was lower than that of participants with non-agricultural household registration (66.86%). The utilization rate showed a J-shaped upward trend with the increase of educational attainment. Educational attainment (P = 0.002), perceived usefulness of assistive devices (P < 0.001), home living environment (P < 0.001), public environment (P < 0.001) and disability type (significant differences were found in visual and hearing disabilities compared with physical disability, P < 0.05) were key predictors of satisfaction with assistive device use. The impact of public environment on satisfaction was exerted through two indirect mediating paths: mediating effect via perceived usefulness of assistive devices (ind₁ = 0.357, 95%CI 0.279 to 0.437, P < 0.001), contributing approximately 70% of the total indirect effect; mediating effect via home living environment (ind₂ = 0.129, 95%CI 0.006 to 0.242, P = 0.038), contributing approximately 25% of the total indirect effect. ConclusionThere is a structural imbalance between assistive device use and demand in Sichuan-Chongqing region. People with psycho-intellectual disabilities are most likely to be excluded from the service chain because they neither perceive need nor access information. Education exerts a robust positive effect on both adoption and satisfaction, so training content must be tailored to different educational levels. Satisfaction is shaped by disability type, device usefulness and environmental factors. Future product development should therefore integrate functional and psychosocial dimensions. Priority should be given to micro-scale home-and-community accessibility retrofits before extending upward to public transportation and employment settings, to maximize the cost-effectiveness of limited funds.

ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

Objective To evaluate the characteristics, related therapeutic regimens, risk factors of cardiovascular adverse events (CVAEs) and prognosis in the current therapy of newly diagnosed multiple myeloma (NDMM) patients in China. Methods A retrospective observational study was performed on patients with NDMM treated at Zhongshan Hospital, Fudan University, from January 2013 to October 2021. The propensity score matching at a ratio of 1∶1 was employed to balance baseline confounders between the therapeutic group and the control group, and CVAEs incidences were compared between the corresponding groups. Independent risk factors for CVAEs were identified through Fine-Gray competing risk regression model. Kaplan-Meier survival curves and log-rank tests were used to assess overall survival and progression-free survival of patients. Results A total of 829 patients with NDMM were analyzed, with a median of 33.1 months of follow-up for survivors. CVAEs occurred in 65 patients (7.8%) during first-line treatment, and a total of 74 events were recorded, with 52.7% grade 3 or greater in severity. Arrhythmia (particularly atrial fibrillation), thrombotic event (TE), and heart failure were the most common types. The median time from treatment to the first occurrence of CVAEs was 26 days, while the medium occurrence time of TE was later than the other events (76 d vs 19 d, P＝0.003). The exposure to immunomodulatory drugs was related to a higher incidence of TEs, whereas other therapeutic regimens, including bortezomib, didn’t show the effect of cardiovascular toxicity. Results of multivariate analysis showed that Eastern Cooperative Oncology Group performance status ＞2, symptomatic heart diseases within three months before treatment, and estimated glomerular filtration rate≤50 mL·min⁻¹·(1.73 m²)⁻¹ were independent risk factors for CVAEs. Compared with patients without CVAE, patients who experienced CVAEs had significantly inferior progression-free survival and overall survival, and higher cardiovascular mortality (P＜0.001). Conclusions The incidence of CVAE is relatively high during first-line treatment in NDMM patients, and the prognosis of CVAE patients is poor. The risk of CVAE is significantly increased in patients with underlying cardiovascular diseases.

Objective: To explore the independent risk factors of allogeneic blood transfusion during perioperative period of cytoreductive surgery in patients with ovarian cancer, and to construct a predictive model to facilitate clinical risk assessment and optimize perioperative blood management. Methods: Clinical data of 156 patients who underwent cytoreductive surgery for ovarian cancer in our hospital from January 2020 to December 2025 were retrospectively collected. The patients were divided into transfusion group (n=51) and non-transfusion group (n=105) according to whether they received allogeneic blood transfusion during perioperative period. The 1∶1 propensity score matching (PSM) was used to correct the confounding factors. Independent sample t test or Mann-Whitney U test was used for measurement data, and chisquare test was used for enumeration data. Variables with P<0.05 in univariate analysis were included in binary logistic regression for multivariate analysis to determine independent risk factors. A nomogram model for perioperative allogeneic blood transfusion risk prediction was constructed based on independent risk factors. Bootstrap method (100 samples) was used for internal calibration verification. ROC curve was used to evaluate the discrimination efficiency, and decision curve analysis (DCA) was used to evaluate the clinical net benefit of the model. Results: After propensity matching, the baseline data of the two groups were balanced and comparable. Multivariate logistic regression analysis showed that preoperative prothrombin time (PT) (OR=2.666, 95%CI 1.249~5.693, P=0.011), preoperative hemoglobin (Hb) (OR=0.953, 95%CI 0.923~0.984, P=0.003), intraoperative blood loss (OR=1.004, 95%CI 1.001-1.006, P=0.004), preoperative anemia grade (OR=3.052, 95%CI 1.007-9.252, P=0.049) were independent influencing factors of perioperative allogeneic blood transfusion. The nomogram model based on the above four factors was significant (LR χ =58.617, P<0.001), and the internal calibration curve showed that the predicted probability of the model was in good agreement with the actual probability (mean absolute error=0.042). The area under the ROC curve (AUC) was 0.890, indicating good discrimination efficiency. DCA showed that the clinical net benefit of the model was better than that of the unified transfusion/non-transfusion strategy in the 0-0.45 risk threshold range. Conclusion: Intraoperative blood loss, preoperative PT, preoperative Hb and preoperative anemia grade are independent risk factors for perioperative allogeneic blood transfusion in patients undergoing cytoreductive surgery for ovarian cancer. The nomogram model based on the above factors has good predictive efficacy and clinical hierarchical decision-making value, which can provide reference for clinical implementation of individualized blood management for high-risk patients and reduction of unnecessary blood transfusion rate.

PURPOSE: Early mortality in major trauma has decreased, but MODS remains a leading cause of poor outcomes, driven by trauma-induced cytokine storms that exacerbate injuries and organ damage. METHODS: This prospective cohort study included 79 major trauma patients (ISS >15) treated in the National Center for Trauma Medicine, Peking University People's Hospital, from September 1, 2021, to July 31, 2023. Patients (1) with ISS >15 (according to AIS 2015), (2) aged 15-80 years, (3) admitted within 6 h of injury, (4) having no prior treatment before admission, were included. Exclusion criteria were (1) GCS score <9 or AIS score ≥3 for TBI, (2) confirmed infection, infectious disease, or high infection risk, (3) pregnancy, (4) severe primary diseases affecting survival, (5) recent use of immunosuppressive or cytotoxic drugs within the past 6 months, (6) psychiatric patients, (7) participation in other clinical trials within the past 30 days, (8) patients with incomplete data or missing blood samples. Admission serum inflammatory cytokines and pathophysiological data were analyzed to develop machine learning models predicting MODS within 7 days. LR, DR, RF, SVM, NB, and XGBoost were evaluated based on the area under the AUROC. The SHAP method was used to interpret results. RESULTS: This study enrolled 79 patients with major trauma, and the median (Q₁, Q₃) age was 51 (35, 59) years (52 males, 65.8%). The inflammatory cytokine data were collected for all participants. Among these patients, 35 (44.3%) developed MODS, and 44 (55.7%) did not. Additionally, 2 patients (2.5%) from the MODS group succumbed. The logistic regression model showed strong performance in predicting MODS. Ten key cytokines, IL-18, Eotaxin, MCP-4, IP-10, CXCL12, MIP-3α, MCP-1, IL-1RA, Cystatin C, and MRP8/14 were identified as critical to the trauma-induced cytokine storm and MODS development. Early elevation of these cytokines achieved high predictive accuracy, with an AUROC of 0.887 (95% CI 0.813-0.976). CONCLUSION Trauma-induced cytokine storms are strongly associated with MODS. Early identification of inflammatory cytokine changes enables better prediction and timely interventions to improve outcomes.
Humans ; Prospective Studies ; Middle Aged ; Male ; Female ; Adult ; Aged ; Cytokine Release Syndrome/etiology* ; Adolescent ; Young Adult ; Aged, 80 and over ; Wounds and Injuries/complications* ; Cytokines/blood* ; Multiple Organ Failure/diagnosis* ; Machine Learning

Objective To investigate the relationship between serum trimethylamine oxide(TMAO),endo-thelial cell specific molecule 1(Endocan)and cardiac function and pregnancy outcome in patients with hyper-tensive disorders of pregnancy(HDP).Methods A total of 182 patients with HDP admitted to Handan Ma-ternal and Child Health Hospital from January 2021 to June 2023(HDP group)and 98 healthy pregnant women admitted to this hospital during the same period(control group)were selected as research subjects.Serum TMAO,Endocan and left ventricular cardiac function indexes[left ventricular ejection fraction(LVEF),left ventricular end-diastolic volume(LVEDV)and left ventricular end-systolic volume(LVESV)]were compared between the two groups.According to pregnancy outcome,HDP patients were divided into poor outcome group(78 cases)and good outcome group(104 cases).Spearman correlation analysis was used to analyze the correlation between serum TMAO and Endocan and cardiac function indexes in HDP patients,and multi-factor Logistic regression was used to analyze the influencing factors of adverse pregnancy outcomes in HDP patients.The predictive value of serum TMAO and Endocan for adverse pregnancy outcomes in HDP patients was analyzed by receiver operating characteristic(ROC)curve.Results Compared with control group,serum TMAO,Endocan,LVEDV and LVESV were increased in HDP group,and LVEF was decreased(P＜0.05).Serum TMAO and Endocan in HDP patients were negatively correlated with LVEF(P＜0.05),and positively correlated with LVEDV and LVESV(P＜0.05).The incidence of adverse pregnancy outcomes in 182 HDP patients was 42.86％(78/182).Preeclampsia(PE),severe preeclampsia(SPE),24 h urine protein increase,LVEDV increase,LVESV increase,TMAO increase,Endocan increase were independent risk factors for adverse pregnancy outcomes in HDP patients,and LVEF increase was protective factor(P＜0.05).The area under the curve of serum TMAO combined with Endocan in predicting adverse pregnancy outcomes in HDP patients was 0.880,which was greater than 0.793 and 0.788 predicted by serum TMAO and Endocan a-lone.Conclusion The increase of serum TMAO and Endocan levels in HDP patients are relate to the decrease of cardiac function and adverse pregnancy outcomes,and the combined detection of the two has high predictive value for adverse pregnancy outcomes in HDP patients.

Objective To investigate the expression levels of peroxisome proliferator-activated receptor gamma coactivator-1β(PGC-1β),hypoxia-inducible factor-1α(HIF-1α),and resistin(RETN)in gouty arthri-tis(GA),and analyze their correlation with the degree of joint damage.Methods A total of 134 patients with GA in the hospital from January 2022 to October 2023 were selected as GA group,and 134 healthy people who underwent the physical examination in the same period were selected as control group.The serum expression levels of PGC-1β,HIF-1α and Retn were compared between the two groups.The expression levels of PGC-1β,HIF-1α and Retn in serum and synovial fluid of patients with different clinical characteristics in GA group were compared,the degree of joint destruction was graded according to the subjective pain grading method(VAS)and the patients were divided into a severe GA subgroup of 78 cases and a mild GA subgroup of 56 ca-ses.The expression levels of PGC-1β,HIF-1α,RETN,bone destruction factors[β-cross linked degradation products(β-CTX),tartrate resistant acid phosphatase-5b(TRACP5b),receptor activator of nuclear factor kappa B ligand(RANKL)]and inflammatory factors[tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β)]were compared among different degrees of joint destruction,and the correlation between serum and syno-vial fluid PGC-1β,HIF-1α,RETN and the degree of joint destruction,bone destruction factors,and inflamma-tory factors was analyzed.Results The expression level of PGC-1β in serum of GA group was lower than that of the control group,while the expression levels of HIF-1α and RETN in serum were higher than those of the control group(P＜0.05).There were statistically significant differences in serum and synovial fluid PGC-1β,HIF-1α,and RETN levels among GA patients with different clinical stages,affected joints,disease duration,and annual seizure frequency(P＜0.05).The expression levels of PGC-1β in the serum and synovial fluid of the severe GA subgroup were lower than those of the mild GA subgroup(P＜0.05),while the expression lev-els of HIF-1α and RETN were higher than those of the mild GA subgroup(P＜0.05).The expression levels ofβ-CTX and TRACP5b in the severe GA subgroup were higher than those in the mild GA subgroup(P＜0.05),while the expression level of RANKL was lower than that in the mild GA subgroup(P＜0.05).PGC-1βin serum and synovial fluid was negatively correlated with the degree of joint destruction,β-CTX,TRACP5b,TNF-α,and IL-1β,and positively correlated with RANKL.HIF-1α and RETN were positively correlated with the degree of joint destruction,β-CTX,TRACP5b,TNF-α,and IL-1β,and negatively correlated with RANKL.Conclusion PGC-1β,HIF-1α,and RETN are abnormally expressed in patients with GA,and are closely associ-ated with the degree of joint destruction,bone destruction factors,and inflammatory factors.They are expec-ted to become reliable indicators for evaluating the occurrence and progression of GA.

Objective To explore the relationship between serum pregnancy-specific protein 1(PSG1),stress-induced protein 2(Sestrin 2),growth arrest-specific protein 6(Gas6)and uterine artery blood flow pa-rameters and fetal growth restriction(FGR)in patients with gestational hypertension(GH).Methods A to-tal of 485 GH patients admitted to Handan Maternal and Child Health Hospital from January 2020 to October 2023 were selected as the research objects and divided into the occurrence group(81 cases)and the non-occur-rence group according to whether FGR occurred.The correlations between serum PSG1,Sestrin 2,Gas6 and uterine artery blood flow parameters[pulse index(PI),resistance index(RI),ratio of peak systolic velocity to end diastolic velocity(S/D)]was analysed,as well as the related influencing factors of FGR in GH patients.In addition,a Nomogram model based on the influencing factors was constructed to analyze the predictive value.Results The serum PSG1 level in occurrence group was significantly lower than that in non-occurrence group,and the serum Sestrin 2,Gas6 levels and PI,RI,S/D values were significantly higher than those in non-occurrence group(P＜0.05).Pearson correlation results showed that serum PSG1 was negatively correlated with the uterine artery blood flow parameters PI,RI,and S/D,and the levels of serum Sestrin 2 and Gas6 were positively correlated with the uterine artery blood flow parameters PI,RI,and S/D(P＜0.05).Gestational di-abetes mellitus,umbilical cord abnormalities,high Sestrin 2,high Gas6,high PI,high RI,and high S/D were independent risk factors for the occurrence of FGR in GH patients(P＜0.05),and increased PSG1 level was protective factor for the occurrence of FGR in GH patients(P＜0.05).Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC)of the Nomogram prediction model con-structed based on the influencing factors for predicting the occurrence of FGR in GH patients was 0.982,and the sensitivity and specificity were 0.943 and 0.938,respectively.The internal verification of the Bootstrap method shows that the Bias-corrected prediction curve basically coincides with the Ideal line,and the consis-tency index(C-index)was 0.964,indicating that the model was relatively stable.The decision curve shows that the threshold probability of this model was 0.01-1.00 and the net return rate was above 0.Conclusion Ser-um PSG1,Sestrin 2 and Gas6 in GH patients are closely related to uterine artery blood flow parameters and FGR,and the three are the influencing factors for the occurrence of FGR in GH patients.The constructed No-mogram model has a good predictive efficacy for FGR.

OBJECTIVE To evaluate the cost-effectiveness of finerenone combined with standard of care （SoC） in the treatment of heart failure with mildly reduced ejection fraction （HFmrEF） or preserved ejection fraction （HFpEF）. METHODS Based on a phase Ⅲ clinical trial， a Markov model was constructed from the perspective of China’s healthcare system to compare the treatment outcomes of finerenone combined with SoC regimen versus SoC regimen alone in the treatment of different cardiac functional statuses of HFmrEF/HFpEF. Using quality-adjusted life year （QALY） as the health output index， 3 times China’s per capita GDP in 2023 as the willingness-to-pay （WTP） threshold， a simulation was conducted with a 3-month cycle length and a 10- year time horizon， incorporating an annual discount rate of 5%. The dynamic changes across various stages of HFmrEF/HFpEF treated with finerenone combined with SoC versus SoC alone were simulated to evaluate the long-term effectiveness and costs of the two treatment strategies. Additionally， one-way sensitivity analysis and probabilistic sensitivity analysis were performed， to test the robustness of the results. RESULTS The incremental cost-effectiveness ratio （ICER） of the finerenone combined with SoC regimen versus SoC regimen alone was 179 504.75 yuan/QALY， which was below the WTP threshold set in this study， indicating that the finerenone combined with SoC regimen possessed certain economic advantages. The results of one-way sensitivity analysis showed that the utility value of NYHA Ⅱ status， the drug price of finerenone， the discount rate， and the probability of hospital transfer for both groups had a great influence on ICER， but did not affect the robustness of the model. The probabilistic sensitivity analysis also confirmed the robustness of the model. CONCLUSIONS Under the WTP threshold set in this study， finerenone combined with SoC is cost-effective in the treatment of HFmrEF/HFpEF， compared with the SoC regimen.

BACKGROUND: The American Heart Association recently released a new cardiovascular health (CVH) metric, Life's Essential 8 (LE8), for health promotion. However, the association between LE8 scores and the risk of chronic kidney disease (CKD) remains uncertain. We aimed to explore the association of LE8 scores with new-onset CKD and examine whether socioeconomic deprivation and genetic risk modify this association. METHODS: A total of 286,908 participants from UK Biobank and without prior CKD were included between 2006 and 2010. CVH was categorized using LE8 scores: low (LE8 scores <50), moderate (LE8 scores ≥50 but <80), and high (LE8 scores ≥80). The study outcome was new-onset CKD, ascertained by data linkage with primary care, hospital inpatient, and death data. Cox proportional hazard regression models were used to investigate the association between CVH categories and new-onset CKD. RESULTS: During a median follow-up of 12.5 years, 8857 (3.1%) participants developed new-onset CKD. Compared to the low CVH group, the moderate (adjusted hazards ratio [HR], 0.50; 95% confidence interval [CI]: 0.47-0.53) and high CVH (adjusted HR, 0.31; 95% CI: 0.27-0.34) groups had a significantly lower risk of developing new-onset CKD. The population-attributable risk associated with high vs. intermediate or low CVH scores was 40.3%. Participants who were least deprived ( vs.  most deprived; adjusted HR, 0.75; 95% CI: 0.71-0.79) and with low genetic risk of CKD ( vs.  high genetic risk; adjusted HR, 0.89; 95% CI: 0.85-0.94) had a significantly lower risk of developing new-onset CKD. However, socioeconomic deprivation and genetic risks of CKD did not significantly modify the relationship between LE8 scores and new-onset CKD (both P -interaction >0.05). CONCLUSION Achieving a higher LE8 score was associated with a lower risk of developing new-onset CKD, regardless of socioeconomic deprivation and genetic risks of CKD.
Humans ; Renal Insufficiency, Chronic/epidemiology* ; Male ; Female ; Middle Aged ; Genetic Predisposition to Disease/genetics* ; Aged ; Risk Factors ; Adult ; Proportional Hazards Models ; Socioeconomic Factors