Objective To evaluate the effectiveness of schistosomiasis surveillance in Jiangsu Province during the stage moving from transmission control to transmission interruption, and to analyze the current risk and challenges, so as to provide the evidence for achieving the target of schistosomiasis elimination. Methods Schistosomiasis surveillance data were collected from Jiangsu Province from 2012 to 2024, and the endemic areas, Schistosoma japonicum infections in humans and livestock, Oncomelania hupensis snail distribution and implementation of integrated interventions were descriptively analyzed. In addition, the trends in areas with snails, seroprevalence of human S. japonicum infections and numbers of advanced schistosomiasis cases were assessed using a Joinpoint regression model. Results The endemic areas of schistosomiasis continued to shrink in Jiangsu Province from 2012 to 2024, with the number of schistosomiasis-eliminated counties (cities, districts) increasing from 53 (75.71%) to 63 (96.92%), and interruption of schistosomiasis transmission was achieved across the province. A total of 4 600 300 person-times were tested for serum antibodies against S. japonicum, with 28 719 person-times positive detected; and 616 500 person-times were tested S. japonicum infections among local residents in Jiangsu Province from 2012 to 2024, with only 3 egg-positives detected, and no egg-positives found since 2017. A total of 187 600 herd-times were tested for schistosomiasis in livestock, and no S. japonicum infections were found. O. hupensis snail survey was performed covering 1 018 408.97 hm², and a total of 35 556.35 hm² was found with snail-infested habitats, including 174.40 hm2 of emerging snail-infested habitats. A total of 1 102 800 O. hupensis snails were identified for S. japonicum infections, and no infections were found. The areas of snail-infested habitats appeared a tendency towards a rise in Jiangsu Province from 2019 to 2023 (APC = 23.67%, P < 0.05), and the actual areas of snail-infested habitats appeared a tendency towards a decline from 2012 to 2015 (APC = −22.77%, P < 0.05), and towards a rise from 2015 to 2023 (APC = 9.76%, P < 0.01). The seroprevalence of anti-S. japonicum antibodies appeared a tendency towards a decline among residents in Jiangsu Province from 2017 to 2023 (APC = −14.92%, P < 0.01). In addition, the number of newly diagnosed advanced schistosomiasis cases appeared a tendency towards a decline from 2012 to 2024 (APC = −12.02%, P < 0.01), and the numbers of advanced schistosomiasis patients requiring treatment showed a tendency towards a decline from 2012 to 2021 (APC = −10.56%, P < 0.01) and from 2021 to 2023 (APC = −20.06%, P < 0.01). Conclusions Great progresses had been achieved in schistosomiasis control in Jiangsu Province following transmission control, and transmission interruption had been achieved; however, there are still snail-infested habitats. High-intensity surveillance and integrated control are required to be maintained to advance the achievement of the target of schistosomiasis elimination in Jiangsu Province.

Objective To explore the prevalence of depressive symptoms in postoperative patients with ovarian cancer and to analyze its influencing factors from multiple dimensions, including clinical characteristics, psychological factors, and laboratory indicators. Methods A cross-sectional study was conducted, which enrolled 235 postoperative patients with ovarian cancer. Depressive status was assessed using the patient health questionnaire, and the demographic, pathological, and medical record data of the patients were collected using the generalized anxiety disorder scale, Pittsburgh sleep quality index, European organization for research and treatment of cancer quality of life questionnaire core 30, and ECOG performance status score. Peripheral blood tumor marker (CA125), routine blood test, lymphocyte subsets, and serum cytokine levels were measured. Univariate and multivariate binary logistic regression analysis were used for statistical analysis. Results The prevalence of depression in postoperative patients with ovarian cancer was 39.15% (92/235). Univariate analysis showed that ECOG score ≥ 2 points, pain, anxiety, poor sleep quality, low quality of life, low life satisfaction, tumor recurrence, six or more cycles of chemotherapy, as well as higher levels of CA125, NLR, and NAR, and lower hemoglobin levels were significantly associated with depression (all P<0.05). Multivariate binary Logistic regression analysis showed that anxiety (OR=1.975, 95%CI: 1.231-3.170), sleep efficiency (OR=4.181, 95%CI: 1.211-14.43), sleep latency (OR=34.806, 95%CI: 4.258-284.542), ECOG performance status score, cognitive function (OR=0.918, 95%CI: 0.868-0.97), and life satisfaction were independent risk factors for depression (all P<0.05). Laboratory indicators were not independent influencing factors in the multivariate Logistic regression model. Conclusion Depression in postoperative patients with ovarian cancer is influenced by physiological, psychological, and social factors. Clinical management should focus on patients with anxiety, sleep disorders, poor physical condition, and low life satisfaction, and a comprehensive prevention and treatment strategy centered on psychological intervention and taking into account symptom management and social support should be implemented.

Objective To investigate the factors influencing the development of extra-pulmonary tuberculosis(EPTB)in patients with viral hepatitis complicated by pulmonary tuberculosis(PTB).Methods A retrospective analysis was conducted on 427 patients with Hepatitis B Virus(HBV)and Hepatitis C Virus(HCV)infections complicated by PTB admitted to the tuberculosis department of Kunming Third People's Hospital from January 2015 to December 2020.Patients were divided into the EPTB complication group(n=72)and the non-EPTB complication group(n=355)based on the presence of EPTB.Clinical treatment data of patients were collected.Univariate and multivariate Logistic regression analyse were used to screen independent risk factors for EPTB as predictive factors.A nomogram prediction model was established for Extrapulmonary Tuberculosis(EPTB)complications in patients with viral hepatitis and Pulmonary Tuberculosis(PTB),evaluated using the Hosmer-Lemeshow test and ROC curve analysis.Results Among the 427 patients,292(68.3%)were male and 135(31.7%)were female,with 72 cases of EPTB,resulting in an incidence rate of 16.86%.In the EPTB group,there were 34 males(47.2%)and 38 females(52.8%).The types of EPTB included tuberculous pleuritis(21 cases,29%),tuberculous peritonitis(16 cases,22%),lymph node tuberculosis(13 cases,18%),tuberculous encephalitis(5 cases,6%),intestinal tuberculosis(6 cases,8%),bone tuberculosis(5 cases,6%),pelvic tuberculosis(3 cases,4%),and genitourinary tuberculosis(3 cases,4%).Multivariate logistic regression analysis showed that gender(OR=0.425,95%CI:0.250-0.722,P=0.02),low triglyceride(TG)levels(OR=0.837,95%CI:0.717-0.978,P=0.025),the tuberculosis-specific antigen A(ESAT-6)(OR=1.007,95%CI:1.003～1.011 were independent influencing factors for EPTB in patients with PTB complicated by HBV and HCV infections.The optimal cutoff value for the nomogram model is 0.192,with a sensitivity of 0.611,specificity of 0.710,Youden index of 0.741,positive likelihood ratio of 2.103,and negative likelihood ratio of 0.548.The Hosmer-Lemeshow test yielded χ2=2.631,P=0.955.ROC curve analysis showed an AUC of 0.693,95%CI:0.629 1～0.7574.Conclusion The prediction model based on gender,low TG levels and ESAT-6 can well predict the occurrence of EPTB to some extent,providing a reference for clinical treatment.

Objective To evaluate the relationship between nutritional parameters and the risk of venous thromboembolicism(VTE)in patients with tuberculosis so as to identify the risk factors and predictors of thrombosis and assist in the early identification of high-risk factors for VTE in patients with the pulmonary tuberculosis.Methods A total of 323 patients diagnosed with the pulmonary tuberculosis and hospitalized in Kunming Third People's Hospital from August 2021 to August 2023 were collected.According to the VTE risk assessment of non-operative patients,they were divided into the high-risk group and the low-risk group respectively with 116 and 207 in each group.The nutritional indicators with statistically significant differences between the two groups were screened by Lasso regression.Multivariate Logistic regression was used to screen the independent risk factors for high VTE risk in pulmonary tuberculosis patients,and a nomogram prediction model was constructed.The prediction model was evaluated by receiver operating characteristic curve(ROC),calibration curve,decision curve,and influence curve.Results Patients in the high-risk group were significantly older than those in the low-risk group(59 vs.41,P<0.001),hypertension,gender,and Type 2 diabetes did not differ significantly(P values were 0.084,0.724 and 0.488,respectively).9 variables were selected from the inter-group comparison and Lasso regression,including ALB,HCT,NRS2002 scores,HBDH,RDW-SD,RDW-CV,TG,CONUT scores,and NEFA.Multivariate Logistic regression analysis showed that ALB,NRS2002 scores,RDW-SD,and CONUT scores were independent influencing factors for the high risk of VTE scores in patients with tuberculosis(P<0.005).Area under the ROC curve showed that the AUC(0.892)for high-risk VTE scores in patients with the pulmonary tuberculosis was greater than that of ALB(0.803),NRS2002 score(0.735),RDW-SD(0.685),and CONUT score(0.774).Fitting prediction model:Logit(P):Y=0.433×NRS-0.136×ALB+0.411×CONUT score+0.072×RDW-SD-1.770,P=1/(1+e-Y)(Y:prediction index,P:prediction probability).Calibration curve showed that the model prediction tended to be consistent with the actual results(U:>0.05),and the decision curve and influence curve showed that the model can bring clinical benefits.Conclusion ALB,NRS2002 scores,RDW-SD,and CONUT scores are independent influencing factors for the high risk of VTE scores in patients with tuberculosis.They can guide the clinical practice,improve these indicators as soon as possible,reduce VTE scores,and reduce the thrombosis risk.At the same time,the prediction model performs well in the verification cohort,with its discrimination ability,calibration accuracy and clinical utility(decision curve analysis)all reaching a satisfactory level.

Purpose: This study assessed the performance of the ultrasound-guided attenuation parameter (UGAP) in diagnosing and grading hepatic steatosis in patients with metabolic dysfunctionassociated steatotic liver disease (MASLD). Magnetic resonance imaging proton density fat fraction (MRI-PDFF) served as the reference standard. Methods: Patients with hepatic steatosis were enrolled in this prospective study and underwent UGAP measurements. MRI-PDFF values of ≥5%, ≥15%, and ≥25% were used as references for the diagnosis of steatosis grades ≥S1, ≥S2, and S3, respectively. Spearman correlation coefficients and area under the receiver operating characteristic curves (AUCs) were calculated. Results: Between July 2023 and June 2024, the study included 88 patients (median age, 40 years; interquartile range [IQR], 36 to 46 years), of whom 54.5% (48/88) were men and 45.5% (40/88) were women. Steatosis grades exhibited the following distribution: 22.7% (20/88) had S0, 50.0% (44/88) had S1, 21.6% (19/88) had S2, and 5.7% (5/88) had S3. The success rate for UGAP measurements was 100%. The median UGAP value was 0.74 dB/cm/MHz (IQR, 0.65 to 0.82 dB/ cm/MHz), and UGAP values were positively correlated with MRI-PDFF (r=0.77, P<0.001). The AUCs of UGAP for the diagnoses of ≥S1, ≥S2, and S3 steatosis were 0.91, 0.90, and 0.88, respectively. In the subgroup analysis, 98.4% (60/61) of patients had valid controlled attenuation parameter (CAP) values. UGAP measurements were positively correlated with CAP values (r=0.65, P<0.001). Conclusion Using MRI-PDFF as the reference standard, UGAP demonstrates good diagnostic performance in the detection and grading of hepatic steatosis in patients with MASLD.

Objective To investigate the effect of health failure mode and effect analysis(HFMEA)in optimizing the management process of postoperative diabetes insipidus in children undergoing neurosurgery.Methods Based on HFMEA,a management flowchart for postoperative diabetes insipidus in children undergoing neurosurgery was created.Brainstorming was adopted to identify failure modes in the workflow,analyze risk factors,and develop improvement measures,thereby refining the management flowchart.The amelioration and prognosis of diabetes insipidus in these children before(October 2022 to November 2023)and after(January 2024 to February 2025)implementation of the management flowchart were compared.Results The HFMEA-based management process for postoperative diabetes insipidus in children undergoing neurosurgery alleviated the symptoms of diabetes insipidus regarding the number of diabetes insipidus in the pediatric intensive care unit(P=0.006),the average daily urine output in the pediatric intensive care unit(P=0.001),the proportion of electrolyte abnormalities at discharge/transfer(P=0.037),the duration of mechanical ventilation(P=0.007),and the length of stay in the intensive care unit(P=0.001).Conclusion The HFMEA-based management process for postoperative diabetes insipidus in children undergoing neurosurgery is beneficial to the optimization of the management process,the alleviation of postoperative diabetes insipidus,and the improvement of prognosis in these children.
Humans ; Diabetes Insipidus/etiology* ; Neurosurgical Procedures/adverse effects* ; Child ; Postoperative Complications/therapy* ; Healthcare Failure Mode and Effect Analysis ; Intensive Care Units, Pediatric ; Risk Factors

Objective To establish a chromatography-tandem mass spectrometry method for detecting chlorfenapyr and its metabolite tralopyril in blood,and to investigate the toxicokinetics in rats.Methods Chlorfenapyr(8 mg/kg)was administered orally to rats,and blood samples were collected from rats'canthus vein at 5 min,15 min,30 min,1 h,3 h,6 h,12 h,24 h and 48 h after administration.The blood samples were extracted using 100 μL of 5%formic acid solution and 400 μL of acetonitrile.Chlorfena-pyr was qualitatively and quantitatively detected by triple quadrupole gas chromatography-tandem mass spectrometry(GC-MS/MS)and tralopyril was detected by triple quadrupole liquid chromatography-tandem mass spectrometry(LC-MS/MS).The DAS 3.0 software was used to fit the toxicokinetic equa-tions and calculate the toxicokinetic parameters.Results Chlorfenapyr was detectable from 5 min to 24 h with a peak time of 1 h.Tralopyril was detectable from 15 min to 48 h with a peak time of 3 h.The toxicokinetic process of chlorfenapyr in rat blood conformed to a first-order absorption one-compartment open model,with the toxicokinetic equation described as C=e-0.265t-e-0.175t.Tralopyril con-formed to the first-order absorption three-compartment model,and the toxicokinetic equation was C=47 361.069e-2.209t-35 404.962e-1.486t+11 956.363e-0.512t.In the equations,C stands for the concentration of the target substance in the blood,e is the natural constant(≈2.718 28),and t stands for time.Conclu-sion This study optimized the detection method for chlorfenapyr and its metabolite tralopyril in blood.The toxicokinetic equations and parameters of chlorfenapyr and tralopyril can provide a reference for the estimation of oral intake time of chlorfenapyr.

Objective To investigate the effectiveness and safety of combining Omalizumab with compound glycyrrhetinic acid glycoside in the management of chronic urticaria that exhibits poor response to antihistamine therapy.Methods 92 patients with chronic urticaria who were treated with H1 antihistamines and still had symp-toms from February 2022 to February 2024 in the hospital were selected as the study subjects.The study partici-pants were randomly assigned to either the observation group,consisting of 46 cases,or the control group,also comprising 46 cases,using a random number table method.The control group received subcutaneous injection of omalizumab for treatment.The observation group was treated with oral compound glycyrrhizin tablets on the basis of the control group.After 24 weeks of treatment,compare the efficacy,adverse reactions,Urticaria Activity Score over 7 days(UAS7),Dermatology Life Quality Index(DLQI),Immunoglobulin(Ig)E,and High Sensitivity C-reactive protein(hs CRP)between the two groups,and record the recurrence rate.Results After treatment,the UAS7,DLQI,IgE and hs-CRP of both groups of patients decreased compared to before treatment,and the observation group demonstrated lower results compared to the control group(P<0.05).After treatment,the overall effectiveness rate in the observation group exceeded that of the control group(P<0.05),and the recurrence rate was lower than that of the control group(P<0.05).There was no statistically significant difference in the incidence of adverse reactions between the two groups of drugs(P>0.05).Conclusion The combination therapy of omali-zumab and compound glycyrrhetinic acid glycoside in the treatment of chronic urticaria patients with low response to antihistamines helps reduce IgE expression,improve treatment effectiveness,lower recurrence rates,and does not increase adverse drug reactions.

Objective:To explore the types and characteristics of self-management behaviors among stroke patients, as well as to analyze the influencing factors associated with these different types, providing a reference for developing intervention programs aimed at enhancing self-management behaviors in stroke patients.Methods:This study adopted a cross-sectional survey design. The stroke inpatients were selected through convenience sampling from the Department of Neurology at Huashan Hospital, Fudan University between October 2023 and August 2024. Data collection was conducted using the following instruments: the General Information Questionnaire, Stroke Self-Management Behavior Rating Scale, Self-Efficacy for Managing Chronic Disease 6-Item Scale, Stroke Health Knowledge Questionnaire, Social Support Rating Scale, Generalized Anxiety Disorder Scale, Patient Health Questionnaire-9, and the modified Rankin Scale. Stroke patients' self-management behaviors were categorized using systematic cluster analysis, and disordered multi-class Logistic regression was employed to identify the influencing factors associated with each category.Results:Finally, 210 stroke patients were enrolled, there were 148 males and 62 females, aged (60.82 ± 13.05) years. The total score of self-management behavior in stroke patients was (144.18 ± 23.24) points, with a score rate of 56.54%. Systematic cluster analysis identified four distinct self-management behaviors patterns: consistent implementers (25.71%, 54/210); unrealistically optimistic(54.76%, 115/210); optimistically proactive (13.81%, 29/210); and passive and resigned (5.71%, 12/210). Disordered multi-class Logistic regression analysis indicated that higher scores in stroke-related health knowledge were associated with a greater likelihood of being categorized as stable practice type and optimistic proactive type ( OR=1.130, 1.254, both P<0.05). Conversely, increased levels of depression correlate with a higher probability of being classified as passive waiting type ( OR=0.684, 0.722, 0.540, all P<0.05). Additionally, lower modified Rankin Scale scores were linked to an increased tendency to fall into the categories of stable practice type and blind optimism type ( OR=19.759, 23.148, both P<0.05). Conclusions:The self-management behaviors of stroke patients are generally suboptimal and exhibited distinct classification features. Significant differences are observed in stroke health knowledge, depression, and the modified Rankin Scale scores among the four patient types. Healthcare professionals should tailor intervention measures to the characteristics of each type to enhance patients' self-management capacity.

Objective:To construct a prediction model for the risk of sarcopenia in middle-aged and elderly patients with knee osteoarthritis (KOA) based on machine learning, and to provide a basis for carrying out the prevention of sarcopenia in patients with KOA.Methods:Clinical data of KOA patients from three tertiary hospitals in Guangdong Province were collected between December 2023 and September 2024 using a convenience sampling method. The data were randomly split into training and test sets at an 8:2 ratio, with the occurrence of sarcopenia as the outcome variable. Risk prediction models for sarcopenia were constructed using eight machine learning algorithms: logistic regression, K-nearest neighbors, support vector machine, decision tree, neural network, random forest, gradient boosting machine (GBM), and eXtreme gradient boosting. Model performance was evaluated based on metrics including the area under the receiver operating characteristic curve (AUC), accuracy, precision, sensitivity, specificity, and F1 score. The optimal model was selected, and feature importance was visualized using the Shapley Additive exPlanations (SHAP) method.Results:Data from 640 KOA patients were analyzed, 143 males and 497 females, (67.51± 7.72) years, with 136 cases (21.25%) developing sarcopenia. All eight prediction models showed high AUC values, with the GBM model demonstrating the best performance. Its metrics included an AUC of 0.926 (95% CI 0.874 - 0.965), accuracy of 0.852, precision of 0.611, sensitivity of 0.815, specificity of 0.861, and F1 score of 0.698. SHAP analysis identified body mass index, calf circumference, body fat percentage, WOMAC score, and age as the most important predictive features. Conclusions:The GBM-based risk prediction model for sarcopenia in middle- aged and elderly KOA patients demonstrated optimal performance, enabling healthcare professionals to accurately and promptly identify high-risk groups among these patients and to develop effective, evidence-based intervention strategies.