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

OBJECTIVES: To study the effect of prophylactic phenytoin (PHT) or levetiracetam (LEV) on busulfan (BU) blood concentration in children undergoing hematopoietic stem cell transplantation. METHODS: Pediatric patients conditioned with BU plus cyclophosphamide and fludarabine at the First People's Hospital of Chenzhou from September 2023 to February 2025 were retrospectively included. Patients were grouped by prophylactic antiepileptic regimen into PHT (n=24) and LEV (n=26). BU blood concentrations at the end of infusion (0 hour) and at 1, 2, and 4 hours post-infusion were compared between groups. RESULTS: At 0 hour post-infusion, BU blood concentrations did not differ significantly between groups (P>0.05). At 1, 2, and 4 hours post-infusion, BU blood concentrations were higher in the LEV group than in the PHT group (P<0.05). The area under the concentration-time curve from 0 to ∞ (AUC_0-∞) was greater in the LEV group (P<0.001), and the attainment rate of AUC_0-∞ was higher in the LEV group than in the PHT group (73% vs 21%, P<0.001). No significant differences were observed between groups in time to hematopoietic engraftment or in the incidence of BU-related adverse drug reactions (P>0.05). CONCLUSIONS Compared with PHT, LEV prophylaxis is associated with higher BU blood concentration and a higher AUC_0-∞ attainment rate. There is no observed difference in BU efficacy or safety between PHT and LEV.
Humans ; Levetiracetam/therapeutic use* ; Busulfan/pharmacokinetics* ; Hematopoietic Stem Cell Transplantation ; Male ; Female ; Child ; Child, Preschool ; Phenytoin/pharmacology* ; Infant ; Retrospective Studies ; Anticonvulsants/pharmacology* ; Adolescent

To promote the effective implementation of China's Essential Public Health Services Program(EPHSP)and ensure the secure and efficient utilization of project funds,China officially initiated the performance evaluation of EPHSP in 2011.This performance evaluation has evolved through three distinct phases:initial exploration(2011-2014),steady advancement(2015-2018),and reform and enhancement(2019—present).The evaluation objectives have progressively expanded from an initial focus on fund security and service coverage to a broader emphasis on enhancing service quality,improving residents'health status and sense of benefit,and facilitating the refinement of policy frameworks and the implementation of primary responsibilities.Performance evaluation has emerged as a critical instrument for strengthening project governance and optimizing resource allocation,gradually establishing a performance-driven incentive mechanism that aligns rewards with both the quantity and quality of work.This approach has effectively contributed to the continuous improvement of service quality.To further advance the high-quality development of EPHSP,future efforts should optimize the performance evaluation system,prioritize the adoption of a full-cycle performance management approach and the integration of health outcome-based indicators.Additionally,it is essential to deepen the application of information technologies to enhance the precision and efficiency of evaluations,and to innovate mechanisms for utilizing evaluation results to reinforce accountability at the local level.These measures will collectively strengthen project performance management capabilities.

Objective To summarize the imaging characteristics of occult rib fracture(ORF),analyze the causes of missed diagnosis and misdiagnosis of ORF,and explore strategies to improve the detection rate of ORF.Methods A total of 142 patients with rib fractures who underwent multi spiral computed tomography(MSCT)were selected.The initial examination was conducted within 1 week after the injury,and follow-up examinations were performed at multiple time points after 1 week post-injury.A retrospective analysis was conducted to review the fracture detection and locations during the follow-up period.The time of fracture edge sclerosis or callus growth was observed in the young group(17 cases),middle-aged group(64 cases),and elderly group(61 cases).Results The anterior segment of the ribs was the predilection site for occult fractures,with 199 cases(53.4％).The missed diagnosis rates of fracture were higher for fractures near the costal cartilage segment and the posterior segment of the ribs,with missed diagnosis rates of 49.4％and 58.8％,respectively.Compared with the number of rib fractures identified in the initial examination,there was a statistically significant difference in the number of rib fractures at 3-6 weeks after injury(P＜0.05).The time of local sclerosis or callus growth in the young,middle-aged and elderly groups was(18.76±3.849)d,(26.14±6.597)d,and(37.69±5.726)d,respectively,with statistically significantl differences between the groups(P＜0.05).Conclusion MSCT has certain limits in diagnosing ORF in the short term after injury.Primarily observing the predilection sites and missed sites of occult fractures,systematically recognizing the imaging characteristics of ORF,and adopting the optimal detection-time window for patients of different age groups can reduce the missed diagnosis rate and misdiagnosis rate of ORF and improve the detection rate of fractures.This provides accurate and objective basis for clinical and forensic identification,with significant clinical importance and application value.

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.

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.

To promote the effective implementation of China's Essential Public Health Services Program(EPHSP)and ensure the secure and efficient utilization of project funds,China officially initiated the performance evaluation of EPHSP in 2011.This performance evaluation has evolved through three distinct phases:initial exploration(2011-2014),steady advancement(2015-2018),and reform and enhancement(2019—present).The evaluation objectives have progressively expanded from an initial focus on fund security and service coverage to a broader emphasis on enhancing service quality,improving residents'health status and sense of benefit,and facilitating the refinement of policy frameworks and the implementation of primary responsibilities.Performance evaluation has emerged as a critical instrument for strengthening project governance and optimizing resource allocation,gradually establishing a performance-driven incentive mechanism that aligns rewards with both the quantity and quality of work.This approach has effectively contributed to the continuous improvement of service quality.To further advance the high-quality development of EPHSP,future efforts should optimize the performance evaluation system,prioritize the adoption of a full-cycle performance management approach and the integration of health outcome-based indicators.Additionally,it is essential to deepen the application of information technologies to enhance the precision and efficiency of evaluations,and to innovate mechanisms for utilizing evaluation results to reinforce accountability at the local level.These measures will collectively strengthen project performance management capabilities.

Objective To summarize the imaging characteristics of occult rib fracture(ORF),analyze the causes of missed diagnosis and misdiagnosis of ORF,and explore strategies to improve the detection rate of ORF.Methods A total of 142 patients with rib fractures who underwent multi spiral computed tomography(MSCT)were selected.The initial examination was conducted within 1 week after the injury,and follow-up examinations were performed at multiple time points after 1 week post-injury.A retrospective analysis was conducted to review the fracture detection and locations during the follow-up period.The time of fracture edge sclerosis or callus growth was observed in the young group(17 cases),middle-aged group(64 cases),and elderly group(61 cases).Results The anterior segment of the ribs was the predilection site for occult fractures,with 199 cases(53.4％).The missed diagnosis rates of fracture were higher for fractures near the costal cartilage segment and the posterior segment of the ribs,with missed diagnosis rates of 49.4％and 58.8％,respectively.Compared with the number of rib fractures identified in the initial examination,there was a statistically significant difference in the number of rib fractures at 3-6 weeks after injury(P＜0.05).The time of local sclerosis or callus growth in the young,middle-aged and elderly groups was(18.76±3.849)d,(26.14±6.597)d,and(37.69±5.726)d,respectively,with statistically significantl differences between the groups(P＜0.05).Conclusion MSCT has certain limits in diagnosing ORF in the short term after injury.Primarily observing the predilection sites and missed sites of occult fractures,systematically recognizing the imaging characteristics of ORF,and adopting the optimal detection-time window for patients of different age groups can reduce the missed diagnosis rate and misdiagnosis rate of ORF and improve the detection rate of fractures.This provides accurate and objective basis for clinical and forensic identification,with significant clinical importance and application value.

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.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*