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 analyze the MYH9 gene sequence of a patient with hereditary thrombocytopenia and diffuse large B-cell lymphoma and his family members, and to explore the relationship between MYH9 gene and tumors. METHODS: Peripheral blood samples were collected from the patients and their family members for complete blood count analysis. The platelet morphology was observed under microscope. The MYH9 gene sequence was analyzed by Whole Exon Sequencing and Sanger Sequencing. RESULTS: The mutation site c.279C>A:p.(Asn93Lys) in exon 2 of the MYH9 gene were found in patient and his family members, both presenting as thrombocytopenia. The platelet count was significantly increased after the administration of Avatrombopag. CONCLUSION A novel mutation of MYH9 was found in this study, and the case was sensitive to Avatrombopag, by exploring the relationship between the MYH9 gene and tumors, suggesting that the MYH9 gene may be associated with the development of diffuse large B-cell lymphoma.
Humans ; Myosin Heavy Chains/genetics* ; Thrombocytopenia/genetics* ; Mutation ; Male ; Lymphoma, Non-Hodgkin/genetics* ; Lymphoma, Large B-Cell, Diffuse/genetics* ; Molecular Motor Proteins/genetics* ; Pedigree

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

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::In patients with heatstroke, disseminated intravascular coagulation (DIC) is associated with greater risk of in-hospital mortality. However, time-consuming assays or a complex diagnostic system may delay immediate treatment. Therefore, the present study proposes a new heatstroke-induced coagulopathy (HIC) score in patients with heat illness as an early warning indicator for DIC.Methods::This retrospective study enrolled patients with heat illness in 24 Chinese hospitals from March 2021 to May 2022. Patients under 18 years old, with a congenital clotting disorder or liver disease, or using anticoagulants were excluded. Data were collected on demographic characteristics, routine blood tests, conventional coagulation assays and biochemical indexes. The risk factors related to coagulation function in heatstroke were identified by regression analysis, and used to construct a scoring system for HIC. The data of patients who met the diagnostic criteria for HIC and International Society on Thrombosis and Haemostasis defined-DIC were analyzed. All statistical analyses were performed using SPSS 26.0.Results::The final analysis included 302 patients with heat illness, of whom 131 (43.4%) suffered from heatstroke, including 7 death (5.3%). Core temperature ( OR = 1.681, 95% CI 1.291 - 2.189, p < 0.001), prothrombin time ( OR = 1.427, 95% CI 1.175 - 1.733, p < 0.001) and D-dimer ( OR = 1.242, 95% CI 1.049 - 1.471, p = 0.012) were independent risk factors for heatstroke, and therefore used to construct an HIC scoring system because of their close relation with abnormal coagulation. A total score ≥ 3 indicated HIC, and HIC scores correlated with the score for International Society of Thrombosis and Hemostasis-DIC ( r = 0.8848, p < 0.001). The incidence of HIC (27.5%) was higher than that of DIC (11.2%) in all of 131 heatstroke patients. Meanwhile, the mortality rate of HIC (19.4%) was lower than that of DIC (46.7%). When HIC developed into DIC, parameters of coagulation dysfunction changed significantly: platelet count decreased, D-dimer level rose, and prothrombin time and activated partial thromboplastin time prolonged ( p < 0.05). Conclusions::The newly proposed HIC score may provide a valuable tool for early detection of HIC and prompt initiation of treatment.

Objective To investigate the risk factors for bronchopulmonary dysplasia(BPD)in twin preterm infants with a gestational age of<34 weeks,and to provide a basis for early identification of BPD in twin preterm infants in clinical practice.Methods A retrospective analysis was performed for the twin preterm infants with a gestational age of<34 weeks who were admitted to 22 hospitals nationwide from January 2018 to December 2020.According to their conditions,they were divided into group A(both twins had BPD),group B(only one twin had BPD),and group C(neither twin had BPD).The risk factors for BPD in twin preterm infants were analyzed.Further analysis was conducted on group B to investigate the postnatal risk factors for BPD within twins.Results A total of 904 pairs of twins with a gestational age of<34 weeks were included in this study.The multivariate logistic regression analysis showed that compared with group C,birth weight discordance of>25%between the twins was an independent risk factor for BPD in one of the twins(OR=3.370,95%CI:1.500-7.568,P<0.05),and high gestational age at birth was a protective factor against BPD(P<0.05).The conditional logistic regression analysis of group B showed that small-for-gestational-age(SGA)birth was an independent risk factor for BPD in individual twins(OR=5.017,95%CI:1.040-24.190,P<0.05).Conclusions The development of BPD in twin preterm infants is associated with gestational age,birth weight discordance between the twins,and SGA birth.

During his studies at the Peking Union Medical College(1921-1929),Chen Zhiqian formed his thoughts on public health under the influences of modern medical education and the advanced thinking of the times,which laid an ideological foundation for his later engagement in rural health care and reflected the medical progress in China at that time.In the 1920s,Chen Zhiqian's thoughts on public health mainly encompassed five aspects.First,health was a cornerstone of the country's wealth and people's well-being.Second,he belived in comprehensive"big medicine"which emphasized the combination of prevention and treatment.Third,he advoca-ted the return of medicine to the state and the building of a medical system covering all people.Fourth,he advo-cated maternal training and institutional standardization,emphasizing child health protection.Fifth,he was com-mitted to the popularization of health science and advocated health education reform.Summarizing the above five aspects is of great significance for enriching and improving the academic evaluation about Chen Zhiqian and pro-vides a reference for today's work on public health.

Purpose: To intelligently diagnose whether there is bladder outlet obstruction (BOO) in female with decent detrusor contraction ability by focusing on urodynamic study (UDS) data. Materials and Methods: We retrospectively reviewed the UDS data of female patients during urination. Eleven easily accessible urinary flow indicators were calculated according to the UDS data of each patient during voiding period. Eight diagnosis models based on back propagation neural network with different input feature combination were constructed by analyzing the correlations between indicators and lower urinary tract dysfunction labels. Subsequently, the stability of diagnostic models was evaluated by five-fold cross-validation based on training data, while the performance was compared on test dataset. Results: UDS data from 134 female patients with a median age of 51 years (range, 27–78 years) were selected for our study.Among them, 66 patients suffered BOO and the remaining were normal. Applying the 5-fold cross-validation method, the model with the best performance achieved an area under the receiver operating characteristic curve (AUC) value of 0.949±0.060 using 9 UDS input features. The accuracy, sensitivity, and specificity for BOO diagnosis model in the testing process are 94.4%, 100%, and 89.3%, respectively. Conclusions The 9 significant indicators in UDS were employed to construct a diagnostic model of female BOO based on machine learning algorithm, which performs preferable classification accuracy and stability.

The increasing prevalence of chronic kidney disease (CKD) is a major global public health concern. Despite the complicated pathogenesis of CKD, renal fibrosis represents the most common pathological condition, comprised of progressive accumulation of extracellular matrix in the diseased kidney. Over the last several decades, tremendous progress in understanding the mechanism of renal fibrosis has been achieved, and corresponding potential therapeutic strategies targeting fibrosis-related signaling pathways are emerging. Importantly, extracellular vesicles (EVs) contribute significantly to renal inflammation and fibrosis by mediating cellular communication. Increasing evidence suggests the potential of EV-based therapy in renal inflammation and fibrosis, which may represent a future direction for CKD therapy.

Humans ; Bacteremia ; Cross Infection ; Methicillin-Resistant Staphylococcus aureus ; Retrospective Studies ; Sepsis ; Staphylococcal Infections/epidemiology* ; Staphylococcus aureus ; Tertiary Care Centers ; China