1.Explainable Machine Learning Model for Predicting Prognosis in Patients with Malignant Tumors Complicated by Acute Respiratory Failure: Based on the eICU Collaborative Research Database in the United States
Zihan NAN ; Linan HAN ; Suwei LI ; Ziyi ZHU ; Qinqin ZHU ; Yan DUAN ; Xiaoting WANG ; Lixia LIU
Medical Journal of Peking Union Medical College Hospital 2026;17(1):98-108
To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework. Clinical data of patients with malignant tumors and ARF were extracted from the eICU Collaborative Research Database in the United States, including demographic characteristics, comorbidities, vital signs, laboratory test indicators, and major interventions within the first 24 hours after ICU admission.The study outcome was ICU death.Enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3.Predictor variables were selected using least absolute shrinkage and selection operator (LASSO) regression.Five machine learning algorithms-extreme gradient boosting (XGBoost), support vector machine (SVM), Logistic regression, multilayer perceptron (MLP), and C5.0 Decision Tree-were employed to construct predictive models.Model performance was evaluated based on the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and other metrics.The optimal model was further interpreted using the Shapley additive explanations (SHAP) algorithm. A total of 3196 patients with malignant tumors complicated by ARF were included.The training set comprised 2, 261 patients and the validation set 935 patients; 683 patients died during ICU stay, while 2513 survived.LASSO regression ultimately selected 12 variables closely associated with patient ICU outcomes, including sepsis comorbidity, use of vasoactive drugs, and within the first 24 hours after ICU admission: minimum mean arterial pressure, maximum heart rate, maximum respiratory rate, minimum oxygen saturation, minimum serum bicarbonate, minimum blood urea nitrogen, maximum white blood cell count, maximum mean corpuscular volume, maximum serum potassium, and maximum blood glucose.After model evaluation, the XGBoost model demonstrated the best performance.The AUCs for predicting ICU mortality risk in the training and validation sets were 0.940 and 0.763, respectively; accuracy was 88.3% and 81.2%;sensitivity was 98.5% and 95.9%.Its predictive performance also remained optimal in sensitivity analyses.SHAP analysis indicated that the top five variables contributing to the model's predictions were minimum oxygen saturation, minimum serum bicarbonate, minimum mean arterial pressure, use of vasoactive drugs, and maximum white blood cell count. This study successfully developed a mortality risk prediction model for ICU patients with malignant tumors complicated by ARF based on a large-scale dataset and performed explainability analysis.The model aids clinicians in early identification of high-risk patients and implementing individualized interventions.
2.Serological and molecular genetic study of the Ael/AelB phenotype induced by the c. 575T>C variant in the ABO gene
Yanying DONG ; Qinqin ZUO ; Peixing XU ; Minggang ZHANG ; Xia JIANG ; Zixuan WANG ; Miao WANG ; Gengyuan LIU ; Yi DING ; Tianju WANG ; Junhui QUAN
Chinese Journal of Blood Transfusion 2026;39(7):922-927
Objective: To analyze the serological phenotypes and molecular genetic characteristics of a proband with ABO forward and reverse typing discrepancy and their family members, and to investigate the molecular genetic mechanism underlying the Ael/AelB phenotype caused by the c. 575T>C variant on an ABO
A1.02 background. Methods: Serological testing and adsorption-elution assays were performed for blood group identification of the proband and family members. PCR-SBT, cloning sequencing, and Nanopore third-generation sequencing were used to analyze ABO gene variants and haplotypes. Phyre2 and PyMOL were used to predict the effect of the p. Ile192Thr variant on the structure of glycosyltransferase A (GTA), and plasma GTA activity was evaluated using an in vitro transferase assay. Results: Among thirteen family members, four members showed a serological phenotype consistent with the Ael subtype and one with the AelB subtype. Cloning sequencing and third-generation sequencing confirmed that five family members carried the ABO
A1.02 (c. 575T>C) variant, which co-segregated with the weak A phenotype in the family. Structural modeling suggested that p. Ile192Thr may alter the local spatial conformation and hydrogen-bond interactions of GTA. Plasma GTA activity testing showed markedly reduced GTA activity in the tested individuals. Conclusion: The ABO
A1.02 (c. 575T>C) variant is associated with the Ael/AelB phenotype. The p. Ile192Thr substitution may weaken A antigen expression by altering GTA conformation and reducing enzymatic activity. This study provides additional evidence for the role of this variant in the Ael/AelB phenotype from the perspectives of familial inheritance, full-length haplotype analysis, and functional assessment, which is important for accurate ABO subtype identification and individualized transfusion strategies.
3.Association of short-term exposure to polycyclic aromatic hydrocarbons in ambient fine particulate matter with resident mortality: a case-crossover study
Sirong WANG ; Zhi LI ; Yanmei CAI ; Chunming HE ; Huijing LI ; Yi ZHENG ; Lu LUO ; Ruijun XU ; Yuewei LIU ; Huoqiang XIE ; Qinqin JIANG
Journal of Public Health and Preventive Medicine 2025;36(6):6-11
Objective To quantitatively assess the association of short-term exposure to polycyclic aromatic hydrocarbons (PAHs) in ambient fine particulate matter (PM2.5) with residents mortality. Methods A time-stratified case-crossover study was conducted from 2020 to 2022 among 10606 non-accidental residents by using the Guangzhou Cause of Death Surveillance System in Conghua District, Guangzhou. Exposure levels of PAHs in PM2.5 and meteorological data during the study period were obtained from the Center for Disease Control and Prevention in Conghua District and the China Meteorological Administration Land Data Assimilation System (CLDAS-V2.0), respectively. Conditional Poisson regression model was used to estimate the exposure-response association between PAHs and the mortality risk. Results Fluoranthene, chrysene, benzo[k]fluoranthene, benzo[a]pyrene, and indeno[1,2,3-cd]pyrene were significantly associated with an increased risk of mortality. For every one interquartile range increase in exposure levels, the non-accidental mortality risks increased by 8.33% (95% CI: 1.80%, 15.27%), 4.67% (95% CI: 1.86%, 7.57%), 6.07% (95% CI: 2.08%, 10.21%), 4.62% (95% CI: 1.85%, 7.47%), and 4.70% (95% CI: 0.53%, 9.03%), respectively. The estimated non accidental deaths attributable to exposure to fluoranthene, chrysene, benzo[k]fluorine, benzo[a]pyrene and indine[1,2,3-cd]pyrene were 5.91%, 6.08%, 6.51%, 6.46%, and 4.21%, respectively. Conclusions Short-term exposure to PAHs in PM2.5, including fluoranthene, chrysene, benzo[k]fluoranthene, benzo[a]pyrene and indine[1,2,3-cd]pyrene, was significantly associated with an increased risk of mortality among residents.
4.Gut microbiota and their metabolites in hemodialysis patients.
Junxia DU ; Xiaolin ZHAO ; Xiaonan DING ; Qinqin REN ; Haoran WANG ; Qiuxia HAN ; Chenwen SONG ; Xiaochen WANG ; Dong ZHANG ; Hanyu ZHU
Chinese Medical Journal 2025;138(4):502-504
5.Potential utility of albumin-bilirubin and body mass index-based logistic model to predict survival outcome in non-small cell lung cancer with liver metastasis treated with immune checkpoint inhibitors.
Lianxi SONG ; Qinqin XU ; Ting ZHONG ; Wenhuan GUO ; Shaoding LIN ; Wenjuan JIANG ; Zhan WANG ; Li DENG ; Zhe HUANG ; Haoyue QIN ; Huan YAN ; Xing ZHANG ; Fan TONG ; Ruiguang ZHANG ; Zhaoyi LIU ; Lin ZHANG ; Xiaorong DONG ; Ting LI ; Chao FANG ; Xue CHEN ; Jun DENG ; Jing WANG ; Nong YANG ; Liang ZENG ; Yongchang ZHANG
Chinese Medical Journal 2025;138(4):478-480
6.Construction of a new predictive score for severe fever with thrombocytopenia syndrome combined with bacterial/fungal infections based on clinical data
Ran WANG ; Yan DAI ; Qinqin PU ; Nannan HU ; Ke JIN ; Jun LI
Chinese Journal of Infectious Diseases 2025;43(4):202-209
Objective:To study the risk factors for combined bacterial/fungal infections in patients with severe fever with thrombocytopenia syndrome (SFTS) and to develop a novel and validated prediction model.Methods:The basic data and the results of the first laboratory examination after admission were retrospectively collected from patients diagnosed with SFTS who were hospitalized in the First Affiliated Hospital, Nanjing Medical University from January 2018 to December 2022. The patients were categorized into co-infected and non-co-infected groups according to whether they had co-infections with bacterial/fungal infections or not.Independent risk factors were screened by multivariate logistic regression analyses. A novel prediction model was constructed, and the predictive value of the model was assessed using receiver operating characteristic curve. Non-parametric tests and chi-square test were used for statistical analysis.Results:A total of 294 patients were included, and 62 cases were in the combined infection group including 39 cases of simple respiratory tract infections, 11 cases of simple bloodstream infections, four cases of simple urinary tract infections, four cases of respiratory tract combined with bloodstream infection, and four cases of respiratory tract combined with urinary tract infection. Acinetobacter baumannii was mostly found in bacterial infections, with a total of 19 strains, followed by Escherichia coli and Pseudomonas aeruginosa, both with seven strains. Aspergillus were mostly common in fungi, with a total of 16 strains which were all collected from patients with pulmonary infections. Compared with the non-co-infected group, patients in the co-infected group had longer hospital stays, with statistically significant differences ( Z=-6.18, P<0.001). The patients also had higher frequencies of bleeding symptoms, neurological symptoms, severe illness, and death, with statistically significant differences ( χ2=23.91, 16.37, 15.51 and 15.58, respectively, all P<0.001). The aspartate transaminase-to-platelet ratio index (APRI) was also higher in patients with coinfection, with a statistically significant difference ( Z=-4.64, P<0.001). Multivariate binary logistic regression showed that severe illness (odds ratio ( OR)=2.567, 95% confidence interval ( CI) 1.344 to 4.904, P=0.004), blood glucose level higher than 7.782 mmol/L ( OR=4.766, 95% CI 2.493 to 9.109, P<0.001), procalcitonin level higher than 0.228 μg/L ( OR=2.487, 95% CI 1.289 to 4.799, P=0.007), and APRI value higher than 6.268 ( OR=3.032, 95% CI 1.404 to 6.548, P=0.005) were the independent risk factors for co-infections in SFTS patients. Disease severity, blood glucose, procalcitonin, and APRI were combined to construct a novel predictive model: Infect-risk score=-3.331+ 0.654×severity (severe=1, non-severe=0)+ 0.160×blood glucose+ 0.066×procalcitonin+ 0.013×APRI. The AUC for this score was 0.764 (95% CI 0.698 to 0.830, P<0.001), with Youden index of 0.416, sensitivity of 0.839, and specificity of 0.578. Conclusions:Severe illness, blood glucose levels higher than 7.782 mmol/L, procalcitonin levels above 0.228 μg/L, and APRI values above 6.268 are independent risk factors for bacterial/fungal coinfection in SFTS patients. The constructed Infect-risk score model has good predictive value for bacterial/fungal coinfection in SFTS patients.
7.Research on the current status and influencing factors of post ICU syndrome in severe patients
Tingshu WANG ; Li YAO ; Yan LIU ; Bei JING ; Qinqin LI ; Tingrui WANG
Chinese Journal of Nursing 2025;60(19):2356-2363
Objective To explore the current situation and influencing factors of post-intensive care syndrome(PICS)in critically ill patients a month after their transfer out,and to provide a basis for formulating individualized intervention measures.Methods By the convenience sampling method,550 patients who were transferred out of the ICU of a tertiary A hospital in Guizhou Province for a month from April to November 2024 were selected as the survey subjects.The general information of the patients was collected and sorted out.During their stay in the ICU,the Barthel Index,the Richards Campbell Sleep Scale,and the Perceived Social Support Scale were employed for evaluation.A month after the patients were transferred out of the ICU,the assessment was completed through telephone follow-up using the Chinese version of the Brain Care Monitoring Questionnaire for Healthy Aging.According to the assessment a month after the patients were transferred out,they were divided into a PICS group and a non-PICS group.Univariate analysis and binary Logistic regression analysis were completed based on the data of the 2 groups.Results A total of 550 questionnaires were distributed,and 442 valid questionnaires were ultimately collected,with a valid questionnaire collection rate of 80.3%.Among them,194 cases(43.9%)were high-risk patients with PICS.Binary logistic regression analysis showed that advanced age,pulmonary infection,total hospitalization time>15 days,and internal environment disorder were the risk factors for PICS in ICU patients(P<0.05).Conclusion The risk of PICS is relatively high in critically ill patients a month after the transfer.Medical staff need to pay attention to patients who are older,have pulmonary infections and internal environment disorders,and formulate personalized intervention measures for different disease types to improve the long-term health prognosis of patients.
8.Comparative analysis of the efficacy of cold snare polypectomy and endoscopic mucosal resection in treatment of colonic adenoma in proximity to the orifice of appendix
Bin LIU ; Qinqin QI ; Xinglin CHEN ; Ke WEI ; Yuanyuan CAI ; Zhemin WANG ; Liuyong CHEN
China Journal of Endoscopy 2025;31(2):63-69
Objective To investigate the feasibility,efficacy and safety of cold snare polypectomy(CSP)and endoscopic mucosal resection(EMR)in treatment of colonic adenoma in proximity to the orifice of appendix.Methods Clinical data of 41 cases of colonic adenoma in the orifice of appendix treated with CSP(CSP group)and 15 cases treated with EMR(EMR group)from January 2018 to January 2023 were collected.The clinicopathological features and outcomes were analyzed.The main outcome was postoperative complications,including bleeding,perforation and postoperative appendicitis,while the secondary outcome was the total resection rate,block resection rate and local recurrence rate.Results The operation time and treatment cost of CSP group were shorter than EMR group,and the differences were statistically significant(P<0.05).The diameter of applicable lesions in CSP group was smaller than that in EMR group,and the proportion of lesions with tubular adenoma was significantly higher than that in EMR group.There were no significant differences in the time of admission,intestinal preparation score,length of stay,lesion morphology and lesion type between the two groups(P>0.05).Perforation and postoperative appendicitis were not observed in both groups,and delayed postoperative hemorrhage occurred in 1 case in the CSP group,but it could heal itself after surgery without endoscopic intervention.The complete resection rate was 100.0%in both groups.The total removal rate of CSP group was 100.0%,which was significantly higher than that of EMR group(86.7%),and the difference was statistically significant(P<0.05).The local recurrence rate was 2.4%(1/41)in CSP group,and no local recurrence was observed in EMR group(0/15),with no statistical significance(P>0.05).Conclusion CSP and EMR are safe and effective in the treatment of colonic adenoma in proximity to the orifice of appendix,and they are trustworthy.Compared with EMR,CSP is more applied to small diameter tubular adenomas,which has the characteristics of economy and time saving,but at the same time there is the risk of recurrence.EMR obviously has a wider application range,but there is a disadvantage in price and time,and individual cases need to be segmented resection.
9.Jasurolignoside from Ilex pubescens exerts a therapeutic effect on acute lung injury in vitro and in vivo by binding to TLR4.
Shan HAN ; Chi Teng VONG ; Jia HE ; Qinqin WANG ; Qiumei FAN ; Siyuan LI ; Jilang LI ; Min LIAO ; Shilin YANG ; Renyikun YUAN ; Hongwei GAO
Chinese Journal of Natural Medicines (English Ed.) 2025;23(9):1058-1068
Acute lung injury (ALI) is a severe disease caused by viral infection that triggers an uncontrolled inflammatory response. This study investigated the capacity of jasurolignoside (JO), a natural compound, to bind to Toll-like receptor 4 (TLR4) and treat ALI. The anti-inflammatory properties of JO were evaluated in vitro through Western blotting, enzyme-linked immunosorbent assay (ELISA), immunofluorescence staining, and co-immunoprecipitation. The investigation utilized a lipopolysaccharide (LPS)-induced ALI animal model to examine the therapeutic efficacy and mechanism of JO in vivo. JO attenuated inflammatory symptoms in infected cells and tissues by modulating the NOD-like receptor family pyrin domain containing protein 3 (NLRP3) inflammasome and the nuclear factor κB (NF-κB)/mitogen-activated protein kinase (MAPK) pathway. Molecular docking simulations revealed JO binding to TLR4 active sites, confirmed by cellular thermal shift assay. Surface plasmon resonance (SPR) demonstrated direct interaction between JO and TLR4 with a Kd value of 35.1 μmol·L-1. Moreover, JO inhibited tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β), and IL-6 secretion and reduced leukocyte, neutrophil, lymphocyte, and macrophage infiltration in ALI-affected mice. JO also enhanced lung function and reduced ALI-related mortality. Immunohistochemical staining demonstrated JO's ability to suppress TLR4 expression in ALI-affected mouse lung tissue. This study establishes that JO can bind to TLR4 and effectively treat ALI, indicating its potential as a therapeutic agent for clinical applications.
Toll-Like Receptor 4/chemistry*
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Animals
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Acute Lung Injury/chemically induced*
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Mice
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Humans
;
Ilex/chemistry*
;
Molecular Docking Simulation
;
Male
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NF-kappa B/immunology*
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Mice, Inbred C57BL
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NLR Family, Pyrin Domain-Containing 3 Protein/immunology*
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Tumor Necrosis Factor-alpha/genetics*
;
Interleukin-1beta/genetics*
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RAW 264.7 Cells
;
Disease Models, Animal
10.Association between short-term exposure to air pollution and outpatient and emergency visits for neurological diseases in Conghua District, Guangzhou from 2015 to 2022
Lu LUO ; Zhi LI ; Yanmei CAI ; Chunming HE ; Yi ZHENG ; Sirong WANG ; Ruijun XU ; Yuewei LIU ; Qinqin JIANG
Journal of Environmental and Occupational Medicine 2025;42(11):1307-1314
Background Exposure to air pollutants increases the risk of diseases in multiple systems, including respiratory and cardiovascular systems, yet its association with neurological diseases remains unclear. Objective To quantitatively evaluate the association between short-term exposure to air pollutants and outpatient and emergency visits for neurological diseases, identify potential susceptible populations, and quantify associated disease burden. Methods Daily 24-hour average concentrations of fine particulate matter (PM2.5), inhalable particulate matter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and carbon monoxide (CO), daily maximum 8-hour average concentration of ozone (O3), daily meteorological data (24-hour average temperature, 24-hour average relative humidity), and data on daily outpatient and emergency department visits for neurological diseases from two hospitals in Conghua District, Guangzhou, China, were collected from 2015 to 2022. A time-stratified case-crossover design was adopted, and a conditional Poisson regression model was constructed to analyze the association between air pollution exposure and neurological disease visits. Two-pollutant models and sensitivity analysis were used to validate model stability. Stratified analyses by season (cold season: from November to March; warm season: from April to October), sex (male, female), and age (≤45 years, 46–60 years, ≥61 years) were performed to identify vulnerable group. Additionally, the number and proportion of neurological disease visits attributable to short-term air pollutant exposure were calculated. Results A total of 72 673 outpatient and emergency department visits for neurological diseases were included during the study period. Most of the patients were middle-aged and elderly individuals (69.89% were over 45 years old) and females (60.25%). The results of single-pollutant models showed that for each interquartile range (IQR) increase in exposure to PM2.5, PM10, SO2, NO2, CO, and O3, the risk of outpatient and emergency department visits for neurological diseases increased by 7.54% (95%CI: 4.69%, 10.46%), 6.66% (95%CI: 3.92%, 9.46%), 16.72% (95%CI: 10.58%, 23.19%), 8.12% (95%CI: 4.82%, 11.53%), 5.60% (95%CI: 2.34%, 8.97%), and 6.11% (95%CI: 2.91%, 9.40%), respectively. The results of the two-pollutant model showed that the association between PM2.5 and SO2 exposure and outpatient and emergency department visits for neurological diseases were relatively stable. The stratified analyses showed that the effect of SO2 was stronger in the cold season. It was estimated that 8.32% (95%CI: 5.55%, 10.96%) and 6.65% (95%CI: 4.27%, 8.96%) of the outpatient and emergency department visits were attributable to short-term exposure to SO2 and PM2.5, respectively. Conclusion Exposure to PM2.5 and SO2 is associated with increased risks of outpatient and emergency visits for neurological diseases. SO2 shows stronger effects during the cold season, and exposure to air pollution contributes to up to 8.32% of neurological disease visits.


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