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.

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.

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.

OBJECTIVE To explore the effects of piperacillin/tazobactam combined with acetylcysteine solution on severe pneumonia after cerebral infarction,and to analyze its impact on cardiopulmonary and neurological function.METHODS A total of 86 patients with severe pneumonia after cerebral infarction admitted to Yulin Xingyuan Hos-pital from Jan.2022 to Jun.2024 were selected and divided into a control group and a study group using the ran-dom number table method(single blind),with 43 cases in each group.The control group was treated with intrave-nous drip of piperacillin/tazobactam,while the study group received additional inhalation of acetylcysteine solution based on the control group's treatment.The levels of inflammatory factors[C-reactive protein(CRP),interleukin-6(IL-6)and procalcitonin(PCT)],lung function indicators[forced vital capacity(FVC),peak expiratory flow rate(PEF),forced expiratory volume in one second(FEV1)and mean maximal expiratory flow rate(MMEF)],cardiac function indicators[left ventricular ejection fraction(LVEF),cardiac output(CO),cardiac index(CI)and stroke volume(SV)],NIH Stroke Scale(NIHSS)score,clinical efficacy,and the occurrence of adverse reactions were compared before and after treatment.RESULTS Compared with the control group,the study group had low levels of CRP,IL-6,PCT and NIHSS scores after treatment(P<0.05),and high levels of FVC,PEF,FEV1,MMEF,LVEF,CO,CI,and SV after treatment(P<0.05).The overall response rate in the study group was 95.35%,higher than 81.40%in the control group(χ2=4.074,P=0.044).There was no statistically significant difference in the incidence of adverse reactions between the control group and the study group during treatments(χ2=0.179,P=0.672).CONCLUSION Piperacillin/tazobactam combined with inhaled acetylcysteine solution for the treatment of severe pneumonia after cerebral infarction can improve clinical efficacy,reduce levels of inflamma-tory factors,and enhance cardiopulmonary and neurological functions in patients,which has a high safety profile.

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* ; Animals ; Acute Lung Injury/chemically induced* ; Mice ; Humans ; Ilex/chemistry* ; Molecular Docking Simulation ; Male ; NF-kappa B/immunology* ; Mice, Inbred C57BL ; NLR Family, Pyrin Domain-Containing 3 Protein/immunology* ; Tumor Necrosis Factor-alpha/genetics* ; Interleukin-1beta/genetics* ; RAW 264.7 Cells ; Disease Models, Animal

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 (PM_2.5), 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 PM_2.5, 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 PM_2.5 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 PM_2.5, respectively. Conclusion Exposure to PM_2.5 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.

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 PM_2.5 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 PM_2.5, 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.