Jinxiang Wang

Patients with chronic obstructive pulmonary disease (COPD) and coronary heart disease (CHD) frequently exhibit heightened systemic inflammation, oxidative stress, and cardiopulmonary dysfunction, contributing to an increased risk of recurrent exacerbations. The lactate dehydrogenase-to-albumin ratio (LAR) is a readily available biomarker reflecting inflammatory and metabolic stress; however, its association with the frequent-exacerbator phenotype in patients with COPD and CHD remains unclear. This study aimed to evaluate the relationship between admission LAR levels and frequent exacerbations in this high-risk population. This retrospective study analyzed 489 hospitalized patients with acute exacerbations of COPD (AECOPD) and comorbid CHD. Patients with two or more exacerbations were classified as frequent exacerbators. Demographic characteristics, comorbidities, and lab parameters were collected. Multivariable logistic regression and restricted cubic spline analyses were performed to evaluate the association between LAR and the frequent-exacerbator phenotype. A total of 489 patients with AECOPD and CHD were included, with a mean age of 76 years, and 66.9% were male. Higher admission LAR levels were significantly associated with the frequent-exacerbator phenotype in the unadjusted analysis (Odds Ratio [OR] 1.23; 95% confidence interval [CI] 1.12 ~ 1.35; p < 0.001). The association remained significant after adjustment for potential confounders (adjusted OR 1.34; 95% CI 1.19 ~ 1.51; p < 0.001). Restricted cubic spline analysis demonstrated a significant nonlinear association (p = 0.004), with an inflection point at a LAR value of approximately 5.1 (OR 4.04, p = 0.001), whereas a more modest increase was observed above this threshold (OR 1.45, p = 0.009). Higher admission LAR levels were independently associated with the frequent-exacerbator phenotype among patients with AECOPD and CHD. This readily available biomarker may improve risk stratification and personalized management in this high-morbidity population.

Background: Acute respiratory distress syndrome (ARDS) is a common clinical syndrome among critically ill patients and is associated with high mortality. Although scoring tools based on organ dysfunction currently exist, their ability to assess the immune status of patients remains limited. This study aimed to develop a predictive model for in-hospital mortality in non-immunosuppressed adults with pneumonia-associated ARDS by integrating clinical and host immune parameters. Methods: This single-center retrospective study included 126 adults with p-ARDS. Data collected within 48 h of admission were analyzed. Candidate predictors ( p < 0.10 in univariate analysis, excluding post-admission treatments) underwent simultaneous selection by BIC-based best subset selection and LASSO regression; variables identified by both methods were retained. A multivariable model combining selected predictors with the SOFA score (Model 2) was constructed, and a SOFA-only model served as the baseline (Model 1). Performance was evaluated for discrimination, calibration, and clinical utility. Bootstrap internal validation (500 iterations) was performed. Results: The overall in-hospital mortality rate was 35.7% (45/126). The final combined model incorporated the following variables: heart failure (aOR = 5.207), CD3 + CD4 + T-cell count (aOR = 0.719 per 100 cells/μL), D-dimer (aOR = 1.113 per 1 μg/mL) and SOFA score (aOR = 1.126 per point). The model demonstrated excellent predictive performance, with an AUC of 0.805 (95% CI: 0.730–0.879), which was significantly higher than that of the baseline model (AUC: 0.707; 95% CI: 0.618–0.797; p = 0.020). Calibration curves and decision curve analysis further confirmed its good calibration and superior clinical net benefit. Bootstrap internal validation demonstrated robustness (optimism-corrected C-statistic: 0.788). Conclusion: We developed a multidimensional model for predicting in-hospital mortality in non-immunosuppressed adult patients with p-ARDS. The model’s performance was superior to the SOFA score. External validation is needed for the widespread application of this model.

Background: Acute respiratory distress syndrome (ARDS) is a severe complication of pneumonia that significantly increases mortality. Its pathogenesis is associated with dysregulated host immune responses, which has been a topic of global research in lung injury. Methods: In this cross-sectional study, we enrolled adult patients with pneumonia from the Department of Infectious Diseases between May 2021 and June 2025. Participants were categorized into ARDS and non-ARDS groups based on the presence of ARDS at admission. We employed multivariable logistic regression and restricted cubic spline models to evaluate the association between lymphocyte subset levels and ARDS, adjusting for key clinical confounders. Results: Of the 227 eligible patients, 127 were diagnosed with ARDS. Patients with ARDS exhibited lower CD3 ⁺ CD4 ⁺ T-cell counts compared to non-ARDS controls. Furthermore, CD3 ⁺ CD4 ⁺ T-cell counts decreased progressively with increasing ARDS severity ( P for trend + CD4 ⁺ T-cell count was significantly associated with 33% lower odds of presenting with ARDS (adjusted OR 0.67, 95% CI 0.48–0.95), with evidence of a dose–response relationship. A nonlinear threshold effect was observed, with a significant inverse association noted above 227 cells/μL. This relationship remained consistent across all prespecified subgroups, with no evidence of effect modification. Conclusion: This study indicates an independent inverse association between CD3 ⁺ CD4 ⁺ T-cell counts and the presence of pneumonia-related ARDS. However, the cross-sectional design precludes any conclusions about its clinical applicability. Further research in prospective cohorts is warranted.

Objective: Acute exacerbations of chronic obstructive pulmonary disease (COPD) are a major cause of hospitalization and readmission, severely impacting patients’ quality of life and long-term prognosis. This study aimed to identify risk factors for both 30-day and frequent readmissions within one year following hospitalization for an acute exacerbation of COPD. Methods: We conducted a retrospective analysis of 1,208 patients hospitalized for acute COPD exacerbations. Patients were categorized based on readmission within 30 days or multiple readmissions in the subsequent year. Univariate and multivariate logistic regression analyses were employed to identify independent risk factors. A predictive nomogram model was developed and internally validated using bootstrapping techniques. Results: For 30-day readmissions, age was identified as an independent risk factor (OR=1.044, 95% CI: 1.008– 1.081). For frequent one-year readmissions, multivariate analysis revealed age (OR=1.025, 95% CI: 1.008– 1.042) and Anthonisen classification Type I/II (OR=1.556, 95% CI: 1.021– 2.369) as independent risk factors, while creatine kinase (CK) acted as a protective factor (OR=0.998, 95% CI: 0.996– 1.000). The nomogram demonstrated good predictive performance, with a C-index of 0.730 and an AUC of 0.730 upon internal validation. Conclusion: This study identifies age and Anthonisen classification as key risk factors, and CK as a protective factor for readmissions in COPD patients following acute exacerbation. The validated nomogram provides a practical clinical tool for predicting readmission risks, enabling early identification of high-risk patients during hospitalization or at discharge. This risk stratification approach can facilitate implementation of personalized management strategies, such as intensified follow-up or targeted interventions, to reduce readmission rates and improve patient outcomes.

Although pulmonary infections caused by Schizophyllum commune (S. commune) are still relatively rare in clinical practice, they are increasingly familiar and valued by clinicians. The clinical symptoms and imaging of pulmonary infection with S. commune are not typical, thus diagnosis needs to be confirmed by clinical etiology. S. commune is one of the main fungal species causing allergic bronchopulmonary mycosis. The overall prognosis of S. commune pulmonary infection is good. This paper describes a case of a woman with no underlying disease who had pulmonary infection with S. commune. This report aims to improve clinicians’ awareness of the disease.

Objective: Smoke inhalation lung injury (SILI) is a common complication in fires and wars, characterized by acute onset and severe condition. Pirfenidone (PFD), a new small‐molecule drug, has been shown to improve lung function and inhibit pulmonary fibrosis and inflammation. This study aimed to elucidate the effect and underlying mechanism of PFD on SILI in rats. Materials and Methods: SILI rats were constructed using a homemade smoking device, which was then treated with PFD. The blood was collected from the abdominal aorta, and the arterial blood gas was detected. The productions of oxidative stress markers and inflammatory cytokines in plasma were measured by enzyme linked immunosorbent assay assay. Moreover, the alveolar surface area, wet:dry weight ratio of the lung tissues, and bronchoalveolar lavage fluid (BALF) were determined as well. The pulmonary histopathology, cell apoptosis, and the related proteins of nuclear factor kappa B (NF‐κB) pathway were determined by hematoxylin‐eosin staining, TdT‐mediated dUTP‐biotin nick end labeling, and western blot assays, respectively. Results: PFD had a significant protective effect on SILI via inhibiting oxidative stress, inflammation, and apoptosis. Mechanistically, PFD inhibited the activation of NF‐κB pathway in vivo. Moreover, activation of NF‐κB pathway attenuated the PFD‐mediated protective effect against SILI. Conclusions: These data demonstrate that PFD alleviates SILI of rats via the NF‐κB signaling pathway, which provides an attractive therapeutic option for SILI treatment.

This study aimed to develop nomograms to predict high hospitalization costs and prolonged stays in hospitalized acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients with community‐acquired pneumonia (CAP), also known as pAECOPD. A total of 635 patients with pAECOPD were included in this observational study and divided into training and testing sets. Variables were initially screened using univariate analysis, and then further selected using a backward stepwise regression. Multivariable logistic regression was performed to establish nomograms. The predictive performance of the model was evaluated using the receiver operating characteristic (ROC) curve, area under the curve (AUC), calibration curve, and decision curve analysis (DCA) in both the training and testing sets. Finally, the logistic regression analysis showed that elevated white blood cell count (WBC>10 × 10⁹ cells/l), hypoalbuminemia, pulmonary encephalopathy, respiratory failure, diabetes, and respiratory intensive care unit (RICU) admissions were risk factors for predicting high hospitalization costs in pAECOPD patients. The AUC value was 0.756 (95% CI: 0.699–0.812) in the training set and 0.792 (95% CI: 0.718–0.867) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. Furthermore, decreased total protein, pulmonary encephalopathy, reflux esophagitis, and RICU admissions were risk factors for predicting prolonged stays in pAECOPD patients. The AUC value was 0.629 (95% CI: 0.575–0.682) in the training set and 0.620 (95% CI: 0.539–0.701) in the testing set. The calibration plot and DCA curve indicated the model had good predictive performance. We developed and validated two nomograms for predicting high hospitalization costs and prolonged stay, respectively, among hospitalized patients with pAECOPD. This trial is registered with ChiCTR2000039959.

Introduction. The impaired proliferative capacity of alveolar epithelial cells after injury is an important factor causing epithelial repair dysfunction, leading to the occurrence of idiopathic pulmonary fibrosis (IPF). Alveolar type 2 (AT2) cells as the stem cells of alveolar epithelium participate in the repair process after alveolar injury. Lipocalin‐2 (LCN2) participates in multiple processes regulating the pathological process of alveolar epithelial cells, but the mechanisms involved are still unclear. Method. We used a BLM‐treated mouse model to characterize the expression of LCN2 in lung fibrosis regions and analyzed the location of LCN2 in alveolar epithelial cells. Moreover, human pulmonary alveolar epithelial cells (HPAEpiCs) were transfected with the LCN2 overexpression plasmid vector in vitro. Recombinant human interleukin‐17 (IL‐17) protein (rhIL‐17) at different concentrations was administered to intervene in HPAEpiCs, observing cell viability and analyzing the concentration‐dependent effect of IL‐17. Results. LCN2 was increased in the alveolar epithelium post‐BLM injury, and highly expressed LCN2 was mainly concentrated on AT2 cells in BLM‐injured lungs. Meanwhile, LCN2‐overexpressing HPAEpiCs showed impaired cell viability and cell growth. HPAEpiC intervention with rhIL‐17 mildly rescued the impaired cell proliferation induced by LCN2 overexpression, and the effect of IL‐17 intervention was partially concentration‐dependent. Conclusions. The results revealed the reversed effect of IL‐17 on the impaired proliferative capacity of the alveolar epithelium induced by LCN2 overexpression. The target alveolar epithelial cells regulated by this process were AT2 cells, providing new clues for alveolar epithelium repair after injury and the treatment of lung injury diseases.