Risk Factors of Readmission Within 90 Days for Chronic Obstructive Pulmonary Disease Patients with Frailty and Construction of an Early Warning Model.

Objective: This study aimed to explore the risk factors for readmission within 90 d in Chronic Obstructive Pulmonary Disease (COPD) patients with frailty and construct a clinical warning model. Methods: COPD patients with frailty hospitalized in the Department of Respiratory and Critical Care Medicine of Yixing Hospital, Affiliated to Jiangsu University, were retrospectively collected from January 1, 2020, to June 30, 2022. Patients were divided into readmission and control groups according to readmission within 90 d. The clinical data of the two groups were evaluated by univariate and multivariate logistic regression analyses to identify readmission risk factors within 90 d in COPD patients with frailty. Then, a risk quantitative early warning model was constructed. Finally, the model's prediction efficiency was evaluated, and external verification was carried out. Results: The multivariate logistic regression analysis showed that BMI, number of hospitalizations in the past year ≥ 2, CCI, REFS, and 4MGS were independent risk factors for readmission within 90 d in COPD patients with frailty. The early warning model for these patients was established as follows: Logit (p) = -1.896 + (-0.166 × BMI) + (0.969 × number of hospitalizations in the past year ≥ 2) + (0.265 × CCI) + (0.405 × REFS) + (-3.209 × 4MGS), and presented an area under the ROC curve (AUC) of 0.744 [95% CI: 0.687-0.801]. The AUC of the external validation cohort was 0.737 (95% CI: 0.648-0.826), and the AUC of the LACE warning model was 0.657 (95% CI:0.552-0.762). Conclusion: The BMI, number of hospitalizations in the past year ≥ 2, CCI, REFS, and 4MGS were independent risk factors for readmission within 90 d in COPD patients with frailty. The early warning model presented a moderate predictive value for assessing the risk of readmission within 90 d in these patients.

Associations of Clinical Characteristics and Intestinal Flora Imbalance in Stable Chronic Obstructive Pulmonary Disease (COPD) Patients and the Construction of an Early Warning Model.

OBJECTIVE: Establish a simple predictive model and scoring rule that is suitable for clinical medical staff in respiratory departments to assess intestinal flora imbalance occurrence in stable chronic obstructive pulmonary disease (COPD) patients. METHODS: From January 1, 2019, to December 31, 2020, COPD patients (195 cases) - who attended the Outpatient Department, Respiratory and Critical Care, Yixing Hospital, Jiangsu University - were enrolled in a cross-sectional study. Based on stool examination results, patients were divided into experimental (41 cases) and control (154 cases) groups. Single-factor and logistic regression analyses were performed with the baseline data of the two groups to obtain a new predictive model, which was further simplified. RESULTS: Five predictive factors composed the model: body mass index (BMI), serum albumin (ALB), Charlson's Comorbidity Index (CCI), gastrointestinal symptom score (GSRs), and Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification. The model to predict intestinal flora imbalance in stable COPD patients had an area under the ROC curve (AUC) of 0.953 [95% CI (0.924, 0.982)]. After simplifying the scoring rules, the AUC was 0.767 [95% CI (0.676, 0.858)]. CONCLUSION: In the current study, we obtained a model that could effectively predict intestinal flora imbalance risk in stable COPD patients, being suitable for implementation in early treatments to improve the prognosis. Moreover, all indicators can be easily and simply obtained.