Lung tissue repair mechanisms and risk models for chronic obstructive pulmonary disease: an analysis based on computer simulation and experimental validation

Abstract

BACKGROUND: Understanding the characteristics of lung tissue repair and risk factors in patients with chronic obstructive pulmonary disease (COPD) is crucial for improving disease management and enhancing patient quality of life. Existing clinical indicators cannot accurately quantify the tissue repair potential and disease progression risk in patients with a history of frequent hospitalizations. OBJECTIVE: To conduct a risk prediction model analysis of lung tissue repair mechanisms in COPD based on computer simulation and case validation, thereby promoting lung tissue repair/regeneration in COPD patients, reducing the frequency of hospitalizations, and improving quality of life. METHODS: Medical records from 200 patients with COPD hospitalized at Beijing Jingmei Group General Hospital from 2022-10-01 to 2023-10-01 were collected. Patients were grouped based on the number of hospitalizations for COPD within 1 year after discharge: 100 patients with ≥2 hospitalizations were assigned to the frequent hospitalization group, and 100 patients with <2 hospitalizations were assigned to the non-frequent hospitalization group. General clinical data, pulmonary function, blood gas analysis, and hematological indicators were compared between the two groups. Variables with P < 0.05 were included in a multivariate logistic regression model to identify risk factors for rehospitalization within 1 year. The area under the receiver operating characteristic curve (AUC) was used to evaluate the predictive efficacy of the clinical risk factor model. RESULTS AND CONCLUSION: (1) Pulmonary function: There were significant differences between the two groups in FEV1% predicted, FVC, FVC% predicted, FEV1/FVC, residual volume/total lung capacity ratio, diffusing capacity of the lung for carbon monoxide (DLCO), and DLCO/alveolar volume (P < 0.05). (2) Blood gas analysis: Significant differences were found in oxygen partial pressure, carbon dioxide partial pressure, oxygen saturation, and respiratory failure type (P < 0.05). (3) Hematological indicators: Significant differences were observed in absolute neutrophil count, D-dimer, absolute lymphocyte count, neutrophil percentage, and red blood cell distribution width (RDW) (P < 0.05), while no significant differences were found in eosinophil percentage, fibrinogen, and absolute eosinophil count (P > 0.05). (4) Logistic regression analysis showed that FEV1% predicted (OR=1.01, 95%CI: 1.004-1.017, P=0.011), DLCO (OR=2.28, 95%CI: 1.270-3.025, P=0.004), type I respiratory failure (OR=3.15, 95%CI: 2.414-5.947, P=0.001), type II respiratory failure (OR=7.03, 95%CI: 1.688-8.604, P=0.001), and RDW (OR=1.50, 95%CI: 0.65-3.44, P < 0.0001) were risk factors for frequent hospitalizations in COPD patients. (5) ROC curve analysis showed that when FEV1% predicted was below 52.9%, DLCO below 4 mmol/(min·kPa), presence of type I respiratory failure, or RDW above 14.5%, the risk of frequent hospitalizations increased. (6) The logistic regression model and ROC curve analysis indicated that severely impaired diffusion capacity, combined respiratory failure, and elevated RDW are major risk factors for frequent hospitalizations in COPD patients. Early identification and intervention of these factors are important for improving lung tissue repair potential, predicting disease progression risk, and enhancing quality of life.

1. Introduction

Chronic obstructive pulmonary disease (COPD) severely affects patients' quality of life [1-2]. Its core pathological features are irreversible airflow limitation and progressive destruction of lung tissue, especially alveoli and airways. Traditional treatment mainly focuses on relieving symptoms, while promoting lung tissue repair/regeneration and reversing disease progression remain fundamental therapeutic challenges. Some studies have shown that even patients with relatively good pulmonary function may experience frequent hospitalizations, while others with severely impaired lung function may not have a history of frequent hospitalizations [3], suggesting that relying solely on pulmonary function tests to assess the severity of COPD may be incomplete.

The number of frequent hospitalizations in the past year is a risk factor for predicting future frequent hospitalization frequency in COPD patients [4]. For patients with frequent hospitalizations, closer monitoring and management are needed to reduce the risk of future hospitalizations. Long-term follow-up studies have shown that frequent hospitalizations in the first year are closely related to those in subsequent years [5], further emphasizing the importance of early diagnosis and treatment of COPD [6]. For those who have experienced two or more frequent hospitalizations in the past year, avoiding precipitating factors is crucial [7], which may include adjusting medication, enhancing pulmonary rehabilitation programs, vaccination, and other preventive measures [8-9].

Currently, most studies focus on differences between acute exacerbation and stable phases of COPD, while research on the mechanisms of lung tissue repair and risk prediction models for frequent hospitalizations is limited. This study aims to analyze the lung tissue repair mechanisms and risk factors in COPD patients using computer simulation and case validation, providing evidence for early intervention and improved management.