Predictors of Length of Stay, Mortality and Rehospitalization in COPD Patients: A Retrospective Cohort Study

A Pilot Study on Proteomic Predictors of Mortality in Stable COPD

Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of global mortality. Despite clinical predictors (age, severity, comorbidities, etc.) being established, proteomics offers comprehensive biological profiling to obtain deeper insights into COPD pathophysiology and survival prognoses. This pilot study aimed to identify proteomic footprints that could be potentially useful in predicting mortality in stable COPD patients. Plasma samples from 40 patients were subjected to both blind (liquid chromatography-mass spectrometry) and hypothesis-driven (multiplex immunoassays) proteomic analyses supported by artificial intelligence (AI) before a 4-year clinical follow-up. Among the 34 patients whose survival status was confirmed (mean age 69 ± 9 years, 29.5% women, FEV1 42 ± 15.3% ref.), 32% were dead in the fourth year. The analysis identified 363 proteins/peptides, with 31 showing significant differences between the survivors and non-survivors. These proteins predominantly belonged to different aspects of the immune response (12 proteins), hemostasis (9), and proinflammatory cytokines (5). The predictive modeling achieved excellent accuracy for mortality (90%) but a weaker performance for days of survival (Q2 0.18), improving mildly with AI-mediated blind selection of proteins (accuracy of 95%, Q2 of 0.52). Further stratification by protein groups highlighted the predictive value for mortality of either hemostasis or pro-inflammatory markers alone (accuracies of 95 and 89%, respectively). Therefore, stable COPD patients' proteomic footprints can effectively forecast 4-year mortality, emphasizing the role of inflammatory, immune, and cardiovascular events. Future applications may enhance the prognostic precision and guide preventive interventions.

The Management of Acute Exacerbations in COPD: A Retrospective Observational Study and Clinical Audit

(1) Background: Acute exacerbations of chronic obstructive pulmonary disease (COPD) are not only associated with increased patient morbidity and mortality, but with extensive healthcare costs. Thus, adequate clinical management is crucial. The aim of this project was to evaluate the management of acute COPD exacerbations in a public teaching hospital in Switzerland. (2) Methods: We retrospectively analyzed clinical routine data of patients presenting with an acute exacerbation of COPD at the emergency department of a Swiss hospital between January 2019 and February 2020. Management was evaluated against recommendations from the GOLD 2019 report and previous audits. (3) Results: The data of 184 patients (mean age 73.5 years, range 41-95 years, 53% male) with 226 visits were included. While the documentation of GOLD stage (I-IV) and smoking status was consistent (81.0% and 91.6%), GOLD risk category (A-D) was only documented in 36% of the cases. Patients' respiratory rate upon presentation was measured in 73%, and blood gas analysis was performed in 70%. A total of 94% of the patients received a chest imaging; spirometry was performed in 10%. Initial symptomatic therapy with short acting bronchodilators was applied in 56%. Systemic steroid treatment was installed in 86%. Antibiotics were given in 56%, but in one fourth the indication was not clear. Non-invasive ventilation was applied in 25% of the indicated cases. Smoking cessation was recommended to 26% of the current smokers and referral to pulmonary rehabilitation was given in 16%. (4) Conclusion: GOLD recommendations were not comprehensively implemented, especially with regard to the assessment of severity, initial symptomatic therapy, and non-invasive ventilation. These results show the importance of the frequent revision of routine practice and may help to create awareness among practitioners and ultimately improve the quality of COPD management.

The rate of ward to intensive care transfer and its predictors among hospitalized COPD patients, a retrospective study in a local tertiary center in Saudi Arabia

OBJECTIVE

To investigate the prevalence of intensive care unit (ICU) admission and its predictors among hospitalized chronic obstructive pulmonary disease (COPD) patients.

METHODS

An observational retrospective study was conducted. All patients with a confirmed diagnosis of COPD according to the GOLD guidelines between 28 and 2020 and 1 March 2023 at Al-Noor Specialist Hospital were included in this study. Patients were excluded if a preemptive diagnosis of COPD was made clinically without spirometry evidence of fixed airflow limitation. Descriptive results were presented as frequency (percentage) for categorical variables and mean (SD) for continuous variables and to estimate prevalence of ICU admission. Predictors of ICU admission among hospitalized COPD patients were determined using logistic regression analysis. A SPSS (Statistical Package for the Social Sciences) version 25 was used to perform all statistical analysis.

RESULTS

A total of 705 patients with COPD were included in this study. The mean age was 65.4 (25.3) years. Around 12.4% of the hospitalized patients were admitted to the ICD. Logistic regression analysis identified that older age (OR; 1.92, (1.41-2.62)), smoking (OR; 1.60 (1.17-2.19)), and having specific comorbidities (Hypertension (OR; 1.98 (1.45-2.71)), Diabetes mellitus (OR; 1.42 (1.04-1.93)), GERD (OR; 2.81 (1.99-3.96)), Ischemic heart disease (OR; 3.22 (2.19-4.75)), Obstructive sleep apnea syndrome (OR; 2.14 (1.38-3.33)), stroke (OR; 4.51 (2.20-9.26))) were predictors of ICU admissions among patients with COPD.

CONCLUSIONS

Our study found that a step-up approach to inpatient COPD management requires admission to the ICU in 12.4%, for which age, smoking status, cardiovascular, and stroke were important predictors. Further clinical research is needed to provide a validated model that can be incorporated into clinical practice to monitor this patient population during their admission and identify at-risk individuals for early transfer to higher acuity settings and intensive care units.