What Are the Most Effective Factors in Determining Future Exacerbations, Morbidity Weight, and Mortality in Patients with COPD Attack?

Machine learning approaches for practical predicting outpatient near-future AECOPD based on nationwide electronic medical records

In this research, we aimed to harness machine learning to predict the imminent risk of acute exacerbation in chronic obstructive pulmonary disease (AECOPD) patients. Utilizing retrospective data from electronic medical records of two Taiwanese hospitals, we identified 26 critical features. To predict 3- and 6-month AECOPD occurrences, we deployed five distinct machine learning algorithms alongside ensemble learning. The 3-month risk prediction was best realized by the XGBoost model, achieving an AUC of 0.795, whereas the XGBoost was superior for the 6-month prediction with an AUC of 0.813. We conducted an explainability analysis and found that the episode of AECOPD, mMRC score, CAT score, respiratory rate, and the use of inhaled corticosteroids were the most impactful features. Notably, our approach surpassed predictions that relied solely on CAT or mMRC scores. Accordingly, we designed an interactive prediction system that provides physicians with a practical tool to predict near-term AECOPD risk in outpatients.

Platelet count and platelet-to-lymphocyte ratio at the onset of a severe COPD exacerbation are unrelated to the time till the next moderate or severe relapse

PURPOSE

Acute exacerbations (AE) are severe complications of chronic obstructive pulmonary disease (COPD); however, the need for biomarkers which predict them is still unmet. High platelet count (PLC) and platelet-to-lymphocyte ratio (PLR) are associated with higher mortality in patients with COPD. We investigated if PLC and PLR at the onset of a severe AE could predict the time of the next relapse.

METHODS

In a prospective observational cohort study, data of 152 patients hospitalized with AECOPD were collected, and patients were divided into PLC-low (<239 ​× ​109/L, n ​= ​51), PLC-medium (239-297 ​× ​109/L, n ​= ​51) and PLC-high (>297 ​× ​109/L, n ​= ​50) or PLR-low (<147, N ​= ​51), PLR-medium (147-295, n ​= ​51) and PLR high (>295, n ​= ​50) groups based on PLC and PLR tertiles using admission laboratory results. Clinical characteristics and the time to the next severe or moderate AE within 52 weeks were compared among subgroups using log-rank test.

RESULTS

PLC and PLR tertiles did not differ in clinical characteristics or the time till the next AE (p ​> ​0.05). PLC and PLR showed a direct weak correlation to neutrophil count (Pearson r ​= ​0.26, p ​< ​0.01 and r ​= ​0.20, p ​= ​0.01) and PLC also demonstrated a weak relationship to white blood cell counts (Pearson r ​= ​0.29, p ​< ​0.001). However, PLR presented an inverse relationship to monocyte and eosinophil counts (r ​= ​-0.32, p ​< ​0.001 and r ​= ​-0.17, p ​= ​0.03).

CONCLUSION

PLC and PLR do not predict the time till the next relapse; however, they may reflect on neutrophilic inflammatory response during an exacerbation of COPD.

Prognostic Value of Serum Cholinesterase Levels for In-Hospital Mortality among Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease

Cholinesterase (ChE) is associated with the pathogenesis of chronic obstructive pulmonary disease (COPD), including chronic airway inflammation and oxidation/antioxidant imbalance. However, the relationship between serum ChE levels and survival outcomes of patients hospitalized with acute exacerbations of COPD (AECOPD) is unknown. In this retrospective single-center study, we investigated the ability of the serum ChE level to predict in-hospital death in patients hospitalized with AECOPD. The clinicopathological data, including serum ChE levels as well as clinical and biochemical indicators were extracted for 477 patients from the hospital records and analyzed. Our results demonstrated that AECOPD patients with lower serum ChE levels were associated with increased mortality, frequent hospitalization due to acute exacerbations (AE) in the past year, and longer hospital stay. The optimal cutoff value for the serum ChE level was 4323 U/L. The area under the ROC curve (AUC) values for predicting in-hospital mortality based on the serum ChE level was 0.79 (95% confidence interval (CI), 0.72-0.85). Multivariate logistic regression analysis demonstrated that serum ChE level ≤ 4323 U/L (odds ratio (OR) 9.09, 95% CI 3.43-28.3, p < 0.001), age-adjusted Charlson comorbidity index (aCCI), and the number of hospitalizations due to AE in the past year were independent risk factors for predicting the in-hospital mortality of AECOPD patients. In conclusion, our study demonstrated that low serum ChE levels were associated with significantly higher in-hospital mortality rates of patients hospitalized with AECOPD. Therefore, serum ChE level is a promising prognostic predictor of hospitalized AECOPD patients.

Evaluation of the Effect of COVID-19 Vaccination on Exacerbations of Chronic Obstructive Pulmonary Disease: A Single-Center Study

BACKGROUND AND AIM

 Vaccinations have been one of the main approaches to reducing mortality and exacerbations caused by infectious agents in chronic obstructive pulmonary disease (COPD). Among viral pathogens, coronaviruses have been described to play a role. This study aims to investigate the role of coronavirus disease 2019 (COVID-19) vaccination on exacerbation reduction in patients with COPD.

METHODS

Patients diagnosed with COPD prior to the study date were considered the study population. Exacerbations of COPD before and after the COVID-19 vaccination were recorded. Patients with influenza and/or pneumococcal vaccination were excluded from the study due to their known role in reducing exacerbations of COPD.

RESULTS

The study included 152 patients with a mean age of 67.5 ± 9.7 years. Most patients were classified under Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2 and 3. In fully vaccinated patients, COPD exacerbation was observed to be higher than in those without full vaccination (70.5% vs. 55.3%, respectively). Total risk status and vaccination status, however, were seen to be in a positive correlation, with higher risk and complete vaccination status presenting with a higher count of COPD exacerbation.

CONCLUSION

Although it is known that the administration of COVID-19 vaccines in patients in risk groups reduces the risk of disease, there is no study showing a positive effect on COPD exacerbations alone. In our study, it was observed that only the COVID-19 vaccine was ineffective in attacks without influenza and pneumococcal vaccines.

Using inflammatory index to distinguish asthma, asthma-COPD overlap and COPD: A retrospective observational study

BACKGROUND

Although asthma and chronic obstructive pulmonary disease (COPD) are two well-defined and distinct diseases, some patients present combined clinical features of both asthma and COPD, particularly in smokers and the elderly, a condition termed as asthma-COPD overlap (ACO). However, the definition of ACO is yet to be established and clinical guidelines to identify and manage ACO remain controversial. Therefore, in this study, inflammatory biomarkers were established to distinguish asthma, ACO, and COPD, and their relationship with the severity of patients' symptoms and pulmonary function were explored.

MATERIALS AND METHODS

A total of 178 patients, diagnosed with asthma (n = 38), ACO (n = 44), and COPD (n = 96) between January 2021 to June 2022, were enrolled in this study. The patients' pulmonary function was examined and routine blood samples were taken for the analysis of inflammatory indexes. Logistic regression analysis was used to establish inflammatory biomarkers for distinguishing asthma, ACO, and COPD; linear regression analysis was used to analyze the relationship between inflammatory indexes and symptom severity and pulmonary function.

RESULT

The results showed that, compared with ACO, the higher the indexes of platelet, neutrophil-lymphocyte ratio (NLR) and eosinophil-basophil ratio (EBR), the more likely the possibility of asthma and COPD in patients, while the higher the eosinophils, the less likely the possibility of asthma and COPD. Hemoglobin and lymphocyte-monocyte ratio (LMR) were negatively correlated with the severity of patients' symptoms, while platelet-lymphocyte ratio (PLR) was negatively correlated with forced expiratory volume in the 1 s/forced vital capacity (FEV1/FVC) and FEV1 percent predicted (% pred), and EBR was positively correlated with FEV1% pred.

CONCLUSION

Inflammatory indexes are biomarkers for distinguishing asthma, ACO, and COPD, which are of clinical significance in therapeutic strategies and prognosis evaluation.

The Emerging Clinical Significance of the Red Cell Distribution Width as a Biomarker in Chronic Obstructive Pulmonary Disease: A Systematic Review

There is an intense focus on the identification of novel biomarkers of chronic obstructive pulmonary disease (COPD) to enhance clinical decisions in patients with stable disease and acute exacerbations (AECOPD). Though several local (airway) and circulatory inflammatory biomarkers have been proposed, emerging evidence also suggests a potential role for routine haematological parameters, e.g., the red cell distribution width (RDW). We conducted a systematic literature search in PubMed, Web of Science, and Scopus, from inception to April 2022, for articles investigating the diagnostic and prognostic role of the RDW in stable COPD and AECOPD. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist. Significant associations between the RDW and the presence and severity of disease, outcomes (mortality, hospital readmission), and other relevant clinical parameters (right heart failure, pulmonary arterial hypertension) were reported in 13 out of 16 studies in stable COPD (low risk of bias in 11 studies), and 17 out of 21 studies of AECOPD (low risk of bias in 11 studies). Pending further research, our systematic review suggests that the RDW might be useful, singly or in combination with other parameters, for the diagnosis and risk stratification of patients with stable COPD and AECOPD (PROSPERO registration number: CRD42022348304).