Feasibility of mean platelet volume as a biomarker for chronic obstructive pulmonary disease: A systematic review and meta-analysis

A predictive model for frequent exacerbator phenotype of acute exacerbations of chronic obstructive pulmonary disease

Background

The frequent exacerbator phenotype of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is characterized by experiencing at least two exacerbations per year, leading to a significant economic burden on healthcare systems worldwide. Although several biomarkers have been shown to be effective in assessing AECOPD severity in recent years, there is a lack of studies on markers to predict the frequent exacerbator phenotype of AECOPD. The current study aimed to develop a new predictive model for the frequent exacerbator phenotype of AECOPD based on rapid, inexpensive, and easily obtained routine markers.

Methods

This was a single-center, retrospective study that enrolled a total of 2,236 AECOPD patients. The participants were divided into two groups based on the frequency of exacerbations: infrequent group (n=1,827) and frequent group (n=409). They underwent a complete blood count, as well as blood biochemistry, blood lipid and coagulation testing, and general characteristics were also recorded. Univariate analysis and binary multivariate logistic regression analyses were used to explore independent risk factors for the frequent exacerbator phenotype of AECOPD, which could be used as components of a new predictive model. The receiver operator characteristic (ROC) curve was used to assess the predictive value of the new model, which consisted of all significant risk factors predicting the primary outcome. The nomogram risk prediction model was established using R software.

Results

Age, gender, length of stay (LOS), neutrophils, monocytes, eosinophils, direct bilirubin (DBil), gamma-glutamyl transferase (GGT), and the glucose-to-lymphocyte ratio (GLR) were independent risk factors for the frequent exacerbator phenotype of AECOPD. The area under the curve (AUC) of the new predictive model was 0.681 [95% confidence interval (CI): 0.653-0.708], and the sensitivity was 63.6% (95% CI: 58.9-68.2%) and the specificity was 65.0% (95% CI: 60.3-69.6%).

Conclusions

A new predictive model based on demographic characteristics and blood parameters can be used to predict the frequency of acute exacerbations in the management of chronic obstructive pulmonary disease (COPD).

Platelet Count and Platelet Indices in Patients with Stable and Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Systematic Review and Meta-Analysis

Platelets play an important role in the pathophysiology of chronic obstructive pulmonary disease (COPD) by mediating thrombotic, inflammatory, and immune processes in the lung. We conducted a systematic review and meta-analysis of studies investigating the platelet count and three platelet indices, mean platelet volume (MPV), platelet distribution width (PDW), and platelet to lymphocyte ratio (PLR) in stable COPD vs. non-COPD patients and in stable COPD vs. acute exacerbation of COPD (AECOPD) patients (PROSPERO registration number: CRD42021228263). PubMed, Web of Science, Scopus and Google Scholar were searched from inception to December 2020. Twenty-seven studies were included in the meta-analysis, 26 comparing 4,455 stable COPD patients with 7,128 non-COPD controls and 14 comparing 1,251 stable COPD with 904 AECOPD patients. Stable COPD patients had significantly higher platelet counts (weighted mean difference, WMD = 13.39 x10⁹/L, 95% CI 4.68 to 22.11 x10⁹/L; p < 0.001) and PLR (WMD = 59.52, 95% CI 29.59 to 89.44; p < 0.001) than non-COPD subjects. AECOPD patients had significantly higher PLR values than stable COPD patients (WMD = 46.03, 95% CI 7.70 to 84.35; p = 0.02). No significant differences were observed in MPV and PDW. Between-study heterogeneity was extreme. In sensitivity analysis, the effect size was not modified when each study was sequentially removed. The was no evidence of publication bias. In our meta-analysis, specific platelet biomarkers were associated with stable COPD (platelet count and PLR) and AECOPD (PLR). However, the observed heterogeneity limits the generalizability of the findings. Further studies are required to determine their prognostic utility and the effects of targeted interventions in COPD.