COPD: Will There Be Room for Nebulisers After the Current COVID-19 Pandemic?

Risk factors of mortality in hospitalized patients with COVID-19 applying a Machine Learning algorithm

Introduction

Risk stratification of patients with COVID-19 can be fundamental to support clinical decision-making and optimize resources. The objective of our study is to identify among the routinely tested clinical and analytical parameters those that would allow us to determine patients with the highest risk of dying from COVID-19.

Material and methods

We carried out a retrospective cohort multicentric study by consecutively, including hospitalized patients with COVID-19 admitted in any of the 11 hospitals in the healthcare network of HM Hospitals-Spain. We collected the clinical, demographic, analytical, and radiological data from the patient's medical records.

To assess each of the biomarkers’ predictive impact and measure the statistical significance of the variables involved in the analysis, we applied a random forest with a permutation method. We used the similarity measure induced by a previously classification model and adjusted the k-groups clustering algorithm based on the energy distance to stratify patients into a high and low-risk group. Finally, we adjusted two optimal classification trees to have a schematic representation of the cut-off points.

Results

We included 1246 patients (average age of 65.36 years, 62% males). During the study one hundred sixty-eight patients (13%) died. High values of age, D-Dimer, White Blood Cell, Na, CRP, and creatinine represent the factors that identify high-risk patients who would die.

Conclusions

Age seems to be the primary predictor of mortality in patients with SARS-CoV-2 infection, while the impact of acute phase reactants and blood cellularity is also highly relevant.

Matching the Inhaler to the Patient in COPD

Selecting the most appropriate inhalation device from the wide range available is essential for the successful management of patients with chronic obstructive pulmonary disease. Although choice is good for healthcare professionals, knowing which inhaler to prescribe is a complex consideration. Among the key factors to consider are quality of disease control, inhaler technique, inhaler resistance and inspiratory flow, inhaler design and mechanisms of drug delivery, insurance and reimbursement restrictions, and environmental impact. In this article, we offer a simple, practical tool that brings together all these factors and includes hyperlinks to other published resources from the United Kingdom, Belgium, and The Netherlands.