View Score: An early warning score to detect possible complications among COVID-19 patients

Autor: Meenakshi Bhakare, Rajkumar Nikalje, Reshma Patil, Urvi Shukla, Rupesh Bokade, Gajanan Sakhare, Shardul Joshi, Aditi Pais
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Journal of Family Medicine and Primary Care, Vol 12, Iss 12, Pp 3160-3166 (2023)
Druh dokumentu: article
ISSN: 2249-4863
2278-7135
DOI: 10.4103/jfmpc.jfmpc_221_23
Popis: Introduction: Understanding pulmonary function at various phases after coronavirus disease 2019 (COVID-19) infection is critical for determining the exact pathophysiological mechanism of COVID-19. Research Question: What is the correlation between spirometry indices and clinical indicators in COVID-19 patients over a 6-week follow-up? Objectives: 1) To assess deterioration or improvement in spirometry parameters including forced vital capacity (FVC), forced expiratory volume in one second (FEV1), and ratio FEV1/FVC in COVID-19 patients. 2) To study the correlation between FVC, FEV1, and FEV1/FVC with oxygen saturation and clinical findings. Materials and Methods: A prospective observational study was conducted for a 6-week period among 25, COVID-19 patients who were either asymptomatic or mildly symptomatic. Each patient received a home-use-connected spirometer—SpiroPRO®, a pulse oximeter, and a thermometer from Briota Technologies Pvt Ltd. (BRIOTA). Patients and healthcare professionals were given training for performing spirometry twice a day as well as access to mobile apps was provided. Spirometry indices, patient symptoms, and vital statistics were used to calculate the VIEW™ score using machine learning algorithms. Result: The Bland–Altman plots showed that FEV1 reduced slightly up to 21–28 days and comes back to normal around 42 days. VIEW™ score increased up to day 21 and then decreased toward day 42. An increase in VIEW™ score increases the risk of COVID-19 complications. VIEW™ score and FEV1 showed a significant correlation. Conclusion: Home-based spirometry acts as an effective tool for COVID-19 patients to predict lung complications and also promote self-monitoring thereby reducing the burden on the health system.
Databáze: Directory of Open Access Journals
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