ABSTRACT
OBJECTIVES: To devise a novel, simple chest x-ray (CXR) scoring system which would help in prognosticating the disease severity and ability to predict comorbidities and in-hospital mortality. METHODS: We included a total of 343 consecutive hospitalised patients with COVID-19 in this study. The chest x-rays of these patients were scored retrospectively by three radiologists independently. We divided CXR in to six zones (right upper, mid & lower and left, upper mid & lower zones). We scored each zone as- 0, 1 or 2 as follows- if that zone was clear (0) Ground glass opacity (1) or Consolidation (2). A total of score from 0 to 12 could be obtained. RESULTS: A CXR score cut off ≥3 independently predicted mortality. Along with a relatively higher NPV ≥80%, it reinforced the importance of CXR score is a screening tool to triage patients according to risk of mortality. CONCLUSIONS: We propose that Pennine score is a simple tool which can be adapted by various countries, experiencing a large surge in number of patients, to decide which patient would need a tertiary Hospital referral/admission as opposed to patients that can be managed locally or at basic/primary care hospitals.
Subject(s)
COVID-19/diagnostic imaging , Radiography, Thoracic , Adult , Age Factors , Aged , Aged, 80 and over , COVID-19/diagnosis , COVID-19/mortality , Comorbidity , Female , Hospital Mortality , Humans , Length of Stay , Male , Middle Aged , Predictive Value of Tests , Prognosis , Radiography, Thoracic/methods , Radiography, Thoracic/statistics & numerical data , Retrospective Studies , Risk Factors , Severity of Illness IndexABSTRACT
OBJECTIVES: The recovery rate is important to determine a country's development towards controlling coronavirus. It is a function of myriad factors - death rate, cases requiring hospitalization, quality of care, and discharge policies, among others. India's recovery rate is growing steadily from an earlier low of 10% to 11%. It is imperative to understand the determinants of recovery rate in a country to enable improvements in the same. MATERIAL AND METHODS: COVID-19 data have been compiled from several sources, including the Ministry of Health and Family Welfare, National Disaster Management Authority, and Indian Council of Medical Research and demographic and health data from Census of India, 2011, National Health Profile, 2019, and were used. The study uses linear regression to understand the relationship between recovery rate and development indicators in India. RESULTS: Our analysis emphasizes the beneficial impacts of the health system and better economy on the recovery rate. Investment in health, urban stay, non-slum and non-poor population, and effective governance is instrumental in improving recovery rate. CONCLUSION: Scaling up health facilities and medical infrastructure, slum decongestion, focus on economically weaker sections, capacity building of health workers and ameliorating long-term investments in health, health research, and better quality of living are also essential to address recovery of COVID-19.