Background: COVID -19 has been infecting large number of people worldwide. The need for proper isolation and along with a health-care facility that has been modified to handle these patients has been high demand throughout the year. The cost for additional infrastructure to support these patients and treat them has been dear which has aggravated the economic burden on the sick. Predicting the need for oxygen requirement can help in providing home quarantine to those who wouldn’t need oxygen support, thus freeing up hospital resources for patients who really need the critical care. Hence a proper means of identifying these patients could serve an important role in decision making.
Objective: To validate a pre-existing clinical score (COVID-GRAM score) to predict the need for oxygen requirement or to predict those who are at risk of desaturation.
Patients and Methods: All patient data was obtained without disclosure of personal identifying information from hospital records. The COVID GRAM Score was calculated in these patients as per admission day clinical and laboratory parameters. The collected data were analysed with IBM.SPSS statistics software 23.0 Version.
Results: The study included 234 patients. A cut-off score of 72.3 showed an AUC of 0.965 with a sensitivity of 90% and specificity of 89.6%, (95% CI, 0.94-0.98)
Conclusion: From this study, we found that patients will a GRAM SCORE of more than 72 were very most-likely to need oxygen requirement and it can be used as a cut-off to predict risk of desaturation.
Impact Factor
2022: 6.012
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