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Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19
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General Severity of Illness Scoring Systems and COVID-19 Mortality Predictions: Is "Old Still Gold?"

Suhail S Siddiqui1, Rohit Patnaik2, Atul P Kulkarni3

  • 1Department of Critical Care Medicine, King George's Medical University, Lucknow, Uttar Pradesh, India.

Indian Journal of Critical Care Medicine : Peer-Reviewed, Official Publication of Indian Society of Critical Care Medicine
|June 3, 2022
PubMed

Insights

General Severity of Illness Scoring Systems can predict COVID-19 mortality. Older scoring systems remain valuable for assessing patient severity and outcomes in critical care settings.

Area of Science:

  • Critical Care Medicine
  • Epidemiology
  • Health Informatics

Background:

  • The COVID-19 pandemic necessitated rapid assessment of patient severity.
  • General Severity of Illness Scoring Systems (GSIS) are established tools in critical care.
  • The utility of traditional GSIS for predicting COVID-19 mortality requires evaluation.

Discussion:

  • This study examines the efficacy of established GSIS in predicting mortality among COVID-19 patients.
  • Comparison of different GSIS performance in diverse critical care populations.
  • Analysis of factors contributing to the predictive accuracy of older scoring systems.

Key Insights:

  • Traditional GSIS demonstrate significant predictive value for COVID-19 mortality.
  • The "old is still gold" adage holds relevance, as established scoring systems remain effective.
  • GSIS provide a crucial framework for resource allocation and clinical decision-making during pandemics.

Outlook:

  • Further research should explore refining existing GSIS or developing novel tools incorporating COVID-19 specific markers.
  • Integration of GSIS with real-time data analytics for enhanced predictive capabilities.
  • Validation of GSIS across different healthcare systems and patient demographics is essential.

Keywords:
COVID-19 mortalityCritically ill adultsPredictive model

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