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Abstract

In the early, chaotic hours of hospital admission during the COVID-19 pandemic, clinical clarity was often obscured by urgency. The National Early Warning Score (NEWS) functioned as a fast assessment tool that used physiological parameters to sort patients into different risk categories. The research evaluates how NEWS predicts patient outcomes, resource needs, and disease severity among COVID-19 patients admitted to hospitals in Kyrgyzstan, which operates as an LMIC under significant healthcare system pressure. The tool gained worldwide recognition, yet there was insufficient research about its effectiveness for Central Asian patients during the pandemic. The research team analyzed 395 confirmed COVID-19 patient records through retrospective observation to create three risk groups based on their NEWS scores at admission (≤4, 5–6, ≥7). The research showed that higher NEWS scores correlated strongly with increased mortality rates (p < 0.0001) as well as higher rates of ICU admissions and mechanical ventilation requirements and shorter hospital stays because patients deteriorated quickly. The mortality rate reached 70.4% among patients who received NEWS scores of 7 or higher, while the low-risk group experienced only 4.05% deaths. The study confirmed that the scale effectively tracked patient clinical changes during 20 days, which supported its purpose for early intervention and triage. The tool shows potential to enhance patient results in LMICs through its ability to direct prompt medical choices and distribute limited medical resources effectively during current and future public health crises‎.

Keywords: COVID-19, National Early Warning Score (NEWS), Risk stratification, Hospital outcomes, Low- and Middle-Income Countries (LMICs)

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