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Forecasting mortality rates in hyponatremia: a statistical approach using Holt-Winters models
Rawiyah Muneer Alraddadi1, Mohamed Abd Allah El-Hadidy2, Qin Shao3
1Department of Mathematics and Statistics, College of Science in Yanbu, Taibah University, Madinah, Saudi Arabia.
Abstract:
Hyponatremia, characterized by a serum sodium concentration below 135 mEq/L, is a prevalent electrolyte imbalance associated with increased morbidity and mortality across various clinical conditions. This study employs the Holt-Winters seasonal method, a robust time series forecasting model, to predict mortality rates attributed to hyponatremia. Leveraging retrospective mortality data from a cohort of hospitals in the United States, our analysis aims to elucidate temporal patterns and trends in hyponatremia-related deaths. The findings underscore the critical role of statistical forecasting in healthcare, facilitating proactive resource allocation and targeted interventions to mitigate mortality risks associated with electrolyte imbalances. Integrating predictive analytics into clinical practice holds promise for enhancing patient care and optimizing health outcomes in populations vulnerable to hyponatremia-related complications.
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