Evaluate how daily collective physiological parameter monitoring affects medically admitted patient outcomes

Aim: This study aimed to analyze the prognostic significance of vital signs in patients, focusing on trending patterns rather than actual assessments. It assessed the relationship between monitored vital signs and adverse outcomes. Methods: This study examines the prognostic performance of three trending vital signs in patients admitted to the ICU between January 2023 and May 2024. The three primary vital signs were mean arterial blood pressure (MAP), heart rate (HR), and core body temperature (Temp). The study used the Binary Logistic Regression test and sensitivity analyses to determine the best sensitivity and specificity for the predictors. The sensitivity indices included true positive rate (TPR), true negative rate (TNR), positive predictive value (PPV), negative predictive value (NPV), and accuracy indices (AI). The study used SPSS Statistics Version 25 for analysis, with a P-value below 0.05 considered statistically significant. The study adhered to the principles of the Helsinki Declaration and adhered to the principles of the Helsinki Declaration. Results: The study used Binary Logistic Regression models to analyze patients' vital signs and overall critical illness mortality. The models identified variations in dependent variables and accurately classified 77.6%, 79.6%, and 79.4% of cases. Sensitivity analysis revealed that increased values of Temp_Trending and HR_Trending indicate a positive actual state, while diminished values of MAP_Trending suggest a favorable condition. The optimal cut-off points, sensitivities, specificities, positive and negative predictive values, likelihood ratios, and Youden and accuracy indices were found for the six evaluated patients' vital signs. Conclusion: Utilising dynamic tracking for vital signs in hospitalised patients with a tendency for rapid fluctuations may enhance prognostic performance and utility in predicting adverse outcomes, including prolonged length of stay and mortality.