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Abstract
Objective: Identify predictors of early clinical deterioration and investigate the predictive value of early warning scores including NEWS, NEW2C, MEWS, and HEWS to detect clinical deterioration in patients after discharge from intensive care unit (ICU
Methods: A prospective cohort study was conducted in the Department of Neurology and Neuro Intensive Care, VietDuc University Hospital. Logistic regression was used to identify predictors of early clinical deterioration. Area under the receiver operating characteristic curves (AUROC curve) was used to compare the predictive accuracy of the National Early Warning Score (NEWS), National Early Warning Score C (NEWSC), Modified Warning Score (MEWS), and Hamilton Early Warning Scores (HEWS).
Results: A total of 147 patients were included in this study. The reasons for ICU admission, plan for ICU discharges, use of vasopressors at discharge, NEWS, NEWS2, and HEWS scores at discharge were statistically significant predictors of early clinical deterioration (p < 0.05). Among three tools, HEWS had the highest predictive value for early clinical deterioration, with the largest AUROC (0.743 ± 0.062). A HEWS score ≥ 3 showed the highest predictive accuracy, with 93.3% sensitivity and 41.7% specificity.
Conclusion: HEWS has the highest predictive value for clinical deterioration in the context of neurology patients being transferred from the ICU to general ward. The use of predictive tool should be assessed alongside other clinical indicators, as this may support clinicians in making accurate decisions before discharging patients from ICU
References
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| Published | 29-12-2024 | |
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| Issue | Vol. 16 No. 9 (2024) | |
| Section | Original article | |
| DOI | 10.38103/jcmhch.16.9.12 | |
| Keywords | Suy giảm lâm sàng, người bệnh hồi sức, xuất ICU, yếu tố dự đoán Early clinical deterioration, intensive care patient, discharge, predictors |
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