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The National Early Warning Score predicts mortality in hospital ward patients with deviating vital signs: A retrospective medical record review study.
Journal of Clinical Nursing 2019 April
AIMS AND OBJECTIVES: To evaluate whether the scale used for assessment of hospital ward patients could predict in-hospital and 30-day mortality amongst those with deviating vital signs; that is, that patients classified as medium or high risk would have increased risk of in-hospital and 30-day mortality compared to patients with low risk.
BACKGROUND: The National Early Warning Score (NEWS) is a widely adopted scale for assessing deviating vital signs. A clinical risk scale that comes with the NEWS divides the risk for critical illness into three risk categories, low, medium and high.
DESIGN: Retrospective analysis of vital sign data.
METHODS: Logistic regression models for age-adjusted in-hospital and 30-day mortality were used for analyses of 1,107 patients with deviating vital signs.
RESULTS: Patients classified as medium or high risk by NEWS experienced a 2.11 or 3.40 increase, respectively, in odds of in-hospital death (95% CI: 1.27-3.51, p = 0.004% and 95% CI: 1.90-6.01, p < 0.001) compared to low-risk patients. Moreover, those with NEWS medium or high risk were associated with a 1.98 or 3.19 increase, respectively, in odds of 30-day mortality (95% CI: 1.32-2.97, p = 0.001% and 95% CI: 1.97-5.18, p < 0.001).
CONCLUSION: The NEWS risk classification seems to be a reliable predictor of mortality on patients in hospital wards.
RELEVANCE TO CLINICAL PRACTICE: The NEWS risk classification offers a simple way to identify deteriorating patients and can aid the healthcare staff to prioritise amongst patients.
BACKGROUND: The National Early Warning Score (NEWS) is a widely adopted scale for assessing deviating vital signs. A clinical risk scale that comes with the NEWS divides the risk for critical illness into three risk categories, low, medium and high.
DESIGN: Retrospective analysis of vital sign data.
METHODS: Logistic regression models for age-adjusted in-hospital and 30-day mortality were used for analyses of 1,107 patients with deviating vital signs.
RESULTS: Patients classified as medium or high risk by NEWS experienced a 2.11 or 3.40 increase, respectively, in odds of in-hospital death (95% CI: 1.27-3.51, p = 0.004% and 95% CI: 1.90-6.01, p < 0.001) compared to low-risk patients. Moreover, those with NEWS medium or high risk were associated with a 1.98 or 3.19 increase, respectively, in odds of 30-day mortality (95% CI: 1.32-2.97, p = 0.001% and 95% CI: 1.97-5.18, p < 0.001).
CONCLUSION: The NEWS risk classification seems to be a reliable predictor of mortality on patients in hospital wards.
RELEVANCE TO CLINICAL PRACTICE: The NEWS risk classification offers a simple way to identify deteriorating patients and can aid the healthcare staff to prioritise amongst patients.
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