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Title
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The optimal threshold for prompt clinical review : an external validation study of the national early warning score
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Author
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Abstract
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| Aim The aim of this study was to determine the optimal threshold for NEWS in clinical practice. Background The national early warning score (NEWS) is an aggregate early warning score aiming to predict patient mortality. Studies validating NEWS did not use standardised patient outcomes or did not always include clinical workload in their results. Since all patients with a positive NEWS require a clinical workup, it is crucial to determine the optimal threshold to limit false‐positive alerts. Design External validation study using retrospectively collected data of patient admissions in six Belgian hospitals. Methods We adhered to the STARD guideline for reporting. Two sample groups were selected: the cross‐sectional sample (admitted patients, one day every four months) and the serious adverse event (SAE) sample (all patients with unexpected death, cardiac arrest and unplanned admission to the intensive care unit). The maximum registered NEWS value was collected in both groups. Predictive values (PPVs) were used as estimates for clinical workload. Results We collected 1523 in the cross‐sectional sample and 390 patients in the SAE sample. A NEWS ≥5 had a PPV of 6.8% and a negative predictive value of 99.5% to predict unexpected death, cardiac arrest with cardiopulmonary resuscitation or unplanned admission to intensive care (AUROC 0.841). The performance of NEWS differed between outcome measures. Considering the PPV, the optimal threshold for NEWS is ≥5. Conclusions We validated NEWS to be applied in general hospital wards and confirmed the optimal threshold (≥5). |
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Language
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English
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Source (journal)
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Journal of clinical nursing. - Oxford
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Publication
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Hoboken
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Wiley
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2020
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ISSN
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0962-1067
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DOI
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10.1111/JOCN.15493
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Volume/pages
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29
:23-24
(2020)
, p. 4594-4603
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ISI
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000576625700001
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Pubmed ID
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32920891
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Full text (Publisher's DOI)
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Full text (open access)
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Full text (publisher's version - intranet only)
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