Development and validation of a score to identify in the Emergency Department patients who may benefit from a time-critical intervention: a cohort study

Abstract Background Risk stratification methods developed on the basis of predicting illness severity are often used to prioritise patients on the basis of urgency. Illness severity and urgency may not be interchangeable. Severe illness places patients at risk of adverse outcome, but treatment is only urgent if adverse outcome can be prevented by time-sensitive treatment. We aimed to develop a score to identify patients in need of urgent treatment, on the basis of potential to benefit from time-sensitive intervention, and to compare this with a severity score identifying patients at high risk of death. Methods A sequential cohort of adults presenting to one Emergency Department by ambulance and admitted to hospital was prospectively collected (2437 derivation, 2322 validation). Data on outcomes representing potential to benefit was collected retrospectively on a random subset (398 derivation, 227 validation). Logistic regression identified variables predictive of death and potential to benefit from urgent treatment. Results Death was predicted using age, respiratory rate, diastolic blood pressure, oxygen saturations, temperature, GCS and respiratory disease (AUROC 0.84 (95 % CI 0.8–0.89) derivation and 0.74 (0.69–0.81) validation), while potential to benefit was predicted by pulse, systolic blood pressure and GCS (AUROC 0.74 (0.67–0.80) derivation and 0.71 (0.59–0.82) validation). Conclusions A score developed to predict the need for urgent treatment has a different composition to a score developed to predict illness severity, suggesting that triage methods based on predicting severity could lead to inappropriate prioritisation on the intended basis of urgency.

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PID https://www.doi.org/10.6084/m9.figshare.c.3646325
PID https://www.doi.org/10.6084/m9.figshare.c.3646325.v1
URL http://dx.doi.org/10.6084/m9.figshare.c.3646325.v1
URL http://dx.doi.org/10.6084/m9.figshare.c.3646325
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Author Challen, Kirsty
Author Bradburn, Mike
Author Goodacre, Steve
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Collected From Datacite
Hosted By figshare
Publication Date 2015-01-01
Publisher Figshare
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Language UNKNOWN
Resource Type Collection
keyword FOS: Mathematics
keyword FOS: Health sciences
keyword FOS: Biological sciences
keyword FOS: Clinical medicine
system:type other
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Source https://science-innovation-policy.openaire.eu/search/other?orpId=dedup_wf_001::bc25591ea22e89dcc17ea78a4f96a0c5
Author jsonws_user
Last Updated 19 December 2020, 21:11 (CET)
Created 19 December 2020, 21:11 (CET)