ArticleCMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne2019
Computer-aided National Early Warning Score to predict the risk of sepsis following emergency medical admission to hospital: a model development and external validation study.
Article in CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Impact of diastolic blood pressure time under range on mortality and acute kidney injury in septic patients: a retrospective cohort study.BMC anesthesiology · 2025Article
- Plasmonic coffee-ring biosensing for AI-assisted point-of-care diagnostics.Nature communications · 2025Article
- Combining host immune response biomarkers and clinical scores for early prediction of sepsis in infection patients.Annals of medicine · 2024Article
- Accuracy of automated computer-aided risk scoring systems to estimate the risk of COVID-19: a retrospective cohort study.BMC research notes · 2024Article
- Comparing 11 early warning scores and three shock indices in early sepsis prediction in the emergency department.World journal of emergency medicine · 2024Article
- Computerized Clinical Decision Support Systems for the Early Detection of Sepsis Among Adult Inpatients: Scoping Review.Journal of medical Internet research · 2022Article
- Observational study on wearable biosensors and machine learning-based remote monitoring of COVID-19 patients.Scientific reports · 2021Article
- Early detection of sepsis using artificial intelligence: a scoping review protocol.Systematic reviews · 2021Article
- What's new in critical illness and injury science? The use of risk stratification tools in patients with suspected sepsis in the acute care settings.International journal of critical illness and injury scienceArticle
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7 authors.
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Abstract
backgroundIn hospitals in England, patients' vital signs are monitored and summarized into the National Early Warning Score (NEWS); this score is more accurate than the Quick Sepsis-related Organ Failure Assessment (qSOFA) score at identifying patients with sepsis. We investigated the extent to which the accuracy of the NEWS is enhanced by developing and comparing 3 computer-aided NEWS (cNEWS) models (M0 = NEWS alone, M1 = M0 + age + sex, M2 = M1 + subcomponents of NEWS + diastolic blood pressure) to predict the risk of sepsis.
methodsWe included all emergency medical admissions of patients 16 years of age and older discharged over 24 months from 2 acute care hospital centres (York Hospital [YH] for model development and a combined data set from 2 hospitals [Diana, Princess of Wales Hospital and Scunthorpe General Hospital] in the Northern Lincolnshire and Goole National Health Service Foundation Trust [NH] for external model validation). We used a validated Canadian method for defining sepsis from administrative hospital data.
resultsThe prevalence of sepsis was lower in YH (4.5%, 1596/35 807) than in NH (8.5%, 2983/35 161). The C statistic increased across models (YH: M0 0.705, M1 0.763, M2 0.777; NH: M0 0.708, M1 0.777, M2 0.791). For NEWS of 5 or higher, sensitivity increased (YH: 47.24% v. 50.56% v. 52.69%; NH: 37.91% v. 43.35% v. 48.07%), the positive likelihood ratio increased (YH: 2.77 v. 2.99 v. 3.06; NH: 3.18 v. 3.32 v. 3.45) and the positive predictive value increased (YH: 11.44% v. 12.24% v. 12.49%; NH: 22.75% v. 23.55% v. 24.21%).
interpretationFrom the 3 cNEWS models, model M2 is the most accurate. Given that it places no additional burden of data collection on clinicians and can be automated, it may now be carefully introduced and evaluated in hospitals with sufficient informatics infrastructure.
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