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dc.contributor.authorJarvis, S.W.*
dc.contributor.authorKovacs, C.*
dc.contributor.authorBadriyah, T.*
dc.contributor.authorBriggs, J.*
dc.contributor.authorMohammed, Mohammed A.*
dc.contributor.authorMeredith, P.*
dc.contributor.authorSchmidt, P.E.*
dc.contributor.authorFeatherstone, P.I.*
dc.contributor.authorPrytherch, D.R.*
dc.contributor.authorSmith, G.B.*
dc.date.accessioned2016-10-07T15:33:59Z
dc.date.available2016-10-07T15:33:59Z
dc.date.issued2013-11
dc.identifier.citationJarvis SW, Kovacs C, Badriyah T, Briggs J, Mohammed MA et al (2013) Development and validation of a decision tree early warning score based on routing laboratory test results for the discrimination of hospital mortality in emergency medical admissions. Resuscitation. 84(11): 1494-1499.
dc.identifier.urihttp://hdl.handle.net/10454/9783
dc.descriptionNo
dc.description.abstractTo build an early warning score (EWS) based exclusively on routinely undertaken laboratory tests that might provide early discrimination of in-hospital death and could be easily implemented on paper. Using a database of combined haematology and biochemistry results for 86,472 discharged adult patients for whom the admission specialty was Medicine, we used decision tree (DT) analysis to generate a laboratory decision tree early warning score (LDT-EWS) for each gender. LDT-EWS was developed for a single set (n=3496) (Q1) and validated in 22 other discrete sets each of three months long (Q2, Q3...Q23) (total n=82,976; range of n=3428 to 4093) by testing its ability to discriminate in-hospital death using the area under the receiver-operating characteristic (AUROC) curve. The data generated slightly different models for male and female patients. The ranges of AUROC values (95% CI) for LDT-EWS with in-hospital death as the outcome for the validation sets Q2-Q23 were: 0.755 (0.727-0.783) (Q16) to 0.801 (0.776-0.826) [all patients combined, n=82,976]; 0.744 (0.704-0.784, Q16) to 0.824 (0.792-0.856, Q2) [39,591 males]; and 0.742 (0.707-0.777, Q10) to 0.826 (0.796-0.856, Q12) [43,385 females]. CONCLUSIONS: This study provides evidence that the results of commonly measured laboratory tests collected soon after hospital admission can be represented in a simple, paper-based EWS (LDT-EWS) to discriminate in-hospital mortality. We hypothesise that, with appropriate modification, it might be possible to extend the use of LDT-EWS throughout the patient's hospital stay.
dc.relation.isreferencedbyhttp://dx.doi.org/10.1016/j.resuscitation.2013.05.018
dc.subjectAdolescent
dc.subject; Adult
dc.subject; Aged
dc.subject; Algorithms
dc.subject; Decision trees
dc.subject; Diagnostic tests
dc.subject; Emergencies
dc.subject; Female
dc.subject; Hospital mortality
dc.subject; Humans
dc.subject; Male
dc.subject; Middle aged
dc.subject; Patient admission
dc.subject; Predictive value of tests
dc.subject; Biochemistry
dc.subject; Early warning scores
dc.subject; Haematology
dc.subject; Illness severity score
dc.subject; Risk prediction
dc.titleDevelopment and validation of a decision tree early warning score based on routine laboratory test results for the discrimination of hospital mortality in emergency medical admissions
dc.status.refereedYes
dc.date.Accepted2013-05-24
dc.date.application2013-05-31
dc.typeArticle
dc.type.versionNo full-text available in the repository


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