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dc.contributor.authorHaugan, Kristin
dc.contributor.authorKlaksvik, Jomar
dc.contributor.authorFoss, Olav A.
dc.date.accessioned2022-03-02T07:59:21Z
dc.date.available2022-03-02T07:59:21Z
dc.date.created2021-03-10T14:25:02Z
dc.date.issued2021
dc.identifier.issn0020-1383
dc.identifier.urihttps://hdl.handle.net/11250/2982273
dc.description.abstractObjective: To compare the Charlson Comorbidity Index (CCI) and American Society of Anesthesiologists (ASA) Physical Status Classification used in two prediction models for 30-day mortality after hip fracture surgery. Study design and setting: Data from 3651 patients (mean age: 83 years) from a Norwegian University Hospital were retrospectively obtained and randomly divided into two cohorts: a model cohort (n = 1825) to develop two prediction models with CCI and ASA as the main predictors, and a validation cohort (n = 1826) to assess the predictive ability of both models. A receiver operating characteristic (ROC) curve determined the best model to predict mortality. Results: Area under the ROC curve at 30 days was 0.726 (p = 0.988) for both the CCI- and ASA-model. The chosen cut-off-points on the ROC curve for CCI- and ASA-model corresponded to similar model sensitivities of 0.657 and specificities of 0.680 and 0.679, respectively. Hence, each model predicts correctly 66% (n = 96) of the mortalities and 68% (n = 1132 and n = 1131) of the survivals. 23% (n = 33) of the mortalities were predicted by neither model. Conclusion: The CCI- and ASA-model had equal predictive ability of 30-day mortality after hip fracture. Considering the effort involved in calculating Charlson Comorbidity Index score, the ASA score may be the preferred tool to predict the 30-day mortality after hip fracture.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.title30-day mortality in patients after hip fracture surgery: A comparison of the Charlson Comorbidity Index score and ASA score used in two prediction modelsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.journalInjuryen_US
dc.identifier.doi10.1016/j.injury.2021.02.004
dc.identifier.cristin1897016
dc.relation.projectSt Olavs Hospital HF: xxxxxxen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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