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• W2095100018 abstract "Background We performed a retrospective study to compare the precision of a regression model (RM) system with the precision of the standard method of surgical length prediction using historical means (HM). Methods Data were collected on patients who underwent carotid endarterectomy and lower-extremity bypass. Multiple linear regression was used to model the operative time length (OTL). The precision of the RM versus HM in predicting case length then was compared in a validation dataset. Results With respect to carotid endarterectomy, surgeon, surgical experience, and cardiac surgical risk were significant predictors of OTL. For lower-extremity bypass, surgeon, use of prosthetic conduit, and performance of a sequential bypass or hybrid procedure were significant predictors of OTL. The precision of out-of-sample prediction was greater for the RM system compared with HM for both procedures. Conclusions A regression methodology to predict case length appears promising in decreasing uncertainty about surgical case length." @default.
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• W2095100018 date "2012-11-01" @default.
• W2095100018 modified "2023-09-23" @default.
• W2095100018 title "Derivation and out-of-sample validation of a modeling system to predict length of surgery" @default.
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• W2095100018 doi "https://doi.org/10.1016/j.amjsurg.2012.07.013" @default.
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