Establishment of a model for predicting the postoperative morbidity in patients with pelvic and acetabulum fractures.
- Author:
Yi-Lin SU
1
;
Gang WANG
;
Rui-Jin WANG
Author Information
- Publication Type:Journal Article
- MeSH: Acetabulum; injuries; surgery; Adult; China; epidemiology; Female; Fractures, Bone; surgery; Humans; Logistic Models; Male; Morbidity; Pelvic Bones; injuries; surgery; Postoperative Complications; epidemiology; etiology; Prognosis; ROC Curve; Retrospective Studies; Risk Assessment; Treatment Outcome
- From: Journal of Southern Medical University 2008;28(1):116-118
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo establish a model for predicting the postoperative morbidity in patients with pelvic and acetabulum fractures.
METHODSThe clinical of 94 patients with pelvic and acetabulum fractures were retrospectively reviewed for analysis of the postoperative complications and duration of hospital stay. The preoperative physiological scores (PS) and operative severity scores (OS) of the patients were selected as the variables, and their regression coefficients were calculated by logistic regression analysis to establish the model for predicting the postoperative morbidities. The predictive value of the model was evaluated according to the ROC curve.
RESULTSThe model for predicting postoperative morbidities of pelvic and acetabulum fractures, ln P/(1-P)=-13.83+0.47x PS+0.33xOS, has an area under ROC curve of 0.888-/+0.037 with the cut-off point of 37%, sensitivity of 84.21%, specificity of 82.14%, concordance rate of 82.98%, misclassification rate of 15.79% and omission classification rate of 17.86%.
CONCLUSIONThis model possesses a high predictive capability for postoperative morbidities of pelvic and acetabulum fractures, and can be helpful for clinical therapeutic decision-making and lower the risks in operation.
