Establishment and validation of a predictive model for increased drainage volume after open transforaminal lumbar interbody fusion
- VernacularTitle:开放式经椎间孔腰椎椎间融合术后引流量增加的预测模型构建与验证
- Author:
Yin HU
1
;
Hai-long YU
;
Hong-wen GU
;
Kang-en HAN
;
Shi-lei TANG
;
Yuan-hang ZHAO
;
Zhi-hao ZHANG
;
Jun-chao LI
;
Le XING
;
Hong-wei WANG
Author Information
- Publication Type:Journal Article
- Keywords: transforaminal lumbar interbody fusion; predictive model; drainage volume; risk factors
- From: Journal of Regional Anatomy and Operative Surgery 2025;34(11):981-986
- CountryChina
- Language:Chinese
- Abstract: Objective To analyze the risk factors for increased drainage volume after open transforaminal lumbar interbody fusion(TLIF),and to establish a predictive model and then validate it.Methods The clinical data of 680 patients who underwent open TLIF at the General Hospital of Northern Theater Command from January 2016 to December 2019 were collected and the patients were randomly divided into the training group(n=476)and the validation group(n=204).Taking the predictive factors screened out by LASSO regression analysis as independent variables,a multivariate Logistic regression predictive model was constructed.The model was internally validated through the receiver operating characteristic(ROC)curve,Hosmer-Lemeshow goodness-of-fit test,and calibration curve,and its clinical utility was assessed via decision curve analysis(DCA).Results LASSO regression analysis screened out four predictive variables:age,number of surgical segments,operative duration,and intraoperative blood loss.The multivariate Logistic regression predictive model demonstrated that age≥60 years,number of surgical segments≥4,operative duration≥2 hours,and intraoperative blood loss≥200 mL were independent influencing factors for the increased postoperative drainage volume in patients undergoing TLIF(P<0.05).ROC curve analysis revealed an area under the curve(AUC)of 0.816(95%CI:0.798 to 0.867)in the training group and 0.783(95%CI:0.685 to 0.823)in the validation group,indicating that the predictive model had good discriminatory ability.Additionally,the Hosmer-Lemeshow goodness-of-fit test and calibration curve indicated that the predictive model had a good degree of fit,and the predicted probability was basically consistent with the actual probability,demonstrating a good calibration.The DCA results confirmed that this predictive model could be applied in clinical practice.Conclusion The risk factors for increased drainage volume after open TLIF include age,number of surgical segments,operative duration,and intraoperative blood loss.The predictive model established based on these factors demonstrates good performance,and it can be applied in clinical guidance for the selection of drainage tube removal time after TLIF.
