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| Establish and evaluation of a regression prediction model of the lower extremity deep vein thrombosis after laparoscopic ovarian cystectomy |
| Linquan County People's Hospital, Linquan, Anhui Province, 236400 |
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Abstract To investigate the influencing factors of the lower extremity deep vein thrombosis (DVT) of patients after laparoscopic ovarian cystectomy, to identify the risk indicators of DVT, and to establish and evaluate a regression prediction model of DVT of the patients. Methods: The clinical data of 292 patients who underwent laparoscopic ovarian cystectomy from June 2021 to February 2023 were selected as research subjects by convenience sampling. The postoperative lower extremity DVT occurrence of the patients were statistically analyzed. Univariate analysis and multivariate logistic regression analysis were used to explore the independent risk factors of the lower extremity DVT of the patients after laparoscopic ovarian cystectomy. A regression prediction model was established, and its goodness of fit of the model was evaluated by Hosmer Lemeshow (H-L) test. The predictive efficiency of the model for DVT was assessed by receiver operating characteristic (ROC) curve. Results: In 292 patients, there were 21 (7.2%) cases with lower limb DVT. Logistic regression analysis showed that the history of high blood pressure, the long operative time, the high intraoperative pneumoperitoneum pressure, and the increase of the levels of the D dimers and blood coagulation factor VIII in the postoperative 1st day of the patients after laparoscopic ovarian cystectomy were all the independent risk factors of their lower extremity DVT occurrence (all P<0.05). Based on these independent risk factors, a logistic regression prediction model was established, and H-L test showed that P=0.847, and which suggested that the model was efficacy. ROC curve showed that the area under the curve of the model for predicting the lower extremity DVT of the patients after laparoscopic ovarian cystectomy was 0.764, and the prediction efficiency of which was medium. When the maximum Youden index was 0.448, the sensitivity and the specificity of the model for predicting the lower extremity DVT of the patients after laparoscopic ovarian cystectomy were 76.2% and 68.6%. Conclusion: The regression prediction model established in this study can provide the evidences for identifying the lower extremity DVT of the patients after laparoscopic ovarian cystectomy, which may assist the personalized postoperative DVT prevention management of the patients.
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