Dataset Information

Prediction Model of in-Hospital Venous Thromboembolism in Chinese Adult Patients after Hernia Surgery: The CHAT Score.

ABSTRACT:

Background

Venous thromboembolism (VTE) events after hernia surgery influence prognosis and life quality and may be preventable. This study aimed to develop a useful model for predicting in-hospital VTE in Chinese patients after hernia surgery.

Methods

Patients after hernia surgery were retrospectively recruited from 58 institutions (n = 14 322). Totally, 36 potential predictors were involved in the regression analysis. Weighted points were assigned to the predictors of in-hospital VTE identified in the multivariate logistic regression analysis and a prediction model was established. Decision curve analysis was performed to evaluate the net clinical benefit between the established and Caprini models.

Results

A total of 11 707 patients were included and five variables were explored as predictors related to in-hospital VTE: varicose veins of lower extremity, history of VTE, family history of thrombosis, interruption of antithrombotic agents, and reducible hernia. The prediction model (the CHAT score) revealed a good performance metrics (c-statistic, 0.81 [95% CI, 0.80 to 0.81]; Nagelkerke R², 0.27 [95% CI, 0.26 to 0.30]; Brier score, 0.16 [95% CI, 0.13 to 0.23]). The rate of in-hospital VTE after hernia surgery at low-risk (-4 points), intermediate-risk (0-1 points), high-risk (4 points) and very high-risk (≥5 points) were 0.05%, 0.39%, 0.73% and 8.62%, respectively. The CHAT score identified a considerable variability (from 0.05% to 8.62%) for in-hospital VTE among the overall population after hernia surgery. Decision curve analysis found a superior net benefit of the established model than the Caprini score.

Conclusions

The CHAT score is likely to be a practical 5-item supporting tool to identify patients at high risk of in-hospital VTE after hernia surgery that might assist in decision making and VTE prevention. Further validated study will strengthen this finding.

SUBMITTER: Gu ZC

PROVIDER: S-EPMC8725045 | biostudies-literature |

REPOSITORIES: biostudies-literature

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