Key result
A nomogram incorporating age, operation time, diabetes, white blood cell count, and hemoglobin effectively predicted postoperative surgical site infection with an AUC of 0.842 in the training set and 0.898 in the external validation set.
Why the study?
Surgical site infection is a common postoperative complication with serious consequences, motivating the development of a nomogram to estimate its probability in orthopaedic patients.
Observational (n=787)
Yes
Effect estimate: AUC 0.842 (95% CI 0.777-0.907)
A novel nomogram incorporating age, operation time, diabetes, WBC, and HGB demonstrated good discriminative ability for predicting postoperative surgical site infections in adult orthopaedic patients.
May inform SSI risk stratification in orthopaedics; leaves open prospective validation before clinical adoption.
Surgical site infection is a common postoperative complication with serious consequences. This study developed a nomogram to estimate the probability of postoperative surgical site infection for orthopaedic patients. Adult patients following orthopaedic surgery during hospitalization were included in this study. We used univariate and multivariate logistic regression analyses to establish the predictive model, which was also visualized by nomogram. To evaluate the model performance, we applied the receiver operating characteristic curve, calibration curve, and decision curve analysis, which were utilized in external validation and internal validation. From January 2021 to June 2022, a total of 787 patients were enrolled in this study. After statistical analysis, five variables were enrolled in the predictive model, including age, operation time, diabetes, WBC, and HGB. The mathematical formula has been established as follows: Logit (SSI) = - 6.301 + 1.104 * (Age) + 0.669 * (Operation time) + 2.009 * (Diabetes) + 1.520 * (WBC) - 1.119 * (HGB). The receiver Operating Characteristic curve, calibration curve, and decision curve analysis presented a good performance of this predictive model. Our nomogram showed great discriminative ability, calibration, and clinical practicability in the training set, external validation, and internal validation.
No takes yet. Share an insight, caveat, or question.
Huang et al. (2023) conducted an observational in Postoperative surgical site infection (n=787). Nomogram incorporating age, operation time, diabetes, WBC, and HGB was evaluated on Discriminative ability (AUC) for predicting surgical site infection in the training set (AUC 0.842, 95% CI 0.777-0.907). A nomogram incorporating age, operation time, diabetes, white blood cell count, and hemoglobin effectively predicted postoperative surgical site infection with an AUC of 0.842 in the training set and 0.898 in the external validation set.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: