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Randomized Controlled Trial
. 2024 Jan 5;19(1):38.
doi: 10.1186/s13018-023-04473-2.

A predictive nomogram for surgical site infection in patients who received clean orthopedic surgery: a retrospective study

Zhi Li #  1 , Lihua Song #  1 , Baoju Qin #  1 , Kun Li #  1 , Yingtao Shi  2 , Hongqing Wang  3 , Huiwang Wang  3 , Nan Ma  3 , Jinlong Li  4 , Jitao Wang  5 , Chaozheng Li  6
Affiliations
Randomized Controlled Trial

A predictive nomogram for surgical site infection in patients who received clean orthopedic surgery: a retrospective study

Zhi Li et al. J Orthop Surg Res. .

Abstract

Background: Surgical site infection (SSI) is a common and serious complication of elective clean orthopedic surgery that can lead to severe adverse outcomes. However, the prognostic efficacy of the current staging systems remains uncertain for patients undergoing elective aseptic orthopedic procedures. This study aimed to identify high-risk factors independently associated with SSI and develop a nomogram prediction model to accurately predict the occurrence of SSI.

Methods: A total of 20,960 patients underwent elective clean orthopedic surgery in our hospital between January 2020 and December 2021, of whom 39 developed SSI; we selected all 39 patients with a postoperative diagnosis of SSI and 305 patients who did not develop postoperative SSI for the final analysis. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. Univariate and multivariate logistic regression analyses were conducted in the training cohort to screen for independent risk factors of SSI, and a nomogram prediction model was developed. The predictive performance of the nomogram was compared with that of the National Nosocomial Infections Surveillance (NNIS) system. Decision curve analysis (DCA) was used to assess the clinical decision-making value of the nomogram.

Results: The SSI incidence was 0.186%. Univariate and multivariate logistic regression analysis identified the American Society of Anesthesiology (ASA) class (odds ratio [OR] 1.564 [95% confidence interval (CI) 1.029-5.99, P = 0.046]), operative time (OR 1.003 [95% CI 1.006-1.019, P < 0.001]), and D-dimer level (OR 1.055 [95% CI 1.022-1.29, P = 0.046]) as risk factors for postoperative SSI. We constructed a nomogram prediction model based on these independent risk factors. In the training and validation cohorts, our predictive model had concordance indices (C-indices) of 0.777 (95% CI 0.672-0.882) and 0.732 (95% CI 0.603-0.861), respectively, both of which were superior to the C-indices of the NNIS system (0.668 and 0.543, respectively). Calibration curves and DCA confirmed that our nomogram model had good consistency and clinical predictive value, respectively.

Conclusions: Operative time, ASA class, and D-dimer levels are important clinical predictive indicators of postoperative SSI in patients undergoing elective clean orthopedic surgery. The nomogram predictive model based on the three clinical features demonstrated strong predictive performance, calibration capabilities, and clinical decision-making abilities for SSI.

Keywords: Elective clean orthopedic surgery; Nomogram; Prediction model; Surgical site infection.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
A nomogram model for predicting overall risk of surgical site infection after elective orthopedic surgery
Fig. 2
Fig. 2
ROC curve analysis was used to compare the performance of the nomogram and the NNIS system for predicting surgical site infection in A the training cohort and B the validation cohort. ROC receiver operating characteristic, NNIS national nosocomial infections surveillance
Fig. 3
Fig. 3
Calibration curves of the nomogram for predicting the risk of surgical site infection in A the training cohort and B the validation cohort
Fig. 4
Fig. 4
Decision curve analysis for the nomogram and the NNIS system for surgical site infection in A the training cohort and B the validation cohort
See this image and copyright information in PMC

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