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A nomogram to predict postoperative infection for older hip fracture patients

  • Orthopaedic Surgery
  • Published:
Archives of Orthopaedic and Trauma Surgery Aims and scope Submit manuscript

Abstract

Introduction

Postoperative infection is one of the most common postoperative complications in hip fracture surgery. It is related with increased morbidity and mortality. This study aimed at developing a nomogram to predict the individual probability of postoperative infection to facilitate perioperative decision-making.

Materials and Methods

In this retrospective study, we included all patients over 65 years old admitted for hip fracture in West China Hospital of Sichuan University from 1 January 2015 to 31 December 2019. Univariate and multivariate logistic regression analyses were used to identify significant predictors. We used all-subsets regression to screen an optimal model, and visualized the model through drawing nomogram. To evaluate the model performance, we applied receiver operating characteristic curve and calibration curve.

Results

We enrolled 677 older patients. 136 (20.1%) patients developed postoperative infection during hospitalization. Variables retained in the final model were albumin [odds ratio (OR) 0.90, 95% confidence interval (CI) 0.84–0.96], cholesterol (OR 1.49, 95% CI 1.04–2.15), blood phosphorus (OR 0.16, 95% CI 0.05–0.48), high-density lipoprotein (OR 0.42, 95% CI 0.19–0.89), surgery type (OR 2.27, 95% CI 1.35–3.90), smoking (OR 1.95, 95% CI 1.02–3.66), American Society of Anesthesiologists classification [class III (OR 1.02, 95% CI 0.55–1.93); class IV (OR 1.93, 95% CI 0.76–4.82)], and chronic pulmonary disease (OR 2.16, 95% CI 1.25–3.68). The C-index of the nomogram was 0.752 (95% CI 0.697–0.806). Calibration curve showed good agreement between predicted value and observed outcome. In the validation group, our nomogram showed an area under the receiver operating characteristic curve of 0.723 (95% CI 0.639–0.807).

Conclusion

Our nomogram showed good discrimination ability in predicting individual probability of postoperative infection among older patients with hip fracture surgery. The nomogram could help clinicians identify patients at high risk of postoperative infection before surgery.

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Funding

This work was supported by National Key R&D Program of China (grant number 2018YFC2001800) to XCH and TZ; National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University (grant number Z2018A02) to TZ; and 1·3·5 project for disciplines of excellence, West China Hospital, Sichuan University to TZ.

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Author notes

  1. Xiran Peng and Xuechao Hao authors contributed equally to this article and should be considered as co-first authors.

Authors and Affiliations

  1. Department of Anesthesiology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, China

    Xiran Peng, Xuechao Hao & Tao Zhu

Authors
  1. Xiran Peng
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  2. Xuechao Hao
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  3. Tao Zhu
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Contributions

All authors contributed to the study conception and design. Data acquisition, data analysis and model construction were performed by XP and XH. The initial draft of the manuscript was written by XP. Critical revision of manuscript was performed by XH and TZ. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Tao Zhu.

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Conflict of interest

The authors have no conflicts of interest to declare that are relevant to the content of this article.

Ethical approval

The protocol of this study was approved by Committee of Ethics from West China Hospital of Sichuan University (2019-473) with waiver of informed consent, and registered at www.chictr.org.cn (ChiCTR1900025160).

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Supplementary Information

Below is the link to the electronic supplementary material.

402_2021_4171_MOESM1_ESM.pdf

Supplementary file1 Supplementary table S1 Variables included in study. Supplementary table S1 Univariate logistic regression analysis of predictors for postoperative infection Supplementary table S3 VIF value of each variable. Supplementary table S4 VIF value of each variable after adjustment for strongly correlated variables (PDF 443 kb)

Supplementary file2 (PDF 617 kb)

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Peng, X., Hao, X. & Zhu, T. A nomogram to predict postoperative infection for older hip fracture patients. Arch Orthop Trauma Surg 143, 847–855 (2023). https://doi.org/10.1007/s00402-021-04171-w

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  • DOI: https://doi.org/10.1007/s00402-021-04171-w

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