Evidence map›Paper›PMID 38988810›Full record

ArticleFrontiers in cellular and infection microbiology2024

A novel web-based risk calculator for predicting surgical site infection in HIV-positive facture patients: a multicenter cohort study in China.

Bo Liu, Guo Wei, Liqiang Hu, Qiang Zhang

Abstract readMulticenter Study
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Bo LiuDepartment of Orthopaedics, Beijing Ditan Hospital, Capital Medical University, National Center for Infectious Diseases, Beijing, China.
Guo WeiDepartment of Surgery, Chengdu Public Health Clinical Medical Center, Chengdu, China.
Liqiang HuDepartment of Orthopaedics, Changsha First Hospital, Xiangya Medical College, Changsha, China.
Qiang ZhangDepartment of Orthopaedics, Beijing Ditan Hospital, Capital Medical University, National Center for Infectious Diseases, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Surgical site infection (SSI) is a common complication in HIV-positive fracture patients undergoing surgery, leading to increased morbidity, mortality, and healthcare costs. Accurate prediction of SSI risk can help guide clinical decision-making and improve patient outcomes. However, there is a lack of user-friendly, Web-based calculator for predicting SSI risk in this patient population. Objective: This study aimed to develop and validate a novel web-based risk calculator for predicting SSI in HIV-positive fracture patients undergoing surgery in China. Method: A multicenter retrospective cohort study was conducted using data from HIV-positive fracture patients who underwent surgery in three tertiary hospitals in China between May 2011 and September 2023. We used patients from Beijing Ditan Hospital as the training cohort and patients from Chengdu Public Health and Changsha First Hospital as the external validation cohort. Univariate, multivariate logistic regression analyses and SVM-RFE were performed to identify independent risk factors for SSIs. A web-based calculator was developed using the identified risk factors and validated using an external validation cohort. The performance of the nomogram was evaluated using the area under the receiver operating characteristic (AUC) curves, calibration plots, and decision curve analysis (DCA). Results: A total of 338 HIV-positive patients were included in the study, with 216 patients in the training cohort and 122 patients in the validation cohort. The overall SSI incidence was 10.7%. The web-based risk calculator (https://sydtliubo.shinyapps.io/DynNom_for_SSI/) incorporated six risk factors: HBV/HCV co-infection, HIV RNA load, CD4+ T-cell count, Neu and Lym level. The nomogram demonstrated good discrimination, with an AUC of 0.890 in the training cohort and 0.853 in the validation cohort. The calibration plot showed good agreement between predicted and observed SSI probabilities. The DCA indicated that the nomogram had clinical utility across a wide range of threshold probabilities. Conclusion: Our study developed and validated a novel web-based risk calculator for predicting SSI risk in HIV-positive fracture patients undergoing surgery in China. The nomogram demonstrated good discrimination, calibration, and clinical utility, and can serve as a valuable tool for risk stratification and clinical decision-making in this patient population. Future studies should focus on integrating this nomogram into hospital information systems for real-time risk assessment and management.

Indexed as

HIV InfectionsInternetSurgical Wound InfectionAdultChinaFemaleHumansMaleMiddle AgedNomogramsRetrospective StudiesRisk AssessmentRisk FactorsROC Curvebinary logistic regressionfractureHIVmulticenter cohort studypredictive modelrisk factorssurgical site infectionSVM-RFE

Identifiers

PMID38988810
PMCPMC11233529

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