NDLI: Surgical site infection surveillance in knee and hip arthroplasty: optimizing an algorithm to detect high-risk patients based on electronic health records

Content Provider	Springer Nature : BioMed Central
Author	Guedes, Mariana Almeida, Francisco Andrade, Paulo Moreira, Lucybell Pedrosa, Afonso Azevedo, Ana Rocha-Pereira, Nuno
Abstract	Background Surgical site infection (SSI) is an important cause of disease burden and healthcare costs. Fully manual surveillance is time-consuming and prone to subjectivity and inter-individual variability, which can be partly overcome by semi-automated surveillance. Algorithms used in orthopaedic SSI semi-automated surveillance have reported high sensitivity and important workload reduction. This study aimed to design and validate different algorithms to identify patients at high risk of SSI after hip or knee arthroplasty. Methods Retrospective data from manual SSI surveillance between May 2015 and December 2017 were used as gold standard for validation. Knee and hip arthroplasty were included, patients were followed up for 90 days and European Centre for Disease Prevention and Control SSI classification was applied. Electronic health records data was used to generate different algorithms, considering combinations of the following variables: ≥1 positive culture, ≥ 3 microbiological requests, antimicrobial therapy ≥ 7 days, length of hospital stay ≥ 14 days, orthopaedics readmission, orthopaedics surgery and emergency department attendance. Sensitivity, specificity, negative and predictive value, and workload reduction were calculated. Results In total 1631 surgical procedures were included, of which 67.5% (n = 1101) in women; patients’ median age was 69 years (IQR 62 to 77) and median Charlson index 2 (IQR 1 to 3). Most surgeries were elective (92.5%; n = 1508) and half were hip arthroplasty (52.8%; n = 861). SSI incidence was 3.8% (n = 62), of which 64.5% were deep or organ/space infections. Positive culture was the single variable with highest sensitivity (64.5%), followed by orthopaedic reintervention (59.7%). Twenty-four algorithms presented 90.3% sensitivity for all SSI types and 100% for deep and organ/space SSI. Workload reduction ranged from 59.7 to 67.7%. The algorithm including ≥ 3 microbiological requests, length of hospital stay ≥ 14 days and emergency department attendance, was one of the best options in terms of sensitivity, workload reduction and feasibility for implementation. Conclusions Different algorithms with high sensitivity to detect all types of SSI can be used in real life, tailored to clinical practice and data availability. Emergency department attendance can be an important variable to identify superficial SSI in semi-automated surveillance.
Related Links	https://aricjournal.biomedcentral.com/counter/pdf/10.1186/s13756-024-01445-x.pdf
Ending Page	10
Page Count	10
Starting Page	1
File Format	HTM / HTML
ISSN	20472994
DOI	10.1186/s13756-024-01445-x
Journal	Antimicrobial Resistance & Infection Control
Issue Number	1
Volume Number	13
Language	English
Publisher	BioMed Central
Publisher Date	2024-08-15
Access Restriction	Open
Subject Keyword	Medical Microbiology Drug Resistance Infectious Diseases Surgical site infection Healthcare-associated infections Surveillance Semi-automated surveillance Infection prevention and control Orthopaedic surgery Knee arthroplasty Hip arthroplasty Electronic health records Algorithm
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health Infectious Diseases Microbiology (medical) Pharmacology (medical)
Journal Impact Factor	4.8/2023
5-Year Journal Impact Factor	5.8/2023

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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