ArticlePharmacoepidemiology and drug safety2021
Development and validation of case-finding algorithms to identify prosthetic joint infections after total knee arthroplasty in Veterans Health Administration data.
Article in Pharmacoepidemiology and drug safety, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it, 9 citations in OpenAlex.
- Application of artificial intelligence in X-ray imaging analysis for knee arthroplasty: A systematic review.PloS one · 2025Pooled it
- Incidence of periprosthetic joint infection after primary total hip arthroplasty is underestimated: a synthesis of meta-analysis and bibliometric analysis.Journal of orthopaedic surgery and research · 2023Pooled it
- Development and Validation of Case-Finding Algorithms to Identify Periprosthetic Joint Infections After Total Hip Arthroplasty in Veterans Health Administration Data.Pharmacoepidemiology and drug safety · 2026Article
- Incidence, Microbiological Studies, and Factors Associated With Prosthetic Joint Infection After Total Knee Arthroplasty.JAMA network open · 2023Article
- Estimating incidence rates of periprosthetic joint infection after hip and knee arthroplasty for osteoarthritis using linked registry and administrative health data.The bone & joint journal · 2022Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
purposeTo determine the positive predictive values (PPVs) of ICD-9, ICD-10, and current procedural terminology (CPT)-based diagnostic coding algorithms to identify prosthetic joint infection (PJI) following knee arthroplasty (TKA) within the United States Veterans Health Administration.
methodsWe identified patients with: (1) hospital discharge ICD-9 or ICD-10 diagnosis of PJI, (2) ICD-9, ICD-10, or CPT procedure code for TKA prior to PJI diagnosis, (3) CPT code for knee X-ray within ±90 days of the PJI diagnosis, and (4) at least 1 CPT code for arthrocentesis, arthrotomy, blood culture, or microbiologic procedure within ±90 days of the PJI diagnosis date. Separate samples of patients identified with the ICD-9 and ICD-10-based PJI diagnoses were obtained, stratified by TKA procedure volume at each medical center. Medical records of sampled patients were reviewed by infectious disease clinicians to adjudicate PJI events. The PPV (95% confidence interval [CI]) for the ICD-9 and ICD-10 PJI algorithms were calculated.
resultsAmong a sample of 80 patients meeting the ICD-9 PJI algorithm, 60 (PPV 75.0%, [CI 64.1%-84.0%]) had confirmed PJI. Among 80 patients who met the ICD-10 PJI algorithm, 68 (PPV 85.0%, [CI 75.3%-92.0%]) had a confirmed diagnosis.
conclusionsAn algorithm consisting of an ICD-9 or ICD-10 PJI diagnosis following a TKA code combined with CPT codes for a knee X-ray and either a relevant surgical procedure or microbiologic culture yielded a PPV of 75.0% (ICD-9) and 85.0% (ICD-10), for confirmed PJI events and could be considered for use in future pharmacoepidemiologic studies.
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