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Record W4415430192 · doi:10.1302/1358-992x.2025.10.061

SURGICAL AND CLINICAL OUTCOMES FOLLOWING MANAGEMENT OF TOTAL KNEE ARTHROPLASTY PERIPROSTHETIC JOINT INFECTION WITH EXTENSOR MECHANISM DISRUPTION AND SOFT-TISSUE DEFECT: THE KNEE ARTHROPLASTY TERRIBLE TRIAD

2025· article· en· W4415430192 on OpenAlexaff
Bahar Entezari, Johnathan R. Lex, Madison L. Litowski, Saud Almaslmani, David Backstein, J. Wolfstadt

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopedic Infections and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPeriprostheticOdds ratioLogistic regressionArthroplastyConfidence intervalComplicationRange of motionExact testSoft tissueStatistical significance

Abstract

fetched live from OpenAlex

Periprosthetic infection (PJI) with concomitant extensor mechanism disruption (EMD) and soft tissue defect – hereinafter termed the “Terrible Triad” – is a devastating complication following total knee arthroplasty (TKA). The purpose of this study was to define the surgical and clinical outcomes following management of patients with the Terrible Triad. From 2000 to 2022, 127 patients underwent operative management for PJI, 25 for PJI with major soft tissue defect (defined as defects requiring flap reconstruction or being a main factor contributing to the decision of performing above-knee-amputation (AKA) or arthrodesis), 14 for PJI with EMD (with or without attempted repair or reconstruction), and 22 for the Terrible Triad. A composite outcome considering infection status (defined according to the 2018 ICM consensus statement for PJI management), range of motion (ROM), extensor lag, and ambulatory status at final follow-up was used to determine the proportion of patients in each group with a favorable overall knee outcome and compared across groups (Table 1) [1]. Two-year mortality from initiation of PJI treatment was compared across groups. Differences in continuous data were assessed using one-way ANOVA and Tukey's post hoc test. Differences in categorical data were assessed using Pearson's Chi-squared test or Fisher's exact test. Multivariable logistic regression was used to calculate odds ratios (OR) and 95% confidence intervals (CI). The Kaplan-Meier survival analysis and log-rank test were used to assess mortality. Statistical significance was set at α=0.05. Mean duration of follow-up was 7.71 years and equivalent between groups (p=0.053). Patients in both the Terrible Triad group and PJI with soft tissue defect group demonstrated lower incidence of infection control with no continued antibiotic therapy and higher incidence of AKA or arthrodesis (Tier 3E) compared to patients in both the PJI group and PJI with EMD group (p<0.001), and higher incidence of limited ambulation compared to those in the PJI group (p<0.001). Patients in the Terrible Triad group demonstrated higher incidence of ROM arc <90° than those in the PJI group (p=0.031), and higher incidence of extensor lag >15° than those in the PJI group and PJI and soft tissue defect group (p<0.001) (Table 2). Patients in the PJI with soft tissue defect, PJI with EMD, and Terrible Triad groups showed higher odds of unfavorable overall knee outcome than those in the PJI group (OR=5.81, OR=5.50, OR=11.61, respectively). Mean two-year mortality was 7.8%, 8.0%, 42.9%, and 9.1% in the PJI, PJI with soft tissue defect, PJI with EMD, and Terrible Triad groups, respectively (p=0.472). Symbols (§, †, ‡, ¶) within a row indicate statistically significant differences between two groups as determined by Tukey's post hoc test following one-way ANOVA for continuous data and chi squared test or fisher's exact test for categorical data. This study demonstrates that the Terrible Triad of TKA is a dreaded diagnosis with poor outcomes, leaving 86.4% of patients with an unfavorable overall knee outcome. Patients should be warned of high risk for failure with multiple revisions during their management. Early treatment with definitive fusion or AKA should be considered by patients and surgeons. For any figures or tables, please contact the authors directly.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.829

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.287
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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