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Record W4200204513 · doi:10.1097/corr.0000000000002055

Prior Intra-articular Corticosteroid Injection Within 3 Months May Increase the Risk of Deep Infection in Subsequent Joint Arthroplasty: A Meta-analysis

2021· article· en· W4200204513 on OpenAlexaboutno aff

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2021
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsCorticosteroidOrthopedic surgeryJoint (building)Infection riskMEDLINEJoint arthroplasty

Abstract

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BACKGROUND: Intra-articular injections containing a corticosteroid are used frequently, and periprosthetic joint infection is a serious complication after total joint arthroplasty. There is debate regarding whether intra-articular corticosteroid injections before arthroplasty increase periprosthetic joint infection after surgery. QUESTIONS/PURPOSES: (1) Does a previous intra-articular corticosteroid injection increase the odds of infection after subsequent hip or knee arthroplasty? (2) Does this risk vary based on how soon before the arthroplasty (such as less than 3 months before surgery) the injection is administered? METHODS: Using the PubMed, Embase, Cochrane Library, and Web of Science databases from inception to July 2021, we searched for comparative studies in English on patients who received intra-articular corticosteroid injections before arthroplasty and that tracked the frequency of infection after arthroplasty. We extracted data on the risk of infection after subsequent joint arthroplasty. The keywords included "corticosteroid," "steroid," "arthroplasty," "knee replacement," and "hip replacement." Eleven retrospective, comparative studies from four countries were included, of which 10 reported the specific diagnosis criteria and one did not. These articles included data on 173,465 arthroplasties in the hip or knee, as well as of 73,049 injections and 100,416 control patients. The methodologic quality of the included studies was evaluated according to the Newcastle-Ottawa Quality Assessment Scale; the articles' scores ranged from 6 to 7 (the score itself spans 0 to 9, with higher scores representing better study quality). We found no evidence of publication bias based on the Egger test, and tests of heterogeneity generally found heterogeneity, so a random-effects model was used of our meta-analyses. A meta-analysis was performed with Review Manager 5.3 software and Stata version 12.0 software. RESULTS: Overall, there were no differences in the odds of periprosthetic joint infection between the injection group and the control group among patients who received any kind of injection (odds ratio 1.22 [95% CI 0.95 to 1.58]; p = 0.12). However, in a subgroup analysis, there was a higher OR for postoperative PJI in patients with an intra-articular corticosteroid injection in the knee or hip within 3 months (OR 1.39 [95% CI 1.04 to 1.87]; p = 0.03). There were no differences in the infection risk in patients who had injections between 3 and 6 months before arthroplasty (OR 1.19 [95% CI 0.95 to 1.48]; p = 0.13) or between 6 and 12 months before arthroplasty. CONCLUSION: The current evidence suggests ipsilateral intra-articular corticosteroid injections within 3 months before arthroplasty were associated with an increased risk of periprosthetic joint infection during subsequent joint arthroplasty. We recommend against performing total joint arthroplasty on a patient who has received an intra-articular corticosteroid injection within 3 months. Further high-quality studies on this topic from registries, national databases, or insurance company data are still required to confirm and extend our findings. LEVEL OF EVIDENCE: Level III, therapeutic study.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.040
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0140.059
Bibliometrics0.0050.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.089
GPT teacher head0.383
Teacher spread0.293 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
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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Citations47
Published2021
Admission routes1
Has abstractyes

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