RETRACTED: Association between malnutrition and surgical site and periprosthetic joint infections following joint arthroplasty: A systematic review and meta‐analysis
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
Abstract Post‐joint arthroplasty infections, especially surgical site infections (SSI) and periprosthetic joint infections (PJI), significantly impact patient outcomes. The potential influence of malnutrition on these postoperative complications remains a crucial concern for clinicians. Adhering to PRISMA guidelines, we performed a systematic review and meta‐analysis using four databases up to 19 July 2023. We sought studies on joint replacements, focusing on malnutrition as an SSI risk factor. The malnutrition criteria were defined by specific laboratory parameters. Two independent reviewers undertook data extraction and quality assessment, with discrepancies resolved through consensus or third‐party review. Studies were evaluated for methodological quality using the Newcastle‐Ottawa Scale (NOS). For statistical analyses, heterogeneity was assessed using the I 2 statistic, and both fixed and random‐effects models were employed based on heterogeneity levels, utilizing Stata software (version 17). Significant heterogeneity was present among studies examining the relationship between malnutrition and SSI ( I 2 = 59.5%, p = 0.03%). Employing the random‐effects model, results indicated that malnourished individuals were approximately 2.63 times more likely to develop SSI post‐operation. Further exploration into the association between malnutrition and PJI, from seven pertinent studies, also revealed an elevated risk (OR = 2.59, 95% CI: 1.79–3.39). Sensitivity analyses confirmed the robustness of these findings, and publication bias assessments supported the validity of the included studies. Malnutrition robustly correlates with an increased risk of both SSI and PJI following total joint arthroplasty. Emphasizing preoperative nutritional assessments and intervention strategies may offer a promising avenue to enhance patient outcomes and reduce postoperative complications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.014 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".