Patients with metabolic syndrome have a greater rate of complications after arthroplasty
Bibliographic record
Abstract
Aims Patients with metabolic syndrome (MetS) are known to be at increased risk of postoperative complications, but it is unclear whether MetS is also associated with complications after total hip arthroplasty (THA) or total knee arthroplasty (TKA). Here, we perform a systematic review and meta-analysis linking MetS to postoperative complications in THA and TKA. Methods The PubMed, OVID, and ScienceDirect databases were comprehensively searched and studies were selected and analyzed according to the guidelines of the Meta-analysis of Observational Studies in Epidemiology (MOOSE). We assessed the methodological quality of each study using the Newcastle-Ottawa Scale (NOS), and we evaluated the quality of evidence using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Data were extracted and meta-analyzed or qualitatively synthesized for several outcomes. Results Ten cohort studies involving 1,352,685 patients were included. Qualitative analysis suggested that MetS was associated with a higher incidence of cardiovascular events, and meta-analysis showed that MetS increased the risk of all-cause complications (risk ratio (RR) 1.55, 95% confidence interval (CI) 1.28 to 1.89), surgical site infection (SSI; RR 2.99, 95% CI 1.30 to 6.90), urinary tract infection (UTI; RR 2.58, 95% CI 1.03 to 6.43), and 30-day readmission (RR 1.45, 95% CI 1.33 to 1.59). There was insufficient evidence for assessing an association between MetS and venous thromboembolism events, pulmonary or gastrointestinal complications, or mortality. Conclusion Patients with MetS undergoing THA and TKA are at increased risk of all-cause complications, cardiovascular complications, SSI, UTI, and 30-day readmission. Surgeons should be aware of the increased risk of these complications in MetS, and presurgical protocols for these complications should give special consideration to MetS patients. Cite this article: Bone Joint Res. 2020;9(3):120–129.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.016 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".