Outcomes of Total Knee and Hip Arthroplasty in Patients With Perioperative Thrombocytopenia
Bibliographic record
Abstract
BACKGROUND: Thrombocytopenia is an abnormally low level of blood platelets (less than 150,000/mL) resulting in an increased risk for bleeding. Typically, patients with platelet levels below 50,000/mL should delay arthroplasty or be transfused with platelets before surgery. However, existing studies are mixed regarding the effects of more moderate thrombocytopenia in terms of total knee and hip arthroplasty outcomes. METHODS: This level III retrospective chart review examined the effects of different severities of preoperative thrombocytopenia on length of hospitalization, readmission, and transfusion rates in 5,617 primary total knee and hip arthroplasties at one tertiary academic medical center. Preoperative platelet levels were sectioned into clinically relevant groups and compared with clinical outcomes using univariable and multivariable models. RESULTS: On univariate analysis, having platelet levels of <100,000/mL and 100 to 149,000/mL was associated with a longer length of stay. However, after controlling individual demographics, there was no association between platelet levels and length of stay, nor with 30-day readmission. Finally, on univariate analysis, patients with platelet levels of <100,000/mL and 100 to 149,000/mL were more likely to have a blood transfusion, which remained true for those with <100,000/mL after controlling for individual demographics. CONCLUSIONS: Total hip and total knee arthroplasty are safe in patients with varying platelet levels and not associated with increased length of stay or 30-day readmission. However, patients with more severe thrombocytopenia are more likely to receive red blood cell transfusions than patients with milder thrombocytopenia.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".