Suction drainage in total knee replacement does not influence early functional outcomes or blood loss: a randomized control trial
Bibliographic record
Abstract
INTRODUCTION: The use of wound drainage following total knee arthroplasty (TKA) remains controversial. The purpose of this study was to evaluate the impact of suction drainage on early postoperative outcomes in patients who underwent TKA with concomitant administration of intravenous tranexamic acid (TXA). METHOD: One hundred forty-six patients undergoing primary TKA with systematic intravenous TXA were prospectively selected and randomly divided into two groups. The first "Study group" (n = 67) received no suction drain and the second "Control" group (n = 79) had a suction drain. Perioperative hemoglobin levels, blood loss, complications, and length of hospital stay were assessed in both groups. Preoperative and postoperative range of motion and Knee Injury and Osteoarthritis Outcome Scores (KOOS) were also compared at a 6-week follow-up. RESULTS: The study group was found to have higher hemoglobin levels preoperatively and during the first two days following surgery, and no difference was found between the groups on the third day. No significant discrepancies at any time were found between groups in terms of blood loss, length of hospitalization, knee range of motion, and KOOS score. Complications requiring further treatment were observed in one patient from the study group and ten patients from the control group. CONCLUSION: The use of suction drains after TKA with TXA did not alter early postoperative outcomes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".