Water-Tight Knee Arthrotomy Closure: Comparison of a Novel Single Bidirectional Barbed Self-Retaining Running Suture Versus Conventional Interrupted Sutures
Bibliographic record
Abstract
Standard medial parapatellar arthrotomies of 10 cadaveric knees were closed with either conventional interrupted absorbable sutures (control group, mean of 19.4 sutures) or a single running knotless bidirectional barbed absorbable suture (experimental group). Water-tightness of the arthrotomy closure was compared by simulating a tense hemarthrosis and measuring arthrotomy leakage over 3 minutes. Mean total leakage was 356 mL and 89 mL in the control and experimental groups, respectively (p = 0.027). Using 8 of the 10 knees (4 closed with control sutures, 4 closed with an experimental suture), a tense hemarthrosis was again created, and iatrogenic suture rupture was performed: a proximal suture was cut at 1 minute; a distal suture was cut at 2 minutes. The impact of suture rupture was compared by measuring total arthrotomy leakage over 3 minutes. Mean total leakage was 601 mL and 174 mL in the control and experimental groups, respectively (p = 0.3). In summary, using a cadaveric model, arthrotomies closed with a single bidirectional barbed running suture were statistically significantly more water-tight than those closed using a standard interrupted technique. The sample size was insufficient to determine whether the two closure techniques differed in leakage volume after suture rupture.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".