Avoiding Flexor Tendon Repair Rupture with Intraoperative Total Active Movement Examination
Bibliographic record
Abstract
BACKGROUND: Wide-awake flexor tendon repair in tourniquet-free unsedated patients permits intraoperative Total Active Movement examination (iTAMe) of the freshly repaired flexor tendon. This technique has permitted the intraoperative observation of tendon repair gapping induced by active movement when the core suture is tied too loosely. The gap can be repaired intraoperatively to decrease postoperative tendon repair rupture rates. The authors record their rupture rate in the first 15 years of experience with iTAMe. METHODS: This was a retrospective chart review of 102 consecutive patients with wide-awake flexor tendon repair (no tourniquet, no sedation, and pure locally injected lidocaine with epinephrine anesthesia) in which iTAMe was performed by two hand surgeons in two Canadian cities between 1998 and 2008. Intraoperative gapping and postoperative rupture were analyzed. RESULTS: The authors observed intraoperative bunching and gap formation with active movement in flexor tendon repair testing (iTAMe) in seven patients. In all seven cases, they redid the repair and repeated iTAMe to confirm gapping was eliminated before closing the skin, and those seven patients did not rupture postoperatively. In 68 patients with known outcomes, four of 122 tendons ruptured (tendon rupture rate, 3.3 percent) in three of 68 patients (patient rupture rate, 4.4 percent). All three patients who ruptured had accidental jerk forced rupture. All those patients who did what we asked them did not rupture. CONCLUSIONS: Tendons can gap with active movement if the core suture is tied too loosely. Gapping can be recognized intraoperatively with iTAMe and repaired to decrease postoperative rupture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".