Comparison of knot-tying proficiency and knot characteristics for square and reversing half hitch alternating-post surgical knots in a simulated deep body cavity among novice medical students
Bibliographic record
Abstract
<h3>Background:</h3> Proficiency-based knot-tying curricula have been developed for square knots for medical students, but, to our knowledge, no such curriculum exists for the reverse half hitch alternating-post (RHAP) knot. We aimed to compare medical students’ knot-tying proficiency, knot-tying self-confidence and final knot characteristics for RHAP and square knots in a simulated deep body cavity. <h3>Methods:</h3> We performed a within-subject prospective crossover study of novice medical students who received 30 minutes of training in tying both RHAP and square knots. Participant performance was assessed via a knot-tying checklist, and knot configuration, tensile strength, tightness (loop circumference) and mechanism of failure were also assessed. Participants’ self-reported confidence in knot tying was captured. <h3>Results:</h3> Twenty-one students participated in the study. Mean scores on the knot-tying checklist were significantly higher for RHAP knots than for square knots (6.9 [standard deviation (SD) 2.1] v. 5.2 [SD 2.3], <i>p</i> < 0.01), and RHAP knots were significantly tighter than square knots (46.8 mm [SD 0.4 mm] v. 49.3 mm [SD 0.7 mm], <i>p</i> < 0.05). There were no differences between RHAP and square knots in correct knot configuration, breaking strength or mechanism of failure. Reverse half hitch alternating-post knots were easier to tie within a deep-body cavity, whereas square knots were easier to learn. <h3>Conclusion:</h3> Novice medical students were more proficient in tying RHAP knots than square knots in a simulated deep body cavity. Students were able to construct RHAP knots more securely and reported increased confidence in tying RHAP knots at depth compared to square knots.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".