Bibliographic record
Abstract
BACKGROUND: In distal upper extremity surgeries, there can be a choice to use an upper arm or forearm tourniquet. This study examines discomfort and tolerance in healthy volunteers to determine whether one is more comfortable. METHODS: Forty healthy, study participants were randomized to an upper extremity laterality and site. Tourniquets were inflated to 100 mm Hg over systolic blood pressure. Participants experienced an upper arm and a forearm tourniquet sequentially. Visual analog scores (VAS) were recorded at 2-minute intervals. Time until request and VAS at tourniquet deflation were recorded. Time until the complete resolution of paresthesias was also recorded. Participants subjectively stated which tourniquet felt more comfortable. RESULTS: Tourniquets were inflated longer on the forearm than the upper arm (mean 16.1 minutes versus 12.2 minutes; P < 0.0001). VAS at tourniquet removal was not different between the sites (means 7.3 and 7.3) (P = 0.839). Time until paresthesia resolution after the tourniquet was deflated was not different (means 8.1 and 7.7 minutes) (P = 0.675). Time until paresthesia resolution was proportional to tourniquet inflation time for both sites (regression coefficient 0.41; P < 0.00001). Participants found the forearm more comfortable (95% confidence interval, 0.63 to 0.92). CONCLUSION: Forearm placement allows the tourniquet to be inflated for an average of 4 minutes longer. Forearm tourniquet is subjectively more comfortable.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.006 | 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".