Evaluation of Skin Damage from Accidental Removal of a Hemostatic Wound Clamp (The iTClamp)
Bibliographic record
Abstract
BACKGROUND: Controlling bleeding early in the prehospital and military setting is an extremely important and life-saving skill. Wound clamping is a newly introduced technique that may augment both the effectiveness and logistics of wound packing with any gauze product. As these devices may be inadvertently removed, the potential consequences of such were examined in a simulated, extreme, inadvertent disengagement. METHODS: The wound clamp used was an iTClamp (Innovative Trauma Care; Edmonton, Alberta, Canada) that was applied and forcefully removed (skin-pull) from the skin of both a human cadaver and swine. Sixty skin-pull tests were sequentially performed to measure the pull weight required to remove the device, any potential skin and device damage, how the device failed, and if the device could be re-applied. RESULTS: Observations of the skin revealed that other than the expected eight small needle holes from device application, no other damage to the skin was sustained in 98.3% of cases. Conversely, of the 60 devices pulled, 93.3% of the devices sustained no damage and all could be re-applied. Four (6.7%) of the devices remained in place despite a maximum pull weight >22lb F (pound-force). The mean pull weights for pin bar pull were (lb F ): vertical 9.2 (SD=5.0); perpendicular 2.5 (SD=1.7); and parallel 5.3 (SD=3.1). For the encompassed pull position group, mean pull weights were (lb F ): vertical 5.7 (SD=2.3); perpendicular 3.0 (SD=2.5); and parallel 14.5 (SD=3.5). The overall mean for all groups was 6.7 (SD=5.2). The two main reasons that the iTClamp was pulled off were because the friction lock let go or the needles slipped out of one side of the skin due to the angle of the pull. CONCLUSION: Inadvertent, forcible removal of the iTClamp created essentially no skin damage seen when the wound clamp was forcibly removed from either cadaver or swine models in a variety of positions and directions. Thus, the risks of deployment in operational environments do not seem to be increased. Mckee JL , Lakshminarasimhan P , Atkinson I , LaPorta AJ , Kirkpatrick AW . Evaluation of skin damage from accidental removal of a hemostatic wound clamp (the iTClamp). Prehosp Disaster Med. 2017;32(6):651-656.
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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 | 0.002 |
| 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 | 0.000 |
| 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".