Personalizing Tourniquet Pressures – SBP-Based Estimation Methods are Unsafe, Unreliable, and Inconsistent
Bibliographic record
Abstract
It is well established that unnecessarily high tourniquet pressures are associated with higher probability of patient injuries, and insufficient tourniquet pressures can lead to break-through bleeding and other complications. Measurement of a patient’s limb occlusion pressure (LOP) through the use of an automatic personalized tourniquet system enables the simple and safe application of personalized tourniquet pressures, reducing the risk of tourniquet-related injuries. Doppler ultrasound may be used to measure LOP, however manual measurement of LOP by Doppler is time-consuming and error-prone if attempted by inadequately trained staff. Other methods based on systolic blood pressure (SBP) have been proposed in an attempt to indirectly estimate personalized tourniquet pressures. Such methods include: (1) setting tourniquet pressure as a function of the patient’s SBP, (2) indirectly estimating LOP by using a formula based on SBP and a ‘tissue padding coefficient’. Alternatively, non-personalized fixed tourniquet pressures are used, resulting in pressures that may be hazardously high or low. Data from a previous clinical study involving 143 patients was retrospectively analysed to compare the differences between measured LOP to the recommended pressures of the two SBP-based estimation methods. Results from method (1) using only SBP indicate a predicted bleed-through for 41% of patients, and results from method (2) using SBP and a coefficient indicate an estimated bleed-through rate for 62% of patients. Alternatively, using a non-personalized fixed pressure predicted no bleed-throughs, but resulted in unnecessarily high pressures that were on average 121 mmHg above LOP. This study demonstrates that indirect SBP-based estimation methods recommend unsafe, unreliable, and inconsistent tourniquet pressure settings when compared to the measurement and setting of tourniquet pressures by LOP. The next advances in tourniquet safety will come from widespread adoption of using personalized tourniquet systems to automatically measure LOP, and by personalizing safety margins to further reduce applied tourniquet pressure levels.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".