Incidence and Risk Factors for Venous Gas Emboli Formation in Canadian Forces Experimental Divers
Bibliographic record
Abstract
This study aims to investigate the relationship of self-reported pre-dive behaviours of Canadian Forces (CF) divers and detected venous gas emboli (VGE) post-experimental dive. A retrospective chart review of pre-dive questionnaires and matching post-dive venous Doppler bubble scores of 1,092 cf experimental dives was completed. Non-parametric categorical statistics were used to measure the effect of independent variables of age, exercise, alcohol, medication, smoking, food, fluid, fatigue, and infectious symptoms on maximum bubble grades (BG) measured precordially and at any site. Dives were analyzed as a single group and stratified into high-, moderate-, and low-stress dives, as well as exercise / no exercise during the dive subsets. Results : 12.6% of precordial bg and 26.1% of maximum any-site bg recorded as ≥ 3. Within 48 hours of diving, 45% exercised, 16.7% used oral medications, 38.25% consumed alcohol, 15.4% smoked, and 9.7% experienced infectious symptoms. Prior to the dive, 88.1% consumed food, 91.8% consumed liquids, and 26.3% felt fatigued. There was a statistically significant difference in bg among divers based on age ( p = 0.043, binary logistic regression All Dives, Maxbg) and smoking ( p = 0.045, Fisher’s exact test, All Dives Maxbg). These differences did not continue in the other diving subsets, and no statistically significant effects attributed to the other variables were noted in any dive subset. cf experimental divers do report exposure to potential pre-dive risk factors for vge. Significant association is detected between age, smoking status, and bg in one subset (all dives, Maxbg any site). No significant effect attributed to the remaining risk factors and bg is found. This study suggests that these factors may not affect vge formation and its attendant risk of decompression sickness (DCS) in this military experimental diver population. However, as the result of study limitations, future studies are required to evaluate each risk factor prospectively to determine its impact on vge formation during diving.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".