Population-based study of severe trauma due to electrocution in the Calgary Health Region, 1996-2002.
Bibliographic record
Abstract
BACKGROUND: Severe trauma arising from electrocution is uncommon, and we wished to study the incidence, risk factors and outcome to identify potential areas of prevention. We therefore studied an active population of adult victims of severe electrical trauma in a large area of Canada (the Calgary Health Region [CHR]). METHODS: From 3 databases, we collected data on all adult (> or = 18 yr) residents of the CHR who suffered electrical injury associated with an Injury Severity Score of 12 or greater or died as a result of electrocution between Apr. 1, 1996, and Mar. 1, 2002. Of particular interest were the incidence, the age and sex of the victims, the mechanism, the type of electrical power and the outcome. RESULTS: Ten cases of severe electrical trauma were identified (2.4 per 1 million population annually). Victims' ages were a mean (and standard deviation) of 38.2 (10.3) years. All 10 victims were male for an annual sex-specific incidence of 4.9 per 1 million people. Men aged 18-49 years were nearly 3 times more likely to be victims of electrocution than older men, although this result was not statistically significant (6.1 v. 2.1 per 1 million annually; relative risk 2.9; 95% confidence interval 0.4-127.5). All episodes of electrocution were unintentional, and 7 were occupationally related. All 10 electrocutions resulted from domestically generated current, and 9 were related to power-line exposure. Overall, 6 patients died for a death rate due to severe electrical trauma of 1.4 per 1 million people annually. CONCLUSION: This population-based study demonstrates that severe electrocution is rare but is associated with death in the majority of cases in this large Canadian region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".