Bibliographic record
Abstract
OBJECTIVE: To summarize the current evidence-based knowledge about the long-term sequelae of injuries from electrical current. QUALITY OF EVIDENCE: MEDLINE was searched for English-language articles published in the past 20 years using the following search terms: electrical, injuries, wound, trauma, accident, sequelae, long-term, follow-up, and aftereffects. For obvious reasons, it is unethical to randomly study electrical injury in controlled clinical trials. By necessity, this topic is addressed in less-rigorous observational and retrospective work and case studies. Therefore, the strength of the literature pertaining to the long-term sequelae of electrical injury is impaired by the necessity of retrospective methods and case studies that typically describe small cohorts. MAIN MESSAGE: There are 2 possible consequences of electrical injury: the person either survives or dies. For those who survive electrical injury, the immediate consequences are usually obvious and often require extensive medical intervention. The long-term sequelae of the electrical injury might be more subtle, pervasive, and less well defined, but can include neurologic, psychological, and physical symptoms. In the field of compensation medicine, determining causation and attributing outcome to an injury that might not result in objective clinical findings becomes a considerable challenge. CONCLUSION: The appearance of these consequences of electrical injury might be substantially delayed, with onset 1 to 5 or more years after the electrical injury. This poses a problem for patients and health care workers, making it hard to ascribe symptoms to a remote injury when they might not arise until well after the incident event.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".