Finger Injection with High-Dose (1:1,000) Epinephrine: Does it Cause Finger Necrosis and should it be Treated?
Bibliographic record
Abstract
OBJECTIVES: Accidental finger injections with high-dose (1:1,000) epinephrine is a new and increasing phenomenon. The purpose of this study is to document the incidence of finger necrosis and the treatment for this type of injury. The necessity or type of treatment required for this type of injury has not been established. METHODS: The literature was reviewed from 1900 to 2005 by hand and by Internet to document all cases of high-dose (1:1,000) finger epinephrine injection. In addition, the authors added five additional cases. RESULTS: There are a total of 59 reported cases of finger injections with high-dose epinephrine, of which, 32 cases were untreated. There were no instances of necrosis or skin loss, but neuropraxia lasting as long as 10 weeks and reperfusion pain were carefully documented. Treatment was not uniform for those who received it, but phentolamine was the most commonly used agent. CONCLUSIONS: There is not one case of finger necrosis in all of the 59 reported cases of finger injections with 1:1,000 epinephrine in the world literature. The necessity or type of treatment of high-dose epinephrine injection injuries remains conjecture, but phentolamine is the most commonly used agent in the reported cases, and the rationale and evidence for its use are discussed.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.004 | 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".