Optimal Time Delay between Epinephrine Injection and Incision to Minimize Bleeding
Bibliographic record
Abstract
BACKGROUND: The time until maximal cutaneous vasoconstriction after injection of lidocaine with epinephrine is often given in textbooks and multiple choice examinations as 7 to 10 minutes. However, in our experience, there is significantly less cutaneous bleeding if one waits considerably longer than 7 to 10 minutes after injection of local anesthesia with epinephrine for most procedures on human skin. METHODS: This was a prospective, randomized, triple-blind study where 12 volunteers were injected simultaneously in each arm with either 1% lidocaine with epinephrine (study group) or 1% plain lidocaine (control group), after which the relative hemoglobin concentration of the underlying skin and soft tissues was measured over time using spectroscopy. RESULTS: In the epinephrine group, the mean time at which the lowest cutaneous hemoglobin level was obtained was 25.9 minutes (95 percent CI, 25.9 ± 5.1 minutes). This was significantly longer than the historical literature values of 7 to 10 minutes for maximum vasoconstriction after injection. Mean hemoglobin index values at every time measurement after postinjection minute 1 were significantly different between the study group and the control group, with use of a two-tailed paired t test (p < 0.01). CONCLUSIONS: If optimal visualization is desired, the ideal time for the surgeon to begin the incision should be 25 minutes after injection of local anesthetic with epinephrine. It takes considerably longer than 7 to 10 minutes for a new local equilibrium to be obtained in relation to hemoglobin quantity.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".