Stapled double head and neck drape for otological procedures
Bibliographic record
Abstract
INTRODUCTION: During otologic surgical procedures, there is often a dilemma when ensuring that hair is kept out of the surgical field. For a surgeon, the simplest and commonest technique is to liberally shave the head, but this can cause aesthetic concerns for the patient. Failure to keep the area hair-free can lead to a range of adverse surgical outcomes including wound infection and poor scar cosmesis. We describe a technique used in our department to effectively control hair during otologic surgical procedures, with no post-operative aesthetic concerns. METHODS: The use of re-usable or disposable surgical drapes with disposable skin staples can effectively exclude hair from the operative field throughout the procedure, without fear of the drapes slipping or losing adhesiveness. RESULTS: The authors have obtained good results both during and after surgery, using this quick and easily learnt method, with no cases of long-term skin damage or scarring. DISCUSSION: We find this to be an effective method of hair and skin preparation for otologic surgical procedures, and suggest it to fellow otorhinolaryngologists as a helpful alternative technique.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".