The microdebrider, a step forward or an expensive gadget?
Bibliographic record
Abstract
BACKGROUND: Although the use of the microdebrider (shaver) is well known in endoscopic sinus surgery (FESS), there is lack of evidence from comparative studies focussing on the difference in operating time, intra-operative blood loss and user-friendliness between the microdebrider and traditional operating techniques. In this study we compared the use of the microdebrider to conventional instruments in FESS in these areas. METHODS: A prospective randomised double blind controlled trial in 60 patients with chronic rhinosinusitis with nasal polyposis (CRSwNP) undergoing bilateral FESS. Each subject received FESS using only traditional instruments (Blakseley forceps) on one side and the other side with the additional use of the microdebrider, this way serving as their own control. The primary outcome was operation time, intra-operative blood loss and user friendliness and secondly safety and postoperative healing with a follow-up period at different time points up to three months postoperative. RESULTS: We found a 37% longer operating time when operating without a microdebrider. This difference was highly significant. The microdebrider scored significantly higher on every different parameter of user friendliness, except on the preparation of the instrument needed before surgery. For estimated blood loss during surgery we found no differences. Also there was no significant difference in postoperative healing at any point of time. CONCLUSIONS: This study demonstrates that operating patient with CRSwNP with the microdebrider is efficient and that the microdebrider at the same time is safe and easy to use.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".