Cost minimization while ensuring safety of reduction mammaplasty
Bibliographic record
Abstract
A prospective randomized study was designed to address the safety of performing reduction mammaplasty without drains. In the same cohort, the postoperative pain requirements, length of stay and complications were recorded in an effort to document the efficacy of performing this surgery in an outpatient setting. All women presenting for reduction mammaplasty at the Royal Victoria Hospital during a one-year period were asked to participate in the study. A total of 75 patients enrolled, and complete data were available at the 28-day follow-up for all women. The overall hematoma rate was 0% with drains and 2.7% without drains. The observed infection rate was 8% with drains and 5% without drains. There is no statistically significant or clinically meaningful difference in complication rates between breasts treated with drains and those treated without drains. In addition, 90% of women can be managed with oral analgesics within 23 h of surgery. Combined, this information suggests a potential cost savings of 57% based on prestudy observations. Careful analysis of the process of care will continue to enable the care of patients to be more efficient without compromising quality or safety.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".