Clinical curative effect of video-assisted breast surgery by single incision through the anterior axillary line for removing mammary fibroma
Bibliographic record
Abstract
Objective: This study aims to investigate the clinical curative effect of Video-Assisted Breast Surgery (VABS) by single incision through the anterior axillary line for removing mammary fibroma. Methods: Sixty-eight mammary fibroma cases treated in the hospital from November 2013 to June 2015 were selected and randomly divided into control and observation groups (34 cases per group). The control group was subjected to conventional ring areola incision, and the observation group was subjected to VABS by single incision through the anterior axillary line. Intraoperative blood loss, incision length, postoperative complication, and cosmetic effects after the operation were determined and compared between the two groups. Results: The observation group showed shorter incision length and hospital stay and less intraoperative blood losses than those in the control group (p 0.05). The complication rates in the observation and control groups were 5.88% and 23.33%, respectively (p<0.05). The Vancouver scar scale score in the observation group was lower than that in the control group. Furthermore, breast appearance satisfaction score in the observation group was significantly higher than that in the control group (p<0.05). Conclusion: Patients with mammary fibroma who underwent VABS received improved clinical curative effects in terms of few intraoperative injuries, fast recovery after the surgery, low complication rate, non-restricted lesion depth limit, and satisfactory cosmetic effect. Overall, this technique improved the prognosis of the patients.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".