Contrast of Mastoscopic and Conventional Axillary Lymph Node Dissection of Patients With Breast Cancer: Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mastoscopic axillary lymph node dissection (MALND) is a currently used and safe surgical treatment option for breast cancer. However, the extensive application of MALND is still debatable because of the use of conventional axillary lymph node dissection (CALND). Therefore, in the current study, we aimed to compare the efficacy and safety of MALND and CALND for obtaining evidence-based conclusions about the short-term and long-term outcomes of MALND for patients with breast cancer. PubMed, Web of Science, Cochrane Library, and CNKI were comprehensively searched for articles published between January 1998 and January 2019. Then Newcastle-Ottawa scale was used for quality assessment. The Review Manager software version 5.0 was utilized for generating forest maps and funnel plots. Twelve studies including 2157 patients were selected for the meta-analysis. There were no significant differences in the number of lymph node dissections, tumor recurrence rate, axillary drainage, postoperative hospitalization time, and tumor size between the MALND and CALND groups ( P > .05). In the MALND group, the surgery time was longer, while the incidence of intraoperative bleeding was lesser and the duration of drainage was shorter than those in the CALND group ( P < .01). The complications in the MALND group were also fewer than those in the CALND group ( P < .05). The results of the current study showed that MALND is reliable and feasible for breast cancer owing to the lesser incidence of intraoperative bleeding, shorter drainage duration, and lower incidence of complications compared to CALND.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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) | 0.000 | 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 it