Quality-of-life of breast cancer women who underwent axillary node dissection by using ultrasound scissors. A prospective clinical study
Bibliographic record
Abstract
Background: In patients with early-stage breast cancer undergoing surgery axillary lymph node dissection (ALND) still represents the most accurate means of determining the axillary node status. Unfortunately, such procedure is usually associated with prolonged serous drainage that may result in an increased risk of lymphedema. The aim of this study was to analyze whether the use of ultrasound scissors (US) in performing ALND may reduce the risk of long-term morbidity, subsequently improving the quality of life of patients. Methods: Ninety-seven women (median age 55 years, range 33-74) underwent modified radical mastectomy (N=40, 41.2 %) or breast-conserving surgery with ALND (N=57, 58.8%) for primary pT1-2 breast cancer. Patients were randomly assigned to undergo ALND by either using (Group A, N=51) or not using (Group B, N=46) US. Health-related quality-of-life was measured with the Medical Outcomes Study Short Form 36 (MOS-SF-36). Assessment of pain was observed using the short form of the McGill Pain Questionnaire. Data were collected 15-18 months after surgery. Results: Age, BMI, tumor staging, number of removed and involved nodes, and type of surgery did not differ between Groups. Both total amount of drainage (449±152 vs. 384±131 mL; p=0.03), and the number of axillary seromas (19 of 51 vs. 24 of 46; p=0.14) were reduced in Group A patients. The results are shown in the table. Arm or shoulder pain was reported in 35% (Group A) and 52% (Group B) of patients (p=0.20). Conclusions: In patients undergoing ALND for breast cancer the use of US is useful both in reducing the total amount of drainage and the risk of seroma formation. However, such advantages may have a limited impact on long-term quality-of-life since only few parameters in the MOS-SF-36 form improved significantly.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".