Comparison of quality of life and arm complaints after axillary lymph node dissection vs sentinel lymph node biopsy in breast cancer patients
Bibliographic record
Abstract
The sentinel lymph node biopsy (SLNB) represents a minimal invasive surgical method for axillary staging in patients with primary breast cancer. In a prospective study, evaluation of quality of life (QOL) and arm morbidity was performed before surgery on a total of 56 breast cancer patients. The EORTC QLQ-C30 and EORTC QLQ-BR23 questionnaires were used for QOL assessment. Assessment of pain was additionally observed using the McGill Pain Questionnaire. Arm mobility was observed by goniometric measurement of arm movement. Data were collected before surgery (t1), 1 week after discharge (t2) and 9-12 months after surgery (t3). The type of axillary surgery does not seem to affect global QOL at a short-time follow-up, but patients recover sooner after SLNB. Body image and sexual functioning remain stable in both types of axillary surgery. Arm/shoulder pain was reported in 36% of patients after SLNB in comparison to 68% receiving axillary lymph node dissection (ALND), and 'numbness' was reported only in 4% of patients in the SLNB group vs 19.3% after ALND. Abduction, flexion and horizontal adduction of the affected arm show significant impairment after ALND. Breast cancer patients should be counselled about the benefits of SLNB over ALND concerning QOL and postsurgery side effects in a short-term follow-up.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".