Effects of systemic lidocaine versus magnesium administration on postoperative functional recovery and chronic pain in patients undergoing breast cancer surgery: A prospective, randomized, double-blind, comparative clinical trial
Bibliographic record
Abstract
INTRODUCTION: We aimed to compare the effects of intraoperative lidocaine and magnesium on postoperative functional recovery and chronic pain after mastectomy due to breast cancer. Systemic lidocaine and magnesium reduce pain hypersensitivity to surgical stimuli; however, their effects after mastectomy have not been evaluated clearly. METHODS: In this prospective, double-blind, clinical trial, 126 female patients undergoing mastectomy were randomly assigned to lidocaine (L), magnesium (M), and control (C) groups. Lidocaine and magnesium were administered at 2 mg/kg and 20 mg/kg for 15 minutes immediately after induction, followed by infusions of 2 mg/kg/h and 20 mg/kg/h, respectively. The control group received the same volume of saline. Patient characteristics, perioperative parameters, and postoperative recovery profiles, including the Quality of Recovery 40 (QoR-40) survey, pain scales, length of hospital stay, and the short-form McGill pain questionnaire (SF-MPQ) at postoperative 1 month and 3 months were evaluated. RESULTS: The global QoR-40 scores on postoperative day 1 were significantly higher in group L than in group C (P = 0.003). Moreover, in sub-scores of the QoR-40 dimensions, emotional state and pain scores were significantly higher in group L than those in groups M and C (P = 0.027 and 0.023, respectively). At postoperative 3 months, SF-MPQ and SF-MPQ-sensitive scores were significantly lower in group L than in group C (P = 0.046 and 0.036, respectively). CONCLUSIONS: Intraoperative infusion of lidocaine improved the quality of recovery and attenuated the intensity of chronic pain in patients undergoing breast cancer surgery.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".