Efficacy and Safety of Sugammadex versus Neostigmine in Reversing Neuromuscular Blockade in Morbidly Obese Adult Patients
Bibliographic record
Abstract
Context: Sugammadex is known to reverse neuromuscular blockade (NMB) more rapidly and reliably than neostigmine. However, data remain limited in bariatric patients. In this review, we systematically evaluated the efficacy and safety of sugammadex versus neostigmine in reversing NMB in morbidly obese (MO) patients undergoing bariatric surgery. Aims: Our primary objective was to determine the recovery time from drug administration to a train-of-four (TOF) ratio >0.9 from a moderate or deep NMB. Settings and Design: This systematic review and meta-analysis (SR and MA) was conducted in accordance with the Preferred Items for SRs and MAs guidelines. Subjects and Methods: A systematic search was conducted within multiple databases for studies that compared sugammadex and neostigmine in MO patients. Statistical Analysis Used: We reported data as mean difference (MD) or odds ratios (OR) and corresponding 95% confidence interval (CI) using random-effects models. A two-sided P < 0.05 was considered statistically significant. Results: Seven studies with 386 participants met the inclusion criteria. Sugammadex significantly reduced the time of reversal of moderate NMB-to-TOF ratio >0.9 compared to neostigmine, with a mean time of 2.5 min (standard deviation [SD] 1.25) versus 18.2 min (SD 17.6), respectively (MD: −14.52; 95% CI: −20.08, −8.96; P < 0.00001; I 2 = 96%). The number of patients who had composite adverse events was significantly lower with sugammadex (21.2% of patients) compared to neostigmine (52.5% of patients) (OR: 0.15; 95% CI: 0.07–0.32; P < 0.00001; I 2 = 0%). Conclusions: Sugammadex reverses NMB more rapidly with fewer adverse events than neostigmine in MO patients undergoing bariatric surgery.
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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 | 0.000 | 0.001 |
| 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) | 0.000 | 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".