Anesthetic management of patients with class 3 obesity undergoing elective Cesarean delivery: a single-centre historical cohort study
Bibliographic record
Abstract
The preferred neuraxial anesthetic technique for patients with class 3 obesity undergoing elective Cesarean delivery is still under debate. We aimed to describe the anesthetic technique used in our tertiary institution across body mass index (BMI) groups and different surgical incisions. In this historical cohort study, we reviewed medical records of patients with a BMI ≥ 40 kg·m –2 undergoing elective Cesarean delivery between July 2014 and December 2020. We collected data on patient characteristics, anesthetic and surgical technique, and procedural times. For data analysis, we stratified patients by BMI into three different groups: 40.0–49.9 kg·m –2 , 50.0–59.9 kg·m –2 , and ≥ 60.0 kg·m –2 . We included 396 deliveries, distributed as follows: 258 with a BMI 40.0–49.9 kg·m –2 , 112 with a BMI 50.0–59.9 kg·m –2 , and 26 with a BMI ≥ 60.0 kg·m –2 . For patients with a BMI 40.0–49.9 kg·m –2 , the anesthetic technique of first choice was predominantly spinal anesthesia (71%), whereas for those with a BMI ≥ 60.0 kg·m –2 , spinal anesthesia was never used as the anesthetic of first choice. With regard to the surgical incision, spinal anesthesia was almost exclusively used for patients undergoing Pfannenstiel incision and was rarely used for a higher supra- or infraumbilical transverse or midline incision. The overall incidence of general anesthesia was low (7/396, 1.8%). Anesthetic time, surgical time, and operating room time increased almost twofold in patients with a BMI ≥ 60.0 kg·m –2 compared with those with a BMI of 40.0–49.9 kg·m –2 . Neuraxial anesthesia was successfully used in approximately 98% of patients with class 3 obesity undergoing elective Cesarean delivery. The choice of regional anesthesia technique varied with increasing BMI and with the planned surgical incision. Procedural times increased with increasing BMI. This information should prove useful for comparing anesthetic choices and outcomes in this challenging population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".