Spinal anesthesia for cesarean section in a super morbidly obese parturient
Bibliographic record
Abstract
INTRODUCTION: The population of obese individuals is increasing worldwide, and as a result, the number of mothers with super morbid obesity undergoing cesarean sections is also increasing. However, little is known about which anesthetic technique is appropriate for cesarean sections of super morbidly obese parturients. PATIENT CONCERNS: A 35-year-old woman with body mass index 61.3 kg/m at a gestational age of 37 weeks. DIAGNOSIS: The patient was super morbidly obese parturient. INTERVENTIONS: Spinal anesthesia was performed. A spinal needle was inserted into the L4-5 interspinous space in the sitting position. After confirmation of cerebrospinal fluid, 0.5% hyperbaric bupivacaine 9 mg and fentanyl 20 μg were injected into the subarachnoid space. OUTCOMES: After the administration of spinal anesthetics, the nerve block to the T8 dermatome level was confirmed, surgery was performed, and the fetus was delivered. The patient's vital signs were stable until the end of the operation. CONCLUSION: There is no established strategy for selecting a method of anesthesia in patients with morbid obesity (body mass index 40 kg/m or more). For this reason and considering the amount of bupivacaine used for spinal anesthesia, we wanted to share our experience with spinal anesthesia for cesarean section in a super morbidly obese parturients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".