The Incidence and Predictors of Failed Spinal Anesthesia After Intrathecal Injection of Local Anesthetic for Cesarean Delivery: A Single-Center, 9-Year Retrospective Review
Bibliographic record
Abstract
BACKGROUND: The incidence of failed spinal anesthesia varies widely in the obstetric literature. Although many risk factors have been suggested, their relative predictive value is unknown. The primary objective of this retrospective cohort study was to determine the incidence of failed spinal anesthesia for cesarean deliveries at a tertiary care obstetric hospital, and its secondary objectives were to identify predictors of failed spinal anesthesia in the obstetrics population and quantify their relative importance in a predictive model for failure. METHODS: With local institutional ethics committee approval, a retrospective review of our hospital database identified the incidence of failed spinal anesthesia for 5361 cesarean deliveries between 2010 and 2019. We performed a multivariable analysis to assess the association of predictors with failure and a dominance analysis to assess the importance of each predictor. RESULTS: The incidence of failed spinal anesthesia requiring an alternative anesthetic was 2.1%, with conversion to general anesthesia occurring in 0.7% of surgeries. Supplemental analgesia or sedation was provided to an additional 2.0% of women. The most important predictors of a failed spinal anesthetic were previous cesarean delivery (odds ratio [OR], 11.33; 95% confidence interval [CI], 7.09-18.20; P < .001), concomitant tubal ligation (OR, 8.23; 95% CI, 3.12-19.20; P < .001), lower body mass index (BMI) (kg·m -2 , OR, 0.94; 95% CI, 0.90-0.98; P = .005), and longer surgery duration (minutes, OR, 1.02; 95% CI, 1.01-1.03; P = .006). Previous cesarean delivery was the most significant risk factor, contributing to 9.6% of the total 17% variance predicted by all predictors examined. CONCLUSIONS: Spinal anesthesia failed to provide a pain-free surgery in 4.1% of our cesarean deliveries. Previous cesarean delivery was the most important predictor of spinal failure. Other important predictors included tubal ligation, lower BMI, and longer surgery duration.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".