Maternal factors implicated in fetal bradycardia after combined spinal epidural for labour pain
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Combined spinal epidural analgesia is effective for fast relief of severe labour pain but has been associated with worrisome decreases in fetal heart rate. Since the reasons for this phenomenon remain elusive, some anaesthesiologists may abstain from using this technique. We postulated that factors unrelated to the neuraxial technique could play a role in the decrease in fetal heart rate. To our knowledge, no prospective study has previously looked into this possibility. METHODS: We collected prospective data on 223 consecutive patients who received combined spinal epidural analgesia (123) or epidural analgesia (100). Maternal blood pressure, analogue pain scores, exogenous infusion of oxytocin, cervical dilatation, maternal age, parity and ethnicity were collected and correlated with the occurrence of decreases in fetal heart rate post combined spinal epidural. RESULTS: Univariate analysis showed a correlation between the incidence of fetal bradycardia and higher maternal pain scores, older maternal age, and combined spinal epidural analgesia. Multivariate analysis revealed that only pain scores and maternal age were independent predictors of fetal bradycardia post neuraxial blockade. CONCLUSIONS: Maternal pain scores and older maternal age are factors unrelated to the neuraxial technique that are independent predictors of fetal bradycardia after neuraxial analgesia for labour.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".