Prevention of hypotension after spinal anaesthesia for caesarean section: a systematic review and network meta‐analysis of randomised controlled trials
Bibliographic record
Abstract
Spinal anaesthesia for caesarean section commonly causes maternal hypotension. This systematic review and network meta-analysis compared methods to prevent hypotension in women receiving spinal anaesthesia for caesarean section. We selected randomised controlled trials that compared an intervention to prevent hypotension with another intervention or inactive control by searching MEDLINE and Embase, Web of Science to December 2018. There was no language restriction. Two reviewers extracted data on trial characteristics, methods and outcomes. We assessed risk of bias for individual trials (Cochrane tool) and quality of evidence (GRADE checklist). We assessed 109 trials (8561 women) and 12 different methods that resulted in 30 direct comparisons. Methods ranked by OR (95%CI) from most effective to least effective were: metaraminol 0.11 (0.04-0.26); norepinephrine 0.13 (0.06-0.28); phenylephrine 0.18 (0.11-0.29); leg compression 0.25 (0.14-0.43); ephedrine 0.28 (0.18-0.43); colloid given before induction of anaesthesia 0.38 (0.24-0.61); angiotensin 2, 0.12 (0.02-0.75); colloid given after induction of anaesthesia 0.52 (0.30-0.90); mephentermine 0.09 (0.01-1.30); crystalloid given after induction of anaesthesia 0.78 (0.46-1.31); and crystalloid given before induction of anaesthesia 1.16 (0.76-1.79). Phenylephrine caused maternal bradycardia compared with control, OR (95%CI) 0.23 (0.07-0.79). Ephedrine lowered umbilical artery pH more than phenylephrine, standardised mean difference (95%CI) 0.78 (0.47-1.49). We conclude that vasopressors should be given to healthy women to prevent hypotension during caesarean section with spinal anaesthesia.
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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 | 0.021 | 0.055 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.040 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".