An Australian and Aotearoa New Zealand Audit of Obstetric Fluid Management During Induction of Labor
Bibliographic record
Abstract
Background: Although guidelines are in place for obstetric indications that warrant an induction of labor, no such guidelines or policies exist for the management of fluids during labor. This extends to the concentration of oxytocin used for induction, maintenance rate of intravenous crystalloids and subsequent boluses of this crystalloid. The aim of this survey was to obtain a snapshot of current Australian and Aotearoa New Zealand obstetric practice as it pertains to fluid management during induction of labor. Methods: A REDCap survey was made available to medical practitioners registered with the Australian and New Zealand College of Obstetricians and Gynecologists (RANZCOG) via email. Results: A total of 287/6,707 (4.3%) medical practitioners registered with RANZCOG completed the survey. A response was received from medical practitioners in all states and territories of Australia and Aotearoa New Zealand, from a total of 140 hospitals. The majority of respondents were consultants (178/287 (62%)). Variability was noted for the concentration of oxytocin that was used. Three different types of crystalloid were used. Marked variability was noted for the rate of infusion of crystalloid, the indications for a bolus of crystalloid and the size of this bolus. Conclusions: The management of fluid during induction of labor has marked variability both in Australia and Aotearoa New Zealand, suggesting that a policy to guide this management does not exist, and best practice has not been identified. J Clin Gynecol Obstet. 2023;12(3):71-77 doi: https://doi.org/10.14740/jcgo924
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".