Use of wind-up fetal Doppler versus Pinard for fetal heart rate intermittent monitoring in labour: a randomised clinical trial
Bibliographic record
Abstract
OBJECTIVES: In resource-poor settings, the standard of care to inform labour management is the partograph plus Pinard stethoscope for intermittent fetal heart rate (FHR) monitoring. We compared FHR monitoring in labour using a novel, robust wind-up handheld Doppler with the Pinard as a primary screening tool for abnormal FHR on perinatal outcomes. DESIGN: Prospective equally randomised clinical trial. SETTING: The labour and delivery unit of a teaching hospital in Kampala, Uganda. PARTICIPANTS: Of the 2042 eligible antenatal women, 1971 women in active term labour, following uncomplicated pregnancies, were randomised to either the standard of care or not. INTERVENTION: Intermittent FHR monitoring using Doppler. PRIMARY OUTCOME MEASURES: Incidence of FHR abnormality detection, intrapartum stillbirth and neonatal mortality prior to discharge. RESULTS: Age, parity, gestational age, mode of delivery and newborn weight were similar between study groups. In the Doppler group, there was a significantly higher rate of FHR abnormalities detected (incidence rate ratio (IRR)=1.61, 95% CI 1.13 to 2.30). However, in this group, there were also higher though not statistically significant rates of intrapartum stillbirths (IRR=3.94, 0.44 to 35.24) and neonatal deaths (IRR=1.38, 0.44 to 4.34). CONCLUSIONS: Routine monitoring with a handheld Doppler increased the identification of FHR abnormalities in labour; however, our trial did not find evidence that this leads to a decrease in the incidence of intrapartum stillbirth or neonatal death. TRIAL REGISTRATION NUMBER: Clinical Trails.gov (1000031587).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".