Proportion of foetal and placental implantation abnormalities in Madagascar: A cross-sectional study of 35,919 women at public-sector primary healthcare facilities in central and southern Madagascar, 2017–2020
Bibliographic record
Abstract
BACKGROUND: Like other countries in sub-Saharan Africa, Madagascar has a high burden of maternal and neonatal mortality. However, as the proportion of foetal and placental abnormalities among the Malagasy population is unknown, strategies aimed at reducing maternal and neonatal mortality are challenging to define and implement. METHODS: We conducted a multi-year, cross-sectional study using secondary NGO data on obstetric ultrasound, including patient records of all pregnant women who received an obstetric ultrasound screening between July 1st, 2017, and September 30th, 2020, at 62 public-sector primary care facilities in urban and rural regions of Madagascar. We analysed demographic characteristics and determined the prevalence of foetal and placental abnormalities. RESULTS: The dataset included 38,688 ultrasound screening reports from 35,919 women, where 2,587/35,919 (7.20%) women had more than one ultrasound exam. Most women (68.63%, 26,550/38,688) received their first ultrasound during the third trimester of pregnancy. Foetal malpresentation at 36 weeks of gestation or later was diagnosed in 5.48% (176/3,211) of women with the breech presentation being most common (breech 3.99%, 128/3,211; transverse 0.84%, 27/3,211; mobile 0.5%, 16/3,211; oblique 0.16%, 5/3,211). Placenta previa was found in 2.31% (875/38,755) and multiple gestations in 1.03% (370/35,919) cases. Around one in every 150 women (0.66%, 234/38,702) had amniotic fluid disorders. CONCLUSION: The proportion of foetal and placental abnormalities detected by obstetric ultrasound is consistent with findings from other countries in sub-Saharan Africa. In contrast to current WHO recommendations, pregnant women, particularly those from rural, resource-constrained settings attend obstetric ultrasound screenings most commonly during their third trimester of pregnancy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".