Population-level data on antenatal screening for proteinuria; India, Mozambique, Nigeria, Pakistan
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence and prognosis of proteinuria at enrolment in the 27 intervention clusters of the Community-Level Interventions for Pre-eclampsia cluster randomized trials. METHODS: We identified pregnant women eligible for inclusion in the trials in their communities in four countries (2013-2017). We included women who delivered by trial end and received an intervention antenatal care visit. The intervention was a community health worker providing supplementary hypertension-oriented care, including proteinuria assessment by visual assessment of urinary dipstick at the first visit and all subsequent visits when hypertension was detected. In a multilevel regression model, we compared baseline prevalence of proteinuria (≥ 1+ or ≥ 2+) across countries. We compared the incidence of subsequent complications by baseline proteinuria. FINDINGS: Baseline proteinuria was detected in less than 5% of eligible pregnancies in each country (India: 234/6120; Mozambique: 94/4234; Nigeria: 286/7004; Pakistan: 315/10 885), almost always with normotension (India: 225/234; Mozambique: 93/94; Nigeria: 241/286; Pakistan: 264/315). There was no consistent relationship between baseline proteinuria (either ≥ 1+ or ≥ 2+) and progression to hypertension, maternal mortality or morbidity, birth at < 37 weeks, caesarean section delivery or perinatal mortality or morbidity. If proteinuria testing were restricted to women with hypertension, we projected annual cost savings of 153 223 981 United States dollars (US$) in India, US$ 9 055 286 in Mozambique, US$ 53 181 933 in Nigeria and US$ 38 828 746 in Pakistan. CONCLUSION: Our findings question the recommendations to routinely evaluate proteinuria at first assessment in pregnancy. Restricting proteinuria testing to pregnant women with hypertension has the potential to save resources.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".