The use of loop diuretics in the context of hypertensive disorders of pregnancy: a systematic review and meta-analysis
Bibliographic record
Abstract
AIMS: Addressing volume expansion may improve the management of hypertension across the pregnancy continuum. We conducted a systematic review to summarize the evidence on the use of loop diuretics in the context of hypertensive disorders during pregnancy and the postpartum period. METHODS AND RESULTS: Medline, Embase, Cochrane library, ClinicalTrials.gov, and Google Scholar were searched for original research articles published up to 29 June 2021. Of the 2801 results screened, 15 studies were included: eight randomized controlled trials, six before-after studies, and one cohort study. Based on random effects meta-analysis of before-after studies, antepartum use of loop diuretics was associated with lower DBP [mean difference -17.73 mmHg, (95% confidence intervals -34.50 to -0.96); I2 = 94%] and lower cardiac output [mean difference -0.75 l/min, (-1.11 to -0.39); I2 = 0%], with no difference in SBP, mean arterial pressure, heart rate, or total peripheral resistance. Meta-analysis of randomized controlled trials revealed that postpartum use of loop diuretics was associated with decreased need for additional antihypertensive patients [relative risk 0.69, (0.50-0.97); I2 = 14%], and an increased duration of hospitalization [mean difference 8.80 h, (4.46-13.14); I2 = 83%], with no difference in the need for antihypertensive therapy at hospital discharge, or persistent postpartum hypertension. CONCLUSION: Antepartum use of loop diuretics lowered DBP and cardiac output, while their postpartum use reduced the need for additional antihypertensive medications. There was insufficient evidence to suggest a clear benefit. Future studies focusing on women with hypertensive pregnancy disorders who may most likely benefit from loop diuretics are required.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".