Maternal cardiac function during pregnancy at high altitude
Bibliographic record
Abstract
OBJECTIVE: To investigate the maternal cardiovascular adaptation in pregnancy at high altitude, compared with that at sea level. DESIGN: Cross sectional study. SETTING: Two maternity units providing routine antenatal care: one at 4370 m above sea level (Cerro de Pasco, Peru) and one at sea level (Lima, Peru). POPULATION: We examined 175 pregnant women at 5-41 weeks of gestation and 16 non-pregnant controls resident at high altitude and 132 pregnant women and 18 non-pregnant controls at sea level. METHODS: Two-dimensional and M-mode echocardiography of the left ventricle. MAIN OUTCOME MEASURES: Maternal cardiac output and left ventricular longitudinal and transverse systolic function indices. RESULTS: Pregnancy at high altitude, compared with sea level, is associated with 11% lower birthweight and 31% lower maternal cardiac output, due to 15% lower stroke volume and 11% lower heart rate. The lower stroke volume was due to a lower preload and impaired longitudinal and transverse left ventricular systolic function. Mean arterial pressure was about 8% lower during pregnancy at high altitude versus sea level. Pregnant women at high altitude failed to expand their intravascular space to the same extent as the sea level group: cardiac output increased by 17%, left atrial diameter by 12% and end-diastolic diameter by 1% at high altitude versus 41%, 25% and 5%, respectively, at sea level. CONCLUSIONS: Pregnancy at high altitude, compared with sea level, is characterised by lower cardiac output due to lower heart rate and lower stroke volume and reduced expansion of the maternal intravascular space compared with the non-pregnant state.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".