Hemodynamic Assessment of Pregnant People with and without Obesity by Noninvasive Bioreactance: A Pilot Study
Bibliographic record
Abstract
Abstract Objective This study aimed to identify cardiovascular differences between pregnant people with and without obesity for trimester-specific changes in hemodynamic parameters using noninvasive cardiac output monitoring (NICOM). Study Design This study is a pilot prospective comparative cohort between pregnant people with and without obesity. Hemodynamic assessment was performed with NICOM (12–14, 21–23, and 34–36 weeks) during pregnancy. Results In first trimester, pregnant people with obesity had higher blood pressure, stroke volume (SV), total peripheral resistance index (TPRI), and cardiac output (CO). Pregnant people with obesity continued to have higher SV and cardiac index (second and third trimesters). During the first trimester, body mass index (BMI) positively correlated with SV, TPRI, and CO. Fat mass showed a strong correlation with TPRI. BMI positively correlated with CO during the second trimester and fat mass was positively associated with CO. During the third trimester, TPR negatively correlated with BMI and fat mass. Conclusion Fat mass gain in the period between the first and second trimesters in addition to the hemodynamic changes due to obesity and pregnancy contribute to some degree of left ventricular diastolic dysfunction which was manifested by lower SVs. Future work should investigate the possible causative role of obesity in the cardiovascular changes identified in people with obesity.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".