Pulse wave analysis: a preliminary study of a novel technique for the prediction of pre‐eclampsia
Bibliographic record
Abstract
OBJECTIVE: To investigate whether first-trimester arterial pulse wave analysis (PWA) can predict pre-eclampsia. DESIGN: This was a prospective screening study. SETTING: The Homerton University Hospital, a London teaching hospital. POPULATION: Two hundred and ten low-risk women with a singleton pregnancy were analysed. METHODS: Radial artery pulse waveforms were measured between the 11(+0) and 13(+6) weeks of gestation and the aortic waveform derived by applying a generalised transfer function. Augmentation pressure (AP) and augmentation index at heart rate of 75 beats per minute (AIx-75), measures of arterial stiffness, were calculated. The multiple of the gestation-specific median in controls for AP and AIx-75 were calculated. Logistic regression models were developed and their predictive ability assessed using the area under the receiver operator curve. MAIN OUTCOME MEASURES: Prediction of pre-eclampsia by AIx-75. RESULTS: Fourteen (6.7%) women developed pre-eclampsia, and 196 remained normotensive. Eight of the 14 women developed pre-eclampsia before 34 weeks of gestation (early-onset pre-eclampsia). For a false-positive rate of 11%, AIx-75 had a detection rate of 79% for all cases of pre-eclampsia and 88% for early-onset pre-eclampsia. CONCLUSION: First-trimester arterial PWA can play a significant role in understanding the pathophysiology of pre-eclampsia and may play a role in early screening.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".