Timely Assessment of Cardiovascular Risk after Preeclampsia
Bibliographic record
Abstract
Evaluation of: Cusimano MC, Pudwell J, Roddy M, Chan-Kyung JC, Smith GN. The maternal health clinic: an initiative for cardiovascular identification in women with pregnancy-related complications. Am. J. Obstet. Gynecol. 438, e1 (2014). Cardiovascular risk management, for men and women alike, is a preventative means to detect individuals' running an elevated risk of myocardial disorders, stroke and metabolic syndrome. Because age is an important factor in the risk assessment, especially young women almost always are classified in the low-risk category and therefore do not qualify for preventive treatment. A history of preeclampsia identifies women who have underlying cardiovascular risk factors. Approximately 6-8% of all pregnancies are complicated by hypertensive disorders, about 2% ends in preeclampsia. For that very reason, the Maternal Health Clinic at Kingston General Hospital in Kingston, Canada, was established to provide postpartum cardiovascular risk counseling or follow-up for women with the pregnancy-related complications. The outcomes were significant: 17% of the young target population with an average age of 33 years met criteria of metabolic syndrome and 85% revealed elevated lifetime cardiovascular disease risk. These figures are to be compared with control results of women with uncomplicated pregnancies: 7% metabolic syndrome and 46% non-optimal risk. It is concluded that the clinic may serve as a prolific and effective primary prevention strategy.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".