High potassium level during pregnancy is associated with future cardiovascular morbidity
Bibliographic record
Abstract
OBJECTIVE: The present study was aimed to determine whether high potassium level during pregnancy is an independent risk factor for future atherosclerotic morbidity. PATIENTS AND METHODS: A case-control study was conducted including women who delivered between the years 2000-2012 and subsequently developed atherosclerotic morbidity after their last delivery (n = 653) and matched controls (n = 4101). The mean follow-up duration was 57.7 ± 36.5 and 78.5 ± 42.3 months, respectively. The cases were further divided into: major events (severe atherosclerotic morbidity; n = 363), minor events (i.e. cardiovascular risk factors; n = 201) and cardiovascular evaluation tests (n = 89). The Cox proportional hazards models were used to estimate the adjusted hazard ratios (HR) for hospitalizations while controlling for confounders. RESULTS: A Cox proportional hazard model, controlling for confounders such as gestational hypertension, gestational diabetes mellitus, obesity, maternal age, creatinine level and gestational week at index pregnancy showed that K(+ )≥ 5.0 mEq/L during pregnancy was significantly associated with hospitalizations due to severe atherosclerotic morbidity (adjusted HR = 1.55; 95% CI 1.02-2.35; p = 0.039). A non-significant trend was also noted with long-term total hospitalizations for atherosclerotic (adjusted HR = 1.39; 95% CI 0.99-1.94; p = 0.052). CONCLUSION: High potassium level during pregnancy is associated with a significant risk for severe atherosclerotic morbidity, as it might be an indication for occult metabolic and renal dysfunction.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".