Bibliographic record
Abstract
This review reflects both the variable presentation and the systemic nature of preeclampsia. Recommendations for the comprehensive evaluation and management of organ dysfunction associated with pre-eclampsia are included. The main points in the review are that: (1) Preeclampsia is a systemic disorder that may affect many organ systems. (2) For preeclampsia remote from term (<34 weeks), expectant management improves perinatal outcomes, but requires obsessive surveillance to mitigate maternal risks and is a "package." (3) Initial assessment and ongoing surveillance of women with preeclampsia should include assessment of all vulnerable maternal organs as well as of the fetus. (4) Initiate antihypertensive drug treatment immediately if sBP >160 mmHg or dBP more than 110 mmHg, or if sBP 140-159 mmHg and/or dBP 85-109 mmHg (prepregnancy renal disease or diabetes). (5) The treatment of nonsevere pregnancy hypertension should include a treatment goal of dBP 80-105 mmHg (depending on practitioner preference), with one of the following agents, Methyldopa, Labetalol, Nifedipine, or, with special indications (renal or cardiac diseases), diuretics. (6) Drugs to avoid: angiotensin-converting enzyme inhibitors; angiotensin II receptor antagonists; and atenolol. (7) For the acute management of severe hypertension, initially reduce dBP by 10 mmHg and maintain the blood pressure at or below that level with either Nifedipine or Labetalol. (8) For both prophylaxis against and treatment of eclampsia, MgSO4 (4 g IV stat, then 1 g/hr). (9) For recurrent seizures, MgSO4 (2g IV stat, then increase to 1.5 g/hr). (10) Total fluid intake should not exceed 80 ml/hr; tolerate urine outputs as low as 10 ml/hr. (11) Early-onset and/or severe preeclampsia predict later cardiovascular morbidity and mortality; it would seem prudent to offer such women screening and lipid lowering interventions.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".