Critical pathways for the management of preeclampsia and severe preeclampsia in institutionalised health care settings
Bibliographic record
Abstract
BACKGROUND: Preeclampsia is a complex disease in which several providers should interact continuously and in a coordinated manner to provide proper health care. However, standardizing criteria to treat patients with preeclampsia is problematical and severe flaws have been observed in the management of the disease. This paper describes a set of critical pathways (CPs) designed to provide uniform criteria for clinical decision-making at different levels of care of pregnant patients with preeclampsia or severe preeclampsia. METHODS: Clinicians and researchers from different countries participated in the construction of the CPs. The CPs were developed using the following steps: a) Definition of the conceptual framework; b) Identification of potential users: primary care physicians and maternal and child health nurses in ambulatory settings; ob/gyn and intensive care physicians in secondary and tertiary care levels. c) Structural development. RESULTS: The CPs address the following care processes: 1. Screening for preeclampsia, risk assessment and classification according to the level of risk. 2. Management of preeclampsia at primary care clinics. 3. Evaluation and management of preeclampsia at secondary and tertiary care hospitals: 4. Criteria for clinical decision-making between conservative management and expedited delivery of patients with severe preeclampsia. CONCLUSION: Since preeclampsia continues to be one of the primary causes of maternal deaths and morbidity worldwide, the expected impact of these CPs is the contribution to improving health care quality in both developed and developing countries. The CPs are designed to be applied in a complex health care system, where different physicians and health providers at different levels of care should interact continuously and in a coordinated manner to provide care to all preeclamptic women. Although the CPs were developed using evidence-based criteria, they could require careful evaluation and remodelling according to each system's demands. Additionally, the CPs need to be tested in large-scale, multi-level studies in order to thoroughly examine and evaluate their efficacy and effectiveness.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".