A quality improvement intervention to optimize the management of severe hypertension during pregnancy and postpartum
Bibliographic record
Abstract
OBJECTIVE: Severe hypertension (two systolic blood pressure [BP] values ≥ 160 mm Hg or diastolic BP values ≥ 110 mm Hg, 15-60 min apart) is a modifiable cause of maternal morbidity and mortality. We aimed to assess the impact of a quality improvement (QI) intervention to optimize the management of severe hypertension during pregnancy and postpartum. STUDY DESIGN: We developed and implemented a QI intervention for severe hypertension management at a Canadian tertiary care center and conducted a quasi-experimental pre- and post-intervention cohort study. Pregnant and postpartum patients with a hypertensive disorder of pregnancy (HDP) between 2020 and 2022 were identified, and pre- and post-intervention cohorts were constructed. MAIN OUTCOME MEASURES: Severe hypertension management was assessed according to quality indicators, including time-to-target BP within 60 min and use of appropriate antihypertensive therapy. RESULTS: Among 697 patients with HDP, 134 (19 %) experienced severe hypertension (pre-intervention: n = 56; post-intervention: n = 78). Immediate release oral nifedipine was the most frequently used medication to treat severe hypertension episodes (63 %). Median time-to-target BP was 49.5 min pre-intervention (interquartile range [IQR] 28.0-69.8) vs. 33.5 min (IQR 19.8-65.2) post-intervention (p = 0.102). Time-to-target BP within 60 min was achieved in 64 % of patients pre- vs. 74 % post-intervention (p = 0.209), meeting our pre-established institutional target. Appropriate antihypertensive administration increased from 55 % pre-intervention to 76 % post-intervention (p = 0.014). CONCLUSION: Developing and implementing a QI intervention resulted in achievement of our institutional target for time-to-severe hypertension resolution and increased use of appropriate antihypertensive medications. Standardized protocols and QI interventions can optimize severe hypertension management to reduce severe maternal morbidity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 | 0.001 |
| 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".