Magnesium sulfate for eclampsia prevention: Quality of care evaluation in a tertiary centre in Québec, Canada
Bibliographic record
Abstract
BACKGROUND: The current Canadian guidelines endorse the use of MgSO4 for treatment of eclampsia and for prophylaxis in severe preeclampsia. Our study aimed to audit our institution's compliance regarding these guidelines. METHODS: We conducted a retrospective study to evaluate MgSO4 use in: all our cases of eclampsia since 2002, 50 cases of severe preeclampsia, and 50 cases of non-severe preeclampsia. RESULTS: Sixty-five cases of preeclampsia were analyzed after initial chart review. A high rate of preeclampsia severity misdiagnosis was observed (35%, 23/65). Only 69% (25/36) of the patients correctly diagnosed with severe preeclampsia received MgSO4; after diagnosis correction, 42% (25/59) of the patients with severe preeclampsia received the medication. Of our eight cases of eclampsia, none of the patients received MgSO4 before the seizure (although three had clear indications). CONCLUSION: Given the importance of prophylactic MgSO4 use in preventing eclampsia, we have implemented informative measures aimed at rapidly achieving complete compliance with the national guidelines.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".