Comparison between near miss criteria in a maternal intensive care unit
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare the incidence of different criteria of maternal near miss in women admitted to an obstetric intensive care unit and their sensitivity and specificity in identifying cases that have evolved to morbidity. METHOD: A cross-sectional analytical epidemiological study was conducted with women admitted to the intensive care unit of the Maternity School Assis Chateaubriand in Ceará, Brazil. The Chi-square test and odds ratio were used. RESULTS: 560 records were analyzed. The incidence of maternal near miss ranged from 20.7 in the Waterstone criteria to 12.4 in the Geller criteria. The maternal near-miss mortality ratio varied from 4.6:1 to 7.1:1, showing better index in the Waterstone criteria, which encompasses a greater spectrum of severity. The Geller and Mantel criteria, however, presented high sensitivity and low specificity. Except for the Waterstone criteria, there was an association between the three other criteria and maternal death. CONCLUSION: The high specificity of Geller and Mantel criteria in identifying maternal near miss considering the World Health Organization criteria as a gold standard and a lack of association between the criteria of Waterstone with maternal death.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".