Timing of delivery in a high-risk obstetric population: a clinical prediction model
Bibliographic record
Abstract
BACKGROUND: The efficacy of antenatal corticosteroid treatment for women with threatened preterm birth depends on timely administration within 7 days before delivery. We modelled the probability of delivery within 7 days of admission to hospital among women presenting with threatened preterm birth, using routinely collected clinical characteristics. METHODS: Data from the Canadian Perinatal Network (CPN) were used, 2005-11, including women admitted to hospital with preterm labour, preterm pre-labour rupture of membranes, short cervix without contractions, or dilated cervix or prolapsed membranes without contractions at preterm gestation. Women with fetal anomaly, intrauterine fetal demise, twin-to-twin transfusion syndrome, and quadruplets were excluded. Logistic regression was undertaken to create a predictive model that was assessed for its calibration capacity, stratification ability, and classification accuracy (ROC curve). RESULTS: We included 3012 women admitted at 24-28 weeks gestation, or readmitted at up to 34 weeks gestation, to 16 tertiary-care CPN hospitals. Of these, 1473 (48.9%) delivered within 7 days of admission. Significant predictors of early delivery included maternal age, parity, gestational age at admission, smoking, preterm labour, prolapsed membranes, preterm pre-labour rupture of membranes, and antepartum haemorrhage. The area under the ROC curve was 0.724 (95% CI 0.706-0.742). CONCLUSION: We propose a useful tool to improve prediction of delivery within 7 days after admission among women with threatened preterm birth. This information is important for optimal corticosteroid treatment.
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) | 0.000 | 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".