Evaluation of Cesarean Delivery Rates across Ontario from 2012 to 2019 Using the Modified Robson Classification System: A Population-Based Study
Bibliographic record
Abstract
Objective This study aimed to describe the trends in cesarean delivery (CD) rates in Ontario using the modified Robson classification system and identify the most common indications for CD. Methods We conducted a population-based retrospective cross-sectional study using data from the Better Outcomes Registry & Network (BORN), a comprehensive maternal-child registry in Ontario. The analysis included all pregnant individuals who delivered a live or stillborn infant weighing ≥500 grams at ≥20 weeks' gestation between 1 April 2012 and 31 March 2019. Results A total of 952 567 pregnant individuals gave birth in Ontario, Canada, during the study period. Our findings demonstrated a slight increase in the overall CD rate over seven fiscal years from 2012-2013 to 2018-2019. Robson Group 5 (term singleton cephalic pregnancy with previous CD), Groups 1 and 2 (nulliparous, term, singleton, cephalic pregnancy and no labour, induced labour, or spontaneous labour), and Group 6 (nulliparous pregnancy with breech presentation) made the largest contributions to the overall CD rate over the study period. The top five primary indications for CD across all years included previous CD, atypical or abnormal fetal surveillance, malposition/malpresentation, non-progressive first stage of labour and non-progressive second stage of labour. Conclusion The results enhance our understanding of the key drivers of the CD rates. These findings will help to inform practice improvement, support policy change, and identify areas where future research is needed.
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 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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".