Advanced Maternal Age and Perinatal and Obstetrical Outcomes – A Population-Based Study [37C]
Bibliographic record
Abstract
INTRODUCTION: Our objectives are to update the existing literature on the association between advanced maternal age (AMA) and adverse obstetrical and perinatal outcomes and to determine the effect of parity on this association. METHODS: A retrospective cohort study was conducted using the Alberta Perinatal Health Program database including all singleton births without congenital or chromosomal anomalies at greater than 20 weeks gestation from 1998-2013. Maternal age was categorized as less than 20, 20-24, 25-30, 31-34, 35-40, and greater than 40 years. Outcomes were grouped by obstetrical and perinatal. Multinomial logistic regression models were constructed controlling for various confounders. RESULTS: 105,067 of 690,471 total births (15.2%) were in women 35 years or greater. Compared with those 20-24, women 35-40 have increased risk of various adverse obstetrical outcomes including pre-existing hypertension or diabetes (aOR 3.40 95%CI 3.09-3.74), gestational diabetes (aOR 5.01 95%CI 4.69-5.36), preeclampsia (aOR 1.28 95%CI 1.14-1.43). Controlling for additional relevant obstetrical complications, they have increased risk of adverse perinatal outcomes including preterm birth (aOR 1.33 95%CI 1.26-1.39), low birth weight (LBW) (aOR 1.29 95%CI 1.21-1.38), and low Apgar score at 5 minutes (aOR 1.17 95%CI 1.08-1.26). Women under 20 and over 40 also have increased risk of perinatal mortality (aOR 1.35 and 1.36 95%CI 1.12-1.64 and 1.01-1.82). Compared to multiparas, primiparas have greater risk of adverse outcomes including preeclampsia, preterm birth, LBW, low Apgar score at 5 minutes and NICU admission (P<.05). CONCLUSION: AMA is independently associated with various pregnancy complications while primiparas have greater risk of these complications.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".