Associations Between Modifiable Preconception Care Indicators and Pregnancy Outcomes
Bibliographic record
Abstract
PURPOSE: This study explored gaps and opportunities in preconception care with a focus on determining whether modifiable preconception care indicators are associated with preterm births. METHODS: This retrospective case-control study explored prepregnancy data of patients ≥18 years old who delivered preterm (cases) versus full term (controls) between June 1, 2018, and May 31, 2019, at a health care network in Pennsylvania. Cases were matched 1:2 with controls based on age, parity, and history of preterm delivery. A literature review yielded 11 key indicators of quality preconception care. Documentation of counseling on these indicators were extracted from patient charts from their most recent primary care visit before pregnancy (preconception care) and their pregnancy intake visit (prenatal care). Bivariate analyses were used to assess whether any of the 11 preconception indicators were associated with preterm birth. All analyses were conducted using SPSS statistical software. RESULTS: Our sample included 663 patient charts: 221 preterm births and 442 term births. Elevated blood pressure (>120/80) in the preconception period (Odds Ratio [OR] = 1.84) and at the prenatal intake visit (OR = 1.68) was significantly associated with preterm birth. In addition, patients with Body Mass Index (BMI) ≤18 or ≥30 at their prenatal visit were nearly twice as likely (OR = 1.85) to have pregnancies resulting in preterm birth. CONCLUSIONS: Our study highlights BMI and Blood Pressure (BP) as key focus points for preconception counseling. Additional studies are needed to determine whether pregnancy outcomes other than preterm birth may be influenced by these and other preconception care indicators.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".