Prenatal treatment for opioid dependency: observations from a large inner-city clinic
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to review changes in the prevalence of opioid use disorder in pregnancy, and to describe the prenatal care and neonatal outcomes following the implementation of buprenorphine treatment at a large US obstetrical clinic during the on-going opioid epidemic. METHODS: We conducted a retrospective cohort study of 310 women (332 pregnancies) with opioid use disorders and their neonates delivered between June 2006 and December 2010 at an obstetrical clinic in the US. Trends in patient volume, characteristics and outcomes by calendar year were assessed using the Cochran-Armitage test and linear regression. RESULTS: There was an almost two-fold increase in the volume of pregnant women treated annually from 2006 through 2010. Most women were treated with methadone (74%), with buprenorphine becoming more common over calendar time: 3.0% in 2006 to 41% in 2010. The mean dose of buprenorphine at delivery was: 11.4 mg in 2007, 14.1 mg in 2008, 14.1 mg in 2009, and 16.8 mg in 2010; an average increase of 2.1 mg year. There were no differences in mean methadone dose over time. From 2006 to 2010 there were increases in the prevalence of prescribed concomitant psychotropic medications and vaginal deliveries, and in the proportion of neonates treated pharmacologically for neonatal abstinence syndrome (NAS). NAS pharmacologic management also varied by calendar year with more use of neonatal morphine and clonidine in later years. CONCLUSIONS: The number of mother-infant pairs increased significantly from 2006 to 2010 and the clinical characteristics of these patients changed over time. Our experience reflects the rising increase in opioid use disorders in pregnancy and NAS, mandating the need for expansion of comprehensive prenatal care options for these women and their children.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".