MétaCan
Menu
Back to cohort
Record W2107717472 · doi:10.1136/ebmed-2012-100777

Oxycodone administered as postpartum pain relief is associated with maternal report of infant central nervous system depression in breastfed infants

2012· letter· en· W2107717472 on OpenAlexaff
Wibke Jonas

Bibliographic record

VenueEvidence-Based Medicine · 2012
Typeletter
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineBreastfeedingOxycodoneBreast milkCodeinePostpartum depressionPediatricsAnesthesiaMorphineInternal medicineOpioidPregnancyChemistry

Abstract

fetched live from OpenAlex

Commentary on: Lam J, Kelly L, Ciszkowski C, et al. Central nervous system depression of neonates breastfed by mothers receiving oxycodone for postpartum analgesia. J Pediatr 2012; 160: 33– 7.e2.[OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] Despite our knowledge that codeine is excreted in breast milk, administration of codeine as a pain relief to breastfeeding mothers during the early postpartum period was considered safe until a healthy newborn died.1 The mother was an ultra-rapid metaboliser of codeine and thus, produced effectively the metabolite morphine. As a consequence, the guidelines for codeine use during breastfeeding were changed to include more caution about the possible central nervous system (CNS) depression effects on the neonate.2 As a result, many clinicians started to prescribe oxycodone, a semisynthetic opioid, instead. Little is known about the excretion of oxycodone into breast milk and the safety for newborns to mothers taking oxycodone while breastfeeding. Lam et al … [1]: {openurl}?query=rft.jtitle%253DThe%2BJournal%2Bof%2Bpediatrics%26rft.stitle%253DJ%2BPediatr%26rft.aulast%253DLam%26rft.auinit1%253DJ.%26rft.volume%253D160%26rft.issue%253D1%26rft.spage%253D33%26rft.epage%253D7.e2%26rft.atitle%253DCentral%2Bnervous%2Bsystem%2Bdepression%2Bof%2Bneonates%2Bbreastfed%2Bby%2Bmothers%2Breceiving%2Boxycodone%2Bfor%2Bpostpartum%2Banalgesia.%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.jpeds.2011.06.050%26rft_id%253Dinfo%253Apmid%252F21880331%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/j.jpeds.2011.06.050&link_type=DOI [3]: /lookup/external-ref?access_num=21880331&link_type=MED&atom=%2Febmed%2F18%2F1%2F40.atom [4]: /lookup/external-ref?access_num=000298143000011&link_type=ISI

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0070.002

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.

Opus teacher head0.033
GPT teacher head0.296
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
Domainnot available
GenreEmpirical · Commentary

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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueEvidence-Based MedicineSame topicMaternal Mental Health During Pregnancy and PostpartumFrench-language works237,207