Characteristics of breastfeeding newborns in the first month of life with in utero selective serotonin reuptake inhibitor medication exposure: a scoping review protocol
Bibliographic record
Abstract
OBJECTIVE: The objective of this scoping review is to understand the extent and type of evidence in relation to the characteristics of breastfeeding newborns in the first month of life who have been exposed in utero to selective serotonin reuptake inhibitor (SSRI) medications. INTRODUCTION: SSRIs are the most commonly prescribed antidepressant medication in pregnancy. Up to 30% of newborns who are prenatally exposed to SSRIs demonstrate withdrawal signs. Poor neonatal adaptation syndrome represents a constellation of signs observed in these newborns. Little information has been studied regarding breastfeeding, as it relates to the impact of in utero SSRI exposure on the newborn. Parents have many questions regarding the safety of taking medications during pregnancy and breastfeeding. It is important for health care providers to collate evidence-based information and facilitate shared decision-making. We aim to identify the approaches researchers have used to investigate in utero SSRI exposure among breastfed newborns to determine knowledge gaps. INCLUSION CRITERIA: Primary peer-reviewed studies will be considered for inclusion according to the following criteria: newborns, 31 days of age or less, with in utero SSRI exposure in any trimester of pregnancy, who were breastfed or received breast-milk feedings. METHODS: MEDLINE, CINAHL, Embase, LactMed, the Maternity and Infant Care Database, and ClinicalTrials.gov databases will be searched. JBI methodology will be used. Abstracts will be assessed for eligibility and full texts will be retrieved if they meet the inclusion criteria. Two reviewers will independently extract the data from identified studies using a data extraction form and the results will be summarized descriptively and in tabular format. REVIEW REGISTRATION: Open Science Framework osf.io/2bt39.
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 | 0.041 | 0.047 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.015 | 0.013 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.007 | 0.003 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
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".