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Record W3010659542 · doi:10.1186/s13063-020-4183-9

Outcome reporting in neonates experiencing withdrawal following opioid exposure in pregnancy: a systematic review

2020· review· en· W3010659542 on OpenAlexafffund
Flora Shan, Sonya MacVicar, Karel Allegaert, Martin Offringa, Lauren M. Jansson, Sarah Simpson, Wendy Moulsdale, Lauren E. Kelly

Bibliographic record

VenueTrials · 2020
Typereview
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsHealth Sciences CentreSt. Joseph’s Healthcare HamiltonGeorge & Fay Yee Centre for Healthcare InnovationUniversity of TorontoSunnybrook Health Science CentreInstitute for Clinical Evaluative SciencesUniversity of Manitoba
FundersUniversity of Manitoba
KeywordsMedicineRandomized controlled trialObservational studyAbstinencePsychological interventionMEDLINEClinical trialPediatricsIntensive care medicinePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Neonatal withdrawal secondary to in utero opioid exposure is a growing global concern stressing the psychosocial well-being of affected families and scarce hospital resources. In the ongoing search for the most effective treatment, randomized controlled trials are indispensable. Consistent outcome selection and measurement across randomized controlled trials enables synthesis of results, fostering the translation of research into practice. Currently, there is no core outcome set to standardize outcome selection, definition and reporting. This study identifies the outcomes currently reported in the literature for neonates experiencing withdrawal following opioid exposure during pregnancy. METHODS: A comprehensive literature search of MEDLINE, EMBASE and Cochrane Central was conducted to identify all primary research studies (randomized controlled trials, clinical trials, case-controlled studies, uncontrolled trials, observational cohort studies, clinical practice guidelines and case reports) reporting outcomes for interventions used to manage neonatal abstinence syndrome between July 2007 and July 2017. All "primary" and "secondary" neonatal outcomes were extracted by two independent reviewers and were assigned to one of OMERACT's core areas of "pathophysiological manifestation", "life impact", "resource use", "adverse events", or "death". RESULTS: Forty-seven primary research articles reporting 107 "primary" and 127 "secondary" outcomes were included. The most frequently reported outcomes were "duration of pharmacotherapy" (68% of studies, N = 32), "duration of hospital stay" (66% of studies, N = 31) and "withdrawal symptoms" (51% of studies, N = 24). The discrepancy between the number of times an outcome was reported and the number of articles was secondary to the use of composite outcomes. Frequently reported outcomes had heterogeneous definitions or were not defined by the study and were measured at different times. Outcomes reported in the literature to date were mainly assigned to the core areas "pathophysiologic manifestations" or "resource use". No articles reported included parent or former patient involvement in outcome selections. CONCLUSIONS: Inconsistent selection and definition of primary and secondary outcomes exists in the present literature of pharmacologic and nonpharmacologic interventions for managing opioid withdrawal in neonates. No studies involved parents in the process of outcome selection. These findings hinder evidence synthesis to generate clinically meaningful practice guidelines. The development of a specific core outcome set is imperative.

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 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)0.025
metaresearch head score (Gemma)0.133
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.133
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0080.009
Bibliometrics0.0150.016
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0030.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.153
GPT teacher head0.435
Teacher spread0.282 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations14
Published2020
Admission routes2
Has abstractyes

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