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Record W2810745327 · doi:10.1111/apa.14491

Comparison of outcomes between morphine and concomitant morphine and clonidine treatments for neonatal abstinence syndrome

2018· article· en· W2810745327 on OpenAlexafffund
Courtney Gullickson, Stefan Kuhle, Marsha Campbell‐Yeo

Bibliographic record

VenueActa Paediatrica · 2018
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsIzaak Walton Killam Health CentreDalhousie University
FundersDalhousie Medical Research Foundation
KeywordsMedicineClonidineMorphineMethadoneIncidence (geometry)Abstinence SyndromeAbstinenceAnesthesiaRetrospective cohort studyOpioidRegimenConcomitantPopulationInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

AIM: To examine whether adding clonidine to the morphine regimen for treatment of neonatal abstinence syndrome (NAS) is associated with a shorter length of treatment compared with morphine alone. METHODS: Using a retrospective cohort design, infants with NAS resulting from opioid exposure delivered between 2006 and 2015 (n = 174) were identified using the Nova Scotia Atlee Perinatal Database (NSAPD). Maternal and infant characteristics were collected from the NSAPD. The database was augmented with chart review for treatment information. RESULTS: The incidence of NAS in the study population increased fivefold from 1.48/1000 live births in 2007 to 7.50/1000 live births in 2015. Of the 174 infants, 22 were treated with morphine and 100 were treated with morphine + clonidine. Longer length of treatment (p = 0.004) and higher peak morphine dose (p = 0.045) were observed in the combination group. CONCLUSION: The increase in the incidence of NAS is consistent with recent published reports. The increase in length of treatment and peak morphine dose in the morphine + clonidine group is in marked contrast to previous work on this treatment combination. Further study on the impact of clinical characteristics such as methadone and antidepressant exposure on the association is warranted.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.889

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.325
Teacher spread0.299 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations7
Published2018
Admission routes2
Has abstractyes

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