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Record W4390619049 · doi:10.3233/npm-230077

The association of cumulative vasoactive drugs and neurodevelopmental outcomes in preterm Infants <29 weeks gestation

2024· article· en· W4390619049 on OpenAlexaff
Reem Amer, Cecilia deCabo, Merhan El-Nagary, Mary Seshia, Yasser Elsayed

Bibliographic record

VenueJournal of Neonatal-Perinatal Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsUniversity of ManitobaMcMaster University
Fundersnot available
KeywordsMedicineBayley Scales of Infant DevelopmentInotropeVasoactivePediatricsGestationGestational ageRetrospective cohort studyAnesthesiaInternal medicineCognitionPregnancyPsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the effect of cardiovascular medications on the neurodevelopment of preterm infants, as measured by calculated cumulative time of vasoactive-inotropic score (VISct). METHODS: A retrospective study was conducted on preterm infants who developed significant hypotension defined as a mean BP more than 2SDs below the mean for GA and received treatment with duration > 6 hours for each hypotensive episode, we calculated the vasoactive inotropic score (VIS) and cumulative exposure to cardiovascular medications over time (VISct). The composite Bayley III was reported from the high-risk follow-up clinic for the surviving infants between 18 to 21 months corrected age. RESULTS: VISct was significantly higher in infants with abnormal neurodevelopment. Cognitive Bayley was the most affected component with median (IQR) VISct 882.5(249,2047) versus 309(143,471) (p-value 0.012), followed by language function with VISct 786(261,1563.5), versus 343(106.75,473.75) (p-value 0.016) when those with Bayley III <85 were compared with those with normal Bayley IIIs. CONCLUSION: High VISct scores may have negative effect on cognitive and language neurodevelopmental outcomes.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.475

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.011
GPT teacher head0.290
Teacher spread0.279 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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