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Abstract 15672: Cerebral and Renal Saturation Trendings in Neonates With Congenital Heart Disease in the Pre-Intervention Period: A Prospective Study

2023· article· en· W4389957756 on OpenAlexaff
Carolina Lara Michel, Marina Mir, S. Moore, Punnanee Wutthigate, Jessica Simoneau, Daniela Villegas Martinez, Sam D. Shemie, Marie Brossard‐Racine, Adrian Dancea, Gianluca Bertolizio, Gabriel Altit

Bibliographic record

VenueCirculation · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsMedicineProspective cohort studyCardiologyInternal medicineDiastoleAnesthesiaBlood pressure

Abstract

fetched live from OpenAlex

Introduction: Limited data exists on the trends of cerebral (CSat) and renal (RSat) saturations measured by near infrared spectroscopy (NIRS) of neonates with a congenital heart defect (CHD) during the first days of life in the pre-interventional setting. Hypothesis: We hypothesized that retrograde aortic flow in aorta as an indicator of diastolic steal would be associated with adverse CSat/Rsat profiles. Methods: We conducted a single-center prospective study recruiting newborns with CHD. CSat/ RSat were monitored until day 7 and averaged every hour. Daily echocardiograms were performed. Presence/ absence of holodiastolic retrograde flow in post-ductal aorta was assessed by an expert blinded to NIRS measurements and clinical status. Random mixed effect models were constructed to evaluate the association between NIRS trends and retrograde flow. Results: We included 49 newborns, of which 27 (55%) had retrograde flow. CSat remained stable throughout the monitoring period in the non-retrograde group, while it progressively declined in those with retrograde flow. An association was found between retrograde flow and negative trends CSat (β= -9.1%, 95%CI [-14.3 — -3.8]) and RSat (β= -8.4%, 95%CI [-14.5— -2.3]). Conclusions: In infants with CHD, retrograde flow in the descending aorta was associated with a CSat/RSat decline within the first week of life. Future studies should evaluate whether normalization of these parameters decreases the burden of neurological injury.

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)0.002
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.288
Teacher spread0.269 · 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 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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