MétaCan
Menu
Back to cohort
Record W4413924751 · doi:10.1101/2025.09.01.25334829

Investigating brain haemodynamics during hypoglycaemia in very preterm neonates using diffuse optical tomography

2025· preprint· en· W4413924751 on OpenAlexaff
Guy A. Perkins, Silvia Guiducci, Giulia Res, Federica Savio, Daniele Trevisanuto, Elena Priante, Eugenio Baraldi, Alfonso Galderisi, Sabrina Brigadoi

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsChildren's & Women's Health Centre of British Columbia
FundersMinistero della Salute
KeywordsHemodynamicsDiffuse optical imagingMedicineCardiologyInternal medicineTomographyRadiology

Abstract

fetched live from OpenAlex

Very preterm neonates are more prone to experience hyper and hypo-glycaemia after birth. To date, there is no available evidence on the local brain hemodynamic response to these glycemic changes. This study uses continuous glucose monitoring (CGM) and diffuse optical tomography (DOT) to investigate this issue. Sixty very preterm neonates were recruited and continuously monitored after birth with CGM and DOT for several days. Patients with only mild (Sensor glucose concentration (SGC) ≥ 48 mg/dL & ≤ 72 mg/dL) or severe (SGC ≤ 47 mg/dL) hypoglycaemia (N=17) were then selected for analysis. DOT data were reconstructed in three 10-minute windows throughout each hypoglycemic event: at the beginning of the event, after the minimum of hypoglycemia, and at the end of the event. Correlations and spatial consistencies were found between changes in blood volume and SGC during these time windows, suggesting a coupling between SGC and brain hemodynamics in very preterm newborns after birth.

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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.020
GPT teacher head0.316
Teacher spread0.296 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuemedRxivSame topicOptical Imaging and Spectroscopy TechniquesFrench-language works237,207