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Record W4295221099 · doi:10.1016/j.ensci.2022.100424

Discussing brain magnetic resonance imaging results for neonates with hypoxic-ischemic encephalopathy treated with hypothermia: A challenge for clinicians and parents

2022· article· en· W4295221099 on OpenAlexafffund
M. Ariel Cascio, Amaryllis Ferrand, Éric Racine, Marie St‐Hilaire, Priscille-Nice Sanon, Andreea Gorgos, Pia Wintermark

Bibliographic record

VenueeNeurologicalSci · 2022
Typearticle
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsMontreal Children's HospitalMcGill UniversityJewish General HospitalMcGill University Health CentreMontreal Clinical Research InstituteUniversité de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsMedicineHypothermiaMagnetic resonance imagingEncephalopathyHypoxic Ischemic EncephalopathyNeuroimagingHypoxia (environmental)Neonatal encephalopathyAnesthesiaInternal medicinePsychiatryRadiologyOxygen

Abstract

fetched live from OpenAlex

Context: Clinicians use brain magnetic resonance imaging (MRI) to discuss neurodevelopmental prognosis with parents of neonates with hypoxic-ischemic encephalopathy (HIE) treated with therapeutic hypothermia (TH). Purpose: To investigate how clinicians and parents discuss these MRI results in the context of HIE and TH and how these discussions could be facilitated and more meaningful for parents. Procedures: Mixed-methods surveys with open-ended and closed-ended questions were completed by two independent groups. (1) Clinicians responded to clinical vignettes of neonates with HIE treated with TH with various types of clinical features, evolution and extent of brain injury and questions about how they discuss brain MRI results in this context. (2) Parents of children with HIE treated with TH responded to questions about the discussion of MRI that they had while still in the neonatal intensive care unit and were asked to place it in perspective with the outcomes of their child when he/she reached at least 2 years of age. Open-ended responses were analyzed using a thematic analysis approach. Closed-ended responses are presented descriptively. Results: Clinicians reported uncertainty, lack of confidence, and limitations when discussing brain MRI results in the context of HIE and TH. Brain MRI results were "usually" (53%) used in the prognostication discussion. When dealing with day-2 brain MRIs performed during TH, most clinicians (40%) assumed that the results of these early MRIs were only "sometimes" accurate and only used them "sometimes" (33%) to discuss prognosis; a majority of them (66%) would "always" repeat imaging at a later time-point to discuss prognosis. Parents also struggled with this uncertainty, but did not discuss limitations of MRI as often. Parents raised the importance of the setting where the discussion took place and the importance to inform them as quickly as possible. Clinicians identified strategies to improve these discussions, including interdisciplinary approach, formal training, and standardized approach to report brain MRI. Parents highlighted the importance of communication skills, the stress, the hope surrounding their situation, and the need to receive answers as soon as possible. The importance of showing the pictures or making representative drawing of the injury, but also highlighting the not-injured brain, was also highlighted by parents. Conclusions: Discussing brain MRI results for neonates with HIE treated with TH are challenging tasks for clinicians and daunting moments for parents.

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)0.038
metaresearch head score (Gemma)0.114
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.114
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0060.008
Open science0.0020.007
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0020.001

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 head0.255
Teacher spread0.236 · 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 designCase report
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

Citations13
Published2022
Admission routes2
Has abstractyes

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