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Record W2939686499 · doi:10.1093/schbul/sbz019.287

T7. ELECTRORETINOGRAPHY FOR MAJOR PSYCHIATRIC DISORDERS IN MULTICENTRIC SITES

2019· article· en· W2939686499 on OpenAlexaffabout
Martin Roy, Marie‐Pierre F. Strippoli, Marc Hébert, Martin Preisig, Pierre Marquet

Bibliographic record

VenueSchizophrenia Bulletin · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsErgMedicineElectroretinographyCohortSchizophrenia (object-oriented programming)Bipolar disorderOphthalmologyDepression (economics)Cohort studyPsychiatryAmbulatoryPediatricsSurgeryInternal medicineRetinalLithium (medication)

Abstract

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The retinal response to light assessed by electroretinography (ERG) has been recognized as a promising site of investigation for psychiatric disorders. Indeed, ERG anomalies were reported in major depression, schizophrenia and offspring of patients (1,2,3). Traditionally, it is performed with bulky equipment using a corneal electrode which may cause some discomfort. Recently an ambulatory portable device was proposed (RETeval; LKC Gaithersburg MD) along with a novel skin electrode allowing ambulatory non-invasive recordings to be performed anywhere. This device was recently introduced in the Lausanne-Geneva High Risk Cohort (4). Participants of the cohort are interviewed every three years over a mean duration follow-up of 12 years using a semi-structured Diagnostic Interview for Genetic Studies (DIGS). The 15 min ERG is performed at the end of the interview at the research center (Cery hospital) or at the participant’s home. The device is also used in Canada where ERG was performed in 16 controls and 17 patients with bipolar disorder (BPD). A few schizophrenia patients (SZ) have been recruited both in Switzerland and Canada and the recruitment is still ongoing. Since the introduction of ERG in November 2017 in Lausanne, 33 people (54.5% women) agreed to participate that is 10 patients with BPD and 15 controls. Two thirds of the ERG were performed at home. A significant a-wave reduction and b-wave latency delay (both p=0.01) were observed in BPD when compared to controls in both Swiss and Canada cohorts. Moreover, controls and BPD from both cohorts did not differ respectively. We confirm high acceptance and feasibility of ERG use in our follow-up study. This portable non-invasive device render recording at the participant’s home possible. Even in a small sample, we were able to detect significant retinal anomalies in BPD in two continents suggesting some universality in the diagnosis. SZ results are on their way and may also enable to delineate these patients from BPD and controls. We hope that the discovery of ERG anomalies could shed new light onto the underlying pathophysiology of psychiatric disorders. References: 1) Hébert M. et al. (2017) Prog Neuropsychopharmacol Biol Psychiatry 75:10–5. 2) Hebert M. et al (2015) Schizophr Res 162, 294–5. 3) Hebert M. et al (2010). Biol Psychiatry 1;67(3):270–4. 4) Vandeleur CL. et al (2017). Soc Psychiatry Psychiatr Epidemiol 52, 1041–58.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0360.004

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 head0.003
GPT teacher head0.211
Teacher spread0.208 · 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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Citations1
Published2019
Admission routes2
Has abstractyes

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