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Record W2795025376 · doi:10.1093/schbul/sby014.142

34.1 DO ALL INDIVIDUALS WITH A FEP PASS THROUGH AN EARLIER CHR-P STATE? IMPLICATIONS FOR CLINICAL STAGING, EARLY DETECTION AND PHASE-SPECIFIC INTERVENTIONS

2018· article· en· W2795025376 on OpenAlexaffabout
Jai Shah, Rachel Rosengard, Sarah V. McIlwaine, Sally Mustafa, Srividya N. Iyer, Martín Lepage, Ridha Joober, Ashok Malla

Bibliographic record

VenueSchizophrenia Bulletin · 2018
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsMcGill University
Fundersnot available
KeywordsAnxietyPsychiatryPsychological interventionPsychosisIntervention (counseling)Depression (economics)PsychologyProdromeMental healthClinical psychologyMedicine

Abstract

fetched live from OpenAlex

The CHR-P syndrome has attracted much attention as a potentially important stage for early intervention aimed at preventing or delaying the onset of psychosis. Knowledge regarding the transition from CHR-P to FEP has been widely described and disseminated, but a major (untested) assumption permeates this literature: that most or all patients with a FEP actually experienced an earlier CHR-P state. Examining this assumption will provide crucial information regarding the potential utility of public mental health efforts such as early case identification and prevention directed at the CHR-P stage. Semistructured interviews of 351 patients and families with the Circumstances of Onset and Relapse Schedule were supplemented by chart reviews in a catchment area–based sample of FEP patients in Montréal, Canada. Retrospective information was extracted regarding baseline sociodemographic variables, psychiatric and behavioral changes, and help-seeking behavior up to the point of intake in the FEP service. Experts (N=30) working in FEP and CHR settings identified which of 27 early signs and symptoms in the Topography of Psychotic Episode instrument constituted sub-threshold psychotic symptoms if they appeared prior to a syndromal-level psychotic episode. Individuals were then followed within the FEP service for up to 2 years in order to record a range of symptomatic (positive and negative symptoms, depression and anxiety) and functional (global functioning, social and occupational functioning) outcomes. While most clients (between 50–68%) experienced at least one early sub-threshold psychotic symptom prior to their FEP, a substantial minority recalled no CHR-P symptoms en route to psychosis. At entry to FEP services, there were no differences in sociodemographic, cognitive, or functional variables between youth who had experienced a CHR-P state versus those who had not. Youth with a CHR-P profile had significantly longer durations between psychosis onset and making the decision to seek help (median 7.7 weeks versus 3.7 weeks), as well as the total length of the prodrome leading up to psychosis (median 36.4 weeks versus 15.0 weeks). These subgroups also differed in key symptomatic and functional outcomes, with those who passed through CHR-P states en route to FEP having significantly higher depressive and anxiety symptoms at baseline, more positive and negative psychotic symptoms at 1 year, and lower functioning for at least 1 year after the initiation of FEP treatment. A substantial minority of FEP cases did not recall a CHR-P state, suggesting that a wide range of psychopathology precedes FEP. Nonetheless, our estimates indicate that over 50% of FEP cases could still be prevented through optimal interventions targeting the CHR-P phase. This adds a novel component to previous arguments regarding the feasibility and relevance of the CHR-P construct for FEP, and underscores the importance of early case identification for this vulnerable population. Implications of these findings for contemporary clinical staging models, prevention and intervention efforts will be discussed.

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)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.115
GPT teacher head0.419
Teacher spread0.304 · 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 designNot applicable
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
Published2018
Admission routes2
Has abstractyes

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