Evidence map›Paper›PMID 22759464›Full record

ArticleBMC psychiatry2012

The identification of family subtype based on the assessment of subclinical levels of psychosis in relatives.

Eske M Derks, Marco P M Boks, Jeroen K Vermunt, Genetic Risk and Outcome of Psychosis (GROUP) investigators

Open access · goldAbstract read
In one paragraph

Article in BMC psychiatry, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 46% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Eske M DerksUniversity Medical Center Utrecht, Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, AMC-APC, room PA1-179 Meibergdreef, Amsterdam, AZ 51105, The Netherlands. e.m.derks@amc.uva.nl
Marco P M Boks
Jeroen K Vermunt
Genetic Risk and Outcome of Psychosis (GROUP) investigators
Tilburg University · NLUniversity Medical Center Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSchizophrenia is a complex psychiatric disorder characterized by high phenotypic heterogeneity. Previous studies have distinguished between familial and sporadic forms of schizophrenia and have suggested clinical differentiation between patients and relatives from sporadic and multiplex families. We will introduce a more refined method to distinguish between family subtypes based on psychosis dimension profiles in the relatives of schizophrenia patients.

methodsPositive, negative, disorganization, mania, and depression scores were assessed in 1,392 relatives. Mixed Model Latent Class Analysis was used to identify family subtypes. A family subtype is a relatively homogeneous group of families with similar symptom profiles in the relatives in these families. Next, we investigated in 616 schizophrenia patients whether family subtype was associated with symptom profiles, IQ, cannabis dependence/abuse, or age of onset of psychosis.

resultsBased on the data of relatives, we identified two different family types: "healthy" and "at risk for psychiatric disorder". Patients from at risk families obtained higher positive scores compared to patients from healthy families (Wald(1) =6.6293, p=0.010). No significant differences were found in any of the remaining variables.

conclusionsOur findings confirm the existence of high-risk families and although we did not establish an etiological basis for the distinction between family types, genetic studies might reveal whether family subtype is associated with genetic heterogeneity.

Indexed as

AdolescentAdultFamilyFemaleGenetic Predisposition to DiseaseHumansMaleMiddle AgedPsychiatric Status Rating ScalesPsychotic DisordersSchizophrenia

Identifiers

PMID22759464
PMCPMC3504553
OpenAlexW1996045574

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.