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The influence of family history of schizophrenic spectrum disorders on the clinical presentation of schizophrenia

2024· article· en· W4403029606 on OpenAlexaboutno aff
Vadim R. Gashkarimov, Renata I. Sultanova, I. S. Efremov, I. E. Sabanaeva, Albert Iskhakov, L. R. Bakirov, Azat R. Asadullin

Bibliographic record

VenueMedical Herald of the South of Russia · 2024
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Schizophrenia spectrumPresentation (obstetrics)Family historyPsychologyPsychiatrySpectrum (functional analysis)MedicinePsychosisPhysicsInternal medicine

Abstract

fetched live from OpenAlex

Objective: to identify the characteristics of the clinical debut of schizophrenia, as well as clinical aspects related to hereditary aggravation within schizophrenic spectrum disorders.Materials and methods: patients with a confirmed diagnosis of F20.0 “Paranoid schizophrenia” selected according to inclusion/non-inclusion criteria participated in the study. Material was collected through clinical interviewing, analysis of medical records and documentation, and self-questionnaires.Results: a total of 264 individuals participated in the study. Hereditary aggravation with schizophrenic spectrum disorders within two generations was detected in 127 of them (48.1%). Our results showed that having a family history of schizophrenic spectrum disorders correlated with earlier age of schizophrenia debut (p=0.018) and higher scores on the Calgary Depression Scale (p=0.013).Conclusions: the findings may serve as an effective tool for developing more accurate diagnostic strategies in individuals at high risk of developing schizophrenia due to hereditary aggravation, as well as for the subsequent treatment of these individuals.

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)0.005
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.322
Teacher spread0.293 · 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
Published2024
Admission routes1
Has abstractyes

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