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Record W3210521752 · doi:10.1503/jpn.200154

Hepatitis C–associated late-onset schizophrenia: a nationwide, population-based cohort study

2021· article· en· W3210521752 on OpenAlexvenueno aff
Jur‐Shan Cheng, Jinghong Hu, Ming‐Yu Chang, Ming‐Shyan Lin, Hsin‐Ping Ku, Rong‐Nan Chien, Ming‐Ling Chang

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2021
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
FundersChang Gung Medical FoundationNational Science Council
KeywordsMedicineInternal medicineHazard ratioCumulative incidenceHepatitis CCohortPopulationIncidence (geometry)Schizophrenia (object-oriented programming)Hepatitis C virusCohort studyConfidence intervalProportional hazards modelImmunologyPsychiatryVirus

Abstract

fetched live from OpenAlex

Background: Whether infection with the hepatitis C virus (HCV) causes schizophrenia — and whether the associated risk reverses after anti-HCV therapy — is unknown; we aimed to investigate these topics. Methods: We conducted a nationwide, population-based cohort study using the Taiwan National Health Insurance Research Database (TNHIRD). A diagnosis of schizophrenia was based on criteria from the International Classification of Diseases, 9th revision (295.xx). Results: From 2003 to 2012, from a total population of 19 298 735, we enrolled 3 propensity-score-matched cohorts (1:2:2): HCV-treated (8931 HCV-infected patients who had received interferon-based therapy for ≥ 6 months); HCV-untreated (17 862); and HCV-uninfected (17 862) from the TNHIRD. Of the total sample (44 655), 82.81% (36 980) were 40 years of age or older. Of the 3 cohorts, the HCV-untreated group had the highest 9-year cumulative incidence of schizophrenia (0.870%, 95% confidence interval [CI] 0.556%–1.311%; p < 0.001); the HCV-treated (0.251%, 95% CI 0.091%–0.599%) and HCV-uninfected (0.118%, 95% CI 0.062%–0.213%) cohorts showed similar cumulative incidence of schizophrenia ( p = 0.33). Multivariate Cox analyses showed that HCV positivity (hazard ratio [HR] 3.469, 95% CI 2.168–5.551) was independently associated with the development of schizophrenia. The HCV-untreated cohort also had the highest cumulative incidence of overall mortality (20.799%, 95% CI 18.739%–22.936%; p < 0.001); the HCV-treated (12.518%, 95% CI 8.707%–17.052%) and HCV uninfected (6.707%, 95% CI 5.533%–8.026%) cohorts showed similar cumulative incidence of mortality ( p = 0.12). Limitations: We were unable to determine the precise mechanism of the increased risk of schizophrenia in patients with HCV infection. Conclusion: In a population-based cohort (most aged ≥ 40 years), HCV positivity was a potential risk factor for the development of schizophrenia; the HCV-associated risk of schizophrenia might be reversed by interferon-based antiviral therapy.

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)0.001
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 score0.021
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.324
Teacher spread0.301 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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