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Record W4396801090 · doi:10.1002/wps.21205

Real‐world effectiveness of antidepressants, antipsychotics and their combinations in the maintenance treatment of psychotic depression. Evidence from within‐subject analyses of two nationwide cohorts

2024· article· en· W4396801090 on OpenAlexaff
Heidi Taipale, Johannes Lieslehto, Markku Lähteenvuo, Aleksi Hamina, Antti O. Tanskanen, Ellenor Mittendorfer‐Rutz, Tapio Paljärvi, Marco Solmi, Andrea Cipriani, Christoph U. Correll, Jari Tiihonen

Bibliographic record

VenueWorld Psychiatry · 2024
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsRoyal Ottawa Mental Health CentreOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsDepression (economics)PsychiatryPsychotic depressionReal world evidenceSubject (documents)MedicinePsychologyClinical psychologyPsychosisInternal medicineComputer science

Abstract

fetched live from OpenAlex

Psychotic depression (PD) is a severe mental disorder leading to functional disability and high risk of suicide, but very little is known about the comparative effectiveness of medications used in its maintenance treatment. The objective of this study was to investigate the comparative effectiveness of specific antipsychotics and antidepressants, and their combinations, on the risk of psychiatric hospitalization among persons with PD in routine care. Persons aged 16-65 years with a first-time diagnosis of PD were identified from Finnish (years 2000-2018) and Swedish (years 2006-2021) nationwide registers of inpatient care, specialized outpatient care, sickness absence, and disability pension. The main exposures were specific antipsychotics and antidepressants, and the main outcome measure was psychiatric hospitalization as a marker of severe relapse. The risk of hospitalization associated with periods of use vs. non-use of medications (expressed as adjusted hazard ratio, aHR) was assessed by a within-individual design, using each individual as his/her own control, and analyzed with stratified Cox models. The two national cohorts were first analyzed separately, and then combined using a fixed-effect meta-analysis. The Finnish cohort included 19,330 persons (mean age: 39.8±14.7 years; 57.9% women) and the Swedish cohort 13,684 persons (mean age: 41.3±14.0 years; 53.5% women). Individual antidepressants associated with a decreased risk of relapse vs. non-use of antidepressants were bupropion (aHR=0.73, 95% CI: 0.63-0.85), vortioxetine (aHR=0.78, 95% CI: 0.63-0.96) and venlafaxine (aHR=0.92, 95% CI: 0.86-0.98). Any long-acting injectable antipsychotic (LAI) (aHR=0.60, 95% CI: 0.45-0.80) and clozapine (aHR=0.72, 95% CI: 0.57-0.91) were associated with a decreased risk of relapse vs. non-use of antipsychotics. Among monotherapies, only vortioxetine (aHR=0.67, 95% CI: 0.47-0.95) and bupropion (aHR=0.71, 95% CI: 0.56-0.89) were associated with a significantly decreased risk of relapse vs. non-use of both antidepressants and antipsychotics. In an exploratory analysis of antidepressant-antipsychotic combinations, a decreased relapse risk was found for amitriptyline-olanzapine (aHR=0.45, 95% CI: 0.28-0.71), sertraline-quetiapine (aHR=0.79, 95% CI: 0.67-0.93) and venlafaxine-quetiapine (aHR=0.82, 95% CI: 0.73-0.91) vs. non-use of antidepressants and antipsychotics. Benzodiazepines and related drugs (aHR=1.29, 95% CI: 1.24-1.34) and mirtazapine (aHR=1.17, 95% CI: 1.07-1.29) were associated with an increased risk of relapse. These data indicate that, in the maintenance treatment of PD, bupropion, vortioxetine, venlafaxine, any LAI, clozapine, and only few specific antidepressant-antipsychotic combinations are associated with a decreased risk of relapse. These findings challenge the current recommendation by treatment guidelines to combine an antipsychotic with an antidepressant (without further specification) as standard treatment in PD.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.026
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.044
GPT teacher head0.386
Teacher spread0.341 · 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 teacher head, 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

Citations11
Published2024
Admission routes1
Has abstractyes

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