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Record W4308255865 · doi:10.1093/schbul/sbac152

Antipsychotic Use and Risk of Low-Energy Fractures in People With Schizophrenia: A Nationwide Nested Case-Control Study in Finland

2022· article· en· W4308255865 on OpenAlexaff
Marco Solmi, Markku Lähteenvuo, Christoph U. Correll, Antti Tanskanen, Jari Tiihonen, Heidi Taipale

Bibliographic record

VenueSchizophrenia Bulletin · 2022
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersCilagAcademy of Finland
KeywordsMedicineAntipsychoticSchizophrenia (object-oriented programming)Odds ratioNested case-control studyLogistic regressionInternal medicineCase-control studyPopulationConfidence intervalPsychiatryPediatricsEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Low-energy fractures (LEF) are more frequent in people with schizophrenia than the general population, and the role of prolactin-increasing antipsychotics is unknown. STUDY DESIGN: We conducted a nested case-control study using Finnish nationwide registers (inpatient, specialized outpatient care, prescription drug purchases). We matched each person with schizophrenia aged 16-85 years and incident LEF (cases) with 5 age/sex/illness duration-matched controls with schizophrenia, but no LEF. We investigated the association between cumulative exposure (duration, and Defined Daily Doses, DDDs) to prolactin-increasing/sparing antipsychotics and LEF. Adjusted conditional logistic regression analyses were performed. Sensitivity analyses were conducted. STUDY RESULTS: Out of 61 889 persons with schizophrenia between 1972 and 2014, we included 4960 cases. Compared with 24 451 controls, 4 years or more of exposure to prolactin-increasing antipsychotics was associated with increased risk of LEF (adjusted odds ratio (aOR) from aOR = 1.22, 95%CI = 1.09-1.37 to aOR = 1.38, 95%CI = 1.22-1.57, for 4-< 7 />13 years of exposure, respectively), without a significant association for prolactin-sparing antipsychotics. All cumulative doses higher than 1000 DDDs of prolactin-increasing antipsychotics were associated with LEF (from aOR = 1.21, 95%CI = 1.11-1.33, 1000-<3000 DDDs, to aOR = 1.64, 95%CI = 1.44-1.88, >9000 DDDs). Only higher doses of prolactin-sparing antipsychotics reached statistical significance (aOR = 1.24, 95%CI = 1.01-1.52, 6000-<9000 DDDs, aOR = 1.45, 95%CI = 1.13-1.85, >9000 DDDs). Sensitivity analyses confirmed the main analyses for prolactin-increasing antipsychotics. For prolactin-sparing antipsychotics, significant associations were limited to extreme exposure, major LEF, older age group, and males. CONCLUSIONS: Long-term exposure to prolactin-increasing antipsychotics at any dose, and high cumulative doses of prolactin-sparing antipsychotics is associated with significantly increased odds of LEF. Monitoring and addressing hyperprolactinemia is paramount in people with schizophrenia receiving prolactin-increasing antipsychotics.

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)0.001
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 score0.029
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.010
GPT teacher head0.267
Teacher spread0.257 · 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

Citations16
Published2022
Admission routes1
Has abstractyes

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