MétaCan
Menu
Back to cohort
Record W4380291887 · doi:10.1001/jamaneurol.2023.1580

Independent Associations of Incident Epilepsy and Enzyme-Inducing and Non–Enzyme-Inducing Antiseizure Medications With the Development of Osteoporosis

2023· article· en· W4380291887 on OpenAlexaff
Colin B. Josephson, Arturo González-Izquierdo, Spiros Denaxas, Tolulope T. Sajobi, Karl Martin Klein, Samuel Wiebe

Bibliographic record

VenueJAMA Neurology · 2023
Typearticle
Languageen
FieldMedicine
TopicPharmacological Effects and Toxicity Studies
Canadian institutionsAlberta Children's HospitalHotchkiss Brain InstituteUniversity of Calgary
FundersMedical Research CouncilNational Institute for Health and Care Research
KeywordsMedicineOsteoporosisEpilepsyBody mass indexInternal medicineRheumatoid arthritisProportional hazards modelCohortCohort studyPhysical therapyPediatricsPsychiatry

Abstract

fetched live from OpenAlex

Importance: Both epilepsy and enzyme-inducing antiseizure medications (eiASMs) having varying reports of an association with increased risks for osteoporosis. Objective: To quantify and model the independent hazards for osteoporosis associated with incident epilepsy and eiASMS and non-eiASMs. Design, Setting, and Participants: This open cohort study covered the years 1998 to 2019, with a median (IQR) follow-up of 5 (1.7-11.1) years. Data were collected for 6275 patients enrolled in the Clinical Practice Research Datalink and from hospital electronic health records. No patients who met inclusion criteria (Clinical Practice Research Datalink-acceptable data, aged 18 years or older, follow-up after the Hospital Episode Statistics patient care linkage date of 1998, and free of osteoporosis at baseline) were excluded or declined. Exposure: Incident adult-onset epilepsy using a 5-year washout and receipt of 4 consecutive ASMs. Main Outcomes and Measures: The outcome was incident osteoporosis as determined through Cox proportional hazards or accelerated failure time models where appropriate. Incident epilepsy was treated as a time-varying covariate. Analyses controlled for age, sex, socioeconomic status, cancer, 1 or more years of corticosteroid use, body mass index, bariatric surgery, eating disorders, hyperthyroidism, inflammatory bowel disease, rheumatoid arthritis, smoking status, falls, fragility fractures, and osteoporosis screening tests. Subsequent analyses (1) excluded body mass index, which was missing in 30% of patients; (2) applied propensity score matching for receipt of an eiASM; (3) restricted analyses to only those with incident onset epilepsy; and (4) restricted analyses to patients who developed epilepsy at age 65 years or older. Analyses were performed between July 1 and October 31, 2022, and in February 2023 for revisions. Results: Of 8 095 441 adults identified, 6275 had incident adult-onset epilepsy (3220 female [51%] and 3055 male [49%]; incidence rate, 62 per 100 000 person-years) with a median (IQR) age of 56 (38-73) years. When controlling for osteoporosis risk factors, incident epilepsy was independently associated with a 41% faster time to incident osteoporosis (time ratio [TR], 0.59; 95% CI, 0.52-0.67; P < .001). Both eiASMs (TR, 0.91; 95% CI, 0.87-0.95; P < .001) and non-eiASMs (TR, 0.77; 95% CI, 0.76-0.78; P < .001) were also associated with significant increased risks independent of epilepsy, accounting for 9% and 23% faster times to development of osteoporosis, respectively. The independent associations among epilepsy, eiASMs, and non-eiASMs remained consistent in propensity score-matched analyses, cohorts restricted to adult-onset epilepsy, and cohorts restricted to late-onset epilepsy. Conclusions and Relevance: These findings suggest that epilepsy is independently associated with a clinically meaningful increase in the risk for osteoporosis, as are both eiASMs and non-eiASMs. Routine screening and prophylaxis should be considered in all people with epilepsy.

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 score0.197
Threshold uncertainty score0.326

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.302
Teacher spread0.275 · 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

Citations19
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJAMA NeurologySame topicPharmacological Effects and Toxicity StudiesFrench-language works237,207