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Record W4402940718 · doi:10.1111/epi.18133

Association of first antiseizure medication with acute health care utilization in a cohort of adults with newly diagnosed epilepsy

2024· article· en· W4402940718 on OpenAlexaff
Leah J. Blank, Parul Agarwal, Churl‐Su Kwon, Kenneth S. Boockvar, Nathalie Jetté

Bibliographic record

VenueEpilepsia · 2024
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Calgary
FundersNational Institute on AgingEpilepsy SocietyVA National Center for Patient SafetyAmerican Epilepsy Society
KeywordsMedicineEpilepsyTopiramatePolypharmacyCohortDiagnosis codeComorbidityLevetiracetamAcute careRetrospective cohort studyMedical prescriptionRate ratioPediatricsStroke (engine)Emergency medicineConfidence intervalHealth careInternal medicinePsychiatryPopulation

Abstract

fetched live from OpenAlex

OBJECTIVE: Epilepsy is primarily treated with antiseizure medications (ASMs). The recommendations for first ASM in newly diagnosed epilepsy are inconsistently followed, and we sought to examine whether nonrecommended first ASM was associated with acute care utilization. METHODS: We conducted a retrospective cohort study of adults (≥18 years old) with newly diagnosed epilepsy (identified using validated epilepsy/convulsion International Classification of Diseases, Clinical Modification codes) in 2015-2019, sampled from Marketscan's Commercial and Medicare Databases. Exposure of interest was receipt of a non-guideline-recommended ASM, and the primary outcome was acute care utilization (an emergency department visit or hospitalization after the first ASM claim). Descriptive statistics characterized covariates, and multivariable negative binominal regression models were built adjusting for age, sex, Elixhauser Comorbidity Index, comorbid neurologic disease (e.g., stroke), and ASM polypharmacy. RESULTS: Approximately 14 681 people with new epilepsy were prescribed an ASM within 1 year. The three most prescribed medications were levetiracetam (54%, n = 7912), gabapentin (10%, n = 1462), and topiramate (7%, n = 1022). Approximately 4% (n = 648) were prescribed an ASM that should be avoided, and ~74% of people with new epilepsy had an acute care visit during the follow-up period. Mean number of acute care visits during follow-up was 3.34 for "recommended" ASMs and 4.42 for ASMs that "should be avoided." Prescription of a recommended/neutral ASM as compared to an ASM that should be avoided was associated with reduced likelihood of acute care utilization (incidence rate ratio [IRR] = .85, 95% confidence interval [CI] = .77-.94). The recommended/neutral category of ASMs was not statistically significantly associated with seizure- or epilepsy-specific acute care utilization (IRR = .93, 95% CI = .79-1.09). SIGNIFICANCE: Adults with new epilepsy are frequent users of acute care. There remain a proportion of persons with epilepsy prescribed ASMs that guidelines suggest avoiding, and these ASMs are associated with increased likelihood of emergency department visit or hospitalization. These findings reinforce the importance of optimizing the choice of first ASM in 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 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)0.003
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.302
Teacher spread0.290 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

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