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Record W2313788386 · doi:10.2147/ppa.s98498

Treatment outcomes after methylphenidate in adults with attention-deficit/hyperactivity disorder treated with lisdexamfetamine dimesylate or atomoxetine

2016· article· en· W2313788386 on OpenAlexaff
Alain Joseph, Martin Cloutier, Annie Guérin, Roy Nitulescu, Vanja Sikirica

Bibliographic record

VenuePatient Preference and Adherence · 2016
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsAtomoxetineMethylphenidateMedicineAttention deficit hyperactivity disorderPsychiatryAtomoxetine hydrochlorideStimulantAttention deficit disorderPharmacology

Abstract

fetched live from OpenAlex

PURPOSE: To compare treatment adherence, discontinuation, add-on, and daily average consumption (DACON) among adults with attention-deficit/hyperactivity disorder receiving second-line lisdexamfetamine dimesylate (LDX) or atomoxetine (ATX), following methylphenidate. PATIENTS AND METHODS: A retrospective cohort study using US commercial claims databases (Q2/2009-Q3/2013). RESULTS: At month 12, the LDX cohort (N=2,718) had a higher adherence level (proportion of days covered: 0.48 versus 0.30, P<0.001) and was less likely to discontinue (Kaplan-Meier estimate: 63% versus 85%, P<0.001) than the ATX cohort (N=674). There were no statistical differences in treatment add-on rates between cohorts (Kaplan-Meier estimate: 26% versus 25%, P=0.297). The LDX cohort had a lower DACON (1.10 versus 1.31, P<0.001) and was less likely to have a DACON >1 (adjusted odds ratio: 0.20, 95% confidence interval: 0.15-0.25, P<0.001) than the ATX cohort. CONCLUSION: Adults with attention-deficit/hyperactivity disorder treated with LDX following methylphenidate had a higher treatment adherence and lower discontinuation and DACON relative to those treated with ATX following methylphenidate.

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)0.000
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 score0.055
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.278
Teacher spread0.246 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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