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Record W4379197331 · doi:10.1177/17407745231176834

The improving Medication Adherence in Adolescents and young adults following Liver Transplantation (iMALT) multisite trial: Design and trial implementation considerations

2023· article· en· W4379197331 on OpenAlexaboutno aff
Eyal Shemesh, Sarah E. Duncan, George Mazariegos, Rachel A. Annunziato, Ravinder Anand, Miguel Reyes‐Múgica, Jeff Mitchell, Benjamin L. Shneider

Bibliographic record

VenueClinical Trials · 2023
Typearticle
Languageen
FieldMedicine
TopicRenal Transplantation Outcomes and Treatments
Canadian institutionsnot available
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesNational Institutes of Health
KeywordsMedicineRandomized controlled trialLiver transplantationClinical trialIncidence (geometry)Intervention (counseling)TransplantationInformed consentInternal medicineAlternative medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Medication non-adherence is a leading cause of transplant rejection, organ loss, and death; yet no rigorous controlled study to date has shown compelling clinical benefits from an adherence-improving intervention. Non-adherent patients are less likely to participate in trials, and therefore, most studies enroll a majority of adherent patients who do not stand to benefit from the intervention, as they do not have the condition (non-adherence) under investigation. The improving Medication Adherence in adolescent Liver Transplant recipients trial specifically targets non-adherent patients to investigate whether a remote intervention to improve adherence results in reduced incidence of biopsy-confirmed rejection. METHODS: Improving Medication Adherence in adolescent Liver Transplant is a randomized single-blind controlled multisite, multinational National Institutes of Health-funded trial involving 13 pediatric transplant centers in the United States and Canada. An innovative, objective adherence biomarker-the Medication Level Variability Index, which is the standard deviation of a series of medication blood levels for each patient, is used to identify non-adherent patients at risk for rejection. The index is computed using electronic health record information for all potentially eligible patients based on repeated reviews of the entire clinic's roster. Identified patients, after consent, are randomized to intervention versus control (treatment as usual) arms. The remote intervention is delivered for 2 years by trained interventionists who reside in various locations in the United States. The primary outcome is the incidence of biopsy-confirmed acute cellular rejection, as confirmed by a majority vote of three pathologists who are masked to the study allocation and clinical information. DISCUSSION: Improving Medication Adherence in adolescent Liver Transplant includes several innovative design elements. The use of a validated, objective adherence index to survey a large cohort of transplant recipients allows the teams to avoid bias inherent in both convenience sampling and referral-based recruitment and enroll only patients whose computed index indicates substantially increased risk of rejection. The remote intervention paradigm helps to engage patients who are by definition hard to engage. The use of an objective, masked medical (rather than behavioral) outcome measure reduces the likelihood of biases related to clinical information and ensures broad acceptance by the field. Finally, monitoring for potential adverse events related to increased medication exposure due to the adherence intervention acknowledges that a successful intervention (increasing adherence) could have detrimental side effects via increased exposure to and potential toxicity of the medication. Such monitoring is almost never attempted in clinical trials evaluating adherence interventions.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.228
GPT teacher head0.486
Teacher spread0.259 · 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 designRandomized trial
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

Citations6
Published2023
Admission routes1
Has abstractyes

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