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Record W3080650048 · doi:10.1177/1740774520945988

Recruitment, retention, and adherence in a clinical trial: The Pediatric Heart Network’s Marfan Trial experience

2020· article· en· W3080650048 on OpenAlexaff
Michelle Hamstra, Victoria L. Pemberton, Nicholas Dagincourt, Danielle Hollenbeck-Pringle, Felicia Trachtenberg, James Cnota, Andrew M. Atz, Elizabeth Cappella, Sylvia De Nobele, Josephine Grima, Martha King, Rosalind Korsin, Linda M. Lambert, Meghan K MacNeal, Larry W. Markham, Gretchen MacCarrick, Donna Sylvester, Patricia Walter, Mingfen Xu, Ronald V. Lacro

Bibliographic record

VenueClinical Trials · 2020
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersNational Center for Advancing Translational SciencesNational Heart, Lung, and Blood InstituteU.S. Food and Drug AdministrationMarfan FoundationMerck
KeywordsMedicineRandomized controlled trialRetention rateAmbulatoryDescriptive statisticsYoung adultPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: The Pediatric Heart Network Marfan Trial was a randomized trial comparing atenolol versus losartan on aortic root dilation in 608 children and young adults with Marfan syndrome. Barriers to enrollment included a limited pool of eligible participants, restrictive entry criteria, and a diverse age range that required pediatric and adult expertise. Retention was complicated by a 3-year commitment to a complex study and medication regimen. The Network partnered with the Marfan Foundation, bridging the community with the research. The aims of this study are to report protocol and medication adherence and associated predictive factors, and to describe recruitment and retention strategies. METHODS: Recruitment, retention, and adherence to protocol activities related to the primary outcome were measured. Retention was measured by percentage of enrolled participants with 3-year outcome data. Protocol adherence was calculated by completion rates of study visits, ambulatory electrocardiography (Holter monitoring), and quarterly calls. Medication adherence was assessed by the number of tablets or the amount of liquid in bottles returned. Centers were ranked according to adherence (high, medium, and low tertiles). Recruitment, retention, and adherence questionnaires were completed by sites. Descriptive statistics summarized recruitment, retention, and adherence, as well as questionnaire results. Regression modeling assessed predictors of adherence. RESULTS: Completion rates for visits, Holter monitors, and quarterly calls were 99%, 94%, and 96%, respectively. Primary outcome data at 3 years were obtained for 88% of participants. The mean percentage of medication taken was estimated at 89%. Site and age were associated with all measures of adherence. Young adult and African American participants had lower levels of adherence. Higher adherence sites employed more strategies; had more staffing resources, less key staff turnover, and more collaboration with referring providers; utilized the Foundation's resources; and used a greater number of strategies to recruit, retain, and promote protocol and medication adherence. CONCLUSION: Overall adherence was excellent for this trial conducted within a National Institutes of Health-funded clinical trial network. Strategies specifically targeted to young adults and African Americans may have been beneficial. Many strategies employed by higher adherence sites are ones that any site could easily use, such as greeting families at non-study hospital visits, asking for family feedback, providing calendars for tracking schedules, and recommending apps for medication reminders. Additional key learnings include adherence differences by age, race, and site, the value of collaborative learning, and the importance of partnerships with patient advocacy groups. These lessons could shape recruitment, retention, and adherence to improve the quality of future complex trials involving rare conditions.

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)0.169
metaresearch head score (Gemma)0.620
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1690.620
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.006
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 head0.960
GPT teacher head0.735
Teacher spread0.226 · 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; both teacher heads agree on what is shown here.

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

Citations7
Published2020
Admission routes1
Has abstractyes

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