Multifaceted Intervention to Improve Graft Outcome Disparities in African American Kidney Transplants (MITIGAAT Study): Protocol for a Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: The outcome disparities for African American recipients of kidney transplant is a public health issue that has plagued the field of transplant since its inception. Based on national data, African American recipients have nearly twice the risk of graft loss at 5 years after transplant, when compared with White recipients. Evidence demonstrates that medication nonadherence and high tacrolimus variability substantially impact graft outcomes and racial disparities, most notably late (>2 years) after the transplant. Nonadherence is a leading cause of graft loss. Prospective multicenter data demonstrate that one-third of all graft loss are directly attributed to nonadherence. We have spent 10 years of focused research to develop a comprehensive model explaining the predominant risk factors leading to disparities in African American kidney recipients. However, there are still gaps in patient-level data that hinder the deeper understanding of the disparities. Lack of data from the patient often lead to provider biases, which will be addressed with this intervention. Culturally competent, pharmacist-led interventions in medication therapy management will also address therapeutic inertia. Pharmacist interventions will mitigate medication access barriers as well (cost and insurance denials). Thus, this multidimensional intervention addresses patient, provider, and structural factors that drive racial disparities in African American kidney recipients. OBJECTIVE: This prospective, randomized controlled trial aimed to determine the impact of multimodal health services intervention on health outcomes disparities in African American recipients of kidney transplant. The aims of this study are to improve adherence and control of late clinical issues, which are predominant factors for racial disparities in kidney recipients, through a technology-enabled, telehealth-delivered, 4-level intervention. METHODS: The Multifaceted Intervention to Improve Graft Outcome Disparities in African American Kidney Transplants (MITIGAAT) study is a 24-month, 2-arm, single-center (Medical University of South Carolina), 1:1 randomized controlled trial involving 190 participants (95 in each arm), measuring the impact on adherence and control of late clinical issues for racial disparities in kidney recipients, through a technology-enabled, telehealth-delivered, 4-level intervention. The key clinical issues for this study include tacrolimus variability, blood pressure, and glucose control (in those with diabetes mellitus). We will also assess the impact of the intervention on health care use (hospitalizations and emergency department visits) and conduct a cost-benefit analysis. Finally, we will assess the impact of the intervention on acute rejection and graft survival rates as compared with a large contemporary national cohort. RESULTS: This study was funded in July 2023. Enrolled began in April 2024 and is expected to be complete in 2026. All patients will complete the study by the end of 2028. CONCLUSIONS: In this protocol, we describe the study design, methods, aims, and outcome measures that will be used in the ongoing MITIGAAT clinical trials. TRIAL REGISTRATION: ClinicalTrials.gov NCT06023615; https://www.clinicaltrials.gov/study/NCT06023615. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/57784.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,035 | 0,035 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,013 | 0,007 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,005 | 0,005 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,008 | 0,009 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,084 | 0,011 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».