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Record W4408664177 · doi:10.1186/s12913-025-12520-3

Integrated specialty care for amyloidosis: a scoping review using the Consolidated Framework for Implementation Research

2025· review· en· W4408664177 on OpenAlexaff
Mary J. O’Sullivan, Wahab Osman, Archanaa Krisnagopal, Monica Parry, Margot K. Davis, Charlene H. Chu

Bibliographic record

VenueBMC Health Services Research · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAmyloidosis: Diagnosis, Treatment, Outcomes
Canadian institutionsSt. Paul's HospitalUniversity of Toronto
Fundersnot available
KeywordsNursing researchMedicineHealth informaticsHealth administrationSpecialtyQuality of Life ResearchPain medicinePublic healthHealth services researchNursingFamily medicinePathologyAnesthesiology

Abstract

fetched live from OpenAlex

BACKGROUND: Amyloidosis is a complex and rare disease requiring specialized, multidisciplinary care to effectively manage its diverse manifestations. Existing evidence underscores the benefits of such care, linked to improved patient outcomes and clinician satisfaction. With the rising incidence of amyloidosis diagnoses and rapid advancements in treatment, the need for coordinated, expert-led care is increasing. However, implementing these centers is challenging due to resource allocation and inter-specialty collaboration. While resource allocation is a known hurdle, there has not been a comprehensive review of all the barriers and facilitators to establishing these clinics. This scoping review aims to identify the barriers and facilitators related to the implementation of coordinated, multidisciplinary specialty care clinics in amyloidosis management. METHODS: An electronic search was conducted in Medline, Embase, and CINAHL for studies published in English from 2013 to 2023, supplemented by a grey literature search. The inclusion criteria focused on studies discussing multidisciplinary clinical environments for amyloidosis care, particularly light-chain (AL) and transthyretin amyloidosis (TTR). Exclusion criteria included books, opinion pieces, dissertations, and conference abstracts. Data were analyzed and synthesized using a narrative synthesis approach, guided by the Consolidated Framework for Implementation Research (CFIR), and reported according to PRISMA-ScR guidelines. RESULTS: The search resulted in 1547 findings. After screening with Covidence, 7 papers were included in the final review. Independent reviewers screened and extracted the papers. Key facilitators identified include access to experts, adequate staffing, secure funding, partnerships with patient advocacy groups, and robust processes for multidisciplinary communication. Barriers primarily relate to the complexity of care, a lack of standardized protocols, difficulties in communication and coordination between providers, and challenges in training and maintaining knowledgeable care providers. The review also revealed significant gaps in existing research. CONCLUSIONS: This review enhances understanding of the barriers and facilitators in establishing amyloidosis specialty clinics. Addressing these barriers and leveraging facilitators are crucial for shaping the future of amyloidosis care. These insights support a model for implementing integrated care for this growing patient population and highlight the need for further research to support policy development and effective implementation of these specialized clinics.

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)0.191
metaresearch head score (Gemma)0.353
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.191
Threshold uncertainty score0.997

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1910.353
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0160.019
Bibliometrics0.0480.050
Science and technology studies0.0040.004
Scholarly communication0.0130.011
Open science0.0080.011
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0080.001

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 head0.208
GPT teacher head0.593
Teacher spread0.385 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

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