Consensus recommendations on holistic care in hereditary ATTR amyloidosis: an international Delphi survey of patient advocates and multidisciplinary healthcare professionals
Bibliographic record
Abstract
BACKGROUND: Hereditary transthyretin-mediated amyloidosis is a rare, progressive and potentially life-limiting multisystem disease, affecting every aspect of a patient's life. OBJECTIVES: This online international Delphi survey aimed to evolve clinical-patient-led practical guidance, to inspire and encourage a holistic approach to care that is managed in specialist settings by multidisciplinary teams and supported by allied healthcare professionals (HCPs) and patient advocacy groups (PAGs). DESIGN: A 14-member joint patient advocate-HCP primary panel was convened including representation from PAGs and key clinical specialties (neurology, cardiology, internal medicine, physiotherapy, clinical psychology, dietetics and specialist nursing). Guidance evolved on the care provision needed to support seven core goals: early diagnosis and treatment; disease monitoring and organisation of care; maintenance of physical and mental health; family-centred care and caregiver support; patient-doctor dialogue; access to social support and social networking. PARTICIPANTS: From June to October 2022, 252 HCPs and 51 PAG representatives from 27 countries were invited to participate in a Delphi survey. Of the 122 respondents who answered at least one survey question, most were HCPs (100, 82%) from specialist centres; the remainder were PAG representatives (22, 18%). MAIN OUTCOME MEASURE: Both level of agreement and feasibility in practice of each recommendation was tested by two anonymised online Delphi voting rounds. RESULTS: Based on an a priori threshold for consensus of ≥75% agreement, the clinical-patient community endorsed all but one recommendation. However, only 17/49 (35%) recommendations were identified by most HCPs as a core part of routine care; the remainder (32/49 (65%)) were identified as part of core care by <50% of HCPs respondents, or as largely achievable by 30%-45% of HCPs. By comparison, PAGs recorded lower implementation levels. CONCLUSIONS: Further consideration is needed on how to evolve multidisciplinary services (supported by allied HCPs and PAGs) to address the complex needs of those affected by this disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.146 | 0.161 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".