Consensus guidelines for sarcopenia prevention, diagnosis and management in Australia and New Zealand
Bibliographic record
Abstract
BACKGROUND: Sarcopenia is an age-associated skeletal muscle condition characterized by low muscle mass, strength, and physical performance. There is no international consensus on a sarcopenia definition and no contemporaneous clinical and research guidelines specific to Australia and New Zealand. The Australian and New Zealand Society for Sarcopenia and Frailty Research (ANZSSFR) Sarcopenia Diagnosis and Management Task Force aimed to develop consensus guidelines for sarcopenia prevention, assessment, management and research, informed by evidence, consumer opinion, and expert consensus, for use by health professionals and researchers in Australia and New Zealand. METHODS: A four-phase modified Delphi process involving topic experts and informed by consumers, was undertaken between July 2020 and August 2021. Phase 1 involved a structured meeting of 29 Task Force members and a systematic literature search from which the Phase 2 online survey was developed (Qualtrics). Topic experts responded to 18 statements, using 11-point Likert scales with agreement threshold set a priori at >80%, and five multiple-choice questions. Statements with moderate agreement (70%-80%) were revised and re-introduced in Phase 3, and statements with low agreement (<70%) were rejected. In Phase 3, topic experts responded to six revised statements and three additional questions, incorporating results from a parallel Consumer Expert Delphi study. Phase 4 involved finalization of consensus statements. RESULTS: Topic experts from Australia (n = 62, 92.5%) and New Zealand (n = 5, 7.5%) with a mean ± SD age of 45.7 ± 11.8 years participated in Phase 2; 38 (56.7%) were women, 38 (56.7%) were health professionals and 27 (40.3%) were researchers/academics. In Phase 2, 15 of 18 (83.3%) statements on sarcopenia prevention, screening, assessment, management and future research were accepted with strong agreement. The strongest agreement related to encouraging a healthy lifestyle (100%) and offering tailored resistance training to people with sarcopenia (92.5%). Forty-seven experts participated in Phase 3; 5/6 (83.3%) revised statements on prevention, assessment and management were accepted with strong agreement. A majority of experts (87.9%) preferred the revised European Working Group for Sarcopenia in Older Persons (EWGSOP2) definition. Seventeen statements with strong agreement (>80%) were confirmed by the Task Force in Phase 4. CONCLUSIONS: The ANZSSFR Task Force present 17 sarcopenia management and research recommendations for use by health professionals and researchers which includes the recommendation to adopt the EWGSOP2 sarcopenia definition in Australia and New Zealand. This rigorous Delphi process that combined evidence, consumer expert opinion and topic expert consensus can inform similar initiatives in countries/regions lacking consensus on sarcopenia.
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 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 | 0.122 | 0.184 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.009 | 0.008 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.005 |
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".