Recommendations for culturally safe clinical kidney care for First Nations Australians: a guideline summary
Bibliographic record
Abstract
Abstract Introduction First Nations Australians display remarkable strength and resilience despite the intergenerational impacts of ongoing colonisation. The continuing disadvantage is evident in the higher incidence, prevalence, morbidity and mortality of chronic kidney disease (CKD) among First Nations Australians. Nationwide community consultation (Kidney Health Australia, Yarning Kidneys, and Lowitja Institute, Catching Some Air) identified priority issues for guideline development. These guidelines uniquely prioritised the knowledge of the community, alongside relevant evidence using an adapted GRADE Evidence to Decision framework to develop specific recommendations for the management of CKD among First Nations Australians. Main recommendations These guidelines explicitly state that health systems have to measure, monitor and evaluate institutional racism and link it to cultural safety training, as well as increase community and family involvement in clinical care and equitable transport and accommodation. The guidelines recommend earlier CKD screening criteria (age ≥ 18 years) and referral to specialists services with earlier criteria of kidney function (eg, estimated glomerular filtration rate [eGFR], ≤ 45 mL/min/1.73 m2, and a sustained decrease in eGFR, > 10 mL/min/1.73 m2 per year) compared with the general population. Changes in management as result of the guidelines Our recommendations prioritise health care service delivery changes to address institutional racism and ensure meaningful cultural safety training. Earlier detection of CKD and referral to nephrologists for First Nations Australians has been recommended to ensure timely implementation to preserve kidney function given the excess burden of disease. Finally, the importance of community with the recognition of involvement in all aspects and stages of treatment together with increased access to care on Country, particularly in rural and remote locations, including dialysis services.
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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 | 0.012 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".