Supportive Care: Comprehensive Conservative Care in End-Stage Kidney Disease
Bibliographic record
Abstract
Comprehensive conservative (nondialytic) kidney care is widely recognized and delivered but until recently, has not been clearly defined. We provide a clear definition of comprehensive conservative care. This includes interventions to delay progression of kidney disease and minimize complications as well as detailed communication, shared decision making, advance care planning, and psychologic and family support. It does not include dialysis. Limited epidemiologic evidence from Australia and Canada indicates that, for every new person diagnosed with ESRD who receives dialysis or transplant, there is one new person who is managed conservatively (either actively or not). For older patients (those >75 or 80 years old) who have higher levels of comorbidity (such as diabetes and heart disease) and poorer functional status, the survival advantage of dialysis may be limited, and comprehensive conservative management may be considered; however, robust comparative evidence remains limited. Considerations of symptoms, quality of life, and hospital-free days are as or sometimes more important for patients and families than survival. There is some evidence that communication about possible conservative management options is generally insufficient, even where comprehensive conservative care pathways are already established. Symptom control and the cost-effectiveness of interventions are addressed in the companion papers within this Moving Points in Nephrology series. There is almost no evidence about which models of care and which interventions might be most beneficial in this population; future research on these areas is much needed. Meanwhile, consistency in definition of comprehensive conservative care and basing interventions on existing evidence about survival, symptoms, quality of life, and experience will maximize patient-centered and holistic care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".