Is Maximum Conservative Management an Equivalent Treatment Option to Dialysis for Elderly Patients with Significant Comorbid Disease?
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: There is ongoing growth of elderly populations with ESRD in Western Europe and North America. In our center, we offer an alternative care pathway of 'maximum conservative management' (MCM) to patients who elect not to start dialysis, often because of a heavy burden of comorbid illness and advanced age. The objective of our study was to compare clinical outcomes for patients who had ESRD and chose either MCM or renal replacement therapy (RRT). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This is an observational study of a single-center cohort in the United Kingdom that evaluating 202 elderly (> or =70 yr) patients who had ESRD and had chosen either MCM (n = 29) or RRT (n = 173). We report survival, hospitalization rates, and location of death for this cohort. Survival was measured from a standardized 'threshold' estimated GFR of 10.8 ml/min per 1.73 m(2). RESULTS: Median survival, including the first 90 d, was 37.8 mo (range 0 to 106 mo) for RRT patients and 13.9 mo (range 2 to 44) for MCM patients (P < 0.01). RRT patients had higher rates of hospitalization (0.069 [95% confidence interval (CI) 0.068 to 0.070]) versus 0.043 [95% CI 0.040 to 0.047] hospital days/patient-days survived) compared with MCM patients. MCM patients were significantly more likely to die at home or in a hospice (odds ratio 4.15; 95% CI 1.67 to 10.25). A survey of the literature describing elderly ESRD outcomes is also presented. CONCLUSIONS: Dialysis prolongs survival for elderly patients who have ESRD with significant comorbidity by approximately 2 yr; however, patients who choose MCM can survive a substantial length of time, achieving similar numbers of hospital-free days to patients who choose hemodialysis.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".