Dialysis Initiation: What's the Rush?
Bibliographic record
Abstract
The recent trend to early initiation of dialysis (at eGFR >10 ml/min/1.73 m(2) ) appears to have been based on conventional wisdoms that are not supported by evidence. Observational studies using administrative databases report worse comorbidity-adjusted dialysis survival with early dialysis initiation. Although some have concluded that the IDEAL randomized controlled trial of dialysis start provided evidence that patients become symptomatic with late dialysis start, there is no definitive support for this view. The potential harms of early start of dialysis, including the loss of residual renal function (RRF), have been well documented. The rate of RRF loss (renal function trajectory) is an important consideration for the timing of the dialysis initiation decision. Patients with low glomerular filtration rate (GFR) may have sufficient RRF to be maintained off dialysis for years. Delay of dialysis start until a working arterio-venous access is in place seems prudent in light of the lack of harm and possible benefit of late dialysis initiation. Prescribing frequent hemodialysis is not recommended when dialysis is initiated early. The benefits of early initiation of chronic dialysis after episodes of congestive heart failure or acute kidney injury require further study. There are no data to show that early start benefits diabetics or other patient groups. Preemptive start of dialysis in noncompliant patients may be necessary to avoid complications. The decision to initiate dialysis requires informed patient consent and a joint decision by the patient and dialysis provider. Possible talking points for obtaining informed consent are provided.
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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 | 0.024 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.009 | 0.018 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.013 | 0.022 |
| Insufficient payload (model declined to judge) | 0.012 | 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".