Suboptimal initiation of dialysis with and without early referral to a nephrologist
Bibliographic record
Abstract
BACKGROUND: Our objective was to examine patients who initiate renal replacement therapy (RRT) at 10 representative Canadian centers, characterize their initiation as inpatient or outpatient and describe their initial type of dialysis access, duration of pre-dialysis care and clinical status at the time of dialysis initiation. We also examined the impact of an optimal dialysis start (i.e. initiated as an outpatient with an arteriovenous fistula, arteriovenous graft or peritoneal dialysis catheter) on subsequent health outcomes. METHODS: Charts of consecutive incident RRT patients were identified from 1 July to 31 December 2006. Information was collected until 6 months after the initiation or until death, transplant or transfer. RESULTS: Three hundred and thirty-nine incident RRT patients were studied: 39.6% initiated as an inpatient; 54% started hemodialysis (HD) with a central venous catheter; 15.3% had <1 month predialysis care, while 64.6% had >1 year. Optimal starts occurred in 39.5% of patients. For HD patients, optimal starts occurred in 19.8%. Suboptimal starts were noted in patients referred <12 months prior to end-stage renal disease (44%) and in patients referred earlier (56%). The composite end point of death, transfusion or subsequent hospitalization was significantly reduced with an optimal start [hazard ratio 0.47 (95% confidence interval 0.32-0.68), P = 0.0001]. CONCLUSIONS: Suboptimal initiation of dialysis is common in patients referred early or late. The benefits of early referral are lost if dialysis is initiated suboptimally. There is a need to identify factors that lead to suboptimal initiation despite early referral.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".