Risk Factors for Suboptimal Dialysis Initiation
Bibliographic record
Abstract
Key Points Suboptimal dialysis initiation is common and is associated with increased morbidity and mortality. Lower hemoglobin and higher comorbidity were risk factors for suboptimal dialysis initiation, but health literacy and kidney disease knowledge were not. Modifiable patient risk factors for suboptimal dialysis initiation were not found. Our study highlights the complexity of preventing this outcome. Background Suboptimal dialysis initiation is common and is associated with increased morbidity and mortality. We sought to determine risk factors for suboptimal dialysis initiation among patients with advanced CKD. Methods This was a prospective cohort study that enrolled English-speaking patients without cognitive impairment followed in multidisciplinary kidney clinics across four regional kidney programs in Ontario, Canada. Patients completed a 6-month follow-up visit with further follow-up using health care administrative data. The primary outcome was suboptimal dialysis initiation defined by dialysis initiation with a central venous catheter, in patients younger than 75 years, or during a hospitalization. Adjusted cause-specific hazard models were used to examine the association of prespecified characteristics with suboptimal dialysis initiation. Results Three hundred and sixty-six patients were included; 122 (33%) patients had a suboptimal dialysis start (69% of dialysis starts) over a median follow-up of 1.9 (interquartile range, 0.7–2.5) years. Higher hemoglobin (time varying) was associated with a lower risk of suboptimal dialysis initiation (adjusted hazard ratio, 0.96; 95% confidence interval [CI], 0.95 to 0.98). The mean (SD) hemoglobin in those with suboptimal dialysis initiation was 10.7 (1.5) g/dl. Higher comorbidity index and greater number of nephrologist visits within the past 6 months were associated with a higher risk of suboptimal dialysis initiation (adjusted hazard ratio, 1.17 [95% CI, 1.01 to 1.35] and 1.70 [95% CI, 1.39 to 2.08]; respectively). Measures of health literacy, kidney disease knowledge, and influenza vaccination were not associated with suboptimal dialysis initiation. A secondary analysis defining suboptimal dialysis initiation by dialysis initiation during a hospitalization showed similar results. Conclusions Suboptimal dialysis initiation was common despite established nephrology follow-up. Our study did not find readily modifiable patient-related risk factors for suboptimal dialysis initiation.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".