Access Type as a Predictor of Dialysis Adequacy in Chronic Hemodialysis Patients
Bibliographic record
Abstract
Dialysis prescription commonly exceeds the delivered dialysis dose. Tunneled hemodialysis catheters (PC) may provide less dialysis than arteriovenous fistula (AVF) and polytetrafluoroethylene grafts (GG), but the impact of access type on the discrepancy (deltaHD) between dialysis prescription and dose is unknown. This study investigates the relationship between deltaHD and vascular access type. Fifty three chronic hemodialysis patients in our unit were prospectively studied for 3 weeks with measurement of delivered single pool and prescribed Kt/V(urea). There were 25 patients with AVF, 17 with GG, and 11 with PC. Demographic characteristics did not significantly differ between groups. Mean prescribed Kt/V(urea) was 1.73 +/- 0.26, and mean delivered Kt/V(urea) was 1.61 +/- 0.26. For 10 of 53 (19%) patients, dialysis delivery was at least equal to that prescribed, and this proportion did not differ between access types. Forty six of fifty three patients (86.7% of all patients) received Kt/V(urea) > 1.3, with no difference in this proportion between access types: AVF 22 of 25 (88.0%), GG 16 of 17 (94.1%), PC 8 of 11 (72.7%). Surprisingly, prescription times for patients with PC (3.6 +/- 0.3 hr) were significantly shorter than for those with AVF (3.9 +/- 0.3 hr) and GG (3.9 +/- 0.3 hr) (p = 0.02), perhaps indicating physician bias toward patients with tunneled catheters. In summary, access type was not a significant predictor of deltaHD, although patients with arteriovenous access tended to receive more dialysis than those with tunneled catheters. While a large proportion of patients received less dialysis than prescribed, the high levels of delivered Kt/V(urea) indicate that adequate dialysis is possible even in patients who must use tunneled catheters.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".