Reply
Bibliographic record
Abstract
Sir, We appreciate the interest and contribution of Liberek et al . to the controversy regarding timely initiation of dialysis. We agree that the findings of our study should not be used to advocate a late or low eGFR start on dialysis. In fact, as an observational cohort study, our study simply describes outcomes of those in whom dialysis was started at different levels of eGFR, and the data suggest that eGFR values should not be used in isolation, either to make a judgement on starting dialysis or as an auditing tool for the quality of ESRF care [ 1 ]. In fact, we describe an excellent example of ‘confounding by indication’: those with higher eGFR appear to be sicker, thus leading physicians to commence dialysis. Interestingly, however, the European Best Practice Guidelines [ 2 ] recommend ensuring that all patients have started dialysis before eGFR < 6 ml/min/1.73 m 2 , regardless of the presence or absence of signs and symptoms. Methods of assessing residual renal function that consider weight, and thus indirectly muscle mass and nutrition, such as creatinine clearance, are preferable in this setting and particularly relevant in Liberek's own study [ 3 ] of peritoneal dialysis patients in whom appropriate nutrition had a significant role. Traynor et al . [ 4 ] published results on survival and dialysis initiation utilizing the Cockcroft–Gault formula, which at least incorporates weight. The results are consistent with our findings and also contradict the concept of ‘early’ or ‘healthy’ start. While our study uses age and diabetes as indicators of comorbidity, both van Manen et al . [ 5 ] and Stel et al . [ 6 ] have found that after adjusting for age and diabetes, further adjustments for comorbidity made little further difference in European populations. Furthermore, it is interesting that Stel et al . found that the distribution of causes of death was similar in high, medium and low eGFR groups [ 6 ]. Finally, we welcome the sentiment that the individual decision of dialysis timing involves a clinical judgement of nephrologists on the basis of a variety of clinical features, particularly fluid overload in patients with left ventricular dysfunction. This is valuable to consider not only when met with studies that counter-intuitively appear to suggest a benefit in delaying the start of dialysis, but also when met with contradictory recommendations of a healthy early start. While we hope that the randomized controlled IDEAL trial [ 7 ] may be able provide some answers next year, meanwhile our study and that of Stel et al . demonstrate that nephrology is a specialty that values the physician who adopts a patient-centred approach. Conflict of interest statement . KS is the Chair of the Scottish Renal Registry. AL is provincial executive director of the BC Provincial Renal Agency, BCPRA.
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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 | 0.004 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.042 | 0.042 |
| Insufficient payload (model declined to judge) | 0.019 | 0.013 |
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".