Effectiveness of a multidisciplinary kidney disease clinic in achieving treatment guideline targets
Bibliographic record
Abstract
BACKGROUND: We have demonstrated previously that at referral most chronic kidney disease (CKD) patients have suboptimal metabolic and hypertension control. Although several studies suggest that CKD clinics improve patient outcome, in fact there are minimal published data describing the actual effect of such clinics on these parameters. METHODS: We performed a historical prospective review of a cohort of 340 CKD patients referred to our multidsciplinary clinic in 1998 or 1999, with estimated creatinine clearance (CCr) <60 ml/min. Data regarding blood pressure (BP) control, metabolic/anaemia parameters, medications, access planning and dialysis starts were collected. RESULTS: The number of patients followed was 234, 144, 100 and 70 at years 1-4 of follow-up, respectively. Twenty-five percent of the patients were diabetic, and 25% were suspected to have ischaemic nephropathy; mean age was 67+/-15 years. Although phosphate control improved from referral, below a CCr of 30 ml/min, 27% of visits showed hyperphosphataemia. Thirty-one percent of patients with CCr <15 ml/min had haemoglobin <100 g/l at follow-up despite the availability of erythropoietin. BP improved from a mean of 151/80 mmHg at referral to 137/75 mmHg in subsequent visits. At follow-up visits, 62% of BPs were still >130 mmHg systolic or 85 mmHg diastolic. For proteinuric patients (>1 g/day), 75% of follow-up visits showed BP >125/75 mmHg, despite angiotensin-converting enzyme inhibitor use increasing from 35% at referral to 79% at follow-up. Twenty-four percent of patients started renal replacement therapy, initially haemodialysis (HD) in 57%, peritoneal dialysis (PD) in 35% and pre-emptive transplant in 8%. Thirty-eight percent of dialysis starts occurred within 6 months of referral, but PD was the modality in half of these. Only half of the HD patients started using an aterio-venous fistula, and of those using a central catheter 11 of 24 had been followed >6 months, but only four of them had attempted fistula creation. CONCLUSIONS: CKD clinic attendance was associated with improvements in metabolic and BP control, and was able to facilitate the use of PD even for late referrals. However, even the multidisciplinary model with nephrologists, nurse educators and dietitians was unable to achieve guideline-recommended metabolic, anaemia, BP and access targets for a significant number of patients.
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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 | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 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".