A Nurse-coordinated Model of Care versus Usual Care for Stage 3/4 Chronic Kidney Disease in the Community
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: It is unclear how to optimally care for chronic kidney disease (CKD). This study compares a new coordinated model to usual care for CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A randomized trial in nephrology clinics and the community included 474 patients with median estimated GFR (eGFR) 42 ml/min per 1.73 m(2) identified by laboratory-based case finding compared care coordinated by a general practitioner (controls) with care by a nurse-coordinated team including a nephrologist (intervention) for a median (interquartile range [IQR]) of 742 days. 32% were diabetic, 60% had cardiovascular disease, and proteinuria was minimal. Guided by protocols, the intervention team targeted risk factors for adverse kidney and cardiovascular outcomes. Serial eGFR and clinical events were tracked. RESULTS: The average decline in eGFR over 20 months was -1.9 ml/min per 1.73 m(2). eGFR declined by ≥4 ml/min per 1.73 m(2) within 20 months in 28 (17%) intervention patients versus 23 (13.9%) control patients. Control of BP, LDL, and diabetes were comparable across groups. In the intervention group there was a trend to greater use of renin-angiotensin blockers and more use of statins in those with initial LDL >2.5 mmol/L. Treatment was rarely required for anemia, acidosis, or disordered mineral metabolism. Clinical events occurred in 5.2% per year. CONCLUSIONS: Patients with stage 3/4 CKD identified through community laboratories largely had nonprogressive kidney disease but had cardiovascular risk. Over a median of 24 months, the nurse-coordinated team did not affect rate of GFR decline or control of most risk factors compared with usual care.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".