Integrating Risk-Based Care for Patients With Chronic Kidney Disease in the Community: Study Protocol for a Cluster Randomized Trial
Bibliographic record
Abstract
BACKGROUND: A risk-based model of care for managing patients with chronic kidney disease (CKD) using the Kidney Failure Risk Equation (KFRE) has been successfully integrated into nephrology care pathways in several jurisdictions. However, as most patients with CKD can be managed in primary care, the next pertinent steps would be to integrate the KFRE into primary care pathways. OBJECTIVE: Using a risk-based approach for guiding CKD care in the primary care setting, the objective of the study is to develop, implement, and evaluate tools that can be used by patients and providers. DESIGN: This study is a multicenter cluster randomized control trial. SETTING: Thirty-two primary care clinics belonging to the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) across Manitoba and Alberta. PATIENTS: All patients at least 18 years old or older with CKD categories G3-G5 attending the participating clinics; we estimate each clinic will have an average of 185 patients with CKD. METHODS: Thirty-two primary care clinics will be randomized to receive either an active knowledge translation intervention or no intervention. The intervention involves the addition of the KFRE and decision aids to clinics' Data Presentation Tool (DPT), as well as patient-facing visual aids, a medical detailing visit, and sentinel feedback reports. Control clinics will only be exposed to current guidelines for CKD management, without active dissemination. MEASUREMENTS: Data from the CPCSSN repository will be used to assess whether a risk-based care approach affected management of CKD. Primary outcomes are as follows: the proportion of patients with measured urine albumin-to-creatinine ratio, and the proportion of patients being appropriately treated with angiotensin-converting enzyme inhibitor or angiotensin receptor blockers. Secondary outcomes are as follows: the optimal management of diabetes (hemoglobin A1C <8.5%, and the use of sodium-glucose cotransporter-2 inhibitors in CKD G3 patients), hypertension (office blood pressure <130/80 for patients with diabetes, 140/90 for those without), and cardiovascular risk (statin prescription); prescriptions of nonsteroidal anti-inflammatory drugs; and decline in estimated glomerular filtration rate (eGFR). In addition, in a substudy, we will measure CKD-specific health literacy and trust in physician care via surveys administered in the clinic post-visit. At the provider level, we will measure satisfaction with the risk prediction tools. Lastly, at the health system level, outcomes include cost of CKD care, and appropriate referrals for patients at high risk of kidney failure based on provincial guidelines. Primary and secondary outcomes will be measured at the patient level and enumerated at the clinic level 1 year after the intervention implementation, except for decline in eGFR, which will be measured 2 years postintervention. LIMITATIONS: Limitations include scalability of the proposal in other health care systems. CONCLUSIONS: If successful, this intervention has the potential to improve the management of patients with CKD within Canadian primary care settings, leading to health and economic benefits, and influencing practice guidelines. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03365063.
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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 | 0.036 | 0.035 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.006 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.066 | 0.009 |
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".