The Primary-Secondary Care Partnership to Improve Outcomes in Chronic Kidney Disease (PSP-CKD) Study: A Cluster Randomized Trial in Primary Care
Bibliographic record
Abstract
Significance Statement Although most patients with CKD are managed in the primary care setting, the evidence base for CKD care in general practice is scant, and it is not clear whether specific CKD management programs can alter outcomes in primary care. The authors conducted a cluster randomized, controlled trial comparing 23 primary care practices offering usual care with 23 primary care practices in which a nurse practitioner helped those practices interpret patient data files and implement guideline-based CKD interventions. They found that the intervention did not affect rate of eGFR decline, but it did lead to significant improvements in processes, quality of care, and the number of patients achieving BP targets. This approach may improve processes of care, potentially reducing the burden of cardiovascular disease in patients with CKD. Background Most patients with CKD are managed in the community. Whether nurse-led CKD management programs improve outcomes in patients with CKD in primary care is unclear. Methods To assess the effect of such a program on the rate of renal function decline in patients with CKD (stages 3–5) in primary care in the United Kingdom, we conducted a cluster randomized trial, the Primary-Secondary Care Partnership to Improve Outcomes in Chronic Kidney Disease study. A software program designed for the study created a data file of patients with CKD in participating practices. In 23 intervention practices (11,651 patients), a CKD nurse practitioner worked with nominated practice leads to interpret the data file and implement guideline-based patient-level CKD management interventions. The 23 control practices (11,706 patients) received a data file but otherwise, continued usual CKD care. The primary outcome was defined at the cluster (practice) level as the change from baseline of the mean eGFR of the patients with CKD at 6-month intervals up to 42 months. Secondary outcomes included numbers of patients coded for CKD, mean BP, numbers of patients achieving National Institute for Health and Care Excellence BP targets for CKD, and proteinuria measurement. Results After 42 months, eGFR did not differ significantly between control and intervention groups. CKD- and proteinuria-related coding improved significantly along with the number of patients achieving BP targets in the intervention group versus usual care. Conclusions CKD management programs in primary care may not slow progression of CKD, but they may significantly improve processes of care and potentially decrease the cardiovascular disease burden in CKD and related costs.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".