Implementing a Formalized Risk-Based Approach to Determine Candidacy for Multidisciplinary CKD Care: A Descriptive Cohort Study
Bibliographic record
Abstract
Background: The kidney failure risk equation (KFRE) can be used to predict progression to end-stage kidney disease in a clinical setting. Objective: Evaluate implementation of a formalized risk-based approach in nephrologists' outpatient clinics and multidisciplinary chronic kidney disease (CKD) clinics to determine candidacy for multidisciplinary care, and the impact of CKD care selection on clinical outcomes. Design: Population-based descriptive cohort study. Setting: Alberta Kidney Care South. Patients: Adults attending or considered for a multidisciplinary CKD clinic between April 1, 2017, and March 31, 2019. Measurements: -Death, emergency department visits, and hospitalizations. Methods: We linked operational data from the clinics (available until March 31, 2019) with administrative health and laboratory data (available until March 31, 2020). Comparisons among patient groups, courses of care, and clinical settings with negative binomial regression count models and calculated unadjusted and fully adjusted incidence rate ratios. For the all-cause death outcome, we used Cox survival models to calculate unadjusted and fully adjusted hazard ratios. Results: Of the 1748 patients for whom a KFRE was completed, 1347 (77%) remained in or were admitted to a multidisciplinary CKD clinic, 310 (18%) were managed by a nephrologist only, and 91 (5%) were referred back for management by their primary care physician. There was a much higher kidney failure risk among patients who remained at or were admitted to a multidisciplinary CKD clinic (median 2-year risk of 34.7% compared with 3.6% and 0.8% who remained with a nephrologist or primary care physician, respectively). None of the people managed by their primary care physician alone commenced KRT, while only 2 (0.6%) managed by a nephrologist without multidisciplinary CKD care commenced KRT. The rates of emergency department visits, hospitalizations, and death were lower in those assigned to management outside the multidisciplinary CKD clinics when compared with those managed in the multidisciplinary care setting. Limitations: The follow-up period may not have been long enough to determine outcomes, and potentially limited generalizability given variability of care in multidisciplinary clinics. Conclusions: Our findings indicate that a portion of patients can be directed to less resource-intensive care without a higher risk of adverse events. Trial registration: Not applicable.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".