Patient Outcomes Following Discharge from a CKD Clinic
Bibliographic record
Abstract
Background: In Ontario, Canada multidisciplinary care for patients with advanced chronic kidney disease (CKD) is delivered in Multi-Care-Kidney-Clinic (MCKC) operated by Regional Programs funded through a provincial network based on the number of eligible patients. These eligibility criteria were progressively revised between 2016 and 2018 from an absolute estimated glomerular filtration rate (eGFR) less than 30 ml/min/1.73m2 to less than 15 ml/min/1.73m2 or a two-year risk of end-stage kidney disease, calculated by the Kidney Failure Risk Equation (KFRE), greater than 10%. The objective of this study was to ascertain the outcomes of existing MCKC patients who were discharged as these criteria were implemented. Methods: This is a retrospective cohort study of prevalent CKD patients in MCKC in 2013 in the region of South Eastern Ontario, followed to January 2020. The outcomes were discharge from MCKC, re-referral, initiation of kidney replacement therapy (KRT), and death. Data were extracted from electronic medical record. Death was ascertained through Ontario’s Office of the Registrar General. Patients’ 2 and 5-year KFRE scores were calculated using the 4-variable KFRE. Results: Of the 643 MCKC patients in 2013 with available data, 470 (73%) continued follow-up in MCKC, while 142 (22%) and 31 (5%) were discharged to primary care and general nephrology respectively. Of those discharged to primary care, 52 (37%) died, while 15 (11%) were re-referred to nephrology, and 8 (6%) initiated KRT within median (IQR) times of 982 (560) and 850 (1411) days from discharge respectively. Five (63%) of the 8 discharged patients who required KRT did so for unforeseen acute illness rather than progressive CKD. Conclusions: The results of this study suggest that gradually moving MCKC funding eligibility criteria from absolute eGFR level to one based on both eGFR and the KFRE prediction model resulted in the discharge of a significant number of patients. Notably, few of the discharged patients ultimately required KRT that could have been prevented. This study offers a regional perspective with low loss to follow-up as there is only one Renal Program in the region. The results may not be generalizable to different populations, health care systems, or predictive models. Further research is needed to establish the optimal KFRE criterion upon which MCKC funding eligibility can be based.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".