#3667 REVEAL-CKD: PREVALENCE OF UNDIAGNOSED STAGE 3 CHRONIC KIDNEY DISEASE IN AUSTRALIA, BRAZIL, CANADA AND SPAIN
Bibliographic record
Abstract
Abstract Background and Aims Chronic kidney disease (CKD) is a progressive condition that affects >850 million people globally. Global clinical guidelines from K-DIGO recommend early CKD identification and management to mitigate disease progression. The REVEAL-CKD study aims to assess the prevalence of, and factors associated with, undiagnosed stage 3 CKD across 11 countries. Here we report data from 4 countries in 4 continents. Method REVEAL-CKD is a multi-national, observational study, using secondary data from electronic medical records (EMR) and claims data. For this analysis, data were extracted from Australian General Practices through Pen CS (Australia), University of Sao Paulo (Brazil), the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) (Canada), and BIGPAC (Spain). The study cohort included patients aged ≥18 years with two consecutive estimated glomerular filtration rate (eGFR) values ≥30 and <60 mL/min/1.73 m2 recorded 91-730 days apart. The date of the second qualifying eGFR was the index date. Patients with no CKD diagnosis code before and up to 6 months after their index date were considered undiagnosed. The prevalence of undiagnosed CKD was calculated as the ratio of undiagnosed patients to all patients meeting the study inclusion criteria. Results The prevalence and baseline characteristics of undiagnosed Stage 3 CKD appear in Table 1. In all 4 countries, the undiagnosed prevalence was >80% and predominantly was more commonly observed in female patients, in patients aged > 65y, and remained high in patients with baseline comorbidities, particularly for those at highest risk of CKD (DM, CVD, HTN). Underreporting of CKD diagnosis in Brazil may be due to the inability to code for >1 condition in a patient. Conclusion These results indicate that a large proportion of patients across four world regions and who have biochemical evidence of early CKD lack a recorded diagnosis. An opportunity exists to identify, diagnose, and implement guideline-directed management for early CKD in order to delay its complications and improve clinical outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".