Diagnostic Yield of Various Serum Creatinine Testing Frequencies in People at Risk for CKD
Bibliographic record
Abstract
Key Points The annual incidence of CKD is relatively low (approximately 2%) even in groups that are considered at higher risk, such as people with diabetes or hypertension. A substantial number of people are tested at least annually for CKD despite being at very low risk, such as those with an annual incidence of 0.02%. Considering age together with other risk factors for CKD to determine the frequency of testing may increase the diagnostic yield for incident CKD. Background Guidelines recommend regular serum creatinine testing to detect CKD among people with diabetes or hypertension, but the ideal frequency of testing is unknown. We determined the diagnostic yield for incident CKD as defined by ≥2 measures of eGFR <60 ml/min per 1.73 m 2 , based on testing frequencies of every 2, 3, 4, or 5 years as compared with annually. Methods We did a retrospective population-based cohort study of 3,515,163 adults older than 18 years with eGFR >60 ml/min per 1.73 m 2 at baseline in Alberta, Canada. We assessed diagnostic yield overall and in categories defined by age, sex, comorbidity, albuminuria, or levels of a multivariable risk score for CKD. Results Assuming annual testing, the number of tests needed (NTN) to detect one new CKD case was >67-fold higher among those younger than 50 years (2149, [95% confidence interval (CI), 2103 to 2196]) as compared with older than 70 years (32, [95% CI, 32 to 32]). NTN for annual testing was 50 (95% CI, 49 to 50) among people with diabetes, 57 (95% CI, 57 to 58) in those with hypertension, and 20 (95% CI, 20 to 21) among people with heart failure. When stratified by CKD risk score, the NTN for annual testing ranged from 7 (95% CI, 7 to 8) at a score of 9 (highest risk) to 5708 (95% CI, 5494 to 5930) at a score of 0 (lowest risk). Testing people with diabetes every 3 years instead of every year would delay the diagnosis of CKD by a mean of 1.5 years for 2, 12, and 32 per 1000 people with diabetes aged <50, 50–70, and >70 years, respectively. Corresponding delays associated with testing people with hypertension every 3 years instead of every year would affect 2, 9, and 27 per 1000 people aged <50, 50–70, and >70 years, respectively. If applied to all adult Albertans, these two changes in testing frequency would potentially avert more than 5.9 million laboratory assays over the next decade. Conclusions Tailoring the frequency of serum creatinine testing according to age and the presence of other risk factors would decrease the NTN to detect cases of incident CKD.
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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 | 0.005 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".