Rationale and population-based prospective cohort protocol for the disadvantaged populations at risk of decline in eGFR (CO-DEGREE)
Bibliographic record
Abstract
Introduction A recently recognised form of chronic kidney disease (CKD) of unknown origin (CKDu) is afflicting communities, mostly in rural areas in several regions of the world. Prevalence studies are being conducted in a number of countries, using a standardised protocol, to estimate the distribution of estimated glomerular filtration rate (eGFR), and thus identify communities with a high prevalence of reduced glomerular filtration rate (GFR). In this paper, we propose a standardised minimum protocol for cohort studies in high-risk communities aimed at investigating the incidence of, and risk factors for, early kidney dysfunction. Methods and analysis This generic cohort protocol provides the information to establish a prospective population-based cohort study in low-income settings with a high prevalence of CKDu. This involves a baseline survey that included key elements from the DEGREE survey (eg, using the previously published DEGREE methodology) of a population-representative sample, and subsequent follow-up visits in young adults (without a pre-existing diagnosis of CKD (eGFR<60 mL/min/1.73m 2 ), proteinuria or risk factors for CKD at baseline) over several years. Each visit involves a core questionnaire, and collection and storage of biological samples. Local capacity to measure serum creatinine will be required so that immediate feedback on kidney function can be provided to participants. After completion of follow-up, repeat measures of creatinine should be conducted in a central laboratory, using reference standards traceable to isotope dilution mass spectrometry (IDMS) quality control material to quantify the main outcome of eGFR decline over time, alongside a description of the early evolution of disease and risk factors for eGFR decline. Ethics and dissemination Ethical approval will be obtained by local researchers, and participants will provide informed consent before the study commences. Participants will typically receive feedback and advice on their laboratory results, and referral to a local health system where appropriate.
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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 | 0.072 | 0.067 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.014 |
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".