Cystatin C and acute changes in glomerular filtration rate
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The identification of an effective marker of acutely changing kidney function is a priority in clinical nephrology. While serum creatinine is the most widely used surrogate for glomerular filtration rate (GFR), its vulnerability to non-glomerular clearance results in biased estimates of GFR and may delay the identification of acute changes. Alternatively, cystatin C (CysC) has been recognized as a promising marker of GFR. Controlled physiological studies in diabetes, protein-induced glomerular hyperfiltration and extreme exercise demonstrated that acute changes in CysC provide a better approximation of GFR than serum creatinine. Clinical studies examining contrast induced nephropathy, acute kidney injury, and kidney transplantation have also demonstrated several possible advantages of CysC with respect to accurately measuring GFR and early diagnosis of renal dysfunction. CysC measurements also provide ancillary benefits such as improved prediction of patient outcomes and prognosis. Our aim was to review the literature on short-term changes in CysC over days, weeks and months to explore the clinical utility of CysC in the acute setting. Based on existing evidence, CysC may improve clinicians' ability to detect acute changes in kidney function.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it