Ability of Cystatin C to Detect Changes in Glomerular Filtration Rate After ACE Inhibition in Patients with Uncomplicated Type 1 Diabetes
Bibliographic record
Abstract
Although it is known that glomerular filtration rate (GFR) declines in response to angiotensin converting enzyme (ACE) inhibition, recent observations using GFR(CYSTATIN C) have shown a paradoxical increase calling into question its validity. In this descriptive study, we aimed to reconcile this observation by simultaneously measuring GFR(CYSTATIN C), GFR(CREATININE), and gold standard GFR(INULIN) responses to ACE inhibition. Adolescents with type 1 diabetes and hyperfiltration (n = 9, GFR(INULIN) ≥ 135 mL/min/1.73 m(2)) or normofiltration (n = 11) were studied during clamped euglycemia at baseline and after 3-week enalapril therapy. In hyperfilterers, the anticipated GFR(INULIN) decline before and after enalapril was observed (174 ± 29 mL/min/1.73 m(2) to 140 ± 26 mL/min/1.73 m(2), P = .01). Although GFR(CYSTATIN C) equations tended to underestimate while GFR(CREATININE) equations tended to overestimate baseline GFR(INULIN) in hyperfilterers, both approaches generally reflected declining GFR(INULIN) responses to enalapril. Normofilterers demonstrated a trend toward rising GFR(INULIN) in response to enalapril (112 ± 16 mL/min/1.73 m(2) to 119 ± 27 mL/min/1.73 m(2), P = .35). Although all estimating equations tended to overestimate baseline GFR(INULIN), they generally reflected the rising trend in GFR(INULIN) in response to enalapril in normofilterers. Although GFR(INULIN) declines in response to enalapril among hyperfilterers, we confirm the previous observation that it demonstrates a trend to rising among normofilterers. These group trends are both reflected by cystatin C- and creatinine-based estimates.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".