SP237SERUM BTP CONCENTRATIONS ARE NOT AFFECTED BY HEPATIC DYSFUNCTION
Bibliographic record
Abstract
Introduction and Aims: Beta Trace Protein (BTP) is emerging as a promising novel endogenous marker of glomerular filtration rate (GFR). New equations are being developed to convert its serum concentration into an estimate of GFR. Very little is known about BTP’s production and metabolism. It has been hypothesized that the liver metabolizes certain BTP isoforms. As such, hepatic dysfunction may influence serum levels independently of GFR. This would impact on the accuracy and precision of GFR estimates using BTP. The aim of this study was to determine whether patients with hepatic dysfunction have higher than expected serum BTP concentrations due to reduced hepatic BTP clearance. Methods: BTP, cystatin C (cysC) and creatinine (Cr) were measured in 99 cirrhotic subjects and in age, gender and diabetes status matched controls. BTP/cysC and Cr/cysC ratios were compared between cases and controls. This was repeated after stratification by Child Pugh category. Comparisons of ratios between Child Pugh category A and combined B and C case subjects were also performed. The BTP/cysC ratio was chosen in lieu of the BTP/Cr ratio due to the well-recognized inaccuracy of Cr as a marker of GFR in the setting of hepatic dysfunction. Prior studies have shown a strong inverse relationship between inulin GFR and cysC in cirrhotic patients and a lack of impact of cirrhosis on serum cysC levels, suggesting that cysC is an acceptable surrogate for measured GFR.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".