The increase in paraoxonase-1 is associated with a decrease in left ventricular volume in kidney transplant recipients
Bibliographic record
Abstract
Abstract Background Patients on dialysis have impaired cardiac function, in part due to increased fluid volume and ventricular stress. Restored kidney function through transplantation reduces left ventricular volume in both systole and diastole. Paraoxonase 1 (PON1) is reduced in patients on dialysis, which may be related to their impaired cardiac function. We tested the hypothesis that change in PON1 is associated with changes in left ventricular (LV) end-volume and LV mass after kidney transplantation. Methods Patients were studied before and 12 months after kidney transplantation. The control group was patients on dialysis not expected to receive a transplant in the next 12 months. Cardiac magnetic resonance imaging was used to measure LV end-diastolic and end-systolic volume and LV mass. PON1 was measured by arylesterase activity and by mass. Results PON1 mass and activity were not different between the groups at baseline. Both PON1 mass and activity were increased post-kidney transplantation (p<0.0001 for change). The change in PON1 mass (p=0.0062) and PON1 arylesterase activity (p=0.0254) were inversely correlated with the change in NT-proBNP for patients receiving a kidney transplant. However, only the change in the PON1 mass, but not the change in PON1 arylesterase, was inversely correlated with the change in left ventricular volume (ml/m 2.7 ) (p=0.0146 and 0.0114 for diastolic and systolic, respectively) and with the change in hemoglobin (p=0.0042). Conclusions PON1 mass and activity increase after kidney transplantation. The increase in PON1 mass is consistent with a novel relationship to the increase in hemoglobin and the decrease in LV end-systolic and end-diastolic volume.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".