Multiple Regression Analysis of Factors Predicting Mycophenolic Acid Free Fraction in 91 Adult Organ Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Mycophenolic acid (MPA) is an antirejection drug used in various types of solid organ transplants. MPA is extensively bound to albumin, and free MPA is thought to be the primary immunosuppressive agent. Little is known of what contributes to the wide interindividual variability in the observed MPA free fraction (MPAf) in humans. The purpose of this study was to determine, using multiple regression analysis of demographic and laboratory variables that are routinely collected during clinic visits, patient factors that predict MPAf in a large sample (n = 91) of organ transplant recipients. METHODS: Age, weight, height, total daily MPA dose, albumin, serum creatinine (SrCr), and MPAf were obtained from islet (n = 16), kidney (n = 28), and heart/lung (n = 47) transplant recipients. Multiple linear regression analysis and the The Spearman rank correlation were conducted using SigmaStat (version 3.5 for Windows). Significance was set a priori at P = 0.05. RESULTS: The pooled data can be described as (mean ± SD) follows: age (52 ± 13 years), weight (72 ± 15 kg), height (169 ± 9 cm), total daily MPA dose (1632 ± 667 mg), albumin (42 ± 7 g/L), SrCr (112 ± 34 µmol/L), and MPAf (2.9% ± 3.5%). Multiple regression of all commonly acquired variables generated the following equation: MPAf = 1.865 + (0.0357 × age (yrs)) + (0.0125 × weight (kg)) - (0.0202 × height (cm)) - (0.000323 × total daily dose (mg)) + (0.0122 × albumin (g/L)) + (0.0160 × SrCr (µmol/L)) (r = 0.06), but none of the variables were significant predictors of MPAf (P > 0.05). The Spearman rank correlation of each individual variable confirmed lack of significant correlation with MPAf. CONCLUSIONS: To our knowledge, this is the first study attempting to describe factors predicting MPAf in adult organ transplant recipients involving a large sample size. The novel findings of lack of significant predictors warrant further investigations using additional patient factors.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".