Correlation Between Health Literacy and Tacrolimus Variability in Solid Organ Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Adherence to immunosuppressive therapy is crucial for successful outcomes in solid organ transplantation. Tacrolimus intra-patient variability (%CV) is a validated marker of adherence and has been associated with graft outcomes. Health literacy (HL), a modifiable factor, may influence this variability, but its role remains unexplored. METHODS: We conducted a prospective observational study including adult kidney, liver, and lung transplant recipients receiving tacrolimus. HL was assessed using the Short Test of Functional Health Literacy in Adults (S-TOFHLA); a score <23 indicated insufficient HL. Tacrolimus %CV was calculated over 6 months post-discharge. Linear regression models, adjusted for sociodemographic variables, evaluated the association between HL and %CV. RESULTS: Ninety-eight patients were included (kidney: n = 38, liver: n = 24, lung: n = 36). Patients with insufficient HL had higher %CV than those with sufficient HL (31.5% vs. 16.1%, p < 0.05). HL remained independently associated with %CV after adjusting for age and transplant type (β = -1.60, SE = 0.17, p < 0.05). The final model explained 53% of %CV variability. CONCLUSIONS: HL is independently associated with tacrolimus variability. HL screening and targeted educational interventions may help improve medication stability and long-term transplant outcomes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".