<scp>HELP</scp>‐<scp>KIDNEY</scp>: Health Literacy and Patient Outcomes in Pediatric Kidney Transplant
Bibliographic record
Abstract
ABSTRACT Background Below adequate health literacy is common and linked to increased risk of adverse health outcomes. Supporting optimal health following kidney transplantation requires the capacity to understand health information and make decisions about care. The impact of low health literacy in the context of pediatric kidney transplant has not previously been studied. Methods This retrospective cohort study sought to determine the relationship between caregiver or patient health literacy and healthcare utilization (outpatient hospital visits, days in hospital) and to explore relationships between health literacy and adherence to tacrolimus (trough level coefficient of variation) and allograft function post‐transplant. Results Forty patients were included in the analysis. 60% were identified as having adequate literacy using the Newest Vital Sign (NVS). Lower health literacy was significantly correlated with increased healthcare utilization in the first 3 months post‐transplant (rs = −0.36, p = 0.024) and in the first year post‐transplant (rs = −0.35, p = 0.029). No association was demonstrated between health literacy level and number of days admitted to the hospital (rs = −0.16, p = 0.321), adherence to tacrolimus 6–12 months post‐transplant (rs = 0.078, p = 0.68), or change in allograft function 2 years post‐transplant (rs = −0.13, p = 0.43). Conclusion Limited health literacy is common in pediatric kidney transplant recipients and families and is associated with increased frequency of hospital and outpatient clinic department visits early post‐transplant. In this small‐sized cohort, we did not identify a relationship between health literacy level and hospitalization days, allograft function, or tacrolimus adherence. Larger studies are needed to evaluate the relationship between health literacy and transplant outcomes in children and test interventions that may improve communication and optimize care.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".