Post‐traumatic stress as a determinant of quality of life in pediatric solid‐organ transplant recipients
Bibliographic record
Abstract
Living with end-stage organ failure is associated with an accumulation of traumatic medical events, and despite recovery after solid-organ transplantation (SOT), many children continue to exhibit lower quality of life (QOL). Few studies have examined the relationship between post-traumatic stress disorder (PTSD) and QOL among pediatric SOT recipients. We conducted a retrospective, cross-sectional review of 61 pediatric SOT recipients (12 heart, 30 kidney, and 19 liver) to evaluate the association of PTSD with self-reported QOL. PTSD was measured by the Child Trauma Screening Questionnaire (CTSQ), and QOL was measured using the PedsQL and PedsQL Transplant Module (PedsQL-TM) surveys. Demographics, baseline, and contemporaneous factors were tested for independent association. SOT recipients were 15.2 (12.1-17.6) years old at survey completion. Median CTSQ score was 2 (1-3), highest in kidney recipients, and 13% were identified as high risk for PTSD. Median PedsQL score was 83 (70-91) and significantly associated with the CTSQ score (r = -.68, p < .001). Median PedsQL Transplant Module score was 89 (83-95) and similarly associated with the CTSQ score (r = -.64, p < .001). Age at time of surveys and presence of any disability were also independently associated with PedsQL and PedsQL-TM, respectively. When adjusted for Emotional Functioning, CTSQ remained associated with PedsQL subscores (r = -.65, p < .001). Trauma symptoms are a major modifiable risk factor for lower self-perceived QOL and represent a potentially important target for post-transplant rehabilitation. Additional research is needed to understand the root contributors to PTSD and potential treatments in this population.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".