Effect of inpatient palliative care during hematopoietic stem cell transplantation (HCT) hospitalization on psychological distress at six months post-HCT.
Bibliographic record
Abstract
10005 Background: Patients’ experience during HCT hospitalization leads to significant psychological distress post-HCT. Inpatient palliative care integrated with transplant care improves patient-reported QOL and symptom burden during hospitalization for HCT. We assessed the impact of the inpatient palliative care intervention on patients’ QOL, mood, and post-traumatic stress disorder (PTSD) at 6 months post-HCT. Methods: We randomized 160 patients with hematologic malignancies admitted for autologous or allogeneic HCT to an inpatient palliative care intervention (n=81) integrated with transplant care compared to transplant care alone (n=79). At baseline and 6 months post-HCT, we assessed QOL, mood, and PTSD symptoms using the Functional Assessment of Cancer Therapy-Bone Marrow Transplant (FACT-BMT), the Hospital Anxiety and Depression Scale (HADS) and Patient Health Questionnaire (PHQ-9), and the PTSD checklist, respectively. To assess symptom burden during HCT hospitalization, we used the Edmonton Symptom Assessment Scale. We utilized linear regression models controlling for baseline values to analyze the intervention effects on outcomes at 6 months. We conducted causal mediation analyses to examine whether symptom burden during HCT mediated the effect of the intervention on o utcomes at 6 months. Results: Between 8/14 and 1/16, we enrolled 160/186 (86%) of potentially eligible patients. At 6 months post-HCT, the intervention led to improvements in depression and PTSD symptoms, but not QOL or anxiety [Table]. Improvement in symptom burden during HCT hospitalization partially mediated the effect of the intervention on patient-reported outcomes at six months post-HCT. Conclusions: Inpatient palliative care integrated with transplant care leads to improvements in depression and PTSD symptoms at 6 months post-HCT. Addressing symptom burden during HCT hospitalization partially accounts for the effect of the intervention on these long-term outcomes. Clinical trial information: NCT02207322. [Table: see text]
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".