Randomized trial of inpatient palliative care in patients hospitalized for hematopoietic stem cell transplantation (HCT).
Bibliographic record
Abstract
103 Background: During HCT, patients experience physical and psychological symptoms that negatively impact their quality of life (QOL). We assessed the impact of an inpatient palliative care intervention on patient QOL, symptom burden, and mood during HCT hospitalization and at 3 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). We used the Functional Assessment of Cancer Therapy-Bone Marrow Transplant (FACT-BMT) to assess QOL, the Hospital Anxiety and Depression Scale (HADS) and Patient Health Questionnaire (PHQ-9) to assess mood, and Edmonton Symptom Assessment Scale (ESAS) to measure symptoms at baseline, week-2, and 3 months post-HCT. We measured post-traumatic stress (PTSD) symptoms using the PTSD checklist at baseline and 3 months post-HCT. We used linear regression models controlling for baseline values to assess the intervention effects on outcomes at week-2 and 3 months post-HCT. Results: Between 8/2014 and 1/2016, we enrolled 160/186 (86%) of potentially eligible patients. At week-2, the intervention led to improvements in QOL, depression, anxiety, and symptom burden. At 3 months post-HCT, the intervention led to improvements in QOL, depression, and PTSD [Table 1]. PHQ-9 scores at week-2 and HADS-anxiety scores at 3 months did not differ significantly. Conclusions: Palliative care improved QOL, depression, anxiety, and symptom burden in patients hospitalized for HCT with notable sustained effects 3 months post-HCT. Involvement of palliative care for patients with hematologic malignancies can improve their outcomes and substantially reduce the morbidity of HCT. 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".