Patient‐Reported Oral Symptoms and Their Impact on Well‐Being After Haematopoietic Cell Transplantation
Bibliographic record
Abstract
OBJECTIVE: Oral complications may negatively influence outcomes of haematopoietic cell transplantation (HCT). A comprehensive view of oral symptoms and symptom burden post-HCT is lacking. This study aimed to determine the prevalence, severity, and temporal relationships of oral symptoms and their impact on well-being in the early post-HCT phase. Effects of transplant type and conditioning intensity were evaluated. METHODS: In this prospective multicentre observational study, adult HCT recipients were interviewed and completed questionnaires on oral symptoms and well-being three times a week during hospitalisation early post-HCT. RESULTS: Of 194 patients, 177 (91.2%) reported oral symptoms. Dry mouth was the earliest and most common (80.9%) followed by oral pain (35.6%), thickening/swollen mucosa (33.0%), and taste changes (30.9%). Symptom frequency peaked on days 6 to 11 post-HCT and caused significant burden: 59.3% experienced moderate to severe distress and 53.6% reported moderate to severe impact on well-being. Symptom prevalence was highest among patients who received allogeneic HCT with MAC and those who underwent autologous HCT. Overall, MAC regimens were associated with earlier and more frequent symptoms, greater distress and higher impact on well-being during days 0 to 11 post-HCT compared to reduced/non-myeloablative regimens. CONCLUSIONS: Oral symptoms are prevalent, burdensome and significantly impact well-being early post-HCT, underscoring the need for close monitoring and supportive oral care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".