Early integrated palliative care for haematology cancer patients-the impact on symptom burden in Hong Kong
Bibliographic record
Abstract
BACKGROUND: Evidence showed that early palliative care could have many benefits in clinical outcomes for patients living with advanced medical illnesses. In fact, most of these studies have not involved patients with advanced haematologic cancer (HC), which are known to be associated with significant physical and psychological symptoms. In Hong Kong, an Early Integrated Palliative Care (EIPC) collaboration involving both Heamatology unit of Queen Mary Hospital (QMH) and the Palliative Medical Unit of Grantham Hospital (GH) has been started since early 2018 as a better way to improve the service gap. The HC patients failed 2 or more lines of cancer treatment are identified during the joint round and hematology clinic. Some of these patients will be referred to our PC services. Our joint PC clinic has multidisciplinary input from palliative care physicians, hematologists, and clinical psychologists. The clinic program is well coordinated and structured. The HC patients are initially seen by the parent team for disease treatment and then by GH PC team for symptom control and psychosocial care. METHODS: This was a retrospective study with a review of the clinical charts and electronic healthcare records of all patients who attended the Hematology PC clinic from June 2018 to September 2020. For the inclusion criteria, patients were found eligible if they had prospectively completed Edmonton Symptom Assessment Scale (ESAS) assessments for at least the initial and follow-up visits within a range of ≥7 days and ≤60 days of the first visit. RESULTS: Thirty-eight patients ultimately agreed to the referral. The mean age was 70.5 (12.5) years old. Twenty-five patients (66%) had myelodysplastic syndrome (MDS); 10 (26%) had acute myeloid leukemia (AML). Around 50-60% of patients reported significant symptoms of fatigue, anxiety, drowsiness, and anorexia; 42% of patients had significantly depressed moods while 37% had pain. There were significant symptom improvements for pain, depression, and anxiety after follow-up visits. CONCLUSIONS: The study showed that our EIPC program resulted in a significant reduction in some of the important symptom item scores, including pain, anorexia, anxiety, and depression, after the follow-up visits.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".