Examining the Characteristics of Patients With Non-Malignant Lung Disease at the Time of Referral to An Inter-Professional Supportive Care Clinic
Bibliographic record
Abstract
CONTEXT: Patients with non-malignant, advanced lung diseases (NMALD), such as chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD), experience a high symptom burden over a prolonged period. Involvement of palliative care has been shown to improve symptom management, reduce hospital visits and enhance psychosocial support; however, optimal timing of referral is unknown. OBJECTIVE: The aim of this study was to identify the stage in the illness trajectory that patients with NMALD are referred to an ambulatory palliative care clinic. METHODS: A retrospective chart review was conducted on all patients with NMALD who attended a Supportive Care Clinic (SCC) between March 1, 2017 and March 31, 2019. RESULTS: Thirty patients attended the SCC during the study period. The most common diagnoses included COPD (36.7%), ILD (36.7%), and bronchiectasis (3.3%). At the time of initial consultation, the majority (89.4%) had Medical Research Council (MRC) class 4-5 dyspnea, however, only 1 patient had been prescribed opioids for management of breathlessness. Twenty-six patients had advance care planning discussions in the SCC. Phone appointments were a highly utilized feature of the program as patients had difficulty attending in-person appointments due to frailty and dyspnea. One-half of patients had at least 1 disease-related hospital admission in the previous year. Six patients were referred directly to home palliative care at their initial consultation. CONCLUSIONS: Referral to palliative care often occurs at late stages in non-malignant lung disease. Further, opioids for the management of dyspnea are significantly underutilized by non-palliative providers.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".