Multimorbidity, frailty and chronic obstructive pulmonary disease
Bibliographic record
Abstract
The overwhelming majority of people with chronic obstructive pulmonary disease (COPD) have at least one coexisting medical condition often conceptualized as 'comorbidities'. These coexisting conditions vary in severity and impact; it is likely that for some patients, COPD is not their most important or severe condition. The concepts of multimorbidity and frailty may be useful to understand the broader needs of people with COPD undergoing pulmonary rehabilitation. Multimorbidity describes the coexistence of two or more chronic conditions, without reference to a primary condition. Best care for people with multimorbidity has been described as a shift from providing disease-focused to patient-centred care. Pulmonary rehabilitation is well placed to deliver such care as it focuses on optimizing function, encourages integration across care settings, values input from multidisciplinary teams and measures patient-important outcomes. When designing optimal pulmonary rehabilitation services for people with multimorbidity, the concept of frailty may be useful. Frailty focuses on impairments rather than medical conditions including impairments in mobility, strength, balance, cognition, nutrition, endurance, mood and physical activity. Emerging data suggest that frailty may be modifiable with pulmonary rehabilitation. The challenge for pulmonary rehabilitation clinicians is to broaden our perspective on the role and outcomes of pulmonary rehabilitation for people with multimorbidity.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".