Co-morbidity in older patients with COPD—its impact on health service utilisation and quality of life, a community study
Bibliographic record
Abstract
BACKGROUND: co-morbidity has been shown to be an important consideration in COPD with an estimated prevalence of 84%. In the Netherlands, a weak association between health-related quality of life and lung function has been found, with a closer link to co-morbidity. OBJECTIVE: to determine the influence of co-morbidity on quality of life and health service utilisation in older patients with COPD in the community. DESIGN: observational cohort study. SETTING: general practice in the North East of England that has a list size of 8300. PARTICIPANTS: 27 patients aged 70 years or above on the practice COPD register. MEASUREMENTS: data on age and sex, spirometry to confirm the diagnosis of COPD, questionnaires to assess quality of life, activities of daily living (ADLs) and co-morbidity. Health service utilisation was recorded by the number of primary and secondary care attendances in the previous year. RESULTS: 10 had mild, 12 had moderate, and 5 had severe disease. Mean age was 76 years. Quality of life (QOL), co-morbidity and health service utilisation measurements were not significantly different between COPD severity groups. There was a significant positive correlation between increasing co-morbidity and poor QOL (r = 0.45, P < 0.05), and significant negative correlation between co-morbidity and ADL scores (scored inversely), r = -0.54, P < 0.05. Significant negative correlation was found between co-morbidity and primary care attendances (r = -0.41, P < 0.05) and significant positive correlation between worsening QOL and secondary care attendances (r = 0.46, P < 0.05). CONCLUSIONS: co-morbidity has an important part to play in COPD assessment, more accurately reflecting QOL in our population. Health service utilisation did not correlate to forced expiratory volume (FEV1)-defined COPD severity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".