Cognitive impairment in patients with COPD
Bibliographic record
Abstract
Introduction: COPD is one of the most common respiratory disease in this era. Respiratory pysicians mostly manage COPD patients for their respiratory issues. Recent studies have shown that cognitive dysfunction is present in around 60% of the patients with COPD affecting their quality of life. Pulmonary rehabilitation seems to delay the decline in cognition. Aims and objectives: The aim of this study is to highlight the hidden burden of cognitive dysfuction in COPD patient. Early detection of cognitive impairment is important as clinicians can offer pulmonary rehabilitation to patients. Methods: This desriptive cross-sectional study was done in Pulmonology outpatient department of Fazaia Ruth Pfau Medical College for 6 months from May 2023 to October 2023. Sample size was 67 and patients were selected by non-probability consecutive sampling technique within the age bracket of 25 to 65 year. Diagnosed cases of COPD were taken. Spirometry was performed to grade them according to GOLD severity. Patients were classified into COPD groups using ABE assessment tool by taking into account exacerbation history and their functional status by mMRC grade. Patients cognitive dysfunction was assessed using Montreal cogntive assessment(MOCA) score. Results: Out of 67 patients, 12 were female and 55 were male with mean age of 49+-10 years. The congitive function assessed is as below: erj;66/suppl_69/PA1447/TB1 T1 TB1 Cognitive function No. of patients(n)% Normal 25(37.3%) Mild 22(32.8%) Moderate 16(23.9%) Severe 4(6.0%) Conclusion: Our study showed that cognitive impairment is associated with COPD especially in patients of advanced disease. Early assessment and intervention can improve patients' mental health.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".