Prevalence Of Obstructive Sleep Apnea (Osa) Risk And Sleep Quality Of Life (Sqol) Among Copd Patients Of A Tertiary Care Hospital, Ludhiana, Punjab.
Bibliographic record
Abstract
Background: Chronic Obstructive Pulmonary Disease (COPD) is one of the most common and serious disorder which not only affect the individual physically but also the quality of life of the person to a higher extent. Obstructive sleep apnea (OSA) syndrome and (COPD) are two diseases that often coexist within an individual. Sleep-related disturbances and insomnia have been shown to be higher in COPD patients. Objective: The present study was conducted with an objective to assess the prevalence of obstructive sleep apnea risk and sleep quality of life among COPD patients.Methodology: A descriptive study was conducted on 100 stable COPD patients at medical OPD of DMC & Hospital, Ludhiana. The subjects were selected by convenience sampling technique. Modified Berlin questionnaire was used to check OSA risk and Quebec sleep questionnaire was used for assessing SQOL among the subjects. Data was collected by self-report method.Results: The findings revealed that 72% of COPD patients (Mean age 57.1± 1.70) were at high risk of OSA while 68% showed average sleep quality of life. There was a significant association between OSA risk and SQOL among COPD patients (p = 0.00). OSA risk was also associated with married (p=0.03), non working (0.01), presence of chronic illness (p=0.00), obese (p=0.00) and bigger neck circumference (p=0.00).Conclusion: It was concluded that there was high risk of obstructive sleep apnea in COPD patients and average sleep quality of life. There is a significant association of OSA risk and sleep quality of life among COPD patients. Therefore a protocol should be made to screen the COPD patients for OSA risk. Keywords: Obstructive sleep apnea risk, sleep quality of life, COPD patients.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".