Prevalence and risk factors of sleep disturbances in a large HIV‐infected adult population
Bibliographic record
Abstract
INTRODUCTION: Sleep disturbances are frequently reported in HIV-infected patients but there is a lack of large studies on prevalence and risk factors, particularly in the context of current improved immuno-clinical status and use of the newest antiretrovirals (ARV). METHOD: Cross-sectional study to evaluate the prevalence and factors associated with sleep disturbance in adult HIV-infected patients in six French centres of the region "Pays de la Loire". Patients filled a self-administered questionnaire on their health behaviour, sleep attitudes (Pittsburgh Sleep Quality Index PSQI), quality of life (WHO QOL HIV BREF questionnaire) and depression (Beck depression Inventory (BDI)-II questionnaire). Socio-demographic and immunovirologic data, medical history, ARVs were collected. RESULTS: From November 2012 to May 2013, 1354 consecutive non-selected patients were enrolled. Patients' characteristics were: 73.5% male, median age 47 years, active employment 56.7%, France-native 83% and Africa-native 14.7%, CDC stage C 21%, hepatitis co-infection 13%, lipodystrophy 11.8%, dyslipidemia 20%, high BP 15.1%, diabetes 3%, tobacco smokers 39%, marijuana and cocaine users, 11.7% and 1.7% respectively, and excessive alcohol drinkers 9%. Median (med) duration of HIV infection was 12.4 years, med CD4 count was 604/mm(3); 94% of Patients were on ARVs, 87% had undetectable viral load. Median sleeping time was 7 hours. Sleep disturbances (defined as PSQI score >5) were observed in 47% of the patients, more frequently in female (56.4%) than in male (43.9%) (p<0.05) and moderate to serious depressive symptoms (BDI score>19) in 19.7% of the patients. In multivariate analysis, factors associated with sleep disturbances (p<0.05) were depression (odds ratio [OR] 4.6; 95% confidence interval [CI] 3.2-6.8), male gender (OR 0.7; CI 0.5-0.9), active employment (OR 0.7; CI 0.5-0.9), living single (OR 1.5; CI 1.2-2.0), tobacco-smoking (OR 1.3; CI 1.0-1.8), duration of HIV infection (>10 vs. <10 y.) (OR 1.5; CI 1.1-2.0), ARV regimen containing nevirapine (OR 0.7; CI 0.5-0.9) or efavirenz (OR 0.5; CI 0.3-0.7). CONCLUSIONS: Prevalence of sleep disturbances is high in this HIV population and roughly similar to the French population. Associated factors are rather related to social and psychological status than HIV infection. Depression is frequent and should be taken in care to improve sleep quality.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".