De Francesco, D;
Sabin, CA;
Winston, A;
Rueschman, MN;
Doyle, ND;
Anderson, J;
Vera, JH;
... Kunisaki, KM; + view all
(2021)
Sleep health and cognitive function among people with and without HIV: the use of different machine learning approaches.
Sleep
10.1093/sleep/zsab035.
(In press).
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Abstract
STUDY OBJECTIVES: We investigated associations between actigraphy-assessed sleep measures and cognitive function in people with and without HIV using different analytical approaches to better understand these associations and highlight differences in results obtained by these approaches. METHODS: Cognitive and 7-day/night actigraphy data were collected from people with HIV (PWH) and lifestyle-similar HIV-negative individuals from HIV and sexual health clinics in UK/Ireland. A global cognitive T-score was obtained averaging the standardized individual cognitive test scores accounting for socio-demographics. Average and standard deviation (SD) of eleven sleep measures over 7-days/nights were obtained. Rank regression, partial least-squares (PLS) regression, random forest, sleep dimension construct, and latent class analysis (LCA) were applied to evaluate associations between global T-scores and sleep measures. RESULTS: In 344 PWH (median age 57 years, 86% males), average sleep duration, efficiency and wake after sleep onset were not associated with global T-scores according to rank regression (p=0.51, p=0.09, p=0.16, respectively). In contrast, global T-scores associated with average and SD of length of nocturnal awakenings, SD of maintenance efficiency and average out-of-bed time when analyzed by PLS regression and random forest. No associations were found when using sleep dimensions or LCA. Overall, findings observed in PWH were similar to those seen in HIV-negative individuals (median age 61 years, 67% males). CONCLUSIONS: Using multivariable analytical approaches, measures of sleep continuity, timing and regularity were associated with cognitive performance in PWH, supporting the utility of newer methods of incorporating multiple standard and novel measures of sleep-wake patterns in assessment of health and functioning.
| Type: | Article |
|---|---|
| Title: | Sleep health and cognitive function among people with and without HIV: the use of different machine learning approaches |
| Location: | United States |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1093/sleep/zsab035 |
| Publisher version: | https://doi.org/10.1093/sleep/zsab035 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
| Keywords: | HIV, cognition, machine learning, sleep, sleep quality |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute for Global Health > Infection and Population Health |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10122378 |
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