Background Reports of subjective sleep quality are frequently collected in research and clinical practice. It is unclear, however, how well polysomnographic measures of sleep correlate with subjective reports of prior-night sleep quality in elderly men and women. Furthermore, the relative importance of various polysomnographic, demographic and clinical characteristics in predicting subjective sleep quality is not known. We sought to determine the correlates of subjective sleep quality in in older adults using more recently developed machine learning algorithms that are suitable for selecting and ranking important variables. Methods Community-dwelling older men (n=1024) and women (n=459), a subset of those participating in the Osteoporotic Fractures in Men study and the Study of Osteoporotic Fractures study, respectively, completed a single night of at-home polysomnographic recording of sleep followed by a set of morning questions concerning the prior night's sleep quality. Questionnaires concerning demographics and psychological characteristics were also collected prior to the overnight recording and entered into multivariable models. Two machine learning algorithms, lasso penalized regression and random forests, determined variable selection and the ordering of variable importance separately for men and women. Results Thirty-eight sleep, demographic and clinical correlates of sleep quality were considered. Together, these multivariable models explained only 11-17% of the variance in predicting subjective sleep quality. Objective sleep efficiency emerged as the strongest correlate of subjective sleep quality across all models, and across both sexes. Greater total sleep time and sleep stage transitions were also significant objective correlates of subjective sleep quality. The amount of slow wave sleep obtained was not determined to be important. Conclusions Overall, the commonly obtained measures of polysomnographically-defined sleep contributed little to subjective ratings of prior-night sleep quality. Though they explained relatively little of the variance, sleep efficiency, total sleep time and sleep stage transitions were among the most important objective correlates.
Pneumocystis causes pneumonia in immunodeficient hosts but also likely causes infection in healthy hosts. To characterize infection in healthy mice, we developed and validated a real-time polymerase chain reaction assay for quantitation of Pneumocystis carinii f. sp. muris. In healthy mice exposed to Pneumocystis-infected animals, organisms were first detected at 2-3 weeks, peaked at 5-6 weeks, and were cleared by 7-9 weeks. The peak organism load in healthy animals was 2-3 logs lower than that in immunodeficient animals. This approach should facilitate studies of anti-Pneumocystis immune mechanisms in healthy hosts and provide insights into the development of Pneumocystis pneumonia in immunodeficient hosts.
Background Scheduled exposure to bright light (phototherapy) has been used, with varying degrees of success, to treat sleep disruption in older individuals. Most of these studies have been done in institutional settings and have used several hours of daily light exposure. Such a regimen in the home setting may be untenable, especially when the individual with the sleep disruption has memory impairment and is being cared for by a family member. As such, we examined the effectiveness of a “user-friendly” phototherapy protocol that would be readily usable in the home environment. Methods We exposed a group of 54 older caregiver/care recipient dyads, in which the care recipient had a memory impairment, to two weeks of morning bright light phototherapy. Dyads were exposed to either bright white (~4,200 lux) or dim red (~90 lux) light for 30 minutes every day, starting within 30 minutes of arising. All subjects also received sleep hygiene therapy. Objective (actigraphy) and subjective measures of sleep and mood were obtained at baseline and at the end of the two weeks of phototherapy. Results In care recipients, actigraphy- and log-determined time in bed and total sleep time declined in the active condition (p<0.05, ANOVA); there was no corresponding change in subjective insomnia symptoms (p’s>0.37, ANOVA). The decrease in time in bed was associated with an earlier out of bed time in the morning (p<0.001, Pearson correlation). The decrease in total sleep time was associated with a decrease in sleep efficiency (p<0.001, Pearson correlation) and an increase in wake after sleep onset (p<0.001, Pearson correlation). In caregivers, there were no differential changes in actigraphic measures of sleep (p’s>0.05, ANOVA). Actigraphy-measured wake after sleep onset and sleep efficiency did, however, improve in both conditions, as did sleepiness, insomnia symptoms, and depressive symptomatology (p’s<0.05, ANOVA). Conclusions Exposure to this regimen of phototherapy diminished sleep in older individuals with memory impairments. Their caregivers, however, experienced an improvement in sleep and mood that appeared independent of the phototherapy and likely due to participation in this protocol or the sleep hygiene therapy.
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