Sanford Auerbach

Background/Objectives: Obstructive sleep apnea (OSA) is diagnosed using pulse oximetry, which is less accurate in patients with darker skin. Two hypopnea definitions are in use: the American Academy of Sleep Medicine allows either (A) a 30% airflow decrease with a 3% oxygen desaturation or EEG arousal (“3% Rule”) or (B) a 30% airflow decrease with a 4% oxygen desaturation (“4% Rule”). The Centers for Medicare and Medicaid Services and many payers use only the 4% Rule. We hypothesized that patients from racial minority groups with darker skin tones would be less likely to qualify for OSA treatment using the 4% Rule compared to the 3% Rule. A secondary aim was to examine sex disparities. Methods: We reviewed records of adults undergoing overnight sleep studies at an urban academic hospital. Demographics, medical history, and comorbidities were collected. Analyses controlled for age, sex, BMI, anxiety, depression, hypertension, COPD, and smoking. Results: A total of 1354 records were analyzed. We found no racial or sex disparities in the proportion of participants who met the 3% but not the 4% Rule. After controlling for covariates, no racial group differed from White participants in meeting only the 3% Rule. However, female participants were significantly less likely than males to meet the 4% Rule. Conclusions: Despite known limitations of pulse oximetry associated with skin tone, no racial differences in the diagnosis of OSA were seen in this cohort. However, female patients had lower odds of meeting the 4% Rule, suggesting a potential barrier to treatment.

Background Insomnia is more common as people age. Several common hypnotics used to treat insomnia often do not adequately alleviate sleep issues in older adults and may be associated with negative residual effects such as an increased risk of falls, cognitive impairment, automobile accidents, and lack of response to auditory stimuli. The objective of these analyses of three clinical studies was to investigate the efficacy and safety of the dual orexin-receptor antagonist lemborexant (LEM) in older adults. Methods Study E2006-G000-304 (Study 304; NCT02783729) was a randomized, double-blind, placebo (PBO)-controlled, active-comparator trial where subjects with insomnia disorder received LEM 5 mg (LEM5), LEM 10 mg (LEM10), zolpidem tartrate extended-release 6.25 mg (ZOL), or PBO for 30 days. In crossover Study E2006-E044-106 (Study 106; NCT02583451), healthy subjects (good sleepers) received LEM 2.5 mg, LEM5, LEM10, or PBO for eight nights or zopiclone on days 1 and 8 (and PBO on days 2–7). In crossover Study E2006-A001-108 (Study 108; NCT03008447), healthy subjects received a single dose of LEM5, LEM10, PBO, or ZOL. Sleep assessments included polysomnography-based latency to persistent sleep (LPS), wake after sleep onset (WASO), WASO in the second half of the night (WASO2H), sleep efficiency, postural stability, middle-of-the-night and next-day cognitive performance, middle-of-the-night auditory awakening threshold and return-to-sleep latency, and driving performance. Results Overall, 453 of 1006 (45%; Study 304), 24 of 48 (50%; Study 106), and 28 of 56 (50%; Study 108) subjects were aged ≥ 65 years. In Study 304, LEM decreased (improved) LPS, WASO, and WASO2H from baseline more than ZOL and PBO; subjects treated with LEM had greater increases in sleep efficiency (improved) than with ZOL or PBO. In both Studies 304 and 108, postural stability was not impaired at waketime in subjects who received LEM compared with PBO. At waketime, LEM did not impair memory compared with PBO. In Study 108, following middle-of-the-night awakening, LEM and ZOL did not affect subjects’ ability to awaken to auditory stimuli; LEM did not affect tests of memory and attention. In Study 106, LEM did not impair next-day driving performance in healthy elderly compared with PBO. LEM was well tolerated in subjects aged ≥ 65 years. Conclusions LEM provided benefits on sleep variables without next-morning residual effects in subjects aged ≥ 65 years, supporting LEM as a treatment option for older adults with insomnia. Trial Registration Numbers and Dates of Registration Study 304: ClinicalTrials.gov identifier, NCT02783729, date of registration, 26 May 2016. Study 106: ClinicalTrials.gov identifier, NCT02583451, date of registration, 22 October 2015. Study 108: ClinicalTrials.gov identifier, NCT03008447, date of registration, 2 January 2017.

Background: The digital Clock Drawing Test (dCDT) has been recently used as a more objective tool to assess cognition. However, the association between digitally obtained clock drawing features and structural neuroimaging measures has not been assessed in large population-based studies. Objective: We aimed to investigate the association between dCDT features and brain volume. Methods: This study included participants from the Framingham Heart Study who had both a dCDT and magnetic resonance imaging (MRI) scan, and were free of dementia or stroke. Linear regression models were used to assess the association between 18 dCDT composite scores (derived from 105 dCDT raw features) and brain MRI measures, including total cerebral brain volume (TCBV), cerebral white matter volume, cerebral gray matter volume, hippocampal volume, and white matter hyperintensity (WMH) volume. Classification models were also built from clinical risk factors, dCDT composite scores, and MRI measures to distinguish people with mild cognitive impairment (MCI) from those whose cognition was intact. Results: A total of 1656 participants were included in this study (mean age 61 years, SD 13 years; 50.9% women), with 23 participants diagnosed with MCI. All dCDT composite scores were associated with TCBV after adjusting for multiple testing (P value <.05/18). Eleven dCDT composite scores were associated with cerebral white matter volume, but only 1 dCDT composite score was associated with cerebral gray matter volume. None of the dCDT composite scores was associated with hippocampal volume or WMH volume. The classification model for differentiating MCI and normal cognition participants, which incorporated age, sex, education, MRI measures, and dCDT composite scores, showed an area under the curve of 0.897. Conclusions: dCDT composite scores were significantly associated with multiple brain MRI measures in a large community-based cohort. The dCDT has the potential to be used as a cognitive assessment tool in the clinical diagnosis of MCI.

Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet #Preprint #PeerReviewMe: Warning: This is a unreviewed preprint. Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn. Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period. Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author). Background: The digital Clock Drawing Test (dCDT) has been recently used as a more objective tool to assess cognition. However, the association between digitally obtained clock drawing features and structural neuroimaging measures has not been assessed in large population-based studies. Objective: We aimed to investigate the association between dCDT features and brain volume. Methods: This study included participants from the Framingham Heart Study who had both a dCDT and magnetic resonance imaging (MRI) scan, and were free of dementia or stroke. Linear regression models were used to assess the association between 18 dCDT composite scores (derived from 105 dCDT raw features) and brain MRI measures, including total cerebral brain volume (TCBV), cerebral white matter volume, cerebral gray matter volume, hippocampal volume, and white matter hyperintensity (WMH) volume. Classification models were also built from clinical risk factors, dCDT composite scores, and MRI measures to distinguish people with mild cognitive impairment (MCI) from those whose cognition was intact. Results: A total of 1656 participants were included in this study (mean age 61 years, SD 13 years; 50.9% women), with 23 participants diagnosed with MCI. All dCDT composite scores were associated with TCBV after adjusting for multiple testing (P value <.05/18). Eleven dCDT composite scores were associated with cerebral white matter volume, but only 1 dCDT composite score was associated with cerebral gray matter volume. None of the dCDT composite scores was associated with hippocampal volume or WMH volume. The classification model for differentiating MCI and normal cognition participants, which incorporated age, sex, education, MRI measures, and dCDT composite scores, showed an area under the curve of 0.897. Conclusions: dCDT composite scores were significantly associated with multiple brain MRI measures in a large community-based cohort. The dCDT has the potential to be used as a cognitive assessment tool in the clinical diagnosis of MCI.

Sleep disordered breathing (SDB) is highly prevalent, but frequently unrecognized among stroke patients. Polysomnography (PSG) is difficult to perform soon after a stroke. We evaluated the use of screening questionnaires and portable sleep testing (PST) for patients with acute stroke, subarachnoid hemorrhage, or transient ischemic attack to expedite SDB diagnosis and management. We performed a single-center retrospective analysis of a quality improvement study on SDB screening of consecutive daytime, weekday, adult admissions to a stroke unit. We excluded patients who were unable to communicate and lacked available family members. Patients were screened with the Epworth Sleepiness Scale, Berlin Questionnaire, and STOP-BANG Questionnaire and underwent overnight PST and/or outpatient PSG. The 4-item STOP Questionnaire was derived from STOP-BANG for a secondary analysis. We compared the sensitivity and specificity of the questionnaires for the diagnosis of at least mild SDB (apnea hypopnea index (AHI) ≥5) on PST and correlated AHI measurements between PST and PSG using the Spearman correlation. Out of sixty-eight patients included in the study, 54 (80%) were diagnosed with SDB. Only one (1.5%) had a previous SDB diagnosis. Thirty-three patients completed all questionnaires and a PST. The STOP-BANG questionnaire had the highest sensitivity for at least mild SDB (0.81, 95% CI (confidence interval): 0.65–0.92) but a low specificity (0.33, 95% CI 0.10, 0.65). The discrimination of all questionnaires was overall poor (C statistic range 0.502–0.640). There was a strong correlation (r = 0.71) between the AHI results estimated using PST and outpatient PSG among 28 patients. The 4-item STOP Questionnaire was the easiest to administer and had a comparable or better sensitivity than the other questionnaires. Inpatient PSTs were useful for screening in the acute setting to facilitate an early diagnosis of SDB and to establish further outpatient evaluations with sleep medicine.

Circadian rhythms are maintained by a complex “system of systems” that continuously coordinates biological processes with each other and the environment. Although humans predominantly entrain to solar time, individual persons vary in their precise behavioral timing due to endogenous and exogenous factors. Endogenous differences in the timing of individual circadian rhythms relative to a common environmental cue are known as chronotypes, ranging from earlier than average (Morningness) to later than average (Eveningness). Furthermore, individual behavior is often constrained by social constructs such as the 7-day week, and the “sociogenic” impact our social calendar has on our behavioral rhythms is likely modified by chronotype. Our aim in this study was to identify and characterize differences in sleep and rest-activity rhythms (RAR) between weekends and weekdays and between-chronotypes. Male volunteers (n = 24, mean age = 23.46 y) were actigraphically monitored for 4 weeks to derive objective behavioral measures of sleep and RARs. Chronotype was assessed through self-report on the Morningness-Eveningness Questionnaire. Sleep characteristics were derived using Actiware; daily rest-activity rhythms were modeled using a basic 3-parameter cosinor function. We observed that both Eveningness and Morningness Chronotypes were more active and slept later on the weekends than on weekdays. Significant between-chronotype differences in sleep timing and duration were observed within individual days of the week, especially during transitions between weekends and the workweek. Moreover, chronotypes significantly varied in their weekly rhythms: e.g. Morningness Chronotypes generally shifted their sleep duration, timing and quality across work/rest transitions quicker than Eveningness Chronotypes. Although our results should be interpreted with caution due to the limitations of our cosinor model and a homogenous cohort, they reinforce a growing body of evidence that day of the week, chronotype and their interactions must be accounted for in observational studies of human behavior, especially when circadian rhythms are of interest.

Background: The Clock Drawing Test (CDT) has been widely used in clinic for cognitive assessment. Recently, a digital Clock Drawing Text (dCDT) that is able to capture the entire sequence of clock drawing behaviors was introduced. While a variety of domain-specific features can be derived from the dCDT, it has not yet been evaluated in a large community-based population whether the features derived from the dCDT correlate with cognitive function. Objective: We aimed to investigate the association between dCDT features and cognitive performance across multiple domains. Methods: Participants from the Framingham Heart Study, a large community-based cohort with longitudinal cognitive surveillance, who did not have dementia were included. Participants were administered both the dCDT and a standard protocol of neuropsychological tests that measured a wide range of cognitive functions. A total of 105 features were derived from the dCDT, and their associations with 18 neuropsychological tests were assessed with linear regression models adjusted for age and sex. Associations between a composite score from dCDT features were also assessed for associations with each neuropsychological test and cognitive status (clinically diagnosed mild cognitive impairment compared to normal cognition). Results: The study included 2062 participants (age: mean 62, SD 13 years, 51.6% women), among whom 36 were diagnosed with mild cognitive impairment. Each neuropsychological test was associated with an average of 50 dCDT features. The composite scores derived from dCDT features were significantly associated with both neuropsychological tests and mild cognitive impairment. Conclusions: The dCDT can potentially be used as a tool for cognitive assessment in large community-based populations.

BACKGROUND The Clock Drawing Test (CDT) has been widely used in clinic for cognitive assessment. Recently, a digital Clock Drawing Text (dCDT) that is able to capture the entire sequence of clock drawing behaviors was introduced. While a variety of domain-specific features can be derived from the dCDT, it has not yet been evaluated in a large community-based population whether the features derived from the dCDT correlate with cognitive function. OBJECTIVE We aimed to investigate the association between dCDT features and cognitive performance across multiple domains. METHODS Participants from the Framingham Heart Study, a large community-based cohort with longitudinal cognitive surveillance, who did not have dementia were included. Participants were administered both the dCDT and a standard protocol of neuropsychological tests that measured a wide range of cognitive functions. A total of 105 features were derived from the dCDT, and their associations with 18 neuropsychological tests were assessed with linear regression models adjusted for age and sex. Associations between a composite score from dCDT features were also assessed for associations with each neuropsychological test and cognitive status (clinically diagnosed mild cognitive impairment compared to normal cognition). RESULTS The study included 2062 participants (age: mean 62, SD 13 years, 51.6% women), among whom 36 were diagnosed with mild cognitive impairment. Each neuropsychological test was associated with an average of 50 dCDT features. The composite scores derived from dCDT features were significantly associated with both neuropsychological tests and mild cognitive impairment. CONCLUSIONS The dCDT can potentially be used as a tool for cognitive assessment in large community-based populations.

Background: Although some neuropsychological (NP) tests are considered more central for the diagnosis of Alzheimer disease (AD), there is a lack of understanding about the interaction between different cognitive tests. Objective: This study aimed to demonstrate a global view of hierarchical probabilistic dependencies between NP tests and the likelihood of cognitive impairment to assist physicians in recognizing AD precursors. Methods: Our study included 2091 participants from the Framingham Heart Study. These participants had undergone a variety of NP tests, including Wechsler Memory Scale, Wechsler Adult Intelligence Scale, and Boston Naming Test. Heterogeneous cognitive Bayesian networks were developed to understand the relationship between NP tests and the cognitive status. The performance of probabilistic inference was evaluated by the 10-fold cross validation. Results: A total of 4512 NP tests were used to build the Bayesian network for the dementia diagnosis. The network demonstrated conditional dependency between different cognitive functions that precede the development of dementia. The prediction model reached an accuracy of 82.24%, with sensitivity of 63.98% and specificity of 92.74%. This probabilistic diagnostic system can also be applied to participants that exhibit more heterogeneous profiles or with missing responses for some NP tests. Conclusions: We developed a probabilistic dependency network for AD diagnosis from 11 NP tests. Our study revealed important psychological functional segregations and precursor evidence of AD development and heterogeneity.

BACKGROUND Although some neuropsychological (NP) tests are considered more central for the diagnosis of Alzheimer disease (AD), there is a lack of understanding about the interaction between different cognitive tests. OBJECTIVE This study aimed to demonstrate a global view of hierarchical probabilistic dependencies between NP tests and the likelihood of cognitive impairment to assist physicians in recognizing AD precursors. METHODS Our study included 2091 participants from the Framingham Heart Study. These participants had undergone a variety of NP tests, including Wechsler Memory Scale, Wechsler Adult Intelligence Scale, and Boston Naming Test. Heterogeneous cognitive Bayesian networks were developed to understand the relationship between NP tests and the cognitive status. The performance of probabilistic inference was evaluated by the 10-fold cross validation. RESULTS A total of 4512 NP tests were used to build the Bayesian network for the dementia diagnosis. The network demonstrated conditional dependency between different cognitive functions that precede the development of dementia. The prediction model reached an accuracy of 82.24%, with sensitivity of 63.98% and specificity of 92.74%. This probabilistic diagnostic system can also be applied to participants that exhibit more heterogeneous profiles or with missing responses for some NP tests. CONCLUSIONS We developed a probabilistic dependency network for AD diagnosis from 11 NP tests. Our study revealed important psychological functional segregations and precursor evidence of AD development and heterogeneity.