Maiti, Dolly

Abstract Background The implications of poor sleep for cardiovascular disease risk are increasingly recognised. Although previous research has focused on clinical sleep disorders, emerging evidence highlights the relevance of subclinical sleep aspects for cardiovascular health. Sleep midpoint, an index of sleep timing and a proxy of circadian phase, has been shown to be associated with markers of cardiometabolic risk, including obesity, in the general population. Purpose We aimed to assess whether sleep midpoint was related to body composition measures in patients with coronary heart disease enrolled in cardiac rehabilitation (CR). Methods Study participants were recruited from the patient population referred to our CR center for acute coronary syndrome or coronary revascularisation. Shift work was exclusionary. Participants underwent sleep testing prior to entering the CR program, including completion of one week of wrist actigraphy and sleep log. Using actigraphy-derived sleep metrics, sleep midpoint was calculated as the middle time (hh:mm) between bedtime and wake up time for each individual night, and averaged across the monitoring week. Based on the median sleep midpoint of the sample, participants were categorised as having early (before 2:42) or late (after 2:42) sleep midpoint. Body composition and regional fat distribution were determined by whole-body dual-energy absorptiometry (DEXA). Between-group characteristics were compared using independent t-test, Mann-Whitney U test and Chi-square statistics as appropriate. Linear regression was used to test the association between sleep midpoint and body fat measures. Results Thirty-one participants (26 males, 64.7±12.5 years) completed both actigraphy and DEXA assessments. Demographics, lifestyle, and clinical characteristics were similar between patients with early sleep midpoint (n=15; sleep midpoint, hh:mm: 2:00, range 0:57 to 2:41) and patients with late sleep midpoint (n=16; sleep midpoint 3:18, range 2:42 to 4:17). Despite comparable body mass index between groups (p=0.21), patients with late sleep midpoint had significantly higher total body fat percentage (p=0.017), android fat percentage (p=0.015), and gynoid fat percentage (p=0.045). Late sleep midpoint remained significantly associated with adiposity measures in age- and sex-adjusted analysis (total body fat percentage, beta = 0.371, 95% CI 0.063 to 0.68; android fat percentage, beta = 0.394, 95% CI 0.078 to 0.71; gynoid fat percentage, beta = 0.301, 95% CI 0.007 to 0.596). Conclusions Late sleep midpoint was associated with excess adiposity in patients with coronary heart disease enrolled in CR. These findings support the predictive value of sleep timing for cardiometabolic risk and emphasise the importance of objective sleep assessment for secondary prevention.

Background: Sleep regularity is emerging as an independent determinant of health. Multiple studies suggest a link between increased variability in sleep duration and timing and adverse cardiovascular, metabolic, and cognitive outcomes. There is, however, a lack of data on the implications of sleep regularity for aerobic capacity and physical endurance, particularly in patients with established cardiovascular disease. This study seeks to investigate the influence of irregularity in sleep duration on functional capacity in patients with coronary artery disease (CAD) undergoing cardiac rehabilitation (CR). Methods: We recruited a sample of patients with CAD who were referred to CR at Mayo Clinic Rochester. Participants completed a 6-minute walk test (6MWT) upon enrollment into CR. 6MWT variables included distance walked (meters), predicted distance walked (percentage) and estimated metabolic equivalents (METs). 24-hour objective sleep quality and quantity were assessed over a 7-day period by wrist actigraphy. Average standard deviation (SD) of sleep duration was used to define sleep regularity, with SD >60 minutes indicating irregular sleep. Chi-square test, independent samples t-test, and linear regression were used for statistical analysis. Results: Twenty-eight participants with valid actigraphy and 6MWT were included in this analysis (eight females; mean age 67.4 ± 11.6 years; body mass index 31.1 ± 5.8 kg/m 2 ). The average total sleep time was 7.1 ± 1.2 hours, and 10 participants (35.7%) exhibited sleep duration SD >60 minutes. Demographic, clinical and sleep characteristics were comparable between the regular and irregular sleep groups. Compared to patients with regular sleep, those with irregular sleep had poorer 6MWT, with shorter distance walked (406.2 ± 81.2 meters vs 338.8 ± 80.7 meters; p = 0.045), lower % of predicted distance walked (87.1 ± 18.7% vs 69.2 ± 11.4%; p = 0.011), and lower METS (2.99 ± 0.36 vs 2.63 ± 0.38; p = 0.022). Irregular sleep remained significantly associated with performance at the 6MWT after taking into account age and sex, with patients walking 14.4 meters fewer with every 10-minute increase in sleep variability (95% CI -28.1, -0.7; p 0.041). Conclusions: Increased day-to-day fluctuation in sleep duration is associated with reduced exercise capacity in patients with CAD undergoing CR. These findings add to the mounting body of evidence linking irregular sleep patterns to heightened cardiovascular risk, and support the integration of sleep monitoring in the CR practice to enhance risk stratification and outcome prediction. Funding Source: Sleep Number Corp. This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.

Introduction: Sleep duration is now recognized as an important determinant of cardiovascular (CV) health. Recently, the CV implications of day-to-day variability in sleep duration have become apparent, with irregular sleep duration associated with increased risk of CV disease, including hypertension. However, the relationship between sleep duration variability and ambulatory blood pressure (BP) patterns in the general population or in patients with CV disease is unknown. Research Questions: We sought to investigate whether irregular sleep duration is associated with aberrant ambulatory BP or heart rate (HR) profiles in patients undergoing cardiac rehabilitation (CR). Methods: We recruited a sample of 42 patients with coronary artery disease enrolled in CR at Mayo Clinic Rochester. Participants underwent 24-hour ambulatory BP monitoring and sleep assessment including one week of wrist actigraphy and sleep diary prior to entering CR. Twenty-four hour, awake, and asleep averages were calculated for systolic BP, diastolic BP, and HR. Nocturnal dipping and morning surge were also computed for BP and HR. Sleep regularity was quantified by SD of actigraphy-derived sleep duration and irregular sleep duration was defined as SD >1 hour. Chi-square tests and Mann-Whitney U tests were used to compare groups. Results: Thirty-six participants (22% females, median age [25 th ,75 th IQR] 66.5 [61,75.8] years, body mass index 31.7 [26.9,35.1] kg/m 2 ) had valid actigraphy and ambulatory BP recordings. We found sleep duration SD >1 hour in 36% of them. Demographics and average sleep duration were similar between those with irregular and regular sleep duration (all Ps>0.11). Twenty-four-hour, awake and asleep HR values were comparable between groups (all Ps>0.26). Participants with irregular sleep duration exhibited lower nocturnal HR dipping (9.2 [3.1,11.6] % vs 12.9 [8.9,18.2] %, P=0.019) than their counterparts with regular sleep. Morning HR surge was also attenuated in patients with irregular sleep duration (3 [-1,9] bpm vs 10 [7,14] bpm, P=0.006). Ambulatory SBP and DBP measures did not differ significantly between groups (all Ps>0.17). Conclusions: High day-to-day variability in sleep duration is linked to blunted nocturnal dipping and morning surge in HR in patients with coronary artery disease enrolled in CR. Because altered ambulatory HR profile predicts unfavorable CV outcomes, evaluation of sleep patterns in the CR setting may yield important prognostic information.

Abstract Deep vein thrombosis (DVT) is the formation of thrombosis or blood clot in the deep veins of the body, usually in the lower extremities or pelvic vein. During this time, a hypercoagulable state results in a higher rate of deep vein thrombosis (DVT) and pulmonary embolism (PE) during gestation and the postnatal stage. PE is the leading cause of maternal death, making early diagnosis and clinical treatment vital to both the mother’s and fetal life. The current technologies for the diagnosis of DVT reduced detection accuracy with increased depth, false negatives when parallel veins are present, and the incompetence of imaging due to factors such as obesity and edema. The drawback of compression ultrasound is that clots may emboli during diagnosis and travel to vital organs such as the heart. In this study a new technological advancement is explored to superior diagnostic methods, and a near infrared device will be able to provide relative measurements of the oxygenation levels of calf veins and can help identify excessive deoxygenation and specific locations. Oxyhemoglobin & deoxyhemoglobin absorbs red light and infra-red lights differently. Oxygenated blood gets absorbed by IR light while deoxygenated gets transmitted. When infrared light is emitted onto a vein, it gets absorbed by the oxygenated hemoglobin and gives an absorbance ratio of output to the input close to 1. Infrared radiation spectroscopy measurements can indicate Δ½HbO2 and Δ½Hb to show a comparison, helping to indicate the presence or absence of a clot. . The circuit is designed with capacitors, resistors, and transistors to act as filters and triggers to pulsate at 20Hz, to pick up biological signals. An Arduino Uno microcontroller helped to process data in order to analyze signal proximity to 0 or 1 to classify DVT and validate the efficacy of using IR for DVT detection Testing of the device allowed for a functionality check to understand whether it was able to pick up signals of oxygenation levels. The 3 tests have insight on the potential of the device; however, the results were inconclusive, due to a lack of sufficient testing. The limitation has been the inability to test on a large sample size and insufficient data, therefore it can’t be said for now whether IR is an effective way of diagnosing DVT. However, since on localized testing, the device seems to be gathering programmed signals, the research can be furthered, and the efficacy can be proved by testing on expecting patients.