Examination of prospective sleep across the menstrual cycle

Introduction: Women are twice as likely to develop insomnia across their lifetime compared with men. This may be explained, in part, by changes in hormones and menstrual cycle phase in reproductive-aged women. Intra- and inter-variability of menstrual cycle timing can make it difficult to accurately measure sleep quality and quantity in sleep research studies. This study aimed to examine the role of menstrual cycle phase in daily self-report and actigraphy-assessed sleep across two consecutive menstrual cycles. Materials and Methods: Fifty-one women (43% Caucasian) between the ages of 18 and 35 (m age = 23.67, SD = 4.68) completed continuous sleep monitoring via actigraphy and daily sleep diaries over two menstrual cycles (m days = 51.29). Cycles were identified via first date of menstrual bleeding and midcycle urinary ovulation testing and were coded into four phases: perimenstrual, mid-follicular, periovulatory, and mid-luteal. The perimenstrual phase was defined as the 3 days prior to and the first 3 days of menstrual bleeding. Within- and between-person relationships between menstrual phase and sleep parameters were estimated using multistep hierarchical linear modeling. Subjective and objective measures yielded the following sleep variables: Total Wake Time (TWTsub and TWTobj), Sleep Efficiency (SEsub and SEobj), and subjective sleepiness. Pandemic-related stress and daily US and region-specific COVID-19 case counts were included as covariates in adjusted models. Results: The sample had a mean a cycle length of 28.61 days (SD = 2.69). Regarding actigraphy data, menstrual phase predicted TWTobj and SEobj. Women spent 4-7 fewer minutes awake during the mid-follicular (m = 61.54, SE = 3.37) and mid-luteal phases (m = 63.11, SE = 3.29), compared to the perimenstrual phase (m = 67.54, SE = 3.37;p <.001). Sleep efficiency was higher in the mid-luteal phase (m = 82.50, SE = 0.79) compared to the perimenstrual phase (m = 80.71, SE = 0.82, p =.006). Subjective ratings indicated that during the perimenstrual phase women spent 8-16 minutes longer awake (m = 52.23, SE = 5.01, p <.001) and experienced reduced sleep efficiency of between 1-3 percentage points (m = 89.70, SE = 0.10, p <.001) compared to all other phases. Women also reported increased morning sleepiness in the perimenstrual (m = 4.71, SE = 0.21) compared to the periovulatory phase (m = 4.34, SE = 0.22, p =.02). Random coefficients models for objective and subjective sleep variables were nonsignificant, indicating that these relationships did not vary significantly between participants. Conclusions: To our knowledge, this is one of the first studies to examine subjective and objective sleep prospectively across two consecutive menstrual cycles. Disturbed sleep was highest in the perimenstrual phase. Future studies should measure menstrual cycle phase when investigating sleep in reproductive age women.

Bioconvertible IVC filters: safety, efficacy, and bioconversion times in a real-world cohort

Purpose: To examine the outcomes of patients with venous thromboembolism (VTE) who underwent placement of a bioabsorbable inferior vena cava filter (IVCF) for temporary pulmonary embolism (PE) protection Materials and Methods: From 10/1/2020 to 11/31/2021, 17 patients (mean age 71, range 45-92, 58% female) underwent placement of a bioabsorbable IVCF (Sentry, Boston Scientific) at a single academic center. Thirteen of the 17 filters (76.4%) were placed in the inpatient setting, and the remainder were placed outpatient. VTE risk factors included malignancy (70.6%), immobility (5.9%), COVID-19 (5.9%), and unprovoked (7.6%). Prior to IVCF, 11 patients presented with deep venous thrombosis (DVT) alone, two had PE alone, and four were diagnosed both DVT and PE. The contraindication to anticoagulation (AC) was active bleeding in 47.1% of the cohort, upcoming surgery in 41.2%, worsening of DVT on AC in 5.9%. and brain tumor in 5.9%. The pre-implantation infrarenal IVC diameter ranged from 1.6 to 2.6 cm. Technical success (TS), adverse events (AEs), and follow-up IVCF characteristics were recorded. Results: TS was 100%. No AEs occurred during placement. Mean follow-up period was 4.9 months (range 0-12.9). No new PEs were diagnosed after IVCF placement, and no patients required replacement of IVCF. Nine of the 17 patients had follow-up CTs after filter placement, two had follow up radiographs in which the filter state could be assessed, and the remaining six had no imaging evaluating the filter after placement. Asymptomatic IVCF associated non-occlusive thrombosis was seen in 3 patients. The longest amount of time after placement that a Sentry filter was observed to still be in the filter state was 3.9 months, and the shortest time in which imaging showed a filter bio-converted to the open state was 3.1 months. Three patients underwent serial imaging which incidentally demonstrated the timeframe in which the IVCF converted from a filter-state to an open-state. In one patient this conversion occurred between 2.1 and 3.1 months, in another between 1.7 and 3.3 months, and in the last patient between 3.9 and 4.4 months. Conclusion: In VTE patients with either a temporary contraindication to anticoagulation or a transitory high-PE-risk period, bioconvertible IVC filters are a safe and effective option for short-term protection against pulmonary embolism.

DEPRESSION, ANXIETY AND COPING-AVOIDANCE BEHAVIORS ASSOCIATED WITH LONG-TERM INSOMNIA SYMPTOMS DURING THE COVID-19 PANDEMIC

Introduction: Stressful events, such as the COVID-19 pandemic, can have long-lasting, detrimental effect on sleep. It is important for practitioners to understand how their patients may be stil experiencing residual negative effects of the pandemic to optimize their care. In this study we evaluated how measures of self-reported measures of anxiety and depression during the COVID-19 pandemic predicted measures of sleep disturbnce 6 months later among sleep medicine clinic patients. Methods: Between June-November 2020, 81 sleep medicine clinic patients (54.8±15.9 y, 44% male, 69% Caucasian) completed an online survey that included PROMIS measures (Sleep Disturbance, Sleep-Related Impairments, Informational Support, Emotional Distress-Anxiety) and Insomnia Severity Index (ISI). Patients were recontacted 6 months later to complete the same surveys. 54 patients (55.2±18.4 y, 39% male, 70% Caucasian) completed the follow-up survey and were included in this present analysis. We conducted multivariate regression analyses to determine how the change in self-reported PROMIS measures from baseline during the pandemic were predictive of post-pandemc 6 month follow-up PROMIS measures and ISI. Results: PROMIS depression score at baseline was predictive of both sleep disturbance (0.63 ± 0.15;p<.0001) and sleep impairment (0.49 ± 0.18;p=0.01) 6 months later. Baseline brief coping avoidance also predicted 6 month sleep disturbance (0.85 ± 0.33;p<0.009) and sleep impairment (0.85 ± 0.33;p=0.014) as well as ISI (0.52 ± 0.18 units;p=0.006). Baseline anxiety predicted ISI at 6 months (0.25 ± 0.09 units, p=0.009). Conclusion: Higher levels of self-reported depression, anxiety and coping-avoidance behaviors during the COVID-19 pandemic lead to long-lasting increase in sleep disturbance and impairment as well as insomnia. Addressing depression, anxiety and coping behaviors that occur as result as a stressful event is advised to avoid long-term detrimental effects on sleep.

CHANGES IN HEALTHCARE VISITS AND EXERCISE HABITS ASSOCIATED WITH POOR SLEEP IN SLEEP MEDICINE PATIENTS DURING THE COVID-19 PANDEMIC

Introduction: Patients may be experiencing increased stress and sleep disturbance due to healthcare and changes in daily habit during the COVID-19 pandemic. Healthcare changes may include telemedicine visits, delayed or canceled appointments and sleep studies. The purpose of this study was to assess the association between changes in healthcare and daily habits on sleep. Methods: Sleep medicine clinic patients completed an online survey during the pandemic and again 6 months later (December 2020 - May 2021), where they answered questions about COVID- 19 (COVID-19 vaccination and test results, changes in health care visits and habits during the pandemic), PROMIS measures (Sleep Disturbance, Sleep-Related Impairments), and Insomnia Severity Index (ISI). General linear regression model was performed using SAS to determine if changes in healthcare and daily habits predicted poorer sleep. Results: Among 81 patients who completed baseline survey, 54 (aged 55.2±18.4 y, 61% female, 70% Caucasian) completed the 6-month follow-up survey. Among them, 6% tested positive for COVID-19 and 83% were vaccinated. 30% changed their healthcare office appointments to telephone visits, 50% changed to video visits;whereas 22% cancelled and 30% rescheduled their healthcare appointments. At baseline, changes in health care visits had significant increase on ISI (3.98 ± 1.66, p=0.02). Upon follow-up, changes in health care visits had significant increase on ISI (4.77 ± 2.12, p=0.03) and Sleep Impairments (7.97 ± 3.83, p=0.04). A decrease in exercise predicted lower Sleep Disturbance (6.81 ± 3.31, p=0.04). Conclusion: Sleep medicine patients who reported changes in health care visits at baseline and 6-month follow up reported higher insomnia severity, and sleep-related impairments. Changes in healthcare had deleterious effects on sleep and should be considered when managing patients' healthcare. Unexpectedly, patients who reported a reduced level of exercise reported improved sleep. Pandemic public policies (e.g., gym closures) may have made it more difficult to exercise but allowed for greater opportunity to sleep.

INTERACTION OF SLEEP AND EMOTION ACROSS THE MENSTRUAL CYCLE

Introduction: Women experience increased risk for sleep and affective disorders compared to men, attributed in part to monthly oscillations in sex hormones. Emotional functioning worsens during the perimenstrual phase. There is increasing evidence that sleep continuity also decreases during this phase. Thus, this study examined the interactive effects of sleep and menstrual phase on emotion across two menstrual cycles in healthy women. Methods: Participants (N=51, 43% Caucasian) aged 18-35 (m=23.67) completed actigraphy and daily sleep/emotion diaries over two menstrual cycles (m days=51.29). Cycles were identified via date of menses and urinary ovulation detection, and coded into four phases: perimenstrual, mid-follicular, periovulatory, and mid-luteal. The perimenstrual phase was defined the 3 days prior to and the 3 days following menses onset. Variables included diary and actigraphic total wake time (TWT), daily ratings of positive (happy, calm, enthusiastic) and negative (angry, afraid, sad) affect using a 9-point scale. Relationships between phase, sleep, and emotion were estimated using multistep hierarchical linear modeling. Pandemic-related stress and daily US and region-specific COVID-19 case counts were included as covariates in adjusted models. Results: Mean menstrual cycle length was 28.61±2.69 days. Menstrual phase was first entered into models as predictors for sleep and emotion variables independently. The perimenstrual phase positively predicted anger (p<.001) but no other emotions. Additionally, the perimenstrual phase predicted higher rates of TWT, such that diary-reported TWT was 8-16 minutes longer during the perimenstrual (m=67.54, SE=3.37) compared to other phases (p<.001). Actigraphic TWT was also increased by 4-7 minutes (m=61.54, SE=3.37) in the perimenstrual phase (p<.001). A second model included the interaction term, TWT∗phase to the original model. Positive emotions were .05- .10 points lower (ps=.006-.02) when TWT was greater in the perimenstrual phase. Conclusion: Menstruating women experienced greater rates of anger and sleep disruption during the perimenstrual phase compared to other phases. When poor sleep occurred during the perimenstrual phase, however, women reported reduced positive emotions. Sleep disruptions, particularly occurring during the perimenstrual phase, may be an important intervention target for women at risk for affective disorders. Future studies should be mindful to assess menstrual phases when assessing sleep and circadian rhythm.

Changes in healthcare visits and sleep medication use in sleep medicine patients during the COVID-19 pandemic

Introduction: Patients may be experiencing increased stress and sleep disturbance due to healthcare changes during the COVID-19 pandemic. Healthcare changes may include telemedicine visits, delayed or canceled appointments and sleep studies. The purpose of this study was to assess the association between changes in healthcare and sleep medication use on sleep disturbance and insomnia severity. Methods: Between June-November 2020, 81 sleep medicine clinic patients (54.8 ± 15.9 y, 44% male, 69% Caucasian) completed an online survey that included questions about COVID-19 (tested for coronavirus, test results, willingness to be vaccinated for COVID-19, changes in health care visits and sleep medications during the pandemic), PROMIS measures (Sleep Disturbance, Sleep-Related Impairments), and Insomnia Severity Index (ISI). Stepwise linear regression was performed using SAS to determine if changes in healthcare and sleep medications predicted poorer sleep. Results: Among participants, 32% were tested for coronavirus, out of those 8% tested positive for COVID-19. 74% were willing to get vaccinated and 65% were willing to get their children vaccinated. 35% changed their healthcare office appointments to telephone visits, 54% changed to video visits;whereas 26% cancelled and 32% rescheduled their healthcare appointments. Changes in health care visits during the pandemic had a significant increase on ISI score (3.98 ± 1.66, p=0.019). Changes in sleep medication during the pandemic had significant effect on Sleep Disturbance (7.15 ± 2.51, p=0.005), Sleep- Related Impairments (8.69 ± 2.68, p=0.001) and ISI (6.04 ± 1.66, p=0.001) measures. Conclusion: Sleep medicine patients who reported changes in sleep medication reported higher insomnia severity, sleep disturbance, and sleep-related impairments. Patients who reported changes in healthcare visits during the pandemic reported higher insomnia severity. Assessing sleep medication changes and preference for healthcare visit format is advised when treating sleep medicine patients during the pandemic.

Association of social isolation, perceived stress, and cpap use in sleep medicine patients during the COVID-19 pandemic

Introduction: Due to the COVID-19 pandemic, many individuals are likely experiencing increased stress and social isolation. This study aimed to examine the effect of perceived stress and social isolation on self-reported continuous positive airway pressure (CPAP) use and treatment adherence among sleep medicine clinic patients during the pandemic. Methods: Between June-November 2020, 81 sleep medicine clinic patients (54.8±15.9y, 44% male, 69% Caucasian) completed an online survey that included self-reported changes in CPAP use and using CPAP as advised;and PROMIS Social Isolation and Perceived Stress Scale (PSS). CPAP measures were categorized based on reported changes during the pandemic. Stepwise logistic regression was performed using SAS to determine if Social Isolation and PSS predicted change in CPAP measures. Results: Among participants, 53% reported using CPAP. Out of those, 61% reported change, 16% reported no change, and 23% reported they do not know if there is a change in using CPAP as advised during the pandemic. Social Isolation predicted an increase in odds of CPAP use by a factor of 1.15 (p=0.024). PSS predicted a decrease in odds of using CPAP therapy as advised by a factor of 0.86 (p=0.049). Conclusion: Increases in perceived stress predicted lower odds of utilizing CPAP as advised. Increases in self-reported social isolation predicted greater odds of CPAP use in sleep medicine clinic patients during the COVID-19 pandemic. Addressing stressors/coping and social isolation/support as part of routine clinical care in sleep medicine clinic patients is advised.

Association of self-reported anxiety, informational support, and sleep in sleep medicine patients during the COVID-19 pandemic

Introduction: Stressful events, such as the COVID-19 pandemic, can have a detrimental effect on sleep. It is important for practitioners to understand how their patients are affected by events to optimize their care. In this study we evaluated associations of anxiety and daily habits with self-reported sleep disturbance among sleep medicine clinic patients. Methods: Between June-November 2020, 81 sleep medicine clinic patients (54.8±15.9 y, 44% male, 69% Caucasian) completed an online survey that included PROMIS measures (Sleep Disturbance, Sleep- Related Impairments, Informational Support, Emotional Distress- Anxiety) and Insomnia Severity Index (ISI). Patients were asked about changes in their daily habits (sunlight exposure, caffeine consumption). During the 5-month survey completion time window, the weekly average of positive COVID-19 cases in the Houston area was 2,914. Stepwise linear regression was performed using SAS to determine if self-reported anxiety and informational support predicted PROMIS Sleep Disturbance, PROMIS Sleep-Related Impairments and ISI. Results: Anxiety had a significant effect on Sleep Disturbance (0.43 ± 0.11, p=0.0001), Sleep-Related Impairments (0.53 ± 0.12, p=0.0001) and ISI (0.28 ± 0.08, p=0.0004). Informational support had a significant inverse effect on Sleep Disturbance (-0.29 ± 0.10, p=0.0063), Sleep-Related Impairments (-0.26 ± 0.11, p=0.01) and ISI (-0.31 ± 0.08, p<0.0001) measures. Decreased sunlight exposure during the pandemic contributed to a significant increase in Sleep Disturbance scores (0.06 ± 0.03, p=0.045). Increased caffeine consumption during the pandemic had significant increase in ISI scores (16.3 ± 7.59, p=0.035). Conclusion: Higher levels of anxiety and lower levels of informational support predicted greater insomnia severity, sleep disturbance, and sleep-related impairments in sleep medicine clinic patients during the COVID-19 pandemic. Decreased sunlight exposure and increased caffeine consumption also predicted greater sleep disturbance and insomnia severity, respectively. Addressing anxiety symptoms and access to accurate information during the pandemic is advised when treating sleep medicine clinic patients.