Tocchi, Christine

Introduction: Poor sleep contributes to outcomes in heart failure (HF). Phenotypes reflecting multi-dimensional sleep health may better predict outcomes and support more precise interventions than single measures, but few studies have used this approach. Aims: 1) Describe phenotypes of sleep health and 2) Evaluate whether sleep health phenotypes predict symptoms, cognitive function, and time to first hospitalization and emergency department (ED) visits among HF patients. Methods: We performed secondary analysis of a randomized controlled trial of cognitive behavioral therapy for insomnia compared with HF self-management education with HF patients. We measured sleep [rest-activity rhythms, sleep duration, and efficiency (2-week wrist actigraphy/follow-ups); insomnia; CPAP use; and daytime sleepiness (Epworth Scale)]; perceived stress; fatigue; anxiety; depression; pain; and cognitive ability (Patient-Reported Outcomes Measurement System: PROMIS) at baseline and 3, 6, and 12 months post-intervention and tracked hospitalizations and ED visits. We used K-means clustering to identify sleep phenotypes and generalized linear mixed models and Cox models to predict outcomes, adjusted for demographic factors. Results: Among 166 participants (M age = 63.2 (SD = 12.8) years; 57% female; 23% NYHA Class 3/4 HF; 35% EF less than 45%), there were 4 phenotypes [poor sleep (14%); short sleep/high sleep efficiency (39%); long sleep/low sleep efficiency (25%); and healthy sleep (21%)] at baseline. The healthy sleep group was older and had lower BMIs and less comorbidity and had better outcomes compared to all other phenotypes. In particular, this group had better fatigue (-2.43±0.87), pain (-1.86±1.05), anxiety (-1.50±0.89), stress (-1.46±0.69), and cognitive ability (1.76±0.80) than the poor sleep group. The poor sleep group had shorter time to adverse events compared to the other phenotypes (Hazard ratios of 0.41 to 0.56 for hospitalizations and 0.35 to 0.60 for ED visits). Conclusions: Multidimensional aspects of sleep predict HF outcomes and may improve on prediction with single measures. Future tailored sleep interventions focused on phenotypes may more precisely improve outcomes among HF patients than traditional approaches.

SummaryPeople with heart failure (HF) experience a high symptom burden and prevalent insomnia. However, little is known about daytime symptom trajectories after cognitive behavioural therapy for insomnia (CBT‐I). In this study we describe: (1) daytime symptom trajectories among adults with insomnia and stable HF over 1 year, (2) how symptom trajectories differ between CBT‐I versus HF self‐management interventions, and (3) associations between demographic, clinical, and sleep characteristics, perceived stress, health‐related quality of life (HRQoL), functional performance and daytime symptoms trajectories. We retrospectively analysed data from a randomised controlled trial of CBT‐I versus HF self‐management (NCT0266038). We measured sleep, perceived stress, HRQoL, and functional performance at baseline and symptoms at baseline, 3, 6, and 12 months. We conducted group‐based trajectory modelling, analysis of variance, chi‐square, and proportional odds models. Among 175 participants (mean [standard deviation] age 63.0 [12.9] years, 57.1% male, 76% White), we found four daytime symptom trajectories: (A) low improving symptoms (38.3%); (B) low psychological symptoms and high improving physical symptoms (22.8%); (C) high improving symptoms (24.0%); and (D) high not improving symptoms (14.9%). The CBT‐I versus the HF self‐management group had higher odds of belonging to Group A compared to other trajectories after controlling for baseline fatigue (odds ratio = 3.27, 95% confidence interval 1.39–7.68). The difference between the CBT‐I and the HF self‐management group was not statistically significant after controlling for baseline characteristics. Group D had the highest body mass index, perceived stress, and insomnia severity and the lowest cognitive ability, HRQoL, and functional performance. Research is needed to further evaluate factors contributing to symptom trajectories.

Abstract Introduction People with heart failure (HF) have frequent hospitalizations, and emergency department (ED) visits. We examined the effects of insomnia and rest-activity rhythms (RARs) on time to hospitalizations and ED visits after controlling for other known risk factors among participants in a randomized controlled trial of cognitive behavioral therapy for insomnia compared to heart failure self-management education (attention control). Methods The analysis included 168 HF patients who had available medical records for dates of hospitalization, ED visit, transplant, and death from a randomized clinical trial for insomnia of people with HF and insomnia. The known risk factors included age, sex, New York Heart Association (NYHA) Class, ejection fraction, and comorbid conditions. We used the insomnia severity index (ISI) and evaluated the strength of RAR using the ratio of the amplitude to the MESOR estimated with cosinor analysis with activity counts from a wrist-actigraph worn for at least five consecutive days. Cox proportional hazard models were used to examine ­insomnia and the RAR metrics with the known risk factors on time to first hospitalization, ED visit, transplant, and death. Results Eighty-five (50.1%) had at least one hospitalization, and ninety-one (54.2%) participants had an ED visit. Approximately 42% of the participants were admitted to the hospital due to cardiac events. Older age, male sex, higher NYHA, and greater comorbidity were associated with earlier hospitalization or ED visits. After controlling for those risk factors, stronger RAR was associated with later time to hospitalization, and ED visit with hazard ratios (HRs) of 0.26 (95% CI=[0.07, 0.91]) and 0.25 (95% CI=[0.07, 0.89]); higher insomnia severity (ISI ≥22) was associated with shorter time to ED visits, with an HR of 2.28 (95% CI=[1.19, 4.38]). Conclusion In addition to known demographic and clinical risk factors, insomnia severity and RAR predict hospitalizations and ED visits in people with HF. Further research is necessary to assess the biological mechanism of the associations and examine whether the effects of the risk factors could be modified by improving insomnia severity and RAR in people with HF. Support (if any) This study was financially supported by grants R01NR016191 and P20NR014126 from NIH/NINR.

Abstract Introduction Cognitive behavioral therapy for insomnia (CBT-I) improves individual symptoms of fatigue and daytime sleepiness; however, little is known how CBT-I improves multiple co-occurring daytime symptoms. The purposes of this study are to (1) identify daytime symptom trajectories in adults with insomnia and stable chronic heart failure (HF) over one year, and (2) determine how symptom trajectories vary based on participation in CBT-I or HF self-management education (attention control condition). Methods We conducted a retrospective analysis of data from a randomized controlled trial that looked the sustained effects of CBT-I compared to HF self-management over one year (NCT02660385). We measured daytime symptoms (fatigue, depression, anxiety, dyspnea, pain, and daytime sleepiness) at baseline (pre-treatment) and 3, 6 and 12 months. Symptom cluster trajectory were identified using group-based trajectory modeling, and the association with CBT-I was examined using logistic regressions. Results We randomized 175 participants (M age=63.0 (12.9) years, 57% men). We found four daytime symptom cluster trajectories, (A) low improving symptoms (N = 67, 38.3%); (B) low psychological symptoms and high improving physical symptoms (N = 40, 22.8%); (C), high improving symptoms (N = 42, 24.0%); and (D) high not improving symptoms (N = 26, 14.9%). There was no statistically significant difference between CBT-I and HF self-management across 4 symptom trajectories (p = .2509). However, people who received CBT-I vs. HF self-management education had higher odds of belonging to trajectory A compared to B/C/D after controlling for baseline fatigue (OR = 3.27 95% Confidence Intervals [1.39, 7.68]). Conclusion Most participants experienced improved daytime symptom profiles over 12 months after both interventions. Participants in the CBT-I group experienced symptom improvement even when they started with low symptoms. Support (if any) National Institute of Nursing Research [R01NR016191 and P20NR014126].