Citations

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.

Introduction and background Key factors that relate to worse quality of life (QoL) in acute leukemia patients were identified in a global survey conducted by the Acute Leukemia Advocates Network (ALAN) such as age, gender, socioeconomic state, social functioning (e.g., worries about family and friends, feeling isolated, finances, etc.[ Pemberton-Whiteley et al, 2023]). These factors should be taken into consideration by healthcare professionals caring for acute leukemia patients to enable a robust support system. The role of patient organizations (PO) in the care of the patient and family is becoming increasingly important, however, patients are often not aware of the existence of POs and physicians and providers are often unsure of the role and benefits of PO, which then leads to a delay in patients reaching out to POs (for information, education resources, support resources [support groups, online chat, peer-to-peer support, financial support, psychological support, carer support], etc.). To date, there is limited evidence showing the importance of support offered to patients and their families. The ALAN, the Mayo Clinic and a national PO, are conducting a study that aims to assess both retrospectively and prospectively the benefits of active referrals to PO for patients with acute leukemia. Hypothesis We hypothesize that active referrals of adult patients with acute leukemia to PO at diagnosis has a positive impact on patient-reported outcomes and patient experience. Methods Here we present the study methodology that uses a quantitative method via administration of surveys at different timepoints. We plan to do both a retrospective and prospective evaluation of patients (target N=200) previously referred and new patients with a diagnosis of acute leukemia. There are 4 scenarios which are presented in Figure 1. For patients already diagnosed and evaluated at Mayo Clinic (scenarios 3 and 4), we will contact them either via email or portal message to see if they are interested in the study. A study consent form will be sent to them. If they indicate interest and consent, they will be contacted to understand whether they were referred to or sought help from PO around the time of their diagnosis or subsequently, and a questionnaire will be sent to them to assess if PO services helped them in their disease or treatment course. For newly diagnosed patients (scenarios 1 and 2), active referral to PO using PO referral online form will be provided and they will receive study consent form during their first visit at Mayo Clinic. A questionnaire will be sent to them to understand if they used the services from PO after the referral and if yes, to assess if PO services helped them in their disease or treatment course. In addition, every month from diagnosis up to 6 months, all patients who consented to take part in the study will be asked to complete the validated HM-PRO QoL assessment tool (an instrument designed to measure patient-reported outcomes in those with hematological malignancies), to assess QoL and symptoms and change over time. Conclusion This is a pilot study aiming at building evidence on the importance of support offered to patients and their families and demonstrating the impact of an active referral at diagnosis. 1 Pemberton-Whiteley Z, Nier S, Geissler J, Wintrich S, Verhoeven B, Christensen RO, Salek S, Oliva EN, Ionova T, Bradley J. Understanding quality of life in patients with acute leukemia, a global survey. J Patient Cent Res Rev. 2023;10:21-30