A Broken Heart and Windy Nights: Single Center Results of Inpatient Sleep Studies and Interventions in Hospitalized Heart Failure Patients
by
,
Justin N. Durland
1, 
Frank Hoyland
2,
John Elliott Epps
3,
Mathew J. Gregoski
4
,
Jacqueline Angles
2 and
Gregory R. Jackson
5,* 1
Department of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
2
Department of Medicine, Division of Pulmonary and Sleep Medicine, Medical University of South Carolina, Charleston, SC 29425, USA
3
Wofford College, Spartanburg, SC 29303, USA
4
Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
5
Department of Medicine, Division of Cardiology, Medical University of South Carolina, Charleston, SC 29425, USA
*
Author to whom correspondence should be addressed.
Therapeutics 2025, 2(1), 1; https://doi.org/10.3390/therapeutics2010001
Submission received: 29 August 2024
/
Revised: 31 December 2024
/
Accepted: 13 January 2025
/
Published: 17 January 2025
Abstract
Background: Past studies have found mixed benefits to treatment of obstructive sleep apnea (OSA) with continuous positive airway pressure (CPAP) in heart failure (HF) patients. Here we evaluate the effect of OSA treatment in symptomatic HF patients who received an inpatient sleep study. Methods: We performed a retrospective observational review of 6-month outcomes in 109 hospitalized HF patients with newly diagnosed OSA who followed up to initiate PAP therapy (N = 48) or never started PAP (N = 61). Primary outcomes were cardiovascular readmissions and all-cause mortality. Results: Patients who started PAP overall had worse apnea–hypopnea index (AHI) compared to those who did not (AHI 49.4 vs. 31.3). There were significantly fewer deaths in the “PAP” group versus the “non-PAP” group: 2% versus 15% (p = 0.04). We then sub-analyzed our population based on strict CPAP adherence, defined as ≥4 PAP hours per night and at least ≥70% of nights used. Twenty-eight out of 48 PAP patients met adherence criteria. The “Adherent” group (N = 28) had notable PAP use of 6.3 h per night (interquartile range 5–7.7 h/night). In comparison to the “Non-Adherent or Never Started PAP” group (N = 81), the Adherent group had no observed deaths and significantly fewer first-time readmissions: 11% versus 33% (p = 0.026). Conclusions: Despite worse baseline OSA in our PAP population, we found an association between PAP compliance and improved cardiovascular outcomes. Future research should investigate dose–response relationships between PAP use and HF outcomes. There are important limitations to our study.
1. Introduction
Sleep-disordered breathing (SDB)—an umbrella term including both obstructive (OSA) and central sleep apnea (CSA)—is characterized by apneas and hypopneas (cessation or decreased amplitude of breathing for ≥10 s, respectively). SDB is common in heart failure (HF) patients, with prevalence rates between 50–75% and rising to 44–97% in acute decompensation [1]. SDB is often under- or undiagnosed and under- or untreated in patients with HF. In patients with HF, OSA is associated with increased morbidity and mortality, independent of confounding factors [2].
Poor cardiovascular (CV) outcomes are hypothesized to be due to increased sympathetic nervous system activity and intermittent hypoxemia, endothelial dysfunction, oxidative stress, worsening myocardial ischemia, and atrial and ventricular arrhythmia risk [3]. There is also an indirect consequence due to negative intrathoracic pressure causing increased ventricular wall tension and lower stroke volume, as well as OSA-associated hypertension [4]. Prior studies on the benefit of positive airway pressure (PAP) in HF patients with OSA have been mixed [5,6,7]. Studies have demonstrated improvement in AHI, blood pressure, and left ventricular ejection fraction [8,9]. Observational studies have also shown survival benefit of OSA diagnosis and PAP treatment in HF patients in the out of hospital setting.
Here, we retrospectively evaluate the impact of inpatient sleep studies (ISS) to designate a new diagnosis of OSA, and assess the relationship of treatment with PAP therapy on cardiovascular-related hospital readmissions and deaths in HF patients.
2. Methods
2.1. Subject Identification
Between 19 August 2020 and 7 December 2021, a sleep study specialist evaluated all patients admitted to a tertiary hospital with symptomatic heart failure. Each patient was screened for OSA and daytime sleepiness using the STOP-BANG questionnaire and the Epworth Sleepy Scale (ESS), respectively. We chose an inpatient population as these HF patients are generally at higher risk of cardiovascular events compared to their outpatient counterparts.
2.2. Inpatient Testing
Patients identified as likely to have OSA participated in an inpatient sleep study using the Itamar WatchPAT device (Zoll Itamar Medical, Chelmsford, MA, USA). Sleep studies were reviewed and interpreted by a Sleep Medicine physician at a centralized sleep laboratory. An AHI 4% scoring criteria was used.
2.3. Intervention
After OSA was identified, inpatient PAP therapy was initiated. All patients were started on a standard continuous positive airway pressure (CPAP) setting of 8 mmHg. Then, PAP pressures were manually adjusted by a sleep specialist based on apnea frequency, sleep quality, and patient comfort. Machine reports were generated from daily use to review each patients’ needs, and changes made for compliance while on PAP therapies during hospitalization. This occurred over 1–3 nights, depending on the individual patient’s length of hospital stay. Before discharge, patients were referred to a sleep center for follow-up and outpatient PAP initiation.
2.4. Outpatient Follow-Up
Follow-up appointments were scheduled in <1 month following inpatient admission. It was at the patient’s discretion to follow up at the Sleep Medicine appointment, and outpatient PAP was only started in patients who followed up at this appointment. At follow-up, patients were registered to ResMed AirViewTM, an online cloud-based meter recording system monitoring PAP usage. Based on their sleep requirements, patients utilized CPAP, bilevel PAP (BiPAP), or auto-PAP (automatic adjustment of PAP based on real-time breathing monitoring). Type of therapy was determined by the Sleep Medicine physician working in conjunction with Respiratory Therapist/Sleep Technologist, based on patient co-morbid conditions and disease process. Auto-PAP therapy was not used in any patients with HF with LVEF < 45% as the SERVE-HF trial showed harm in these patients with predominant-CSA with use of adaptive servo-ventilation (ASV) [5]. For patients who followed up to start PAP, the 6-month post-ISS period started on the day of PAP initiation (the average time was 76 ± 70 days). There was an unfortunate delay in PAP distribution due to a weakened supply chain during the COVID-19 pandemic. In patients who never followed up to start PAP, the 6-month post-ISS period started immediately after their initial hospital discharge.
2.5. Data Collection
Following 6-months of data collection, we retrospectively reviewed patient outcomes. All information was obtained through a central electronic medical record (EMR) and organized into data sheets by two separate investigators.
2.6. Outcomes
Primary outcomes were hospital readmission rates due to significant cardiovascular events and death within a 6-month period. Cardiovascular events were defined as any of the following that necessitated hospital admission: symptomatic arrhythmia, acute coronary syndrome (ACS), acute decompensated heart failure (ADHF), or stroke. All planned readmissions (e.g., cardioversion, anti-arrhythmic induction, or heart catheterization) or non-cardiovascular admissions were not included in the readmission count. Patients were categorized based on initial readmission and then >1 readmission to prevent any outlier from skewing the results.
2.7. Exclusion Criteria
Patients were excluded from the analysis if they (1) did not consent for an inpatient sleep study, (2) did not have symptomatic HF, (3) did not meet diagnostic criteria for OSA, or (4) were not expected to follow-up in our system based on a home address outside of South Carolina or record of being temporary to the area.
2.8. Heart Failure Classification and Guideline-Directed Medical Therapy
Heart failure was classified based on the updated 2022 AHA/ACC/HFSA guidelines—heart failure with reduced ejection fraction (HFrEF, left ventricular ejection fraction [LVEF] ≤ 40%), heart failure with improved ejection fraction (HFimpEF, previous LVEF ≤ 40% and follow-up measurement of LVEF > 40%), heart failure with mid-range ejection fraction (HFmrEF, LVEF 41–49%), and heart failure with preserved ejection fraction (HFpEF, LVEF ≥ 50%) [10]. We defined guideline-directed medical therapy (GDMT) as medications shown to provide a mortality benefit in HF, including beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor blockade/angiotensin receptor–neurolysin inhibitor (ACEi/ARB/ARNI), mineralocorticoid antagonists (MRA), sodium–glucose cotransporter-2 inhibitors (SGLT2 inhibitors), and the combination of hydralazine plus long-acting nitrate. A patient was marked as taking a GDMT medication if it was included on the discharge medication list and reported as taking at their first outpatient follow-up visit.
2.9. Sleep Apnea Classification and PAP Adherence
OSA severity was diagnosed and defined per the International Classification of Sleep Disorders [11]. Minimal diagnostic criteria included an AHI score of ≥5 with symptoms or an AHI score of ≥15. Concomitant CSA was diagnosed if a patient had a central apnea index (CAI) greater than 50% of AHI. Adherence was defined as using PAP for an average of ≥4 h per day and at least ≥70% of the 180 nights of six month follow up period (i.e., use for at least 126 out of 180 nights) [12].
2.10. Co-Morbidities
A patient was deemed a smoker if they consumed any number of cigarettes just before their initial admission, or a former smoker if they reported any lifetime smoking history. Ischemic heart disease (IHD) was determined by a history of acute coronary syndrome, myocardial infarction, or a record of ≥70% coronary stenosis on cardiac catheterization. Diagnosis of chronic kidney disease (CKD) stage 3 was based on the estimated glomerular filtration rate (eGFR) being ≤60 mg/mmol for at least three consecutive months.
2.11. Statistical Analysis
Statistical analyses were completed using SPSS version 27 (IBM Corporation, Armonk, NY, USA). Data distributions were examined for normality via Shapiro–Wilk statistics and examination of histograms. For statistical analyses with continuous outcomes, data were examined using Levene’s Test for equality of variances. If significant variance differences were found between groups, results were reported based on adjusted degrees of freedom using the Welch–Satterthwaite method. If continuous values did not follow a normal distribution, Mann–Whitney U test to determine statistical significance were reported. Categorical variables were assessed using X2 analyses or Fischer’s exact tests as appropriate. The Medical University of South Carolina (MUSC) Institutional Review Board approved this analysis. The data that support the findings of this study are available from the corresponding author, GRJ, upon reasonable request.
3. Results
3.1. Patient Population
Out of 239 cardiology patients deemed appropriate to participate in an inpatient sleep study, 109 were found to meet the inclusion criteria (Figure 1). A total of 48 patients followed up to start PAP therapy, termed the “PAP” group; 61 patients did not follow up to start PAP, termed the “No-PAP” group. As a sub-analysis to adjust for PAP adherence, we further stratified patients into the “Adherent” (N = 28) versus “Non-Adherent” groups (N = 81).
3.2. Demographics and Co-Morbidities
The average age of our population was 56.1 ± 14.1 years, with a body mass index (BMI) of 34.4 ± 8.5. There was a statistically significant difference between the average number of black and white patients who followed up to receive PAP—with a trend towards more white than black patients. Otherwise, there were no statistically significant differences in comorbidities between the two groups. Patient demographics and comorbidities are seen in Table 1.
3.3. Heart Failure and Cardiac Parameters
In total, HFrEF was seen in 43% of patients and HFpEF in 28%. There was a statistically significant difference in HFrEF patients when looking at PAP vs. No-PAP patients (54% vs. 34%; p = 0.03). This difference was absent after we performed our sub-analysis between Adherent vs. Non-Adherent. There was no significant difference between right ventricular parameters on transthoracic echocardiography or the use of GDMT, loop diuretic, or anti-arrhythmic drugs. Heart failure and cardiac parameters are seen in Table 2.
3.4. Sleep Apnea Characteristics
Most patients had moderate-to-severe sleep apnea with an average AHI of 39.2 ± 28.9 (Figure 2). All patients had OSA, and 16 of 109 (15%) had concomitant CSA. As per the ESS questionnaire, 77% of patients had daytime sleepy symptoms. The patients most likely to follow up to start PAP therapy (44%) had worse sleep apnea (AHI 49.4 versus 31.3 events per hour) and higher ESS scores (12.4 versus 11.5). These patients also had clinically significant worse oxygen desaturation indices (46.7 versus 31.0 events per hour), oxygen nadir (75.6% versus 78.1% oxygen saturation), and total sleep time hypoxemic of less than 88%. Sleep apnea characteristics are seen in Table 3.
3.5. Positive Airway Pressure Use and Adherence Data
There was a dramatic difference in PAP use between the patients who did versus did not meet adherence criteria—as seen by an average use of 6.2 ± 1.7 versus 1.4 ± 0.9 h per night (p < 0.01). Table 4 quantifies PAP use out of 180 days in our treatment population.
3.6. Results
We first looked at the PAP versus No-PAP groups and found lower death rate: 2% vs. 15%, p = 0.04 (Figure 3). The average time to death following initial admission was 63 ± 56 days. Otherwise, there was no statistical difference between first-time CV readmission rates (p = 0.29) or >1 CV readmissions (p = 0.39) at six months. We found the Adherent group had fewer overall readmissions and deaths, 11% vs. 33% (p = 0.03). Despite worse sleep apnea, no deaths were seen in the Adherent group, and only 1 out of 28 (4%) patients had >1 readmission. Statistical significance was narrowly missed for deaths between Adherent and Non-Adherent groups (0% vs. 12%, p = 0.06) and >1 CV readmission rates (4% vs. 19%, p = 0.07). Table 5 summarizes our primary outcomes.
4. Discussion
Obstructive sleep apnea is associated with increased morbidity and mortality in HF patients. It has been demonstrated in a longitudinal study that OSA is an independent risk factor for sudden cardiac death (SCD) [13]. SCD is associated with higher AHI and nighttime hypoxemia. The pathophysiological consequence of this is multifold. Hypoxemia, with associated hypercapnia, activates chemoreceptors that increase vascular sympathetic tone and serum catecholamines. Surges in heart rate and blood pressure increase myocardial oxygen demand when oxygen saturation is already low—setting up a situation that may lead to myocardial ischemia and potential dysrhythmia [13].
Multiple randomized control trials (RCT) have evaluated the treatment of moderate-to-severe OSA (AHI ≥ 15 events/h) and incidence of cardiovascular events. In general, there has been minimal benefit seen [14,15,16,17]. However, limited studies have examined symptomatic heart failure patients with sleep apnea and assessed cardiovascular outcomes following adequate adherence to PAP therapy. For example, one of the largest RCT looking at OSA therapy and cardiovascular outcomes excluded heart failure patients with New York Heart Association (NYHA) class III or IV symptoms [14], which encompasses patients with symptomatic heart failure or a recent heart failure hospitalization. In this study, 80% of the patients had NYHA class II or III heart failure (53% and 27%, respectively). Adherence to PAP was also analyzed in this study and showed positive correlation to outcomes.
In this analysis, when comparing the “PAP” vs. “No-PAP” groups, we found a statistically significant difference in death rates between patients who started PAP and those who did not: 2% vs. 15% (p = 0.04). Patients who followed up to receive PAP displayed significant variation in PAP use. PAP use for at least 4 h during sleep is typically used to define minimally acceptable levels for adherence. Only 28 out of 109 (26%) patients met our adherence criteria. Adherence to PAP therapy is difficult for many patients, and prior studies recognize PAP adherence rates between 30–60%. Multiple factors affect adherence, and some of these include (1) accessibility (e.g., cost, insurance authorization, local or global resources), (2) discomfort (e.g., claustrophobia, skin irritation, gastric fullness, nasal stuffiness), (3) social support (e.g., partner involvement), and (4) perceived benefit (i.e., does the patient feel rested the next day), among others [18]. There are limited studies looking at robust PAP adherence and outcomes in HF patients of varying severity [19].
Current PAP technology allows clinicians to objectively track patient adherence, which mitigates bias and provides exact quantification of PAP use. In this study, the “Adherent” group had effective PAP use of 6.2 ± 1.7 h per night, and this was associated with overall fewer readmissions and deaths. However, statistical significance was narrowly missed for deaths (p = 0.06) and >1 CV readmission (p = 0.07). There is evidence that suggests a continuous dose–response relationship between hours of use and therapeutic response [8,20,21]. Greater PAP adherence in HF patients with OSA has been associated with decreased hospitalization and death [22]. A randomized controlled trial looking at the effect of PAP on left ventricular ejection fraction showed no significant difference; however, a sub-analysis showed a positive correlation between increased PAP adherence and improved LVEF [8]. In addition, studies show different co-morbidities may benefit from varying amounts of OSA management [16,23]. Lastly, there are descriptions of the complexity of sleep and periods that may be more critical than others for intervention [24]. Rapid eye movement (REM) sleep is associated with worse OSA due to oropharyngeal muscle paralysis and an increased propensity towards airway collapse. More significant amounts of REM sleep occur during the latter hours of nocturnal sleep; therefore, if patients only adhere to their PAP during the early hours of night, they may miss critical periods of PAP benefit during REM sleep [24]. This raises the question of whether a higher degree of PAP adherence (e.g., ≥5 h per night) is necessary for HF benefit.
Interestingly, despite more severe sleep apnea parameters seen in both the “PAP” and “Adherent” groups, there was improved overall mortality rate. This further supports an association between PAP therapy improving outcomes in HF patients with OSA. This improvement may be attributed to the beneficial effects of PAP therapy, which not only enhances nocturnal oxygen levels but also exerts various favorable hemodynamic influences by increasing intrathoracic pressure. In cases of congestive heart failure—characterized by excessive volume and vascular congestion—PAP usage reduces preload and lessens left ventricular afterload [25]. This conceptually positions PAP as a potential advantage for heart failure patients, especially when employing advanced technologies that automatically adapt pressures according to individual patient physiology.
However, we must acknowledge the findings from the extensive SERVE-HF randomized controlled trial, which explored the use of adaptive servo-ventilation (ASV)—a sophisticated, automated version of PAP therapy that adjusts PAP continuously. This trial revealed adverse effects in patients with HF patients with LVEF < 45% who experienced CSA-predominance [5]. In fact, current guidelines discourage the use of ASV in the treatment of CSA in this patient population [10]. Given that 15% of our study population had CSA-predominance, we took care to exclude any patient with LVEF < 45% and CSA from ASV treatment. Looking back, only one patient with CSA-predominance found in the “No-PAP” group experienced a CV readmission and >1 CV readmission.
Despite our comprehensive analysis, several limitations in our study warrant consideration. First, the sample size was relatively small, which may raise concerns about the generalizability and reliability of our results. Second, there was an unfortunate delay in PAP distribution due to a weakened supply chain during the COVID-19 pandemic. Third, the primary control group consists of patients who did not initiate PAP therapy, leaving room for debate about whether PAP directly reduces cardiovascular events or if its usage is linked to healthier lifestyle choices, such as smoking cessation or compliance to medical recommendations such as adherence to guideline-directed medical therapy (GDMT). Fourth, our single center, non-randomized study design introduces inherent imbalances between the control and study groups that are challenging to control. Lastly, we saw a statistically significant difference in the racial composition of patients who started PAP, with a higher proportion of black patients facing socioeconomic disadvantages, raising the possibility of unnoticed social barriers that may confound our study results.
5. Conclusions
There are limited data looking at the outcomes of HF patients and PAP adherence in OSA treatment. As seen here, there may be improved outcomes in adequately treated, symptomatic HF patients with OSA—though there are important limitations to our study. Future studies should focus on a dose–response relationship between PAP use and HF outcomes. As newer, more tolerable PAP technology becomes available, PAP therapy in HF could be a revealing area of research.
Author Contributions
G.R.J. takes primary responsibility for the content, data, and analysis of this manuscript. G.R.J., F.H. and J.A. had significant contribution to the study design. F.H. screened patients admitted to our facility’s cardiology services, performed inpatient sleep studies, and aided in the final manuscript. J.A. interpreted inpatient sleep studies, distributed CPAP machines, and assisted in data interpretation. J.N.D. and J.E.E. had full access to the data and took responsibility for the integrity of the data and the accuracy of the data analysis. G.R.J. and J.N.D. had substantial contributions to data interpretation and writing the manuscript. M.J.G. performed statistical analyses and aided in data analysis. All authors have read and agreed to the published version of the manuscript.
Funding
No funding was received for this research.
Institutional Review Board Statement
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee (Medical University of South Carolina Institutional Review Board). The study was conducted according to the guidelines of the Declaration of Helsinki, and its later amendments or comparable ethical standards, and approved by the Institutional Review Board of Medical University of South Carolina (Pro00110993, approved 22 November 2022).
Informed Consent Statement
For this study, informed consent was waived and not required by the IRB as medical practice is within standard of medical care, and does not involve and experimental procedure, device, or medication. Formal consent was not required for retrospective data collection of existing medical practice, and quality improvement.
Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors on request.
Conflicts of Interest
All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge, or beliefs) in the subject matter or materials discussed in this manuscript.
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Figure 1.
Patient population: AHI: apnea–hypopnea index, HF: heart failure, ISS: inpatient sleep study, OSA: obstructive sleep apnea, PAP: positive airway pressure.
Figure 1.
Patient population: AHI: apnea–hypopnea index, HF: heart failure, ISS: inpatient sleep study, OSA: obstructive sleep apnea, PAP: positive airway pressure.
Figure 2.
Sleep apnea severity. Here we compare sleep apnea variables that are surrogates for sleep apnea severity between the PAP, No-PAP, Adherent, and Non-Adherent groups. * Signifies statistical significance (p-value ≤ 0.05) when comparing CPAP vs. No-CPAP or Adherent vs. Non-Adherent only. AHI: apnea–hypopnea index, CAI: central apnea index, O2: oxygen, pOx: pulse oximetry, TST: total sleep time.
Figure 2.
Sleep apnea severity. Here we compare sleep apnea variables that are surrogates for sleep apnea severity between the PAP, No-PAP, Adherent, and Non-Adherent groups. * Signifies statistical significance (p-value ≤ 0.05) when comparing CPAP vs. No-CPAP or Adherent vs. Non-Adherent only. AHI: apnea–hypopnea index, CAI: central apnea index, O2: oxygen, pOx: pulse oximetry, TST: total sleep time.
Figure 3.
Primary outcomes. Here we compare the percentage of patients who experienced a cardiovascular (CV) readmission or death per population between the PAP, No-PAP, Adherent, and Non-Adherent groups. * Signifies statistical significance (p-value ≤ 0.05) when comparing CPAP vs. No-CPAP or Adherent vs. Non-Adherent only. CV readmission was defined as any of the following that necessitated hospital admission: symptomatic arrhythmia, acute coronary syndrome, acute decompensated heart failure, or stroke. >1 CV readmission represents patients who required more than 1 CV readmission during the 180-day study period.
Figure 3.
Primary outcomes. Here we compare the percentage of patients who experienced a cardiovascular (CV) readmission or death per population between the PAP, No-PAP, Adherent, and Non-Adherent groups. * Signifies statistical significance (p-value ≤ 0.05) when comparing CPAP vs. No-CPAP or Adherent vs. Non-Adherent only. CV readmission was defined as any of the following that necessitated hospital admission: symptomatic arrhythmia, acute coronary syndrome, acute decompensated heart failure, or stroke. >1 CV readmission represents patients who required more than 1 CV readmission during the 180-day study period.
Table 1.
Patient demographics and comorbidities. Here we compare general characteristics in our positive airway pressure (PAP) vs. No-PAP populations, followed by the sub-analysis Adherent vs. Non-Adherent populations. Values are provided as: n (%) or mean ± standard deviation (SD).
Table 1.
Patient demographics and comorbidities. Here we compare general characteristics in our positive airway pressure (PAP) vs. No-PAP populations, followed by the sub-analysis Adherent vs. Non-Adherent populations. Values are provided as: n (%) or mean ± standard deviation (SD).
| All (N = 109) | PAP (N = 48) | No-PAP (N = 61) | p-Value | Adherent (N = 28) | Non-Adherent (N = 81) | p-Value | |
|---|---|---|---|---|---|---|---|
| Age (years) | 56.1 ± 14.1 | 56.6 ± 14.1 | 55.6 ± 14.9 | 0.98 | 58.6 ± 14.0 | 55.2 ± 15.7 | <0.01 |
| Body mass index (kg/m2) | 34.4 ± 8.5 | 35.1 ± 8.5 | 33.8 ± 11.3 | 0.12 | 34.2 ± 8.1 | 34.5 ± 10.8 | 0.77 |
| Male | 75 (69) | 34 (71) | 41 (67) | 0.84 | 18 (64) | 50 (70) | 0.64 |
| White | 62 (57) | 33 (69) | 29 (48) | 0.03 | 22 (79) | 40 (49) | <0.01 |
| Black | 43 (39) | 13 (27) | 30 (49) | 0.03 | 4 (14) | 39 (48) | <0.01 |
| Other | 4 (4) | 2 (4) | 2 (3) | 1.00 | 2 (7) | 2 (2) | 0.57 |
| Admission length of stay (days) | 11.1 ± 11.5 | 10.1 ± 11.7 | 11.8 ± 11.5 | 0.18 | 11.3 ± 13.5 | 11.0 ± 10.8 | 0.33 |
| Comorbidities | |||||||
| Arrythmia | 57 (52) | 24 (50) | 33 (54) | 0.70 | 15 (54) | 42 (52) | 1.00 |
| Coronary artery disease | 40 (37) | 18 (38) | 22 (36) | 1.00 | 13 (46) | 27 (33) | 0.26 |
| Chronic kidney disease, ≥stage 3 | 36 (33) | 15 (31) | 21 (34) | 0.84 | 10 (36) | 26 (32) | 0.82 |
| Diabetes | 44 (40) | 20 (42) | 28 (46) | 0.70 | 14 (50) | 34 (42) | 0.51 |
| Hyperlipidemia | 55 (50) | 21 (44) | 34 (56) | 0.25 | 13 (46) | 42 (52) | 0.67 |
| Hypertension | 88 (81) | 39 (81) | 49 (80) | 1.0 | 20 (71) | 68 (84) | 0.17 |
| Implantable cardioverter defibrillator | 55 (50) | 20 (42) | 35 (57) | 0.12 | 9 (32) | 46 (57) | 0.03 |
| Smoker | 15 (14) | 5 (10) | 10 (16) | 0.42 | 2 (7) | 13 (16) | 0.35 |
| Former smoker | 42 (39) | 16 (33) | 26 (43) | 0.43 | 8 (29) | 34 (42) | 0.26 |
Table 2.
Patient heart failure and cardiac characteristics. Here we compare heart failure severity, biventricular cardiac function, and medication use in our positive airway pressure (PAP) vs. No-PAP populations, followed by the sub-analysis Adherent vs. Non-Adherent populations. GDMT: guideline-directed medical therapy, HF: heart failure, HFimpEF: heart failure with improved ejection fraction, HFmrEF: heart failure with mid-range ejection fraction, HFpEF: heart failure with preserved ejection fraction, HFrEF: heart failure with reduced ejection fraction, LVAD: left ventricular assist device, NYHA: New York Heart Association. Values are provided as: n (%) or mean ± standard deviation (SD).
Table 2.
Patient heart failure and cardiac characteristics. Here we compare heart failure severity, biventricular cardiac function, and medication use in our positive airway pressure (PAP) vs. No-PAP populations, followed by the sub-analysis Adherent vs. Non-Adherent populations. GDMT: guideline-directed medical therapy, HF: heart failure, HFimpEF: heart failure with improved ejection fraction, HFmrEF: heart failure with mid-range ejection fraction, HFpEF: heart failure with preserved ejection fraction, HFrEF: heart failure with reduced ejection fraction, LVAD: left ventricular assist device, NYHA: New York Heart Association. Values are provided as: n (%) or mean ± standard deviation (SD).
| All | PAP | No-PAP | p-Value | Adherent | Non-Adherent | p-Value | |
|---|---|---|---|---|---|---|---|
| (N = 109) | (N = 48) | (N = 61) | (N = 28) | (N = 81) | |||
| HF diagnosis to inpatient sleep study (years) * | 2.8 ± 4.2 | 2.5 ± 3.9 | 2.9 ± 4.4 | 0.24 | 2.5 ± 4.0 | 2.8 ± 4.2 | 0.86 |
| NYHA class | |||||||
| Class I | 3 (3) | 1 (2) | 2 (3) | 1.00 | 0 (0) | 3 (4) | 0.57 |
| Class II | 58 (53) | 29 (60) | 29 (48) | 0.25 | 18 (64) | 40 (49) | 0.19 |
| Class III | 29 (27) | 11 (23) | 18 (30) | 0.52 | 6 (21) | 23 (28) | 0.62 |
| Class IV | 19 (17) | 7 (15) | 12 (20) | 0.61 | 4 (14) | 15 (19) | 0.78 |
| Ischemic heart disease (%) | 40 (37) | 17 (35) | 23 (38) | 0.84 | 12 (43) | 28 (35) | 0.50 |
| Orthotopic heart transplant (%) | 11 (10) | 6 (13) | 5 (8) | 0.53 | 3 (11) | 8 (10) | 1.00 |
| LVAD (%) | 10 (9) | 3 (6) | 7 (11) | 0.51 | 2 (7) | 8 (10) | 0.73 |
| HF by class † | |||||||
| HFrEF ≤ 40 | 47 (43) | 26 (54) | 21 (34) | 0.03 | 15 (54) | 32 (40) | 0.23 |
| HFmrEF 41–49 | 2 (2) | 1 (2) | 1 (2) | 1.00 | 0 (0) | 2 (2) | 0.61 |
| HFimpEF > 40 | 8 (7) | 2 (4) | 6 (10) | 0.29 | 1 (4) | 7 (9) | 0.45 |
| HFpEF ≤ 50 | 31 (28) | 10 (21) | 21 (34) | 0.12 | 7 (25) | 24 (30) | 0.62 |
| Cardiac function ‡ | |||||||
| LVEF at initial admission (%) | 40.1 ± 19.9 | 38.3 ± 17.7 | 41.4 ± 20.5 | 0.57 | 39.2 ± 18.0 | 40.4 ± 20.6 | 0.96 |
| Right ventricular base size (mm) | 42.3 ± 7.3 | 43.2 ± 6.9 | 41.7 ± 7.6 | 0.33 | 41.0 ± 6.9 | 42.8 ± 7.5 | 0.31 |
| Tricuspid annular plane systolic excursion (mm) | 17.7 ± 8.1 | 17.7 ± 5.2 | 17.7 ± 9.8 | 0.50 | 17.8 ± 4.8 | 17.6 ± 9.0 | 0.44 |
| Right ventricular systolic pressure (mmHg) | 40.3 ± 14.2 | 41.2 ± 14.3 | 39.6 ± 14.4 | 0.54 | 41.7 ± 14.3 | 39.9 ± 14.3 | 0.53 |
| Medications | |||||||
| Anti-arrhythmic | 29 (27) | 9 (19) | 20 (33) | 0.13 | 5 (18) | 24 (30) | 0.32 |
| Loop diuretic | 88 (81) | 41 (85) | 47 (77) | 0.33 | 23 (82) | 65 (80) | 1.00 |
| On GDMT § | 56 (98) | 8 (25) | 6 (18) | 0.49 | 6 (35) | 8 (17) | 1.00 |
| Number of GDMT medications | 2.6 ± 1.1 | 2.6 ± 1.0 | 2.5 ± 1.3 | 0.82 | 2.6 ± 1.1 | 2.6 ± 1.2 | 0.93 |
* HF diagnosis to inpatient sleep study represents the time in years from a patients first documented heart failure diagnosis to inpatient sleep study. † Our HF by class excludes OHT and LVAD patients (N = 21), leaving a population of N = 88. ‡ Data represent inpatient transthoracic echocardiography (TTE) obtained during the initial hospitalization and reflects only data available in that study. § Our count for guideline-directed medical therapy was only applied to HFrEF, HFmrEF, and HFimpEF patients without advanced therapies (like LVAD or OHT). This left an N = 57, and n (%) reflect appropriately.
Table 3.
Sleep apnea diagnostics. Here we compare sleep apnea severity based on various sleep study measurements obtained in our positive airway pressure (PAP) vs. No-PAP populations, followed by the sub-analysis Adherent vs. Non-Adherent populations. ESS: Epworth Sleepiness Scale, O2: oxygen, TST: total sleep time. Values are provided as: n (%) or mean ± standard deviation (SD).
Table 3.
Sleep apnea diagnostics. Here we compare sleep apnea severity based on various sleep study measurements obtained in our positive airway pressure (PAP) vs. No-PAP populations, followed by the sub-analysis Adherent vs. Non-Adherent populations. ESS: Epworth Sleepiness Scale, O2: oxygen, TST: total sleep time. Values are provided as: n (%) or mean ± standard deviation (SD).
| All | PAP | No-PAP | p-Value | Adherent | Non-Adherent | p-Value | |
|---|---|---|---|---|---|---|---|
| (N = 109) | (N = 48) | (N = 61) | (N = 28) | (N = 81) | |||
| STOP-BANG | 6.1 ± 1.7 | 6.5 ± 1.1 | 5.9 ± 2.0 | 0.16 | 6.5 ± 1.0 | 6.0 ± 1.8 | 0.76 |
| ESS score | 11.9 ± 4.5 | 12.4 ± 3.9 | 11.5 ± 4.9 | 0.73 | 10.9 ± 3.3 | 12.2 ± 4.8 | 0.32 |
| Number of ESS score > 10 | 84 (77) | 38 (83) | 45 (73) | 0.32 | 39 (71) | 64 (79) | 0.55 |
| Respiratory disturbance index (events/hour) | 40.5 ± 20.7 | 49.9 ± 29.0 | 33.5 ± 24.7 | <0.01 | 47.3 ± 30.3 | 38.4 ± 26.7 | 0.16 |
| Apnea–hypopnea index (events/hour) | 39.2 ± 28.9 | 49.4 ± 29.9 | 31.3 ± 25.5 | <0.01 | 47.9 ± 32.3 | 36.3 ± 27.2 | 0.09 |
| Central apnea index (events/hour) | 10.2 ± 15.2 | 10.0 ± 14.4 | 10.4 ± 15.8 | 0.44 | 9.4 ± 15.5 | 10.5 ± 15.1 | 0.38 |
| Central sleep apnea * | 16 (15) | 5 (10) | 11 (18) | 0.42 | 4 (15) | 12 (15) | 1.00 |
| Sleep apnea severity (3: severe to 1: mild) | 2.2 ± 0.9 | 2.5 ± 0.9 | 2.0 ± 0.9 | <0.01 | 2.3 ± 0.9 | 2.2 ± 0.9 | 0.23 |
| Severe | 58 (53) | 33 (69) | 25 (41) | <0.01 | 17 (61) | 41 (51) | 0.05 |
| Moderate | 18 (17) | 7 (15) | 11 (18) | 0.63 | 5 (18) | 13 (16) | 0.82 |
| Mild | 33 (30) | 8 (17) | 25 (41) | <0.01 | 6 (21) | 27 (33) | 0.23 |
| Oxygen desaturation index (events/hour) | 34.8 ± 25.3 | 46.7 ± 25.4 | 31.0 ± 24.0 | <0.01 | 47.1 ± 31.7 | 32.2 ± 23.1 | <0.01 |
| O2 nadir (% saturation) † | 77.1 ± 9.4 | 75.6 ± 7.9 | 78.1 ± 10.3 | 0.04 | 76.5 ± 7.6 | 77.3 ± 9.9 | 0.37 |
| TST Hypoxemic < 88% pO2 ‡ | 2.3 ± 9.3 | 3.2 ± 7.8 | 1.6 ± 10.3 | <0.01 | 4.8 ± 9.6 | 1.5 ± 9.0 | <0.01 |
* Patients were diagnosed with central sleep apnea (CSA) if their central apnea index (CAI) score was greater than 50% of the total apnea–hypopnea index (AHI). † O2 nadir refers to the lowest recorded level of blood oxygen saturation (O2 saturation) during sleep. ‡ TST hypoxemic <88% pO2 represents the total sleep time a patient pulse oximetry saturation was less than 88% during their sleep study.
Table 4.
PAP use out of 180 days. We first evaluated the average positive airway pressure (PAP) use in the total “PAP group.” We then viewed the “PAP group” closer to understand the trend of PAP use in patients who did versus did not meet the adherence criteria of ≥4 h per day and at least ≥70% of the 180 nights. Values are provided as n (%) or mean ± standard deviation (SD).
Table 4.
PAP use out of 180 days. We first evaluated the average positive airway pressure (PAP) use in the total “PAP group.” We then viewed the “PAP group” closer to understand the trend of PAP use in patients who did versus did not meet the adherence criteria of ≥4 h per day and at least ≥70% of the 180 nights. Values are provided as n (%) or mean ± standard deviation (SD).
| PAP (N = 48) | Adherent (N = 28) | Did Not Meet Adherence (N = 20) | p-Value | |
|---|---|---|---|---|
| Nights of PAP use (days) | 123 ± 57 | 165 ± 19 | 65 ± 35 | <0.01 |
| Nights with ≥ 4 h of use (days) | 100 ± 64 | 149 ± 26 | 31 ± 23 | <0.01 |
| Average use per night (hours/night) | 4.3 ± 2.8 | 6.2 ± 1.7 | 1.4 ± 0.9 | <0.01 |
| Post-PAP apnea–hypopnea index | 4.5 ± 5.3 | 3.6 ± 4.4 | 5.9 ± 6.3 | 0.07 |
| Post-PAP central apnea index | 0.7 ± 1.2 | 0.6 ± 0.8 | 0.9 ± 1.7 | 0.18 |
| PAP setting * | ||||
| Continuous PAP | 22 (46) | 12 (43) | 10 (50) | 0.62 |
| Bilevel PAP | 9 (19) | 6 (21) | 3 (15) | 0.57 |
| Auto-PAP | 17 (35) | 10 (36) | 7 (35) | 0.96 |
* Auto-PAP was never used in any HF patient with a LVEF < 45%.
Table 5.
Primary outcomes. Primary outcomes were the percent of patients who experienced a cardiovascular readmission or death per population. Cardiovascular readmission was defined as any of the following that necessitated hospital admission: symptomatic arrhythmia, acute coronary syndrome, acute decompensated heart failure, or stroke. CV: cardiovascular, PAP: positive airway pressure. Values are provided as: n (%) or mean ± standard deviation (SD).
Table 5.
Primary outcomes. Primary outcomes were the percent of patients who experienced a cardiovascular readmission or death per population. Cardiovascular readmission was defined as any of the following that necessitated hospital admission: symptomatic arrhythmia, acute coronary syndrome, acute decompensated heart failure, or stroke. CV: cardiovascular, PAP: positive airway pressure. Values are provided as: n (%) or mean ± standard deviation (SD).
| Total (N = 109) | PAP (N = 48) | No-PAP (N = 61) | p-Value | Adherent (N = 28) | Non-Adherent (N = 81) | p-Value | |
|---|---|---|---|---|---|---|---|
| CV death or admission at 6 months | 30 (28) | 11 (23) | 19 (31) | 0.39 | 3 (11) | 27 (33) | 0.03 |
| >1 CV readmission at 6 months * | 16 (15) | 5 (10) | 11 (18) | 0.29 | 1 (4) | 15 (19) | 0.07 |
| Death at 6 months | 10 (9) | 1 (2) | 9 (15) | 0.04 | 0 (0) | 10 (12) | 0.06 |
| Average time to CV admission or death (days) † | 66 ± 50 | 83 ± 56 | 56 ± 44 | 0.16 | 71 ± 52 | 65 ± 50 | 0.84 |
* >1 CV readmission represents patients who required more than 1 CV readmission during the 180-day study period. † Cumulative timing of all admissions, readmissions, and deaths. For No-PAP and Non-Adherent groups, timing to admission or death started at initial hospitalization discharge. For PAP and Adherent groups, timing to admission or death started at PAP initiation.
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Durland, J.N.; Hoyland, F.; Epps, J.E.; Gregoski, M.J.; Angles, J.; Jackson, G.R. A Broken Heart and Windy Nights: Single Center Results of Inpatient Sleep Studies and Interventions in Hospitalized Heart Failure Patients. Therapeutics 2025, 2, 1. https://doi.org/10.3390/therapeutics2010001
AMA Style
Durland JN, Hoyland F, Epps JE, Gregoski MJ, Angles J, Jackson GR. A Broken Heart and Windy Nights: Single Center Results of Inpatient Sleep Studies and Interventions in Hospitalized Heart Failure Patients. Therapeutics. 2025; 2(1):1. https://doi.org/10.3390/therapeutics2010001
Chicago/Turabian StyleDurland, Justin N., Frank Hoyland, John Elliott Epps, Mathew J. Gregoski, Jacqueline Angles, and Gregory R. Jackson. 2025. "A Broken Heart and Windy Nights: Single Center Results of Inpatient Sleep Studies and Interventions in Hospitalized Heart Failure Patients" Therapeutics 2, no. 1: 1. https://doi.org/10.3390/therapeutics2010001
APA StyleDurland, J. N., Hoyland, F., Epps, J. E., Gregoski, M. J., Angles, J., & Jackson, G. R. (2025). A Broken Heart and Windy Nights: Single Center Results of Inpatient Sleep Studies and Interventions in Hospitalized Heart Failure Patients. Therapeutics, 2(1), 1. https://doi.org/10.3390/therapeutics2010001
