Prognostic Significance of Insomnia in Heart Failure

Abstract

Background: Insomnia is associated with incident heart failure (HF), but the clinical significance and impact of insomnia on HF remain unclear.

Methods and Results: Consecutive 1,011 patients admitted for HF were divided into 2 groups according to the presence of insomnia: HF with insomnia (insomnia group, n=519) and HF without insomnia (non-insomnia group, n=492). We compared (1) cardiac event rates including cardiac death and worsening HF; and (2) underlying clinical background including laboratory data, echocardiographic data, and cardiopulmonary exercise test between the 2 groups. On Kaplan-Meier analysis, cardiac event rate was significantly higher in the insomnia group than in the non-insomnia group (39.1 vs. 23.4%, P<0.001). The insomnia group, as compared with the non-insomnia group, had (1) higher plasma renin activity (P=0.042), renin concentration (P=0.007), and aldosterone (P=0.047); (2) lower peak V̇O₂ (14.9 vs. 16.3 ml/kg/min, P=0.002) and higher V̇E/V̇CO₂ slope (36.0 vs. 33.5, P=0.001); and (3) similar B-type natriuretic peptide and left ventricular ejection fraction. Importantly, on multivariate Cox proportional hazard analysis after adjusting for potential confounding factors, insomnia was an independent predictor of cardiac events in HF patients (hazard ratio, 1.899; P<0.001).

Conclusions: Insomnia is an independent predictor of cardiac events in HF patients. HF patients with insomnia have activated renin-angiotensin-aldosterone system and lower exercise capacity. (Circ J 2016; 80: 1571–1577)

Heart failure (HF) is a major cause of death among the elderly in many countries.^1–4 It has recently been reported that insomnia, which is linked to HF in the general population (hazard ratio, 4.53; 95% CI: 1.99–10.31),⁵ is also associated with an increased risk of cardiovascular disease.^5–9 This hyperarousal disorder is accompanied by chronic activation of stress responses with increased activity in the hypothalamic-pituitary-adrenal axis and sympathetic nervous system, leading to increased secretion of cortisol and upregulation of the renin-angiotensin-aldosterone system (RAAS).^5,10 Stress response caused by insomnia is also accompanied by increased heart rate, decreased heart rate variability, increased blood pressure, secretion of pro-inflammatory cytokines and catecholamines, and impaired exercise capacity and activity,^1,5 which are risk factors for the progression of HF, and prognostic factors of HF. These risk factors may in turn contribute to endothelial dysfunction, atherosclerosis, renal dysfunction, and impaired cardiac function. Moreover, these abnormalities may represent a biologically plausible causal link between insomnia and HF. In contrast, insomnia is highly prevalent in patients with chronic disease including HF and is a significant contributing factor to fatigue and poor quality of life.^11–17

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The prognostic impact of insomnia on HF patients, however, remains unclear. We hypothesize that HF patients with insomnia have poor prognosis accompanied with activated RAAS,¹⁸ sympathetic nervous activity and inflammation, impaired cardiac function, and exercise capacity.

To address these issues, we investigated the impact of insomnia on prognosis of HF and compared the underlying clinical background in HF patients with or without insomnia (eg, clinical features, echocardiographic parameters, exercise capacity, and neurohumoral and inflammatory factors such as plasma noradrenalin, renin activity, renin concentration, aldosterone, and C-reactive protein [CRP]).

Methods

Subjects and Study Protocol

This was a prospective observational study that enrolled consecutive symptomatic HF patients (n=1,083) who were hospitalized for decompensated HF and were discharged from Fukushima Medical University between 2009 and 2013. The diagnosis of decompensated HF was made by several cardiologists based on the Framingham criteria.¹⁹ Patients with acute coronary syndrome (n=23), dialysis (n=14) and already diagnosed depression²⁰ (n=35) were excluded. Patients (n=1,011) were divided into 2 groups according to the presence of insomnia based on symptoms in normal daily life and/or at discharge, but not at hospitalization, by direct interview using a questionnaire administered by the attending physicians and medical staff for patients or caregivers. Insomnia was defined by several physicians as (1) usual use of hypnotics (“Do you take hypnotics more than 3 times per week” with the response options yes/no) or (2) presence of either insomnia symptom of grade 3 or 4 accompanied by impairment of daytime function,^5,21 specifically as follows: difficulty initiating sleep (“Do you have difficulties falling asleep?” with the response options 1, Never; 2, Occasionally; 3, Often; 4, Almost every night); difficulty maintaining sleep and/or early morning awakenings (“Do you wake up in the early hours unable to get back to sleep?” with the response options 1, Never; 2, Occasionally; 3, Often; 4, Almost every night); and non-restorative sleep (“How often do you suffer from poor sleep?” with the response options 1, Never or a few times a year; 2, One to two times per month; 3, About once a week; 4, More than once a week), based on modified International Classification of Sleep Disorders-2 criteria^5,21 supported by the American Academy of Sleep Medicine and the Japanese Society of Sleep Research, which are used widely in Japanese clinical practice.

We performed examinations such as general laboratory tests, echocardiography, and cardiopulmonary exercise tests at discharge, and compared parameters between the insomnia and non-insomnia groups. Comorbidities were also assessed by several attending physicians. Hypertension was defined as the recent use of antihypertensive drugs, or systolic blood pressure >140 mmHg, and/or diastolic blood pressure >90 mmHg. Diabetes was defined as the recent use of insulin or anti-diabetic drugs, fasting blood glucose >126 mg/dl, and/or hemoglobin A1c >6.5%. Dyslipidemia was defined as the recent use of cholesterol-lowering drugs, triglyceride >150 mg/dl, low-density lipoprotein cholesterol >140 mg/dl, and/or high-density lipoprotein cholesterol <40 mg/dl. Estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease formula.²² Chronic kidney disease was defined as eGFR <60 ml/min/1.73 m².²² Anemia was defined as hemoglobin <12.0 g/dl in female subjects and <13.0 g/dl in male subjects.¹ Preserved left ventricular ejection fraction (LVEF) was defined as >50%.²

The patients were followed up until March 2015 for cardiac events, which were composite endpoints of cardiac death and/or worsening HF,^23,24 and were adjudicated by several independent cardiologists. Definition of cardiac death included worsening HF that met the Framingham criteria,¹⁹ and ventricular fibrillation documented on electrocardiogram or implantable devices. Status and dates of all deaths were obtained from the medical records or the cardiologists at the patients’ referring hospital. Survival time was calculated from the date of hospitalization until the date of death or last follow-up. Written informed consent was obtained from all study subjects. The study protocol was approved by the ethics committee of Fukushima Medical University. The investigation conformed to the principles outlined in the Declaration of Helsinki. Reporting of the study conformed to STROBE along with references to STROBE and the broader EQUATOR guidelines.²⁵

Echocardiography

Echocardiography was performed by a blinded, experienced echocardiographer using the standard techniques.²⁶ The echocardiographic parameters investigated included LVEF, ratio of early transmitral flow velocity to mitral annular velocity (mitral valve E/e’), inferior vena cava diameter, right ventricular fractional area change (RV-FAC), and tissue Doppler-derived tricuspid lateral annular systolic velocity (tricuspid valve S’).^27,28 LVEF was calculated using a modification of Simpson’s method. Mitral valve E/E’ was calculated on transmitral Doppler flow and tissue Doppler imaging. Tissue Doppler imaging was obtained from the average of the lateral and septal annulus velocities. RV-FAC, defined as (end diastolic area−end systolic area)/end diastolic area×100, is a measure of RV systolic function.^27,28 All recordings were performed on ultrasound systems (ACUSON Sequoia, Siemens Medical Solutions USA, Mountain View, CA, USA).

Cardiopulmonary Exercise Testing

The patients underwent incremental symptom-limited exercise testing using an upright cycle ergometer with a ramp protocol before discharge (Strength Ergo 8; Fukuda Denshi, Tokyo, Japan). Breath-by-breath oxygen consumption (V̇O₂), carbon dioxide production (V̇CO₂), and minute ventilation (V̇E) were measured during exercise using an AE-300S respiratory monitor (Minato Medical Science, Osaka, Japan).^28–30 Peak V̇O₂ was measured as an average of the last 30 s of exercise. Ventilatory response to exercise (expressed as V̇E/V̇CO₂ slope) was calculated as the regression slope relating V̇E to CO₂ from the start of exercise until the respiratory compensation point (the time at which ventilation is stimulated by CO₂ output and end-tidal CO₂ tension begins to decrease).^28,31 The ventilatory anaerobic threshold was calculated using the V-slope method.

Statistical Analysis

Normally distributed data are presented as mean±SD, and non-normally distributed data as median (IQR). Categorical variables are expressed as numbers and percentages. Chi-squared test was used for comparisons of categorical variables. Data for the 2 groups were compared using independent Student’s t-test for normally distributed data and Mann-Whitney U-test for non-normally distributed data. The Kaplan-Meier method was used for analyzing event-free rate, and log-rank test was used for initial comparisons. Univariate and multivariate Cox proportional hazard analysis was used to analyze predictors of cardiac events with adjusted confounding factors. To prepare for potential confounding, we considered the following clinical factors, which are known to affect the risk of cardiac event in HF patients: age, gender, New York Heart Association functional class III or IV, body mass index, systolic blood pressure, heart rate, preserved LVEF, B-type natriuretic peptide (BNP), sodium, albumin, presence of hypertension, diabetes, dyslipidemia, atrial fibrillation, chronic kidney disease, anemia and insomnia, RAAS inhibitors, β-blockers, diuretics, inotropics and device therapy (implantable cardioverter defibrillator and/or cardiac resynchronization therapy). Among these factors, those that were independent in predicting cardiac events with P<0.05 were included in the final adjusted model. P<0.05 was considered significant for all comparisons. These analyses were performed using SPSS ver. 21.0 (IBM, Armonk, NY, USA).

Results

Of all the HF patients, 519 (51.3%) were categorized into the insomnia group (Table 1). During the follow-up period (mean, 801 days; median, 748 days), there were 236 patients with worsening HF (163 and 73 in the insomnia group and non-insomnia groups, respectively) and 151 cardiac deaths (85 and 66 in the insomnia and non-insomnia groups, respectively). The insomnia group had more cardiac events than the non-insomnia group (P<0.001; Figure).

Figure.

Kaplan-Meier analysis for cardiac events (insomnia vs. non-insomnia group) in all heart failure patients (n=1,011).

Table 1. HF Subject Characteristics vs. Presence of Insomnia

	Non-insomnia (n=492)	Insomnia (n=519)	P-value
Age (years)	66.2±15.8	68.5±13.6	0.012
Male gender	313 (63.6)	298 (57.4)	0.044
BMI (kg/cm2)	23.2±4.0	22.7±4.1	0.114
Systolic BP (mmHg)	129.7±31.5	126.9±35.1	0.184
Diastolic BP (mmHg)	73.6±20.2	72.3±22.6	0.308
Heart rate (beats/min)	82.9±24.9	83.9±26.8	0.518
NYHA class III or IV	88 (17.9)	111 (21.4)	0.162
Ischemic etiology	121 (24.6)	134 (25.8)	0.654
Preserved EF	224 (45.5)	227 (43.7)	0.567
Comorbidity
Hypertension	369 (75.0)	389 (75.0)	0.986
Diabetes	205 (41.7)	213 (41.0)	0.840
Dyslipidemia	372 (75.6)	411 (79.2)	0.173
Atrial fibrillation	169 (34.3)	218 (42.0)	0.012
Chronic kidney disease	272 (55.3)	334 (64.4)	0.003
Anemia	272 (55.3)	322 (62.0)	0.029
Medications
RAAS inhibitors	371 (75.4)	399 (76.9)	0.583
β-blockers	368 (74.8)	408 (78.6)	0.151
Diuretics	305 (62.0)	369 (71.1)	0.002
Inotropics	46 (9.3)	84 (16.2)	0.001
ICD or CRT device	76 (15.4)	111 (21.4)	0.015

Data given as mean±SD or n (%). BMI, body mass index; BP, blood pressure; CRT, cardiac resynchronization therapy; EF, ejection fraction; HF, heart failure; ICD, implantable cardioverter defibrillator; NYHA, New York Heart Association; RAAS, renin-angiotensin-aldosterone system.

The clinical features of the study subjects are summarized in Table 1. The insomnia group were older, had a higher prevalence of female sex, and had higher usage of diuretics and inotropics. Comparisons of the laboratory data between the 2 groups are shown in Table 2. The insomnia group had lower eGFR, and higher plasma renin activity, renin concentration, and aldosterone. In contrast, BNP, CRP, albumin, sodium, glucose and lipid parameters, and plasma noradrenaline did not differ between the 2 groups. The parameters of echocardiography and the cardiopulmonary exercise test are summarized in Table 3. Although LV and RV systolic function did not differ between the 2 groups, peak V̇O₂, end-tidal CO₂ at respiratory compensation point, anaerobic threshold, and ∆V̇O₂/∆work rate were significantly lower in the insomnia group than in the non-insomnia group. The minimum V̇E-V̇CO₂ and V̇E/V̇CO₂ slopes were higher in the insomnia group than in the non-insomnia group. Taken together, these data suggest that worse prognosis of HF patients with insomnia may not be related to cardiac function but to activated RAAS and impaired exercise capacity.

Table 2. Laboratory Data

	Non-insomnia (n=492)	Insomnia (n=519)	P-value
White blood cells (/μl)	7.20±3.09	7.45±3.46	0.246
Hemoglobin (g/dl)	12.5±2.5	12.2±2.2	0.061
BNP (pg/ml)	318.8 (597)§	375.0 (660)§	0.501
eGFR (ml/min/1.73 m2)	57.3±26.1	53.1±23.6	0.034
C-reactive protein (mg/dl)	0.26 (0.35)	0.39 (0.46)	0.345
Total protein (g/dl)	6.9±0.8	7.0±0.8	0.263
Albumin (g/dl)	3.6±0.6	3.6±0.6	0.633
Sodium (mEq/L)	138.8±4.0	138.7±4.1	0.693
Glucose (mg/dl)	126.8±55.5	133.1±59.7	0.137
Insulin (μU/ml)	11.2±1.2	11.8±2.0	0.727
Hemoglobin A1c (%)	5.7±0.9	5.9±1.1	0.185
Total cholesterol (mg/dl)	179.1±44.4	177.5±40.4	0.688
HDL-C (mg/dl)	47.7±16.6	50.1±21.6	0.126
LDL-C (mg/dl)	106.5±34.9	103.6±38.6	0.326
Triglyceride (mg/dl)	115.0±72.7	116.2±76.3	0.832
Plasma renin activity (ng/ml/h)	6.2 (3.5)§	9.0 (6.5)§	0.041
Renin concentration (pg/ml)	61.5 (36)§	120.4 (98)§	0.007
Aldosterone (pg/ml)	126.8 (91)§	147.0 (116)§	0.039
Noradrenaline (pg/ml)	811.2±542.7	806.2±453.5	0.960

Data given as mean±SD, n (%) or ^§median (IQR). BNP, B-type natriuretic peptide; eGFR, estimated glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.

Table 3. Echocardiography and Cardiopulmonary Exercise Test Data

	Non-insomnia	Insomnia	P-value
Echocardiography	n=490	n=512
LVEF (%)	48.7±16.0	47.5±16.5	0.264
Mitral valve E/E’	15.4±8.2	16.2±9.0	0.213
Inferior vena cava diameter (mm)	15.2±5.6	15.5±5.2	0.387
SPAP (mmHg)	30.5±14.7	31.2±16.8	0.570
RV-FAC (%)	42.0±15.6	42.4±15.2	0.779
Tricuspid valve S’ (cm/s)	9.3±3.9	9.5±4.6	0.731
Tricuspid valve E/E’	5.7±4.4	6.4±5.5	0.296
Cardiopulmonary exercise test	n=224	n=213
Peak V̇O2 (ml/kg/min)	16.3±5.2	14.9±4.4	0.002
End-tidal CO2 at respiratory compensation point (mmHg)	36.2±5.0	34.9±5.2	0.008
Anaerobic threshold (ml/kg/min)	11.5±2.7	10.8±2.2	0.010
Minimum V̇E-V̇CO2	35.0±6.3	37.0±7.0	0.003
V̇E/V̇CO2 slope	33.5±7.7	36.0±8.4	0.001
ΔV̇O2 /Δwork rate (ml/min/W)	8.4±3.5	7.7±2.2	0.013

Data given as mean±SD. ΔV̇O₂/Δwork rate, rate of increase in V̇O₂ to increase in work rate; LVEF, left ventricular ejection fraction; minimum V̇E-V̇CO₂, rate of minute ventilation to carbon dioxide production; mitral valve E/E’, ratio of the peak transmitral velocity during early diastole to the peak mitral valve annular velocity during early diastole; peak V̇O₂, peak oxygen uptake; RV-FAC, right ventricular fractional area change; SPAP, systolic pulmonary artery pressure; tricuspid valve E/E’, ratio of the peak trans-tricuspid velocity during early diastole to the peak tricuspid valve annular velocity during early diastole; tricuspid valve S’, Doppler-derived tricuspid lateral annular systolic velocity; V̇CO₂, carbon dioxide production; V̇E, minute ventilation; V̇E/V̇CO₂ slope, rate of increase in ventilation per unit increase in carbon dioxide; V̇O₂, oxygen consumption.

The Cox proportional hazard model was used to examine the prognostic impact of insomnia on HF (Table 4). We confirmed that the Cox models supported the assumption of proportional odds. On multivariate analysis, insomnia was an independent predictor of cardiac events (HR, 1.899; 95% CI: 1.333–2.705, P<0.001).

Table 4. Indicators of Cardiac Events in HF (318 events/n=1,011)

Risk factor	Univariate			Multivariate
	HR	95% CI	P-value	HR	95% CI	P-value
Age	1.019	1.011–1.028	<0.001	1.011	0.996–1.025	0.150
Male	0.977	0.780–1.224	0.842
NYHA III or IV	3.777	2.983–4.783	<0.001	2.284	1.497–3.424	<0.001
BMI	0.955	0.925–0.987	0.006	0.997	0.953–1.043	0.891
Systolic BP	0.993	0.989–0.997	<0.001	0.996	0.989–1.002	0.195
Heart rate	1.003	0.999–1.007	0.109
Preserved LVEF	0.471	0.371–0.596	<0.001	0.722	0.477–0.994	0.042
Log BNP	2.389	1.866–3.058	<0.001	1.075	0.730–1.582	0.714
Sodium	0.926	0.901–0.952	<0.001	0.965	0.925–1.007	0.097
Albumin	0.622	0.511–0.756	<0.001	0.970	0.701–1.343	0.856
Ischemic etiology	1.295	1.013–1.654	0.039	1.083	0.706–1.661	0.715
Hypertension	0.985	0.763–1.272	0.909
Diabetes	1.507	1.210–1.878	<0.001	1.002	0.701–1.432	0.993
Dyslipidemia	1.151	0.875–1.514	0.315
Atrial fibrillation	1.398	1.121–1.743	0.003	1.187	0.845–1.667	0.323
Chronic kidney disease	2.848	2.189–3.707	<0.001	1.786	1.194–2.671	0.005
Anemia	2.162	1.692–2.763	<0.001	1.301	0.875–1.934	0.194
RAAS inhibitors	0.774	0.602–0.994	0.045	1.005	0.656–1.540	0.980
β-blockers	0.879	0.680–1.136	0.324
Diuretics	1.601	1.242–2.063	<0.001	1.174	0.772–1.784	0.454
Inotropics	2.919	2.265–3.762	<0.001	1.458	0.914–2.325	0.113
ICD or CRT device	1.659	1.293–2.129	<0.001	1.202	0.772–1.872	0.414
Insomnia	1.864	1.482–2.344	<0.001	1.899	1.333–2.705	<0.001

Abbreviations as in Tables 1–3.

Then, we focused on the relationship between RAAS and cardiac event rates in HF patients with or without insomnia. On Cox proportional hazard analysis, plasma renin activity and renin concentration were predictors of cardiac events in HF patients with insomnia (plasma renin activity: HR, 1.018; 95% CI: 1.003–1.034, P=0.020; renin concentration: HR, 1.001; 95% CI: 1.001–1.002, P<0.001), but not in HF patients without insomnia. Aldosterone was not a predictor of cardiac event in either group.

Discussion

To the best of our knowledge, the present study is the first to show that HF patients with insomnia have more cardiac events, but their worse prognosis is related instead to activated RAAS and impaired exercise capacity than to cardiac function.

In the present study, insomnia was an independent predictor of cardiac events in HF patients after adjusting for multiple known confounding factors. Thus, insomnia itself may be associated with adverse outcomes in HF patients, or insomnia as a symptom can be a potential marker in risk stratification of HF patients. In addition, the insomnia group had activated RAAS, impaired renal function, and lower exercise capacity. These mechanisms may in part explain the poor prognosis of HF patients with insomnia. In contrast, plasma noradrenalin, CRP, and echocardiographic parameters did not differ between the 2 groups. Although we did not investigate the reason for these results, HF itself and HF treatment may strongly affect sympathetic activity, inflammation, and cardiac function.

Restorative functions occur during different stage of sleep, with physical restoration occurring primarily during non-rapid eye movement (NREM) sleep and brain restoration occurring primarily in rapid eye movement (REM) sleep. Sleep and exercise influence each other through complex and bilateral interactions that involve multiple physiological and psychological pathways.³² Insomnia causes inhibition of restorative functions and fatigue, resulting in impairment of psychomotor and physical performance¹ and activity,^5,17 which are risk factors for poor prognosis in HF.

With regard to inflammation, pro-inflammatory cytokines interleukin (IL)-6 and tumor necrosis factor (TNF)-α are fatigue-inducing cytokines that negatively influence quality of sleep. Mean 24-h secretion of these cytokines did not differ between insomnia patients and normal sleepers, but there was a significant increase of IL-6 from mid-afternoon to evening.^10,33 In addition, the characteristic circadian secretion of TNF-α, with a peak close to sleep offset, was observed in the normal sleepers, but not in the insomnia patients.³³ The hypersecretion and/or circadian alteration of cytokine secretion associated with hypothalamic-pituitary-adrenal axis activation may explain the fatigue and poor sleep associated with insomnia.¹⁰ Another study reported elevated CRP in insomnia patients.³⁴ In contrast, erythrocyte sedimentation rate is not associated with incidence of HF in insomnia patients.⁹ Thus, the associations between insomnia and inflammation are complex and not fully addressed especially in HF patients.

Furthermore, symptoms of HF itself, including coughing, orthopnea, paroxysmal nocturnal dyspnea, and nocturia, often lead to insomnia,^13,35 and insomnia itself may reflect the severity of HF. In addition, insomnia is also an indicator of depression, which is associated with adverse prognosis of HF.²⁰ These in turn are associated with poor prognosis of HF patients. In contrast, insomnia increases with both the number of chronic illnesses the patient has and the number of medications taken.^13,36–38 Insomnia could also be partially caused by medications used in the treatment of HF.^1,2 Melatonin production may be affected by β-blockers; diuretics cause nocturia; and inotropics affect agitation; all of which result in poor sleep quality.¹³

In future, functional imaging may be useful to determine the association between HF and insomnia. Functional neuroimaging has shown that transition from wakefulness to sleep is associated with a decrease of brain activity in specific regions, such as the brainstem, thalamus, and prefrontal cortex.³⁹ Cerebral abnormalities detected on magnetic resonance imaging and cognitive performance in HF patients have been reported.⁴⁰ For instance, medial temporal lobe atrophy was related to cognitive dysfunction, involving memory impairment and executive dysfunction, whereas total white matter hyperintensities were related to depression resulting in insomnia.⁴⁰

To date, there are no data on effective treatment for insomnia in HF patients. General behavioral measures for improved sleep hygiene, such as minimal use of caffeine, cigarettes and alcohol, maintaining a regular sleep schedule, going to bed only when sleepy, regular exercise, and avoiding daytime naps, should be explained to the patients.¹⁰ It has recently been reported that exercise training improves sleep quality in HF patients.⁴¹ Given that the present HF patients with insomnia had impaired exercise capacity, cardiac rehabilitation may be more strongly recommended.^1,41

Study Limitations

There are several limitations in the present study. First, the number of subjects was relatively small because the study was performed in a single institution. Further studies with a larger population are needed. Diagnosis of cardiac events, however, was accurately made by the experienced cardiologists. Second, we diagnosed insomnia based on patient symptoms assessed on interview or medical history, hence we could not completely exclude the effect of psychiatric disorders, depression and cognition. The definition of insomnia may have affected the present results. In addition, we did not consider any changes in any parameters, and baseline data at admission were used for the analyses. Furthermore, we did not use polysomnography or actigraphy, which are objective tests of sleep disorders. These, however, are not routinely performed in patients with HF and/or insomnia. Third, plasma renin activity and concentration of renin, aldosterone, and noradrenaline might be affected by RAAS inhibitors and β-blockers. Fourth, although multivariate analysis was used to evaluate associations between insomnia and prognosis in HF patients, confounding factors cannot be entirely eliminated. The results do not establish a cause-effect relationship between the presence of insomnia and increased cardiac events. Finally, further studies are required to examine the impact of hypnotics on prognosis of HF patients with insomnia.

Conclusions

Insomnia was a common and independent predictor of cardiac events in HF patients. HF patients with insomnia had activated RAAS and impaired exercise capacity, and insomnia may be a potential marker of adverse prognosis in HF patients. Further studies are required to determine whether controlling insomnia improves the prognosis of such patients.

Acknowledgments

The authors acknowledge the efforts of Drs Aya Goto and Shinya Ito (Department of Public Health, Fukushima Medical University) for their invaluable advice on medical statistics, and Ms Kumiko Watanabe and Yuko Niimura for their outstanding technical assistance. This study was supported in part by a grant-in-aid for Scientific Research (No. 25461061) from the Japan Society for the Promotion of Science, and grants-in-aid from the Japanese Ministry of Health, Labor, and Welfare, Tokyo, Japan.

Disclosures

A.Y. and S. Suzuki belong to endowed departments supported by Fukuda Denshi and Fukuda Lifetec. These companies are not associated with the present study.

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