Relation of Periodic Leg Movements During Sleep and Mortality in Patients With Systolic Heart Failure

Periodic leg movements during sleep (PLMs) are a disorder characterized by regularly recurring movements of the legs during sleep. Although PLMs are common in patients with heart failure (HF), their clinical significance is unknown. The aim of this study was to determine whether, in patients with HF, PLMs are associated with increased mortality risk. In a prospective cohort study, 218 consecutive patients with systolic HF newly referred to an HF clinic from 1997 to 2004 who underwent overnight polysomnography, regardless of symptoms or signs of sleep disorders, were enrolled. The frequency of PLMs per hour of sleep was quantified as the PLM index (PLMI). Patients were classified as either normal (PLMI <5) or abnormal (PLMI ≥5). Eighty-one of the patients (37%) had PLMIs ≥5. During a mean follow-up period of 32.9 months, complete follow-up data were obtained in 95%. Patients with PLMIs ≥5 were older and had lower left ventricular ejection fractions and higher New York Heart Association classes than patients with PLMIs <5. The mortality rate was significantly higher in patients with PLMIs ≥5 than those with PMLIs <5 (10.4 vs 3.4 deaths/100 patient-years, p = 0.002). After adjusting for significant confounding factors, the presence of PLMI ≥5 remained a significant independent risk for death (hazard ratio 2.42, 95% confidence interval 1.16 to 5.02, p = 0.018). In conclusion, in patients with systolic HF, the presence of PLMI ≥5 is associated with an increased mortality risk, but these findings do not establish a cause-effect relation.

Heart failure (HF) is increasing in prevalence and is associated with high rates of morbidity and mortality. Accordingly, it is important to identify conditions that might contribute to this health burden. Such conditions may include sleep disorders, such as sleep apnea and periodic leg movements during sleep (PLMs). PLMs are characterized by regularly recurring movements of the legs during sleep and are commonly found in patients with HF. However, their clinical significance in patients with HF has not been examined. Because PLMs are often not accompanied by symptoms, patients are frequently unaware of them. Nevertheless, PLMs can be associated with repetitive surges in sympathetic nervous system activity, blood pressure, and heart rate. In 1 small study in patients with renal failure, PLMs were associated with increased mortality. This observation raises the possibility that in patients with HF, PLMs may also contribute to poorer prognosis. We therefore hypothesized that in patients with HF, the presence of PLMs would be associated with increased mortality risk.


We prospectively enrolled, as part of an epidemiologic study, consecutive patients with HF newly referred to the Heart Failure Clinic of the Mount Sinai Hospital in Toronto from September 1, 1997, to December 1, 2004, regardless of symptoms or signs of sleep disorders, who met the following inclusion criteria: (1) men and women aged ≥18 years, (2) HF due to ischemic or nonischemic dilated cardiomyopathy present for ≥6 months, (3) left ventricular systolic dysfunction (left ventricular ejection fraction [LVEF] ≤45% at rest by radionuclide angiography or echocardiography), (4) New York Heart Association [NYHA] class II to IV despite optimization of medical therapy, and (5) stable clinical status on stable optimal medical therapy for ≥1 month before entry. Exclusion criteria were (1) unstable angina, myocardial infarction, or cardiac surgery within the previous 3 months; (2) pregnancy; and (3) history of PLMs. The protocol was approved by the research ethics board of the Mount Sinai Hospital, and all subjects provided written informed consent before entry.

Baseline characteristics and medication use were obtained from patients’ medical records. Each patient’s height and weight were recorded just before overnight polysomnography, from which body mass index was calculated. To assess the degree of subjective daytime sleepiness, the Epworth Sleepiness Scale was administered. NYHA class was assessed at the time of study entry. LVEF, hemoglobin, and plasma creatinine concentrations, and the estimated glomerular filtration rate using the Modification of Diet in Renal Disease (MDRD) formula were measured <3 months before polysomnography.

Overnight polysomnography was performed in eligible patients using standard polysomnographic techniques and criteria for scoring sleep stages and arousals. Arousals from non–rapid eye movement sleep were defined as an abrupt shift of electroencephalographic frequency, including α, θ, and/or frequencies >16 Hz (but not spindles) that lasted ≥3 seconds, with ≥10 seconds of stable sleep preceding the change. Scoring of arousals during rapid eye movement sleep required, in addition, a corresponding increase in submental electromyographic activity lasting ≥1 second. Electromyographic recordings of the limbs were made from the anterior tibialis muscles of both legs only using standard surface electrodes (F-E5GH Genuine Grass Gold Disc Electrodes; Grass Technologies, Astro-Med, Inc., West Warwick, Rhode Island). PLMs were defined, using standard criteria from the American Sleep Disorders Association and the second edition of the International Classification of Sleep Disorders coding manual, as a series of 4 consecutive leg movements lasting 0.5 to 5 seconds, with an amplitude of ≥1/4 of that due to dorsiflexion of the toe during calibration and separated by intervals of 5 to 90 seconds. To avoid overscoring of PLMs that might have occurred secondary to arousals, leg movements that occurred after the onset of an arousal were not scored as PLMs. Similarly, to avoid overscoring of PLMs that might have occurred secondary to the termination of respiratory events, only leg movements that occurred during regular breathing or began and ended ≥0.5 seconds before resolution of an apnea or hypopnea were classified as PLMs. The PLM index (PLMI) was quantified as the frequency of PLMs per hour of sleep. Because we excluded leg movements associated with respiratory-related arousals, we used the traditional lower PLMI cutoff of ≥5 to distinguish between those with PLMs and those without PLMs (i.e., PLMI <5), as originally described.

Thoracoabdominal movements were measured by respiratory inductance plethysmography, whose sum channel was calibrated against a spirometer, and oxyhemoglobin saturation (S a O 2 ) was monitored by oximetry. Apnea and hypopnea were defined as cessation or at least a 50% relative reduction in airflow from baseline assessed from the sum channel of the respiratory inductance plethysmograph, respectively, for ≥10 seconds. Apnea was classified as obstructive or central in the presence or absence of thoracoabdominal motion, respectively. Hypopnea was classified as obstructive or central in the presence or absence of out-of-phase thoracoabdominal motion, respectively. Patients were divided into categories according to the frequency of apnea and hypopnea per hour of sleep (i.e., apnea-hypopnea index [AHI]): mild or no sleep apnea (AHI <15 per hour of sleep), central sleep apnea (AHI ≥15 with >50% central events), and obstructive sleep apnea (AHI ≥15 per hour of sleep with ≥50% obstructive events). All signals were recorded and analyzed on a computerized sleep recording system (Sandman; Nellcor Puritan Bennett, Ltd., Ottawa, Ontario, Canada). Sleep studies were analyzed by technicians who were blinded to the patients’ baseline clinical status.

The primary outcome was the cumulative rate of death from any cause from the date of the diagnostic sleep study until January 1, 2005. Follow-up data were obtained by HF clinic personnel from telephone interviews with the patients or, if the patients had died or were not available, their family members, by review of the patients’ hospital or HF clinic records, or by personal communication with the patients’ primary physicians, including the date and cause of death.

Comparisons between the 2 groups were performed using Student’s t tests for continuous variables that were normally distributed and Mann-Whitney U tests for variables that were not normally distributed. Chi-square or Fisher’s exact tests were used to compare nominal variables. Cumulative probabilities of event curves were estimated using the Kaplan-Meier method. To evaluate the association between those with PLMIs ≥5 or other baseline characteristics and death from any cause, Cox proportional-hazards models were used. On multivariate analysis, variables were included if they conferred at least a 10% change in the hazard ratio (HR) for death when added to the model. Independent variables were introduced into the model 1 at a time and included age, gender, body mass index, NYHA class, LVEF, ischemic origin of HF, atrial fibrillation, history of hypertension, hyperlipidemia, diabetes, obstructive sleep apnea, central sleep apnea, hemoglobin and creatinine concentrations, estimated glomerular filtration rate, medications (including β blockers), and polysomnographic variables (including total sleep time, sleep efficiency, AHI, arousal index, mean S a O 2 , and lowest S a O 2 ). Relations were summarized as HRs with 95% confidence intervals. The best cutoff value for PLMI predicting risk for mortality was generated with receiver-operating characteristic curves as the value that was obtained by the Youden index. Data are presented as mean ± SD or as frequencies. A p value <0.05 was considered statistically significant. All analyses were performed using SPSS version 13.0.1 (SPSS, Inc., Chicago, Illinois).


Figure 1 illustrates the flow of patients through the study. Of the 242 eligible patients, 218 (90%) agreed to undergo sleep studies and were divided into those with PLMIs <5 or ≥5. Patients were followed prospectively for mean and maximum durations of 32.9 and 87.8 months, respectively, during which no specific treatment for PLMs was prescribed. Complete follow-up data were obtained for analysis in 207 patients (95%): 130 with PLMIs <5 and 77 with PLMIs ≥5.

Figure 1

Progress of the cohort through the study.

Table 1 lists the baseline characteristics of the 2 groups. Patients were generally middle-aged, predominantly male, and somewhat overweight, with severely depressed LVEFs. Fifty-four percent of patients were in NYHA class II, 45% in class III, and 1% in class IV, and most had nonischemic cardiomyopathy. Patients were on appropriate anti-HF medications, while 3% had cardioverter-defibrillators implanted and 1% had received cardiac resynchronization therapy. Patients with PLMIs ≥5 were older and had trends toward lower LVEF and higher NYHA class than patients with PLMIs <5. Also, a higher proportion of patients with PLMIs ≥5 had ischemic causes of HF than those with PLMIs <5. A higher proportion of patients with PLMIs ≥5 had central sleep apnea, but not obstructive sleep apnea, than those with PLMIs <5. A higher proportion of patients with PLMIs <5 had histories of hypertension than those with PLMIs ≥5. There was no significant difference in Epworth Sleepiness Scale score between the 2 groups. There were also no significant differences in hemoglobin or creatinine concentrations, or in estimated glomerular filtration rate, and no significant difference in medication use between the 2 groups.

Table 1

Baseline characteristics of the patients

Variable PLMI <5 PLMI ≥5
(n = 130) (n = 77) p Value
Age (years) 54.2 ± 13.1 58.3 ± 11.2 0.022
Men 96 (74%) 62 (81%) 0.277
Body mass index (kg/m 2 ) 29.7 ± 5.3 28.4 ± 5.5 0.091
LVEF (%) 25.6 ± 9.9 22.9 ± 9.6 0.051
NYHA class 2.4 ± 0.6 2.6 ± 0.6 0.053
Ischemic cause of HF 35 (46%) 49 (38%) 0.048
History of hypertension 62 (48%) 24 (31%) 0.020
Atrial fibrillation 12 (9%) 7 (9%) 0.973
Diabetes mellitus 34 (26%) 22 (28%) 0.707
Obstructive sleep apnea 33 (25%) 18 (23%) 0.746
Central sleep apnea 21 (16%) 22 (29%) 0.033
Epworth Sleepiness Scale score 7.6 ± 3.8 6.9 ± 3.8 0.295
Hemoglobin (g/dl) 14.1 ± 1.6 14.1 ± 1.6 0.862
Creatinine (mg/dl) 1.1 ± 0.5 1.2 ± 0.5 0.511
eGFR (ml/min/1.73 m 2 ) 77.2 ± 27.2 72.1 ± 21.1 0.187
Diuretics 99 (76%) 63 (82%) 0.342
β blockers 103 (79%) 55 (71%) 0.204
ACE inhibitors and/or AT2 antagonists 121 (93%) 71 (92%) 0.817
Spironolactone 25 (19%) 21 (27%) 0.170

Data are expressed as mean ± SD or as number (percentage).

ACE = angiotensin-converting enzyme; AT2 = angiotensin II receptor; eGFR = estimated glomerular filtration rate.

Polysomnographic characteristics of the patients are listed in Table 2 . Patients with PLMIs ≥5 had a reduced proportion of slow-wave sleep and a higher frequency of arousals than those with PLMIs <5. There was no significant difference in the AHI, mean S a O 2 , or minimum S a O 2 between the 2 groups.

Dec 22, 2016 | Posted by in CARDIOLOGY | Comments Off on Relation of Periodic Leg Movements During Sleep and Mortality in Patients With Systolic Heart Failure

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