Continuous Positive Airway Pressure: Evaluation of a Novel Therapy for Patients with Acute Ischemic Stroke

Abstract

Background

New approaches are needed to treat patients with stroke. Among acute ischemic stroke patients, our primary objectives were to describe the prevalence of sleep apnea and demonstrate the feasibility of providing auto-titrating continuous positive airway pressure (auto-CPAP). A secondary objective was to examine the effect of auto-CPAP on stroke severity.

Methods

Stroke patients randomized to the intervention group received 2 nights of auto-CPAP, but only those with evidence of sleep apnea received auto-CPAP for the remainder of the 30-day period. Intervention patients received polysomnography 30 days post-stroke. Control patients received polysomnography at baseline and after 30 days. Acceptable auto-CPAP adherence was defined as ≥ 4 h/night for ≥ 75% nights. Change in stroke severity was assessed comparing the NIH Stroke Scale (NIHSS) at baseline versus at 30 days.

Results

The 2 groups (intervention N = 31, control N = 24) had similar baseline stroke severity (both median NIHSS, 3.0). Among patients with complete polysomnography data, the majority had sleep apnea: baseline, 13/15 (86.7%) control patients; 30 days, 24/35 (68.6%) control and intervention patients. Intervention patients had greater improvements in NIHSS (−3.0) than control patients (−1.0); P = 0.03. Among patients with sleep apnea, greater improvement was observed with increasing auto-CPAP use: −1.0 for control patients not using auto-CPAP; −2.5 for intervention patients with some auto-CPAP use; and −3.0 for intervention patients with acceptable auto-CPAP adherence.

Conclusions

The majority of acute stroke patients had sleep apnea. Auto-CPAP was well tolerated, appears to improve neurological recovery from stroke, and may represent a new therapeutic approach for selected patients with acute cerebral infarction.

Citation:

Bravata DM; Concato J; Fried T; Ranjbar N; Sadarangani T; McClain V; Struve F; Zygmunt L; Knight HJ; Lo A; Richerson GB; Gorman M; Williams LS; Brass LM; Agostini J; Mohsenin V; Roux F; Yaggi HK. Continuous positive airway pressure: evaluation of a novel therapy for patients with acute ischemic stroke. SLEEP 2011;34(9):1271-1277.

INTRODUCTION

Sleep apnea is common following stroke, occurring in 60% to 96% of post-stroke patients.^1–10 Sleep apnea, in the setting of an acute stroke, is associated with early neurological worsening, decreased functional recovery, and increased mortality.^5,6,11,12

Continuous positive airway pressure (CPAP) safely and effectively treats sleep apnea.^13–16 Among stroke patients during rehabilitation, CPAP has been associated with improved outcomes (e.g., reduced depressive symptoms, improved sense of well-being) without serious side effects.^17–19 The safety and effectiveness of CPAP in the acute stroke period remains unknown.

In general, interventions aimed at improving post-stroke functioning are more effective the earlier they are delivered after symptom onset. Auto-titrating CPAP (auto-CPAP) senses airflow limitation and delivers pressure in response to apneas and hypopneas. Auto-CPAP is equally efficacious compared with fixed-pressure CPAP, but it eliminates the need for performing CPAP titration during polysomnography—making it especially useful in the acute setting.^20,21

The primary objectives of this study were to describe the prevalence of sleep apnea among stroke patients (at baseline and after 30 days) and to evaluate the feasibility of providing auto-CPAP to acute ischemic stroke patients. A secondary objective was to examine the effect of auto-CPAP on stroke symptom severity.

METHODS

Sample

Patients with acute ischemic stroke were recruited from 3 sites in Connecticut. Patients were included if they had an ischemic stroke,²² an NIH Stroke Scale (NIHSS) score ≥ 2, and age ≥ 50 years. Patients were excluded if they had a prior diagnosis of sleep apnea, respiratory distress requiring mechanical ventilation, oxygen dependent chronic obstructive pulmonary disease, pregnancy, intracranial hemorrhage, time from symptom onset to emergency department arrival > 72 h, receipt of thrombolytic therapy, life expectancy < 6 months, non-English speaking status, or residence outside of Connecticut. Atrial fibrillation and age < 65 years were both originally included as exclusion criteria in our initial human subjects protocol. After the first several months of recruitment, we examined our screening data and observed that many patients were being excluded on the basis of atrial fibrillation and age. The research team discussed the exclusions and made 2 modifications: a reduction in the minimum age from 65 to 50 years (given that there is no rationale to support the contention that the treatment of sleep apnea should have a differential effect on post-stroke outcomes based on age) and elimination of atrial fibrillation as an exclusion (given that sleep apnea is associated with arrhythmias, and hence treatment of sleep apnea might improve outcomes for patients with atrial fibrillation).

Randomization

This feasibility study was designed as a randomized controlled trial (clinical trials.gov; NCT00368628). The randomization was stratified according to NIHSS < 10 or ≥ 10, to ensure balance in the groups in terms of baseline stroke severity. Randomization was performed in a 1 (control):1.5 (intervention) ratio, to ensure a sufficient number of patients in the intervention group, given that one of the primary outcomes was related to auto-CPAP use.

Baseline Measurements

Baseline assessments included a review of the medical record, an interview of patients and/or their proxies, and physical measurements. The following data were collected at baseline: demographic factors, comorbidities, medications, blood pressure, heart rate, neck circumference, height, weight, and concomitant stroke care (e.g., antithrombotic agents, assessment of hyperlipidemia or cholesterol-lowering medication). Stroke symptom severity was measured prospectively using the NIHSS.²³ The NIHSS assesses 11 domains of neurological function, where normal functioning is given a score of zero and higher scores indicate worse stroke severity. In general, points are added for additional domains or extent of impairment; a score ≤ 2 is generally considered mild, 2-9 moderate, and ≥ 10 severe. The NIHSS is the standard measure of stroke severity that is used in stroke clinical trials.²⁴ The NIHSS was assessed by research staff who received certification in administration of the NIHSS.²⁵

Protocol for Control Patients

Control patients received portable unattended polysomnography at baseline and at 30 days post-stroke (Figure 1). The primary care providers of the control patients were notified of the polysomnography results, but control patients were not given CPAP as part of the study. Although it was theoretically possible for control patients with sleep apnea to receive CPAP, none of them actually received CPAP during the one-month study period.

Figure 1.

Research design

Polysomnography was performed by a trained staff member at the patient's bedside. The patients were not moved off their unit if they were admitted to the hospital. The polysomnography included: electroencephalogram (EEG), respiratory inductive plethysmography (RIP), body position, electrocardiogram (ECG), blood pressure, and oxygen saturation.²⁶ We used portable unattended polysomnography (LifeShirt, Vivometrics, Ventura, CA) because it has been validated against the gold standard of polysomnography in a sleep laboratory, has been successfully used in clinical trials of sleep apnea, and can be used throughout the hospital or at a patients' residence.²⁷

Diagnosis of Sleep Apnea

Apnea was defined as an airflow cessation ≥ 10 sec; hypopnea was defined as a reduction in airflow ≥ 10 sec or decrease in amplitude of breathing ≥ 30% followed by an oxygen desaturation ≥ 4%.^28–30 The apnea-hypopnea index (AHI) was calculated from the sum of the number of apneas and hypopneas per hour of sleep. Sleep apnea was diagnosed when the AHI ≥ 5 events/hour.²⁹ Respiratory events in the presence of abdominal effort were scored as obstructive, whereas respiratory events in the absence of abdominal effort were scored as central events. A respiratory event was scored as a mixed apnea if it met apnea criteria and was associated with absent inspiratory effort in the second portion of the event. For the purposes of distinguishing between obstructive and central sleep apnea, mixed apneas were classified as obstructive respiratory events. Patients were classified has having Cheyne-Stokes respiration if the predominant breathing pattern (> 50%) of respiratory events took the form of a waxing and waning ventilatory effort with arousals typically occurring at the peak of the hyperpnea phase.

Protocol for Intervention Patients

All intervention patients received auto-CPAP. The auto-CPAP machine (AutoSet Spirit, ResMed, Poway, CA) measured and stored information about: respiratory events (apneas and hypopneas), patient use (minutes used, nights used), mask leak, and pressure delivered. Auto-CPAP adherence was categorized as: no use; any use (more than no use but < 4 h/night for < 75% of nights); or acceptable adherence (≥ 4 h/night for ≥ 75% of nights).^31,32

The machine was interrogated after 2 nights. If there was no evidence of airflow limitation (AHI < 5 or median pressure < 6 cm H₂O), the auto-CPAP was discontinued. If there was evidence of airflow limitation, the auto-CPAP was continued for the remainder of the 30-day period (Figure 1). To support intervention patients' efforts to use the auto-CPAP, patients received information about sleep apnea, the benefits of CPAP treatment, and instructions about CPAP machine use daily for 2 days and then weekly for the rest of the one-month study period. Research staff included research associates (not respiratory therapists) who were trained in polysomnography and CPAP administration and support specifically for this study. They made visits to the patients (either in the hospital or the patients' homes) to refit masks or to troubleshoot equipment as needed. Whenever possible, the staff showed the patients their own auto-CPAP data to encourage adherence. Because polysomnography (rather than auto-CPAP) is the gold standard method of diagnosing sleep apnea, intervention patients received unattended portable polysomnography at 30 days post-stroke (Figure 1).

Outcomes

The primary outcomes were: (1) sleep apnea prevalence at baseline (based on the polysomnography data from the control patients), and (2) the proportion of intervention patients with sleep apnea with acceptable CPAP adherence. The secondary outcome was change in stroke symptom severity (NIHSS) calculated as the differences between the baseline and 30-day NIHSS scores (a negative number indicates improvement).

Adverse Events

The definition of recurrent vascular events included transient ischemic attacks, recurrent stroke, myocardial infarction, hospitalization for congestive heart failure, or any death.³³ All adverse events were reviewed by a panel that included an internist, a neurologist, and a pulmonologist. The panel classified each adverse event as serious or non-serious and as related or unrelated to the study intervention.

Analysis Plan

Descriptive statistics (e.g., mean with standard deviations, medians, and proportions) were used to describe the baseline characteristics and outcomes. To compare differences in the outcome rates between control and intervention patients and among sleep apnea patients with varying auto-CPAP use, χ² tests or Fisher exact tests were used for binary or ordinal variables, and Student t-tests or Wilcoxon rank sum tests for dimensional variables. Two-sided P-values were used to evaluate differences between the intervention and control groups. A P-value of 0.05 was used to determine statistical significance. An intention-to-treat analysis was performed comparing the change in median NIHSS from baseline to 30 days among intervention patients versus control patients. A secondary prespecified analysis of change in stroke severity was conducted among patients with sleep apnea according to the amount of CPAP used.

This project was designed to enroll a sufficient number of subjects to ensure face validity for our feasibility assessments; it was not powered to identify differences in outcomes between patients in the intervention versus control groups. No imputations were made for missing data. The analyses were conducted using SAS 9.1 (Cary, NC). This study was approved by all of the participating sites' human subjects committees.

RESULTS

Among 955 screened patients, 136 did not have an ischemic stroke, 620 met at least one exclusion criterion, and 144 patients refused to participate (Figure 2). Therefore, 55 patients were enrolled, with 31 in the intervention group and 24 in the control group. Three control patients (12.5%) and 9 intervention patients (29.0%) withdrew (Figure 2). No statistically significant differences were found in the baseline characteristics of the 2 groups, although the control patients were somewhat heavier (mean weight of 202.6 versus 178.0 pounds; Table 1). No clinically or statistically significant differences were observed among patients who withdrew compared with patients who remained in the study (data not shown). The majority of patients received the auto-CPAP within 48 h of symptom onset: < 24 h, 5/31 (16.1%); ≥ 24 < 48 h, 16/31 (51.6%); and ≥ 48 h, 10/31 (32.3%). The control and intervention groups were very similar with respect to the concomitant stroke care they received (data not shown).

Figure 2.

Patient recruitment and retention diagram

Table 1.

Baseline characteristics (N = 55)

Characteristic	Intervention (N = 31)	Control (N = 24)	P-Value*
Age (years): range	52–88	50–94
Mean ± standard deviation	70.6 ± 9.4	71.6 ± 13.3)	0.76
White race: N (%)	24 (77.4)	17 (70.8)	0.58
Female gender: N (%)	10 (32.3)	8 (33.3)	0.93
Previous stroke: N (%)	4 (12.9)	4 (16.7)	0.72
Past medical history: N (%)
Hypertension	24 (77.4)	13 (54.2)	0.07
Congestive heart failure	3 (9.7)	4 (16.7)	0.69
Atrial fibrillation	8 (25.8)	3 (12.5)	0.31
Myocardial infarction	0 (0)	2 (8.3)	0.19
Hyperlipidemia	12 (38.7)	9 (37.5)	0.93
Chronic obstructive pulmonary disorder	1 (3.2)	2 (8.3)	0.57
Diabetes mellitus	7 (22.6)	6 (25.0)	0.83
Current tobacco smoking: N (%)	11 (35.5)	6 (27.3)	0.53
Blood pressure (mm Hg): Mean ± SD
Systolic	146.5 ± 17.0	149.0 ± 19.0)	0.61
Diastolic	79.8 ± 13.4	83.2 ± 11.9)	0.34
Neck circumference (inches): Mean ± SD	16.1 ± 1.3	15.7 ± 2.2)	0.47
Waist circumference (inches): Mean ± SD	40.9 ± 4.4	44.2 ± 6.7)	0.06
Weight (pounds): Mean ± SD	178.0 ± 33.7	202.6 ± 48.9)	0.05
Body mass index (kg/m2): SD	26.8 ± 4.3	29.4 ± 7.2)	0.15
Stroke severity (NIHSS): median (range)	3.0 (2-12)	3.0 (2-18)	-
Mean ± SD	4.1 ± 2.2	4.9 ± 3.9)	0.37
Time from symptom onset to CPAP or sleep study (h): median (range)	39.0 (8.0-63.0)	39.5 (11.0-66.8)	-
Mean ± SD	38.7 ± 14.6	41.3 ± 12.2)	0.49
< 24 h	5 (16.1)	1 (4.2)	-
≥ 24 h, < 48 h	16 (51.6)	16 (66.7)	-
≥ 48 h	10 (32.3)	7 (29.2)	-

^*P-values refer to 2-sided P-values obtained either from Student t-tests, χ² tests, or Fisher exact tests.

Sleep Apnea Prevalence

Among the 24 control patients, 15 (63%) had polysomnography completed at baseline and 18 (75%) at 30 days post-stroke. The main reasons for not being able to complete the polysomnography were: competing diagnostic testing (e.g., patients being sent for brain imaging), poor quality EEG recordings obtained in the inpatient setting, and inability to obtain permission to perform the polysomnography in rehabilitation units. The majority of patients had sleep apnea both at baseline (13/15 [86.7%]) and one month post-stroke, (24/35 [68.6%]; Table 2). The control and intervention groups had similar rates of sleep apnea based on polysomnography at 30 days (72% versus 65%, P = 0.63). Obstructive sleep apnea was the predominant respiratory event, central apneas were rare; no patient had either pure central sleep apnea or Cheyne-Stokes respiration.

Table 2.

Prevalence of sleep apnea^*

Characteristic	Baseline (N = 15)	30-Day (N = 35)
Apnea hypopnea index (events/h): range	4.4-66.0	0.3-94.0
Mean ± SD	27.8 ± 20.8	20.7 ± 20.8
≥ 0 < 5	2 (13.3%)	11 (31.4%)
≥ 5 < 10	3 (20.0%)	4 (11.4%)
≥ 10 < 15	0 (0%)	1 (2.9%)
≥ 15 < 20	0 (0%)	4 (11.4%)
≥ 20 < 25	3 (20.0%)	1 (2.9%)
≥ 25 < 30	1 (6.6%)	3 (8.6%)
≥ 30 < 35	1 (6.6%)	3 (8.6%)
≥ 35	5 (33.3%)	8 (22.9%)
Sleep apnea prevalence: N (%)	13/15 (86.7%)	24/35 (68.6%)

^*The prevalence of sleep apnea is based on data from the portable unattended polysomnography. The diagnosis of sleep apnea was made if the apnea hypopnea index was ≥ 5 events/hour.

Among the 14 intervention patients with both auto-titrating CPAP and polysomnography data, the diagnostic agreement was: agreement in 12/14 (86%), with a positive predictive value of 75% and a negative predictive value of 90%. Among the 2 patients with disagreement, one had evidence of obstruction by the CPAP machine (AHI 0.8, pressure 8.6 cm H₂O), whereas the polysomnography demonstrated an AHI of 2.2. The second patient had no evidence of obstruction from the CPAP machine (AHI 4.4, pressure 4.8 cm H₂O), whereas polysomnography demonstrated an AHI of 5.5.

Auto-CPAP Use

A total of 16 intervention patients were deemed eligible for CPAP, including 15 patients with either an AHI of ≥ 5 or a median pressure ≥ 6 cm H₂O (i.e., the patients who were recommended to use auto-CPAP for 30 days), plus one patient who insisted upon using auto-CPAP machine because it made him feel better. (Note: for this patient who insisted upon continuing auto-CPAP, his beginning CPAP data suggested no obstruction (AHI 2.5, pressure 4.2 cm H₂O), but his end-CPAP data were consistent with obstruction (AHI 5.4, pressure 4.8 cm H₂O), as were his polysomnography data (AHI 15.7).

All 16 patients had some CPAP use, with acceptable adherence observed in 10/16 (62.5%; Table 3). Two intervention patients refused to try auto-CPAP, therefore no recommendation for auto-CPAP use could be made.

Table 3.

Auto-titrating continuous positive airway pressure use

Auto-titrating continuous positive airway pressure (CPAP) use category	Eligible intervention patients* (N = 16)
Proportion of nights used: range	3.3-96.7
Mean ± SD	0.69 ± 0.33
Number of h/night used: range	1.1-8.7
Mean ± SD	5.1 ± 2.3
Auto-CPAP Adherence: N (%)	-
No Use: 0 nights or 0 h/night	0 (0)
Some Use: < 75% nights for < 4 h/night	6 (37.5)
Acceptable Adherence: ≥ 75% nights for ≥ 4 h/night	10 (62.5)

^*Eligible intervention patients (N = 16) include the 15 who had evidence of sleep apnea from the auto-titrating continuous positive airway pressure (auto-CPAP) machine and one patient who did not meet these criteria but insisted upon using auto-CPAP because it made him feel better.

Effect of Auto-CPAP on Stroke Severity

The intervention and control patients had similar stroke severity at baseline (both groups, median NIHSS of 3.0; Table 1). Intervention patients had greater median improvement in NIHSS (−3.0) than control patients (−1.0; P = 0.03; Table 4). Among stroke patients with sleep apnea, the improvement in the NIHSS was greatest among patients with the most auto-CPAP use (median NIHSS change: −3.0 for acceptable adherence, −2.5 for some use, and −1.0 for no use; Table 4). The greatest improvements in NIHSS were observed among patients who started auto-titrating CPAP within 48 h of stroke symptom onset: (median NIHSS change: −3.0, < 24 h; −3.0, ≥ 24 < 48 h; −0, ≥ 48 h).

Table 4.

Clinical outcomes

Outcome	Intention-to-Treat			Adherence Analysis†
	Intervention (N = 31)	Control (N = 24)	P-value	No CPAP (N = 13)	Some CPAP (N = 6)	Acceptable CPAP (N = 10)
Stroke severity (NIHSS) median change from baseline to 30-days	−3.0	−1.0	0.03	−1.0	−2.5	−3.0
Vascular events*	1 (3.2)	3 (12.5)	0.31	2 (15.4)	0 (0)	0 (0)

^*Vascular events were defined as: transient ischemic attacks; recurrent stroke; myocardial infarction; hospitalization for congestive heart failure; or any death.

^†Adherence analysis only among patients with sleep apnea, including 13 control patients in the “no CPAP” group.

Adverse Events

Serious adverse events were observed among 5/24 (20.8%) control patients and 2/31 (6.5%) intervention patients (P = 0.22). No serious adverse events were related to the intervention. Non-serious adverse events were observed among 1/24 (4.2%) control patient and 4/31 (12.9%) intervention patients (P = 0.37). Two patients had non-serious adverse events that were attributed to the study intervention including skin irritation due to the mask (n = 1) and sneezing/nasal irritation due to the CPAP (n = 1).

DISCUSSION

We found that diagnosing and treating sleep apnea with auto-CPAP among selected acute ischemic stroke patients is feasible. Our results indicate that sleep apnea is common in the acute stroke period, that acute stroke patients are able to use auto-CPAP, and that auto-CPAP may improve stroke symptom severity at 30 days post-stroke. Given that the majority of patients had sleep apnea and was eligible for treatment, relatively few are exposed to the intervention who do not have sleep apnea. Therefore, the approach of providing auto-CPAP without incurring the delays of a diagnostic sleep study provides the earliest treatment to the greatest number of patients with minimal risk.

The prevalence of sleep apnea observed in this study is similar to the rates (60% to 96%) observed in prior studies.^1–10 We found that the prevalence of sleep apnea decreased from the acute period (86.7%) to one month post-stroke (68.6%). This decrement in sleep apnea prevalence with increasing time from the stroke event has been reported previously.⁷ This observed pattern in prevalence supports the use of auto-CPAP to treat sleep apnea in the acute period.

Auto-titrating CPAP is not recommended for use among patients with central sleep apnea, which has been demonstrated previously to be rare among patients with stroke and which was not observed in this relatively small study. Certain auto-titrating CPAP units use an algorithm to differentiate obstructive from central apneas by positive airway pressure. This detection algorithm works by delivering one or more pressure pulses when spontaneous breathing is not detected. The device evaluates the response of the patient's airway to the pressure pulses and identifies obstructive apneas or central apneas based on the resulting patient flow. The auto-titrating CPAP unit does not increase pressure in response to central apneas. These units, therefore, are appropriate for use in patients with obstructive or mixed sleep apnea, which is the cohort that was identified in the present study.

Adherence with auto-CPAP in this study was similar to prior reports in non-stroke patients, but higher than studies of post-stroke patients. For example, a study of stroke patients reported that 15% used CPAP in the long term.⁹ Our staff visited patients to encourage CPAP use and to help them overcome any equipment-related difficulties, and our study had a relatively short duration; both factors may account for the observed higher rate of CPAP use. In our analysis of auto-CPAP adherence, we excluded patients who did not have sleep apnea and patients whose sleep apnea status was unknown because they refused auto-CPAP (a standard analytic practice).⁹

Our finding that increasing adherence to auto-CPAP was associated with greater improvements in stroke symptom recovery supports the conclusion that auto-CPAP may provide a new therapeutic approach for ischemic stroke patients. Possible mechanisms by which auto-CPAP may improve neurological recovery include: improved oxygenation, reduced fibrinogen levels, decreased frequency of blood pressure surges associated with apneas, improved left ventricular function, and normalized cerebral vascular reactivity and cerebral blood flow.^13,34–36 We observed that intervention patients had a three-point improvement in their NIH stroke scale from baseline to one month post-stroke, compared with a one-point improvement for control patients (P = 0.03). To provide a context in which to evaluate the current results, this absolute change in stroke severity was similar to the results of the NINDS trial that was the basis of the FDA approval for tissue plasminogen activator (tPA) for the treatment of acute ischemic stroke. The NINDS trial, which was adequately powered to observe a difference in outcomes, found that 20% of placebo patients had an NIHSS of 0-1 compared with 31% of patients in the tPA group—an 11% absolute increase in the favorable outcome.²⁴ We found that 43% of control patients had an NIHSS of 0-1 compared with 57% of intervention patients—a 14% absolute increase in the favorable outcome, albeit with wide confidence intervals given our sample size.

The major strengths of this study were the randomized controlled design and the broad range of patients enrolled from a tertiary-care facility, a community hospital, and a Veterans Administration medical center. Also, we employed a novel intervention treatment strategy and achieved good CPAP compliance rates.

The major limitations of this study were its relatively small sample size and missing data due to withdrawals and missing polysomnography or auto-CPAP data. A 29% withdrawal rate in the intervention arm was higher than expected. Figure 2 provides the reasons for withdrawal, including some related to study activities and others related to the post-stroke clinical course. We designed our protocol to reduce withdrawals as much as possible. For example, we recorded multiple contacts for each patient. We also worked with patients and their caregivers to educate them about the research protocol. We gave several informational sessions about the research to the hospital staff in all of the participating hospitals. As a result, the hospital staff was generally very supportive of this study, yet the attitudes of the patients' primary care providers were mixed: some were very interested, whereas others were less supportive of patients' participation. For example, some of the stroke patients with sleep apnea did not endorse sleepiness symptoms, and their attending clinicians either doubted the diagnosis of sleep apnea or doubted that asymptomatic patients would benefit from treatment. Future trials of stroke patients that involve complex interventions should engage patients' primary care providers as part of the recruitment activities.

Another limitation of this study was that the staff members who performed the NIHSS at baseline and at the end of the 30-day study period were not blinded to treatment group assignment. However, the staff members were trained in the administration of the NIHSS and the NIHSS is considered to be a relatively objective measure of stroke severity, therefore mitigating potential bias due to unblinding.

In conclusion, these findings suggest that the strategy of diagnosing and treating sleep apnea among selected acute ischemic stroke patients is feasible and may be a novel therapeutic approach to improve outcomes. This strategy, if confirmed in future, larger studies, with a less selected population, could be used to complement existing stroke interventions. Given that no specialized systems are needed to implement CPAP therapy, this intervention may have the potential to be applicable to most stroke patients, regardless of the size or complexity of the facility at which they receive their care.

DISCLOSURE STATEMENT

This was not an industry supported study. Dr. Lo has received research grants and is an employee of the United States Veterans Administration. He has also received consulting fees from Acorda and Bayer and a travel stipend from Hocoma. Dr. Mohsenin has received honoraria from Jazz Pharmaceuticals and Cephalon, Inc. Dr. Gorman receives support from Boston Scientific. Dr. Agostini is employed by Aetna. The other authors have indicated no financial conflicts of interest.