International audienceDiagnosis of sleep-related breathing disorders (SBD) usually relies on manual retrospective analysis of the signals recorded during a whole night. We evaluated a novel detector, implemented in a cardio-respiratory Holter device, and capable of automatic event-based detection of SBDs in real time. Events (hypopneas and apneas) detected in real time were compared to those scored on the simultaneously recorded gold standard polysomnography (PSG). 4240 events were recorded by the PSG in 30 severe obstructive SBD patients. The sensitivity and positive predictive value of the detector were 86.2% (CI. 85.2-87.2%) and 60. 7% (C.l. 59.5-61.9%) respectively. The performance of this novel detector suggests that it could be used to trigger and/or adjust an event-based SBD treatment. © 2015 CCAL
Obstructive sleep apnea (OSA) occurs when the upper airway narrows or collapses due to the loss of upper airway muscle activation at sleep onset. This study investigated the effectiveness of triggered kinesthetic stimulation in patients with OSA. This proof-of-concept, open-label, multicenter prospective study was conducted on 24 patients with severe OSA. During a one night evaluation, kinesthetic stimulation was intermittently delivered in 30 minute periods. The duration of apneas and hypopneas during Stimon and Stimoff periods were compared. Five hospital-based university centers in France participated. Sleep studies were evaluated by a single scorer at a core laboratory (CHU Grenoble). Results show that during the Stimon phases, statistically significant decreases in durations of apneas and hypopneas were observed in 56% and 46% of patients, respectively. Overall, 75% of patients showed an improvement in apneas or hypopneas durations. The mean reduction in durations for patients with a significant decrease was 4.86 seconds for apneas and 6.00 seconds for hypopneas. This proof of concept study is the first to identify kinesthetic stimulation as a potentially effective therapy for OSA. These data justify evaluation in a controlled study.
International audienceSleep apnea syndromes are characterized by repeated episodes of breathing pauses (apnea) or significant reductions in respiratory amplitude (hypopnea) during the patient's sleep. These episodes significantly alter the sleep structure of the patient and provoke acute cardiorespiratory responses that may be deleterious in the long term. Continuous positive airway pressure (CPAP) therapy is the gold-standard treatment for SAS, but patient compliance to this therapy is low. This paper presents a new system for real-time detection, monitoring and treatment of SAS, based on triggered kinesthetic stimulation. The system is composed of 3 components: i) a cardio-respiratory recorder, ii) a kinesthetic stimulator and iii) a real-time processing application, integrating an " on-off " control method to trigger the kinesthetic stimulation as a function respiratory event detections. A preliminary evaluation of the system , performed on 46 patients suffering from severe SAS is also presented. This evaluation is focused on i) the performance characterization of the real-time respiratory event detector and ii) a qualitative description of the effect of the therapy. A satisfactory real-time respiratory event detection performance (sensitivity= 89.2%, positive predictive value = 59%) was obtained with the proposed detector, when evaluated retrospectively using the acquired data. Three case reports, describing the cardiorespiratory response to the therapy of a responder, a partially-responder and a non-responder patients ar
Current cardiac implantable devices (IDs) are equipped with a set of sensors that can provide useful information to improve patient follow-up and prevent health deterioration in the postoperative period. In this paper, data obtained from an ID with two such sensors (a transthoracic impedance sensor and an accelerometer) are analyzed in order to evaluate their potential application for the follow-up of patients treated with a cardiac resynchronization therapy (CRT). A methodology combining spatiotemporal fuzzy coding and multiple correspondence analysis (MCA) is applied in order to: 1) reduce the dimensionality of the data and provide new synthetic indexes based on the "factorial axes" obtained from MCA; 2) interpret these factorial axes in physiological terms; and 3) analyze the evolution of the patient's status by projecting the acquired data into the plane formed by the first two factorial axes named "factorial plane." In order to classify the different evolution patterns, a new similarity measure is proposed and validated on the simulated datasets, and then, used to cluster observed data from 41 CRT patients. The obtained clusters are compared with the annotations on each patient's medical record. Two areas on the factorial plane are identified, one being correlated with a health degradation of patients and the other with a stable clinical state.
AAIR-based pacing in SD pts may induce a significant lengthening of pts' AV conduction time, including frequent abnormal adaptation of AV conduction time during exercise.
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