104 resultados para polysomnography


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Study objectives: Currently, esophageal pressure monitoring is the "gold standard" measure for inspiratory efforts, hut its invasive nature necessitates a better tolerated and noninvasive method to be used on children. Pulse transit time (PTT) has demonstrated its potential as a noninvasive surrogate marker for inspiratory efforts. The principle velocity determinant of PTT is the change in stiffness of the arterial wall and is inversely correlated to BP. Moreover, PTT has been shown to identify changes in inspiratory effort via the BP fluctuations induced by negative pleural pressure swings. In this study, the capability of PTT to classify respiratory, events during sleep as either central or obstructive in nature was investigated. Setting and participants: PTT measure was used in adjunct to routine overnight polysomnographic studies performed on 33 children (26 boys and 7 girls; mean +/- SD age, 6.7 +/- 3.9 years). The accuracy of PTT measurements was then evaluated against scored corresponding respiratory events in the polysomnography recordings. Results: Three hundred thirty-four valid respiratory events occurred and were analyzed. One hundred twelve obstructive events (OEs) showed a decrease in mean PTT over a 10-sample window that had a probability of being correctly ranked below the baseline PTT during tidal breathing of 0.92 (p < 0.005); 222 central events (CEs) showed a decrease in the variance of PTT over a 10-sample window that had a probability of being ranked below the baseline PTT of 0.94 (p < 0.005). This indicates that, at a sensitivity of 0.90, OEs can be detected with a specificity of 0.82 and CEs can be detected with a specificity of 0.80. Conclusions: PTT is able to categorize CEs and OEs accordingly in the absence of motion artifacts, including hypopneas. Hence, PTT shows promise to differentiate respiratory, events accordingly and can be an important diagnostic tool in pediatric respiratory sleep studies.< 0.005); 222 central events (CEs) showed a decrease in the variance of PTT over a 10-sample window that had a probability of being ranked below the baseline PTT of 0.94 (p < 0.005). This indicates that, at a sensitivity of 0.90, OEs can be detected with a specificity of 0.82 and CEs can be detected with a specificity of 0.80. Conclusions: PTT is able to categorize CEs and OEs accordingly in the absence of motion artifacts, including hypopneas. Hence, PTT shows promise to differentiate respiratory, events accordingly and can be an important diagnostic tool in pediatric respiratory sleep studies.');"

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Duchenne muscular dystrophy (DMD) is a progressive neuromuscular disease with death usually occurring because of respiratory failure. Signs of early respiratory insufficiency are usually first detectable in sleep. Objective: To study the presentation of sleep-related breathing disorder (SRBD) in patients with DMD. Method:> A retrospective review of patients with DMD attending a tertiary paediatric sleep disorder clinic over a 5-year period. Symptoms, lung function and polysomnographic indices were reviewed. Results: A total of 34 patients with DMD were referred for respiratory assessment (1-15 years). Twenty-two (64%) reported sleep-related symptomatology. Forced vital capacity (FVC) was between 12 and 107% predicted (n = 29). Thirty-two progressed to have polysomnography of which 15 were normal studies (median age: 10 years) and 10 (31%) were diagnostic of obstructive sleep apnoea (OSA) (median age: 8 years). A total of 11 patients (32%) showed hypoventilation (median age: 13 years) during the 5-year period and non-invasive ventilation (NIV) was offered to them. The median FVC of this group was 27% predicted. There was a significant improvement in the apnoea/hypopnoea index (AHI) (mean difference = 11.31, 95% CI = 5.91-16.70, P = 0.001) following the institution of NIV. Conclusions: The prevalence of SRBD in DMD is significant. There is a bimodal presentation of SRBD, with OSA found in the first decade and hypoventilation more commonly seen at the beginning of the second decade. Polysomnography is recommended in children with symptoms of OSA, or at the stage of becoming wheelchair-bound. In patients with the early stages of respiratory failure, assessment with polysomnography-identified sleep hypoventilation and assisted in initiating NIV.

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Obstructive sleep apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The gold standard of diagnosis, called polysomnography (PSG), requires a full-night hospital stay connected to over ten channels of measurements requiring physical contact with sensors. PSG is inconvenient, expensive and unsuited for community screening. Snoring is the earliest symptom of OSA, but its potential in clinical diagnosis is not fully recognized yet. Diagnostic systems intent on using snore-related sounds (SRS) face the tough problem of how to define a snore. In this paper, we present a working definition of a snore, and propose algorithms to segment SRS into classes of pure breathing, silence and voiced/unvoiced snores. We propose a novel feature termed the 'intra-snore-pitch-jump' (ISPJ) to diagnose OSA. Working on clinical data, we show that ISPJ delivers OSA detection sensitivities of 86-100% while holding specificity at 50-80%. These numbers indicate that snore sounds and the ISPJ have the potential to be good candidates for a take-home device for OSA screening. Snore sounds have the significant advantage in that they can be conveniently acquired with low-cost non-contact equipment. The segmentation results presented in this paper have been derived using data from eight patients as the training set and another eight patients as the testing set. ISPJ-based OSA detection results have been derived using training data from 16 subjects and testing data from 29 subjects.

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Aim: Polysomnography (PSG) is the current standard protocol for sleep disordered breathing (SDB) investigation in children. Presently, there are limited reliable screening tests for both central (CE) and obstructive (OE) respiratory events. This study compared three indices, derived from pulse oximetry and electrocardiogram ( ECG), with the PSG gold standard. These indices were heart rate (HR) variability, arterial blood oxygen de-saturation (SaO(2)) and pulse transit time (PTT). Methods: 15 children (12 male) from routine PSG studies were recruited (aged 3 - 14 years). The characteristics of the three indices were based on known criteria for respiratory events (RPE). Their estimation singly and in combination was evaluated with simultaneous scored PSG recordings. Results: 215 RPE and 215 tidal breathing events were analysed. For OE, the obtained sensitivity was HR (0.703), SaO(2) (0.047), PTT (0.750), considering all three indices (0) and either of the indices (0.828) while specificity was (0.891), (0.938), (0.922), (0.953) and (0.859) respectively. For CE, the sensitivity was HR (0.715), SaO(2) (0.278), PTT (0.662), considering all indices (0.040) and either of the indices (0.868) while specificity was (0.815), (0.954), (0.901), (0.960) and (0.762) accordingly. Conclusions: Preliminary findings herein suggest that the later combination of these non-invasive indices to be a promising screening method of SDB in children.

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Conventional overnight polysomnography (PSG) used to determine the respiratory behaviour during sleep can be a complex and expensive procedure. Pulse transit time analysis (PTT) has shown potential to detect obstructive apnoeic and hypopnoeic events in adults. This study was undertaken to determine the potential of PTT to differentiate responses to upper airway obstruction. 103 obstructive respiratory events occurred in PSG studies performed on 11 children (10 male and 1 female, mean age 7.5years). PTT measurements were evaluated against the corresponding PSG results pre-scored by 2 blinded observers. Broadly, there were 2 types of responses. They can be either short period of rapid PTT decreases (Type 1) or prolonged but gradual PTT decreases (Type 2). Type 1 obstructive events showed a mean change of 51.77% (p

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In disorders such as sleep apnea, sleep is fragmented with frequent EEG-arousal (EEGA) as determined via changes in the sleep-electroencephalogram. EEGA is a poorly understood, complicated phenomenon which is critically important in studying the mysteries of sleep. In this paper we study the information flow between the left and right hemispheres of the brain during the EEGA as manifested through inter-hemispheric asynchrony (IHA) of the surface EEG. EEG data (using electrodes A1/C4 and A2/C3 of international 10-20 system) was collected from 5 subjects undergoing routine polysomnography (PSG). Spectral correlation coefficient (R) was computed between EEG data from two hemispheres for delta-delta(0.5-4 Hz), theta-thetas(4.1-8 Hz), alpha-alpha(8.1-12 Hz) & beta-beta(12.1-25 Hz) frequency bands, during EEGA events. EEGA were graded in 3 levels as (i) micro arousals (3-6 s), (ii) short arousals (6.1-10 s), & (iii) long arousals (10.1-15 s). Our results revealed that in beta band, IHA increases above the baseline after the onset of EEGA and returns to the baseline after the conclusion of event. Results indicated that the duration of EEGA events has a direct influence on the onset of IHA. The latency (L) between the onset of arousals and IHA were found to be L=2plusmn0.5 s (for micro arousals), 4plusmn2.2 s (short arousals) and 6.5plusmn3.6 s (long arousals)

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This work has, as its objective, the development of non-invasive and low-cost systems for monitoring and automatic diagnosing specific neonatal diseases by means of the analysis of suitable video signals. We focus on monitoring infants potentially at risk of diseases characterized by the presence or absence of rhythmic movements of one or more body parts. Seizures and respiratory diseases are specifically considered, but the approach is general. Seizures are defined as sudden neurological and behavioural alterations. They are age-dependent phenomena and the most common sign of central nervous system dysfunction. Neonatal seizures have onset within the 28th day of life in newborns at term and within the 44th week of conceptional age in preterm infants. Their main causes are hypoxic-ischaemic encephalopathy, intracranial haemorrhage, and sepsis. Studies indicate an incidence rate of neonatal seizures of 0.2% live births, 1.1% for preterm neonates, and 1.3% for infants weighing less than 2500 g at birth. Neonatal seizures can be classified into four main categories: clonic, tonic, myoclonic, and subtle. Seizures in newborns have to be promptly and accurately recognized in order to establish timely treatments that could avoid an increase of the underlying brain damage. Respiratory diseases related to the occurrence of apnoea episodes may be caused by cerebrovascular events. Among the wide range of causes of apnoea, besides seizures, a relevant one is Congenital Central Hypoventilation Syndrome (CCHS) \cite{Healy}. With a reported prevalence of 1 in 200,000 live births, CCHS, formerly known as Ondine's curse, is a rare life-threatening disorder characterized by a failure of the automatic control of breathing, caused by mutations in a gene classified as PHOX2B. CCHS manifests itself, in the neonatal period, with episodes of cyanosis or apnoea, especially during quiet sleep. The reported mortality rates range from 8% to 38% of newborn with genetically confirmed CCHS. Nowadays, CCHS is considered a disorder of autonomic regulation, with related risk of sudden infant death syndrome (SIDS). Currently, the standard method of diagnosis, for both diseases, is based on polysomnography, a set of sensors such as ElectroEncephaloGram (EEG) sensors, ElectroMyoGraphy (EMG) sensors, ElectroCardioGraphy (ECG) sensors, elastic belt sensors, pulse-oximeter and nasal flow-meters. This monitoring system is very expensive, time-consuming, moderately invasive and requires particularly skilled medical personnel, not always available in a Neonatal Intensive Care Unit (NICU). Therefore, automatic, real-time and non-invasive monitoring equipments able to reliably recognize these diseases would be of significant value in the NICU. A very appealing monitoring tool to automatically detect neonatal seizures or breathing disorders may be based on acquiring, through a network of sensors, e.g., a set of video cameras, the movements of the newborn's body (e.g., limbs, chest) and properly processing the relevant signals. An automatic multi-sensor system could be used to permanently monitor every patient in the NICU or specific patients at home. Furthermore, a wire-free technique may be more user-friendly and highly desirable when used with infants, in particular with newborns. This work has focused on a reliable method to estimate the periodicity in pathological movements based on the use of the Maximum Likelihood (ML) criterion. In particular, average differential luminance signals from multiple Red, Green and Blue (RGB) cameras or depth-sensor devices are extracted and the presence or absence of a significant periodicity is analysed in order to detect possible pathological conditions. The efficacy of this monitoring system has been measured on the basis of video recordings provided by the Department of Neurosciences of the University of Parma. Concerning clonic seizures, a kinematic analysis was performed to establish a relationship between neonatal seizures and human inborn pattern of quadrupedal locomotion. Moreover, we have decided to realize simulators able to replicate the symptomatic movements characteristic of the diseases under consideration. The reasons is, essentially, the opportunity to have, at any time, a 'subject' on which to test the continuously evolving detection algorithms. Finally, we have developed a smartphone App, called 'Smartphone based contactless epilepsy detector' (SmartCED), able to detect neonatal clonic seizures and warn the user about the occurrence in real-time.

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In the present study, multilayer perceptron (MLP) neural networks were applied to help in the diagnosis of obstructive sleep apnoea syndrome (OSAS). Oxygen saturation (SaO2) recordings from nocturnal pulse oximetry were used for this purpose. We performed time and spectral analysis of these signals to extract 14 features related to OSAS. The performance of two different MLP classifiers was compared: maximum likelihood (ML) and Bayesian (BY) MLP networks. A total of 187 subjects suspected of suffering from OSAS took part in the study. Their SaO2 signals were divided into a training set with 74 recordings and a test set with 113 recordings. BY-MLP networks achieved the best performance on the test set with 85.58% accuracy (87.76% sensitivity and 82.39% specificity). These results were substantially better than those provided by ML-MLP networks, which were affected by overfitting and achieved an accuracy of 76.81% (86.42% sensitivity and 62.83% specificity). Our results suggest that the Bayesian framework is preferred to implement our MLP classifiers. The proposed BY-MLP networks could be used for early OSAS detection. They could contribute to overcome the difficulties of nocturnal polysomnography (PSG) and thus reduce the demand for these studies.

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In this study, a new entropy measure known as kernel entropy (KerEnt), which quantifies the irregularity in a series, was applied to nocturnal oxygen saturation (SaO 2) recordings. A total of 96 subjects suspected of suffering from sleep apnea-hypopnea syndrome (SAHS) took part in the study: 32 SAHS-negative and 64 SAHS-positive subjects. Their SaO 2 signals were separately processed by means of KerEnt. Our results show that a higher degree of irregularity is associated to SAHS-positive subjects. Statistical analysis revealed significant differences between the KerEnt values of SAHS-negative and SAHS-positive groups. The diagnostic utility of this parameter was studied by means of receiver operating characteristic (ROC) analysis. A classification accuracy of 81.25% (81.25% sensitivity and 81.25% specificity) was achieved. Repeated apneas during sleep increase irregularity in SaO 2 data. This effect can be measured by KerEnt in order to detect SAHS. This non-linear measure can provide useful information for the development of alternative diagnostic techniques in order to reduce the demand for conventional polysomnography (PSG). © 2011 IEEE.

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A Síndrome da Apneia e Hipopneia Obstrutiva do Sono (SAHOS) é uma doença crónica, de carácter progressivo, que atinge cerca de 4% da população adulta. A obstrução parcial ou total das vias aéreas superiores durante o sono pode provocar quadros de hipopneia (uma redução do fluxo aéreo) ou apneia (cessação completa do fluxo aéreo). Os pacientes queixam-se de sonolência diurna excessiva, ronco durante a noite e além destes problemas sociais a preocupação pela redução de funções cognitivas que se podem desencadear, como memória, atenção, hipertensão pulmonar e insuficiência cardíaca. O Médico Dentista está habilitado para avaliar o espaço aéreo oro e nasofaringeo e diagnosticar, além da necessidade de correções dentárias, a presença de obstruções das Vias Aereas Superiores (VAS) orientando assim o seu tratamento. Além do exame clínico, o diagnóstico de distúrbios respiratórios do sono é baseado na história clínica, exame físico e confirmado através da polissonografia e da análise cefalométrica. Esta tem sido considerada como um método importante no diagnóstico, fornecendo características craniofaciais que permitem verificar a existência de pré-disposição de SAHOS. As avaliações com cefalometrias obtidas em telerradiografias em norma lateral é um recurso essencial para realizar o diagnóstico de distúrbios respiratórios do sono, desde que o profissional tenha domínio da técnica e da sua interpretação. Estes distúrbios são caracterizados por diferentes graus de diminuição do espaço das vias aéreas superiores, causado por factores anatómicos e funcionais, que podem ser analisados pelo profissional. A intervenção precoce torna-se crucial, pela diminuição da morbilidade, melhores resultados no tratamento, diminuição de gastos nos serviços de saúde e melhor qualidade de vida do paciente. O presente trabalho teve por objectivo realizar uma revisão bibliográfica sobre a importância da avaliação das vias aéreas superiores através da análise de grandezas cefalométricas obtidas de telerradiografias em norma lateral como padrão de diagnóstico para a identificação de distúrbios respiratórios do sono.

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Les troubles respiratoires du sommeil ont une prévalence élevée dans la population générale, l’apnée obstructive du sommeil étant le plus important de ces troubles. Malgré tout, une grande proportion des patients avec apnée ne sont pas diagnostiqués. La méthode la plus complète pour diagnostiquer l’apnée est l’enregistrement d’une nuit de sommeil par polysomnographie, aussi appelée enregistrement de type 1, qui est un processus long et coûteux. Pour surmonter ces difficultés, des appareils d’enregistrements portables (ou de type 3) ont été développés. Toutefois, ces enregistrements de type 3 ne capturent pas l’activité cérébrale, mesurée avec l’électroencéphalographie (EEG). Le présent mémoire décrit une étude comparative entre les enregistrements de type 1 et de type 3. Tous les événements respiratoires d’apnée, d’hypopnée et d’éveils liés à un effort respiratoire (RERA, en anglais) seront analysés ainsi que les éveils cérébraux (ou éveils EEG) et les éveils autonomiques. Ces éveils autonomiques se définissent par une hausse de la fréquence cardiaque suite à un événement respiratoire. Pour enrichir les analyses, les variables respiratoires suivantes ont été étudiées : une chute de la saturation en oxygène de 4 % (ODI), l’index d’apnée-hypopnée (IAH), l’indice de perturbations respiratoires avec apnées + hypopnées + RERAs et les éveils EEG (RDIe, en anglais) et le RDI incluant les éveils autonomiques définis par une augmentation de la fréquence cardiaque de 5 bpm (RDIa5). L’objectif de la présente étude est d’évaluer la proportion d’événements respiratoires avec éveils autonomiques ainsi que leur impact sur le RDI des enregistrements de type 1 et 3. L’hypothèse suggère que les événements avec éveils autonomiques auraient un plus grand impact sur le RDI des enregistrements de type 3 contrairement au type 1. Cette étude inclut 72 sujets ayant suivi un enregistrement de polysomnographie complète de type 1 ainsi que 79 sujets différents ayant suivi un enregistrement ambulatoire de type 3. Les analyses suivantes ont été effectuées : 1) les pourcentages d’événements associés avec seulement des éveils autonomiques dans les enregistrements de type 1 et de type 3 ; 2) les fréquences de migration entre les catégories basses et élevées de sévérité de l’AHI en prenant en compte les événements associés avec seulement des éveils autonomiques ; 3) les Bland-Altman (B-A) pour mesurer l’accord entre l’AHI, le RDIe et le RDIa5 (type 1), et entre l’AHI et le RDIa5 (type 3) et ; 4) les corrélations de Pearson et les coefficients de corrélation intraclasse (ICC) pour mesurer l’accord entre l’AHI, le RDIe et le RDIa5 (type 1), et entre l’AHI et le RDIa5 (type 3). L’utilisation du critère de RDIa5 permet d’ajouter 49 % d’événements comptés avec l’AHI pour les enregistrements de type 1, et 51 % d’événements pour ceux de type 3. La présente étude montre que les éveils autonomiques ont un impact similaire autant pour le RDI des enregistrements de type 3 que de type 1. En conclusion, on peut affirmer que le RDIa5 est acceptable et fiable pour les enregistrements de type 3.

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Les troubles respiratoires du sommeil ont une prévalence élevée dans la population générale, l’apnée obstructive du sommeil étant le plus important de ces troubles. Malgré tout, une grande proportion des patients avec apnée ne sont pas diagnostiqués. La méthode la plus complète pour diagnostiquer l’apnée est l’enregistrement d’une nuit de sommeil par polysomnographie, aussi appelée enregistrement de type 1, qui est un processus long et coûteux. Pour surmonter ces difficultés, des appareils d’enregistrements portables (ou de type 3) ont été développés. Toutefois, ces enregistrements de type 3 ne capturent pas l’activité cérébrale, mesurée avec l’électroencéphalographie (EEG). Le présent mémoire décrit une étude comparative entre les enregistrements de type 1 et de type 3. Tous les événements respiratoires d’apnée, d’hypopnée et d’éveils liés à un effort respiratoire (RERA, en anglais) seront analysés ainsi que les éveils cérébraux (ou éveils EEG) et les éveils autonomiques. Ces éveils autonomiques se définissent par une hausse de la fréquence cardiaque suite à un événement respiratoire. Pour enrichir les analyses, les variables respiratoires suivantes ont été étudiées : une chute de la saturation en oxygène de 4 % (ODI), l’index d’apnée-hypopnée (IAH), l’indice de perturbations respiratoires avec apnées + hypopnées + RERAs et les éveils EEG (RDIe, en anglais) et le RDI incluant les éveils autonomiques définis par une augmentation de la fréquence cardiaque de 5 bpm (RDIa5). L’objectif de la présente étude est d’évaluer la proportion d’événements respiratoires avec éveils autonomiques ainsi que leur impact sur le RDI des enregistrements de type 1 et 3. L’hypothèse suggère que les événements avec éveils autonomiques auraient un plus grand impact sur le RDI des enregistrements de type 3 contrairement au type 1. Cette étude inclut 72 sujets ayant suivi un enregistrement de polysomnographie complète de type 1 ainsi que 79 sujets différents ayant suivi un enregistrement ambulatoire de type 3. Les analyses suivantes ont été effectuées : 1) les pourcentages d’événements associés avec seulement des éveils autonomiques dans les enregistrements de type 1 et de type 3 ; 2) les fréquences de migration entre les catégories basses et élevées de sévérité de l’AHI en prenant en compte les événements associés avec seulement des éveils autonomiques ; 3) les Bland-Altman (B-A) pour mesurer l’accord entre l’AHI, le RDIe et le RDIa5 (type 1), et entre l’AHI et le RDIa5 (type 3) et ; 4) les corrélations de Pearson et les coefficients de corrélation intraclasse (ICC) pour mesurer l’accord entre l’AHI, le RDIe et le RDIa5 (type 1), et entre l’AHI et le RDIa5 (type 3). L’utilisation du critère de RDIa5 permet d’ajouter 49 % d’événements comptés avec l’AHI pour les enregistrements de type 1, et 51 % d’événements pour ceux de type 3. La présente étude montre que les éveils autonomiques ont un impact similaire autant pour le RDI des enregistrements de type 3 que de type 1. En conclusion, on peut affirmer que le RDIa5 est acceptable et fiable pour les enregistrements de type 3.

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Introducción: El Síndrome de Apnea Hipopnea Obstructiva del Sueño es un trastorno respiratorio del sueño mayor ampliamente conocido, con importantes implicaciones para los pacientes y cuya incidencia ha venido en aumento durante los últimos años; comprende diversas manifestaciones clínicas que varían desde el ronquido hasta consecuencias cardiovasculares importantes. Objetivo: Describir la experiencia de los procedimientos quirúrgicos más utilizados para el tratamiento de pacientes con Trastornos Respiratorios del Sueño en la Clínica Rivas. Diseño: Estudio observacional descriptivo. Métodos: Revisión de 366 historias clínicas de pacientes con diagnóstico clínico y Polisomnográfico de SAHOS intervenidos quirúrgicamente debido al Trastorno Respiratorio del Sueño por rechazo de terapia de presión positiva en 3 años de observación. Resultados: Se evaluaron diferencias en medianas de los cambios del IAH, índice de Saturación de oxigeno basal y mínima, y el índice de microdespertares nocturnos tanto prequirúrgica como postquirúrgicamente. Como medida de evaluación secundaria se evaluaron las complicaciones quirúrgicas. Conclusión: En nuestra institución, como centro de referencia en apnea del sueño, la cirugía ha demostrado que disminuye de forma significativa gravedad del SAHOS y disminuye el riesgo de los pacientes con trastornos respiratorios del sueño que han rechazado el dispositivo de presión positiva.