MELANIA DIRCE OLIVEIRA MARQUES
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina - Médico
5 resultados
Resultados de Busca
Agora exibindo 1 - 5 de 5
- Phenotyping Pharyngeal Pathophysiology using Polysomnography in Patients with Obstructive Sleep Apnea(2018) SANDS, Scott A.; EDWARDS, Bradley A.; TERRILL, Philip I.; TARANTO-MONTEMURRO, Luigi; AZARBARZIN, Ali; MARQUES, Melania; HESS, Lauren B.; WHITE, David P.; WELLMAN, AndrewRationale: Therapies for obstructive sleep apnea (OSA) could be administered on the basis of a patient's own phenotypic causes (""traits"") if a clinically applicable approach were available. Objectives: Here we aimed to provide a means to quantify two key contributors to OSA-pharyngeal collapsibility and compensatory muscle responsiveness-that is applicable to diagnostic polysomnography. Methods: Based on physiological definitions, pharyngeal collapsibility determines the ventilation at normal (eupneic) ventilatory drive during sleep, and pharyngeal compensation determines the rise in ventilation accompanying a rising ventilatory drive. Thus, measuring ventilation and ventilatory drive (e.g., during spontaneous cyclic events) should reveal a patient's phenotypic traits without specialized intervention. We demonstrate this concept in patients with OSA (N = 29), using a novel automated noninvasive method to estimate ventilatory drive (polysomnographic method) and using ""gold standard"" ventilatory drive (intraesophageal diaphragm EMG) for comparison. Specialized physiological measurements using continuous positive airway pressure manipulation were employed for further comparison. The validity of nasal pressure as a ventilation surrogate was also tested (N = 11). Measurements and Main Results: Polysomnography-derived collapsibility and compensation estimates correlated favorably with those quantified using gold standard ventilatory drive (R = 0.83, P < 0.0001; and R = 0.76, P < 0.0001; respectively) and using continuous positive airway pressuremanipulation (R = 0.67, P < 0.0001; and R = 0.64, P < 0.001; respectively). Polysomnographic estimates effectively stratified patients into high versus low subgroups (accuracy, 69-86% vs. ventilatory drive measures; P < 0.05). Traits were near-identical using nasal pressure versus pneumotach (N = 11, R >= 0.98, both traits; P < 0.001). Conclusions: Phenotypes of pharyngeal dysfunction in OSA are evident from spontaneous changes in ventilation and ventilatory drive during sleep, enabling noninvasive phenotyping in the clinic. Our approach may facilitate precision therapeutic interventions for OSA.
- Predicting sleep apnea responses to oral appliance therapy using polysomnographic airflow(2020) VENA, Daniel; AZARBARZIN, Ali; MARQUES, Melania; BEECK, Sara Op de; VANDERVEKEN, Olivier M.; EDWARDS, Bradley A.; CALIANESE, Nicole; HESS, Lauren B.; RADMAND, Reza; HAMILTON, Garun S.; JOOSTEN, Simon A.; TARANTO-MONTEMURRO, Luigi; KIM, Sang-Wook; VERBRAECKEN, Johan; BRAEM, Marc; WHITE, David P.; SANDS, Scott A.; WELLMAN, AndrewStudy Objectives: Oral appliance therapy is an increasingly common option for treating obstructive sleep apnea (OSA) in patients who are intolerant to continuous positive airway pressure (CPAP). Clinically applicable tools to identify patients who could respond to oral appliance therapy are limited. Methods: Data from three studies (N = 81) were compiled, which included two sleep study nights, on and off oral appliance treatment. Along with clinical variables, airflow features were computed that included the average drop in airflow during respiratory events (event depth) and flow shape features, which, from previous work, indicates the mechanism of pharyngeal collapse. A model was developed to predict oral appliance treatment response (>50% reduction in apnea-hypopnea index [AHI] from baseline plus a treatment AHI <10 events/h). Model performance was quantified using (1) accuracy and (2) the difference in oral appliance treatment efficacy (percent reduction in AHI) and treatment AHI between predicted responders and nonresponders. Results: In addition to age and body mass index (BMI), event depth and expiratory ""pinching"" (validated to reflect palatal prolapse) were the airflow features selected by the model. Nonresponders had deeper events, ""pinched"" expiratory flow shape (i.e. associated with palatal collapse), were older, and had a higher BMI. Prediction accuracy was 74% and treatment AHI was lower in predicted responders compared to nonresponders by a clinically meaningful margin (8.0 [5.1 to 11.6] vs. 20.0 [12.2 to 29.5] events/h, p < 0.001). Conclusions: A model developed with airflow features calculated from routine polysomnography, combined with age and BMI, identified oral appliance treatment responders from nonresponders. This research represents an important application of phenotyping to identify alternative treatments for personalized OSA management. Statement of Significance Treatment response to oral appliance in patients with obstructive sleep apnea can be predicted at baseline from metrics derived from routine polysomnography.
- Loop gain in REM versus non-REM sleep using CPAP manipulation: A pilot study(2019) MESSINEO, Ludovico; TARANTO-MONTEMURRO, Luigi; AZARBARZIN, Ali; MARQUES, Melania; CALIANESE, Nicole; WHITE, David P.; WELLMAN, Andrew; SANDS, Scott A.
- Predicting epiglottic collapse in patients with obstructive sleep apnoea(2017) AZARBARZIN, Ali; MARQUES, Melania; SANDS, Scott A.; BEECK, Sara Op de; GENTA, Pedro R.; TARANTO-MONTEMURRO, Luigi; MELO, Camila M. de; MESSINEO, Ludovico; VANDERVEKEN, Olivier M.; WHITE, David P.; WELLMAN, AndrewObstructive sleep apnoea (OSA) is characterised by pharyngeal obstruction occurring at different sites. Endoscopic studies reveal that epiglottic collapse renders patients at higher risk of failed oral appliance therapy or accentuated collapse on continuous positive airway pressure. Diagnosing epiglottic collapse currently requires invasive studies (imaging and endoscopy). As an alternative, we propose that epiglottic collapse can be detected from the distinct airflow patterns it produces during sleep. 23 OSA patients underwent natural sleep endoscopy. 1232 breaths were scored as epiglottic/nonepiglottic collapse. Several flow characteristics were determined from the flow signal (recorded simultaneously with endoscopy) and used to build a predictive model to distinguish epiglottic from nonepiglottic collapse. Additionally, 10 OSA patients were studied to validate the pneumotachograph flow features using nasal pressure signals. Epiglottic collapse was characterised by a rapid fall(s) in the inspiratory flow, more variable inspiratory and expiratory flow and reduced tidal volume. The cross-validated accuracy was 84%. Predictive features obtained from pneumotachograph flow and nasal pressure were strongly correlated. This study demonstrates that epiglottic collapse can be identified from the airflow signal measured during a sleep study. This method may enable clinicians to use clinically collected data to characterise underlying physiology and improve treatment decisions.
- Quantifying the Arousal Threshold Using Polysomnography in Obstructive Sleep Apnea(2018) SANDS, Scott A.; TERRILL, Philip I.; EDWARDS, Bradley A.; MONTEMURRO, Luigi Taranto; AZARBARZIN, Ali; MARQUES, Melania; MELO, Camila M. de; LORING, Stephen H.; BUTLER, James P.; WHITE, David P.; WELLMAN, AndrewStudy Objectives: Precision medicine for obstructive sleep apnea (OSA) requires noninvasive estimates of each patient's pathophysiological ""traits."" Here, we provide the first automated technique to quantify the respiratory arousal threshold-defined as the level of ventilatory drive triggering arousal from sleep-using diagnostic polysomnographic signals in patients with OSA. Methods: Ventilatory drive preceding clinically scored arousals was estimated from polysomnographic studies by fitting a respiratory control model (Terrill et al.) to the pattern of ventilation during spontaneous respiratory events. Conceptually, the magnitude of the airflow signal immediately after arousal onset reveals information on the underlying ventilatory drive that triggered the arousal. Polysomnographic arousal threshold measures were compared with gold standard values taken from esophageal pressure and intraoesophageal diaphragm electromyography recorded simultaneously (N = 29). Comparisons were also made to arousal threshold measures using continuous positive airway pressure (CPAP) dial-downs (N = 28). The validity of using (linearized) nasal pressure rather than pneumotachograph ventilation was also assessed (N = 11). Results: Polysomnographic arousal threshold values were correlated with those measured using esophageal pressure and diaphragm EMG (R = 0.79, p < .0001; R = 0.73, p = .0001), as well as CPAP manipulation (R = 0.73, p < .0001). Arousal threshold estimates were similar using nasal pressure and pneumotachograph ventilation (R = 0.96, p < .0001). Conclusions: The arousal threshold in patients with OSA can be estimated using polysomnographic signals and may enable more personalized therapeutic interventions for patients with a low arousal threshold.