MELANIA DIRCE OLIVEIRA MARQUES
Projetos de Pesquisa
Unidades Organizacionais
Instituto do Coração, Hospital das Clínicas, Faculdade de Medicina - Médico
3 resultados
Resultados de Busca
Agora exibindo 1 - 3 de 3
- Quantifying the magnitude of pharyngeal obstruction during sleep using airflow shape(2019) MANN, Dwayne L.; TERRILL, Philip I.; AZARBARZIN, Ali; MARIANI, Sara; FRANCIOSINI, Angelo; CAMASSA, Alessandra; GEORGESON, Thomas; MARQUES, Melania; TARANTO-MONTEMURRO, Luigi; MESSINEO, Ludovico; REDLINE, Susan; WELLMAN, Andrew; SANDS, Scott A.Rationale and objectives: Non-invasive quantification of the severity of pharyngeal airflow obstruction would enable recognition of obstructive versus central manifestation of sleep apnoea, and identification of symptomatic individuals with severe airflow obstruction despite a low apnoea-hypopnoea index (AHI). Here we provide a novel method that uses simple airflow-versus-time (""shape"") features from individual breaths on an overnight sleep study to automatically and non-invasively quantify the severity of airflow obstruction without oesophageal catheterisation. Methods: 41 individuals with suspected/diagnosed obstructive sleep apnoea (AHI range 0-91 events.h(-1)) underwent overnight polysomnography with gold-standard measures of airflow (oronasal pneumotach: ""flow"") and ventilatory drive (calibrated intraoesophageal diaphragm electromyogram: ""drive""). Obstruction severity was defined as a continuous variable (flow: drive ratio). Multivariable regression used airflow shape features (inspiratory/expiratory timing, flatness, scooping, fluttering) to estimate flow: drive ratio in 136264 breaths (performance based on leave-one-patient-out cross-validation). Analysis was repeated using simultaneous nasal pressure recordings in a subset (n=17). Results: Gold-standard obstruction severity (flow: drive ratio) varied widely across individuals independently of AHI. A multivariable model (25 features) estimated obstruction severity breath-by-breath (R-2=0.58 versus gold-standard, p<0.00001; mean absolute error 22%) and the median obstruction severity across individual patients (R-2=0.69, p<0.00001; error 10%). Similar performance was achieved using nasal pressure. Conclusions: The severity of pharyngeal obstruction can be quantified non-invasively using readily available airflow shape information. Our work overcomes a major hurdle necessary for the recognition and phenotyping of patients with obstructive sleep disordered breathing.
- 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.
- Palatal prolapse as a signature of expiratory flow limitation and inspiratory palatal collapse in patients with obstructive sleep apnoea(2018) AZARBARZIN, Ali; SANDS, Scott A.; MARQUES, Melania; GENTA, Pedro R.; TARANTO-MONTEMURRO, Luigi; MESSINEO, Ludovico; WHITE, David P.; WELLMAN, AndrewIn some individuals with obstructive sleep apnoea (OSA), the palate prolapses into the velopharynx during expiration, limiting airflow through the nose or shunting it out of the mouth. We hypothesised that this phenomenon causes expiratory flow limitation (EFL) and is associated with inspiratory '' isolated '' palatal collapse. We also wanted to provide a robust noninvasive means to identify this mechanism of obstruction. Using natural sleep endoscopy, 1211 breaths from 22 OSA patients were scored as having or not having palatal prolapse. The patient-level site of collapse (tongue-related, isolated palate, pharyngeal lateral walls and epiglottis) was also characterised. EFL was quantified using expiratory resistance at maximal epiglottic pressure. A noninvasive EFL index (EFLI) was developed to detect the presence of palatal prolapse and EFL using the flow signal alone. In addition, the validity of using nasal pressure was assessed. A cut-off value of EFLI >0.8 detected the presence of palatal prolapse and EFL with an accuracy of >95% and 82%, respectively. The proportion of breaths with palatal prolapse predicted isolated inspiratory palatal collapse with 90% accuracy. This study demonstrates that expiratory palatal prolapse can be quantified noninvasively, is associated with EFL and predicts the presence of inspiratory isolated palatal collapse.