Publications by authors named "Nhat-Nam Le-Dong"

Purpose: This review aims to highlight the pivotal role of the mandibular jaw movement (MJM) signal in advancing artificial intelligence (AI)-powered technologies for diagnosing obstructive sleep apnea (OSA).

Methods: A scoping review was conducted to evaluate various aspects of the MJM signal and their contribution to improving signal proficiency for users.

Results: The comprehensive literature analysis is structured into four key sections, each addressing factors essential to signal proficiency.

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Oral appliances are second-line treatments after continuous positive airway pressure for obstructive sleep apnea (OSA) management. However, the need for oral appliance titration limits their use as a result of monitoring challenges to assess the treatment effect on OSA. To assess the validity of mandibular jaw movement (MJM) automated analysis compared with polysomnography (PSG) and polygraphy (PG) in evaluating the effect of oral appliance treatment and the effectiveness of MJM monitoring for oral appliance titration at home in patients with OSA.

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Background: A single-night attended in-laboratory polysomnography or home sleep testing are common approaches for obstructive sleep apnea (OSA) diagnosis. However, internight variability in apnea-hypopnea index value is common, and may result in misclassification of OSA severity and inapropriate treatment decisions.

Objective: To investigate factors determining short-term apnea-hypopnea index variability using multi-night automated home sleep testing, and to determine how this variability impacts clinical decisions.

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Article Synopsis
  • - The study aimed to explore the link between total sleep time spent with increased respiratory effort and type 2 diabetes prevalence in individuals suspected of having obstructive sleep apnoea.
  • - Researchers analyzed data from 1,128 patients using a machine-learning model that combined clinical, polysomnography, and jaw movement measurements to predict diabetes prevalence.
  • - Results indicated that the amount of sleep time spent with increased respiratory effort was a significant predictor of type 2 diabetes, even more influential than some traditional clinical measures.
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Background: Mechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort is one of the main features of OSA and is associated with sympathetic overactivity, leading to increased vascular wall stiffness and remodelling. This study investigated associations between a new measure of respiratory effort (percentage of total sleep time spent with increased respiratory effort based on measurement of mandibular jaw movements (MJM): REMOV, %TST) and prevalent hypertension in adults referred for evaluation of suspected OSA.

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With the rapid development of computing today, artificial intelligence has become an essential part of everyday life, with medicine and lung health being no exception. Big data-based scientific research does not mean simply gathering a large amount of data and letting the machines do the work by themselves. Instead, scientists need to identify problems whose solution will have a positive impact on patients' care.

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We aimed to investigate the performance of a chest X-ray (CXR) scoring scale of lung injury in prediction of death and ICU admission among patients with COVID-19 during the 2021 peak pandemic in HCM City, Vietnam. CXR and clinical data were collected from Vinmec Central Park-hospitalized patients from July to September 2021. Three radiologists independently assessed the day-one CXR score consisting of both severity and extent of lung lesions (maximum score = 24).

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Purpose: Differentiation between obstructive and central apneas and hypopneas requires quantitative measurement of respiratory effort (RE) using esophageal pressure (PES), which is rarely implemented. This study investigated whether the sleep mandibular movements (MM) signal recorded with a tri-axial gyroscopic chin sensor (Sunrise, Namur, Belgium) is a reliable surrogate of PES in patients with suspected obstructive sleep apnea (OSA).

Patients And Methods: In-laboratory polysomnography (PSG) with PES and concurrent MM monitoring was performed.

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Background: The capacity to diagnose obstructive sleep apnoea (OSA) must be expanded to meet an estimated disease burden of nearly one billion people worldwide. Validated alternatives to the gold standard polysomnography (PSG) will improve access to testing and treatment. This study aimed to evaluate the diagnosis of OSA, using measurements of mandibular movement (MM) combined with automated machine learning analysis, compared to in-home PSG.

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Article Synopsis
  • The study investigates the use of artificial intelligence to automatically detect stereotypical mandibular jaw movements (MJM) in patients with sleep bruxism (SBx) during sleep studies.
  • Utilizing a hardware device and extreme gradient boosting (XGB) classifier, researchers recorded and analyzed data from 67 patients, achieving high accuracy in identifying episodes of rhythmic masticatory muscle activity (RMMA).
  • Results indicate that the AI model effectively distinguishes RMMA events, showing an 86.6% balanced accuracy and strong agreement with traditional manual scoring methods.
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Purpose: Our study aimed to evaluate the relationship between exhaled nitric oxide (eNO) markers and obstructive sleep apnea (OSA) severity and verify the changes in eNO profiles among mild, moderate, and severe OSA subgroups.

Methods: This study was a cross-sectional and in-hospital population-based study. We investigated 123 OSA patients (17 mild, 23 moderate and, 83 severe OSA) in the department of respiratory diseases.

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Rationale: Mandibular position and motion during sleep rely on the balance between mandibular elevators and depressors. We hypothesized that vertical mandibular position (VMP) modulates airflow amplitude during sleep.

Methods: VMP, tidal nasal flow pressure (NFP) and concurrent surface electromyographic activity of the masseters (sEMG-m) were recorded and processed by a customized algorithm from 100 polysomnographic fragments including a micro-arousal (25 obstructive sleep apnea patients).

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Bruxism is a heterogeneous condition related to various underlying mechanisms, including the presence of OSA. This case report illustrates that sleep mandibular movement monitoring and analysis could provide a useful opportunity for detection of both sleep bruxism and respiratory effort. The current case suggests that tracking of respiratory effort could enable evaluation of bruxism and its potential interactions.

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Importance: Given the high prevalence of obstructive sleep apnea (OSA), there is a need for simpler and automated diagnostic approaches.

Objective: To evaluate whether mandibular movement (MM) monitoring during sleep coupled with an automated analysis by machine learning is appropriate for OSA diagnosis.

Design, Setting, And Participants: Diagnostic study of adults undergoing overnight in-laboratory polysomnography (PSG) as the reference method compared with simultaneous MM monitoring at a sleep clinic in an academic institution (Sleep Laboratory, Centre Hospitalier Universitaire Université Catholique de Louvain Namur Site Sainte-Elisabeth, Namur, Belgium).

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Accurate discrimination between obstructive and central hypopneas requires quantitative assessments of respiratory effort by esophageal pressure (OeP) measurements, which preclude widespread implementation in sleep medicine practice. Mandibular Movement (MM) signals are closely associated with diaphragmatic effort during sleep. We aimed at reliably detecting obstructive off central hypopneas events using MM statistical characteristics.

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Context: Mandibular movements (MM) are considered as reliable reporters of respiratory effort (RE) during sleep and sleep disordered breathing (SDB), but MM accuracy has never been validated against the gold standard diaphragmatic electromyography (EMG-d).

Objectives: To assess the degree of agreement between MM and EMG-d signals during different sleep stages and abnormal respiratory events.

Methods: Twenty-five consecutive adult patients with SDB were studied by polysomnography (PSG) that also included multipair esophageal diaphragm electromyography and a magnetometer to record MM.

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Background: The patterns of mandibular movements (MM) during sleep can be used to identify increased respiratory effort periodic large-amplitude MM (LPM), and cortical arousals associated with "sharp" large-amplitude MM (SPM). We hypothesized that Cheyne Stokes breathing (CSB) may be identified by periodic abnormal MM patterns. The present study aims to evaluate prospectively the concordance between CSB detected by periodic MM and polysomnography (PSG) as gold-standard.

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Background: The measure of fractional exhaled nitric oxide (FENO) in the airways is a useful tool to guide the diagnosis and titration of inhaled corticosteroids in patients with asthma. However, its role in diagnosis of allergic rhinitis (AR), especially in subjects with asthma, is not well established.

Objective: To study the cutoff of nasal FENO in the diagnosis of subjects with AR and AR-asthma compared to age-matched subjects without AR or asthma and its correlations with the clinical and functional characteristics.

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Background And Objective: The concentration of exhaled nitric oxide (eNO), reflecting the activity of inducible NO synthase in airway epithelium, has been found to increase in patients with obstructive sleep apnea (OSA). This study aimed to measure eNO concentration in patients with suspected OSA and to correlate different eNO parameters with clinical and sleep apnea characteristics.

Methods: In this cross-sectional study, all patients underwent in-lab overnight polysomnography (PSG) and eNO measurement using a method of multiple flow rates before and after PSG (pre- and post-PSG).

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Background: Systemic sclerosis (SSc) is a connective-tissue disease characterized by vascular injury, immune-system disorders, and excessive fibrosis of the skin and multiple internal organs. Recent reports found that RhoA/Rho-kinase (ROCK) pathway is implicated in various fibrogenic diseases. Intradermal injection of hypochlorous acid (HOCl)-generating solution induced inflammation, autoimmune activation, and fibrosis, mimicking the cutaneous diffuse form of SSc in humans.

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Exhaled nitric oxide (NO) is increased as a result of lung inflammation, which in turn causes subsequent interstitial lung disease in patients with systemic sclerosis (SSc). However, the exact time course of inflammatory and fibrotic changes in the SSc lung has not yet been described. Our objective was to assess the chronological evolution of lung inflammatory and fibrotic processes in mice pre-treated with hypochlorous acid (HOCl) or bleomycin.

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Article Synopsis
  • - The study aimed to evaluate inflammation in the lungs of patients suspected to have obstructive sleep apnea (OSA) by measuring exhaled nitric oxide (NO) using a specific two-compartment model that corrects for certain back-diffusion issues.
  • - Ninety-five patients underwent various tests, and results showed significantly higher levels of alveolar NO in OSA patients compared to those without OSA, indicating a strong correlation between NO levels, the severity of sleep apnea (measured by AHI), and low oxygen levels during sleep.
  • - The findings suggest that increased levels of alveolar NO are linked to worse oxygen desaturation at night in OSA patients, highlighting a potential connection between airway inflammation and intermittent lack of oxygen during sleep
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