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Dive into the research topics where Quan Ni is active.

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Featured researches published by Quan Ni.


European Respiratory Journal | 2015

Effect of upper-airway stimulation for obstructive sleep apnoea on airway dimensions

Faiza Safiruddin; Olivier M. Vanderveken; Nico de Vries; Joachim T. Maurer; Kent Lee; Quan Ni; Kingman P. Strohl

Upper-airway stimulation (UAS) using a unilateral implantable neurostimulator for the hypoglossal nerve is an effective therapy for obstructive sleep apnoea patients with continuous positive airway pressure intolerance. This study evaluated stimulation effects on retropalatal and retrolingual dimensions during drug-induced sedation compared with wakefulness to assess mechanistic relationships in response to UAS. Patients with an implanted stimulator underwent nasal video endoscopy while awake and/or during drug-induced sedation in the supine position. The cross-sectional area, anterior–posterior and lateral dimensions of the retropalatal and retrolingual regions were measured during baseline and stimulation. 15 patients underwent endoscopy while awake and 12 underwent drug-induced sedation endoscopy. Increased levels of stimulation were associated with increased area of both the retropalatal and retrolingual regions. During wakefulness, a therapeutic level of stimulation increased the retropalatal area by 56.4% (p=0.002) and retrolingual area by 184.1% (p=0.006). During stimulation, the retropalatal area enlarged in the anterior–posterior dimension while retrolingual area enlarged in both anterior–posterior and lateral dimensions. During drug-induced sedation endoscopy, the same stimulation increased the retropalatal area by 180.0% (p=0.002) and retrolingual area by 130.1% (p=0.008). Therapy responders had larger retropalatal enlargement with stimulation than nonresponders. UAS increases both the retropalatal and retrolingual areas. This multilevel enlargement may explain reductions of the apnoea–hypopnoea index in selected patients receiving this therapy. Upper-airway stimulation for OSA increases airway dimensions at both the tongue base and the palate http://ow.ly/zZ4hk


Pacing and Clinical Electrophysiology | 2003

Comparison of Impedance Minute Ventilation and Direct Measured Minute Ventilation in a Rate Adaptive Pacemaker

Ron Simon; Quan Ni; Roger Willems; Jesse W. Hartley; Douglas R. Daum; Douglas J. Lang; Kevin Ward; Jaswinder Gill

Respiration rate (RR) and minute ventilation (MV) provide important clinical information on the state of the patient. This study evaluated the accuracy of determining these using a pacemaker impedance sensor. In 20 patients who were previously implanted with a Guidant PULSAR MAX group of pacemakers, the telemetered impedance sensor waveform was recorded simultaneously with direct volume respiration waveforms as measured by a pneumatometer. Patients underwent 30 minutes of breathing tests while supine and standing, and a 10‐minute ergonometer bicycle exercise test at a workload of 50 W. Breathing tests included regular and rapid‐shallow breathing sequences. RR was determined by a computerized algorithm, from impedance and respiration signals. The mean RR by impedance was 21.3 ± 7.7 breaths/min, by direct volume was 21.1 ± 7.6 breaths/min, range 7–66, the mean difference of RR measured by the impedance sensor, as compared with the true measurement, being 0.2 ± 2.1 breaths/min. During the entire exercise, the mean correlation coefficient between impedance (iMV) and direct measured MV was 0.96 ± 0.03, slope 0.13 ± 0.05 L/Ω and range 0.07–0.26 L/Ω. Bland‐Altman limits of agreement were ± 4.6 L/min for MV versus iMV with each patient calibrated separately. The correlation coefficient for iMV versus MV over the entire 10 minutes of exercise, including the initial 4 minutes of exercise, was 0.99. The transthoracic impedance sensor of an implanted pacemaker can accurately detect respiration parameters. There was a large variation between subjects in the iMV versus MV slope during a bicycle exercise test, whereas for each subject, the slope was stable during submaximal bicycle exercise. (PACE 2003; 26:2127–2133)


Pacing and Clinical Electrophysiology | 2006

Feasibility of Automated Detection of Advanced Sleep Disordered Breathing Utilizing an Implantable Pacemaker Ventilation Sensor

A. L. A. A. Shalaby; Charles W. Atwood; Claudius Hansen; Martin Konermann; Pradip Jamnadas; Kent Lee; Roger Willems; Jesse W. Hartley; Jeffrey E. Stahmann; Jonathan Kwok; Quan Ni; Joerg Neuzner

Objectives: This study tested the feasibility of automatically detecting advanced sleep disordered breathing (SDB) from a pacemaker trans‐thoracic impedance sensor.


Archive | 2003

Sleep quality data collection and evaluation

John D. Hatlestad; Quan Ni; Jeffrey E. Stahmann; Jesse W. Hartley; Qingsheng Zhu; Bruce H. Kenknight; Douglas R. Daum; Kent Lee


Archive | 2003

Therapy triggered by prediction of disordered breathing

Jeffrey E. Stahmann; John D. Hatlestad; Quan Ni; Jesse W. Hartley; Douglas R. Daum; Kent Lee


Archive | 2004

Feedback system and method for sleep disordered breathing therapy

Kent Lee; Jesse W. Hartley; Jeffrey E. Stahmann; Quan Ni


Archive | 2004

Posture detection system and method

Jesse W. Hartley; Jeffrey E. Stahmann; Kent Lee; Quan Ni


Archive | 2004

Automatic activation of medical processes

Kent Lee; Jeffrey E. Stahmann; Jesse W. Hartley; Quan Ni


Archive | 2004

System and method for detecting an involuntary muscle movement disorder

Jeffrey E. Stahmann; Jesse W. Hartley; Kent Lee; Quan Ni


Archive | 2004

System and method for discrimination of central and obstructive disordered breathing events

Kent Lee; John D. Hatlestad; Qingsheng Zhu; Jeffrey E. Stahmann; Jesse W. Hartley; Quan Ni

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