Severe Asthma Standard-of-Care Background Medication Reduction With Benralizumab: ANDHI in Practice Substudy

Background: The phase IIIb, randomized, parallel-group, placebo-controlled ANDHI double-blind (DB) study extended understanding of the efficacy of benralizumab for patients with severe eosinophilic asthma. Patients from ANDHI DB could join the 56-week ANDHI in Practice (IP) single-arm, open-label extension substudy. Objective: Assess potential for standard-of-care background medication reductions while maintaining asthma control with benralizumab. Methods: Following ANDHI DB completion, eligible adults were enrolled in ANDHI IP. After an 8-week run-in with benralizumab, there were 5 visits to potentially reduce background asthma medications for patients achieving and maintaining protocol-defined asthma control with benralizumab. Main outcome measures for non-oral corticosteroid (OCS)-dependent patients were the proportions with at least 1 background medication reduction (ie, lower inhaled corticosteroid dose, background medication discontinuation) and the number of adapted Global Initiative for Asthma (GINA) step reductions at end of treatment (EOT). Main outcomes for OCS-dependent patients were reductions in daily OCS dosage and proportion achieving OCS dosage of 5 mg or lower at EOT. Results: For non-OCS-dependent patients, 53.3% (n = 208 of 390) achieved at least 1 background medication reduction, increasing to 72.6% (n = 130 of 179) for patients who maintained protocol-defined asthma control at EOT. A total of 41.9% (n = 163 of 389) achieved at least 1 adapted GINA step reduction, increasing to 61.8% (n = 110 of 178) for patients with protocol-defined EOT asthma control. At ANDHI IP baseline, OCS dosages were 5 mg or lower for 40.4% (n = 40 of 99) of OCS-dependent patients. Of OCS-dependent patients, 50.5% (n = 50 of 99) eliminated OCS and 74.7% (n = 74 of 99) achieved dosages of 5 mg or lower at EOT. Conclusions: These findings demonstrate benralizumab's ability to improve asthma control, thereby allowing background medication reduction

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Mandibular jaw movements as a non-invasive measure of respiratory effort during sleep: application in clinical practice

Assessment of respiratory eort (RE) is key for characterization of respiratory events. The discrimination between central and obstructive events is important because these events are caused by dierent physio-pathological mechanisms and require dierent treatment approaches. Many of the currently available options for home sleep apnea testing either do not measure RE, or RE signal recording is not always reliable. This is due to a variety of factors, including for instance wrong placement of the respiratory inductance plethysmography (RIP) sensors leading to artifacts or signal loss. Monitoring of mandibular jaw movements (MJM) provides the ability to accurately measure RE through a single point of contact sensor placed on the patient’s chin. The inertial unit included in the capturing technology and overnight positional stability of the sensor provide a robust MJM bio-signal to detect sleep-disordered breathing (SDB). Many of the pharyngeal muscles are attached to the mandible directly, or indirectly via the hyoid bone. The motor trigeminal nerve impulses to contract or relax these muscles generate discrete MJM that reflect changes in RE during sleep. Indeed, the central drive utilizes the lower jaw as a fine-tuning lever to stien the upper airway musculature and safeguard the patency of the pharynx. Associations between the MJM bio-signal properties and both physiological and pathological breathing patterns during sleep have been extensively studied. These show a close relationship between changes in the MJM bio-signal as a function of RE that is similar to levels of RE measured simultaneously by the reference bio-signals such as esophageal pressure or crural diaphragmatic electromyography. Specific waveforms, frequencies, and amplitudes of these discrete MJM are seen across a variety of breathing disturbances that are recommended to be scored by the American Academy of Sleep Medicine. Moreover, MJM monitoring provides information about sleep/wake states and arousals, which enables total sleep time measurement for accurate calculation of conventional hourly indices. The MJM bio-signal can be interpreted and its automatic analysis using a dedicatedmachine learning algorithmdelivers a comprehensive and clinically informative study report that provides physicians with the necessary information to aid in the diagnosis of SDB

Insights on mandibular jaw movements during polysomnography in obstructive sleep apnea

A strong and specific comprehensive physiological association has been documented between mandibular jaw movements and related periods of normal or disturbed breathing across different sleep stages. The mandibular jaw movement biosignal can be incorporated in the polysomnography, displayed on the screen as a function of time like any standard polysomnography signal (eg, airflow, oxygen saturation, respiratory inductance plethysmography bands) and interpreted in the context of the target period of breathing and its associated respiratory effort level. Overall, the mandibular jaw movement biosignal that depicts the muscular trigeminal respiratory drive is a highly effective tool for differentiating between central and obstructive sleep episodes including hypopneas and for providing clinicians with valuable insights into wake/sleep states, arousals, and sleep stages. These fundamental characteristics of the mandibular jaw movement biosignal contrast with photoplethysmography, airflow, or oxygen saturation signals that provide information more about the consequence of the disturbed breathing episode than about the event itself. Malhotra A, Martinot J-B, Pépin J-L. Insights on mandibular jaw movements during polysomnography in obstructive sleep apnea. . 2024;20(1):151-163

Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea

International audienceMechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort (RE) 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 RE (percentage of sleep time spent with increased RE based on measurement of mandibular jaw movements [MJM]; REMOV, %TST) and prevalent hypertension in adults referred for evaluation of suspected OSA. A machine learning model was built to predict hypertension from clinical data, conventional polysomnography (PSG) indices, and MJM-derived parameters (including REMOV, %TST). The model was evaluated in a training subset and a test subset. The analysis included 1127 patients, 901 (80%) in the training subset and 226 (20%) in the test subset. The prevalence of hypertension was 31% and 30%, respectively, in the training and test subsets. A risk stratification model based on eighteen input features including REMOV had good accuracy for predicting prevalent hypertension (sensitivity 0.75, specificity 0.83). Using the Shapley additive explanation (SHAP) method, REMOV was the best predictor of hypertension after clinical risk factors (age, sex, body mass index, neck circumference) and time with oxygen saturation <90%, ahead òf standard PSG metrics (including the apnoea-hypopnoea index and oxygen desaturation index). The proportion of sleep time spent with increased RE automatically derived from MJM was identified as a potential new reliable metric to predict prevalent hypertension in patients with OSA

Near-boundary double-labeling-based classification: the new standard when evaluating performances of new sleep apnea diagnostic solutions against polysomnography?

International audienceNo abstract availabl

Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea

International audienceMechanisms underlying blood pressure changes in obstructive sleep apnoea (OSA) are incompletely understood. Increased respiratory effort (RE) 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 RE (percentage of sleep time spent with increased RE based on measurement of mandibular jaw movements [MJM]; REMOV, %TST) and prevalent hypertension in adults referred for evaluation of suspected OSA. A machine learning model was built to predict hypertension from clinical data, conventional polysomnography (PSG) indices, and MJM-derived parameters (including REMOV, %TST). The model was evaluated in a training subset and a test subset. The analysis included 1127 patients, 901 (80%) in the training subset and 226 (20%) in the test subset. The prevalence of hypertension was 31% and 30%, respectively, in the training and test subsets. A risk stratification model based on eighteen input features including REMOV had good accuracy for predicting prevalent hypertension (sensitivity 0.75, specificity 0.83). Using the Shapley additive explanation (SHAP) method, REMOV was the best predictor of hypertension after clinical risk factors (age, sex, body mass index, neck circumference) and time with oxygen saturation <90%, ahead òf standard PSG metrics (including the apnoea-hypopnoea index and oxygen desaturation index). The proportion of sleep time spent with increased RE automatically derived from MJM was identified as a potential new reliable metric to predict prevalent hypertension in patients with OSA

Respiratory effort during sleep and prevalent hypertension in obstructive sleep apnoea.

BackgroundMechanisms 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.MethodsA machine learning model was built to predict hypertension from clinical data, conventional polysomnography (PSG) indices and MJM-derived parameters (including REMOV). The model was evaluated in a training subset and a test subset.ResultsThe analysis included 1127 patients: 901 (80%) in the training subset and 226 (20%) in the test subset. The prevalence of hypertension was 31% and 30%, respectively, in the training and test subsets. A risk stratification model based on 18 input features including REMOV had good accuracy for predicting prevalent hypertension (sensitivity 0.75 and specificity 0.83). Using the Shapley additive explanation method, REMOV was the best predictor of hypertension after clinical risk factors (age, sex, body mass index and neck circumference) and time with oxygen saturation &lt;90%, ahead of standard PSG metrics (including the apnoea-hypopnoea index and oxygen desaturation index).ConclusionThe proportion of sleep time spent with increased respiratory effort automatically derived from MJM was identified as a potential new reliable metric to predict prevalent hypertension in patients with OSA

Echocardiographic and Tissue Doppler Imaging of Cardiac Adaptation to High Altitude in Native Highlanders Versus Acclimatized Lowlanders

High-altitude exposure is a cause of pulmonary hypertension and decreased exercise capacity, but associated changes in cardiac function remain incompletely understood. The aim of this study was to investigate right ventricular (RV) and left ventricular function in acclimatized Caucasian lowlanders compared with native Bolivian highlanders at high altitudes. Standard echocardiography and tissue Doppler imaging studies were performed in 15 healthy lowlanders at sea level; <24 hours after arrival in La Paz, Bolivia, at 3,750 m; and after 10 days of acclimatization and ascent to Huayna Potosi, at 4,850 m, and the results were compared with those obtained in 15 age- and body size-matched inhabitants of Oruro, Bolivia, at 4,000 m. Acute exposure to high altitude in lowlanders caused an increase in mean pulmonary arterial pressure, to 20 to 25 mm Hg, and altered RV and left ventricular diastolic function, with prolonged isovolumic relaxation time, an increased RV Tei index, and maintained RV systolic function as estimated by tricuspid annular plane excursion and the tricuspid annular S wave. This profile was essentially unchanged after acclimatization and ascent to 4,850 m, except for higher pulmonary arterial pressure. The native highlanders presented with relatively lower pulmonary arterial pressures but more pronounced alterations in diastolic function, decreased tricuspid annular plane excursion and tricuspid annular S waves, and increased RV Tei indexes. In conclusion, cardiac adaptation to high altitude was qualitatively similar in acclimatized Caucasian lowlanders and in Bolivian native highlanders. However, lifelong exposure to high altitude may be associated with different cardiac adaptation to milder hypoxic pulmonary hypertension. © 2009 Elsevier Inc. All rights reserved.SCOPUS: ar.jinfo:eu-repo/semantics/publishe