Acute thoracoabdominal and hemodynamic responses to tapered flow resistive loading in healthy adults

We investigated the acute physiological responses of tapered flow resistive loading (TFRL) at 30, 50 and 70% maximal inspiratory pressure (PImax) in 12 healthy adults to determine an optimal resistive load. Increased end-inspiratory rib cage and decreased end-expiratory abdominal volumes equally contributed to the expansion of thoracoabdominal tidal volume (captured by optoelectronic plethysmography). A significant decrease in end-expiratory thoracoabdominal volume was observed from 30 to 50% PImax, from 30 to 70% PImax, and from 50 to 70% PImax. Cardiac output (recorded by cardio-impedance) increased from rest by 30% across the three loading trials. Borg dyspnoea increased from 2.36 ± 0.20 at 30% PImax, to 3.45 ± 0.21 at 50% PImax, and 4.91 ± 0.25 at 70% PImax. End-tidal CO2 decreased from rest during 30, 50 and 70 %PImax (26.23 ± 0.59, 25.87 ± 1.02 and 24.30 ± 0.82 mmHg, respectively). Optimal intensity for TFRL is at 50% PImax to maximise global respiratory muscle and cardiovascular loading whilst minimising hyperventilation and breathlessness

Effect of portable noninvasive ventilation on thoracoabdominal volumes in recovery from intermittent exercise in patients with COPD

We previously showed that use of portable noninvasive ventilation (pNIV) during recovery periods within intermittent exercise improved breathlessness and exercise tolerance in patients with COPD compared with pursed-lip breathing (PLB). However, in a minority of patients recovery from dynamic hyperinflation (DH) was better with PLB, based on inspiratory capacity. We further explored this using Optoelectronic Plethysmography to assess total and compartmental thoracoabdominal volumes. Fourteen patients with COPD (means ± SD) (FEV1: 55% ± 22% predicted) underwent, in a balanced order sequence, two intermittent exercise protocols on the cycle ergometer consisting of five repeated 2-min exercise bouts at 80% peak capacity, separated by 2-min recovery periods, with application of pNIV or PLB in the 5 min of recovery. Our findings identified seven patients showing recovery in DH with pNIV (DH responders) whereas seven showed similar or better recovery in DH with PLB. When pNIV was applied, DH responders compared with DH nonresponders exhibited greater tidal volume (by 0.8 ± 0.3 L, P = 0.015), inspiratory flow rate (by 0.6 ± 0.5 L/s, P = 0.049), prolonged expiratory time (by 0.6 ± 0.5 s, P = 0.006), and duty cycle (by 0.7 ± 0.6 s, P = 0.007). DH responders showed a reduction in end-expiratory thoracoabdominal DH (by 265 ± 633 mL) predominantly driven by reduction in the abdominal compartment (by 210 ± 494 mL); this effectively offset end-inspiratory rib-cage DH. Compared with DH nonresponders, DH responders had significantly greater body mass index (BMI) by 8.4 ± 3.2 kg/m2, P = 0.022 and tended toward less severe resting hyperinflation by 0.3 ± 0.3 L. Patients with COPD who mitigate end-expiratory rib-cage DH by expiratory abdominal muscle recruitment benefit from pNIV application. NEW & NOTEWORTHY Compared with the pursed-lip breathing technique, acute application of portable noninvasive ventilation during recovery from intermittent exercise improved end-expiratory thoracoabdominal dynamic hyperinflation (DH) in 50% of patients with COPD (DH responders). DH responders, compared with DH nonresponders, exhibited a reduction in end-expiratory thoracoabdominal DH predominantly driven by the abdominal compartment that effectively offset end-expiratory rib cage DH. The essential difference between DH responders and DH nonresponders was, therefore, in the behavior of the abdomen

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement–the Mobilise-D study protocol

Background: The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who are working together to jointly develop and implement a digital mobility assessment solution to demonstrate that real-world digital mobility outcomes have the potential to provide a better, safer, and quicker way to assess, monitor, and predict the efficacy of new interventions on impaired mobility. The overarching objective of the study is to establish the clinical validity of digital outcomes in patient populations impacted by mobility challenges, and to support engagement with regulatory and health technology agencies towards acceptance of digital mobility assessment in regulatory and health technology assessment decisions. Methods/design: The Mobilise-D clinical validation study is a longitudinal observational cohort study that will recruit 2400 participants from four clinical cohorts. The populations of the Innovative Medicine Initiative-Joint Undertaking represent neurodegenerative conditions (Parkinson’s Disease), respiratory disease (Chronic Obstructive Pulmonary Disease), neuro-inflammatory disorder (Multiple Sclerosis), fall-related injuries, osteoporosis, sarcopenia, and frailty (Proximal Femoral Fracture). In total, 17 clinical sites in ten countries will recruit participants who will be evaluated every six months over a period of two years. A wide range of core and cohort specific outcome measures will be collected, spanning patient-reported, observer-reported, and clinician-reported outcomes as well as performance-based outcomes (physical measures and cognitive/mental measures). Daily-living mobility and physical capacity will be assessed directly using a wearable device. These four clinical cohorts were chosen to obtain generalizable clinical findings, including diverse clinical, cultural, geographical, and age representation. The disease cohorts include a broad and heterogeneous range of subject characteristics with varying chronic care needs, and represent different trajectories of mobility disability. Discussion: The results of Mobilise-D will provide longitudinal data on the use of digital mobility outcomes to identify, stratify, and monitor disability. This will support the development of widespread, cost-effective access to optimal clinical mobility management through personalised healthcare. Further, Mobilise-D will provide evidence-based, direct measures which can be endorsed by regulatory agencies and health technology assessment bodies to quantify the impact of disease-modifying interventions on mobility. Trial registration: ISRCTN12051706

Clinical validation of digital mobility outcomes in patients with chronic obstructive pulmonary disease

Recent technological advances have enabled us to assess Digital Mobility Outcomes (DMOs) referring to gait characteristics measured in real world conditions using lower back inertial measurement units (IMUs) in health and disease. In COPD, mobility impairment is evident compared to healthy individuals, and whilst the predictive capacity of gait and mobility parameters is high, their construct validity and sensitivity to detect change following different pharmacological and non-pharmacological interventions remain uncertain. This thesis contributed to the clinical validation of novel DMOs developed as part of the joint EU/IMI-funded Mobilise-D project in patients with COPD. A systematic review and meta-analysis evaluated the effect of all available pharmacological and non-pharmacological interventions on physical activity outcomes in COPD patients. Interventions involving bronchodilator therapy and those focusing on behavioural modifications to enhance physical activity demonstrated notable success in significantly increasing daily step counts. In contrast, interventions centred around exercise training, conducted within outpatient or community-based pulmonary rehabilitation programmes or through telerehabilitation, exhibited inconsistent efficacy in improving physical activity outcomes, with observed variations in effects and directions across studies. The construct validity of novel DMOs was assessed during laboratory based, free-living habitual and real-world settings. Irrespective of the degree of lung dysfunction, cadence, walking speed, stride duration and single support duration were shown to be sensitive in reflecting COPD symptom burden. The efficacy of machine learning models for predicting COPD clinical outcomes using real-world DMOs was established. Notably, neural network models outperformed logistic regression and linear regression in terms of accuracy rates, demonstrating robust agreement, precision, accuracy, and sensitivity across variables. DMOs reflecting real-world mobility hold great promise for remote patient monitoring, assessing treatment effects and establishing future biomarkers for regulatory approval while providing a more comprehensive understanding of the holistic health status in patients with COPD

Defragmentering. En fotobok om fragment

How do you reed a book? Do you start at the beginning, or do you begin with the end or maybe in the middle? In my exam project I elected to work with a photographic publication about fragments of pictures combined in different ways, changing the context of the photographs and making the reader search for the whole picture, literary. During the project I tried to create a method for folding which would make the pictures communicate differently depending on how they where stacked against each other. I wanted to explore new ways to read the photo book, and how the format could be transformed by folding, to be able to show the pictures in a larger scale. Working with the material from an earlier project about defragmentation, I wanted to create a book that would correspond to this and figure out how it would work

Ergogenic value of oxygen supplementation in chronic obstructive pulmonary disease

Patients with COPD exhibit limited exercise endurance time compared to healthy age-matched individuals. Oxygen supplementation is often applied to improve endurance time during pulmonary rehabilitation in patients with COPD and thus a comprehensive understanding of the mechanisms leading to improved endurance is desirable. This review analyses data from two studies by our research group investigating the effect of oxygen supplementation on cerebrovascular, systemic, respiratory and locomotor muscle oxygen availability on the same cohort of individuals with advanced COPD, and the mechanisms associated with improved endurance time in hyperoxia, which was essentially doubled (at the same power output). In hyperoxia at isotime (the time at which patients became exhausted in normoxia) exercise was associated with greater respiratory and locomotor muscle (but not frontal cortex) oxygen delivery (despite lower cardiac output), lower lactate concentration and less tachypnoea. Frontal cortex oxygen saturation was higher, and respiratory drive lower. Hence, improved endurance in hyperoxia appears to be facilitated by several factors: increased oxygen availability to the respiratory and locomotor muscles, less metabolic acidosis, and lower respiratory drive. At exhaustion in both normoxia and hyperoxia, only cardiac output and breathing pattern were not different between conditions. However, minute ventilation in hyperoxia exceeded the critical level of ventilatory constraints (V(E)/MVV > 75–80%). Lactate remained lower and respiratory and locomotor muscle oxygen delivery greater in hyperoxia, suggesting greater muscle oxygen availability improving muscle function. Taken together, these findings suggest that central haemodynamic and ventilatory limitations and not contracting muscle conditions dictate endurance time in COPD during exercise in hyperoxia

Effects of pharmacological and nonpharmacological interventions on physical activity outcomes in COPD: a systematic review and meta-analysis

Abstract Rationale The effect of pharmacological and non-pharmacological interventions on physical activity (PA) outcomes is not fully elucidated in patients with COPD. Objectives To provide estimation of treatment effects of all available interventions on PA outcomes in patients with COPD and to provide recommendations regarding the future role of PA outcomes in pharmacological trials. Materials and methods This review was conducted according to the Cochrane Handbook and reported in line with PRISMA. Records were identified through searches of 12 scientific databases; the most updated search was performed in January 2023. Results: Seventy-four studies published from 2000 to 2021 were included, with a total of 8140 COPD patients. FEV1% predicted ranged between 31% and 74%, with a mean of 55%. Steps/day constituted the most frequently assessed PA outcome in interventional studies. Compared to usual care (UC), PA behavioural modification interventions resulted in improvements in the mean (95% CI) steps/day when implemented alone (by 1035 (576, 1493); p<0.00001) or alongside exercise training (by 679 (93, 1266; p=0.02)). Moreover, bronchodilator therapy yielded a favourable difference of 396 (125, 668; p=0.004) steps/day, compared to placebo. Conclusions PA behavioural modification and pharmacological interventions lead to significant improvements in steps/day, compared to control and placebo groups, respectively. Compared to bronchodilator therapy, PA behavioural modification interventions were associated with a 2-fold greater improvement in steps/day. Large-scale pharmacological studies are needed to establish an intervention-specific MCID for PA outcomes as well as their convergent validity to accelerate qualification as potential biomarkers and efficacy endpoints for regulatory approval.This work was supported by the Mobilise-D project that has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No. 820820. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation program and the European Federation of Pharmaceutical Industries and Associations (EFPIA). Content in this publication reflects the authors' view and neither IMI nor the European Union, EFPIA, or any Associated Partners are responsible for any use that may be made of the information contained herein

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases

The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings.MethodsHere, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data.Results and discussionThe results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of −0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, −0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases