Bronchiectasis in India:results from the European Multicentre Bronchiectasis Audit and Research Collaboration (EMBARC) and Respiratory Research Network of India Registry

BACKGROUND: Bronchiectasis is a common but neglected chronic lung disease. Most epidemiological data are limited to cohorts from Europe and the USA, with few data from low-income and middle-income countries. We therefore aimed to describe the characteristics, severity of disease, microbiology, and treatment of patients with bronchiectasis in India. METHODS: The Indian bronchiectasis registry is a multicentre, prospective, observational cohort study. Adult patients ( 6518 years) with CT-confirmed bronchiectasis were enrolled from 31 centres across India. Patients with bronchiectasis due to cystic fibrosis or traction bronchiectasis associated with another respiratory disorder were excluded. Data were collected at baseline (recruitment) with follow-up visits taking place once per year. Comprehensive clinical data were collected through the European Multicentre Bronchiectasis Audit and Research Collaboration registry platform. Underlying aetiology of bronchiectasis, as well as treatment and risk factors for bronchiectasis were analysed in the Indian bronchiectasis registry. Comparisons of demographics were made with published European and US registries, and quality of care was benchmarked against the 2017 European Respiratory Society guidelines. FINDINGS: From June 1, 2015, to Sept 1, 2017, 2195 patients were enrolled. Marked differences were observed between India, Europe, and the USA. Patients in India were younger (median age 56 years [IQR 41-66] vs the European and US registries; p<0\ub70001]) and more likely to be men (1249 [56\ub79%] of 2195). Previous tuberculosis (780 [35\ub75%] of 2195) was the most frequent underlying cause of bronchiectasis and Pseudomonas aeruginosa was the most common organism in sputum culture (301 [13\ub77%]) in India. Risk factors for exacerbations included being of the male sex (adjusted incidence rate ratio 1\ub717, 95% CI 1\ub703-1\ub732; p=0\ub7015), P aeruginosa infection (1\ub729, 1\ub710-1\ub750; p=0\ub7001), a history of pulmonary tuberculosis (1\ub720, 1\ub707-1\ub734; p=0\ub7002), modified Medical Research Council Dyspnoea score (1\ub732, 1\ub725-1\ub739; p<0\ub70001), daily sputum production (1\ub716, 1\ub703-1\ub730; p=0\ub7013), and radiological severity of disease (1\ub703, 1\ub701-1\ub704; p<0\ub70001). Low adherence to guideline-recommended care was observed; only 388 patients were tested for allergic bronchopulmonary aspergillosis and 82 patients had been tested for immunoglobulins. INTERPRETATION: Patients with bronchiectasis in India have more severe disease and have distinct characteristics from those reported in other countries. This study provides a benchmark to improve quality of care for patients with bronchiectasis in India. FUNDING: EU/European Federation of Pharmaceutical Industries and Associations Innovative Medicines Initiative inhaled Antibiotics in Bronchiectasis and Cystic Fibrosis Consortium, European Respiratory Society, and the British Lung Foundation

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Automated gap-filling for marker-based biomechanical motion capture data

Marker-based motion capture presents the problem of gaps, which are traditionally processed using motion capture software, requiring intensive manual input. We propose and study an automated method of gap-filling that uses inverse kinematics (IK) to close the loop of an iterative process to minimize error, while nearly eliminating user input. Comparing our method to manual gap-filling, we observe a 21% reduction in the worst-case gap-filling error (p < 0.05), and an 80% reduction in completion time (p < 0.01). Our contribution encompasses the release of an open-source repository of the method and interaction with OpenSim

Automated gap-filling for marker-based biomechanical motion capture data

Marker-based motion capture presents the problem of gaps, which are traditionally processed using motion capture software, requiring intensive manual input. We propose and study an automated method of gap-filling that uses inverse kinematics (IK) to close the loop of an iterative process to minimize error, while nearly eliminating user input. Comparing our method to manual gap-filling, we observe a 21% reduction in the worst-case gap-filling error (p < 0.05), and an 80% reduction in completion time (p < 0.01). Our contribution encompasses the release of an open-source repository of the method and interaction with OpenSim

Fake news research trends, linkages to generative artificial intelligence and sustainable development goals

In the digital age, where information is a cornerstone for decision-making, social media's not-so-regulated environment has intensified the prevalence of fake news, with significant implications for both individuals and societies. This study employs a bibliometric analysis of a large corpus of 9678 publications spanning 2013–2022 to scrutinize the evolution of fake news research, identifying leading authors, institutions, and nations. Three thematic clusters emerge: Disinformation in social media, COVID-19-induced infodemics, and techno-scientific advancements in auto-detection. This work introduces three novel contributions: 1) a pioneering mapping of fake news research to Sustainable Development Goals (SDGs), indicating its influence on areas like health (SDG 3), peace (SDG 16), and industry (SDG 9); 2) the utilization of Prominence percentile metrics to discern critical and economically prioritized research areas, such as misinformation and object detection in deep learning; and 3) an evaluation of generative AI's role in the propagation and realism of fake news, raising pressing ethical concerns. These contributions collectively provide a comprehensive overview of the current state and future trajectories of fake news research, offering valuable insights for academia, policymakers, and industry

Tunable Mie-Resonant Dielectric Metasurfaces Based on VO2 Phase-Transition Materials

International audienceDielectric metasurfaces have become efficient tools for creating ultrathin optical components with various functionalities for imaging, holography, quantum optics, and topological photonics. While static all-dielectric resonant metaphotonics is reaching maturity, challenges remain in the design and fabrication of efficient reconfigurable and tunable metasurface structures. A promising pathway toward tunable metasurfaces is by incorporating phase-transition materials into the photonic structure design. Here we demonstrate Mie-resonant silicon-based metasurfaces tunable via the insulator-to-metal transition of a thin VO 2 layer with reversible properties at telecom wavelengths. We experimentally demonstrate two regimes of functional tunability driven by the VO 2 transition: (i) 2 orders of magnitude modulation of the metasurface transmission, (ii) spectral tuning of near-perfect absorption. Both functionalities are accompanied by a hysteresis-like behavior that can be exploited for versatile memory effects. Beyond this demonstration of multifunctional properties, this work provides a general framework to efficiently use the full complex refractive index tuning of VO 2 , for both its refractive index modulation and optical absorption tuning. Tunable dielectric metasurfaces may find their applications in various photonics technologies including optical communications, information storage, imaging, detectors, and sensors