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Background: Alpha-1 antitrypsin deficiency (AATD) is characterized by low alpha-1 antitrypsin (AAT) levels, predisposing individuals to lung disease. The standard of care, plasma-derived AAT (pdAAT), is delivered as weekly infusions to maintain serum AAT concentrations ≥11µM (≈50% of those in healthy individuals). INBRX-101, a recombinant human AAT-Fc fusion protein, was designed to have a longer half-life and achieve higher AAT levels than pdAAT. Methods: In this phase 1 dose-escalation study (N=31), adults with AATD received 1 dose (part 1) or 3 doses (part 2) of 10 (part 1), 40, 80, or 120mg/kg INBRX-101 every 3 weeks (Q3W) via intravenous infusion. The primary endpoint was safety and tolerability. Secondary endpoints were pharmacokinetics (PK), pharmacodynamics (PD), and immunogenicity of INBRX-101. Results: INBRX-101 was well tolerated. Most treatment-emergent adverse events were grade ≤2. In part 2 (n=18; each dose, n=6), dose-related increases in serum functional AAT (fAAT) were observed; mean fAAT levels remained above the 21 µM target for up to 4 weeks after the final dose in the 120-mg/kg cohort. Antidrug antibodies had no meaningful impact on PK or PD. INBRX-101 was detected in pulmonary epithelial lining fluid (PELF) from all patients assessed (n=11), and PELF fAAT increased after dosing. PK/PD modeling projected steady-state serum fAAT ≥21µM at 120 mg/kg Q3W (average concentration ≈43µM; trough concentration ≈28µM) and Q4W (≈34µM; ≈21µM). Conclusion: The favorable safety profile and ability to maintain serum fAAT levels >21µM with extended-interval dosing, support a phase 2 trial evaluating Q3W and Q4W dosing of INBRX-101.
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INTRODUCTION: Asthma attacks are a leading cause of morbidity and mortality but are preventable in most if detected and treated promptly. However, the changes that occur physiologically and behaviourally in the days and weeks preceding an attack are not always recognised, highlighting a potential role for technology. The aim of this study 'DIGIPREDICT' is to identify early digital markers of asthma attacks using sensors embedded in smart devices including watches and inhalers, and leverage health and environmental datasets and artificial intelligence, to develop a risk prediction model to provide an early, personalised warning of asthma attacks. METHODS AND ANALYSIS: A prospective sample of 300 people, 12 years or older, with a history of a moderate or severe asthma attack in the last 12 months will be recruited in New Zealand. Each participant will be given a smart watch (to assess physiological measures such as heart and respiratory rate), peak flow meter, smart inhaler (to assess adherence and inhalation) and a cough monitoring application to use regularly over 6 months with fortnightly questionnaires on asthma control and well-being. Data on sociodemographics, asthma control, lung function, dietary intake, medical history and technology acceptance will be collected at baseline and at 6 months. Asthma attacks will be measured by self-report and confirmed with clinical records. The collected data, along with environmental data on weather and air quality, will be analysed using machine learning to develop a risk prediction model for asthma attacks. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the New Zealand Health and Disability Ethics Committee (2023 FULL 13541). Enrolment began in August 2023. Results will be presented at local, national and international meetings, including dissemination via community groups, and submission for publication to peer-reviewed journals. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry ACTRN12623000764639; Australian New Zealand Clinical Trials Registry.
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Inteligencia Artificial , Asma , Adolescente , Adulto , Niño , Femenino , Humanos , Masculino , Nebulizadores y Vaporizadores , Nueva Zelanda , Estudios Observacionales como Asunto , Estudios ProspectivosRESUMEN
Background: Exacerbations of COPD (ECOPD) have a major impact on patients and healthcare systems across the world. Precise estimates of the global burden of ECOPD on mortality and hospital readmission are needed to inform policy makers and aid preventive strategies to mitigate this burden. The aims of the present study were to explore global in-hospital mortality, post-discharge mortality and hospital readmission rates after ECOPD-related hospitalisation using an individual patient data meta-analysis (IPDMA) design. Methods: A systematic review was performed identifying studies that reported in-hospital mortality, post-discharge mortality and hospital readmission rates following ECOPD-related hospitalisation. Data analyses were conducted using a one-stage random-effects meta-analysis model. This study was conducted and reported in accordance with the PRISMA-IPD statement. Results: Data of 65 945 individual patients with COPD were analysed. The pooled in-hospital mortality rate was 6.2%, pooled 30-, 90- and 365-day post-discharge mortality rates were 1.8%, 5.5% and 10.9%, respectively, and pooled 30-, 90- and 365-day hospital readmission rates were 7.1%, 12.6% and 32.1%, respectively, with noticeable variability between studies and countries. Strongest predictors of mortality and hospital readmission included noninvasive mechanical ventilation and a history of two or more ECOPD-related hospitalisations <12â months prior to the index event. Conclusions: This IPDMA stresses the poor outcomes and high heterogeneity of ECOPD-related hospitalisation across the world. Whilst global standardisation of the management and follow-up of ECOPD-related hospitalisation should be at the heart of future implementation research, policy makers should focus on reimbursing evidence-based therapies that decrease (recurrent) ECOPD.