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Abstract Background Mycobacterium avium complex lung disease (MAC-LD) is an infection that is increasing in frequency, associated with substantial disease burden, and often refractory to treatment. Amikacin liposome inhalation suspension (ALIS) is the first therapy approved for refractory MAC-LD. In the CONVERT study of adult patients with refractory MAC-LD, adding ALIS to a multidrug background regimen showed evidence of MAC infection elimination in sputum by month 6, which was maintained in most patients through the end of treatment (≤ 12 months post-conversion). This study assessed changes in healthcare resource utilization (HCRU) among patients initiating ALIS in real-world settings. Methods This retrospective cohort study of the All-Payer Claims Database (October 2018–April 2020) included patients aged ≥ 18 years with ≥ 1 pharmacy claim for ALIS and ≥ 12 months of continuous health plan enrollment pre- and post-ALIS initiation. Respiratory disease-related (and all-cause) HCRU (hospitalizations, length of stay [LOS], emergency department [ED] visits, and outpatient office visits) were compared 12 months pre- and post-ALIS initiation. Outcomes were reported at 6-month intervals; 0–6 months pre-ALIS initiation was the reference period for statistical comparisons. Results A total of 331 patients received ALIS, with HCRU highest in the 6 months pre-ALIS initiation. Compared with 26.9% during the reference period, respiratory-related hospitalizations decreased to 19.3% (P

Rationale Nontuberculous mycobacterial (NTM) diseases are difficult-to-treat infections, especially in lung transplant (LTx) candidates. Currently, there is a paucity of recommendations on the management of NTM infections in LTx, focusing on Mycobacterium avium complex (MAC), M. abscessus and M. kansasii. Methods Pulmonologists, infectious disease specialists, LTx surgeons and Delphi experts with expertise in NTM were recruited. A patient representative was also invited. Three questionnaires comprising questions with multiple response statements were distributed to panellists. Delphi methodology with a Likert scale of 11 points (5 to −5) was applied to define the agreement between experts. Responses from the first two questionnaires were collated to develop a final questionnaire. The consensus was described as a median rating >4 or

Durante los primeros 10 días de guerra, en febrero de 2022, la invasión rusa de Ucrania provocó lo que las Naciones Unidas han descrito como la crisis humanitaria con más rápido crecimiento desde la Segunda Guerra Mundial, y el primer ataque militar contra una planta de energía nuclear activa. Este análisis presenta el primer análisis conocido de ética computacional (AICE), equidad en salud y rentabilidad (CEA) impulsado por la Inteligencia Artificial (IA) para la prevención y respuesta al terrorismo nuclear y al bioterrorismo (en medio de una creciente preocupación mundial por el uso deliberado de armas nucleares tácticas). Aborda el riesgo de operaciones de falsa bandera (encubiertas) para sabotear y, por lo tanto, de usar como arma una central eléctrica ucraniana, y el escenario relacionado con el ataque y ocupación continuos que derivan en el peligro de un accidente en dicha planta, con un resultado similar en ambos escenarios de una explosión nuclear y de un potencial problema de salud en toda Europa, además de una crisis humanitaria y ecológica. Usando datos, metodologías y suposiciones ampliamente aceptadas y disponibles, este análisis computacional demuestra que la prevención de dicho bioterrorismo en promedio produciría ahorros netos de $306.2 billones en general, además de $493.7 billones ahorrados en inequidades explosivas de salud relacionadas de otro modo. Dadas las entradas de estos datos, el análisis ético computacional sugiere la convergencia multicultural sustancial de los diversos sistemas de creencias del mundo (incluidos el budismo, el cristianismo, el confucianismo, el hinduismo, el islam, el judaísmo y el secularismo) sobre el hecho de que la dignidad, los derechos y la justicia requieren la prevención de dicho bioterrorismo y la rápida conclusión de este conflicto, como la respuesta más eficaz y urgente para el sistema de salud y para la salud pública ante esta crisis.

Background and objectives: Little is known about outcome improvements and disparities in cardiac arrest and active cancer. We performed the first known AI and propensity score (PS)-augmented clinical, cost-effectiveness, and computational ethical analysis of cardio-oncology cardiac arrests including left heart catheterization (LHC)-related mortality reduction and related disparities. Materials and methods: A nationally representative cohort analysis was performed for mortality and cost by active cancer using the largest United States all-payer inpatient dataset, the National Inpatient Sample, from 2016 to 2018, using deep learning and machine learning augmented propensity score-adjusted (ML-PS) multivariable regression which informed cost-effectiveness and ethical analyses. The Cardiac Arrest Cardio-Oncology Score (CACOS) was then created for the above population and validated. The results informed the computational ethical analysis to determine ethical and related policy recommendations. Results: Of the 101,521,656 hospitalizations, 6,656,883 (6.56%) suffered cardiac arrest of whom 61,300 (0.92%) had active cancer. Patients with versus without active cancer were significantly less likely to receive an inpatient LHC (7.42% versus 20.79%, p < 0.001). In ML-PS regression in active cancer, post-arrest LHC significantly reduced mortality (OR 0.18, 95%CI 0.14–0.24, p < 0.001) which PS matching confirmed by up to 42.87% (95%CI 35.56–50.18, p < 0.001). The CACOS model included the predictors of no inpatient LHC, PEA initial rhythm, metastatic malignancy, and high-risk malignancy (leukemia, pancreas, liver, biliary, and lung). Cost-benefit analysis indicated 292 racial minorities and $2.16 billion could be saved annually by reducing racial disparities in LHC. Ethical analysis indicated the convergent consensus across diverse belief systems that such disparities should be eliminated to optimize just and equitable outcomes. Conclusions: This AI-guided empirical and ethical analysis provides a novel demonstration of LHC mortality reductions in cardio-oncology cardiac arrest and related disparities, along with an innovative predictive model that can be integrated within the digital ecosystem of modern healthcare systems to improve equitable clinical and public health outcomes.

Abstract Background A substantial increase in pulmonary and extra-pulmonary diseases due to non-tuberculous mycobacteria (NTM) has been documented worldwide, especially among subjects suffering from chronic respiratory diseases and immunocompromised patients. Many questions remain regarding the epidemiology of pulmonary disease due to NTM (NTM-PD) mainly because reporting of NTM-PD to health authorities is not mandated in several countries, including Italy. This manuscript describes the protocol of the first Italian registry of adult patients with respiratory infections caused by NTM (IRENE). Methods IRENE is an observational, multicenter, prospective, cohort study enrolling consecutive adult patients with either a NTM respiratory isolate or those with NTM-PD. A total of 41 centers, including mainly pulmonary and infectious disease departments, joined the registry so far. Adult patients with all of the following are included in the registry: 1) at least one positive culture for any NTM species from any respiratory sample; 2) at least one positive culture for NTM isolated in the year prior the enrolment and/or prescribed NTM treatment in the year prior the enrolment; 3) given consent to inclusion in the study. No exclusion criteria are applied to the study. Patients are managed according to standard operating procedures implemented in each IRENE clinical center. An online case report form has been developed to collect patients’ demographics, comorbidities, microbiological, laboratory, functional, radiological, clinical, treatment and outcome data at baseline and on an annual basis. An IRENE biobank has also been developed within the network and linked to the clinical data of the registry. Conclusions IRENE has been developed to inform the clinical and scientific community on the current management of adult patients with NTM respiratory infections in Italy and acts as a national network to increase the disease’s awareness. Trial registration Clinicaltrial.gov: NCT03339063.

The main objectives of the two symposia were to raise awareness of nontuberculous mycobacterial lung disease (NTM-LD); evaluate the key microbiological and clinical aspects of the disease, including its association with other conditions, such as bronchiectasis and common coinfections; outline the current treatment and management strategies; and review data from clinical trials of new therapies and how these could shape future management strategies. Dr Chalmers, Dr Griffith, and Dr Haworth opened the symposia by introducing NTM-LD and providing a brief overview of the key topics. Dr Ringshausen focussed on the epidemiology, prevalence, and burden of NTM-LD, and briefly discussed pathophysiology. Dr van Ingen outlined the microbiological diagnosis of NTM-LD, in particular the importance of molecular identification and drug susceptibility testing (DST). Dr Aliberti introduced bronchiectasis, outlined the relationship between the two diseases, and discussed the clinical relevance of comorbid disease. Dr Aksamit addressed the assessment and management of co-isolated NTM and other respiratory pathogens. Dr Griffith and Dr Loebinger each summarised the current treatment and management strategies, and reviewed the latest research regarding new therapies and what this could mean for the future. Dr Koh closed the symposium by outlining the latest clinical research on the natural history of NTM-LD from a global perspective.

Bronchiectasis is one of the most neglected diseases in respiratory medicine. There are no approved therapies and few large-scale, representative epidemiological studies. The EMBARC (European Multicentre Bronchiectasis Audit and Research Collaboration) registry is a prospective, pan-European observational study of patients with bronchiectasis. The inclusion criterion is a primary clinical diagnosis of bronchiectasis consisting of: 1) a clinical history consistent with bronchiectasis; and 2) computed tomography demonstrating bronchiectasis. Core exclusion criteria are: 1) bronchiectasis due to known cystic fibrosis; 2) age