Identifying and managing patient–ventilator asynchrony: An international survey.

Objective: To describe the main factors associated with proper recognition and management of patient ventilator asynchronies (PVA). Design: Analytical cross-sectional study. Setting: International study conducted in 20 countries through an online survey. Participants: Physicians, respiratory therapists, nurses and physiotherapists that are currently working at the Intensive Care Unit (ICU). Main variables of interest: Univariate and multivariate logistic regression models were used to establish associations between all variables (profession, training in mechanical ventilation, type of training program, years of experience and ICU characteristics) with the ability of HCPs to correctly identify and manage 6 PVA. Results: A total of 431 HCPs answered a validated survey. The main factors associated with the proper recognition of PVA were: specific training program in mechanical ventilation (MV) (OR 2.27; 95% CI 1.14-4.52; p = 0.019), courses with more than 100 hours completed (OR 2.28; 95% CI 1.29-4.03; p = 0.005) and the number of intensive care unit (ICU) beds (OR 1.037; 95% CI 1.01-1.06; p = 0.005). The main factor that influenced PVA management was recognizing 6 PVA correctly (OR 118.98; 95%CI 35.25-401.58; p < 0.001). Conclusion: Identifying and managing PVA using ventilator waveform analysis is influenced by many factors including specific training programs in MV, number of ICU beds and the recognized number of PVA.pre-print169 K

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals