Artificial intelligence for mechanical ventilation: systematic review of design, reporting standards, and bias.

BACKGROUND: Artificial intelligence (AI) has the potential to personalise mechanical ventilation strategies for patients with respiratory failure. However, current methodological deficiencies could limit clinical impact. We identified common limitations and propose potential solutions to facilitate translation of AI to mechanical ventilation of patients. METHODS: A systematic review was conducted in MEDLINE, Embase, and PubMed Central to February 2021. Studies investigating the application of AI to patients undergoing mechanical ventilation were included. Algorithm design and adherence to reporting standards were assessed with a rubric combining published guidelines, satisfying the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis [TRIPOD] statement. Risk of bias was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST), and correspondence with authors to assess data and code availability. RESULTS: Our search identified 1,342 studies, of which 95 were included: 84 had single-centre, retrospective study design, with only one randomised controlled trial. Access to data sets and code was severely limited (unavailable in 85% and 87% of studies, respectively). On request, data and code were made available from 12 and 10 authors, respectively, from a list of 54 studies published in the last 5 yr. Ethnicity was frequently under-reported 18/95 (19%), as was model calibration 17/95 (18%). The risk of bias was high in 89% (85/95) of the studies, especially because of analysis bias. CONCLUSIONS: Development of algorithms should involve prospective and external validation, with greater code and data availability to improve confidence in and translation of this promising approach. TRIAL REGISTRATION NUMBER: PROSPERO - CRD42021225918.

A Core Outcome Set for Pediatric Critical Care.

OBJECTIVES: More children are surviving critical illness but are at risk of residual or new health conditions. An evidence-informed and stakeholder-recommended core outcome set is lacking for pediatric critical care outcomes. Our objective was to create a multinational, multistakeholder-recommended pediatric critical care core outcome set for inclusion in clinical and research programs. DESIGN: A two-round modified Delphi electronic survey was conducted with 333 invited research, clinical, and family/advocate stakeholders. Stakeholders completing the first round were invited to participate in the second. Outcomes scoring greater than 69% "critical" and less than 15% "not important" advanced to round 2 with write-in outcomes considered. The Steering Committee held a virtual consensus conference to determine the final components. SETTING: Multinational survey. PATIENTS: Stakeholder participants from six continents representing clinicians, researchers, and family/advocates. MEASUREMENTS AND MAIN RESULTS: Overall response rates were 75% and 82% for each round. Participants voted on seven Global Domains and 45 Specific Outcomes in round 1, and six Global Domains and 30 Specific Outcomes in round 2. Using overall (three stakeholder groups combined) results, consensus was defined as outcomes scoring greater than 90% "critical" and less than 15% "not important" and were included in the final PICU core outcome set: four Global Domains (Cognitive, Emotional, Physical, and Overall Health) and four Specific Outcomes (Child Health-Related Quality of Life, Pain, Survival, and Communication). Families (n = 21) suggested additional critically important outcomes that did not meet consensus, which were included in the PICU core outcome set-extended. CONCLUSIONS: The PICU core outcome set and PICU core outcome set-extended are multistakeholder-recommended resources for clinical and research programs that seek to improve outcomes for children with critical illness and their families.

Linking of global intensive care (LOGIC): An international benchmarking in critical care initiative.

Benchmarking is a common and effective method for measuring and analyzing ICU performance. With the existence of national registries, objective information can now be obtained to allow benchmarking of ICU care within and between countries. The present manuscript briefly describes the current status of benchmarking in healthcare and critical care and presents the LOGIC project, an initiative to promote international benchmarking for intensive care units. Currently 13 registries have joined LOGIC. We showed large differences in the utilization of ICU as well as resources and in outcomes. Despite the need for careful interpretation of differences due to variation in definitions and limited risk adjustment, LOGIC is a growing worldwide initiative that allows access to insightful epidemiologic data from ICUs in multiple databases and registries.