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Fulltext Next-generation, personalised, model-based critical care medicine: a state-of-the art review of in silico virtual patient models, methods, and cohorts, and how to validation them

Chase JG, Preiser JC, Dickson JL, Pironet A, Chiew YS, Pretty CG, et al.

Biomed Eng Online, 2018 Feb 20;17(1):24.
PMID: 29463246 DOI: 10.1186/s12938-018-0455-y

Critical care, like many healthcare areas, is under a dual assault from significantly increasing demographic and economic pressures. Intensive care unit (ICU) patients are highly variable in response to treatment, and increasingly aging populations mean ICUs are under increasing demand and their cohorts are increasingly ill. Equally, patient expectations are growing, while the economic ability to deliver care to all is declining. Better, more productive care is thus the big challenge. One means to that end is personalised care designed to manage the significant inter- and intra-patient variability that makes the ICU patient difficult. Thus, moving from current "one size fits all" protocolised care to adaptive, model-based "one method fits all" personalised care could deliver the required step change in the quality, and simultaneously the productivity and cost, of care. Computer models of human physiology are a unique tool to personalise care, as they can couple clinical data with mathematical methods to create subject-specific models and virtual patients to design new, personalised and more optimal protocols, as well as to guide care in real-time. They rely on identifying time varying patient-specific parameters in the model that capture inter- and intra-patient variability, the difference between patients and the evolution of patient condition. Properly validated, virtual patients represent the real patients, and can be used in silico to test different protocols or interventions, or in real-time to guide care. Hence, the underlying models and methods create the foundation for next generation care, as well as a tool for safely and rapidly developing personalised treatment protocols over large virtual cohorts using virtual trials. This review examines the models and methods used to create virtual patients. Specifically, it presents the models types and structures used and the data required. It then covers how to validate the resulting virtual patients and trials, and how these virtual trials can help design and optimise clinical trial. Links between these models and higher order, more complex physiome models are also discussed. In each section, it explores the progress reported up to date, especially on core ICU therapies in glycemic, circulatory and mechanical ventilation management, where high cost and frequency of occurrence provide a significant opportunity for model-based methods to have measurable clinical and economic impact. The outcomes are readily generalised to other areas of medical care.
A systematic review and meta-analysis of the clinimetric properties of the core outcome measurement instruments for clinical effectiveness trials of nutritional and metabolic interventions in critical illness (CONCISE)

Davies TW, Kelly E, van Gassel RJJ, van de Poll MCG, Gunst J, Casaer MP, et al.

Crit Care, 2023 Nov 20;27(1):450.
PMID: 37986015 DOI: 10.1186/s13054-023-04729-7

BACKGROUND: CONCISE is an internationally agreed minimum set of outcomes for use in nutritional and metabolic clinical research in critically ill adults. Clinicians and researchers need to be aware of the clinimetric properties of these instruments and understand any limitations to ensure valid and reliable research. This systematic review and meta-analysis were undertaken to evaluate the clinimetric properties of the measurement instruments identified in CONCISE.
METHODS: Four electronic databases were searched from inception to December 2022 (MEDLINE via Ovid, EMBASE via Ovid, CINAHL via Healthcare Databases Advanced Search, CENTRAL via Cochrane). Studies were included if they examined at least one clinimetric property of a CONCISE measurement instrument or recognised variation in adults ≥ 18 years with critical illness or recovering from critical illness in any language. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist for systematic reviews of Patient-Reported Outcome Measures was used. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses were used in line with COSMIN guidance. The COSMIN checklist was used to evaluate the risk of bias and the quality of clinimetric properties. Overall certainty of the evidence was rated using a modified Grading of Recommendations, Assessment, Development and Evaluation approach. Narrative synthesis was performed and where possible, meta-analysis was conducted.
RESULTS: A total of 4316 studies were screened. Forty-seven were included in the review, reporting data for 12308 participants. The Short Form-36 Questionnaire (Physical Component Score and Physical Functioning), sit-to-stand test, 6-m walk test and Barthel Index had the strongest clinimetric properties and certainty of evidence. The Short Physical Performance Battery, Katz Index and handgrip strength had less favourable results. There was limited data for Lawson Instrumental Activities of Daily Living and the Global Leadership Initiative on Malnutrition criteria. The risk of bias ranged from inadequate to very good. The certainty of the evidence ranged from very low to high.
CONCLUSIONS: Variable evidence exists to support the clinimetric properties of the CONCISE measurement instruments. We suggest using this review alongside CONCISE to guide outcome selection for future trials of nutrition and metabolic interventions in critical illness.
TRIAL REGISTRATION: PROSPERO (CRD42023438187). Registered 21/06/2023.
Statistical analysis plan for the replacing protein via enteral nutrition in a stepwise approach in critically ill patients (REPLENISH) randomized clinical trial

Arabi YM, Al-Dorzi HM, Aldibaasi O, Sadat M, Jose J, Muharib D, et al.

Trials, 2024 May 02;25(1):296.
PMID: 38698442 DOI: 10.1186/s13063-024-08105-w

BACKGROUND: The optimal amount and timing of protein intake in critically ill patients are unknown. REPLENISH (Replacing Protein via Enteral Nutrition in a Stepwise Approach in Critically Ill Patients) trial evaluates whether supplemental enteral protein added to standard enteral nutrition to achieve a high amount of enteral protein given from ICU day five until ICU discharge or ICU day 90 as compared to no supplemental enteral protein to achieve a moderate amount of enteral protein would reduce all-cause 90-day mortality in adult critically ill mechanically ventilated patients.
METHODS: In this multicenter randomized trial, critically ill patients will be randomized to receive supplemental enteral protein (1.2 g/kg/day) added to standard enteral nutrition to achieve a high amount of enteral protein (range of 2-2.4 g/kg/day) or no supplemental enteral protein to achieve a moderate amount of enteral protein (0.8-1.2 g/kg/day). The primary outcome is 90-day all-cause mortality; other outcomes include functional and health-related quality-of-life assessments at 90 days. The study sample size of 2502 patients will have 80% power to detect a 5% absolute risk reduction in 90-day mortality from 30 to 25%. Consistent with international guidelines, this statistical analysis plan specifies the methods for evaluating primary and secondary outcomes and subgroups. Applying this statistical analysis plan to the REPLENISH trial will facilitate unbiased analyses of clinical data.
CONCLUSION: Ethics approval was obtained from the institutional review board, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia (RC19/414/R). Approvals were also obtained from the institutional review boards of each participating institution. Our findings will be disseminated in an international peer-reviewed journal and presented at relevant conferences and meetings.
TRIAL REGISTRATION: ClinicalTrials.gov, NCT04475666 . Registered on July 17, 2020.

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