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      Implications for post critical illness trial design: sub-phenotyping trajectories of functional recovery among sepsis survivors

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          Abstract

          Background

          Patients who survive critical illness suffer from a significant physical disability. The impact of rehabilitation strategies on health-related quality of life is inconsistent, with population heterogeneity cited as one potential confounder. This secondary analysis aimed to (1) examine trajectories of functional recovery in critically ill patients to delineate sub-phenotypes and (2) to assess differences between these cohorts in both clinical characteristics and clinimetric properties of physical function assessment tools.

          Methods

          Two hundred ninety-one adult sepsis survivors were followed-up for 24 months by telephone interviews. Physical function was assessed using the Physical Component Score (PCS) of the Short Form-36 Questionnaire (SF-36) and Activities of Daily Living and the Extra Short Musculoskeletal Function Assessment (XSFMA-F/B). Longitudinal trajectories were clustered by factor analysis. Logistical regression analyses were applied to patient characteristics potentially determining cluster allocation. Responsiveness, floor and ceiling effects and concurrent validity were assessed within clusters.

          Results

          One hundred fifty-nine patients completed 24 months of follow-up, presenting overall low PCS scores. Two distinct sub-cohorts were identified, exhibiting complete recovery or persistent impairment. A third sub-cohort could not be classified into either trajectory. Age, education level and number of co-morbidities were independent determinants of poor recovery (AUROC 0.743 ((95%CI 0.659–0.826), p < 0.001). Those with complete recovery trajectories demonstrated high levels of ceiling effects in physical function (PF) (15%), role physical (RP) (45%) and body pain (BP) (57%) domains of the SF-36. Those with persistent impairment demonstrated high levels of floor effects in the same domains: PF (21%), RP (71%) and BP (12%). The PF domain demonstrated high responsiveness between ICU discharge and at 6 months and was predictive of a persistent impairment trajectory (AUROC 0.859 (95%CI 0.804–0.914), p < 0.001).

          Conclusions

          Within sepsis survivors, two distinct recovery trajectories of physical recovery were demonstrated. Older patients with more co-morbidities and lower educational achievements were more likely to have a persistent physical impairment trajectory.

          In regard to trajectory prediction, the PF score of the SF-36 was more responsive than the PCS and could be considered for primary outcomes. Future trials should consider adaptive trial designs that can deal with non-responders or sub-cohort specific outcome measures more effectively.

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          Most cited references34

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          Pulmonary rehabilitation for chronic obstructive pulmonary disease.

          Widespread application of pulmonary rehabilitation (also known as respiratory rehabilitation) in chronic obstructive pulmonary disease (COPD) should be preceded by demonstrable improvements in function (health-related quality of life, functional and maximal exercise capacity) attributable to the programmes. This review updates the review reported in 2006.
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            Methods for assessing responsiveness: a critical review and recommendations.

            A review of the literature suggests there are two major aspects of responsiveness. We define the first as "internal responsiveness," which characterizes the ability of a measure to change over a prespecified time frame, and the second as "external responsiveness, " which reflects the extent to which change in a measure relates to corresponding change in a reference measure of clinical or health status. The properties and interpretation of commonly used internal and external responsiveness statistics are examined. It is from the interpretation point of view that external responsiveness statistics are considered particularly attractive. The usefulness of regression models for assessing external responsiveness is also highlighted.
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              Adaptive designs in clinical trials: why use them, and how to run and report them

              Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial’s course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented. We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.
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                Author and article information

                Contributors
                z.puthucheary@qmul.ac.uk
                Journal
                Crit Care
                Critical Care
                BioMed Central (London )
                1364-8535
                1466-609X
                25 September 2020
                25 September 2020
                2020
                : 24
                : 577
                Affiliations
                [1 ]GRID grid.4868.2, ISNI 0000 0001 2171 1133, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, , Queen Mary University of London, ; London, UK
                [2 ]GRID grid.416041.6, ISNI 0000 0001 0738 5466, Critical Care and Perioperative Medicine Research Group, Adult Critical Care Unit, , Royal London Hospital, ; London, E1 1BB UK
                [3 ]GRID grid.275559.9, ISNI 0000 0000 8517 6224, Institute of General Practice and Family Medicine, , Jena University Hospital, ; Jena, Germany
                [4 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, Institute of Family Medicine, , University Hospital of the Ludwig Maximilian University, ; Munich, Germany
                [5 ]GRID grid.275559.9, ISNI 0000 0000 8517 6224, Center of Sepsis Care and Control, , Jena University Hospital, ; Jena, Germany
                [6 ]GRID grid.451388.3, ISNI 0000 0004 1795 1830, The Francis Crick Institute, ; London, UK
                [7 ]GRID grid.1008.9, ISNI 0000 0001 2179 088X, Physiotherapy Department, , The University of Melbourne, ; Melbourne, Australia
                [8 ]GRID grid.1055.1, ISNI 0000000403978434, Allied Health Department, , Peter MacCallum Cancer Centre, ; Melbourne, Australia
                [9 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Institute of General Practice and Family Medicine, , Charité University Medicine Berlin, ; Berlin, Germany
                [10 ]GRID grid.6363.0, ISNI 0000 0001 2218 4662, Institute of Biometry and Clinical Epidemiology, , Charité University Medicine Berlin, ; Berlin, Germany
                [11 ]Department of Anesthesiology and Operative Intensive Care Medicine, Charité University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
                Author information
                http://orcid.org/0000-0001-5879-0664
                Article
                3275
                10.1186/s13054-020-03275-w
                7517819
                31898531
                211f8360-94f8-42a7-a14c-478ac67c6e30
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 14 May 2020
                : 4 September 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100010571, Bundesministerium für Bildung, Wissenschaft, Forschung und Technologie;
                Award ID: grant 01 E0 1002
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Emergency medicine & Trauma
                sepsis,post intensive care syndrome (pics),physical function,health-related quality of life (hrqol),patient-reported outcome measures (proms),co-morbidity

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