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University Clinic of Medicine, Cantonal Hospital Baselland, Liestal, Switzerland
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, another study found a poor cortisol response after food intake ( 6 , 7 , 8 ). However, these studies were conducted in small populations or outpatient settings. Results from a well-controlled, sufficiently powered trial are lacking. Understanding the
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. Statistical analysis Statistical analysis was performed with IBM SPSS software (version 26.0). G*Power software (version 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany) was used to calculate the power (1 − β) of the study. The type of
Comprehensive Heart Failure Center, University & University Hospital Würzburg, Würzburg, Germany
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Department of Psychiatry, Psychosomatics and Psychotherapy, University Hospital, University of Würzburg, Würzburg, Germany
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Division of Cardiology, Department of Internal Medicine I, University Hospital, University of Würzburg, Würzburg, Germany
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Department of General, Visceral, Transplant, Vascular, and Pediatric Surgery, University Hospital, University of Würzburg, Würzburg, Germany
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Division of Cardiology, Department of Internal Medicine I, University Hospital, University of Würzburg, Würzburg, Germany
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Division of Cardiology, Department of Internal Medicine I, University Hospital, University of Würzburg, Würzburg, Germany
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Comprehensive Heart Failure Center, University & University Hospital Würzburg, Würzburg, Germany
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at the time points indicated in Supplementary Table 2. For the documentation of changes in obesity-related conditions, we applied definitions given in Supplementary Table 3. Sample size calculation, power analysis, and adaptation of the
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Australian Institute for Musculoskeletal Science (AIMSS), Victoria University, Melbourne, Victoria, Australia
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reliant on whole-body fat oxidation during exercise and are more metabolically flexible ( 4 ). It is possible that our study, despite detecting changes in blood lactate levels, was not appropriately powered to detect changes in energy expenditure and whole
Department of Endocrinology, Austin Health, Melbourne, Australia
Division of Endocrinology, Diabetes and Metabolism, Northwell, Great Neck, New York, USA
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Department of Cardiology, Austin Health, Melbourne Australia
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Olivia Newton-John Cancer Research Institute, Austin Health, Melbourne, Australia
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Department of Endocrinology, Austin Health, Melbourne, Australia
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Department of Endocrinology, Austin Health, Melbourne, Australia
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modified during the study period by non-study clinicians. All medication changes were recorded at each visit. Power analysis Our power analysis for our prespecified 12-month end point has previously been reported and published ( 22 ). In Brief
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indexes after correction for differences in age and delivery BMI between the two groups were estimated using covariance analysis. Statistical significance was set as P < 0.05. Statistical analyses were conducted using SPSS 21.0 (IBM). A power
Leicester Diabetes Centre, University of Leicester, Leicester General Hospital, Leicester, UK
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Centre for Physical Activity in Health and Disease, Brunel University London, Uxbridge, UK
Division of Sport, Health and Exercise Sciences, Department of Life Sciences, Brunel University London, Uxbridge, UK
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any allergies to the food and drink being provided in the study. Sample size Sample size estimations were based on previous data ( 18 ). Based on a 10% within-group error variance, a within-person correlation of 0.6, 80% power, and α = 0.05, it
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power of 90% at a 95% CI with the acceptable error of 0.1. This estimation is based on a study reported by Holmes et al . ( 30 ), who showed the mean P-selectin 55.4 ± 17.1 ng/mL vs 40.7 ± 16.9 ng/mL in the cases and controls. Results During
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imputation method was used to impute missing variables in order to maximize statistical power and minimize bias. In addition, to determine whether the generated complete data differed significantly from the original data, a sensitivity analysis was performed
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Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
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Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
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Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
Department of Clinical Pharmacology, Copenhagen University Hospital – Bispebjerg and Frederiksberg, Copenhagen, Denmark
Copenhagen Center for Translational Research, Copenhagen University Hospital – Bispebjerg and Frederiksberg, University of Copenhagen, Copenhagen, Denmark
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Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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; thus, the multiple comparisons combined with the post hoc nature of the analyses limit the power of our statistical comparisons between groups. Furthermore, the correction for multiple testing increases the risk of type 2 errors. Data should be