2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Physical activity and cardiometabolic risk factors in individuals with spinal cord injury: a systematic review and meta-analysis

      review-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Physical inactivity in individuals with spinal cord injury (SCI) has been suggested to be an important determinant of increased cardiometabolic disease (CMD) risk. However, it remains unclear whether physically active SCI individuals as compared to inactive or less active individuals have truly better cardiometabolic risk profile. We aimed to systematically review and quantify the association between engagement in regular physical activity and/or exercise interventions and CMD risk factors in individuals with SCI. Four medical databases were searched and studies were included if they were clinical trials or observational studies conducted in adult individuals with SCI and provided information of interest. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was applied to rate the certainty of evidence. Of 5816 unique citations, 11 randomized clinical trials, 3 non-randomized trial and 32 cross-sectional studies comprising more than 5500 SCI individuals were included in the systematic review. In meta-analysis of RCTs and based on evidence of moderate certainty, physical activity in comparison to control intervention was associated with: (i) better glucose homeostasis profile [WMD of glucose, insulin and Assessment of Insulin Resistance (HOMA-IR) were − 3.26 mg/dl (95% CI − 5.12 to − 1.39), − 3.19 μU/ml (95% CI − 3.96 to − 2.43)] and − 0.47 (95% CI − 0.60 to − 0.35), respectively], and (ii) improved cardiorespiratory fitness [WMD of relative and absolute oxygen uptake relative (VO 2) were 4.53 ml/kg/min (95% CI 3.11, 5.96) and 0.26 L/min (95% CI 0.21, 0.32) respectively]. No differences were observed in blood pressure, heart rate and lipids (based on evidence of low/moderate certainty). In meta-analysis of cross-sectional studies and based on the evidence of very low to low certainty, glucose [WMD − 3.25 mg/dl (95% CI − 5.36, − 1.14)], insulin [− 2.12 μU/ml (95% CI − 4.21 to − 0.03)] and total cholesterol [WMD − 6.72 mg/dl (95% CI − 13.09, − 0.34)] were lower and HDL [WMD 3.86 mg/dl (95% CI 0.66, 7.05)] and catalase [0.07 UgHb-1 (95% CI 0.03, 0.11)] were higher in physically active SCI individuals in comparison to reference groups. Based on limited number of cross-sectional studies, better parameters of systolic and diastolic cardiac function and lower carotid intima media thickness were found in physically active groups. Methodologically sound clinical trials and prospective observational studies are required to further elaborate the impact of different physical activity prescriptions alone or in combination with other life-style interventions on CMD risk factors in SCI individuals.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s10654-022-00859-4.

          Related collections

          Most cited references64

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions

          Non-randomised studies of the effects of interventions are critical to many areas of healthcare evaluation, but their results may be biased. It is therefore important to understand and appraise their strengths and weaknesses. We developed ROBINS-I (“Risk Of Bias In Non-randomised Studies - of Interventions”), a new tool for evaluating risk of bias in estimates of the comparative effectiveness (harm or benefit) of interventions from studies that did not use randomisation to allocate units (individuals or clusters of individuals) to comparison groups. The tool will be particularly useful to those undertaking systematic reviews that include non-randomised studies.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Meta-analysis in clinical trials

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Estimating the mean and variance from the median, range, and the size of a sample

              Background Usually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial. Methods In this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data. Results We found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n ≤ 15). For moderately sized samples (15 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy. Conclusion Using these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.
                Bookmark

                Author and article information

                Contributors
                marija.glisic@paraplegie.ch
                Journal
                Eur J Epidemiol
                Eur J Epidemiol
                European Journal of Epidemiology
                Springer Netherlands (Dordrecht )
                0393-2990
                1573-7284
                7 April 2022
                7 April 2022
                2022
                : 37
                : 4
                : 335-365
                Affiliations
                [1 ]GRID grid.419770.c, Swiss Paraplegic Research, ; Guido A. Zäch Str. 1, 6207 Nottwil, Switzerland
                [2 ]GRID grid.5734.5, ISNI 0000 0001 0726 5157, Graduate School for Health Sciences, , University of Bern, ; Mittelstrasse 43, 3012 Bern, Switzerland
                [3 ]GRID grid.419769.4, ISNI 0000 0004 0627 6016, Sports Medicine, , Swiss Paraplegic Centre Nottwil, ; 6207 Nottwil, Switzerland
                [4 ]GRID grid.5734.5, ISNI 0000 0001 0726 5157, Institute of Social and Preventive Medicine (ISPM), , University of Bern, ; Mittelstrasse 43, 3012 Bern, Switzerland
                [5 ]GRID grid.5734.5, ISNI 0000 0001 0726 5157, Public Health and Primary Care Library, University Library of Bern, , University of Bern, ; Bern, Switzerland
                Author information
                http://orcid.org/0000-0002-0108-2576
                Article
                859
                10.1007/s10654-022-00859-4
                9187578
                35391647
                58a6e000-1ede-4a13-9f6b-9175f97edd8d
                © The Author(s) 2022

                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/.

                History
                : 16 January 2021
                : 7 March 2022
                Funding
                Funded by: University of Bern
                Categories
                Review
                Custom metadata
                © Springer Nature B.V. 2022

                Public health
                spinal cord injury,physical activity,exercise,cardiovascular diseases,cardiac function

                Comments

                Comment on this article