Vacuum assisted closure is being increasingly used for wound management. This review examines the history of its development and appraises the current evidence on its use so far.
Performing short bouts of arm ergometry during prolonged sitting attenuated postprandial glycaemia despite maintaining a seated posture. This may have clinical significance for those with weight-bearing difficulty who may struggle with postural change.
OBJECTIVE
To examine whether circulating metabolic responses to low-volume high-intensity interval exercise (LV-HIIE) or continuous moderate-intensity aerobic exercise (CME) differ between white Europeans and South Asians with nondiabetic hyperglycemia (NDH).
RESEARCH DESIGN AND METHODS
Thirteen white Europeans and 10 South Asians (combined median [interquartile range] age 67 [60–68] years, HbA1c 5.9% [5.8–6.1%] [41.0 (39.9–43.2) mmol ⋅ mol−1]) completed three 6-h conditions (sedentary control [CON], LV-HIIE, and CME) in a randomized order. Exercise conditions contained a single bout of LV-HIIE and CME, respectively (each ending at 2 h), with meals provided at 0 and 3 h. Circulating glucose (primary outcome), insulin, insulin resistance index (IRI), triglycerides, and nonesterified fatty acids were measured at 0, 0.5, 1, 2, 3, 3.5, 4, 5, and 6 h. Data were analyzed as postexercise time-averaged area under the curve (AUC) adjusted for age, sex, and preexercise AUC.
RESULTS
Glucose was similar in each condition and with ethnicity, with no condition-by-ethnicity interaction (P ≥ 0.28). However, insulin was lower in LV-HIIE (mean [95% CI] −44.4 [−23.7, −65.1] mU ⋅ L−1) and CME (−33.8 [−13.7, −53.9] mU ⋅ L−1) compared with CON. Insulin responses were greater in South Asians (interaction P = 0.03) such that values were similar in each ethnicity during exercise conditions, despite being 33% higher in South Asians during CON. IRI followed a similar pattern to insulin. Lipids were unaffected by exercise.
CONCLUSIONS
Reductions in insulin and insulin resistance after acute LV-HIIE and CME are greater in South Asians than in white Europeans with NDH. Further trials are required to examine the longer-term impact of LV-HIIE and CME on cardiometabolic health.
the Victorian Government's OIS Program. There are no other conflicts of interest. The results of the present study do not constitute endorsement by the ACSM. The results of the study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation.
Increases in MVPA and body weight were associated with a reduction and increase in HbA1c, respectively, particularly in those with dysglycemia. Quantifying the effect that health behavior changes have on HbA1c can be used to inform prevention programs.
Background: Accurately predicting the risk of diabetic foot ulceration (DFU) could dramatically reduce the enormous burden of chronic wound management and amputation. Yet, the current prognostic models are unable to precisely predict DFU events. Typically, efforts have focused on individual factors like temperature, pressure, or shear rather than the overall foot microclimate. Methods: A systematic review was conducted by searching PubMed reports with no restrictions on start date covering the literature published until February 20, 2019 using relevant keywords, including temperature, pressure, shear, and relative humidity. We review the use of these variables as predictors of DFU, highlighting gaps in our current understanding and suggesting which specific features should be combined to develop a real-time microclimate prognostic model. Results: The current prognostic models rely either solely on contralateral temperature, pressure, or shear measurement; these parameters, however, rarely reach 50% specificity in relation to DFU. There is also considerable variation in methodological investigation, anatomical sensor configuration, and resting time prior to temperature measurements (5-20 minutes). Few studies have considered relative humidity and mean skin resistance. Conclusion: Very limited evidence supports the use of single clinical parameters in predicting the risk of DFU. We suggest that the microclimate as a whole should be considered to predict DFU more effectively and suggest nine specific features which appear to be implicated for further investigation. Technology supports real-time in-shoe data collection and wireless transmission, providing a potentially rich source of data to better predict the risk of DFU.
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