scholarly journals How Should Adult Handgrip Strength Be Normalized? Allometry Reveals New Insights and Associated Reference Curves

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Alan M Nevill ◽  
Grant R. Tomkinson ◽  
Justin J. Lang ◽  
Wyatt Wutz ◽  
Tony D. Myers
2020 ◽  
Vol 21 (1) ◽  
pp. 49
Author(s):  
Augusto Baumhardt Guidoti ◽  
Ângelo Pereira Cattani ◽  
Cintia Laura De Araujo ◽  
Fernanda Beatriz Costa Delacoste ◽  
Guilherme Scotta Hentschke ◽  
...  

The Glittre ADL-test (TGlittre) has been designed and validated to measure functional capacity during daily living activities in patients with chronic obstructive pulmonary disease (COPD) but is now used in several other situations. The aim of this study was to evaluate the applicability of TGlittre in a sample of overweight and obese eutrophic elderly. This was an experimental and cross-sectional study, which included 21 elderly women, allocated by BMI, in eutrophic (n = 8), overweight (n = 6) and obese (n = 7) groups. They were assessed for functional capacity (TGlittre and 6MWT), quality of life (QOL) with the questionnaire World Health Organization Quality of Life for Older People (WHOQOL-OLD) and handgrip strength (HGS). TGlittre correlated with age (p = 0.0040) and with 6MWT (p = 0.0086), but no statistical difference was found in TGlittre's performance time and the distance covered in 6MWT between groups. TGlittre did not correlate with HGS (p = 0.1493) and WHOQOL-Old (p = 0.0905). The data obtained in the present study corroborate that TGlittre is used as a functional measurement variable in the elderly population.Keywords: aged, obesity, exercise intolerance.­­­


2013 ◽  
Author(s):  
Christine Wohlfahrt-Veje ◽  
Jeanette Tinggaard ◽  
Annette Mouritsen ◽  
Casper Hagen ◽  
Mikkel Grunnet ◽  
...  
Keyword(s):  
Body Fat ◽  
X Ray ◽  

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Haruka Ito ◽  
Shohei Yamamoto ◽  
Manae Harada ◽  
Takaaki Watanabe ◽  
Yuta Suzuki ◽  
...  

Abstract Background and Aims In patients who undergo hemodialysis (HD), malnutrition is a frequent complication associated with higher risk of death, extended hospital stay, physical limitation, and decline of activities of daily living (ADL). Therefore, proper assessment for malnutrition in this population is important for effective disease management. The Global Leadership Initiative on Malnutrition (GLIM) released new criteria for diagnosing and grading malnutrition. Nevertheless, only very few studies have investigated malnutrition prevalence on the basis of the GLIM criteria in hemodialysis patients. Hence, the usefulness of the GLIM criteria’s application in hemodialysis patients remains unclear. The aims of this study were (1) to examine whether malnutrition diagnosed on the basis of the GLIM criteria will produce equivalent results with that diagnosed with the use of existing nutritional indicators and (2) to evaluate the association between the GLIM criteria and decline of physical function and ADL in Japanese patients on HD. Method This cross-sectional study included a total of 185 outpatients who undergo HD three times a week. We measured the existing nutritional indicators (GNRI, MNA-SF, phase angle, mid-arm muscle circumference, and calf circumference), physical function (Fried Scale, handgrip strength, usual gait speed, Short Physical Performance Battery, and physical activity), and ADL status (cumulative score of Barthel Index and instrumental ADL). On the basis of the GLIM criteria, the patients were classified into two groups (no malnutrition and malnutrition). In addition, in case of nutritional risk, nutritional assessment was performed by evaluation of the phenotypic (unintentional weight loss, low BMI, and/or reduced muscle mass) and etiologic (reduced intake or assimilation and/or inflammatory response) factors. Malnutrition was diagnosed if a patient has one or more of these items. The analysis of covariance (ANCOVA) was performed to examine the association between the GLIM criteria and existing nutritional indicators, physical function, and ADL status. Results Malnutrition was diagnosed in 41.1% of the participants based on the GLIM criteria. In contrast, on the basis of the existing nutritional indicators (GNRI, MNA-SF, phase angle, mid-arm muscle circumference, and calf circumference), malnutrition was diagnosed in 22.2%, 58.3%, 48.6%, 57.9%, and 54.6%, respectively. The ANCOVA results, adjusted for the patient’s characteristics, revealed that the malnutrition group had significantly lower score than the non-malnutrition group in the existing nutritional indicators (all P < 0.001) (Figure). Furthermore, the malnutrition group had significantly higher Fried Scale scores, lower handgrip strength results, and lower ADL status than the non-malnutrition group, even after potential confounder adjustment (all P < 0.05). Conclusion The GLIM criteria could be one of the useful tools for screening the risk of malnutrition, frailty, lower handgrip strength, and lower ADL status in patients who undergo HD.


2020 ◽  
Vol 75 (11) ◽  
pp. 2286
Author(s):  
Jose Patricio Lopez ◽  
Patricio Lopez-Jaramillo ◽  
Paul A. Camacho ◽  
Darryl Leong ◽  
Sumathy Rangarajan ◽  
...  

Author(s):  
Philémon Marcel-Millet ◽  
Philippe Gimenez ◽  
Alain Groslambert ◽  
Gilles Ravier ◽  
Sidney Grospretre

2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
P Oleinik ◽  
AN Sumin ◽  
AV Bezdenezhnykh

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): Federal State Budgetary Scientific Institution Research Institute for Complex Issues of Cardiovascular Diseases Introduction The purpose was to evaluate the effectiveness of NMES in patients with complications after cardiac surgery. Methods This study was 37 patients who had significant postoperative complications after cardiovascular surgery. Participants were randomly - NMES group, n = 18; control, n = 19. It was not possible to blind the investigator. Analyzed basic clinical data. The dynamometry of the muscles upper and lower extremities was carried out, as well as a 6-minute walk test (6MWT). Also, the thickness of the quadriceps was measured using ultrasound.The patients underwent NMES on the quadriceps femoris muscle, daily from the third postoperative day, until discharge. The duration session was 90 minutes. Outcomes No differences were found in the baseline characteristics of the groups, including the results of laboratory and instrumental studies. Groups were comparable in the surgery and perioperative parameteres. The initial strength indicators also had no significant differences in the groups. At discharge knee extensors strength (KES) was significantly higher in the NMES group. The knee flexor strength (KFS) and handgrip strength (HF) increased the same in both groups. The quadriceps crosssectional area (CSA) muscle increased more in the NEMS group than in the control to the time of discharge. Average KES increased to a greater extent in the NMES group. At the same time, average and maximum KFS increased equally in both groups. A 6MWT before discharge did not show a difference between groups (P=.166). The NMES course did not affect the duration of hospitalisation (P=.429). Discussion This pilot study show beneficial effects of NMES on muscle strength in patients with complications after cardiovascular surgery. Physical tests initially and in dynamics NEMS Group (n = 18) Control group (n = 19) Baseline Discharge Baseline Discharge P-level Right knee extensors strength (kg) 20,3 [17,9; 26,1] 28,05 [23,8; 36,2] * 20,1 [18,6; 25,4] 22,3 [20,1; 27,1] * 0,004 Left knee extensors strength (kg) 17,75 [15,5; 27,0] 27,45 [22,3; 33,1] * 20,8 [17,5; 24,2] 22,5 [20,1; 25,9] * 0,017 Right knee flexors strength (kg) 14,85 [11,7; 19,5] 17,5 [14,1; 23,4] * 16,9 [13,1; 23,8] 19,2 [12,5; 26,4] * 0,971 Left knee flexors strength (kg) 14,7 [12,6; 19,6] 19,75 [15,9; 24,2] * 16,2, [10,4; 25,1] 18,8 [13,1; 27,7] * 0,889 6-MWT (m) 148,5 [108,5; 174,0] 288,0 [242,0; 319,0] * 169,0 [115,0; 217,0] 315,0 [277,0; 400,0] * 0,166 Right handgrip strength (kg) 24,5 [15,0; 33,0] 25,5 [19,0; 36,0] * 27,0 [18,0; 32,0] 30,0 [20,0; 35,0] * 0,795 Left handgrip strength (kg) 17,0 [12,0; 27,0] 21,0 [15,0; 31,0] * 19,0 [14,0; 29,0] 23,0 [16,0; 30,0] * 0,541 * - p-level from baseline data < 0,05 ** - p-level from baseline data ≥ 0,05


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