Handgrip strength by dynamometry does not identify malnutrition in individual preoperative outpatients q

summary Background & aims: Low handgrip strength by dynamometry is associated with increased postoperativemorbidity, higher mortality and reduced quality of life. The aim of this study was to evaluate the accuracyof four algorithms in diagnosing malnutrition by measuring handgrip strength.Methods: We included 504 consecutive preoperative outpatients. Reference standard for malnutritionwas defined based on percentage involuntary weight loss and BMI. Diagnostic characteristics of thehandgrip strength algorithms (Alvares-da-Silva, Klidjian, Matos, Webb) were expressed by sensitivity,specificity, positive and negative predictive value, false positive and negative rate.Results: The prevalence of malnutrition was 5.8%. Although Klidjian showed the highest sensitivity (79%,95% CI 62%e90%), 6 out of 29 malnourished patients were falsely identified as well-nourished (falsepositive rate 21%, 95% CI 9%e38%). In contrast, this algorithm showed the lowest positive predictive value(8%, 95% CI 5%e13%). Matos presented the highest positive predictive value; the post-test probabilityincreased to 13% (95% CI 8%e20%). The 1-minus negative predictive value ranged between 3% and 5% forall algorithms.Conclusions: None of the algorithms derived from handgrip strength measurements was found to havea diagnostic accuracygood enough to introduce handgrip strength as a systematic institutional screeningtool to detect malnutrition in individual adult preoperative elective outpatients. 2012 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.