Correlations of HOMA2-IR and HbA1c with Algorithms Derived from Bioimpedance and Spectrophotometric Devices

Adami, Chaim Elinton; Gobato, Renata Cristina; Gestic, Martinho Antônio; Cazzo, Everton; Pimentel, Murilo Utrini; Ramos, Marcelo de Carvalho

doi:10.1007/s11695-012-0683-3

Cited by 4 publications

(2 citation statements)

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“…The sample size was calculated based on a study related to the EIS system. 6 , 8 , 10 Stata Software, Version 12.0 was used to calculate sample size, and one-sample comparison of proportions to hypothesized values in which the sensitivity of EIS was determined to be 90%. Therefore, based on the two-sided test, 5% α error and 90% power with 30% estimated prevalence of disease, 6 , 11 , 12 the number of patients needed for the study was calculated to be 117.…”

Section: Methodsmentioning

confidence: 99%

“…Electrical stimulation does act as a predictive tool for early signs of autonomic nervous system dysfunction among people with diabetes by measuring their sweat response and constitutes a modality that can be used in any physical therapy practice providing an inexpensive method to assess endothelial impairment. In addition, the study of Adami et al 8 showed that the homeostasis model assessment of insulin resistance (HOMA2-IR), HbA1c and plasma glucose level highly correlated to the algorithms derived from bio-impedance and spectrophotometric devices. However, no studies have reported the association between electro interstitial scan measured by this device and metabolic syndrome.…”

Section: Introductionmentioning

confidence: 99%

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<p>Screening Test on Metabolic Syndrome Using Electro Interstitial Scan Instrument</p>

Tharavanij

Suwannahitatorn

et al. 2020

MDER

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Background: Metabolic syndrome is diagnosed using clinical and laboratory data. Electro interstitial scan (EIS) is a rapid and noninvasive screening. It measures and calculates the parameters to reflect hypertension, sympathetic activity, stiffness of the arteries, body fat composition, leptin and insulin resistance. Metabolic syndrome will be diagnosed if calculated score ≥10 CU. Purpose: To evaluate the accuracy, validity and appropriate cutoff score to diagnose metabolic syndrome. Materials and Methods: A cross-sectional study was conducted using the populationbased approach. Metabolic syndrome was diagnosed according to the modified National Cholesterol Education Program (NCEP ATP III) and International Diabetes Federation (IDF) criteria. The appropriate cutoff score to diagnose metabolic syndrome by instrument was determined. Results: A total of 253 participants were enrolled with mean age of 40.06±6.33 years, and 64.43% (163/253) were female. Metabolic syndrome was diagnosed among 123 (48.62%) and 104 (41.11%) patients according to the NCEP ATP III and IDF criteria, respectively. The diagnostic indices of metabolic syndrome score ≥10 CU had a sensitivity of 23.6% and 27.9%, a specificity of 100% and area under ROC of 0.62 and 0.64, according to the NCEP ATP III and IDF criteria, respectively. The best cutoff level of metabolic syndrome score was ≥9 CU with a sensitivity of 79.67% (95% CI, 71.5-86.4%) and 88.46% (95% CI, 80.7-93.9%), a specificity of 96.92% (95% CI, 92.3-99.2%) and 93.29% (95% CI, 88.0-96.7%) and area under ROC 0.89 (95% CI, 0.85-0.93) and 0.92 (95% CI, 0.88-0.95), respectively, according to the NCEP ATP III and IDF criteria. Conclusion: Screening of metabolic syndrome using ES TECK in a Thai population demonstrated inadequate accuracy when using metabolic syndrome score ≥10 CU. We recommend using a metabolic syndrome score ≥9 CU to provide the best accuracy. This instrument is safe, fast and easy to use for metabolic syndrome screening.

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