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Tiroid hastalıkları, dünyadaki en yaygın endokrin bozukluklardır. Hiper ve hipotiroidizmin subklinik formları oldukça yaygındır. Dünya Sağlık Örgütüne göre subklinik hipotiroidizm (SKH), referans aralığının üstünde tiroid stimülan hormon (TSH) varlığında, serbest serum tiroksin (sT4) ve triiyodoti-

Hyperuricemia is common in psoriatic arthritis (PsA). The aim of this study is to investigate the effect of PsA and metabolic syndrome (MS) components on serum uric acid (SUA). Material and Methods: A total of 102 adult individuals (53 females and 49 males) participated in this study. Fifty-one consecutive PsA patients followed and treated in the outpatient clinic between April 2011 and 2012 were enrolled in this study retrospectively. The control group consisted of 51 patients who have arthralgia but not arthritis. Insulin resistance was calculated according to the homeostasis model of assessment insulin resistance (HOMA-IR) formula. Patients were classified as having MS according to the National Cholesterol Education Program/Adult Treatment Panel definition. Results: SUA levels were higher in MS (p=0.016), but when adjusted for age, this difference was not found to be statistically significant. It was found that hypertension (HT), triglyceride (TG) and HOMA-IR which are important components of MS had an effect on SUA level but the effect of PsA on SUA was not found. SUA level was higher in patients with HT, TG and HOMA-IR elevation than those without (respectively, p=0.009, p=0.005, p=0.001). It was observed that PsA had no effect on SUA, but when adjusted for age, the UA level in PsA was found to be significantly higher (p=0.027). Conclusion: MS, which is a major risk factor for atherosclerosis, is increased in PsA. However, this increase may also be associated with higher age in PsA patients. It is known that there is a relationship between cardiovascular events and high SUA levels. SUA is known to play a potential role as a risk factor for atherosclerosis and related diseases. More studies are needed to investigate the effects of PsA and MS components on SUA levels.

Objective: The aim of our study is to compile the muscle mass index and cut-off levels of the height squared-, weight-, and body mass index-adjusted models, used in the literature for the diagnosis of sarcopenia. The study also aims to create a new appendicular skeletal muscle mass estimation equation for non-segmental bio-impedance analyzer and to determine the relationship between all these muscle mass indices and muscle strength. Methods: Body composition was assessed with bio-impedance analyzer, and muscle strength was assessed by hand grip strength with hand dynamometer. Absolute muscle mass, fat free mass, skeletal muscle mass, and appendicular skeletal muscle mass levels measured by bio-impedance-analyzer were calculated with the estimation equations defined in the literature; separately, height-, weight-, and body mass-indexed models were created. The averages of these indices, 2 standard deviation low, as well as correlation analysis with hand grip strength were performed. Multiple linear regression analyses were performed to construct the appendicular skeletal muscle mass estimation equation. Results: A total of 200 young healthy individuals aged 18-40 years (50% male) were included in the study. The cut-off thresholds were 28/16 for hand grip strength; 20.1/13.3 kg for appendicular skeletal muscle mass; 7.0/5.4 kg/m2 for appendicular skeletal muscle mass/height squared; 29.7/22.8% for appendicular skeletal muscle mass/weight; 0.81/0.56 for appendicular skeletal muscle mass/body mass index based on 2 standard deviation lower in men and women, respectively. The linear regression analysis, which has a high correlation with hand grip strength (r: 0.719; P < .001), the appendicular skeletal muscle mass estimation, quite strong (adjusted R2: 0.959), was presented as a new equation: ASMM = 3.567 + (0.119 × h2/Z) + (4.323 × gender) + (0.164 × weight). The height squared in cm2; for gender men = 1 and women = 0; weight in kg; Z is bio-impedance-analyzer impedance in 50 Ω frequency. Conclusion: This study showed us that body mass index-adjusted models were more strongly correlated with muscle strength than both height- and weight-indexed models, which differ from those commonly used in the literature.