Abstract Introduction Takayasu’s arteritis (TAK) patients are at an elevated risk of metabolic syndrome and cardiovascular diseases (CVD). Currently, there are no well-validated biomarkers to assess this risk in this population. Previous research in different cohorts has linked serum levels of osteoprotegerin (OPG) and its polymorphisms to accelerated atherosclerosis and a marker of poor prognosis in CVD. Thus, we assessed this protein as a potential biomarker of CVD in TAK patients. Objectives To evaluate the serum levels of OPG and its SNPs (single nucleotide polymorphisms) in TAK patients and healthy controls, and to associate these parameters with clinical data. Methods This bicentric cross-sectional study included TAK patients who were compared with healthy individuals (control group). The serum levels of OPG and the frequency of OPG SNPs [1181G > C (rs2073618), 245 A > C (rs3134069), 163T > C (rs3102735), and 209 C > T (rs3134070)] were compared between the both groups and associated with clinical data. Results In total, 101 TAK patients and 93 controls were included in the study. The serum levels of OPG (3.8 ± 1.9 vs. 4.3 ± 1.8pmol/L, respectively; P = 0.059), and its four polymorphisms were comparable between both groups. In an additional analysis of only TAK patients, serum OPG levels and its four genes were not associated with any CVD parameters, except for higher OPG levels among patients without dyslipidemia. Conclusion No significant differences were observed in serum OPG levels or in the genotype frequencies of OPG SNPs between the patient and control groups. Similarly, no correlation was found between laboratory parameters and clinical data on CVD risk in TAK patients. Takayasus Takayasu s (TAK . (CVD) Currently wellvalidated well validated population (OPG Thus single crosssectional cross sectional group. group group) 1181G G rs2073618, rs2073618 rs , (rs2073618) 24 rs3134069, rs3134069 (rs3134069) rs3102735, rs3102735 (rs3102735) 20 rs3134070 (rs3134070) total 10 9 3.8 38 3 8 (3. 19 1 1. vs 43 4 4. 18pmolL pmolL 8pmol L pmol 1.8pmol/L respectively 0.059, 0059 0.059 0 059 0.059) dyslipidemia Similarly (CVD rs207361 (rs2073618 2 rs313406 (rs3134069 rs310273 (rs3102735 rs313407 (rs3134070 3. (3 005 0.05 05 rs20736 (rs207361 rs31340 (rs313406 rs31027 (rs310273 (rs313407 ( 00 0.0 rs2073 (rs20736 rs3134 (rs31340 rs3102 (rs31027 0. rs207 (rs2073 rs313 (rs3134 rs310 (rs3102 rs20 (rs207 rs31 (rs313 (rs310 rs2 (rs20 rs3 (rs31 (rs2 (rs3 (rs

Abstract Objective: To assess factors associated with emotional changes and Hyperactivity/Inattention (HI) motivated by COVID-19 quarantine in adolescents with immunocompromising diseases. Methods: A cross-sectional study included 343 adolescents with immunocompromising diseases and 108 healthy adolescents. Online questionnaires were answered including socio-demographic data and self-rated healthcare routine during COVID-19 quarantine and validated surveys: Strengths and Difficulties Questionnaire (SDQ), Pittsburgh Sleep Quality Index (PSQI), Pediatric Quality of Life Inventory 4.0 (PedsQL4.0). Results: The frequencies of abnormal emotional SDQ scores from adolescents with chronic diseases were similar to those of healthy subjects (110/343 [32%] vs. 38/108 [35%], p = 0.548), as well as abnormal hyperactivity/inattention SDQ scores (79/343 [23%] vs. 29/108 [27%], p = 0.417). Logistic regression analysis of independent variables associated with abnormal emotional scores from adolescents with chronic diseases showed: female sex (Odds Ratio [OR = 3.76]; 95% Confidence Interval (95% CI) 2.00–7.05; p < 0.001), poor sleep quality (OR = 2.05; 95% CI 1.08–3.88; p = 0.028) and intrafamilial violence during pandemic (OR = 2.17; 95% CI 1.12–4.19; p = 0.021) as independently associated with abnormal emotional scores, whereas total PedsQL score was inversely associated with abnormal emotional scores (OR = 0.95; 95% CI 0.93–0.96; p < 0.0001). Logistic regression analysis associated with abnormal HI scores from patients evidenced that total PedsQL score (OR = 0.97; 95% CI 0.95–0.99; p = 0.010], changes in medical appointments during the pandemic (OR = 0.39; 95% CI 0.19–0.79; p = 0.021), and reliable COVID-19 information (OR = 0.35; 95% CI 0.16–0.77; p = 0.026) remained inversely associated with abnormal HI scores. Conclusion: The present study showed emotional and HI disturbances in adolescents with chronic immunosuppressive diseases during the COVID-19 pandemic. It reinforces the need to promptly implement a longitudinal program to protect the mental health of adolescents with and without chronic illnesses during future pandemics. Objective HyperactivityInattention Hyperactivity Inattention (HI COVID19 COVID 19 COVID-1 Methods crosssectional cross sectional 34 10 sociodemographic socio demographic selfrated self rated surveys SDQ, , (SDQ) PSQI, PSQI (PSQI) 40 4 0 4. PedsQL4.0. PedsQL40 PedsQL4.0 . PedsQL4 (PedsQL4.0) Results 110/343 110343 110 (110/34 32% 32 [32% vs 38108 38 38/10 35%, 35 35% [35%] 0.548, 0548 0.548 548 0.548) hyperactivityinattention hyperactivity inattention 79/343 79343 79 (79/34 23% 23 [23% 29108 29 29/10 27%, 27 27% [27%] 0.417. 0417 0.417 417 0.417) Odds OR 3.76 376 3 76 3.76] 95 (95 2.00–7.05 200705 2 00 7 05 0.001, 0001 0.001 001 0.001) 2.05 205 1.08–3.88 108388 1 08 88 0.028 0028 028 2.17 217 17 1.12–4.19 112419 12 0.021 0021 021 0.95 095 0.93–0.96 093096 93 96 0.0001. 00001 0.0001 0.0001) 0.97 097 97 0.95–0.99 095099 99 0.010, 0010 0.010 010 0.010] 0.39 039 39 0.19–0.79 019079 0.021, 0.35 035 0.16–0.77 016077 16 77 0.026 0026 026 Conclusion pandemics COVID1 COVID- (SDQ (PSQI PedsQL4. (PedsQL4.0 110/34 11034 11 (110/3 [32 3810 38/1 [35% 054 0.54 54 79/34 7934 (79/3 [23 2910 29/1 [27% 041 0.41 41 3.7 37 9 (9 2.00–7.0 20070 000 0.00 2.0 20 1.08–3.8 10838 8 0.02 002 02 2.1 21 1.12–4.1 11241 0.9 09 0.93–0.9 09309 0000 0.000 0.95–0.9 09509 0.01 01 0.3 03 0.19–0.7 01907 0.16–0.7 01607 (PedsQL4. 110/3 1103 (110/ [3 381 38/ [35 0.5 5 79/3 793 (79/ [2 291 29/ [27 04 0.4 3. ( 2.00–7. 2007 0.0 2. 1.08–3. 1083 1.12–4. 1124 0. 0.93–0. 0930 0.95–0. 0950 0.19–0. 0190 0.16–0. 0160 (PedsQL4 110/ (110 [ 79/ (79 2.00–7 200 1.08–3 1.12–4 112 0.93–0 093 0.95–0 0.19–0 019 0.16–0 016 (PedsQL (11 (7 2.00– 1.08– 1.12– 0.93– 0.95– 0.19– 0.16– (1 2.00 1.08 1.12 0.93 0.19 0.16 1.0 1.1 0.1 1.

Abstract Background Few studies have assessed elderly patients with Takayasu’s arteritis (TAK). Objectives To evaluate the progression of TAK in different age groups and its possible effects on drug treatment and disease activity. Methods This cross-sectional and retrospective cohort study included 66 TAK patients. Patients were interviewed and data of the 12 preceding months were collected from electronic medical records. The patients were divided into four quartiles according to current age and compared for clinical and laboratory data, treatment, comorbidities, disease status, and functional status. Statistical significance was set at p<0.05. Results The groups were Q1(22-36 years, n=16), Q2(37-42 years, n=18), Q3(43-49 years, n=17), and Q4(51-66 years, n=15). The frequency of patients with disease activity, fatigue, comorbidities and vascular impairments, and the TAK disease extent index were also comparable between the groups. With age, disease duration was longer (p=0.001), fewer patients used prednisone (Q1:43.8%, Q2:33.3%, Q3:11.8%, and Q4:6.7%; p=0.049) and immunosuppressive drugs [Q1:100.0%, Q2:66.7%, Q3:58.8%, and Q4:46.7%; Q1 versus Q3 (p=0.043), and Q1 versus Q4 (p=0.005) in post-hoc analyses], and patients had greater functional status impairment (Q2 versus Q3, p=0.003). In addition, the levels of disease damage, new TAK symptoms, and complications in the preceding 12 months were not different between the groups. Conclusions Older patients with TAK require minimal drug treatment, and have greater impairment of functional status, which may be attributed to aging-related factors. Takayasus Takayasu s TAK. . (TAK) activity crosssectional cross sectional 6 1 records p005 p 0 05 p<0.05 Q12236 Q 22 36 Q1(22-3 years n=16, n16 n n=16 , 16 n=16) Q23742 Q2 37 42 Q2(37-4 n=18, n18 n=18 18 n=18) Q34349 43 49 Q3(43-4 n=17, n17 n=17 17 n=17) Q45166 51 Q4(51-6 n=15. n15 n=15 15 n=15) fatigue impairments p=0.001, p0001 p=0.001 001 (p=0.001) Q143.8%, Q1438 43.8%, 8 (Q1:43.8% Q233.3%, Q2333 33.3%, 33 3 Q2:33.3% Q311.8%, Q3118 11.8%, 11 Q3:11.8% Q46.7% Q467 6.7% 7 Q4:6.7% p=0.049 p0049 049 Q1100.0%, Q11000 100.0%, 100 [Q1:100.0% Q266.7%, Q2667 66.7%, Q2:66.7% Q358.8%, Q3588 58.8%, 58 Q3:58.8% Q446.7% Q4467 46.7% 46 Q4:46.7% p=0.043, p0043 p=0.043 043 (p=0.043) p=0.005 p0005 005 (p=0.005 posthoc post hoc analyses, analyses analyses] (Q p=0.003. p0003 p=0.003 003 p=0.003) addition damage symptoms agingrelated aging related factors (TAK p00 p<0.0 Q1223 2 Q1(22- n1 n=1 Q2374 4 Q2(37- Q3434 Q3(43- Q4516 5 Q4(51- p000 p=0.00 00 (p=0.001 Q143 Q143.8% 438 43.8% (Q1:43.8 Q233 Q233.3% 333 33.3% Q2:33.3 Q311 Q311.8% 118 11.8% Q3:11.8 Q46 Q46.7 67 6.7 Q4:6.7 p=0.04 p004 04 Q1100 Q1100.0% 1000 100.0% 10 [Q1:100.0 Q266 Q266.7% 667 66.7% Q2:66.7 Q358 Q358.8% 588 58.8% Q3:58.8 Q446 Q446.7 467 46.7 Q4:46.7 (p=0.043 (p=0.00 p0 p<0. Q122 Q1(22 n= Q237 Q2(37 Q343 Q3(43 Q451 Q4(51 p=0.0 Q14 Q143.8 43.8 (Q1:43. Q23 Q233.3 33.3 Q2:33. Q31 Q311.8 11.8 Q3:11. Q46. 6. Q4:6. Q110 Q1100.0 100.0 [Q1:100. Q26 Q266.7 66.7 Q2:66. Q35 Q358.8 58.8 Q3:58. Q44 Q446. 46. Q4:46. (p=0.04 (p=0.0 p<0 Q12 Q1(2 Q2(3 Q34 Q3(4 Q45 Q4(5 p=0. Q143. 43. (Q1:43 Q233. 33. Q2:33 Q311. 11. Q3:11 Q4:6 Q11 Q1100. 100. [Q1:100 Q266. 66. Q2:66 Q358. 58. Q3:58 Q4:46 (p=0. p< Q1( Q2( Q3( Q4( p=0 (Q1:4 Q2:3 Q3:1 Q4: [Q1:10 Q2:6 Q3:5 Q4:4 (p=0 p= (Q1: Q2: Q3: [Q1:1 (p= (Q1 [Q1: (p [Q1 [Q

Resumo Fundamentos Poucos estudos avaliaram pacientes idosos com Arterite de Takayasu (AT). Objetivo Avaliar o progresso de AT em diferentes grupos etários em seus possíveis efeitos sobre o tratamento medicamentoso e atividade da doença. Métodos este estudo transversal, retrospectivo, do tipo coorte incluiu 66 pacientes com AT. Os pacientes foram entrevistados, e dados dos 12 meses anteriores foram coletados dos prontuários médicos eletrônicos. Os pacientes foram divididos em quatro quartis de acordo com idade atual, e comparados quanto aos dados clínicos e laboratoriais, tratamento, comorbidades, status da doença, e status funcional. Um p<0,05 foi estabelecido como estatisticamente significativo. Resultados Os grupos foram definidos como Q1(22-36 anos, n=16), Q2(37-42 anos, n=18), Q3(43-49 anos, n=17), e Q4(51-66 anos, n=15). A frequência de pacientes com atividade da doença, fadiga, comorbidades e comprometimentos vasculares, e o índice de extensão da doença (DEI. Tak) foram comparáveis entre os grupos. Pacientes com idade mais avançada apresentaram maior duração da doença (p=0,001) e maior comprometimento do status funcional (Q2 versus Q3, p=0,003); menos pacientes usaram prednisona (Q1:43,8%; Q2:33,3%; Q3:11,8%; e Q4:6,7%; p=0,049) e agentes imunossupressores [Q1:100,0%; Q2:66,7%; Q3:58,8% e Q4:46,7%; Q1 versus Q3 (p=0,043) e Q1 versus Q4 (p=0,005) nas análises post-hoc]. Além disso, os níveis de danos da doença, sintomas de uma nova ocorrência de AT, e complicações nos 12 meses precedentes não foram diferentes entre os grupos. Conclusão Pacientes com AT e idade mais avançada requerem mínima intervenção medicamentosa e apresentam maior comprometimento no status funcional, o que pode ser atribuído a fatores relacionados ao envelhecimento. . (AT) transversal retrospectivo 6 entrevistados 1 eletrônicos atual laboratoriais p005 p 0 05 p<0,0 significativo Q12236 Q 22 36 Q1(22-3 anos n=16, n16 n n=16 , 16 n=16) Q23742 Q2 37 42 Q2(37-4 n=18, n18 n=18 18 n=18) Q34349 43 49 Q3(43-4 n=17, n17 n=17 17 n=17) Q45166 51 Q4(51-6 n=15. n15 n=15 15 n=15) fadiga vasculares DEI. DEI (DEI Tak p=0,001 p0001 001 (p=0,001 (Q p=0,003 p0003 003 p=0,003) Q143,8% Q1438 43,8% 8 (Q1:43,8% Q233,3% Q2333 33,3% 33 3 Q2:33,3% Q311,8% Q3118 11,8% 11 Q3:11,8% Q46,7% Q467 6,7% 7 Q4:6,7% p=0,049 p0049 049 Q1100,0% Q11000 100,0% 100 [Q1:100,0% Q266,7% Q2667 66,7% Q2:66,7% Q358,8% Q3588 58,8% 58 Q3:58,8 Q446,7% Q4467 46,7% 46 Q4:46,7% p=0,043 p0043 043 (p=0,043 p=0,005 p0005 005 (p=0,005 posthoc. posthoc post hoc post-hoc] disso envelhecimento (AT p00 p<0, Q1223 2 Q1(22- n1 n=1 Q2374 4 Q2(37- Q3434 Q3(43- Q4516 5 Q4(51- p=0,00 p000 00 (p=0,00 Q143 Q143,8 438 43,8 (Q1:43,8 Q233 Q233,3 333 33,3 Q2:33,3 Q311 Q311,8 118 11,8 Q3:11,8 Q46 Q46,7 67 6,7 Q4:6,7 p=0,04 p004 04 Q1100 Q1100,0 1000 100,0 10 [Q1:100,0 Q266 Q266,7 667 66,7 Q2:66,7 Q358 Q358,8 588 58,8 Q3:58, Q446 Q446,7 467 46,7 Q4:46,7 (p=0,04 post-hoc p0 p<0 Q122 Q1(22 n= Q237 Q2(37 Q343 Q3(43 Q451 Q4(51 p=0,0 (p=0,0 Q14 Q143, 43, (Q1:43, Q23 Q233, 33, Q2:33, Q31 Q311, 11, Q3:11, Q46, 6, Q4:6, Q110 Q1100, 100, [Q1:100, Q26 Q266, 66, Q2:66, Q35 Q358, 58, Q3:58 Q44 Q446, 46, Q4:46, p< Q12 Q1(2 Q2(3 Q34 Q3(4 Q45 Q4(5 p=0, (p=0, (Q1:43 Q2:33 Q3:11 Q4:6 Q11 [Q1:100 Q2:66 Q3:5 Q4:46 Q1( Q2( Q3( Q4( p=0 (p=0 (Q1:4 Q2:3 Q3:1 Q4: [Q1:10 Q2:6 Q3: Q4:4 p= (p= (Q1: Q2: [Q1:1 (p (Q1 [Q1: [Q1 [Q

Abstract Background Anabolic androgenic steroid (AAS) abuse has been associated with coronary artery disease (CAD). Pericoronary fat attenuation (pFA) is a marker of coronary inflammation, which is key in the atherosclerotic process. Objective To evaluate pFA and inflammatory profile in AAS users. Methods Twenty strength-trained AAS users (AASU), 20 AAS nonusers (AASNU), and 10 sedentary controls (SC) were evaluated. Coronary inflammation was evaluated by mean pericoronary fat attenuation (mPFA) in the right coronary artery (RCA), left anterior descending coronary artery (LAD), and left circumflex (LCx). Interleukin (IL)-1 (IL-1), IL-6, IL-10, and TNF-alpha were evaluated by optical density (OD) in a spectrophotometer with a 450 nm filter. P<0.05 indicated statistical significance. Results AASU had higher mPFA in the RCA (-65.87 [70.51-60.70] vs. -78.07 [83.66-72.87] vs.-78.46 [85.41-71.99] Hounsfield Units (HU), respectively, p<0.001) and mPFA in the LAD (-71.47 [76.40-66.61] vs. -79.32 [84.37-74.59] vs. -82.52 [88.44-75.81] HU, respectively, p=0.006) compared with AASNU and SC. mPFA in the LCx was not different between AASU, AASNU, and SC (-72.41 [77.17-70.37] vs. -80.13 [86.22-72.23] vs. -78.29 [80.63-72.29] HU, respectively, p=0.163). AASU compared with AASNU and SC, had higher IL-1, (0.975 [0.847-1.250] vs. 0.437 [0.311-0.565] vs. 0.530 [0.402-0.780] OD, respectively, p=0.002), IL-6 (1.195 [0.947-1.405] vs. 0.427 [0.377-0.577] vs. 0.605 [0.332-0.950] OD, p=0.005) and IL-10 (1.145 [0.920-1.292] vs. 0.477 [0.382-0.591] vs. 0.340 [0.316-0.560] OD, p<0.001). TNF-α was not different between the AASU, AASNU, and SC groups (0.520 [0.250-0.610] vs. 0.377 [0.261-0.548] vs. 0.350 [0.182-430]), respectively. Conclusion Compared with ASSNU and controls, AASU have higher mPFA and higher systemic inflammatory cytokines profile suggesting that AAS may induce coronary atherosclerosis through coronary and systemic inflammation. (AAS CAD. CAD . (CAD) (pFA process strengthtrained strength trained , (AASU) 2 (AASNU) 1 (SC (mPFA RCA, (RCA) LAD, (LAD) LCx. (LCx) IL1 IL (IL)- IL1, (IL-1) IL6, IL6 6, 6 IL10, IL10 10, TNFalpha TNF alpha OD (OD 45 filter P005 P 0 05 P<0.0 significance 65.87 6587 65 87 (-65.8 70.5160.70 70516070 70.51 60.70 70 51 60 [70.51-60.70 vs 78.07 7807 78 07 -78.0 83.6672.87 83667287 83.66 72.87 83 66 72 [83.66-72.87 vs.78.46 vs7846 78.46 46 vs.-78.4 85.4171.99 85417199 85.41 71.99 85 41 71 99 [85.41-71.99 HU (HU) respectively p<0.001 p0001 p 001 71.47 7147 47 (-71.4 76.4066.61 76406661 76.40 66.61 76 40 61 [76.40-66.61 79.32 7932 79 32 -79.3 84.3774.59 84377459 84.37 74.59 84 37 74 59 [84.37-74.59 82.52 8252 82 52 -82.5 88.4475.81 88447581 88.44 75.81 88 44 75 81 [88.44-75.81 p=0.006 p0006 006 72.41 7241 (-72.4 77.1770.37 77177037 77.17 70.37 77 17 [77.17-70.37 80.13 8013 80 13 -80.1 86.2272.23 86227223 86.22 72.23 86 22 23 [86.22-72.23 78.29 7829 29 -78.2 80.6372.29 80637229 80.63 72.29 63 [80.63-72.29 p=0.163. p0163 p=0.163 163 p=0.163) 1, IL-1 0.975 0975 975 (0.97 0.8471.250 08471250 0.847 1.250 847 250 [0.847-1.250 0437 437 0.43 0.3110.565 03110565 0.311 0.565 311 565 [0.311-0.565 0530 530 0.53 0.4020.780 04020780 0.402 0.780 402 780 [0.402-0.780 p=0.002, p0002 p=0.002 002 p=0.002) IL- 1.195 1195 195 (1.19 0.9471.405 09471405 0.947 1.405 947 405 [0.947-1.405 0427 427 0.42 0.3770.577 03770577 0.577 377 577 [0.377-0.577 0605 605 0.60 0.3320.950 03320950 0.332 0.950 332 950 [0.332-0.950 p=0.005 p0005 005 1.145 1145 145 (1.14 0.9201.292 09201292 0.920 1.292 920 292 [0.920-1.292 0477 477 0.47 0.3820.591 03820591 0.382 0.591 382 591 [0.382-0.591 0340 340 0.34 0.3160.560 03160560 0.316 0.560 316 560 [0.316-0.560 p<0.001. TNFα α 0.520 0520 520 (0.52 0.2500.610 02500610 0.250 0.610 610 [0.250-0.610 0377 0.37 0.2610.548 02610548 0.261 0.548 261 548 [0.261-0.548 0350 350 0.35 0.182430, 0182430 0.182 430 182 [0.182-430]) (CAD (AASU (AASNU (RCA (LAD (LCx (IL) (IL-1 4 P00 P<0. 65.8 658 8 (-65. 5160 70.5160.7 7051607 7051 70.5 6070 60.7 7 5 [70.51-60.7 78.0 -78. 6672 83.6672.8 8366728 8366 83.6 7287 72.8 [83.66-72.8 vs.78.4 vs784 7846 78.4 vs.-78. 4171 85.4171.9 8541719 8541 85.4 7199 71.9 9 [85.41-71.9 (HU p<0.00 p000 00 71.4 714 (-71. 4066 76.4066.6 7640666 7640 76.4 6661 66.6 [76.40-66.6 79.3 793 3 -79. 3774 84.3774.5 8437745 8437 84.3 7459 74.5 [84.37-74.5 82.5 825 -82. 4475 88.4475.8 8844758 8844 88.4 7581 75.8 [88.44-75.8 p=0.00 72.4 724 (-72. 1770 77.1770.3 7717703 7717 77.1 7037 70.3 [77.17-70.3 80.1 801 -80. 2272 86.2272.2 8622722 8622 86.2 7223 72.2 [86.22-72.2 78.2 782 6372 80.6372.2 8063722 8063 80.6 7229 [80.63-72.2 p016 p=0.16 16 0.97 097 97 (0.9 8471 0.8471.25 0847125 0847 0.84 1250 1.25 25 [0.847-1.25 043 43 0.4 3110 0.3110.56 0311056 0311 0.31 0565 0.56 31 56 [0.311-0.56 053 53 0.5 4020 0.4020.78 0402078 0402 0.40 0780 0.78 [0.402-0.78 1.19 119 19 (1.1 9471 0.9471.40 0947140 0947 0.94 1405 1.40 94 [0.947-1.40 042 42 3770 0.3770.57 0377057 0577 0.57 57 [0.377-0.57 060 0.6 3320 0.3320.95 0332095 0332 0.33 0950 0.95 33 95 [0.332-0.95 1.14 114 14 9201 0.9201.29 0920129 0920 0.92 1292 1.29 92 [0.920-1.29 047 3820 0.3820.59 0382059 0382 0.38 0591 0.59 38 [0.382-0.59 034 34 0.3 3160 0.3160.56 0316056 0316 0560 [0.316-0.56 0.52 052 (0.5 2500 0.2500.61 0250061 0250 0.25 0610 0.61 [0.250-0.61 037 2610 0.2610.54 0261054 0261 0.26 0548 0.54 26 54 [0.261-0.54 035 35 182430 0.182430 018243 0182 0.18 18 [0.182-430] (IL (IL- P0 P<0 65. (-65 516 70.5160. 705160 705 70. 607 60. [70.51-60. 78. -78 667 83.6672. 836672 836 83. 728 72. [83.66-72. vs.78. vs78 784 vs.-78 417 85.4171. 854171 854 85. 719 71. [85.41-71. p<0.0 p00 (-71 406 76.4066. 764066 764 76. 666 66. [76.40-66. 79. -79 84.3774. 843774 843 84. 745 74. [84.37-74. 82. -82 447 88.4475. 884475 884 88. 758 75. [88.44-75. p=0.0 (-72 177 77.1770. 771770 771 77. 703 [77.17-70. 80. -80 227 86.2272. 862272 862 86. 722 [86.22-72. 637 80.6372. 806372 806 [80.63-72. p01 p=0.1 0.9 09 (0. 0.8471.2 084712 084 0.8 125 1.2 [0.847-1.2 04 0. 0.3110.5 031105 031 056 [0.311-0.5 0.4020.7 040207 040 078 0.7 [0.402-0.7 1.1 11 (1. 0.9471.4 094714 094 140 1.4 [0.947-1.4 0.3770.5 037705 057 [0.377-0.5 06 0.3320.9 033209 033 095 [0.332-0.9 0.9201.2 092012 092 129 [0.920-1.2 0.3820.5 038205 038 059 [0.382-0.5 03 0.3160.5 031605 [0.316-0.5 0.2500.6 025006 025 0.2 061 [0.250-0.6 0.2610.5 026105 026 054 [0.261-0.5 18243 0.18243 01824 018 0.1 [0.182-430 P< (-6 70.5160 70516 [70.51-60 -7 83.6672 83667 [83.66-72 vs.78 vs7 vs.-7 85.4171 85417 [85.41-71 p<0. p0 (-7 76.4066 76406 [76.40-66 84.3774 84377 [84.37-74 -8 88.4475 88447 [88.44-75 p=0. 77.1770 77177 [77.17-70 86.2272 86227 [86.22-72 80.6372 80637 [80.63-72 (0 0.8471. 08471 08 12 1. [0.847-1. 0.3110. 03110 [0.311-0. 0.4020. 04020 [0.402-0. (1 0.9471. 09471 [0.947-1. 0.3770. 03770 [0.377-0. 0.3320. 03320 [0.332-0. 0.9201. 09201 [0.920-1. 0.3820. 03820 [0.382-0. 0.3160. 03160 [0.316-0. 0.2500. 02500 02 [0.250-0. 0.2610. 02610 [0.261-0. 1824 0.1824 01 [0.182-43 (- 70.516 [70.51-6 - 83.667 [83.66-7 vs.7 vs.- 85.417 [85.41-7 p<0 76.406 [76.40-6 84.377 [84.37-7 88.447 [88.44-7 p=0 77.177 [77.17-7 86.227 [86.22-7 80.637 [80.63-7 ( 0.8471 [0.847-1 0.3110 [0.311-0 0.4020 [0.402-0 0.9471 [0.947-1 0.3770 [0.377-0 0.3320 [0.332-0 0.9201 [0.920-1 0.3820 [0.382-0 0.3160 [0.316-0 0.2500 [0.250-0 0.2610 [0.261-0 [0.182-4 [70.51- [83.66- [85.41- p< [76.40- [84.37- [88.44- p= [77.17- [86.22- [80.63- [0.847- [0.311- [0.402- [0.947- [0.377- [0.332- [0.920- [0.382- [0.316- [0.250- [0.261- [0.182- [70.51 [83.66 [85.41 [76.40 [84.37 [88.44 [77.17 [86.22 [80.63 [0.847 [0.311 [0.402 [0.947 [0.377 [0.332 [0.920 [0.382 [0.316 [0.250 [0.261 [0.182 [70.5 [83.6 [85.4 [76.4 [84.3 [88.4 [77.1 [86.2 [80.6 [0.84 [0.31 [0.40 [0.94 [0.37 [0.33 [0.92 [0.38 [0.25 [0.26 [0.18 [70. [83. [85. [76. [84. [88. [77. [86. [80. [0.8 [0.3 [0.4 [0.9 [0.2 [0.1 [70 [83 [85 [76 [84 [88 [77 [86 [80 [0. [7 [8 [0 [

Resumo Fundamento O uso abusivo de esteroides anabólicos androgênicos (EAA) tem sido associado à doença arterial coronariana (DAC). A atenuação de gordura pericoronária (AGp) é um marcador de inflamação coronária, a qual exerce um papel chave no processo aterosclerótico. Objetivo Avaliar AGp e perfil inflamatório em usuários de EAA. Método Vinte indivíduos que realizavam treinamento de força, usuários de EAA (UEAA), 20 não usuários de EAA (NUEAA), e 10 indivíduos sedentários controle (SC) foram avaliados. Inflamação coronária foi avaliada por atenuação de gordura pericoronária média (AGPm) artéria coronária direita (ACD), artéria descendente anterior esquerda (ADA) e artéria circunflexa (ACX). Interleucina (IL)-1 (IL-1), IL-6, IL-10, e TNF-alfa foram avaliados por densidade ótica (DO) em um espectrofotômetro com um filtro de 450 nm. Um p<0,05 indicou significância estatística. Resultados Os UEAA apresentaram maior AGPm na ACD [-65,87 (70,51-60,70) vs. -78,07 (83,66-72,87) vs.-78,46 (85,41-71,99] unidades Hounsfield (HU), respectivamente, p<0,001) e AGPm na ADA [-71,47 (76,40-66,610 vs. -79,32 (84,37-74,59) vs. -82,52 (88,44-75,81) HU, respectivamente, p=0,006) em comparação aos NUEAA e CS. A AGPm na ACX não foi diferente entre os grupos UEAA, NUEAA e CS [-72,41 (77,17-70,37) vs. -80,13 (86,22-72,23) vs. -78,29 (80,63-72,29) HU, respectivamente, p=0,163). Em comparação aos NUEAA e aos CS, o grupo UEAA apresentaram maiores níveis de IL-1 [0,975 (0,847-1,250) vs. 0,437 (0,311-0,565) vs. 0,530 (0,402-0,780) DO, respectivamente, p=0,002), IL-6 [1,195 (0,947-1,405) vs. 0,427 (0,377-0,577) vs. 0,605 (0,332-0,950) DO, p=0,005) e IL-10 [1,145 (0,920-1,292) vs. 0,477 (0,382-0,591) vs. 0,340 (0,316-0,560) DO, p<0,001]. TNF-α não foi diferente entre os grupos UEAA, NUEAA e CS [0,520 (0,250-0,610) vs. 0,377 (0.261-0,548) vs. 0,350 (0,182-430)]. Conclusão Em comparação aos NUEAA e controles, os UEAA apresentam maior AGPm e maior perfil de citocinas inflamatórias sistêmicas, sugerindo que os EAA podem induzir aterosclerose por inflamação coronária e sistêmica. (EAA DAC. DAC . (DAC) (AGp aterosclerótico força , (UEAA) 2 NUEAA, (NUEAA) 1 SC (SC (AGPm ACD, (ACD) (ADA ACX. (ACX) IL1 IL (IL)- IL1, (IL-1) IL6, IL6 6, 6 IL10, IL10 10, TNFalfa TNF alfa DO (DO 45 nm p005 p 0 05 p<0,0 estatística 65,87 6587 65 87 [-65,8 70,5160,70 70516070 70,51 60,70 70 51 60 (70,51-60,70 vs 78,07 7807 78 07 -78,0 83,6672,87 83667287 83,66 72,87 83 66 72 (83,66-72,87 vs.78,46 vs7846 78,46 46 vs.-78,4 85,4171,99 85417199 85,41 71,99 85 41 71 99 (85,41-71,99 HU (HU) respectivamente p<0,001 p0001 001 71,47 7147 47 [-71,4 76,4066,610 764066610 76,40 66,610 76 40 610 (76,40-66,61 79,32 7932 79 32 -79,3 84,3774,59 84377459 84,37 74,59 84 37 74 59 (84,37-74,59 82,52 8252 82 52 -82,5 88,4475,81 88447581 88,44 75,81 88 44 75 81 (88,44-75,81 p=0,006 p0006 006 72,41 7241 [-72,4 77,1770,37 77177037 77,17 70,37 77 17 (77,17-70,37 80,13 8013 80 13 -80,1 86,2272,23 86227223 86,22 72,23 86 22 23 (86,22-72,23 78,29 7829 29 -78,2 80,6372,29 80637229 80,63 72,29 63 (80,63-72,29 p=0,163. p0163 p=0,163 163 p=0,163) IL- 0,975 0975 975 [0,97 0,8471,250 08471250 0,847 1,250 847 250 (0,847-1,250 0437 437 0,43 0,3110,565 03110565 0,311 0,565 311 565 (0,311-0,565 0530 530 0,53 0,4020,780 04020780 0,402 0,780 402 780 (0,402-0,780 p=0,002, p0002 p=0,002 002 p=0,002) 1,195 1195 195 [1,19 0,9471,405 09471405 0,947 1,405 947 405 (0,947-1,405 0427 427 0,42 0,3770,577 03770577 0,577 377 577 (0,377-0,577 0605 605 0,60 0,3320,950 03320950 0,332 0,950 332 950 (0,332-0,950 p=0,005 p0005 005 1,145 1145 145 [1,14 0,9201,292 09201292 0,920 1,292 920 292 (0,920-1,292 0477 477 0,47 0,3820,591 03820591 0,382 0,591 382 591 (0,382-0,591 0340 340 0,34 0,3160,560 03160560 0,316 0,560 316 560 (0,316-0,560 p<0,001. p<0,001] TNFα α 0,520 0520 520 [0,52 0,2500,610 02500610 0,250 0,610 (0,250-0,610 0377 0,37 0.2610,548 02610548 0.261 0,548 261 548 (0.261-0,548 0350 350 0,35 0,182430. 0182430 0,182 430 182 (0,182-430)] controles sistêmicas sistêmica (DAC (UEAA (NUEAA (ACD (ACX (IL) (IL-1 4 p00 p<0, 65,8 658 8 [-65, 5160 70,5160,7 7051607 7051 70,5 6070 60,7 7 5 (70,51-60,7 78,0 -78, 6672 83,6672,8 8366728 8366 83,6 7287 72,8 (83,66-72,8 vs.78,4 vs784 7846 78,4 vs.-78, 4171 85,4171,9 8541719 8541 85,4 7199 71,9 9 (85,41-71,9 (HU p<0,00 p000 00 71,4 714 [-71, 4066 76,4066,61 76406661 7640 76,4 66610 66,61 61 (76,40-66,6 79,3 793 3 -79, 3774 84,3774,5 8437745 8437 84,3 7459 74,5 (84,37-74,5 82,5 825 -82, 4475 88,4475,8 8844758 8844 88,4 7581 75,8 (88,44-75,8 p=0,00 72,4 724 [-72, 1770 77,1770,3 7717703 7717 77,1 7037 70,3 (77,17-70,3 80,1 801 -80, 2272 86,2272,2 8622722 8622 86,2 7223 72,2 (86,22-72,2 78,2 782 6372 80,6372,2 8063722 8063 80,6 7229 (80,63-72,2 p016 p=0,16 16 0,97 097 97 [0,9 8471 0,8471,25 0847125 0847 0,84 1250 1,25 25 (0,847-1,25 043 43 0,4 3110 0,3110,56 0311056 0311 0,31 0565 0,56 31 56 (0,311-0,56 053 53 0,5 4020 0,4020,78 0402078 0402 0,40 0780 0,78 (0,402-0,78 1,19 119 19 [1,1 9471 0,9471,40 0947140 0947 0,94 1405 1,40 94 (0,947-1,40 042 42 3770 0,3770,57 0377057 0577 0,57 57 (0,377-0,57 060 0,6 3320 0,3320,95 0332095 0332 0,33 0950 0,95 33 95 (0,332-0,95 1,14 114 14 9201 0,9201,29 0920129 0920 0,92 1292 1,29 92 (0,920-1,29 047 3820 0,3820,59 0382059 0382 0,38 0591 0,59 38 (0,382-0,59 034 34 0,3 3160 0,3160,56 0316056 0316 0560 (0,316-0,56 0,52 052 [0,5 2500 0,2500,61 0250061 0250 0,25 0610 0,61 (0,250-0,61 037 2610 0.2610,54 0261054 0261 0.26 0548 0,54 26 54 (0.261-0,54 035 35 182430 0,182430 018243 0182 0,18 18 (0,182-430) (IL (IL- p0 p<0 65, [-65 516 70,5160, 705160 705 70, 607 60, (70,51-60, 78, -78 667 83,6672, 836672 836 83, 728 72, (83,66-72, vs.78, vs78 784 vs.-78 417 85,4171, 854171 854 85, 719 71, (85,41-71, [-71 406 76,4066,6 7640666 764 76, 6661 66,6 (76,40-66, 79, -79 84,3774, 843774 843 84, 745 74, (84,37-74, 82, -82 447 88,4475, 884475 884 88, 758 75, (88,44-75, p=0,0 [-72 177 77,1770, 771770 771 77, 703 (77,17-70, 80, -80 227 86,2272, 862272 862 86, 722 (86,22-72, 637 80,6372, 806372 806 (80,63-72, p01 p=0,1 0,9 09 [0, 0,8471,2 084712 084 0,8 125 1,2 (0,847-1,2 04 0, 0,3110,5 031105 031 056 (0,311-0,5 0,4020,7 040207 040 078 0,7 (0,402-0,7 1,1 11 [1, 0,9471,4 094714 094 140 1,4 (0,947-1,4 0,3770,5 037705 057 (0,377-0,5 06 0,3320,9 033209 033 095 (0,332-0,9 0,9201,2 092012 092 129 (0,920-1,2 0,3820,5 038205 038 059 (0,382-0,5 03 0,3160,5 031605 (0,316-0,5 0,2500,6 025006 025 0,2 061 (0,250-0,6 0.2610,5 026105 026 0.2 054 (0.261-0,5 18243 0,18243 01824 018 0,1 (0,182-430 p< [-6 70,5160 70516 (70,51-60 -7 83,6672 83667 (83,66-72 vs.78 vs7 vs.-7 85,4171 85417 (85,41-71 [-7 76,4066, 764066 666 66, (76,40-66 84,3774 84377 (84,37-74 -8 88,4475 88447 (88,44-75 p=0, 77,1770 77177 (77,17-70 86,2272 86227 (86,22-72 80,6372 80637 (80,63-72 [0 0,8471, 08471 08 12 1, (0,847-1, 0,3110, 03110 (0,311-0, 0,4020, 04020 (0,402-0, [1 0,9471, 09471 (0,947-1, 0,3770, 03770 (0,377-0, 0,3320, 03320 (0,332-0, 0,9201, 09201 (0,920-1, 0,3820, 03820 (0,382-0, 0,3160, 03160 (0,316-0, 0,2500, 02500 02 (0,250-0, 0.2610, 02610 0. (0.261-0, 1824 0,1824 01 (0,182-43 [- 70,516 (70,51-6 - 83,667 (83,66-7 vs.7 vs.- 85,417 (85,41-7 76,4066 76406 (76,40-6 84,377 (84,37-7 88,447 (88,44-7 p=0 77,177 (77,17-7 86,227 (86,22-7 80,637 (80,63-7 [ 0,8471 (0,847-1 0,3110 (0,311-0 0,4020 (0,402-0 0,9471 (0,947-1 0,3770 (0,377-0 0,3320 (0,332-0 0,9201 (0,920-1 0,3820 (0,382-0 0,3160 (0,316-0 0,2500 (0,250-0 0.2610 (0.261-0 (0,182-4 (70,51- (83,66- (85,41- 76,406 (76,40- (84,37- (88,44- p= (77,17- (86,22- (80,63- (0,847- (0,311- (0,402- (0,947- (0,377- (0,332- (0,920- (0,382- (0,316- (0,250- (0.261- (0,182- (70,51 (83,66 (85,41 (76,40 (84,37 (88,44 (77,17 (86,22 (80,63 (0,847 (0,311 (0,402 (0,947 (0,377 (0,332 (0,920 (0,382 (0,316 (0,250 (0.261 (0,182 (70,5 (83,6 (85,4 (76,4 (84,3 (88,4 (77,1 (86,2 (80,6 (0,84 (0,31 (0,40 (0,94 (0,37 (0,33 (0,92 (0,38 (0,25 (0.26 (0,18 (70, (83, (85, (76, (84, (88, (77, (86, (80, (0,8 (0,3 (0,4 (0,9 (0,2 (0.2 (0,1 (70 (83 (85 (76 (84 (88 (77 (86 (80 (0, (0. (7 (8 (0 (

Abstract Objectives This analysis describes the protocol of a study with a case-cohort to design to prospectively evaluate the incidence of subclinical atherosclerosis and Cardiovascular Disease (CVD) in Chronic Inflammatory Disease (CID) participants compared to non-diseased ones. Methods A high-risk group for CID was defined based on data collected in all visits on self-reported medical diagnosis, use of medicines, and levels of high-sensitivity C-Reactive Protein >10 mg/L. The comparison group is the Aleatory Cohort Sample (ACS): a group with 10% of participants selected at baseline who represent the entire cohort. In both groups, specific biomarkers for DIC, markers of subclinical atherosclerosis, and CVD morbimortality will be tested using weighted Cox. Results The high-risk group (n = 2,949; aged 53.6 ± 9.2; 65.5% women) and the ACS (n=1543; 52.2±8.8; 54.1% women) were identified. Beyond being older and mostly women, participants in the high-risk group present low average income (29.1% vs. 24.8%, p < 0.0001), higher BMI (Kg/m2) (28.1 vs. 26.9, p < 0.0001), higher waist circumference (cm) (93.3 vs. 91, p < 0.0001), higher frequencies of hypertension (40.2% vs. 34.5%, p < 0.0001), diabetes (20.7% vs. 17%, p = 0.003) depression (5.8% vs. 3.9%, p = 0.007) and higher levels of GlycA a new inflammatory marker (p < 0.0001) compared to the ACS. Conclusions The high-risk group selected mostly women, older, lower-income/education, higher BMI, waist circumference, and of hypertension, diabetes, depression, and higher levels of GlycA when compared to the ACS. The strategy chosen to define the high-risk group seems adequate given that multiple sociodemographic and clinical characteristics are compatible with CID.

Resumo Introdução: A composição corporal é fundamental para a avaliação de pacientes com Doença Renal Crônica (DRC), e pode ser obtida por análise de impedância bioelétrica por multifrequência (BIA) ou absorciometria de dupla energia (DXA). Embora a discrepância entre os resultados obtidos pelos dois métodos já tenha sido descrita, os motivos são desconhecidos e podem estar relacionados ao hiperparatireoidismo secundário, devido à perda óssea. Métodos: Avaliamos 49 pacientes (25 homens e 24 mulheres): 20 com DRC não em diálise e 29 em hemodiálise de manutenção [18 com hiperparatireoidismo grave (HD-SHPT) e 11 submetidos à paratireoidectomia (HD-PTX)]. Todos os pacientes foram submetidos à DXA e BIA. Resultados: A mediana da idade e do índice de massa corporal (IMC) foram de 49 anos e 25,6 kg/m2, respectivamente. Os pacientes exibiram baixo conteúdo mineral ósseo (CMO) medido pelo DXA, particularmente aqueles do grupo HD-SHPT. A maior discordância da medida do CMO entre DXA e BIA foi encontrada no grupo HD-SHPT (p = 0,004). Os fatores independentemente associados a essa discrepância na medida do CMO foram fosfato sérico (p = 0,003) e grupo de pacientes (p = 0,027), mesmo após ajustes para idade, IMC e sexo (r2 ajustado = 0,186). PTX atenuou essa diferença. Discussão: A BIA deve ser interpretada com cautela em pacientes com HPTS devido a uma perda de precisão, o que pode comprometer a interpretação da composição corporal.

Abstract Introduction: Body composition is critical for the evaluation of patients with Chronic Kidney Disease (CKD) and can be obtained from either multifrequency bioelectrical impedance analysis (BIA) or dual-energy absorptiometry (DXA). Although the discrepancy between the results obtained from both methods has already been described, reasons are unknown, and might be related to secondary hyperparathyroidism, which is associated with bone loss. Methods: We have evaluated 49 patients (25 males and 24 females): 20 with CKD not on dialysis and 29 on maintenance hemodialysis [18 with severe hyperparathyroidism (HD-SHPT) and 11 submitted to parathyroidectomy (HD-PTX)]. All patients underwent DXA and BIA. Results: The median age and body mass index (BMI) were 49 years and 25.6 kg/m2, respectively. Patients exhibited low bone mineral content (BMC) measured by DXA, particularly those from the HD-SHPT group. The largest BMC measurement disagreement between DXA and BIA was found in the HD-SHPT group (p=0.004). Factors independently associated with this discrepancy in BMC measurement were serum phosphate (p=0.003) and patient group (p=0.027), even after adjustments for age, BMI, and gender (adjusted r2=0.186). PTX attenuated this difference. Discussion: BIA should be interpreted with caution in patients with SHPT due to a loss of accuracy, which can compromise the interpretation of body composition.

Abstract Background: Modifiable cardiovascular risk factors (MCRFs), such as those related to aerobic capacity, muscle strength, physical activity, and body composition, have been poorly studied in Takayasu arteritis (TAK). Therefore, the aim of the study was to investigate MCRFs and their relationships with disease status and comorbidities among patients with TAK. Methods: A multicenter cross-sectional study was conducted between 2019 and 2020, in which 20 adult women with TAK were compared with 16 healthy controls matched by gender, age, and body mass index. The following parameters were analyzed: aerobic capacity by cardiopulmonary test; muscle function by timed-stands test, timed up-and-go test, and handgrip test; muscle strength by one-repetition maximum test and handgrip test; body composition by densitometry; physical activity and metabolic equivalent by IPAQ, quality of life by HAQ and SF-36; disease activity by ITAS2010 and NIH score; and presence of comorbidities. Results: Patients with TAK had a mean age of 41.5 (38.0-46.3) years, disease duration of 16.0 (9.5-20.0) years, and a mean BMI of 27.7±4.5 kg/m2. Three out of the 20 patients with TAK had active disease. Regarding comorbidities, 16 patients had systemic arterial hypertension, 11 had dyslipidemia, and two had type 2 diabetes mellitus, while the control group had no comorbidities. TAK had a significant reduction in aerobic capacity (absolute and relative VO2 peak), muscle strength in the lower limbs, increased visceral adipose tissue, waist-to-hip ratio, reduced walking capacity, decreased weekly metabolic equivalent, and quality of life (P< 0.05) as compared to controls. However, there were no correlations between these MCRFs parameters and disease activity. Conclusions: TAK show impairment in MCRFs; therefore, strategies able to improve MCRF should be considered in this disease.

OBJECTIVE: To assess the possible factors that influence sleep quality in adolescents with and without chronic immunosuppressive conditions quarantined during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: This cross-sectional study included 305 adolescents with chronic immunocompromised conditions and 82 healthy adolescents. Online surveys were completed, which included questions on socio-demographic data and self-rated healthcare routine during COVID-19 quarantine and the following validated questionnaires: the Pittsburgh Sleep Quality Index (PSQI), Pediatric Quality of Life Inventory 4.0 (PedsQL4.0), and Pediatric Outcome Data Collection Instrument (PODCI). RESULTS: The median current age [14 (10-18) vs. 15 (10-18) years, p=0.847] and frequency of female sex (62% vs. 58%, p=0.571) were similar in adolescents with chronic conditions compared with healthy adolescents. The frequency of poor sleep quality was similar in both groups (38% vs. 48%, p=0.118). Logistic regression analysis, including both healthy adolescents and adolescents with chronic conditions (n=387), demonstrated that self-reported increase in screen time (odds ratio [OR] 3.0; 95% confidence interval [CI] 1.3-6.8; p=0.008) and intrafamilial violence report (OR 2.1; 95% CI 1.2-3.5; p=0.008) were independently associated with poor sleep quality in these adolescents. However, the PODCI global function score was associated with a lower OR for poor sleep quality (OR 0.97; 95% CI 0.94-0.99; p=0.001). Further logistic regression, including only adolescents with chronic conditions (n=305), demonstrated that self-reported increase in screen time (OR 3.1; 95% CI 1.4-6.8; p=0.006) and intrafamilial violence report (OR 2.0; 95% CI 1.2-3.4; p=0.011) remained independently associated with poor quality of sleep, whereas a lower PODCI global function score was associated with a lower OR for sleep quality (OR 0.96; 95% CI 0.94-0.98; p<0.001). CONCLUSION: Self-reported increases in screen time and intrafamilial violence report impacted sleep quality in both healthy adolescents and those with chronic conditions. Decreased health-related quality of life was observed in adolescents with poor sleep quality.

OBJECTIVES: To prospectively evaluate demographic, anthropometric and health-related quality of life (HRQoL) in pediatric patients with laboratory-confirmed coronavirus disease 2019 (COVID-19) METHODS: This was a longitudinal observational study of surviving pediatric post-COVID-19 patients (n=53) and pediatric subjects without laboratory-confirmed COVID-19 included as controls (n=52) was performed. RESULTS: The median duration between COVID-19 diagnosis (n=53) and follow-up was 4.4 months (0.8-10.7). Twenty-three of 53 (43%) patients reported at least one persistent symptom at the longitudinal follow-up visit and 12/53 (23%) had long COVID-19, with at least one symptom lasting for >12 weeks. The most frequently reported symptoms at the longitudinal follow-up visit were headache (19%), severe recurrent headache (9%), tiredness (9%), dyspnea (8%), and concentration difficulty (4%). At the longitudinal follow-up visit, the frequencies of anemia (11% versus 0%, p=0.030), lymphopenia (42% versus 18%, p=0.020), C-reactive protein level of >30 mg/L (35% versus 0%, p=0.0001), and D-dimer level of >1000 ng/mL (43% versus 6%, p=0.0004) significantly reduced compared with baseline values. Chest X-ray abnormalities (11% versus 2%, p=0.178) and cardiac alterations on echocardiogram (33% versus 22%, p=0.462) were similar at both visits. Comparison of characteristic data between patients with COVID-19 at the longitudinal follow-up visit and controls showed similar age (p=0.962), proportion of male sex (p=0.907), ethnicity (p=0.566), family minimum monthly wage (p=0.664), body mass index (p=0.601), and pediatric pre-existing chronic conditions (p=1.000). The Pediatric Quality of Live Inventory 4.0 scores, median physical score (69 [0-100] versus 81 [34-100], p=0.012), and school score (60 [15-100] versus 70 [15-95], p=0.028) were significantly lower in pediatric patients with COVID-19 at the longitudinal follow-up visit than in controls. CONCLUSIONS: Pediatric patients with COVID-19 showed a longitudinal impact on HRQoL parameters, particularly in physical/school domains, reinforcing the need for a prospective multidisciplinary approach for these patients. These data highlight the importance of closer monitoring of children and adolescents by the clinical team after COVID-19.

Resumo Fundamento: Hiperatividade simpática de repouso e uma reativação parassimpática diminuída pós-exercício têm sido descritas em pacientes com insuficiência cardíaca (IC). No entanto, a associação dessas alterações autonômicas em pacientes com IC sarcopênicos ainda não são conhecidas. Objetivo: O objetivo deste estudo foi avaliar o impacto da modulação autonômica sobre sarcopenia em pacientes com IC do sexo masculino. Métodos: Foram estudados 116 pacientes com IC e fração de ejeção ventricular esquerda inferior a 40%. Todos os pacientes foram submetidos ao teste de exercício cardiopulmonar máximo. A frequência cardíaca máxima foi registrada, e o delta de recuperação da frequência cardíaca (∆RFC) foi avaliado no primeiro e no segundo minuto após o exercício. A atividade nervosa simpática muscular (ANSM) foi registrada por microneurografia. A Absorciometria Radiológica de Dupla Energia foi usada para medir composição cpororal, e a sarcopenia definida como a soma da massa muscular apendicular (MMA) dividida pela altura em metros ao quadrado e força da mão. Resultados: A sarcopenia foi identificada em 33 pacientes (28%). Os pacientes com sarcopenia apresentaram maior ANSM que aqueles sem sarcopenia - 47 (41-52) vs. 40 (34-48) impulsos (bursts)/min, p = 0,028). Pacientes sarcopênicos apresentaram ∆RFC mais baixo no primeiro [15 (10-21) vs. 22 (16-30) batimentos/min, p < 0,001) e no segundo [25 (19-39) vs. 35 (24-48) batimentos/min, p = 0,017) minuto que pacientes não sarcopênicos. Observou-se uma correlação positiva entre a MMA e a ANSM (r = -0,29; p = 0,003). Conclusão: Um desequilíbrio simpático-vagal parece estar associado com sarcopenia em pacientes com IC do sexo masculino. Esses resultados destacam a importância de uma abordagem terapêutica em pacientes com perda muscular e fluxo simpático periférico aumentado.

Abstract Background: Resting sympathetic hyperactivity and impaired parasympathetic reactivation after exercise have been described in patients with heart failure (HF). However, the association of these autonomic changes in patients with HF and sarcopenia is unknown. Objective: The aim of this study was to evaluate the impact of autonomic modulation on sarcopenia in male patients with HF. Methods: We enrolled 116 male patients with HF and left ventricular ejection fraction < 40%. All patients underwent a maximal cardiopulmonary exercise testing. Maximal heart rate was recorded and delta heart rate recovery (∆HRR) was assessed at 1st and 2nd minutes after exercise. Muscle sympathetic nerve activity (MSNA) was recorded by microneurography. Dual-energy X-ray absorptiometry was used to measure body composition and sarcopenia was defined by the sum of appendicular lean muscle mass (ALM) divided by height in meters squared and handgrip strength. Results: Sarcopenia was identified in 33 patients (28%). Patients with sarcopenia had higher MSNA than those without (47 [41-52] vs. 40 [34-48] bursts/min, p = 0.028). Sarcopenic patients showed lower ∆HRR at 1st (15 [10-21] vs. 22 [16-30] beats/min, p < 0.001) and 2nd min (25 [19-39] vs. 35 [24-48] beats/min, p = 0.017) than non-sarcopenic. There was a positive correlation between ALM and ∆HRR at 1st (r = 0.26, p = 0.008) and 2nd min (r = 0.25, p = 0.012). We observed a negative correlation between ALM and MSNA (r = -0.29, p = 0.003). Conclusion: Sympatho-vagal imbalance seems to be associated with sarcopenia in male patients with HF. These results highlight the importance of a therapeutic approach in patients with muscle wasting and increased peripheral sympathetic outflow.

Resumo Osteoporose, uma doença metabólica caracterizada por baixa massa óssea, deterioração da microarquitetura do tecido ósseo e aumento da suscetibilidade a fraturas, é comumente vista como um problema de saúde feminino. Essa visão tem fundamentos: em comparação com os homens as mulheres têm densidade mineral óssea menor, têm vida mais longa e perdem massa óssea mais rapidamente, principalmente após a menopausa, devido à diminuição acentuada dos níveis séricos de estrógeno. Entretanto, nos últimos 20 anos a osteoporose no homem tem sido reconhecida como um problema de saúde pública devido à ocorrência cada vez maior de fraturas por fragilidade. Cerca de 30% de todas as fraturas de quadril ocorrem em homens. Estudos recentes mostram que a probabilidade de fratura por fragilidade do quadril, vértebra ou punho em homens brancos após os 50 anos, pelo resto de suas vidas, situa-se em torno de 13%, 40% nas mulheres. Os homens apresentam perda de massa óssea e fraturas mais tardiamente do que as mulheres. Embora os homens mais idosos tenham maior risco de fratura, cerca de metade das fraturas de quadril ocorre antes dos 80 anos. A expectativa de vida tem aumentado para ambos os sexos no Brasil e em todo o mundo, porém em uma velocidade maior para homens do que para mulheres. Esta Diretriz foi baseada em uma revisão sistemática da literatura com relação a prevalência, etiologia, diagnóstico e tratamento da osteoporose em homens.

Abstract Osteoporosis, a metabolic disease characterized by low bone mass, deterioration of the bone tissue microarchitecture and increased susceptibility to fractures, is commonly regarded as a women's health problem. This point of view is based on the fact that compared with men, women have lower bone mineral density and longer lifespans and lose bone mass faster, especially after menopause, due to a marked decrease in serum estrogen levels. However, in the last 20 years, osteoporosis in men has become recognized as a public health problem due to the occurrence of an increasingly higher number of fragility fractures. Approximately 30% of all hip fractures occur in men. Recent studies show that the probability of fracture due to hip, vertebral or wrist fragility in Caucasian men older than fifty years, for the rest of their lives, is approximately 13% versus a 40% probability of fragility fractures in women. Men show bone mass loss and fractures later than women. Although older men have a higher risk of fracture, approximately half of all hip fractures occur before the age of 80. Life expectancy is increasing for both sexes in Brazil and worldwide, albeit at a higher rate for men than for women. This Guideline was based on a systematic review of the literature on the prevalence, etiology, diagnosis and treatment of osteoporosis in men.

RESUMO Objetivo: O objetivo deste estudo foi analisar a correlação entre os níveis de vitamina D e parâmetros clínicos, densidade mineral óssea (DMO), qualidade de vida (QV) e capilaroscopia periungueal (CPU) em pacientes com esclerose sistêmica difusa (ES). Métodos: Mensuraram-se os níveis séricos de 25-hidroxivitamina D (25OHD) de 38 pacientes do sexo feminino com ES difusa. No momento da inclusão, analisaram-se o envolvimento de órgãos, autoanticorpos, escore cutâneo de Rodnan modificado (ERM), Medsger Disease Severity Index (MDSI), índice de massa corporal (IMC), DMO, CPU, Short-Form-36 Questionnaire (SF-36) e Health Assessment Questionnaire (HAQ) por meio de uma entrevista padronizada, exame físico e avaliação de prontuário eletrônico. Resultados: A média do nível sérico de 25OHD foi de 20,66 ± 8,20 ng/mL. Dos pacientes, 11% tinham níveis de 25OHD ≤ 10 ng/mL, 50% ≤ 20 ng/mL e 87% ≤ 30 ng/mL. Os níveis séricos de vitamina D estiveram positivamente correlacionados com o IMC (r = 0,338, p = 0,038), DMO-fêmur total (r = 0,340, p = 0,037), DMO-colo femoral (r = 0,384, p = 0,017), SF-36-Vitalidade (r = 0,385, p = 0,017), SF-36-Aspecto social (r = 0,320, p = 0,050), SF-36-Aspecto emocional (r = 0,321, p = 0,049) e SF-36-Saúde mental (r = 0,531, p = 0,0006) e se correlacionaram negativamente com o HAQ-Alcance (r = –0,328, p = 0,044) e HAQ-força de preensão (r = –0,331, p = 0,042). Também foi observada uma correlação negativa com a CPU- desvascularização difusa (p = 0,029) e CPU-área avascular (p = 0,033). Conclusão: O presente estudo fornece evidências novas de que níveis baixos de 25OHD têm um impacto negativo sobre a qualidade de vida de pacientes com ES difusa e que são necessários mais estudos para definir se a suplementação de vitamina D pode melhorar a qualidade de vida relacionada com a saúde desses pacientes. A observação adicional de uma correlação com alterações graves na CPU sugere um possível papel da 25OHD no envolvimento vascular subjacente da ES.

ABSTRACT Objective: The aim of this study was to analyze the correlation of vitamin D levels with clinical parameters, bone mineral density (BMD), quality of life (QoL) and nailfold capillaroscopy (NC) in patients with diffuse systemic sclerosis (SSc). Methods: Thirty-eight female patients with diffuse SSc were analyzed regarding 25-hydroxyvitamin D (25OHD) serum levels. At inclusion, organ involvement, autoantibodies, modified Rodnan skin score (mRSS), Medsger Disease Severity Index (MDSI), body mass index (BMI), BMD, NC, Short-Form-36 Questionnaire (SF-36), and Health Assessment Questionnaire (HAQ), were performed through a standardized interview, physical examination and electronic chart review. Results: Mean 25OHD serum level was 20.66 ± 8.20 ng/mL. Eleven percent of the patients had 25OHD levels ≤10 ng/mL, 50% ≤20 ng/mL and 87% ≤30 ng/mL. Vitamin D serum levels were positively correlated with BMI (r = 0.338, p = 0.038), BMD-total femur (r = 0.340, p = 0.037), BMD-femoral neck (r = 0.384, p = 0.017), SF-36-Vitality (r = 0.385, p = 0.017), SF-36-Social Function (r = 0.320, p = 0.050), SF-36-Emotional Role (r = 0.321, p = 0.049) and SF-36-Mental Health (r = 0.531, p = 0.0006) and were negatively correlated with HAQ-Reach (r = −0.328, p = 0.044) and HAQ-Grip Strength (r = −0.331, p = 0.042). A negative correlation with NC-diffuse devascularization (p = 0.029) and NC-avascular area (p = 0.033) was also observed. Conclusion: The present study provides novel evidence demonstrating that low levels of 25OHD have a negative impact in diffuse SSc QoL and further studies are needed to define whether vitamin D supplementation can improve health related QoL in these patients. The additional observation of a correlation with severe NC alterations suggests a possible role of 25OHD in the underlying SSc vascular involvement.

RESUMO A tomografia computadorizada quantitativa periférica de alta resolução (HR-pQCT) é uma nova tecnologia disponível comercialmente há menos de 10 anos que permite a feitura de exames in vivo para a avaliação de parâmetros ósseos. A HR-pQCT avalia a forma, o número, o volume, a densidade, a conectividade e a separação das trabéculas; a densidade e a espessura do osso cortical e o volume e a densidade total, em alta definição, o que permite a construção digital da microarquitetura óssea adicionalmente. A aplicação de cálculos matemáticos aos dados capturados, método denominado elemento finito (FE), permite a estimativa das propriedades físicas do tecido e simula cargas suportadas de forma não invasiva. Desse modo, a HR-pQCT adquire simultaneamente dados antes fornecidos separadamente pela densitometria óssea, pela ressonância magnética e pela histomorfometria e agrega estimativas biomecânicas antes só possíveis em tecidos extraídos. A reprodutibilidade do método é satisfatória, com coeficientes de variação que raramente ultrapassam os 3%. Quanto à acurácia, os parâmetros apresentam de regular a boa concordância (r2= 0,37-0,97). A principal aplicação clínica é na quantificação e no monitoramento das doenças osteometabólicas, porque avalia de modo mais completo a resistência óssea e o risco de fratura. Na artrite reumatoide permite-se a aferição do número e do tamanho das erosões e dos cistos, além do espaço articular. Na osteoartrite é possível caracterizar as áreas edema-símile que guardam correlação com a degradação da cartilagem. Restritas ainda a um instrumento de pesquisa, dado o seu elevado custo, a alta resolução e a eficiência mostram-se como vantagens em relação aos métodos atualmente usados para a avaliação óssea, com um potencial para tornar-se uma importante ferramenta na prática clínica.

ABSTRACT High resolution peripheral quantitative computed tomography (HR-pQCT) is a new technology commercially available for less than 10 years that allows performing in vivo assessment of bone parameters. HR-pQCT assesses the trabecular thickness, trabecular separation, trabecular number and connectivity density and, in addition, cortical bone density and thickness and total bone volume and density in high-definition mode, which additionally allows obtaining digital constructs of bone microarchitecture. The application of mathematics to captured data, a method called finite element analysis (FEA), allows the estimation of the physical properties of the tissue, simulating supported loads in a non-invasive way. Thus, HR-pQCT simultaneously acquires data previously provided separately by dual energy x-ray absorptiometry (DXA), magnetic resonance imaging and histomorphometry, aggregating biomechanical estimates previously only possible in extracted tissues. This method has a satisfactory reproducibility, with coefficients of variation rarely exceeding 3%. Regarding accuracy, the method shows a fair to good agreement (r2 = 0.37-0.97). The main clinical application of this method is in the quantification and monitoring of metabolic bone disorders, more fully evaluating bone strength and fracture risk. In rheumatoid arthritis patients, this allows gauging the number and size of erosions and cysts, in addition to joint space. In osteoarthritis, it is possible to characterize the bone marrow edema-like areas that show a correlation with cartilage breakdown. Given its high cost, HR-pQCT is still a research tool, but the high resolution and efficiency of this method reveal advantages over the methods currently used for bone assessment, with a potential to become an important tool in clinical practice.

OBJECTIVES: The aim of this study was to investigate the impact of asymptomatic vertebral fractures on the quality of life in older women as part of the Sao Paulo Ageing & Health Study. METHODS: This study was a cross-sectional study with a random sample of 180 women 65 years of age or older with or without vertebral fractures. The Quality of Life Questionnaire of the European Foundation for Osteoporosis was administered to all subjects. Anthropometric data were obtained by physical examination, and the body mass index was calculated. Lateral thoracic and lumbar spine X-ray scans were obtained to identify asymptomatic vertebral fractures using a semi-quantitative method. RESULTS: Women with asymptomatic vertebral fractures had lower total scores [61.4(15.3) vs. 67.1(14.2), p = 0.03] and worse physical function domain scores [69.5(20.1) vs. 77.3(17.1), p = 0.02] for the Quality of Life Questionnaire of the European Foundation for Osteoporosis compared with women without fractures. The total score of this questionnaire was also worse in women classified as obese than in women classified as overweight or normal. High physical activity was related to a better total score for this questionnaire (p = 0.01). Likewise, lower physical function scores were observed in women with higher body mass index values (p<0.05) and lower physical activity levels (p,0.05). Generalized linear models with gamma distributions and logarithmic link functions, adjusted for age, showed that lower total scores and physical function domain scores for the Quality of Life Questionnaire of the European Foundation for Osteoporosis were related to a high body mass index, lower physical activity, and the presence of vertebral fractures (p<0.05). CONCLUSION: Vertebral fractures are associated with decreased quality of life mainly physical functioning in older community-dwelling women regardless of age, body mass index, and physical activity. Therefore, the results highlight the importance of preventing and controlling asymptomatic vertebral fractures to reduce their impact on quality of life among older women.