Dietary and nutrient patterns were identified using factor analysis and a food frequency questionnaire. Blood essential elements levels were measured using atomic absorption spectrometry. A fish-white meat dietary pattern rich in shellfish, deep water fish, white meat, freshwater fish, organ meat and fungi and algae was inversely associated with ADHD (p = 0.006). Further analysis found that a mineral-protein nutrient pattern rich in zinc, protein, phosphorus, selenium, calcium and riboflavin was inversely associated with ADHD (p = 0.014). Additionally, the blood zinc was also negatively related to ADHD (p = 0.003). In conclusion, the fish-white meat dietary pattern and mineral-protein nutrient pattern may have beneficial effects on ADHD in Chinese children, and blood zinc may be helpful in distinguishing ADHD in Chinese children.Dietary or nutrient patterns represent the combined effects of foods or nutrients, and elucidate efficaciously the impact of diet on diseases. Because the pharmacotherapy on attention deficit hyperactivity disorder (ADHD) was reported be associated with certain side effects, and the etiology of ADHD is multifactorial, this study investigated the association of dietary and nutrient patterns with the risk of ADHD. We conducted a case-control study with 592 Chinese children including ADHD ( Attention deficit hyperactivity disorder (ADHD), one of the most common childhood psychiatric disorders, is a worldwide public problem that is characterized by developmentally inappropriate levels of inattention, impulsivity, and hyperactivity ,2. This Based on current studies, diets that reduce the symptoms associated with ADHD include restricting or eliminating the detrimental dietary factors that are associated with the risk of ADHD and supplementing the beneficial dietary factors that protect against ADHD ,14,15,16et al. and Azadbakht et al. have examined unhealthy dietary patterns associated with ADHD in their cross-sectional studies [et al. reported that a Western-style dietary pattern consisting of a high intake of fat, refined sugars, and sodium and a low intake of fiber, folate, and omega-3 fatty acids was associated with increased odds of an ADHD diagnosis, whereas a healthy dietary pattern, with a high intake of fiber, folate, and omega-3 fatty acids, was not correlated with the diagnosis of ADHD [et al. studied the likely causal relationship between dietary patterns and ADHD using factor analysis and 24 h diet recall (24HR) interview based on a case-control study [Foods and nutrients are consumed in various characteristic combinations that synergistically influence the risks related to many diseases. Dietary or nutrient patterns represent a broader series of food and nutrient consumption that is more predictive of disease risk than individual foods or nutrients . In rece studies ,19. In t of ADHD . In Iranol study . The resol study . Howeverol study . Thus, tThe matched case-control study participants were consecutively recruited from children attending pediatric clinics for health care and ADHD assessment from the Jiangxi Provincial Children’s Hospital in Jiangxi Province, China. This hospital, which is the largest hospital that specifically treats children in Jiangxi province, serves children from all of the administrative districts within the province.The subjects with ADHD 10th revision of the International Statistical Classification of Diseases and Related Health Problems  were children of Chinese Han nationality who were aged 6–14 years at the time of the investigation and had a lifetime medical history that fulfilled the Diagnostic and Statistical Manual of Mental Disorders, 4th ed., revised Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV-R) criteria for ADHD [The non-ADHD control children were randomly selected from those receiving routine health care at the same clinics where the ADHD cases were diagnosed. The controls were given the same full diagnostic assessment as the ADHD cases and screened only for the absence of ADHD without exclusion of any other diagnosis except for the same exclusion criteria applied to ADHD cases. By the pair-matched design, each subject with ADHD and control set had the same sex and the same age (difference between birthdays was within six months).The face-to-face interviews were performed in the outpatient clinic by graduate students in epidemiology, and the ADHD diagnosis was made by experienced board-certified child psychiatrists. The design and conduct of the survey was performed according to the guidelines laid down in the Declaration of Helsinki, and all of the procedures involving human subjects/patients were approved by the Institutional Review Board of the First Affiliated Hospital of Nanchang University. Informed consent was obtained from the parents of all of the children before participation.2) based on weight and height measurements with the subjects wearing light clothes and no shoes, according to standard protocols by the World Health Organization (WHO) [The parents of the participating subjects with ADHD and controls were interviewed in person by the study personnel. All of the personnel were current graduate students in epidemiology. Each interviewer was trained in epidemiologic interviewing, dietary assessment, and anthropometry. All of the interviews with the parents of subjects with ADHD and controls were conducted by two individuals under similar conditions. The data were collected using a standardized and structured questionnaire by individuals who were blinded to the subject or control status of the participants. The data collected included demographic information and other relevant factors related to their children, including the family structure, home environment, socioeconomic status, maternal and paternal education, maternal age at childbirth, smoking behavior of the parents, and medical, obstetric, neuro-developmental, and educational histories of the children, as well as the dietary habits in the 12 months before diagnosis (ADHD-patient) or interview (control subjects). The body mass index (BMI) was calculated (kg/mon (WHO) .Dietary intake was assessed by a food frequency questionnaire (FFQ), which consisted of 144 food items that were commonly consumed by the Chinese children. All of the questionnaires used for data collection were designed by a panel of experts, including scientists in the fields of epidemiology and nutrition. For each food item, the parents were invited to indicate their children’s average frequency of consumption over the past year in terms of the specified serving size by checking one of nine frequency categories, which ranged from “almost never” to “≥6 times/day” . PhotogrThe reliability of the FFQ in this study was evaluated in a randomly chosen subgroup of 62 children by comparing nutrient consumption determined by responses on the FFQ on two occasions. The FFQ had a high reliability for nutrients. Mean value for intake of total energy and most nutrients assessed by the FFQ on two occasions were not statistically different. Energy-adjusted correlation coefficients for the principal macronutrients ranged from 0.38 for proteins to 0.65 for zinc. Comparative validity was determined by comparison with intakes estimated from the average of six non-consecutive 24 h dietary recalls. We found that most nutrients were moderately correlated  between these two methods after controlling for total energy intake. Overall, these data indicated that the FFQ provides reasonably valid measurements of average long-term dietary intake.Venous whole blood samples (2 mL/child) were collected from the cubital vein using a metal-free and heparinized vacuum tube. The concentrations of blood iron, zinc, calcium, copper and magnesium were measured using atomic absorption spectrometry . The detection limits for iron, zinc, calcium, copper and magnesium were 6.0 µg/L, 1.0 µg/L, 3.0 µg/L, 1.0 µg/L and 0.1 µg/L, respectively. The values were the means of four analyses of each sample. The quality control measures showed the inter-run coefficients of variation of 3.0%–5.0% for these elements.Sex and age are associated with the prevalence of ADHD, which was demonstrated in several epidemiologic studies ,27. To aAdditionally, we considered multiple covariates and potential confounders for the association of dietary patterns, nutrient patterns, blood elements and ADHD in our study. They were based on the established predictors of child behavioral problems ,28,29. Tt-tests (continuous variables) or paired χ2 tests  to compare the demographic characteristics and other ADHD risk factors between the subjects with ADHD and controls. Factor analysis was adopted to derive the major dietary patterns on the basis of the 28 food groups [We used paired d groups . To idend groups . Finallyd groups . The prod groups . The scod groups . The samThe conditional logistic regressions were used to evaluate the association between the dietary and nutrient patterns and ADHD. For each pattern, T1 was considered to be the reference. The univariate and multivariate analyses were applied to calculate the odds ratios (ORs) and their corresponding 95% confidence intervals (CIs). In the univariate analyses, the crude ORs were calculated without any adjustment in the first model. In the multivariate analyses, we made adjustments for the other potential confounding factors . All of the covariates were introduced using the forward stepwise method. To test for linear trends, the dietary pattern groups for each factor were treated as continuous variables. We also performed a conditional logistic regression analysis with a binary outcome of ADHD in relation to the blood element levels. In addition, the ORs and 95% CIs of ADHD for each blood element were then calculated as the risk for a change in the blood element level by one standard deviation (SD). Meanwhile, adjustments for other potential confounding factors were made.p < 0.05 was considered to be statistically significant.SPSS software  was used for all of the statistical analyses, and Of the 340 children with ADHD diagnosed in pediatric clinics, 11 (3.2%) did not meet the selection criteria for this study. Of the 329 eligible subjects, 33 (10.0%) were excluded because of refusal to participate or unreasonable energy intakes . Finally, a total of 296 ADHD subjects were retained in this analysis, including 248 boys and 48 girls. Additionally, 296 eligible age- (±6 months) and gender-matched controls were recruited from the same pediatric clinics.The demographics and other characteristics are shown in p trend = 0.003) and grain-bean dietary pattern (p trend = 0.018) . No association with ADHD was observed for any other dietary pattern  . With ad pattern .6, dietary fiber, magnesium, iron, potassium, vitamin A, vitamin E, thiamine, copper, niacin, choline and vitamin C, was labeled as the “vitamin-dietary fiber” nutrient pattern. Factor 3, with high loadings for zinc, protein, phosphorus, selenium, calcium and riboflavin, was labeled as the “mineral-protein” nutrient pattern. Factor 4, with high loadings for total fat, polyunsaturated fatty acids, saturated fatty acids, monounsaturated fatty acids and cholesterol, but low loadings for methionine, manganese, and copper, was labeled as the “fatty acid-cholesterol” nutrient pattern. Overall, the four nutrient patterns amounted to 65.72% of the variance in food intake. We analyzed the ORs (95% CIs) of tertiles of nutrient patterns and ADHD  was negatively associated with the risk of ADHD after adjusting for other potential confounding factors. However, the amino acid-carbohydrate, vitamin-dietary fiber and fatty acid-cholesterol nutrient patterns were not significantly associated with the risk of ADHD.Moreover, the nutrient patterns and factor loading scores are presented in and ADHD . The higp = 0.005; 95% CI for OR was 0.96–0.99). After an adjustment was made in model 2 for other potential confounding factors, inversely significant associations existed between the risk of ADHD and blood zinc in p = 0.008; 95% CI for OR was 0.96–0.99). In the fully adjusted model, one SD increase of blood zinc concentration was associated with an OR of 0.73 (95% CI 0.60–0.89) for ADHD. However, no relation was observed between blood iron, calcium, copper, or magnesium concentration and ADHD (p > 0.05).The associations between blood element  levels and ADHD were conducted using conditional logistic regression. The concentration of blood zinc was significantly inversely associated with the risk of ADHD, as shown in model 1 of In the present case-control study, we identified four major dietary patterns and four major nutrient patterns for Chinese children. A fish-white meat dietary pattern rich in shellfish, deep water fish, white meat, freshwater fish, fungi and algae and organ meat was inversely associated with ADHD. Further analysis found that a mineral-protein nutrient pattern rich in zinc, protein, phosphorus, selenium, calcium and riboflavin was inversely associated with ADHD. Additionally, the blood zinc was also negatively related to ADHD. To the best of our knowledge, this study, with 296 pairs of age- and gender-matched Chinese children with ADHD and controls, is the first to specifically identify the potential influence of nutrient patterns on the risk of ADHD based on the association between dietary patterns and ADHD.The diet pattern (including dietary pattern and nutrient pattern) is an aggregate variable that is derived from special statistical methods, which summarizes the food and nutrient intake to create a meaningful overall representation of a large and complex set of interrelated diet factors. Recently, diet pattern analysis has emerged in the field of nutritional epidemiology as an alternative and complementary approach for examining the relationship between diet and the risk of chronic diseases. Rather than considering individual foods or nutrients, diet patterns conceptually represent a broader picture of food and nutrient consumption and may thus be more predictive of disease risk than individual foods or nutrients . Moreoveet al. and ours, included vegetable, fresh fruit, fish, white meat, and whole grains [et al. and Azadbakht et al., included fast food, ice cream, sweets, snacks, and red meat [To date, three previous studies have examined the associations between dietary patterns and ADHD ,19,20. Tred meat ,19.vs. T1). This finding interestingly supported the relationship of fish-white meat pattern and ADHD, because the fish and white meat were abundant with zinc, selenium, calcium, phosphorus and purified protein [et al. and Azadbakht et al. also supported our finding on the opposite side [To further explore the relationship of dietary patterns and ADHD, a nutrient pattern analysis was conducted in our study. In addition, a mineral-protein nutrient pattern typified by the consumption of zinc, protein, phosphorus, selenium, riboflavin and calcium was associated with a 53%  decrease in the risk of ADHD . Although we adjusted for many such factors using statistical analysis, residual confounding was still unavoidable because of measurement errors and missing adjustments for several unmeasured factors. Second, the FFQs are known to contain a certain degree of measurement error although the FFQ used in our study has been previously validated. Third, the four major dietary patterns derived from our data explained only 32.5% of total variance, suggesting the existence of other dietary patterns. However, these values should be interpreted with caution because they depend heavily on the total number of variables used in the factor analysis . FinallyIn conclusion, our findings suggest that the consumption of a fish-white meat dietary pattern and a mineral-protein nutrient pattern may have beneficial effects on ADHD, and may be effective and practical methods to prevent or control ADHD in Chinese children. Additionally, blood zinc might be helpful to distinguish ADHD in Chinese children. Further prospective studies are required to confirm these findings.


Aim. Metabolic syndrome is characterized by a cluster of atherosclerotic cardiovascular risk factors. The cardioankle vascular index (CAVI) reflects arterial stiffness and may be used as an indicator of atherosclerotic cardiovascular disease. In this study, we investigated the association of CAVI with metabolic syndrome. Methods. A total of 1,144 adults were included in this study. We measured CAVIs and examined blood samples to identify metabolic syndrome according to WHO Asia Pacific criteria and NCEP-ATPIII criteria. AST, ALT, r-GTP, BUN, creatinine, high sensitivity C-reactive protein, and uric acid were also measured. Results. CAVI values were significantly higher in subjects with metabolic syndrome than those without metabolic syndrome and increased according to the number of metabolic syndrome components present. Subjects with high fasting blood sugar levels or high blood pressure showed high CAVI values. Multiple regression analysis showed that age, sex, diastolic blood pressure, and uric acid were independent predictors of CAVI. Conclusion. Subjects with metabolic syndrome had high CAVIs, which indicated arterial stiffness, and were closely associated with an increase in the number of metabolic risk factors. The individual risk factors for metabolic syndrome have the synergistic effect of elevating arterial stiffness in asymptomatic Korean population. Metabolic syndrome is an abnormal metabolic state caused by a combination of arteriosclerotic risk factors such as abdominal obesity, dyslipidemia, glucose intolerance, and hypertension and is related to insulin resistance . The natPulse wave velocity (PWV) can be measured easily in noninvasive ways and has been considered a predictor of cardiovascular disease, reflecting vascular injury and arterial stiffness , 6. AmonNakamura reported that among 109 male and female adults who had undergone coronary angiography there was a positive relationship between the number of blood vessels with coronary artery stenosis and CAVI and a meaningful correlation between the severity of coronary atherosclerosis and the increase of CAVI . It was There is one study that showed the association between metabolic syndrome and CAVI in Chinese population. But there is a distinct lack of research on the usefulness of CAVI as an indicator of arterial stiffness in Korean metabolic syndrome patients. Research is needed to determine whether CAVI can be used as a good early predictor of cardiovascular disease and whether there is a relationship between CAVI and risk factors for cardiovascular disorders in metabolic syndrome. Thus, in this study, we investigate the relationship between CAVI and metabolic syndrome in Korean men and women.From January 2011 to January 2012, 1,144 male and female adults who had undergone a complete physical examination at a hospital in Gyeonggi-do were recruited. Eight who had a history of cancer, heart disease, and peripheral vascular disease were excluded.This study was implemented in accordance with ethical and safety guidelines upon the approval of the Institutional Review Board in The Catholic University of Korea, St. Vincent's Hospital . The study was exempted from the written informed consents of participants because we reviewed the health screening data and medical record retrogradely. The IRBs approved this consent procedure.2). Waist circumference (WC) was measured in centimeters at the midsection from the lower rib to the upper crista iliaca, while subjects were standing with their feet 30 cm apart, exhaling comfortably. Blood pressure was measured with an automatic blood pressure monitor while subjects were seated after having rested for 20 minutes. In the morning after subjects had fasted overnight, blood samples were drawn from the brachial veins. Fasting plasma glucose (FPG), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), aspartate transaminase (AST), alanine transaminase (ALT), gamma-glutamyl transpeptidase (r-GTP), blood urea nitrogen (BUN), creatinine (Cr), high sensitivity C-reactive protein (hs-CRP), and uric acid (UA) were also measured.Weight and height were measured to one decimal place in kilograms and centimeters, respectively. Body mass index was calculated by dividing weight (kg) by the value of the square of height .CAVI was measured noninvasively using a Vasera VS-1000 system. While subjects were resting in the supine position, cuffs were wrapped around both their upper arms and ankles. Electrocardiographic electrodes were attached to the upper arms, and a microphone was placed on the sternal angle to measure blood pressure and record an electrocardiogram and a phonocardiogram. After around 5 minutes, volume waveforms and the other data were printed from an embedded printer. PWV was calculated by dividing the directly measured length from the heart to the artery of ankle joint by the sum of the arrival time interval of the brachial pulse wave and the pulse wave of the ankle joint and the time from the closing sound of the aortic valve to the notch of the brachial pulse wave. From this value, the values of the brachial systolic blood pressure (SBP) and diastolic blood pressure (DBP) were applied to the formula of the stiffness parameter Metabolic syndrome was defined according to the criteria suggested in the report of the NCEP-ATPIII in 2005 and the Asia Pacific criteria. These criteria include the presence of any three of the following five risk factors , 10.abdominal obesity: WC of 90 cm or greater in men and 85 cm or greater in women;TG: TG levels of 150 mg/dL (1.69 mmol/L) or greater or being on medicine to treat higher TG levels;HDL-cholesterol: <40 mg/dL (1.04 mmol/L) in men, <50 mg/dL (1.29 mmol/L) in women, or being on medicine to treat lower HDL-cholesterol;blood pressure: 130/85 mmHg or greater or being on medicine to treat hypertension;glucose: 100 mg/dL (6.1 mmol/L) or greater or being on medicine to treat hyperglycemia.Criteria of metabolic syndrome are as follows: t-test. We carried out analysis of covariance (ANCOVA) after adjusting for age in the association between CAVI and metabolic syndrome and performed multiple linear regression analysis to evaluate factors which affected CAVI. P < 0.05 was regarded as statistically significant.The data were analyzed using the Statistical Package for Social Sciences (SPSS) version 12.0 . The continuous variables in each of the two groups were compared using theP < 0.001 was regarded as statistically significant.Of the 1,144 subjects, 372 (32.7%) had metabolic syndrome, 770 (63.7%) did not have metabolic syndrome, and 507 (69%) were men. Subjects in the metabolic syndrome group were older and had greater BMIs, WCs, SBP, DBP, FPG, TG, TC, AST, ALT, Cr, hs-CRP, and UA levels but had lower HDL-C levels than subjects in the nonmetabolic syndrome group. The characteristics of subjects are shown in P = 0.04) than that of the nonmetabolic syndrome group . After analyzing the influence of the components of metabolic syndrome on CAVI, we found that subjects in the metabolic syndrome group whose SBP values were 130 mmHg or greater or whose DBP values were 85 mmHg or greater had higher CAVI values than subjects in the nonmetabolic syndrome group  = 18.180, P = 0.001).The average value of CAVI was 7.55 ± 0.96 in the metabolic syndrome group, which was significantly higher (P < 0.001), sex (P < 0.001), DBP (P = 0.04), and UA (P = 0.001) were independent predictors of CAVI (After performing multiple linear regression analysis, using risk factors for metabolic syndrome which can potentially influence CAVI, we found that age ( of CAVI .The risk factors for coronary artery disease include old age, dyslipidemia, hyperglycemia, obesity, and hypertension, among others . Except β theory and can be determined by measuring PWV and blood pressure. CAVI is not affected by blood pressure at the time of measurement and reflects arterial stiffness more precisely than brachial ankle PWV [PWV, as an index which reflects arterial stiffness and blood vessel injury, is a strong predictor of cardiovascular disease morbidity and mortality , 6. CAVInkle PWV . Thus, iThe study of Shirai et al. showed that, in adults aged 20 to 70 who received an annual health check and had no coronary risk factors, there was a direct association between CAVI and Age. CAVI increases with age almost linearly from 20 to 70 years in males and females. Also, CAVI of men is higher than that of women in almost all age groups . In thisIn this study, CAVI values were found to be greater in the metabolic syndrome group than in the control group and were highly significant even when adjusted for age and sex. Also, in the group whose subjects had at least one component of metabolic syndrome, compared with the group whose subjects did not have metabolic syndrome, CAVI was statistically significantly higher and increased linearly with the number of metabolic syndrome components. These results are consistent with the results of previous studies which investigated the relationship between CAVI and metabolic syndrome , 13. MetAmong the components of metabolic syndrome, the elevation of SBP or DBP had a significant relationship with the elevation of CAVI. After having examined these relationships through multiple linear regression analysis, we found that DBP was an independent predictor of CAVI. The study of Takaki et al. showed that, in adults aged 30 to 80 who had undergone coronary angiographies, there was no direct association between CAVI and SBP or DBP . The stuVarious hypotheses about the mechanism whereby metabolic syndrome influences arterial stiffness have been suggested. First, metabolic syndrome is associated with sympathetic nerve hyperactivity. The increase of tension in sympathetic nerves inhibits artery distensibility and increases the stiffness of blood vessels , 20. TheIn this study, increased FPG was among the metabolic syndrome components associated with a significant increase in CAVI. Ohnishi et al. reported that brachial ankle PWV increases with increasing FPG . SignifiOne interesting finding in this study was that UA was significantly elevated in the metabolic syndrome group and was an independent predictor of the elevation of CAVI. The increase of serum UA has a significant association with metabolic syndrome and is a risk factor for cardiovascular disease , 29. UA This study has a few limitations. First, since this study was cross-sectional, we could not deduce the temporal order of the onset of metabolic syndrome and the elevation of CAVI. Second, as patients who came to the health promotion center of a general hospital were targeted, there could have been a selection bias. Third, we lacked some information associated with metabolic syndrome and arteriosclerosis, such as that regarding smoking, drinking, exercise, and family history.Despite these limitations, this study contributes to the early assessment of cardiac disease by showing that metabolic syndrome and its components have a significant association with increased CAVI as a predictor of arterial stiffness in asymptomatic Korean population. In the future, a clinical trial will be needed to investigate whether CAVI decreases when metabolic syndrome components are improved, and a cohort study will be needed to investigate the relationship between CAVI and the onset of metabolic syndrome, to establish the risk of elevated CAVI in metabolic syndrome more clearly.


In the search of predictors of inadequate physical activity, an investigation was conducted into the association between multimorbidity and physical activity (PA). So far the sum of diseases used as a measure of multimorbidity reveals an inverse association. How specific combinations of chronic diseases are associated with PA remains unclear. The objective of this study is to identify clusters of multimorbidity that are associated with PA. Cross-sectional data of 3,386 patients from the 2003 wave of the Dutch cohort study SMILE were used. Ward's agglomerative hierarchical clustering was executed to establish multimorbidity clusters. Chi-square statistics were used to assess the association between clusters of chronic diseases and PA, measured in compliance with the Dutch PA guideline. The highest rate of PA guideline compliance was found in patients the majority of whom suffer from liver disease, back problems, rheumatoid arthritis, osteoarthritis, and inflammatory joint disease (62.4%). The lowest rate of PA guideline compliance was reported in patients with heart disease, respiratory disease, and diabetes mellitus (55.8%). Within the group of people with multimorbidity, those suffering from heart disease, respiratory disease, and/or diabetes mellitus may constitute a priority population as PA has proven to be effective in the prevention and cure of all three disorders. Multimorbidity, defined as the coexistence of two or more chronic diseases, is progressively more prevalent with age –3. PatieRegular physical activity (PA) has proven to be effective in the prevention and cure of chronic conditions . An invePrior work has shown an inverse relationship between the number of chronic diseases and physical activity. Yet, to our knowledge no study has assessed the association between specific disease clusters and physical activity. This study therefore goes beyond prior work in the field of multimorbidity and investigates which clusters of multiple chronic diseases are associated with PA in a large representative sample of older Dutch people above 55 years of age, measured in compliance with the Dutch PA guideline.This cross-sectional study is part of a dynamic prospective cohort study, the Study of Medical Information and Lifestyles in Eindhoven (SMILE), the Netherlands. The SMILE cohort study was performed between 2002 and 2010 and was a joint project between Maastricht University and the Eindhoven Corporation of Primary Health Care Centres (SGE), including nine centres representing 32 general practitioners. Data for the SMILE cohort study was collected in two ways: (1) information on morbidity, mortality, medication use, and healthcare facility utilisation was continuously registered using electronic medical records (EMRs) in the nine primary healthcare centres and (2) information on lifestyles and chronic diseases was collected by using annual self-administered paper questionnaires. Information on physical activity was collected annually in November. The self-reported chronic disease questionnaire was collected annually in May among all adults aged 55 years and older. The SMILE study protocol has been published  and apprn = 3,386).Registrees (12 years and older) of the participating healthcare centres were invited to participate in the overall study. All patients signed informed consent forms. Adult data (from patients aged 55 years and older) from 2003 was used in the present study since that year included the largest number of patients who completed both questionnaires  on at least five, or preferably all, days of the week , was theData about the level of physical activity came from the adult questionnaire and self-reported chronic diseases data was extracted from the 55+ questionnaire.Physical activity was measured by the “Short Questionnaire to Assess Health-Enhancing Physical Activity (SQUASH)” . PatientAn intensity score and a total activity score were allocated to all activities. Each activity was assigned a MET value using the Ainsworth compendium for physical activities, in which one MET is defined as the energy expenditure for sitting quietly . For eacN = 1,077) were incorporated in the data gathered from the completed self-reported chronic disease questionnaires. Two researchers, assisted by a medical specialist, separately assigned the diseases noted in the open question to the existing categories in the chronic disease questionnaire (JT).The presence or absence of 15 chronic diseases was measured using the self-reported chronic disease questionnaire. This questionnaire is based on a medical screening questionnaire of the Dutch Association of General Practitioners (LHV) . PatientCluster analysis algorithms assume that there are no missing values. Solutions are developed if values are missing; however, these are only technically valid if the values are missing completely at random (MCAR). In the self-reported chronic disease questionnaires, missing values are observed ranging from 592 (17.5%) for epilepsy to 818 (24.2%) for inflammatory joint disease. We assume that these missing values are not completely random (MNAR) [K-means clustering, were used.The aim of the analysis was to identify clusters of chronic diseases based on their relative similarity or dissimilarity (distance). Cluster analysis is used because it best fits the aim of our study, namely, to identify meaningful groups of patients with chronic diseases. Because there is not a one-and-only valid approach to establish groups of patients in relation to chronic diseases, the two most frequently applied forms of clustering, namely, Ward's agglomerative hierarchical clustering and F statistic were used to determine the appropriate number of clusters. The pseudo-F statistic  is the total sum of squares, SS(W) is the within-group sum of squares, and Both the general adult questionnaire and the additional 55+ questionnaire were returned by 3,386 patients.Fifty-three per cent were female and the average age of patients was 68 years (range: 55–95 years). The average length and bodyweight of patients were 1.70 m (range: 1.41–1.99 m) and 75 kg (range: 40 kg–185 kg), respectively. Osteoarthritis of knees, hips, and hands was the most prevalent disease (23%). The prevalence of heart disease or myocardial infarction was approximately twice as high in males as in females . In comparison, musculoskeletal disorders like inflammatory joint disease (7.2% versus 10.4%), rheumatoid arthritis (2.7% versus 6.0%), and osteoarthritis of knees, hips, and hands (18.2% versus 27.4%) were less prevalent among females compared with males . PrevaleTwo-Cluster Solution. For Ward's agglomerative hierarchical clustering, the stepwise agglomerative coefficients and the pseudo-F statistic suggested a two-cluster solution being most feasible  being 2177.8 and pseudo-F being 1318.4.feasible . K-meansOf the patients who have severe bowel disease 96.4% are included in cluster one. Of the patients with severe kidney disease or cancer also the majority is involved in cluster one . Similarly of the patients with epilepsy (65.0%), migraine (71.5%), stroke, or stroke-related complaints (87.1%) and persistent injury from an accident at home, in sports, school/work, or traffic (80.3%) the majority is a member of the first cluster. In other words, cluster one is the dominant cluster for severe bowel disease, severe kidney disease, cancer, epilepsy, migraine, stroke, and persistent injury from an accident.Cluster two is dominated by respiratory disease, heart disease, liver diseases, diabetes mellitus, inflammatory joint disease, rheumatoid arthritis, osteoarthritis, and severe back problems. Of the patients with chronic bronchitis, emphysema and asthma 90.0% are in cluster two. Of the patients with myocardial infarction 89.0% are in cluster two and 81.3% of the patients suffering from liver disease or cirrhosis are included in the second cluster. The majority of the patients with diabetes mellitus (87.4%), inflammatory joint disease (92.1%), rheumatoid arthritis (92.0%), osteoarthritis of knees, hips, and hands (84.7%), and severe back problems, hernia, sciatica, or osteoarthritis (82.3%) are also member of cluster two.A resumed description of the two clusters is also presented in Two-Cluster Solution. Of the total of 3,386 patients, 60.8%  complied with the Dutch physical activity (PA) guideline. Of the people belonging to cluster one, 61.8% complied with the Dutch PA guideline, and, of the people belonging to cluster two, 59.4% complied with this guideline. The proportion of respondents that complied with the Dutch PA guideline was not significantly different between the two clusters .Although statistically a two-cluster solution was identified as being most optimal, the aim of this study was to discover the combination of diseases that not only cluster but also interact with physical activity. To explore whether further branching of clusters might provide information regarding the relationship between clusters and physical activity, analysis proceeded with a Ward's three-cluster solution.Three-Cluster Solution. The results of Ward's three-cluster solution are presented in Three-Cluster Solution. The proportion of adults that comply with the Dutch PA guideline is highest in cluster two (62.4%), followed by cluster one (61.8%) and finally cluster three (55.8%). The relationship between the three-disease clusters and PA guideline compliance was statistically significant .Ward's four-cluster solution led to a cluster containing a single disease (heart disease). First, because a single disease does not represent a multimorbidity cluster and hence does not fit the aim of the present study, clustering was stopped after Ward's three-cluster solution. Second, all other clusters presented in the four-cluster solution were comparable which supports our decision to stick to the three-cluster solution .The aim of the present study was to assess the relationship between multimorbidity clusters and compliance with the Dutch physical activity (PA) guideline. The two-cluster solution showed no significant association with PA guideline compliance. Further exploration revealed a significant relationship between three multimorbidity clusters and physical activity. The highest rate of PA guideline compliance (62.4%) was found in cluster two, of which the majority of patients had liver disease, back problems, rheumatoid arthritis, osteoarthritis, and inflammatory joint disease. The lowest rate of PA guideline compliance (55.8%) was reported in patients with heart disease, respiratory disease, and diabetes mellitus. Compared with the average Dutch proportion of older adults , feThe main limitation of the present study is its cross-sectional design, which prevents the establishment of any causal inference. The quantity of missing values ranging from 17.5% (epilepsy) to 24.2% (inflammatory joint disease) in the self-reported chronic disease questionnaire formed a limitation. To obtain as much information as possible, we interpreted missing values as absence of the disease, and this may have caused the disease burden in this population to have been underestimated. As a control, patient characteristics were checked, revealing comparable results for patients with and without missing data on chronic diseases. Furthermore, the presence of chronic diseases was measured via a self-reported questionnaire, and one may well wonder whether a patient is able to report this information adequately. Informed consent issues prevented us from being able to check the self-reported data against data registered in electronic medical records (EMRs). Nevertheless, previous research on the SMILE cohort identified a high level of agreement between self-reports of chronic diseases and information from EMRs . The higThe first analysis revealed two clusters for which no association with PA was detected. The clusters found were broad (representing at least seven diseases) and diverse in terms of types of the diseases embodied in each cluster. As previous research had shown an inverse relationship between multimorbidity and PA, the question of which specific disease combinations are associated with PA remained unanswered. Therefore, the exploration was continued with the three-cluster solution and we found that only the initial second cluster had branched out into two new ones. The results of the three-cluster solution showed that cluster one remained unchanged and that heart disease, respiratory disease, and diabetes had separated from the original cluster two to form a third cluster. The relationship between the three-cluster solution and PA was significant. The third cluster had the lowest proportion of people who were compliant with the Dutch PA guideline. The highest proportion of people who were compliant was found in cluster two, which had a compliance proportion similar to cluster one.As people in cluster three showed lower activity levels on average, it might be worthwhile to examine the diseases found in this cluster, namely, heart disease, respiratory disease, and diabetes mellitus. It may not be surprising that this combination of diseases formed a separate cluster given that they are highly prevalent diseases that have been shown to be interrelated. For example, Howard et al.  estimateThe fact that the diseases in cluster three showed the lowest proportion of PA guideline compliance could be expected. The inverse relationship between cardiovascular disease, respiratory disease and diabetes mellitus, as individual disorders, and physical activity has been studied extensively –27.p = 0.004). Although in the present study a cluster analysis was performed because contentwise it fitted our primary aim best, other data reduction methods and procedures are expected to reveal comparable groups of patients [To our knowledge, only four studies have until now investigated the relationship between multimorbidity and PA , 28, 29.patients , 32.In conclusion, this study adds to our knowledge of the relationship between multimorbidity and physical activity. In addition to the inverse relationship of the number of chronic diseases and PA, the present study showed that the cluster of patients with cardiovascular disease, respiratory disease, and/or diabetes type II reported the lowest physical activity levels. Belonging to a specific cluster of diseases does make a difference and it is important for general practitioners and physiotherapists to help especially patients with cardiovascular disease, respiratory disease, and/or diabetes to initiate and maintain appropriate physical activity levels. It seems worthwhile to further explore the relationship between multimorbidity clusters and outcomes like physical activity, because it helps to deliver more targeted and effective care for patients.


The aural cavity magnetic susceptibility artifact leads to significant echo planar imaging (EPI) signal dropout in rat deep brain that limits acquisition of functional connectivity fcMRI data. In this study, we provide a method that recovers much of the EPI signal in deep brain. Needle puncture introduction of a liquid-phase fluorocarbon into the middle ear allows acquisition of rat fcMRI data without signal dropout. We demonstrate that with seeds chosen from previously unavailable areas, including the amygdala and the insular cortex, we are able to acquire large scale networks, including the limbic system. This tool allows EPI-based neuroscience and pharmaceutical research in rat brain using fcMRI that was previously not feasible. Resting-state functional connectivity MRI (fcMRI) has been extensively studied using echo planar imaging (EPI) based methods . FunctioThe magnetic susceptibility effect is composed of two types, variations of the resonance field that are intravoxel and that are intervoxel in and near the region of interest. Intravoxel effects are reduced by use of short echo times and small voxels, with the voxel dimension in the slice encoding direction most significant. Intravoxel dephasing results in signal loss that cannot be recovered. Intervoxel susceptibility effects result in image distortion, which can be corrected by producing a magnetic field map.The rat ear can be divided into three parts: external ear, middle ear, and inner ear. The inner ear is composed of bony and membranous labyrinths and is filled with fluid. The susceptibility effect is likely not caused by the inner ear. The middle ear and the external ear are both filled with air. Together they form a two compartment structure that is separated by the tympanic membrane.2 molecule. It seems to be more troublesome than bone, and the effects of air–tissue interfaces do not seem to be ameliorated by intervening bone, although quantitative data are lacking. We have equipment in place that allows relative, but not absolute, measurements of the susceptibility of materials. The fluorocarbon Fomblin Y is nearly identical in these measurements to Teflon. In the experiments reported here, this liquid-phase fluorocarbon seems to match the magnetic susceptibility of brain tissue. It is introduced into the ear canal to displace air and to match the magnetic susceptibility of brain tissue.Air is paramagnetic because of the magnetic properties of the OIn a previous study, toothpaste was used to fill the external ear canal in an attempt to correct this problem . The EPIAnimals were anesthetized under isoflurane inhalation or dexmedetomidine infusion during the study. Animals were euthanized with saturated potassium chloride under isoflurane anesthesia after experiment.The study protocol was reviewed and approved by the Institutional Animal Care and Use Committee (IACUC) of the Medical College of Wisconsin, AUA00001177. The Medical College of Wisconsin is a leader in the ethical and humane use of animals for research. MCW, through IACUC, takes responsibility for the humane care and use of laboratory animals. All protocols are reviewed by this committee, and investigators must comply with the "Principles for the Utilization and Care of Vertebrate Animals", the provisions of the Animal Welfare Act, and other applicable laws and regulations.A tympanostomy tube, also known as an ear tube, is used in a clinical procedure to treat chronic otitis and recurrent acute otitis. After treatment, the tympanic membrane heals within a short period of time. The application of this surgical procedure in the rat followed by injection of a liquid-phase fluorocarbon into the middle ear demonstrates that the signal dropout caused by the magnetic susceptibility of air in the ear can be removed. It is hypothesized that this technique could be applied in survival animal models since the liquid can be easily removed from the ear canal after scanning .Five male Sprague-Dawley  rats weighing between 300–450 g were used in this study. The left ear drum was penetrated and Fomblin Y (Sigma-Aldrich) was injected into the middle and external ear of all rats. We call this procedure “middle ear Fomblin filling,” MEFF. The right external ear canals of these five rats were filled either with gel toothpaste or Fomblin Y, as indicated, and the tympanic membranes were kept intact. All rats were given free access to food and water and were kept in a home cage with 12 hours of day/night light alternation for at least one week before the experiment.2/N2 during surgery. Isoflurane was tapered off during the fcMRI portion of the study, and a continuous subcutaneous infusion of DexDomitor (0.1 mg/kg/hr) was used for maintenance of sedation. The rat was placed on a heated bench and supplied with 30–70% O2/N2. During fcMRI acquisition, pulse oximetry , temperature, respiration rate, and inspired/expired O2 and CO2  were monitored  and maintained within normal physiologic ranges.General surgical protocol: All protocols and procedures were approved and carried out under the guidance of the MCW Institutional Animal Care and Use Committee. Dexmedetomidine hydrochloride  has been used successfully in fcMRI studies and was used here ,14. The 0 axis and approximately with the cephalo-caudal axis of the rat brain. The central X-Y plane of the transmit coil was 3 mm in front of the ear canals. Signal acquisition was achieved using our self-designed 10 mm receive coil with low-noise-amplifier (LNA) displaced about 2 cm from the RF coil. The center of this receive coil was centered in the transmit coil. The coupling circuit uses an American Technical Ceramics  800R series, high-Q, non-magnetic capacitor, a Rogers RT/duroid 5880 low-loss circuit board with 1-ounce copper trace on both sides, and a WanTCom  WMA9RA LNA, with an input impedance of 1.5 Ohms and an overall gain of 28 dB.Each rat was placed on a custom-designed cradle fabricated with G-10 fiberglass material, which has a magnetic susceptibility similar to air. A 9.4 Tesla MRI system with a 31 cm horizontal bore  was used for scanning. A Bruker linear transmit-coil (T10325) was used with the axis of the coil coincident with the BTE = 18.76 ms, TR = 2 s, matrix size 96 × 96, FOV = 3.84 cm, BW = 300 kHz, 20 overscan lines, number of repetitions = 110, 10 contiguous interleaved 1 mm slices. (2) half k-space TE = 10.78 ms, TR = 2 s, matrix size 96 × 96, FOV = 3.84 cm, BW = 300 kHz, 20 overscan lines, number of repetitions = 110, 10 contiguous interleaved 1 mm slices. And (3), parameters used in our previous study [TE = 10.78 ms, TR = 2 s, matrix 128 x 128, BW = 400 kHz, slice thickness = 200 microns. The third set of parameters was used only for high resolution EPI. A RARE anatomical image was acquired before EPI scans with a 256 × 256 matrix, TE = 12.5 ms, TR = 2.5 s, and the same slice geometry as the EPI sequence.A combined symmetrical RT-shim and self-shielded gradient system (B-GA 12S RT) was used to improve magnetic field homogeneity. High order shimming was performed before scans. In order to conform to resolution levels used in most research, three sets of parameters were used. (1) Full k-space, single-shot gradient-echo EPI. p-value for fcMRI results was set at 0.05.Data processing was performed using analysis of functional neuroimages (AFNI) software . Motion Toothpaste has been used as a material to fill the external ear canal in an attempt to reduce the susceptibility artifact. A possible alternative way to reduce the EPI signal loss in the deep brain area is the use of the partial k-space sequence to reduce the echo time. We have demonstrated that we are able to eliminate much of the EPI signal loss in the deep brain, especially around the insular cortex and amygdala areas. It is interesting to demonstrate the application of this technique in an actual neuroscience study. Elimination of signal dropout that arises from intravoxel dephasing in rat fcMRI studies is essential for neuroscience research. Due to the anatomical properties of the rat skull, EPI signal drop-out in deep brain areas is very common and affects many rat fMRI and fcMRI studies. EPI signal loss in this area is widely hypothesized to be a susceptibility artifact that is caused by the air–bone–brain tissue interface ,18. WithFomblin Y is a proton-free liquid material that has been widely used in diffusion tensor imaging. It is inert with no known hazards or toxicity . The magA desirable first step in use of the MEFF method is to shim the brain as well as possible using available current shims. The commercial Bruker current shims in the scanner used for the work presented here are of high quality and are adjusted automatically. More advanced shim strategies are described in the research literature , 20, 21.TE by applying the partial k-space sequence [Researchers have tried many ways to minimize the ear canal susceptibility artifact, including filling with toothpaste , reducinsequence ,22,24,25sequence . Even atsequence . These pThis paper introduces the method of fcMRI for validation of strategies for improving the magnetic field homogeneity over the rat brain. Voxels in gray matter in brain are connected in various ways that can be as close as the adjacent voxel or as distant as the extent of the whole brain. Thus the study of fcMRI in deep brain regions provides both the motivation for the present study and the means to evaluate the success of the MEFF method in reduction of intravoxel dephasing.Due to the difficulties in EPI coverage in deep brain areas, there are no publications that used fcMRI in the deep brain regions of in vivo neuroscience and pharmaceutical research.In order to demonstrate the efficacy of our MEFF procedure, we performed fcMRI analysis with seeds chosen from both insular cortex and amygdala areas based on the brain atlas. As part of the limbic system, the amygdala plays an important role in memory, learning, and emotion. In this study, when seeds from the left amygdala were used for analysis Figs  and 5A, The amygdala has rich anatomical projections with widespread subcortical and cortical regions. Because BOLD functional connectivity does not differentiate between afferent and efferent connections, these are considered together here. Also, the amygdala consists of at least six larger nuclei that, for brevity, will not be distinguished here. The subcortical connections of the amygdala include those with the basal forebrain, such as the nucleus Basalis, substantia innominata, septal preoptic area and the hypothalamus; the thalamus, especially medial, mediodorsal, and ventral nuclei, the striatum including the caudate putamen and n. accumbens; and numerous nuclei of the brainstem, the largest of which is with the parabrachial nucleus. The cortical connections of the amygdala are mainly with visual, auditory and somatosensory sensory association, polysensory cortices, the insula, the medial and orbitofrontal (limbic) frontal regions, and the hippocampus. In the work described here, connectivity from the amygdala seed region was revealed in the insular cortex, perioptic nucleus, medial forebrain, cingulate and hippocampus as indicated by red arrows in The insular cortex is a functionally heterogeneous region with subregions that integrate gustatory, visceral, vestibular, and nociceptive/thermosensitive sensory inputs together with somatic and limbic information. Accordingly, the cortical afferent connections of the insula are widespread, including entrorhinal, perirhinal, orbitofrontal, and cingulate projections, gustatory, olfactory and vestibular cortical inputs, as well as primary and higher-order somatosensory and auditory association fibers. The insula receives thalamic projections from ventromedial and various ventral posterior nuclei and the amygdala . ConnectThis study provides a basic tool for rat fcMRI studies. With it, EPI coverage can be extended to deep brain structures. However, magnetic susceptibility effects in other regions of the brain may require other procedures for reduction or elimination,


Decellularized homografts have shown auspicious early results when used for pulmonary valve replacement (PVR) in congenital heart disease. The first clinical application in children was performed in 2002, initially using pre-seeding with endogenous progenitor cells. Since 2005, only non-seeded, fresh decellularized allografts have been implanted after spontaneous recellularization was observed by several groups.A matched comparison of decellularized fresh pulmonary homografts (DPHs) implanted for PVR with cryopreserved pulmonary homografts (CHs) and bovine jugular vein conduits (BJVs) was conducted. Patients’ age at implantation, the type of congenital malformation, number of previous cardiac operations and number of previous PVRs were considered for matching purposes, using an updated contemporary registry of right ventricular outflow tract conduits .P = 0.01) and 84.3% for BJV (P= 0.01); the rate of freedom from explantation and peak trans-conduit gradient ≥50 mmHg was 86% for DPH, 64% for CH (n.s.) and 49% for BJV (P < 0.001); the rate of freedom from infective endocarditis (IE) was 100% for DPH, 97.3 ± 1.9% within the matched CH patients (P = 0.2) and 94.3 ± 2.8% for BJV patients (P = 0.06). DPH valve annulus diameters converged towards normal Z-values throughout the observation period, in contrast to other valve prostheses (BJV).A total of 131 DPHs were implanted for PVR in the period from January 2005 to September 2015. Of the 131, 38 were implanted within prospective trials on DPH from October 2014 onwards and were therefore not analysed within this study. A total of 93 DPH patients  formed the study cohort and were matched to 93 CH and 93 BJV patients. The mean age at DPH implantation was 15.8 ± 10.21 years  and the mean DPH diameter was 23.9 mm . There was 100% follow-up for DPH, including 905 examinations with a mean follow-up of 4.59 ± 2.76 years , amounting to 427.27 patient-years in total . Tetralogy-of-Fallot was the most frequent malformation . At 10 years, the rate of freedom of explantation was 100% for DPH, 84.2% for CH (Mid-term results of DPH for PVR confirm earlier results of reduced re-operation rates compared with CH and BJV. However, long-term animal models have yet to deliver satisfactory results, due to the lack of mechanical stability of the totally artificial matrices, leading to early failure of valvular function [The possibility of applying artificial tissue-engineered heart valves would solve many unmet clinical demands, such as the permanent availability of different sizes and lengths. These concepts have shown good results in the technical implementation of valved polymeric conduit production and have successfully been used for function .All tissue-engineering concepts currently in use in the clinic are based on the decellularization of biological scaffolds, such as xenogeneic and allogeneic heart valves, some approaches with and some without pre-seeding with stem cells . Many diet al. have developed protocols for the decellularization of donated human heart valves, which avoid the need for cryopreservation and thus minimize risk for the resulting valve scaffold. The first clinical implantations for PVR were performed in 2002, initially with a Trypsin/EDTA decellularization technique and pre-seeding of endothelial progenitor cells in a dynamic bioreactor system. The two paediatric patients were carefully monitored and showed very promising early results [Haverich  results .The clinical use of fresh decellularized allografts continued in 2005 using a modified decellularization detergent-based protocol without pre-seeding of stem cells after several groups observed spontaneous recellularization, including recellularization in senescent animal models .In 2011, we published early data on the use of these decellularized fresh pulmonary homografts (DPHs) in children and adolescents in direct comparison with bovine jugular vein conduits (BJVs) and cryopreserved conventional homografts (CHs), the two most widely used PVR alternatives. The findings of this study suggested improved freedom from re-operation and superior haemodynamics using DPHs . The immwww.pei.de, ESPOIR PV PEI.G.11634.01.1). Within the present study, we provide an update on the clinical results obtained using fresh, DPHs for PVR, again in comparison with the bovine jugular vein conduits and the cryopreserved conventional homografts.The clinical use of DPHs over the last 4 years has increasingly mirrored a real-life scenario, which was further accelerated by formal approval of DPHs by the competent authorities in 2013  for PVR. The study was approved by the Medical Ethics Committee of the Ministry of Health in Moldova and by the institutional Ethics Committee of Hannover Medical School, Germany.Patients from the Cardiac Surgery Center, Chisinau, Moldova and from Hannover Medical School, Hannover, Germany who underwent surgery during the period from January 2005 to September 2015 were enrolled in regular follow-up examinations. All patients were examined, including clinical and functional examinations , after surgery, at 6 months and at 12 months, and then every 12 months. Clinical follow-up included a regular physical examination of the patients . Echocardiographic evaluation  was performed according the current guidelines of the European Association of Cardiovascular Imaging.http://www.kinderkardiologie.org/leitlinien/).The indication for PVR was confirmed in consultation between paediatric cardiologists and cardiothoracic surgeons in accordance with the current guidelines of the German Society for Pediatric Cardiology . Initially, intermittent cold crystalloid or blood cardioplegia was used with a change to beating-heart surgery over the past 4 years. In all cases, the right ventricular outflow tract (RVOT) was reconstructed with an interposition of the DPH, with a continuous suture for the proximal as well as for the distal suture lines. After surgery, aspirin therapy was administered to patients over a period of 3–6 months.Degeneration was defined as a maximal peak gradient over any part of the conduit of 50 mmHg or more and/or at least moderate regurgitation .Each DPH patient was matched to one patient who received a BJV (Contegra®) for PVR and to one patient with a conventional cryopreserved homograft (CH). Patients were chosen from an updated contemporary registry of right ventricular outflow tract conduits (RVOT Conduit Registry) with over 2300 conduits included and a total patient follow-up of over 12 000 patient-years, which has been used for contemporary analysis of CH and BJV results . Data wiPatient matching was performed on the basis of the patient's age at implantation, followed by diagnosis and number of previous operations, as well as the number of previous PVRs. A total of 538 BJVs and 694 CHs were identified within the RVOT Conduit Registry, which were available for matching. Age was considered the most critical aspect in growing patients, especially in infants, and less important in adults.et al. [Summaries of the numerical data are given as means and standard deviation. For comparisons of data with skew distribution, we used the Mann–Whitney U-test for non-paired samples. Time-related events such as freedom from explantation or other degeneration threshold values were evaluated according to Kaplan–Meier, including numbers at risk at 0, 5 and 10 years, as well as freedom-from-event rates at 0, 5 and 10 years, with their 95% confidence limits. Differences are described with pairwise probability value indications derived from the log-rank test, unless otherwise indicated. We are aware of the limitations of applying a Kaplan–Meier analysis to our data, which was developed for terminal, irreversible events such as death or explantation, and not for potentially reversible events, such as an occasionally higher gradient that might decrease by the next examination. To reflect the clinical reality in such cases, i.e. to illustrate the proportion of explanted, well-functioning and dysfunctional grafts at the various examination intervals, we modified the statistical techniques recommended by Akins et al. . The samet al. .Illustrations for the development of gradients or insufficiency over time were obtained by considering the first appearance of a peak gradient  or at least moderate insufficiency as terminal events, with the risk of a certain margin of error that could occur by overestimating or underestimating the parameters. However, because this error would then occur in all three types of conduits assessed, and because large variations of these parameters in the course of a single patient are rare, we felt that this method was sufficient for the purposes of the analysis.Pulmonary valve annulus measurements were converted to age and body size-dependent Z-scores for DPH and BJV patients, according to the approach proposed by W. Berdau . Interpolation lines (Lowess fit) were calculated for Z-value groups  that included conduits with ±1 Z-value with respect to the indicated value (e.g. 0 = −1 to +1). Z-values of groups were calculated for the size at implantation and are displayed over time according echocardiographic measurements. The variation between size at implantation and first echocardiographic measurements explains offset differences in the respective groups.A limited number of annulus diameters for CHs over the period of 10 years disabled the calculation of Z-value developments for CHs; data for BJVs were available from a large European trial .SPSS 23  was used for the analyses; a probability value of 0.05 or less was considered statistically significant.www.espoir-clinicaltrial.eu) at seven clinical sites  and two DPHs were implanted in the framework of a clinical study in Osaka, Japan. These results will be published elsewhere.A total of 131 DPHs were implanted for PVR in the period from January 2005 to September 2015. Of these, 36 DPHs have been implanted within a prospective European clinical trial on DPHs, which has been running since October 2014  and in Hannover (n = 75). These 93 patients  formed the study cohort for a matched comparison with CHs and BJVs , and the mean DPH diameter was 23.9 mm . There was 100% follow-up in DPHs, including 905 examinations with a mean follow-up of 4.59 ± 2.76 years, amounting to a total of 427.27 patient-years. Tetralogy-of-Fallot was the most frequent malformation (50.5%). Details of the three study groups are summarized in Table In total, there have been two deaths in DPH patients, both valve-unrelated. One 18-year old patient died in Moldova 11 months postoperatively due to a suspected mesenteric infarction resulting from cardiac arrhythmia. The intact valve was explanted and histological results published . The othPVR with DPH has proved to be safe. One patient at Hannover Medical School required re-operation (1.1%) on the same day due to a haematoma leading to graft compression. Aside from this case, no other perioperative complications such as DPH rupture or dislodgement were observed.P= 0.01 vs DPH) and 84.3% for BJV (P = 0.01 vs DPH).Figure All CH and BJV explants were performed due to haemodynamic relevant degeneration and not on the occasion of another procedure.P = 0.2 vs DPH) and 94.3 ± 2.8% for BJV patients (P = 0.06 vs DPH). For details, see Fig. At 10 years, the rate of freedom of death was 98% for DPH, 90% within the matched CH patients (n.s.) and 96% within the matched BJV patients (n.s.). At 10 years, freedom from infective endocarditis (IE) was 100% for DPH, 97.3 ± 1.9% within the matched CH patients (Figure In Fig. A comparative study of any option for PVR is hampered by the diversity of the patients treated. Young patients are far more likely to exhibit accelerated degeneration of the biological grafts used in this age group , 16, 17.We have chosen a matched comparison with the two most widely used grafts for paediatric PVR -BJV and CH- to evaluate the mid-term results of DPHs. This matching was based on the factors described above and therefore allowed a valid comparison of the results. DPHs showed superior results to CHs and BJVs with respect to freedom from degeneration and subsequently freedom from explantation. However, a number of DPH grafts nevertheless exhibited stenosis and/or regurgitation within the study period. This was caused predominantly by distal anastomosis stenosis, which is not an unusual diagnosis in patients with multiple pulmonary artery procedures. This is an important finding as it demonstrates the susceptibility of DPHs to such problems and underlines the importance of adequate surgical implantation for decellularized grafts, which, due their softness, are also prone to valvular regurgitation when implanted suboptimally. Within the 10-year period, valvular gradients, however, did not increase with DPHs, a result that was not achieved by CHs and BJVs.Two other groups have also reported on their results using DPHs for PVR and have demonstrated superior results to those obtained using conventional cryopreserved homografts , 22. EveIE is a severe threat for any heart valve prosthesis. Although endocarditis of the pulmonary valve is rarer than in left-sided valves, the impact on the patient can be substantial. CHs, when used for PVR, have demonstrated a rate of freedom from IE of 97.3% at 10 years in a recent comparison with BJVs . We obseDPHs showed, in contrast to BJVs, normal Z-values over a period of up to 10 years. Growth potential is one of the unique features of DPHs and our mid-term results confirm the adaptive growth described in earlier reports .However, there are no data, either clinical or preclinical, which provide an insight in the amount of recellularization in re-do settings after one or multiple thoracotomies. It seems apparent that rapid and thorough recellularization is less likely in the setting of severe scarring around the graft. Laminar flow across the outflow tract is a further prerequisite for sufficient colonization, as recellularization from the luminal side is also important, e.g. for cusps. Mechanical alteration, e.g. due to moderate graft distortion, not only may impede immediate valvular competence of the soft cusps of decellularized homografts, but also is important for long-term function and growth potential, as long-term turbulence will have adverse effects even on native semilunar valves. Future analysis will need to assess the growth potential of DPHs with respect to such factors on the basis of more implantations.Findings are necessarily limited by the number of DPHs implanted so far. However, prospective European-wide multicentre trials on the use of DPHs for pulmonary and aortic valve replacement have been initiated, which will provide further data, and the follow-up of DPH patients is ongoing.Limitations are also present by the matching process itself, which will not allow a 100% perfect matching of patients given the low numbers and variance in congenital heart disease. Within the RVOT Registry, there is slight imbalance regarding the implantation periods of DPHs and CHs, which is explained by the preferential use of DPHs in recent years at our institution and the limited number of available homografts. As there have been no new milestone achievements in allograft cryopreservation within the past years and as CH results are in line with the literature, we do not consider this to be a significant limitation.Data within the Registry originates from 7 experienced international centres, which may introduce bias by different re-operation algorithms. On the other hand, the Registry is minimizing centre effects by its unique number of available RVOT conduits.The lack of histological data resulting from the lack of DPH explantations to date, albeit in itself a positive result, presents a limitation for the evaluation of the recellularization potential of DPHs in humans.Mid-term outcomes of decellularized fresh pulmonary homografts used for PVR confirm earlier results of reduced re-operation rates compared with the current gold standard CH and BJVs. For future investigations, more data, especially on smaller grafts and recellularization conditions, are required, together with long-term performance monitoring, to conduct a more detailed evaluation.European Union's Seventh Framework Programme for Research, Technological Development and Demonstration under Grant Agreement No. 278453. Funding to pay the Open Access publication charges for this article was provided by the European Union's Seventh Framework Programme for Research, Technological Development and Demonstration under Grant Agreement No. 278453.This study was supported by a grant from the Conflict of interest: A. Haverich holds shares in corlife oHG, a company for the future processing of decellularized allografts, equivalent to those used in this study.


Despite the importance of body composition in athletes, reference sex- and sport-specific body composition data are lacking. We aim to develop reference values for body composition and anthropometric measurements in athletes.th, 25th, 50th, 75th, and 95th) were calculated for each measured value, stratified by sex and sport. Because sample sizes within a sport were often very low for some outcomes, the percentiles were estimated using a parametric, empirical Bayesian framework that allowed sharing information across sports.Body weight and height were measured in 898 athletes , anthropometric variables were assessed in 798 athletes , and in 481 athletes  with dual-energy X-ray absorptiometry (DXA). A total of 21 different sports were represented. Reference percentiles  and regional  bone mineral content, bone mineral density, absolute and percentage fat mass, fat-free mass, and lean soft tissue. Additionally, we derived reference percentiles for height-normalized indexes by dividing fat mass, fat-free mass, and appendicular lean soft tissue by height squared. We also derived sex- and sport-specific reference percentiles for the following anthropometry outcomes: weight, height, body mass index, sum of skinfold thicknesses , circumferences , and muscle circumferences .These reference percentiles will be a helpful tool for sports professionals, in both clinical and field settings, for body composition assessment in athletes. Assessment of body composition in athletes may help to optimize competitive performance and monitor the success of training regimens and thus is of considerable interest to sports professionals.Body composition can be organized according to a comprehensive model that consists of five levels of increasing complexity: I, atomic; II, molecular; III, cellular; IV, tissue-system; and V, whole-body The whole-body level of body composition characterizes body size and configuration, which is often described by anthropometric measures such as body weight, skinfold thicknesses, circumferences, and body mass index (BMI) among others. On the other hand, the molecular level consists of six main components: water, lipid, protein, carbohydrates, bone minerals, and soft tissue minerals. Several models ranging from two to six components can be created at this level of analysis.Reference values for DXA results have been developed for North Americans aged 8 to 85 years old by use of the NHANES dataset.All subjects and their parents or guardians were informed about the possible risks of the investigation before giving written informed consent to participate. All procedures were approved by the ethics committee of the Faculty of Human Kinetics, Technical University of Lisbon, and were conducted in accordance with the declaration of Helsinki for human studies of the World Medical Association. With the use of a cross-sectional design, body weight and height were measured in 898 athletes , anthropometric variables (skinfolds and circumferences) were assessed in 798 athletes , and 481 athletes  were evaluated with DXA during the in-season period. From these athletes, a total of 381  were assessed for both measurements, whereas anthropometric or DXA measures were only obtained for the remaining participants. The sample included athletes involved in a total of 21 sports. In Athletes involved in this study were subject to the following inclusion criteria: 1) in at least Tanner stage V  were used to assess reliability between two certified anthropometrists for skinfolds and circumferences for five active male subjects.The subjects came to the laboratory after an overnight fast (12 h fast), refraining from vigorous exercise at least 15 h, no caffeine and alcohol during the preceding 24 h, and consuming a normal evening meal the night before. Athletes underwent a whole-body DXA scan according to the procedures recommended by the manufacturer on a Hologic Explorer-W fan-beam densitometer . The equipment measures the attenuation of X-rays pulsed between 70 and 140 kV synchronously with the line frequency for each pixel of the scanned image. According to the protocol described by the manufacturer, a step phantom with six fields of acrylic and aluminium of varying thicknesses and known absorptive properties was scanned to serve as an external standard for the analysis of different tissue components. For athletes who were taller than the scan area, we used a validated procedure that consisted of the sum of a head and a trunk plus limbs scans. 2), absolute FM (kg), percentage FM (%FM), FFM (kg), and LST (kg). With the exception of BMD, the remaining variables were also presented for predefined subregions, including trunk, appendicular (arms+legs), and subtotal (whole body minus the head) regions. Additionally, from these measures the following variables were calculated: fat mass index (FMI) = FM/height2 (kg/m2), fat-free mass index (FFMI) = FFM/height2 (kg/m2), and appendicular lean soft tissue index (ALSTI) = ALST/height2 (kg/m2).The DXA measurements included whole-body measurements of BMC (g), bone mineral density ] Analyses were performed to complete three tasks: 1) estimate the reference percentiles for each outcome, stratified by sex and sport; 2) test whether the mean for each outcome differed by sex, stratified by sport; and 3) within each outcome, identify sports for which the mean value differed from the others (if any), stratified by sex.Because the sample sizes were very low in many of the outcome/sex/sport combinations, the reference percentiles were estimated through a parametric, empirical Bayesian framework that allowed the sharing of information across sports to augment our inference whenever we had at least two athletes' values. Within a given sex and sport, the athletes' outcome values were assumed to follow a normal (Gaussian) distribution that could be characterized through its mean and precision (inverse variance). If the mean and precision were known, all quantiles followed immediately from the normal assumption. We note that in some cases, raw outcome values were decidedly non-normal, in that they were not unimodal and were skewed strongly to the right and thus were not even roughly symmetric about the mean. Therefore, for BMD, FM, %FM, FMI, FFMI, and ALSTI, raw values were log transformed before running the approach for all subjects and then transformed back afterward, allowing us to gain unimodality and rough symmetry about the mean while maintaining the original units for all results.The sport-specific means and variances were modelled as arising from a normal-gamma, which serves as the prior and forms a conjugate family with our observational model. The hyperparameters of the prior were informed empirically through maximum-likelihood by using all athletes' data for this outcome, restricted by sex. Once this was done, joint posterior distributions for the mean and precision were generated for every sport, giving rise to point estimates and 95% joint confidence regions for the mean and precision, which in turn were used to calculate simultaneous 95% confidence intervals for the reference percentiles of interest.th, 25th, 50th, 75th, and 95th were presented for all sex/sport subsamples with n≥8)Percentiles  for the main outcome variables were calculated with IBM SPSS Statistics version 21.0, 2012 . Normality was tested by using the Shapiro-Wilk test. Sex comparisons were performed with unpaired t-tests or the non-parametric equivalent, the Mann-Whitney U test. Comparisons across sports were made by sex by using the Kruskal-Wallis test with pairwise comparisons performed by using the Dunn test. For both sex and sport comparisons, the p-values presented are nominal, .th, 25th, 50th, 75th, and 95th percentiles.The variables derived from the DXA and anthropometry measures are listed in Descriptive statistics for the main anthropometry and DXA variables are presented in Despite the recognized importance of body composition for athletic performance th, 25th, 50th, 75th, and 90th percentiles for total (whole-body scan) and regional  body composition, including measures of BMD, BMC, absolute and percentage FM, FFM, and LST. Additionally, we also presented reference percentiles for height-normalized indexes such as BMI by dividing FM, FFM, and ALST by height squared. This approach has been suggested to allow comparisons among individuals;th percentile is 8.0% (95% CI: 3.3–11.7%), the estimate for the 25th percentile is 12.9% (95% CI: 9.7–15.7%), and the estimate for the 50th percentile is 16.3% (95% CI: 14.2–18.5%). Thus, the male handball player falls in the bottom half of the distribution but is not in the lowest 5% of that distribution; we estimate that his FM measurement is at about the 25th percentile for his sport.DXA is a widespread method for the assessment of the athletic population because it permits the acquisition of both regional and total body composition without the need for costly or scarce medical imaging techniques.3 for FFM density but observed deviations from this constant may occur.Athletes as a rule have a lower %FM than do nonathletes of the same chronologic age.2 (ALSTI) has been suggested as a proxy index for sarcopenia.It has been shown that athletes have a larger FFM than do nonathletes. Much of these differences may be related to an increased skeletal muscle mass.Another advantage of using DXA in the athletic population is its ability to assess BMD. The female athlete triad syndrome (FTS) position of the American College of Sports Medicine (ACSM) states that BMD should be assessed with DXA whenever the athlete presents a history of stress fractures or fractures from minimal trauma.Body composition disturbances are an important issue in sports medicine. A position statement under the auspices of the IOC Medical Commission has acknowledged this concern and recommends that skinfolds or DXA are used to monitor changes in body composition with interventions that seek to induce weight loss or change body composition in athletes. Despite its advantages, however, DXA may not be practical for field assessment. Furthermore, caution is necessary when using this method on multiple occasions, perhaps no more than four times per year,appSKF, ∑trunkSKF, ∑armSKF, and ∑legSKF) and body circumferences , we were able to reduce errors by avoiding assumptions that may not be valid in the athletic population. In this regard, Ackland et al. Inconsistency exists when using anthropometry to estimate molecular body composition compartments, particularly in the athletic population, because the equations rely on assumptions that may not be valid in athletes.Although circumferences are not often used to assess body composition in the athletic population, it seems likely that muscle circumferences may be a useful anthropometric tool as a representation of skeletal muscle mass.The DXA reference values presented in this study are only comparable with those derived by use of the Hologic fan beam DXA scanner (software version 12.4 or higher). Another limitation of this investigation is that owing to the small sample size in each sport. The empirical Bayesian framework we employed allows us to ‘share’ information across sports whenever there are at least two individuals with recorded outcome measurements for a given sport. The benefit accrued from that communication strongly depends on the nature of the values for the other sports as well as the number of individuals measured for that specific sport. It may be helpful for the reader to think of any given calculation as a weighted estimate between the information available for a given sport and the other sports, with the weight for the latter depending on how consistent their values are across sports, ranging from the high single digits down to less than a tenth of a person. Therefore, if there are many individuals measured for a given sport  their information will dominate that of the other sports. Conversely, estimates for sports with low sample sizes will be strongly influenced by the others. For this reason, we do not present confidence intervals and reference values for estimates when n<8. Additionally, we were not able to present position-specific reference percentiles for each body composition outcome. It is important to reinforce that the “athletics” sport comprised only sprinters, hurdlers, and jumpers (long and triple jump). Finally, ethnic variation should also be considered as a limitation of this study given that variation exists in body proportions and composition.This study provides reference body composition percentiles for athletes by sex and sport. Sports professionals will benefit from using these reference percentiles for assessing and classifying body composition in athletes. We used DXA to derive total and regional body composition reference values. In addition, given their applicability in the field setting, we also used anthropometric methods  to develop reference percentiles for whole-body composition. These reference values should be helpful in the evaluation of athletes from different sports regarding not only performance but also other health-related criteria and to establish directions for future research.File S1Anthropometry variables percentiles by sport and sex.(PDF)Click here for additional data file.File S2Dual Energy X-ray Absorptiometry variables percentiles by sport and sex.(PDF)Click here for additional data file.