Numerical simulation of the electron beam distribution in tissueequivalent materials using GEANT4

The numerical model of the electron beam dose distribution in ABS and HIPS plastics was developed. The calculation results were compared with experimental data of depth dose distribution of electron beam in water phantom for applicability estimation of these polymer materials for the imitation of biological tissues

Predicting the need for renal replacement therapy using a vascular occlusion test and tissue oxygen saturation in patients in the early phase of multiorgan dysfunction syndrome

Background: Acute kidney injury (AKI) is associated with an increased mortality in critically ill patients, especially in patients with multiorgan dysfunction syndrome (MODS). In daily clinical practice, the grading of AKI follows the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. In most cases, a relevant delay occurs frequently between the onset of AKI and detectable changes in creatinine levels as well as clinical symptoms. The aim of the present study was to examine whether a near infrared spectroscopy (NIRS)-based, non-invasive ischemia–reperfusion test (vascular occlusion test (VOT)) together with unprovoked (under resting conditions) tissue oxygen saturation (StO 2 ) measurements, contain prognostic information in the early stage of MODS regarding the developing need for renal replacement therapy (RRT). Methods: Within a period of 18 months, patients at the medical intensive care unit of a tertiary university hospital with newly developed MODS (≤24 h after diagnosis, APACHE II score ≥20) were included in our study. The VOT occlusion slope (OS) and recovery slope (RS) were recorded in addition to unprovoked StO 2 . StO 2 was determined non-invasively in the area of the thenar muscles using a bedside NIRS device. The VOT was carried out by inflating a blood pressure cuff on the upper arm. AKI stages were determined by the changes in creatinine levels, urinary output, and/or the need for RRT according to KDIGO. Results: 56 patients with MODS were included in the study (aged 62.5 ± 14.4 years, 40 men and 16 women, APACHE II score 34.5 ± 6.4). Incidences of the different AKI stages were: no AKI, 16.1% ( n = 9); AKI stage I, 19.6% ( n = 11); AKI stage II, 25% ( n = 14); AKI stage III, 39.3% ( n = 22). Thus, 39.3% of the patients ( n = 22) developed the need for renal replacement therapy (AKI stage III). These patients had a significantly higher mortality over 28 days (RRT, 72% ( n = 16/22) vs. no RRT, 44% ( n = 15/34); p = 0.03). The mean unprovoked StO 2 of all patients at baseline was 81.7 ± 11.1%, and did not differ between patients with or without the need for RRT. Patients with RRT showed significantly weaker negative values of the OS (−9.1 ± 3.7 vs. −11.7 ± 4.1%/min, p = 0.01) and lower values for the RS (1.7 ± 0.9 vs. 2.3 ± 1.6%/s, p = 0.02) compared to non-dialysis patients. Consistent with these results, weaker negative values of the OS were found in higher AKI stages (no AKI, −12.7 ± 4.1%/min; AKI stage I, −11.5 ± 3.0%/min; AKI stage II, −11.1 ± 3.3%/min; AKI stage III, −9.1 ± 3.7%/min; p = 0.021). Unprovoked StO 2 did not contain prognostic information regarding the AKI stages. Conclusions: The weaker negative values of the VOT parameter OS are associated with an increased risk of developing AKI and RRT, and increased mortality in the early phase of MODS, while unprovoked StO 2 does not contain prognostic information in that regard

Further evaluation of plasma sphingomyelin levels as a risk factor for coronary artery disease

BACKGROUND: Sphingomyelin (SM) is the major phospholipid in cell membranes and in lipoproteins. In human plasma, SM is mainly found in atherogenic lipoproteins; thus, high levels of SM may promote atherogenesis. METHODS: We investigated in a median follow up of 6.0 years the association of SM with the incidence of a combined endpoint (myocardial infarction and cardiovascular death) in stable and unstable patients, and its relation to other marker of atherosclerosis in 1,102 patients with angiographically documented CAD and 444 healthy controls. RESULTS AND DISCUSSION: Logistic regression analysis showed that SM categorized by median was associated with an elevated risk for CAD (HR 3.2, 95%CI 2.5–4.0, p < 0.05). SM levels were correlated with apoB (r = 0.34) and triglyceride levels (r = 0.31). In patients with stable angina (n = 614), SM categorized by median was not related to incidence of a combined endpoint (cardiovascular death and myocardial infarction) (p = 0.844 by Log-rank test). However, in patients with acute coronary syndrome (n = 488), elevated SM was related to the combined endpoint (p < 0.05 by Log-rank test), also in a multivariate Cox regression analysis including potential confounders (HR 1.8, 95%CI 1.0–3.3, p < 0.05). CONCLUSION: The results of our study reveal that 1) human plasma SM levels are a risk factor for CAD; 2) the pro-atherogenic property of plasma SM might be related to metabolism of apoB-containing or triglyceride-rich lipoproteins; and 3) plasma SM levels are a predictor for outcome of patients with acute coronary syndrome

Impact of QRS misclassifications on heart-rate-variability parameters (results from the CARLA cohort study)

Background Heart rate variability (HRV), an important marker of autonomic nervous system activity, is usually determined from electrocardiogram (ECG) recordings corrected for extrasystoles and artifacts. Especially in large population-based studies, computer-based algorithms are used to determine RR intervals. The Modular ECG Analysis System MEANS is a widely used tool, especially in large studies. The aim of this study was therefore to evaluate MEANS for its ability to detect non-sinus ECG beats and artifacts and to compare HRV parameters in relation to ECG processing. Additionally, we analyzed how ECG processing affects the statistical association of HRV with cardiovascular disease (CVD) risk factors. Methods 20-min ECGs from 1,674 subjects of the population-based CARLA study were available for HRV analysis. All ECGs were processed with the ECG computer program MEANS. A reference standard was established by experienced clinicians who visually inspected the MEANS-processed ECGs and reclassified beats if necessary. HRV parameters were calculated for 5-minute segments selected from the original 20-minute ECG. The effects of misclassified typified normal beats on i) HRV calculation and ii) the associations of CVD risk factors (sex, age, diabetes, myocardial infarction) with HRV were modeled using linear regression. Results Compared to the reference standard, MEANS correctly classified 99% of all beats. The averaged sensitivity of MEANS across all ECGs to detect non-sinus beats was 76% [95% CI: 74.1;78.5], but for supraventricular extrasystoles detection sensitivity dropped to 38% [95% CI: 36.8;38.5]. Time-domain parameters were less affected by false sinus beats than frequency parameters. Compared to the reference standard, MEANS resulted in a higher SDNN on average (mean absolute difference 1.4ms [95% CI: 1.0;1.7], relative 4.9%). Other HRV parameters were also overestimated as well (between 6.5 and 29%). The effect estimates for the association of CVD risk factors with HRV did not differ between the editing methods.</p

Impact of QRS misclassifications on heart-rate-variability parameters (results from the CARLA cohort study)

Background Heart rate variability (HRV), an important marker of autonomic nervous system activity, is usually determined from electrocardiogram (ECG) recordings corrected for extrasystoles and artifacts. Especially in large population-based studies, computer-based algorithms are used to determine RR intervals. The Modular ECG Analysis System MEANS is a widely used tool, especially in large studies. The aim of this study was therefore to evaluate MEANS for its ability to detect non-sinus ECG beats and artifacts and to compare HRV parameters in relation to ECG processing. Additionally, we analyzed how ECG processing affects the statistical association of HRV with cardiovascular disease (CVD) risk factors. Methods 20-min ECGs from 1,674 subjects of the population-based CARLA study were available for HRV analysis. All ECGs were processed with the ECG computer program MEANS. A reference standard was established by experienced clinicians who visually inspected the MEANS-processed ECGs and reclassified beats if necessary. HRV parameters were calculated for 5-minute segments selected from the original 20-minute ECG. The effects of misclassified typified normal beats on i) HRV calculation and ii) the associations of CVD risk factors (sex, age, diabetes, myocardial infarction) with HRV were modeled using linear regression. Results Compared to the reference standard, MEANS correctly classified 99% of all beats. The averaged sensitivity of MEANS across all ECGs to detect non-sinus beats was 76% [95% CI: 74.1;78.5], but for supraventricular extrasystoles detection sensitivity dropped to 38% [95% CI: 36.8;38.5]. Time-domain parameters were less affected by false sinus beats than frequency parameters. Compared to the reference standard, MEANS resulted in a higher SDNN on average (mean absolute difference 1.4ms [95% CI: 1.0;1.7], relative 4.9%). Other HRV parameters were also overestimated as well (between 6.5 and 29%). The effect estimates for the association of CVD risk factors with HRV did not differ between the editing methods.</p

Serum Thyrotropin Concentrations Are Not Associated with the Ankle-Brachial Index: Results from Three Population-Based Studies

Background: There is only limited data on the potential association between thyroid dysfunction and peripheral arterial disease (PAD). Objective: The aim of our study was to investigate the potential association of thyroid function, as defined by serum concentrations of the clinically used primary thyroid function marker thyrotropin [i.e. thyroid-stimulating hormone (TSH)] and 3,5-diiodothyronine (3,5-T2), with the ankle-brachial index (ABI) as a marker of PAD. Methods: We used data from 5,818 individuals from three cross-sectional population-based studies conducted in Northeast (SHIP-2 and SHIP-TREND) and Central Germany (CARLA). Measurement of serum TSH concentrations was conducted in one central laboratory for all three studies. In a randomly selected subpopulation of 750 individuals of SHIP-TREND, serum 3,5-T2 concentrations were measured with a recently developed immunoassay. ABI was measured either by a hand-held Doppler ultrasound using the Huntleigh Dopplex D900 or palpatorily by the OMRON HEM-705CP device. Results: Serum TSH concentrations were not significantly associated with ABI values in any of the three studies. Likewise, groups of individuals with a TSH 2 concentrations did not reveal consistent significant associations with the ABI. No sex-specific associations were detected. Conclusions: The results of our study do not substantiate evidence for an association between thyroid function and PAD, but further studies are needed to investigate the associations of overt forms of thyroid dysfunction with PAD

Inflammation and prolonged QT time: Results from the Cardiovascular Disease, Living and Ageing in Halle (CARLA) study

Background: Previous research found an association of CRP with QT time in population based samples. Even more, there is evidence of a substantial involvement of the tumor necrosis factor-alpha system in the pathophysiology of cardiac arrhythmia, while the role of Interleukin 6 remains inconclusive. Objective: To determine the association between inflammation with an abnormally prolonged QT-time (APQT) in men and women of the elderly general population. Methods: Data descend from the baseline examination of the prospective, population-based Cardiovascular Disease, Living and Ageing in Halle (CARLA) Study. After exclusion of subjects with atrial fibrillation and missing ECG recording the final study cohort consisted of 919 men and 797 women. Blood parameters of inflammation were the soluble TNF-Receptor 1 (sTNF-R1), the high-sensitive C-reactive protein (hsCRP), and Interleukin 6 (IL-6). In accordance with major cardiologic societies we defined an APQT above a QT time of 460 ms in women and 450 ms in men. Effect sizes and the corresponding 95% confidence intervals (CI) were estimated by performing multiple linear and logistic regression analyses including the analysis of sex differences by interaction terms. Results: After covariate adjustment we found an odds ratio (OR) of 1.89 (95% CI: 1.13, 3.17) per 1000 pg/mL increase of sTNF-R1 in women, and 0.74 (95% CI: 0.48, 1.15) in men. In the covariate adjusted linear regression sTNF-R1 was again positively associated with QT time in women (5.75 ms per 1000 pg/mL, 95% CI: 1.32, 10.18), but not in men. Taking possible confounders into account IL-6 and hsCRP were not significantly related to APQT in both sexes. Conclusion: Our findings from cross-sectional analyses give evidence for an involvement of TNF-alpha in the pathology of APQT in women

which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study

Objective To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. Methods Data of 10 258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. Results Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups (<65 vs ≥65 years). Conclusions We found stronger associations between anthropometric markers that reflect abdominal obesity (ie, WC and WHtR) and incident T2DM than for BMI and weight. The use of these measurements in risk prediction should be encouraged

Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study

Objective: To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. Methods: Data of 10 258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. Results: Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups