Effects of balloon angioplasty and stent implantation on intrarenal echo-Doppler velocimetric indices

Effects of balloon angioplasty and stent implantation on intrarenal echo-Doppler velocimetric indices. This study was aimed at examining whether four intrarenal echo-Doppler velocimetric indices (pulsatility and resistive indices, acceleration and acceleration time) can be useful for assessing the effects of renal artery dilation obtained with either angioplasty or stent implantation. Echo-Doppler studies were performed in 63 hypertensive patients with 68 renal artery stenoses (39 atherosclerotic and 29 fibromuscular) prior to and within five days after the dilation procedures (55 angioplasties, 13 stent implantations), which resulted in an average reduction of arterial narrowing from 79% to 20%. In 24 patients, the velocimetric indices were also examined in relationship to the venoarterial differences of plasma renin activity and of angiotensin II across the stenotic kidneys. We found that after dilation the values of the four indices had returned within the normal range in all but three arteries (one false negative for resistive index and two for acceleration time). However, decrements in acceleration time was the only factor to be significantly correlated with the reduction of arterial narrowing. Moreover, post-dilation values of this index were, on average, slightly but significantly higher in arteries that at follow-up developed restenosis rather than in those that remained patent. For similar reductions in arterial narrowing the absolute changes of all indices were similar in atherosclerotic and fibromuscular stenotic arteries and, in a subset of the atheromatous arteries, were also similar after angioplasty and stent implantation. No relationship was found with the changes in the venoarterial differences of plasma renin activity and angiotensin II. It appears that these intrarenal velocimetric indices and, in particular, acceleration time reliably reflect the technical success of renal artery dilation. The acceleration time index may also be valuable for predicting the restenosis of the dilated vessel. None of the indices, however, mirrors the functional consequences of removal of renal artery stenosis as expressed through the changes in transrenal gradients of the components of the renin-angiotensin system

A novel electrocardiographic index for the diagnosis of diastolic dysfunction

Contains fulltext : 128595.pdf (publisher's version ) (Open Access)BACKGROUND: Although the assessment of diastolic dysfunction (DD) is an integral part of routine cardiologic examinations, little is known about associated electrocardiographic (ECG) changes. Our aim was to investigate a potential role of ECG indices for the recognition of patients with DD. METHODS AND RESULTS: ECG parameters correlating with echocardiographic findings of DD were retrospectively assessed in a derivation group of 172 individuals (83 controls with normal diastolic function, 89 patients with DD) and their diagnostic performance was tested in a validation group of 50 controls and 50 patients. The patient group with a DD Grade 1 and 2 showed longer QTc (422+/-24ms and 434+/-32ms vs. 409+/-25ms, p<0.0005) and shorter Tend-P and Tend-Q intervals, reflecting the electrical and mechanical diastole (240+/-78ms and 276+/-108ms vs. 373+/-110ms, p<0.0001; 409+/-85ms and 447+/-115ms vs. 526+/-119ms, p<0.0001). The PQ-interval was significantly longer in the patient group (169+/-28ms and 171+/-38ms vs. 153+/-22ms, p<0.005). After adjusting for possible confounders, a novel index (Tend-P/[PQxAge]) showed a high performance for the recognition of DD, stayed robust in the validation group (sensitivity 82%, specificity 93%, positive predictive value 93%, negative predictive value 82%, accuracy 88%) and proved a substantial added value when combined with the indexed left atrial volume (LAESVI, sensitivity 90%, specificity 92%, positive predictive value 95%, negative predictive value 86%, accuracy 91%). CONCLUSIONS: A novel electrocardiographic index Tend-P/(PQxAge) demonstrates a high diagnostic accuracy for the diagnosis of DD and yields a substantial added value when combined with the LAESVI

Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R(2)) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R(2) ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R(2) under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE

Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe - The ESCAPE project

Estimating within-city variability in air pollution concentrations is important. Land use regression (LUR) models are able to explain such small-scale within-city variations. Transparency in LUR model development methods is important to facilitate comparison of methods between different studies. We therefore developed LUR models in a standardized way in 36 study areas in Europe for the ESCAPE (European Study of Cohorts for Air Pollution Effects) project. Nitrogen dioxide (NO2) and nitrogen oxides (NOx) were measured with Ogawa passive samplers at 40 or 80 sites in each of the 36 study areas. The spatial variation in each area was explained by LUR modelling. Centrally and locally available Geographic Information System (GIS) variables were used as potential predictors. A leave-one out cross-validation procedure was used to evaluate the model performance. There was substantial contrast in annual average NO2 and NOx concentrations within the study areas. The model explained variances (R2) of the LUR models ranged from 55% to 92% (median 82%) for NO2 and from 49% to 91% (median 78%) for NOx. For most areas the cross-validation R2 was less than 10% lower than the model R2. Small-scale traffic and population/household density were the most common predictors. The magnitude of the explained variance depended on the contrast in measured concentrations as well as availability of GIS predictors, especially traffic intensity data were important. In an additional evaluation, models in which local traffic intensity was not offered had 10% lower R2 compared to models in the same areas in which these variables were offered. Within the ESCAPE project it was possible to develop LUR models that explained a large fraction of the spatial variance in measured annual average NO2 and NOx concentrations. These LUR models are being used to estimate outdoor concentrations at the home addresses of participants in over 30 cohort studies

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P &lt; 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)