Lead-Dependent Infective Endocarditis: The Role of Factors Predisposing to Its Development in an Analysis of 414 Clinical Cases.

BACKGROUND: Lead-dependent infective endocarditis (LDIE) is a serious and insidious infective disease spreading along the leads to valve leaflets and endocardial surface. LDIE is still a lesser known disease with unclear risk factors, most often evaluated jointly for all infectious complications. METHODS: Clinical data from 414 patients with the diagnosis of LDIE according to the Modified Duke Leads Criteria were analyzed. Patients with LDIE were identified in a population of 1,426 subjects submitted to transvenous lead extraction (TLE) in the Reference Center on Lead Extraction in Lublin, Poland, between March 2006 and July 2013 due to infectious (619 patients-43.4%) and noninfectious (807-56.6% of patients) reasons. During the period of 2006-2011, the analysis was conducted retrospectively; from early 2012 on, patients were enrolled prospectively. The effect of potential risk factors on the development of the disease was evaluated in a comparative analysis of clinical data from the LDIE patients and from 807 subjects with noninfectious indications for TLE. Additionally, in order to identify the factors predisposing to the development of LDIE, the population of infectious patients was divided into three subgroups: with isolated LDIE (157 patients), with LDIE and pocket infection (PI; 257 patients), and with isolated PI (205 patients). The groups and subgroups were analyzed for the presence of patient-dependent risk factors (age, gender, accompanying diseases, anticoagulation, or antiplatelet therapy) and procedure-related risk factors (the number and lead dwell time, pacing system, prior procedures, lead loops, and intracardiac abrasion of the leads). Furthermore, microbes' identification was conducted. RESULTS: The LDIE patients were older (67.3 vs 62.3; P = 0.001) and were more frequently male (68.6% vs 55.0%; P = 0.001) as compared with patients submitted to TLE for noninfectious reasons, but not in comparison with subjects diagnosed with isolated LDIE. In univariate analysis, the independent prognostic factors of LDIE were: type 2 diabetes-increase of risk by 37.7% (hazard ratio [HR] = 1,377; 95% confidence interval [CI] [1,088-1,742]), elevated above 2 mg% creatinine level-increase of risk by 61.5% (HR = 1,615; 95% CI [1,96-2,182]), antiplatelet therapy (HR = 1,285; 95% CI [1,052-1,057]), number of intracardiac leads prior to TLE (HR = 1,199; 95% CI [1,075-1,337]), intracardiac device with implantable cardioverter defibrillator (ICD) lead (HR = 1,909; 95% CI [1,492-2,444]), intracardiac device with coronary sinus lead (HR = 1,411; 95% CI [1,099-1,810]), number of procedures prior to TLE (HR = 1,092; 95% CI [1,017-1,172]), and abrasion of intracardiac leads (HR = 1,350; 95% CI [1,097-1,662]). Multivariate logistic regression demonstrated that the independent risk factors of LDIE were: chronic renal failure (HR = 1,406; 95% CI [1,033-1,915]), number of intracardiac leads prior to TLE (HR = 1,152; 95% CI [1,017-1,305]), intracardiac devices with ICD leads (HR = 1,719; 95% CI [1,330-2,223]), and presence of abrasion of intracardiac leads (HR = 1,405; 95% CI [1,129-1,750]). Microbiological analysis showed the domination of coagulase-negative staphylococci with relative advantage of Staphylococcus epidermidis in pathogenesis of LDIE. CONCLUSIONS: The factors predisposing to LDIE are mainly related to procedures performed on the patients. LDIE develops more frequently in patients with multiple leads, especially ICD. An important, until now lesser known, risk factor for LDIE is intracardiac abrasion of the leads strongly connected with procedural agents and properties of specific kind of bacteries. A new concept of the pathogenesis of LDIE was proposed on the basis of present analysis.

The influence of chloride deicers on mineral nutrition and the health status of roadside trees in the city of Kielce, Poland.

Application of chemical road deicers has a negative impact on roadside vegetation. Every year, the trees in cities suffer from direct and indirect effects of salt application for winter road maintenance. To elucidate this problem in the city of Kielce, the chemistry of snow, soil, tree bark, and leaf samples has been investigated together with an assessment of the health status of the trees. Twelve investigation sites were selected along the roads with different traffic intensity. Snow samples were collected twice during the winter and analyzed for pH, EC, Na(+), Ca(2+), Mg(2+), and Cl(-). In soil (collected from two depth intervals), tree bark, and leaf samples, the concentrations of B, Ca, Fe, K, Mg, Mn, N, Na, P, S, and Zn were determined. The contents of total organic carbon (TOC) in soils, as well as the pH of soil and tree bark samples were also measured. Negative symptoms revealed by roadside trees included the loss of assimilative apparatus and decreased vitality. The results of chemical analyses indicated that the snowmelt might be a substantial source of chloride ions and alkalizing substances that influenced higher pH of soils. The soil samples displayed elevated concentrations of S and Zn and lower than typical for soil contents of B, Mg, and TOC. The pH of alkaline soils favored greater bioavailability of B and reduced bioavailability of Na and Zn by the trees examined.

Modelling diameter distributions of two-cohort forest stands with various proportions of dominant species: a two-component mixture model approach.

In recent years finite-mixture models have been employed to approximate and model empirical diameter at breast height (DBH) distributions. We used two-component mixtures of either the Weibull distribution or the gamma distribution for describing the DBH distributions of mixed-species, two-cohort forest stands, to analyse the relationships between the DBH components, age cohorts and dominant species, and to assess the significance of differences between the mixture distributions and the kernel density estimates. The data consisted of plots from the Swietokrzyski National Park (Central Poland) and areas close to and including the North Carolina section of the Great Smoky Mountains National Park (USA; southern Appalachians). The fit of the mixture Weibull model to empirical DBH distributions had a precision similar to that of the mixture gamma model, slightly less accurate estimate was obtained with the kernel density estimator. Generally, in the two-cohort, two-storied, multi-species stands in the southern Appalachians, the two-component DBH structure was associated with age cohort and dominant species. The 1st DBH component of the mixture model was associated with the 1st dominant species sp1 occurred in young age cohort (e.g., sweetgum, eastern hemlock); and to a lesser degree, the 2nd DBH component was associated with the 2nd dominant species sp2 occurred in old age cohort (e.g., loblolly pine, red maple). In two-cohort, partly multilayered, stands in the Swietokrzyski National Park, the DBH structure was usually associated with only age cohorts (two dominant species often occurred in both young and old age cohorts). When empirical DBH distributions representing stands of complex structure are approximated using mixture models, the convergence of the estimation process is often significantly dependent on the starting strategies. Depending on the number of DBHs measured, three methods for choosing the initial values are recommended: min.k/max.k, 0.5/1.5/mean, and multistart. For large samples (number of DBHs measured ≥ 80) the multistage method is proposed--for the two-component mixture Weibull or gamma model select initial values using the min.k/max.k (for k=1,5,10) and 0.5/1.5/mean methods, run the numerical procedure for each method, and when no two solutions are the same, apply the multistart method also.

Accuracy assessment of a small-area method for estimating the spatial distribution of the degree of tree damage.

Tree damage, gauged by the amount of defoliation, is one of the basic criteria used to determine treatments for protected and economic forests. Monitoring should include an assessment of the degree of tree damage in different spatial scales. Therefore, in addition to the commonly applied large-area methods, small-area methods should be used. The aim of the paper is to present the results of the accuracy assessment of a small-area method, proposed by Podlaski (2005) [Podlaski, R. (2005). Inventory of the degree of tree defoliation in small areas. Forest Ecology and Management, 215, 361-377], for monitoring the degree of tree damage. The degree of tree damage was shown in sub-blocks P(3) of the system of information on natural environment (SINUS). To estimate the spatial distribution of the degree of tree defoliation, survey sampling, based on simple random sampling with replacement (SRSWR), was used. The degree of damage to fir (Abies alba Mill.) and beech (Fagus sylvatica L.) was analysed in the Swiety Krzyz forest section in the Swietokrzyski National Park. The maximum total estimation errors for the proportion of trees with a degree zero of damage, and with second and third degrees of damage together (for alpha = 0.05) were at most 30.8% for fir and 24.3% for beech trees. For standard, small-area evaluations, these are satisfactory values. In the Swiety Krzyz forest section, the number of P(3) sub-blocks with 0.00-5.00% of undamaged trees and with 80.01-100.00% of moderately- or severely-damaged trees was significantly greater for fir than for beech. These results indicate that the fir population was unhealthier than the beech group in the study area. P(3) sub-blocks of the SINUS system, in which the proportion of the healthiest trees was highest, were situated at the forest margin, bordering on meadows and arable fields (in the case of fir) and forming dense patches consisting of several sub-blocks, or occurring singly in the whole study area (in the case of beech). The results show the significant differentiation of forest tree health in small areas.