79 research outputs found
Primera aproximació a una llista vermella dels fongs d'Andorra
S'ha avaluat el grau
d'amenaça d'un total de 502 fongs d'Andorra, basant-nos en dades de la bibliografia i en observacions
de camp. La informació obtinguda en aquests treballs ha estat comparada amb la de les bases de dades
de biodiversitat i les llistes vermelles dels països veïns. Posteriorment s'han avaluat els diferents tàxons
amb la metodologia de la IUCN, per determinar el seu grau d'amenaça. S'ha comprovat que moltes de
les espècies que cal incloure en les categories més amenaçades formen part de la micoflora de les
congesteres, tant pel seu grau d'aïllament com per l'amenaça que suposa el canvi climàtic per les
comunitats vegetals de les congesteres. El resultat de l'avaluació de 502 espècies ha estat el següent:
en Perill Crític (CR) no s'ha detectat cap espècie; En Perill (EN) hi ha 7 espècies, que és 1,39% del
total; com Vulnerables (VU) hi ha 23 (4,58% del total); com Quasi Amenaçades (NT) hi ha 30
(5,97%). Hi ha 392 espècies en la categoria de Preocupació Menor (LC) que són un 78,08%. En la
categoria de Dades Insuficients (DD) i No Avaluades (NE) hi ha 44 espècies (8,76%). Finalment, hi ha
6 espècies (1,19%), la presència de les quals no ha estat confirmada.Se ha evaluado el
grado de amenaza de un total de 502 hongos de Andorra basándonos en datos de la bibliografía y en
observaciones de campo. La información obtenida en estos trabajos ha sido cotejada con las bases de
datos de biodiversidad y las listas rojas de los países vecinos. Posteriormente se han evaluado los
diferentes taxones con la metodología de la IUCN para determinar su grado de amenaza. Se ha
comprobado que muchas de las especies a incluir en las categorías más amenazadas forman parte de la
micoflora de los neveros, tanto por su grado de aislamiento como por la amenaza que supone el
cambio climático para las comunidades vegetales que los pueblan. El resultado de la evaluación de
502 especies ha sido el siguiente: en Peligro Crítico (CR) no se ha detectado ninguna especie; En
Peligro (EN) hay 7 especies, que es 1,39% del total; como Vulnerables (VU) hay 23 (4,58% del total);
como Casi Amenazadas (NT) hay 30 (5,97%). Hay 392 especies en la categoría de Preocupación
Menor (LC) que son un 78,08%. En la categoría de Datos Insuficientes (DD) y No Evaluadas (NE)
hay 44 especies (8,76%). Finalmente, hay 6 (1,19%), la presencia de las cuales no ha sido confirmada.The level of threat of 502 fungi
from Andorra has been evaluated according to the data obtained from the bibliography and field
observations. The information from these works has been compared with the biodiversity databases
and the red lists of neighbouring countries. Subsequently, the different taxa were determined with the
IUCN methodology in order to assess their level of threat. It has been found that many of the species
in the highest threatened categories are part of the mycoflora of the snowbeds, both because of their
degree of isolation and the effect of the climate warming. The result of the evaluation of 502 species
is: in Critically Endangered (CR) no species has been detected; Endangered (EN) 7 species, which is
1.39% of the total; Vulnerable (VU) 23 (4.58% of the total); Near Threatened (NT) 30 (5.97%). There
are 392 species in the category of Least Concern (LC) that are 78.08%. In the category of Data
Deficient (DD) and Not Evaluated (NE) there are 44 species (8.76%). Finally, there are 6 species
(1.19%), whose presence has not been confirmed
Postprandial Glucose Improves the Risk Prediction of Cardiovascular Death Beyond the Metabolic Syndrome in the Nondiabetic Population
OBJECTIVE - With increasing evidence about the cardiovascular risk associated with postprandial nonfasting glucose and lipid dysmetabolism, it remains uncertain whether the postprandial glucose concentration increases the ability of metabolic syndrome to predict cardiovascular events. RESEARCH DESIGN AND METHODS - This was an observational study of 15, 145 individuals aged 35-75 years without diabetes or cardiovascular diseases. Postprandial glucose was obtained 2 In after a lunch meal. Metabolic syndrome was diagnosed using the criteria Of the U.S. National Cholesterol Education Program Adult Treatment Panel III. Cardiovascular and all-cause deaths were primary outcomes. RESULTS - During a median follow-up of 6.7 years, 410 individuals died, including 82 deaths from cardiovascular causes. In a Cox model adjusting for metabolic syndrome status as well as age, sex, smoking, systolic blood pressure, LDL, and HDL cholesterol levels, elevated 2-h postprandial glucose increased the risk of cardiovascular and all-cause death (per millimole per liter increase, hazard ratio 1.26 [95% CI 1.11-1.42] and 1.10 [1. 04-1.16], respectively), with significant trends across the postprandial glucose quintiles. Including 2-h postprandial glucose into a metabolic syndrome-included mustivariate risk prediction model conferred a discernible improvement of the model in discriminating between those who died of cardiovascular causes and who did not (integrated discrimination improvement 0.4, P = 0. 005; net reclassification improvement 13.4%, P = 0.03); however, the improvement was only marginal for all-cause death. CONCLUSIONS - Given the risk prediction based on metabolic syndrome and established cardiovascular risk factors, 2-h postprandial glucose improves the predictive ability to identity nondiabetic individuals at increased risk of cardiovascular death
A novel method for measuring patients' adherence to insulin dosing guidelines: introducing indicators of adherence
<p>Abstract</p> <p>Background</p> <p>Diabetic type 1 patients are often advised to use dose adjustment guidelines to calculate their doses of insulin. Conventional methods of measuring patients' adherence are not applicable to these cases, because insulin doses are not determined in advance. We propose a method and a number of indicators to measure patients' conformance to these insulin dosing guidelines.</p> <p>Methods</p> <p>We used a database of logbooks of type 1 diabetic patients who participated in a summer camp. Patients used a guideline to calculate the doses of insulin lispro and glargine four times a day, and registered their injected doses in the database. We implemented the guideline in a computer system to calculate recommended doses. We then compared injected and recommended doses by using five indicators that we designed for this purpose: absolute agreement (AA): the two doses are the same; relative agreement (RA): there is a slight difference between them; extreme disagreement (ED): the administered and recommended doses are merely opposite; Under-treatment (UT) and over-treatment (OT): the injected dose is not enough or too high, respectively. We used weighted linear regression model to study the evolution of these indicators over time.</p> <p>Results</p> <p>We analyzed 1656 insulin doses injected by 28 patients during a three weeks camp. Overall indicator rates were AA = 45%, RA = 30%, ED = 2%, UT = 26% and OT = 30%. The highest rate of absolute agreement is obtained for insulin glargine (AA = 70%). One patient with alarming behavior (AA = 29%, RA = 24% and ED = 8%) was detected. The monitoring of these indicators over time revealed a crescendo curve of adherence rate which fitted well in a weighted linear model (slope = 0.85, significance = 0.002). This shows an improvement in the quality of therapeutic decision-making of patients during the camp.</p> <p>Conclusion</p> <p>Our method allowed the measurement of patients' adherence to their insulin adjustment guidelines. The indicators that we introduced were capable of providing quantitative data on the quality of patients' decision-making for the studied population as a whole, for each individual patient, for all injections, and for each time of injection separately. They can be implemented in monitoring systems to detect non-adherent patients.</p
Results of a Successful Telephonic Intervention to Improve Diabetes Control in Urban Adults: A randomized trial
Relationship between Medication Use and Cardiovascular Disease Health Outcomes in the Jackson Heart Study
Even though some medications have the potential to slow the progress of atherosclerosis and development of CVD, there are many at-risk individuals who continue to resist the benefits that are available by not following the advice of medical professionals. Non-adherence to prescribed drug regimens is a pervasive medical problem that negatively affects treatment outcomes. Information from standardized interviews of 5301 African Americans participating in the Jackson Heart Study was examined to determine the association between demographic parameters, behavior including adherence to prescribed medical regimens, and health outcomes. Data were also collected at Annual Follow-Up and Surveillance visits. During the two weeks prior to the examination visit, almost 52% of the participants reported taking blood pressure medication, 14% took cholesterol medication, 16% took medication for diabetes, and 19% took blood thinning medication. Of those who did not take the prescribed medications, the reasons given were the following: 47% were in a hurry, too busy, or forgot to take medications; 23% were trying to do without medications; 18% had no money to purchase medications; 19% indicated that the medications made them feel bad; 17% felt that they could not carry out daily functions when taking medications. The African American population can benefit from heightened awareness of the risk factors that are associated with CVD and the benefits of following a prescribed treatment regimen. Unacceptable secondary effects of prescribed medication comprised an important cause of non-compliance. Encouragement of this population to communicate with their healthcare providers to ensure that medication regimens are better tolerated could increase compliance and improve health outcomes
Comparison of two independent systematic reviews of trials of recombinant human bone morphogenetic protein-2 (rhBMP-2) : The Yale Open Data Access Medtronic Project
Background: It is uncertain whether the replication of systematic reviews, particularly those with the same objectives and resources, would employ similar methods and/or arrive at identical findings. We compared the results and conclusions of two concurrent systematic reviews undertaken by two independent research teams provided with the same objectives, resources, and individual participant-level data. Methods: Two centers in the USA and UK were each provided with participant-level data on 17 multi-site clinical trials of recombinant human bone morphogenetic protein-2 (rhBMP-2). The teams were blinded to each other's methods and findings until after publication. We conducted a retrospective structured comparison of the results of the two systematic reviews. The main outcome measures included (1) trial inclusion criteria; (2) statistical methods; (3) summary efficacy and risk estimates; and (4) conclusions. Results: The two research teams' meta-analyses inclusion criteria were broadly similar but differed slightly in trial inclusion and research methodology. They obtained similar results in summary estimates of most clinical outcomes and adverse events. Center A incorporated all trials into summary estimates of efficacy and harms, while Center B concentrated on analyses stratified by surgical approach. Center A found a statistically significant, but small, benefit whereas Center B reported no advantage. In the analysis of harms, neither showed an increased cancer risk at 48 months, although Center B reported a significant increase at 24 months. Conclusions reflected these differences in summary estimates of benefit balanced with small but potentially important risk of harm. Conclusions: Two independent groups given the same research objectives, data, resources, funding, and time produced broad general agreement but differed in several areas. These differences, the importance of which is debatable, indicate the value of the availability of data to allow for more than a single approach and a single interpretation of the data. Systematic review registration: PROSPERO CRD42012002040and CRD42012001907
Age- and sex-specific prevalences of diabetes and impaired glucose regulation in 13 European cohorts
Clustering of metabolic syndrome components in a Middle Eastern diabetic and non-diabetic population
<p>Abstract</p> <p>Background</p> <p>Metabolic syndrome (MetS) encompasses a cluster of coronary heart disease and diabetes mellitus risk factors. In this study, we aimed to elucidate the factors underlying the clustering of MetS components in diabetic and non-diabetic individuals.</p> <p>Methods</p> <p>Factor analysis was performed on 2978 (1652 non-diabetic and 1326 diabetic) participants. Entering waist circumference, homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides, high-density lipoprotein-cholesterol (HDL-C) and systolic blood pressure (SBP), we performed exploratory factor analysis in diabetic and non-diabetic individuals separately. The analysis was repeated after replacing triglycerides and HDL-C with triglycerides to HDL-C ratio (triglycerides/HDL-C). MetS was defined by either adult treatment panel III (ATPIII), international diabetes federation (IDF) criteria, or by the modified form of IDF using waist circumference cut-off points for Iranian population.</p> <p>Results</p> <p>The selection of triglycerides and HDL-C as two distinct variables led to identifying two factors explaining 61.3% and 55.4% of the total variance in non-diabetic and diabetic participants, respectively. In both diabetic and non-diabetic subjects, waist circumference, HOMA-IR and SBP loaded on factor 1. Factor 2 was mainly determined by triglycerides and HDL-C. Factor 1 and 2 were directly and inversely associated with MetS, respectively. When triglycerides and HDL-C were replaced by triglycerides/HDL-C, one factor was extracted, which explained 47.6% and 38.8% of the total variance in non-diabetic and diabetic participants, respectively.</p> <p>Conclusion</p> <p>This study confirms that in both diabetic and non-diabetic participants the concept of a single underlying factor representing MetS is plausible.</p
Using quantile regression to investigate racial disparities in medication non-adherence
<p>Abstract</p> <p>Background</p> <p>Many studies have investigated racial/ethnic disparities in medication non-adherence in patients with type 2 diabetes using common measures such as medication possession ratio (MPR) or gaps between refills. All these measures including MPR are quasi-continuous and bounded and their distribution is usually skewed. Analysis of such measures using traditional regression methods that model mean changes in the dependent variable may fail to provide a full picture about differential patterns in non-adherence between groups.</p> <p>Methods</p> <p>A retrospective cohort of 11,272 veterans with type 2 diabetes was assembled from Veterans Administration datasets from April 1996 to May 2006. The main outcome measure was MPR with quantile cutoffs Q1-Q4 taking values of 0.4, 0.6, 0.8 and 0.9. Quantile-regression (QReg) was used to model the association between MPR and race/ethnicity after adjusting for covariates. Comparison was made with commonly used ordinary-least-squares (OLS) and generalized linear mixed models (GLMM).</p> <p>Results</p> <p>Quantile-regression showed that Non-Hispanic-Black (NHB) had statistically significantly lower MPR compared to Non-Hispanic-White (NHW) holding all other variables constant across all quantiles with estimates and p-values given as -3.4% (p = 0.11), -5.4% (p = 0.01), -3.1% (p = 0.001), and -2.00% (p = 0.001) for Q1 to Q4, respectively. Other racial/ethnic groups had lower adherence than NHW only in the lowest quantile (Q1) of about -6.3% (p = 0.003). In contrast, OLS and GLMM only showed differences in mean MPR between NHB and NHW while the mean MPR difference between other racial groups and NHW was not significant.</p> <p>Conclusion</p> <p>Quantile regression is recommended for analysis of data that are heterogeneous such that the tails and the central location of the conditional distributions vary differently with the covariates. QReg provides a comprehensive view of the relationships between independent and dependent variables (i.e. not just centrally but also in the tails of the conditional distribution of the dependent variable). Indeed, without performing QReg at different quantiles, an investigator would have no way of assessing whether a difference in these relationships might exist.</p
Modifiable risk factors for RA: prevention, better than cure?
Objective. To perform a meta-synthesis of the evidence for modifiable lifestyle risk factors for inflammatory polyarthritis (IP) and RA
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