Ireland’s understudied flatfish: reproduction, age and growth of the dab Limanda limanda (L.) in Irish coastal waters

In Ireland, although flatfish form a valuable fishery, little is known about the smallest, the dab Limanda limanda. In this study, a variety of parameters of reproductive development, including ovarian phase description, gonadosomatic index (GSI), hepatosomatic index (HSI), relative condition (Kn) and oocyte size were analysed to provide information on the dab’s reproductive cycle and spawning periods. Sampling were collected monthly over an 18-month period using bottom trawls of the Irish coastline. A six phase macroscopic guide was developed for both sexes of dab, and verified using histology. In comparisons of macroscopic and microscopic phases, there was high agreement in the proposed female guide (86%), with males demonstratively lower (62%). No significant bias was observed between the the two reproductive methods. When the male macroscopic guide was examined, misclassification was high in phase 5 and phase 5 (41%), with 96% of misclassification occurring in adjacent phases. The sampled population was primarily composed of females, with ratios of females to males 1:0.6, although the predominance of females was less noticeable during the reproductive season. Oocyte growth in dab follows asynchronous development, and spawn over a protracted period indicating a batch spawning strategy. Spawning occurred mainly in early spring, with total regeneration of gonads by May. The length at which 50% of the population was reproductively mature was identified as 14cm and 17cm, for male and female dab, respectively. Precision and bias in age determinations using whole otoliths to age dab was investigated using six age readers from various institutions. Low levels of precision were obtained (CV: 10-23%) inferring the need for an alternative methodology. Precision and bias was influence by the level of experience of the reader, with ageing error attributed to interpretative differences and difficulty in edge determination. Sectioned otolith age determinations were subsequently compared to whole otolith age determinations using two age readers experienced in dab ageing. Although increased precision was observed in whole otoliths from previous estimates (CV=0%, 0% APE), sectioned otoliths were used for growth models. This was based on multinominal logistic regression on age length keys developed using both ageing methods. Biological data (length and age) for both sexes was applied to four growth models, where the Akaike criterion and Multi model Inference indicated the logistic model as having the best fit to the collected data. In general, female dab attained a longer length then males, with growth rates significantly different between the two sexes. Length weight relationships between the two sexes were also significantly different.

Survival and Predictive Factors of Lethality in Hemodyalisis: D/I Polymorphism of The Angiotensin I-Converting Enzyme and of the Angiotensinogen M235T Genes

Background: End-stage kidney disease patients continue to have markedly increased cardiovascular disease morbidity and mortality. Analysis of genetic factors connected with the renin-angiotensin system that influences the survival of the patients with end-stage kidney disease supports the ongoing search for improved outcomes. Objective: To assess survival and its association with the polymorphism of renin-angiotensin system genes: angiotensin I-converting enzyme insertion/deletion and angiotensinogen M235T in patients undergoing hemodialysis. Methods: Our study was designed to examine the role of renin-angiotensin system genes. It was an observational study. We analyzed 473 chronic hemodialysis patients in four dialysis units in the state of Rio de Janeiro. Survival rates were calculated by the Kaplan-Meier method and the differences between the curves were evaluated by Tarone-Ware, Peto-Prentice, and log rank tests. We also used logistic regression analysis and the multinomial model. A p value ≤ 0.05 was considered to be statistically significant. The local medical ethics committee gave their approval to this study. Results: The mean age of patients was 45.8 years old. The overall survival rate was 48% at 11 years. The major causes of death were cardiovascular diseases (34%) and infections (15%). Logistic regression analysis found statistical significance for the following variables: age (p = 0.000038), TT angiotensinogen (p = 0.08261), and family income greater than five times the minimum wage (p = 0.03089), the latter being a protective factor. Conclusions: The survival of hemodialysis patients is likely to be influenced by the TT of the angiotensinogen M235T gene.

Atrial Fibrillation in Decompensated Heart Failure: Associated Factors and In-Hospital Outcome

Background: Studies on atrial fibrillation (AF) in decompensated heart failure (DHF) are scarce in Brazil. Objectives: To determine AF prevalence, its types and associated factors in patients hospitalized due to DHF; to assess their thromboembolic risk profile and anticoagulation rate; and to assess the impact of AF on in-hospital mortality and hospital length of stay. Methods: Retrospective, observational, cross-sectional study of incident cases including 659 consecutive hospitalizations due to DHF, from 01/01/2006 to 12/31/2011. The thromboembolic risk was assessed by using CHADSVASc score. On univariate analysis, the chi-square, Student t and Mann Whitney tests were used. On multivariate analysis, logistic regression was used. Results: The prevalence of AF was 40%, and the permanent type predominated (73.5%). On multivariate model, AF associated with advanced age (p < 0.0001), non-ischemic etiology (p = 0.02), right ventricular dysfunction (p = 0.03), lower systolic blood pressure (SBP) (p = 0.02), higher ejection fraction (EF) (p < 0.0001) and enlarged left atrium (LA) (p < 0.0001). The median CHADSVASc score was 4, and 90% of the cases had it ≥ 2. The anticoagulation rate was 52.8% on admission and 66.8% on discharge, being lower for higher scores. The group with AF had higher in-hospital mortality (11.0% versus 8.1%, p = 0.21) and longer hospital length of stay (20.5 ± 16 versus 16.3 ± 12, p = 0.001). Conclusions: Atrial fibrillation is frequent in DHF, the most prevalent type being permanent AF. Atrial fibrillation is associated with more advanced age, non-ischemic etiology, right ventricular dysfunction, lower SBP, higher EF and enlarged LA. Despite the high thromboembolic risk profile, anticoagulation is underutilized. The presence of AF is associated with longer hospital length of stay and high mortality.

Association between LDL-C, Non HDL-C, and Apolipoprotein B Levels with Coronary Plaque Regression

Background:Previous reports have inferred a linear relationship between LDL-C and changes in coronary plaque volume (CPV) measured by intravascular ultrasound. However, these publications included a small number of studies and did not explore other lipid markers.Objective:To assess the association between changes in lipid markers and regression of CPV using published data.Methods:We collected data from the control, placebo and intervention arms in studies that compared the effect of lipidlowering treatments on CPV, and from the placebo and control arms in studies that tested drugs that did not affect lipids. Baseline and final measurements of plaque volume, expressed in mm3, were extracted and the percentage changes after the interventions were calculated. Performing three linear regression analyses, we assessed the relationship between percentage and absolute changes in lipid markers and percentage variations in CPV.Results:Twenty-seven studies were selected. Correlations between percentage changes in LDL-C, non-HDL-C, and apolipoprotein B (ApoB) and percentage changes in CPV were moderate (r = 0.48, r = 0.47, and r = 0.44, respectively). Correlations between absolute differences in LDL-C, non‑HDL-C, and ApoB with percentage differences in CPV were stronger (r = 0.57, r = 0.52, and r = 0.79). The linear regression model showed a statistically significant association between a reduction in lipid markers and regression of plaque volume.Conclusion:A significant association between changes in different atherogenic particles and regression of CPV was observed. The absolute reduction in ApoB showed the strongest correlation with coronary plaque regression.

Echocardiographic Predictors of Worse Outcome After Cardiac Resynchronization Therapy

Abstract Background: Cardiac resynchronization therapy (CRT) is the recommended treatment by leading global guidelines. However, 30%-40% of selected patients are non-responders. Objective: To develop an echocardiographic model to predict cardiac death or transplantation (Tx) 1 year after CRT. Method: Observational, prospective study, with the inclusion of 116 patients, aged 64.89 ± 11.18 years, 69.8% male, 68,1% in NYHA FC III and 31,9% in FC IV, 71.55% with left bundle-branch block, and median ejection fraction (EF) of 29%. Evaluations were made in the pre‑implantation period and 6-12 months after that, and correlated with cardiac mortality/Tx at the end of follow-up. Cox and logistic regression analyses were performed with ROC and Kaplan-Meier curves. The model was internally validated by bootstrapping. Results: There were 29 (25%) deaths/Tx during follow-up of 34.09 ± 17.9 months. Cardiac mortality/Tx was 16.3%. In the multivariate Cox model, EF < 30%, grade III/IV diastolic dysfunction and grade III mitral regurgitation at 6‑12 months were independently related to increased cardiac mortality or Tx, with hazard ratios of 3.1, 4.63 and 7.11, respectively. The area under the ROC curve was 0.78. Conclusion: EF lower than 30%, severe diastolic dysfunction and severe mitral regurgitation indicate poor prognosis 1 year after CRT. The combination of two of those variables indicate the need for other treatment options.

Association between Functional Variables and Heart Failure after Myocardial Infarction in Rats

Background: Heart failure prediction after acute myocardial infarction may have important clinical implications. Objective: To analyze the functional echocardiographic variables associated with heart failure in an infarction model in rats. Methods: The animals were divided into two groups: control and infarction. Subsequently, the infarcted animals were divided into groups: with and without heart failure. The predictive values were assessed by logistic regression. The cutoff values predictive of heart failure were determined using ROC curves. Results: Six months after surgery, 88 infarcted animals and 43 control animals were included in the study. Myocardial infarction increased left cavity diameters and the mass and wall thickness of the left ventricle. Additionally, myocardial infarction resulted in systolic and diastolic dysfunction, characterized by lower area variation fraction values, posterior wall shortening velocity, E-wave deceleration time, associated with higher values of E / A ratio and isovolumic relaxation time adjusted by heart rate. Among the infarcted animals, 54 (61%) developed heart failure. Rats with heart failure have higher left cavity mass index and diameter, associated with worsening of functional variables. The area variation fraction, the E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate were functional variables predictors of heart failure. The cutoff values of functional variables associated with heart failure were: area variation fraction < 31.18%; E / A > 3.077; E-wave deceleration time < 42.11 and isovolumic relaxation time adjusted by heart rate < 69.08. Conclusion: In rats followed for 6 months after myocardial infarction, the area variation fraction, E/A ratio, E-wave deceleration time and isovolumic relaxation time adjusted by heart rate are predictors of heart failure onset.

Assessing the structural change of strategic mobility: determinants under hypercompetitive environments

The primary purpose of this exploratory empirical study is to examine the structural stability of a limited number of alternative explanatory factors of strategic change. On the basis of theoretical arguments and prior empirical evidence from two traditional perspectives, we propose an original empirical framework to analyse whether these potential explanatory factors have remained stable over time in a highly turbulent environment. This original question is explored in a particular setting: the population of Spanish private banks. The firms of this industry have experienced a high level of strategic mobility as a consequence of fundamental changes undergone in their environmental conditions over the last two decades (mainly changes related to the new banking and financial regulation process). Our results consistently support that the effect of most explanatory factors of strategic mobility considered did not remain stable over the whole period of analysis. From this point of view, the study sheds new light on major debates and dilemmas in the field of strategy regarding why firms change their competitive patterns over time and, hence, to what extent the "contextdependency" of alternative views of strategic change as their relative validation can vary over time for a given population. Methodologically, this research makes two major contributions to the study of potential determinants of strategic change. First, the definition and measurement of strategic change employing a new grouping method, the Model-based Cluster Method or MCLUST. Second, in order to asses the possible effect of determinants of strategic mobility we have controlled the non-observable heterogeneity using logistic regression models for panel data.

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

Relationships between imatinib plasma levels and efficacy

Purpose: While imatinib has revolutionized the treatment of chronic myeloid leukaemia (CML) and gastrointestinal stromal tumors (GIST), its pharmacokinetic-pharmacodynamic relationships have been poorly studied. This study aimed to explore the issue in oncologic patients, and to evaluate the specific influence of the target genotype in a GIST subpopulation. Patients and methods: Data from 59 patients (321 plasma samples) were collected during a previous pharmacokinetic study. Based on a population model purposely developed, individual post-hoc Bayesian estimates of pharmacokinetic parameters were derived, and used to estimate drug exposure (AUC; area under curve). Free fraction parameters were deduced from a model incorporating plasma alpha1-acid glycoprotein levels. Associations between AUC (or clearance) and therapeutic response (coded on a 3-point scale), or tolerability (4-point scale), were explored by ordered logistic regression. Influence of KIT genotype on response was also assessed in GIST patients. Results: Total and free drug exposure correlated with the number of side effects (p < 0.005). A relationship with response was not evident in the whole patient set (with good-responders tending to receive lower doses and bad-responders higher doses). In GIST patients however, higher free drug exposure predicted better responses. A strong association was notably observed in patients harboring an exon 9 mutation or a wild type KIT, known to decrease tumor sensitivity towards imatinib (p < 0.005). Conclusions: Our results are arguments to further evaluate the potential benefit of a therapeutic monitoring program for imatinib. Our data also suggest that stratification by genotype will be important in future trials.

A priori ratemaking using bivariate poisson regression models

In automobile insurance, it is useful to achieve a priori ratemaking by resorting to gene- ralized linear models, and here the Poisson regression model constitutes the most widely accepted basis. However, insurance companies distinguish between claims with or without bodily injuries, or claims with full or partial liability of the insured driver. This paper exa- mines an a priori ratemaking procedure when including two di®erent types of claim. When assuming independence between claim types, the premium can be obtained by summing the premiums for each type of guarantee and is dependent on the rating factors chosen. If the independence assumption is relaxed, then it is unclear as to how the tari® system might be a®ected. In order to answer this question, bivariate Poisson regression models, suitable for paired count data exhibiting correlation, are introduced. It is shown that the usual independence assumption is unrealistic here. These models are applied to an automobile insurance claims database containing 80,994 contracts belonging to a Spanish insurance company. Finally, the consequences for pure and loaded premiums when the independence assumption is relaxed by using a bivariate Poisson regression model are analysed.

A general model to predict individual exposure to solar UV by using ambient irradiance data

Excessive exposure to solar ultraviolet (UV) is the main cause of skin cancer. Specific prevention should be further developed to target overexposed or highly vulnerable populations. A better characterisation of anatomical UV exposure patterns is however needed for specific prevention. To develop a regression model for predicting the UV exposure ratio (ER, ratio between the anatomical dose and the corresponding ground level dose) for each body site without requiring individual measurements. A 3D numeric model (SimUVEx) was used to compute ER for various body sites and postures. A multiple fractional polynomial regression analysis was performed to identify predictors of ER. The regression model used simulation data and its performance was tested on an independent data set. Two input variables were sufficient to explain ER: the cosine of the maximal daily solar zenith angle and the fraction of the sky visible from the body site. The regression model was in good agreement with the simulated data ER (R(2)=0.988). Relative errors up to +20% and -10% were found in daily doses predictions, whereas an average relative error of only 2.4% (-0.03% to 5.4%) was found in yearly dose predictions. The regression model predicts accurately ER and UV doses on the basis of readily available data such as global UV erythemal irradiance measured at ground surface stations or inferred from satellite information. It renders the development of exposure data on a wide temporal and geographical scale possible and opens broad perspectives for epidemiological studies and skin cancer prevention.

Predicting smoking cessation and its relapse in HIV-infected patients: the Swiss HIV Cohort Study.

OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.

Probability of achieving optimal molecular response to imatinib in chronic myeloid leukemia (CML) patients: Pharmacokinetic/Pharmacodynamic (PK/PD) relationships observed under field-conditions

Objectives: Imatinib has been increasingly proposed for therapeutic drug monitoring (TDM), as trough concentrations (Cmin) correlate with response rates in CML patients. This analysis aimed to evaluate the impact of imatinib exposure on optimal molecular response rates in a large European cohort of patients followed by centralized TDM.¦Methods: Sequential PK/PD analysis was performed in NONMEM 7 on 2230 plasma (PK) samples obtained along with molecular response (PD) data from 1299 CML patients. Model-based individual Bayesian estimates of exposure, parameterized as to initial dose adjusted and log-normalized Cmin (log-Cmin) or clearance (CL), were investigated as potential predictors of optimal molecular response, while accounting for time under treatment (stratified at 3 years), gender, CML phase, age, potentially interacting comedication, and TDM frequency. PK/PD analysis used mixed-effect logistic regression (iterative two-stage method) to account for intra-patient correlation.¦Results: In univariate analyses, CL, log-Cmin, time under treatment, TDM frequency, gender (all p<0.01) and CML phase (p=0.02) were significant predictors of the outcome. In multivariate analyses, all but log-Cmin remained significant (p<0.05). Our model estimates a 54.1% probability of optimal molecular response in a female patient with a median CL of 14.4 L/h, increasing by 4.7% with a 35% decrease in CL (percentile 10 of CL distribution), and decreasing by 6% with a 45% increased CL (percentile 90), respectively. Male patients were less likely than female to be in optimal response (odds ratio: 0.62, p<0.001), with an estimated probability of 42.3%.¦Conclusions: Beyond CML phase and time on treatment, expectedly correlated to the outcome, an effect of initial imatinib exposure on the probability of achieving optimal molecular response was confirmed in field-conditions by this multivariate analysis. Interestingly, male patients had a higher risk of suboptimal response, which might not exclusively derive from their 18.5% higher CL, but also from reported lower adherence to the treatment. A prospective longitudinal study would be desirable to confirm the clinical importance of identified covariates and to exclude biases possibly affecting this observational survey.

Predictors of HIV-protection behaviour in HIV-positive men who have sex with casual male partners: a test of the explanatory power of an extended Information-Motivation-Behavioural Skills model.

This prospective study applies an extended Information-Motivation-Behavioural Skills (IMB) model to establish predictors of HIV-protection behaviour among HIV-positive men who have sex with men (MSM) during sex with casual partners. Data have been collected from anonymous, self-administered questionnaires and analysed by using descriptive and backward elimination regression analyses. In a sample of 165 HIV-positive MSM, 82 participants between the ages of 23 and 78 (M=46.4, SD=9.0) had sex with casual partners during the three-month period under investigation. About 62% (n=51) have always used a condom when having sex with casual partners. From the original IMB model, only subjective norm predicted condom use. More important predictors that increased condom use were low consumption of psychotropics, high satisfaction with sexuality, numerous changes in sexual behaviour after diagnosis, low social support from friends, alcohol use before sex and habitualised condom use with casual partner(s). The explanatory power of the calculated regression model was 49% (p<0.001). The study reveals the importance of personal and social resources and of routines for condom use, and provides information for the research-based conceptualisation of prevention offers addressing especially people living with HIV ("positive prevention").

Clinical presentation and survival of smear-positive pulmonary tuberculosis patients of a University General Hospital in a developing country

From January 1995 to August 1997 we evaluated prospectively the clinical presentation, laboratory findings and short-term survival of smear-positive pulmonary tuberculosis (TB) patients who sought care at our hospital. After providing informed, written consent, the patients were interviewed and laboratory tests were performed. Information about survivorship and death was collected through September 1998. Eighty-six smear-positive pulmonary TB patients were enrolled; 26.7% were HIV-seropositive. Seventeen HIV-seronegative pulmonary TB patients (19.8%) presented chronic diseases in addition to TB. In the multiple logistic regression analysis a CD4+ cell count <= 200 cell/mm³ was independently associated with HIV seropositivity. In the Cox regression model, fitted to all patients, HIV seropositivity and age > or = 50 years were independently associated with decreased survival. Among HIV-seronegative persons, the presence of an additional disease increased the risk of death of almost six-fold. Use of antiretroviral drugs was associated with a lower risk of death among HIV-seropositive smear-positive pulmonary TB patients (RH = 0.32, 95% CI 0.10-0.92). In our study smear-positive pulmonary TB patients had a low short-term survival rate that was strongly associated with HIV infection, age and co-morbidities. Therapy with antiretroviral drugs reduced the short-term risk of death among HIV-seropositive patients after TB diagnosis.