Maternal Inheritance of Familial Hypercholesterolemia Gene Mutation Predisposes to Coronary Atherosclerosis as Assessed by Calcium Score in Adulthood.

BACKGROUND: Animal studies have demonstrated that fetal exposure to high maternal cholesterol levels during pregnancy predisposes to aortic atheroma in the offspring. In humans, little is known about the consequences of this exposure on the development of atherosclerotic cardiovascular disease later in life. We wanted to assess whether maternal/paternal inheritance of familial hypercholesterolemia (FH) gene mutation could be associated with subclinical coronary atherosclerosis. METHODS: We retrospectively included 1350 patients, followed in the French registry of FH, with a documented genetic diagnosis. We selected 556 age- and sex-matched pair of patients based on the sex of the parents who transmitted the FH gene mutation, free of coronary cardiovascular event, and with a subclinical coronary atherosclerosis evaluation assessed using coronary artery calcium (CAC) score. We performed univariate and multivariate analysis to assess the individual effect of parental inheritance of the FH gene mutation on the CAC score. RESULTS: In the whole population, patients with maternal inheritance of FH gene mutation (n=639) less frequently had a family history of premature cardiovascular events (27.7% versus 45%, P<0.0001) and were 2 years older (46.9±16.8 versus 44.7±15.9 years old, P=0.02) than those with paternal inheritance (n=711). There was no difference in the prevalence of cardiovascular events between the two groups. In the matched subgroup, maternal inheritance was significantly associated with an increase in CAC score value by 86% (95% CI, 23%-170%; P=0.003), a 1.81-fold risk of having a CAC score ≥100 Agatston units (95% CI, 1.06-3.11; P=0.03), and a 2.72-fold risk of having a CAC score ≥400 Agatston units (95% CI, 1.39-5.51; P=0.004) when compared with paternal inheritance in multivariate analysis. CONCLUSIONS: Maternal inheritance of FH gene mutation was associated with more severe subclinical coronary atherosclerosis assessed by CAC score and may be considered as a potential cardiovascular risk factor.

Parotid cancer: analysis of preoperative parameters for adaptation of the therapeutic strategy.

PURPOSE: To establish typical clinical and radiological profiles of primary low-grade parotid cancers in order to tailor therapeutic strategy. MATERIALS AND METHODS: Retrospective study of 57 patients operated on for primary parotid cancer between 2010 and 2021, with review of preoperative MRI and histopathology according to a standardized scoring grid. OBJECTIVE: To study prognostic factors and determine the preoperative clinical and radiological profile of low-grade cancers. RESULTS: Good prognostic factors for specific survival were: staging ≤ cT3 (p = 0.014), absence of adenopathy on cN0 MRI (p < 0.001), superficial lobe location (p = 0.033), pN0 (p < 0.001), absence of capsular rupture (p = 0.004), as well as the absence of peri-tumoral nodules (p = 0.033), intra-parotid adenopathies (p < 0.001), vascular emboli (p < 0.001), peri-neural sheathing (p = 0.016), nuclear atypia (p = 0.031), and necrosis (p = 0.002). It was not possible to define a reliable clinical and radiological profile for low-grade cancers (sensitivity 38%, specificity 79%). CONCLUSION: Our study demonstrated multiple factors of good prognosis, but it was not possible to define a clinical and radiological profile of patients likely to benefit from more limited surgery, nor to diagnose, a priori, low-grade cancers.

Prognostic value of cardiovascular magnetic resonance T1 mapping and extracellular volume fraction in nonischemic dilated cardiomyopathy.

BACKGROUND: Heart failure- (HF) and arrhythmia-related complications are the main causes of morbidity and mortality in patients with nonischemic dilated cardiomyopathy (NIDCM). Cardiovascular magnetic resonance (CMR) imaging is a noninvasive tool for risk stratification based on fibrosis assessment. Diffuse interstitial fibrosis in NIDCM may be a limitation for fibrosis assessment through late gadolinium enhancement (LGE), which might be overcome through quantitative T1 and extracellular volume (ECV) assessment. T1 and ECV prognostic value for arrhythmia-related events remain poorly investigated. We asked whether T1 and ECV have a prognostic value in NIDCM patients. METHODS: This prospective multicenter study analyzed 225 patients with NIDCM confirmed by CMR who were followed up for 2 years. CMR evaluation included LGE, native T1 mapping and ECV values. The primary endpoint was the occurrence of a major adverse cardiovascular event (MACE) which was divided in two groups: HF-related events and arrhythmia-related events. Optimal cutoffs for prediction of MACE occurrence were calculated for all CMR quantitative values. RESULTS: Fifty-eight patients (26%) developed a MACE during follow-up, 42 patients (19%) with HF-related events and 16 patients (7%) arrhythmia-related events. T1 Z-score (p = 0.008) and global ECV (p = 0.001) were associated with HF-related events occurrence, in addition to left ventricular ejection fraction (p < 0.001). ECV > 32.1% (optimal cutoff) remained the only CMR independent predictor of HF-related events occurrence (HR 2.15 [1.14-4.07], p = 0.018). In the arrhythmia-related events group, patients had increased native T1 Z-score and ECV values, with both T1 Z-score > 4.2 and ECV > 30.5% (optimal cutoffs) being independent predictors of arrhythmia-related events occurrence (respectively, HR 2.86 [1.06-7.68], p = 0.037 and HR 2.72 [1.01-7.36], p = 0.049). CONCLUSIONS: ECV was the sole independent predictive factor for both HF- and arrhythmia-related events in NIDCM patients. Native T1 was also an independent predictor in arrhythmia-related events occurrence. The addition of ECV and more importantly native T1 in the decision-making algorithm may improve arrhythmia risk stratification in NIDCM patients. Trial registration NCT02352129. Registered 2nd February 2015-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT02352129.

Correcting for heterogeneity and non-comparability bias in multicenter clinical trials with a rescaled random-effect excess hazard model.

In the presence of competing causes of event occurrence (e.g., death), the interest might not only be in the overall survival but also in the so-called net survival, that is, the hypothetical survival that would be observed if the disease under study were the only possible cause of death. Net survival estimation is commonly based on the excess hazard approach in which the hazard rate of individuals is assumed to be the sum of a disease-specific and expected hazard rate, supposed to be correctly approximated by the mortality rates obtained from general population life tables. However, this assumption might not be realistic if the study participants are not comparable with the general population. Also, the hierarchical structure of the data can induces a correlation between the outcomes of individuals coming from the same clusters (e.g., hospital, registry). We proposed an excess hazard model that corrects simultaneously for these two sources of bias, instead of dealing with them independently as before. We assessed the performance of this new model and compared it with three similar models, using extensive simulation study, as well as an application to breast cancer data from a multicenter clinical trial. The new model performed better than the others in terms of bias, root mean square error, and empirical coverage rate. The proposed approach might be useful to account simultaneously for the hierarchical structure of the data and the non-comparability bias in studies such as long-term multicenter clinical trials, when there is interest in the estimation of net survival.

On models for the estimation of the excess mortality hazard in case of insufficiently stratified life tables.

In cancer epidemiology using population-based data, regression models for the excess mortality hazard is a useful method to estimate cancer survival and to describe the association between prognosis factors and excess mortality. This method requires expected mortality rates from general population life tables: each cancer patient is assigned an expected (background) mortality rate obtained from the life tables, typically at least according to their age and sex, from the population they belong to. However, those life tables may be insufficiently stratified, as some characteristics such as deprivation, ethnicity, and comorbidities, are not available in the life tables for a number of countries. This may affect the background mortality rate allocated to each patient, and it has been shown that not including relevant information for assigning an expected mortality rate to each patient induces a bias in the estimation of the regression parameters of the excess hazard model. We propose two parametric corrections in excess hazard regression models, including a single-parameter or a random effect (frailty), to account for possible mismatches in the life table and thus misspecification of the background mortality rate. In an extensive simulation study, the good statistical performance of the proposed approach is demonstrated, and we illustrate their use on real population-based data of lung cancer patients. We present conditions and limitations of these methods and provide some recommendations for their use in practice.

Insights from intravascular pressure measurement of renal artery revascularization in patients with fibromuscular dysplasia: The DYSART study.

OBJECTIVE: The indication of percutaneous renal transluminal angioplasty (PTRA) in fibromuscular dysplasia (FMD) is mainly based on renal artery stenosis (RAS) due to atherosclerosis criteria, which are not specific to FMD. Consequently, the selection of patients who could benefit from this treatment and its effectiveness remain uncertain. The aims of this study were to: (1) report the effects of PTRA guided by trans-stenotic pressure measurements on hypertension 7 months after treatment; (2) assess the impact of pressure measurement to guide treatment efficacy in comparison to visual angiographic parameters; and (3) evaluate the reproducibility and accuracy of the stenosis measurement using a 4F catheter in comparison to a pressure guidewire. METHODS: This prospective multi-centric study analyzed 24 patients with hypertension with RAS due to FMD that required PTRA. Clinical, duplex ultrasound, and angiographic indices were collected, and patients were followed up for 7 months (±1 month). Angiographic indices were measured twice both by a pressure guidewire and a 4F catheter. Assessment of procedural and clinical success of angioplasty was performed for all patients. RESULTS: Twenty-three patients (96%) had procedural success (considered as a post-PTRA translesional systolic gradient ≤10 mmHg or reduced by at least 80%) with a significant decrease in the systolic gradient after angioplasty (26.50 mmHg; [interquartile range, 16.75-38.75] vs 0.00 [interquartile range, 0.00-2.00]; P < .01). Three patients (12%) had complications, including two renal artery dissections and one partial renal infarction. Twenty-one patients (88%) were clinical responders to angioplasty at follow-up. Visual stenosis assessment showed a poor correlation with systolic gradient measurement before and after PTRA (R from -0.05 to 0.41; P = 0.06-0.82). High correlations were found between pressure measurements made by a 4F catheter and guidewire (R from 0.64 to 0.89; P ≤ .003). CONCLUSIONS: In patients selected by clinical indicators and duplex ultrasound, reaching a translesional systolic gradient ≤10 mmHg or reduced by at least 80% after angioplasty, promotes a high success rate for PTRA in hypertension due to FMD RAS.

A strategy for optimal fitting of multiplicative and additive hazards regression models.

BACKGROUND: In survival analysis, data can be modeled using either a multiplicative hazards regression model (such as the Cox model) or an additive hazards regression model (such as Lin's or Aalen's model). While several diagnostic tools are available to check the assumptions underpinning each type of model, there is no defined procedure to fit these models optimally. Moreover, the two types of models are rarely combined in survival analysis. Here, we propose a strategy for optimal fitting of multiplicative and additive hazards regression models in survival analysis. METHODS: This section details our proposed strategy for optimal fitting of multiplicative and additive hazards regression models, with a focus on the assumptions underpinning each type of model, the diagnostic tools used to check these assumptions, and the steps followed to fit the data. The proposed strategy draws on classical diagnostic tools (Schoenfeld and martingale residuals) and less common tools (pseudo-observations, martingale residual processes, and Arjas plots). RESULTS: The proposed strategy is applied to a dataset of patients with myocardial infarction (TRACE data frame). The effects of 5 covariates (age, sex, diabetes, ventricular fibrillation, and clinical heart failure) on the hazard of death are analyzed using multiplicative and additive hazards regression models. The proposed strategy is shown to fit the data optimally. CONCLUSIONS: Survival analysis is improved by using multiplicative and additive hazards regression models together, but specific steps must be followed to fit the data optimally. By providing different measures of the same effect, our proposed strategy allows for better interpretation of the data.

A filter approach for feature selection in classification: application to automatic atrial fibrillation detection in electrocardiogram recordings.

BACKGROUND: In high-dimensional data analysis, the complexity of predictive models can be reduced by selecting the most relevant features, which is crucial to reduce data noise and increase model accuracy and interpretability. Thus, in the field of clinical decision making, only the most relevant features from a set of medical descriptors should be considered when determining whether a patient is healthy or not. This statistical approach known as feature selection can be performed through regression or classification, in a supervised or unsupervised manner. Several feature selection approaches using different mathematical concepts have been described in the literature. In the field of classification, a new approach has recently been proposed that uses the [Formula: see text]-metric, an index measuring separability between different classes in heart rhythm characterization. The present study proposes a filter approach for feature selection in classification using this [Formula: see text]-metric, and evaluates its application to automatic atrial fibrillation detection. METHODS: The stability and prediction performance of the [Formula: see text]-metric feature selection approach was evaluated using the support vector machine model on two heart rhythm datasets, one extracted from the PhysioNet database and the other from the database of Marseille University Hospital Center, France (Timone Hospital). Both datasets contained electrocardiogram recordings grouped into two classes: normal sinus rhythm and atrial fibrillation. The performance of this feature selection approach was compared to that of three other approaches, with the first two based on the Random Forest technique and the other on receiver operating characteristic curve analysis. RESULTS: The [Formula: see text]-metric approach showed satisfactory results, especially for models with a smaller number of features. For the training dataset, all prediction indicators were higher for our approach (accuracy greater than 99% for models with 5 to 17 features), as was stability (greater than 0.925 regardless of the number of features included in the model). For the validation dataset, the features selected with the [Formula: see text]-metric approach differed from those selected with the other approaches; sensitivity was higher for our approach, but other indicators were similar. CONCLUSION: This filter approach for feature selection in classification opens up new methodological avenues for atrial fibrillation detection using short electrocardiogram recordings.

Correcting inaccurate background mortality in excess hazard models through breakpoints.

BACKGROUND: Methods for estimating relative survival are widely used in population-based cancer survival studies. These methods are based on splitting the observed (the overall) mortality into excess mortality (due to cancer) and background mortality (due to other causes, as expected in the general population). The latter is derived from life tables usually stratified by age, sex, and calendar year but not by other covariates (such as the deprivation level or the socioeconomic status) which may lack though they would influence background mortality. The absence of these covariates leads to inaccurate background mortality, thus to biases in estimating the excess mortality. These biases may be avoided by adjusting the background mortality for these covariates whenever available. METHODS: In this work, we propose a regression model of excess mortality that corrects for potentially inaccurate background mortality by introducing age-dependent multiplicative parameters through breakpoints, which gives some flexibility. The performance of this model was first assessed with a single and two breakpoints in an intensive simulation study, then the method was applied to French population-based data on colorectal cancer. RESULTS: The proposed model proved to be interesting in the simulations and the applications to real data; it limited the bias in parameter estimates of the excess mortality in several scenarios and improved the results and the generalizability of Touraine's proportional hazards model. CONCLUSION: Finally, the proposed model is a good approach to correct reliably inaccurate background mortality by introducing multiplicative parameters that depend on age and on an additional variable through breakpoints.

Glycosylated Hemoglobin as a Surrogate for the Prevention of Cardiovascular Events in Cardiovascular Outcome Trials Comparing New Antidiabetic Drugs to Placebo.

BACKGROUND AND OBJECTIVES: The value of glycosylated hemoglobin (HbA1c) as a surrogate marker for the prevention of cardiovascular outcomes on antidiabetic drugs is debated. The 2008 FDA guidance led to multiple large clinical trials to evaluate the effect of new antidiabetic drugs versus placebo on major adverse cardiac events (MACE). The aim of this study was to evaluate the relation between MACE and HbA1c decrease between antidiabetic drug and placebo across the spectrum of cardiovascular outcome trials (CVOT). METHODS: In this systematic review, we included randomized controlled trials that compared an antidiabetic drug to placebo in addition to current standard of care with the primary intention of demonstrating cardiovascular safety. We investigated the relationship between MACE decrease on antidiabetic drug and HbA1c reduction on antidiabetic drug using the coefficient correlation. We also studied the effects of potential confounders on MACE decrease. RESULTS: Fourteen eligible trials including 128,149 patients were included, 12,114 of whom experienced MACE. Mean achieved HbA1c absolute reductions on antidiabetic treatment versus placebo varied from 0.29 to 1%. The decrease of MACE on antidiabetic drug was significantly correlated with mean HbA1c reduction (r = 0.88, 95% CI: 0.67-0.96, p < 0.001) and weight loss (r = 0.81, 95% CI: 0.46-0.94, p < 0.001). In a bivariate model including weight loss, only HbA1c reduction remained significantly correlated with the decrease of MACE on antidiabetic drug (p = 0.019). CONCLUSION: Across CVOT, the decrease in MACE incidence on various antidiabetic drugs is significantly correlated with HbA1c reduction. This meta-analysis supports HbA1c as an appropriate surrogate endpoint for cardiovascular events. Our analysis supports that changes in HbA1c should be taken into account while interpreting effects of new antidiabetic drugs on cardiovascular outcomes.

Correcting for misclassification and selection effects in estimating net survival in clinical trials.

BACKGROUND: Net survival, a measure of the survival where the patients would only die from the cancer under study, may be compared between treatment groups using either "cause-specific methods", when the causes of death are known and accurate, or "population-based methods", when the causes are missing or inaccurate. The latter methods rely on the assumption that mortality due to other causes than cancer is the same as the expected mortality in the general population with same demographic characteristics derived from population life tables. This assumption may not hold in clinical trials where patients are likely to be quite different from the general population due to some criteria for patient selection. METHODS: In this work, we propose and assess the performance of a new flexible population-based model to estimate long-term net survival in clinical trials and that allows for cause-of-death misclassification and for effects of selection. Comparisons were made with cause-specific and other population-based methods in a simulation study and in an application to prostate cancer clinical trial data. RESULTS: In estimating net survival, cause-specific methods seemed to introduce important biases associated with the degree of misclassification of cancer deaths. The usual population-based method provides also biased estimates, depending on the strength of the selection effect. Compared to these methods, the new model was able to provide more accurate estimates of net survival in long-term clinical trials. CONCLUSION: Finally, the new model paves the way for new methodological developments in the field of net survival methods in multicenter clinical trials.

"Spatial heterogeneity of environmental risk in randomized prevention trials: consequences and modeling".

BACKGROUND: In the context of environmentally influenced communicable diseases, proximity to environmental sources results in spatial heterogeneity of risk, which is sometimes difficult to measure in the field. Most prevention trials use randomization to achieve comparability between groups, thus failing to account for heterogeneity. This study aimed to determine under what conditions spatial heterogeneity biases the results of randomized prevention trials, and to compare different approaches to modeling this heterogeneity. METHODS: Using the example of a malaria prevention trial, simulations were performed to quantify the impact of spatial heterogeneity and to compare different models. Simulated scenarios combined variation in baseline risk, a continuous protective factor (age), a non-related factor (sex), and a binary protective factor (preventive treatment). Simulated spatial heterogeneity scenarios combined variation in breeding site density and effect, location, and population density. The performances of the following five statistical models were assessed: a non-spatial Cox Proportional Hazard (Cox-PH) model and four models accounting for spatial heterogeneity-i.e., a Data-Generating Model, a Generalized Additive Model (GAM), and two Stochastic Partial Differential Equation (SPDE) models, one modeling survival time and the other the number of events. Using a Bayesian approach, we estimated the SPDE models with an Integrated Nested Laplace Approximation algorithm. For each factor (age, sex, treatment), model performances were assessed by quantifying parameter estimation biases, mean square errors, confidence interval coverage rates (CRs), and significance rates. The four models were applied to data from a malaria transmission blocking vaccine candidate. RESULTS: The level of baseline risk did not affect our estimates. However, with a high breeding site density and a strong breeding site effect, the Cox-PH and GAM models underestimated the age and treatment effects (but not the sex effect) with a low CR. When population density was low, the Cox-SPDE model slightly overestimated the effect of related factors (age, treatment). The two SPDE models corrected the impact of spatial heterogeneity, thus providing the best estimates. CONCLUSION: Our results show that when spatial heterogeneity is important but not measured, randomization alone cannot achieve comparability between groups. In such cases, prevention trials should model spatial heterogeneity with an adapted method. TRIAL REGISTRATION: The dataset used for the application example was extracted from Vaccine Trial #NCT02334462 ( ClinicalTrials.gov registry).

Single Injection of High Volume of Autologous Pure PRP Provides a Significant Improvement in Knee Osteoarthritis: A Prospective Routine Care Study.

BACKGROUND: Evidence is growing regarding the ability of platelet-rich plasma (PRP) injections to enhance functional capacity and alleviate pain in knee osteoarthritis (OA). However, heterogeneity in common practice regarding PRP preparation and biological content makes the initiation of this activity in a hospital complex. The aim of this study was to document the efficacy of a single PRP injection to treat knee OA and validate a routine care procedure. METHODS: Fifty-seven patients with symptomatic knee OA received a single injection of large volume of very pure PRP. They were assessed at baseline and after one, three and six months, by measuring Knee Injury and Osteoarthritis Score (KOOS), Observed Pain after a 50-foot walk test and Visual Analog Scale (VAS) assessments. Magnetic Resonance Imaging (MRI) analysis was performed at baseline and six months after the procedure. The objective was to recover 50% of responders three months after the procedure using OMERACT-OARSI criteria. RESULTS: A single administration of high volume pure PRP provided significant clinical benefit for 84.2% of the responders, three months after the procedure. The KOOS total score significantly increased from 43.5 ± 14.3 to 66.4 ± 21.7 six months after the procedure (p < 0.001). Pain also significantly decreased from 37.5 ± 25.1 to 12.9 ± 20.9 (p < 0.001). No difference was observed on MRI parameters. CONCLUSION: A single injection of large volume of very pure PRP is associated with significant functional improvement and pain relief, allowing initiation of daily PRP injection within our hospital.

Embolization of the Superior Rectal Arteries for Hemorrhoidal Disease: Prospective Results in 25 Patients.

PURPOSE: To evaluate efficacy and safety of superior rectal artery embolization of hemorrhoidal disease as a first-line invasive treatment. MATERIALS AND METHODS: This prospective study was conducted between 2014 and 2015 on 25 consecutive patients (16 men and 9 women with a mean age of 53 y [range, 30-76 y]) with grade II-III hemorrhoids refractory to medical treatment. A transfemoral superselective superior rectal artery branch embolization was performed using 2- and 3-mm diameter microcoils. Over the following 12 months, clinical outcomes were evaluated using the French bleeding score, Goligher prolapse score, visual analog scale (VAS) score for pain, quality-of-life score. The primary endpoint was relief of symptoms by 12 months based on a 2-point minimum improvement on VAS score and bleeding score. RESULTS: At 12 months after embolization, clinical success was obtained in 18 patients (72%), 8 of whom had 2 embolizations. VAS score decreased from 4.6 to 2.3 (P < .01), and bleeding score decreased from 5.5 to 2.3 (P < .01). Quality-of-life and prolapse scores also showed improvement (P < .05), and no patients experienced any early or late complications. Complete clinical failure was observed in 7 patients. After coil embolization, the collateral supply to the hemorrhoidal cushions was significantly related to any recurrence (P = .001). CONCLUSIONS: Hemorrhoidal artery coil embolization was found to be a safe and effective treatment for grade II-III hemorrhoids.

Right ventricular and tricuspid valve function in patients chronically implanted with leadless pacemakers.

Aims: Leadless cardiac pacing has recently been proposed as alternative to conventional right ventricular (RV) pacing. With this approach, devices are directly screwed or fixed with tines in the RV wall, but the possible consequences on RV and tricuspid valve (TV) structure and function remain unknown. We thus conducted a study to evaluate this potential impact in chronically implanted patients. Methods and results: Repeated echocardiographic studies were performed prior to implantation, at discharge, and 2 months thereafter on all consecutive patients implanted with a leadless pacemaker at our centre between October 2014 and end-December 2015. Whenever possible, patients were evaluated in non-paced rhythm. Anatomical and functional parameters of RV, TV, and left cardiac structures were assessed. Overall, 23 patients (12 females, aged 85.2 ± 6.3 years) were included, with 14 implanted using Nanostim™ (Saint Jude Medical) and 9 with Micra™ (Medtronic). Indications for pacing were paroxysmal atrio-ventricular block in 12 patients, intermittent sinus bradycardia in 5, unexplained syncope in 3, and atrial fibrillation with slow ventricular rate in the remaining 3. The pacing percentage was 34 ± 42% at the last visit. Most devices were implanted in the septo-apical or mid-septal region. There were no significant changes in echocardiographic parameters observed. One patient developed significantly increased TV regurgitation, without abnormal leaflet motion or TV annulus size changes, suggesting it to be due to RV pressure changes. Conclusion: In patients chronically implanted with leadless pacemakers, there were no significant changes in heart structure and function observed, especially concerning the RV and TV.

Factors limiting adherence to antiepileptic treatment: A French online patient survey.

WHAT IS KNOWN AND OBJECTIVE: There are various reasons why antiepileptic treatment can fail. One is drug-resistant epilepsies, but non-adherence, or poor adherence, to treatment may make some patients' treatment ineffective. The consequences of poor adherence include treatment failure or introduction of more complex treatments involving greater toxicity with uncertain prognosis. This study contributes to a critical research area focused on antiepileptic drug adherence and aims to assess the main factors limiting adherence, as well as psychosocial factors influencing on risk of non-adherence. METHODS: An opinion survey was conducted among patients and parents of children treated for epilepsy and members of a French online support group. RESULTS AND DISCUSSION: A total of 263 questionnaires were collected. Of the patients, 79% said they never forget their medication, whereas 21% admitted occasional or frequent omissions. The main treatment-related factors that can limit adherence were adverse effects (limiting factors reported for 70% of patients) and number of tablets or number of intake per day (limiting factors reported for 32% of patients). Galenic (liquid) formulation (18%), drug taste (18%), tablet size (14%) and concern about the perception of others (17%) were cited in roughly equivalent terms as limiting adherence to treatment. Among the 55 patients who were genuinely non-adherent to their treatment, the occupational difficulties induced by following the treatment were a main cause of non-adherence. WHAT IS NEW AND CONCLUSION: Improving adherence in patients with epilepsy is a difficult and complex problem. Community pharmacists could play a major role in the determination of patients' adherence and should be aware of the risk of non-adherence.

Peri-operative oral caffeine does not prevent postoperative atrial fibrillation after heart valve surgery with cardiopulmonary bypass: A randomised controlled clinical trial.

BACKGROUND: Raised plasma levels of endogenous adenosine after cardiac surgery using cardiopulmonary bypass (CPB) have been related to the incidence of postoperative atrial fibrillation (POAF). OBJECTIVE: We wished to assess if caffeine, an adenosine receptor antagonist could have a beneficial effect on the incidence of POAF. DESIGN: A randomised controlled study. SETTING: Single University Hospital. PATIENTS: One hundred and ten patients scheduled for heart valve surgery with CPB. INTERVENTIONS: We randomly assigned patients to receive peri-operative oral caffeine (400 mg every 8 h for 2 days) or placebo. Adenosine plasma concentrations and caffeine pharmacokinetic profile were evaluated in a subgroup of 50 patients. MAIN OUTCOME MEASURES: The primary endpoint was the rate of atrial fibrillation during postoperative hospital stay. RESULTS: The current study was stopped for futility by the data monitoring board after an interim analysis. The incidence of atrial fibrillation was similar in the caffeine and in the placebo group during hospital stay (33 vs. 29%, P = 0.67) and the first 3 postoperative days (18 vs. 15%; P = 0.60). Basal and postoperative adenosine plasma levels were significantly associated with the primary outcome. Adenosine plasma levels were similar in the two treatment groups. Caffeine administration was associated with a higher incidence of postoperative nausea and vomiting (27 vs. 7%, P = 0.005). CONCLUSION: Oral caffeine does not prevent POAF after heart valve surgery with CPB but increased the incidence of postoperative nausea and vomiting. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, no.: NCT01999829.

Goodness-of-fit test for monotone proportional subdistribution hazards assumptions based on weighted residuals.

Recently goodness-of-fit tests have been proposed for checking the proportional subdistribution hazards assumptions in the Fine and Gray regression model. Zhou, Fine, and Laird proposed weighted Schoenfeld-type residuals tests derived under an assumed model with specific form of time-varying regression coefficients. Li, Sheike, and Zhang proposed an omnibus test based on cumulative sums of Schoenfeld-type residuals. In this article, we extend the class of weighted residuals tests by allowing random weights of Schoenfeld-type residuals at ordered event times. In particular, it is demonstrated that weighted residuals tests using monotone weight functions of time are consistent against monotone proportional subdistribution hazards assumptions. Extensive Monte Carlo studies were conducted to evaluate the finite-sample performance of recent goodness-of-fit tests. Results from simulation studies show that weighted residuals tests using monotone random weight functions commonly used in non-proportional hazards regression settings tend to be more powerful for detecting monotone departures than other goodness-of-fit tests assuming no specific time-varying effect or misspecified time-varying effects. Two examples using real data are provided for illustrations. Copyright © 2016 John Wiley & Sons, Ltd.

Outcomes and costs associated with two different lead-extraction approaches: a single-centre study.

AIMS: We sought to compare outcomes and costs of a stepwise approach to transvenous lead extraction (TLE) involving laser-assisted sheaths or mechanical polypropylene sheaths, with/without crossover. METHODS AND RESULTS: We prospectively included patients who underwent TLE (between August 2013 and December 2014) as part of a stepwise approach involving simple traction, lead snaring, and sheath-assisted dissection; all of these patients underwent a first-line polypropylene-sheath-extraction approach (Group A). The comparison group (Group B) was consecutive patients who had undergone TLE before August 2013, during which laser-assisted sheath extraction was the first-line approach. The number of patients in Group B was adjusted to match the number who eventually needed sheaths in Group A. Procedural data, outcomes, and costs were compared between groups (comparison of approaches) and in patients who needed sheath-assisted extraction (comparison of techniques). Overall, 521 leads were extracted (131 patients in Group A, 104 in Group B). Radiological and clinical success rates were similar; crossover from polypropylene to laser sheaths was needed in 10 patients in Group A (vs. none in Group B). Radiological (P< 0.001) and clinical (P= 0.01) success rates were higher and were achieved with a lower radiation exposure (P= 0.03) with laser sheaths in patients (60 in each group) who needed sheath-assisted extraction. Complication rates were similar in both groups (P= 0.66) but two deaths occurred in Group B. The laser approach had higher material cost (P= 0.002). CONCLUSIONS: Although laser-assisted TLE was more effective than polypropylene sheath-assisted TLE, the latter was associated with fewer complications and was more cost-effective.

Persistent pathways after lung radiofrequency ablation as a risk factor of drain placement.

PURPOSE: The risk factors of pneumothorax after lung radiofrequency (RF) ablation are long known. The objective was to demonstrate that the visualisation of an aeric RF path after the needle withdrawal was predictive of pneumothorax occurrence and chest tube placement. MATERIALS AND METHODS: A total of 70 patients were retrospectively included in this study. For each patient, we determined the pneumothorax risk factors (age, gender, previous surgery, emphysema, lesion size, distance between pleura and lesion), visualisation of a RF track, length and thickness, presence of pneumothorax, volume, chest tube placement, duration of drainage and hospital stay. RESULTS: Among 70 patients included retrospectively, 26 needed a chest tube placement (37%). Considering the group with path visualisation (37 patients, group A) and the patients without path visualisation (group B), the 2 groups were comparable for pneumothorax risk factors. Considering the patients who needed a chest drain, the visualisation of the path was significatively more important (23 cases, 88.4%) (p< 10-3) than in the group without (8 patients, 31.8%). Multivariate analyses were significant in the three analyses after adjustments on the risk factors for the occurrence of pneumothorax. Incidence of drains was significantly more (p < 10-3) important in group A (23 drainages 62%) than in group B (4 drainages or 12%). The length and thickness of the tracks were not predictable of drain placement. CONCLUSIONS: Besides the well-known risk factors of severe pneumothorax after lung RFA, the simple visualisation of an aeric path just after the RF needle withdrawal is significantly associated with chest tube placement and can be considered as a risk factor as itself.