BACKGROUND AND AIMS: For patients with congenitally corrected transposition of the great arteries (ccTGA), factors associated with progression to end-stage congestive heart failure (CHF) remain largely unclear. METHODS: This multicentre, retrospective cohort study included adults with ccTGA seen at a congenital heart disease centre. Clinical data from initial and most recent visits were obtained. The composite primary outcome was mechanical circulatory support, heart transplantation, or death. RESULTS: From 558 patients (48% female, age at first visit 36 ± 14.2 years, median follow-up 8.7 years), the event rate of the primary outcome was 15.4 per 1000 person-years (11 mechanical circulatory support implantations, 12 transplantations, and 52 deaths). Patients experiencing the primary outcome were older and more likely to have a history of atrial arrhythmia. The primary outcome was highest in those with both moderate/severe right ventricular (RV) dysfunction and tricuspid regurgitation (n = 110, 31 events) and uncommon in those with mild/less RV dysfunction and tricuspid regurgitation (n = 181, 13 events, P < .001). Outcomes were not different based on anatomic complexity and history of tricuspid valve surgery or of subpulmonic obstruction. New CHF admission or ventricular arrhythmia was associated with the primary outcome. Individuals who underwent childhood surgery had more adverse outcomes than age- and sex-matched controls. Multivariable Cox regression analysis identified older age, prior CHF admission, and severe RV dysfunction as independent predictors for the primary outcome. CONCLUSIONS: Patients with ccTGA have variable deterioration to end-stage heart failure or death over time, commonly between their fifth and sixth decades. Predictors include arrhythmic and CHF events and severe RV dysfunction but not anatomy or need for tricuspid valve surgery.

• MeSH
• Child MeSH
• Adult MeSH
• Ventricular Dysfunction, Right * complications   MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Retrospective Studies MeSH
• Heart Failure * complications   MeSH
• Transposition of Great Vessels * complications   surgery   MeSH
• Tricuspid Valve Insufficiency * complications   MeSH
• Congenitally Corrected Transposition of the Great Arteries MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH

Studie zkoumá kognitivní výkon ve verbální paměti během remise unipolámí depresivní poruchy. Testovali jsme hypotézu, že ambulantní medikovaní i nemedikovaní pacienti žijící ve svém běžném prostředí se nebudou lišit od kontrol v Paměťovém testu učení. K 97 pacientům jsme přiřadili 97 kontrol podle vzdělání, věku a pohlaví a porovnávali je v Paměťovém testu učení. Pacienti měli horší výkony ve srovnání s kontrolami. 1 po korekci pro subjektivní míru deprese měřenou BDI zůstal deficit v oddáleném vybavení signifikantní. Výsledky naznačují, že deficit ve verbálni paměti by mohl být považován u unipolární depresivní poruchy v remisi za "trait marker".

The present study investigates performance of verbal memory during remission from unipolar depressive episodes. We tested a hy- pothesis that outpatients do not differ in cognitive variables from matched controls, in a well defined outpatient sample, cons isting of medicated and unmedicated patients, with a history of MDD, living in their natural environments. Ninety-seven fully remitted pa tients with MDD were compared to 97 healthy control subjects matched for education, age and gender on Auditory Verbal Learning Test (AVLT). Patients with remitted MDD comparing to controls were impaired on verbal memory tasks. After correction for subjective level of depression, deficits in the delayed verbal recall (AVLT) remained significant. These findings suggest deficits in delayed ve rbal recall can serve as a trait marker for MDD out of hospitalization in unipolar depression.

• MeSH
• Depressive Disorder, Major complications   psychology   MeSH
• Research Support as Topic MeSH
• Financing, Organized MeSH
• Data Interpretation, Statistical MeSH
• Cognition Disorders diagnosis   MeSH
• Humans MeSH
• Evidence-Based Medicine trends   MeSH
• Disease Progression MeSH
• Remission, Spontaneous MeSH
• Verbal Learning physiology   MeSH
• Treatment Outcome MeSH
• Check Tag
• Humans MeSH

• MeSH
• Alcohol Drinking epidemiology   MeSH
• Data Collection MeSH
• Sex Factors MeSH
• Social Problems MeSH
• Socioeconomic Factors MeSH
• Age Factors MeSH
• Developed Countries statistics & numerical data   MeSH
• Employment MeSH

• Conspectus
• Veřejné zdraví a hygiena
• NML Fields
• veřejné zdravotnictví
• adiktologie
• NML Publication type
• studie

• MeSH
• Meta-Analysis as Topic * MeSH
• Statistics as Topic MeSH
• Publication type
• Meta-Analysis MeSH
• Handbook MeSH

• Conspectus
• Statistika
• NML Fields
• statistika, zdravotnická statistika

This paper presents a new size estimation method that can be used to estimate size level for software engineering projects. The Algorithmic Optimisation Method is based on Use Case Points and on Multiple Least Square Regression. The method is derived into three phases. The first phase deals with calculation Use Case Points and correction coefficients values. Correction coefficients are obtained by using Multiple Least Square Regression. New project is estimated in the second and third phase. In the second phase Use Case Points parameters for new estimation are set up and in the third phase project estimation is performed. Final estimation is obtained by using newly developed estimation equation, which used two correction coefficients. The Algorithmic Optimisation Method performs approximately 43% better than the Use Case Points method, based on their magnitude of relative error score. All results were evaluated by standard approach: visual inspection, goodness of fit measure and statistical significance.

• MeSH
• Algorithms * MeSH
• Data Interpretation, Statistical * MeSH
• Humans MeSH
• Regression Analysis * MeSH
• Software MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

Two video sequences of hand motion are analyzed using passive markers for medical diagnostic purposes. Th e correct detection of the marker's position is essential for the next motion evaluation step. GretagMacbeth ColorChecker chart is used for color correction of the video sequences, compensation of diff erent contrast, and brightness conditions during the motion recording. Diff erent color calibration methods were compared based on linear, and cubic Hermite functions, and the multiple linear regression model. Th eir effi ciencies were evaluated from the movement analysis point of view. Th e best results were achieved with multiple linear regression model.

• MeSH
• Video Recording methods   standards   utilization   MeSH
• Color MeSH
• Diagnostic Techniques and Procedures utilization   MeSH
• Diagnostic Imaging methods   instrumentation   utilization   MeSH
• Financing, Organized MeSH
• Humans MeSH
• Linear Models MeSH
• Image Processing, Computer-Assisted methods   instrumentation   utilization   MeSH
• Movement physiology   MeSH
• Regression Analysis MeSH
• Hand physiology   MeSH
• Models, Theoretical MeSH
• Check Tag
• Humans MeSH

OBJECTIVE: Evidence suggests that the most promising results in interictal localization of the epileptogenic zone (EZ) are achieved by a combination of multiple stereo-electroencephalography (SEEG) biomarkers in machine learning models. These biomarkers usually include SEEG features calculated in standard frequency bands, but also high-frequency (HF) bands. Unfortunately, HF features require extra effort to record, store, and process. Here we investigate the added value of these HF features for EZ localization and postsurgical outcome prediction. METHODS: In 50 patients we analyzed 30 min of SEEG recorded during non-rapid eye movement sleep and tested a logistic regression model with three different sets of features. The first model used broadband features (1-500 Hz); the second model used low-frequency features up to 45 Hz; and the third model used HF features above 65 Hz. The EZ localization by each model was evaluated by various metrics including the area under the precision-recall curve (AUPRC) and the positive predictive value (PPV). The differences between the models were tested by the Wilcoxon signed-rank tests and Cliff's Delta effect size. The differences in outcome predictions based on PPV values were further tested by the McNemar test. RESULTS: The AUPRC score of the random chance classifier was .098. The models (broad-band, low-frequency, high-frequency) achieved median AUPRCs of .608, .582, and .522, respectively, and correctly predicted outcomes in 38, 38, and 33 patients. There were no statistically significant differences in AUPRC or any other metric between the three models. Adding HF features to the model did not have any additional contribution. SIGNIFICANCE: Low-frequency features are sufficient for correct localization of the EZ and outcome prediction with no additional value when considering HF features. This finding allows significant simplification of the feature calculation process and opens the possibility of using these models in SEEG recordings with lower sampling rates, as commonly performed in clinical routines.

• MeSH
• Child MeSH
• Adult MeSH
• Electroencephalography * methods   MeSH
• Epilepsy surgery   physiopathology   diagnosis   MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Drug Resistant Epilepsy surgery   physiopathology   diagnosis   MeSH
• Stereotaxic Techniques MeSH
• Treatment Outcome MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Background: Adherence to inhaled medication constitutes a major problem in patients with chronic obstructive pulmonary disease (COPD) globally. However, large studies evaluating adherence in its entirety and capturing a large variety of potentially associated factors are still lacking. Objective: To study both elementary types of adherence to chronic inhaled COPD medication in "real-life" COPD patients and to assess relationships with a wide-ranging spectrum of clinical parameters. Methods: Data from the Czech Multicentre Research Database (CMRD) of COPD, an observational prospective study, were used. Overall adherence (OA) was evaluated with Morisky Medication Adherence Scale (©MMAS-4) and adherence to an application technique (A-ApplT) with the Five Steps Assessment. Mann-Whitney U test, Spearman's correlation, and logistic regression were used to explore relationships between variables. Results: Data of 546 participants (69.6% of all patients from the CMRD) were analyzed. Two-thirds self-reported optimal OA, but only less than one-third demonstrated A-ApplT without any error. OA did not correlate with A-ApplT. Next, better OA was associated with higher education, a higher number of inhalers, a lower rate of exacerbations, poorer lung function, higher degree of upper respiratory tract symptoms (SNOT-22), absence of depressive symptoms, ex-smoking status, regular mouthwash after inhaled corticosteroids (ICS), and flu vaccination. By contrast, better A-ApplT was associated with a lower number of inhalers, better lung function, and regular mouthwash after ICS. Independent predictors of nonoptimal OA included lower degree of education, absence of flu vaccination, anemia, depression, and peptic ulcer history, whereas independent predictors of lower A-ApplT were lower education, absence of regular mouthwash after ICS, and higher COPD Assessment Test score. Conclusions: Parameters associated with OA and A-ApplT differ, and those associated with both adherence domains are sometimes associated inversely. Based on this finding, we understand these as two separate constructs with an overlap.

• Publication type
• Journal Article MeSH

Objective: To evaluate if the morphology of the mandibular symphysis is associated with the development of gingival recession. Materials and methods: A cohort of 177 patients was followed longitudinally for up to 5 years post-treatment. Based on the width of the symphysis, participants were divided into three groups: narrow (n = 57); average (n = 63), and wide symphysis (n = 57). Morphology of the symphysis and inclination of incisors were measured on lateral cephalometric radiographs before treatment (Ts), at the end of treatment (T0) and 5 years after treatment (T5). Gingival recession and the change of clinical crown heights in mandibular incisors were measured on plaster models made at TS, T0, and T5. Results: From TS to T5 the change in inclination was comparable in the narrow, average, and wide groups. At T5, gingival labial recession was present in 19.3 per cent of patients with narrow symphysis, 20.6 per cent with average symphysis, and 14 per cent of patients with wide symphysis. The difference was not significant. The mean change of clinical crown height was <1 mm (TS - T5). The regression model showed some evidence that incisor inclination at Ts might have been associated with the change of mean clinical crown height (-2.51, 95% CI: -4.6 to -0.4, P = 0.02). The logistic regression model demonstrated that H1 (Height 1) might be associated with the development of gingival recession (OR = 0.75, 95% CI: 0.58 to 0.96, P = 0.03). Conclusion: Within the limitations of this study, there is no evidence that the overall morphology of the mandibular symphysis is associated with gingival recession development.

• MeSH
• Child MeSH
• Cephalometry methods   MeSH
• Cohort Studies MeSH
• Humans MeSH
• Longitudinal Studies MeSH
• Mandible pathology   MeSH
• Adolescent MeSH
• Orthodontics, Corrective adverse effects   MeSH
• Retrospective Studies MeSH
• Incisor pathology   MeSH
• Gingival Recession etiology   pathology   MeSH
• Check Tag
• Child MeSH
• Humans MeSH
• Adolescent MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

A method for the determination of 1-hydroxypyrene in urine and hexachlorbenzene in water applying the regression triplet in the calibration procedure of chromatographic data has been applied. The detection limit and quantification limit are currently calculated on the basis of the standard deviation of replicate analyses at a single concentration. However, since the standard deviation depends on concentration, these single-concentration techniques result in limits that are directly dependent on spiking concentration. A more rigorous approach requires first careful attention to the three components of the regression triplet (data, model, method), examining (1) the data quality of the proposed model, (2) the model quality and (3) the least-squares method to be used for fulfilment of all least-squares assumptions. For high-performance liquid chromatography determination of 1-hydroxypyrene in urine and gas chromatography analysis of hexachlorbenzene in water, this paper describes the effects of deviations from five basic assumptions The paper considers the correction of deviations: identifying influential points, namely, outliers, the calibration task depends on the regression model used, and the least-squares method is based on the assumptions of the normality of the errors, homoscedasticity and the independence of errors. Results show that the approach developed provides improved estimates of analytical limits and that the single-concentration approaches currently in wide use are seriously flawed.

• MeSH
• Water Pollutants, Chemical MeSH
• Chromatography, Gas methods   instrumentation   MeSH
• Electrochemistry MeSH
• Electrons MeSH
• Financing, Organized MeSH
• Hexachlorocyclohexane analysis   MeSH
• Data Interpretation, Statistical MeSH
• Calibration MeSH
• Urine chemistry   MeSH
• Pyrenes analysis   MeSH
• Regression Analysis MeSH
• Reproducibility of Results MeSH
• Sensitivity and Specificity MeSH
• Water chemistry   MeSH
• Chromatography, High Pressure Liquid methods   instrumentation   MeSH