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Automated Algorithm (automate + algorithm)
Selected AbstractsHeart rate and QT variability in children with anxiety disorders: A preliminary reportDEPRESSION AND ANXIETY, Issue 2 2001Vikram K. Yeragani M.B.B.S. Abstract This study compared beat-to-beat heart rate and QT variability in children with anxiety disorders (n=7) and normal controls (n=15) by using an automated algorithm to compute QT intervals. An increase in QT variability appears to be associated with a higher risk for sudden cardiac death. A decrease in heart rate variability is also linked to significant cardiovascular events. Supine detrended QT variability, QT variability corrected for mean QT interval, and QTvi (a log ratio of QT variance normalized for mean QT over heart rate variability normalized for mean heart rate) were significantly higher in children with anxiety compared to controls (P<0.05). The largest Lyapunov Exponent (LLE) of heart rate time series was significantly lower (P<0.05) in children with anxiety compared to controls. These findings suggest a relative increase in sympathetic activity and a relative decrease in cardiac vagal activity in children with anxiety disorders, and are discussed in the context of the effects of tricyclics on cardiac autonomic function in children, and the rare occurrence of sudden death during tricyclic antidepressant treatment. Depression and Anxiety 13:72,77, 2001. © 2001 Wiley-Liss, Inc. [source] Increased White Matter Signal Hyperintensities in Long-Term Abstinent Alcoholics Compared with Nonalcoholic ControlsALCOHOLISM, Issue 1 2009George Fein Background:, The harmful effects of alcohol dependence on brain structure and function have been well documented, with many resolving with sufficient abstinence. White matter signal hyperintensities (WMSH) are thought to most likely be consequences secondary to the vascular (i.e., hypertension and atherosclerosis) effects of AD. We hypothesized that such effects would persist into long-term abstinence, and evaluated them in middle-aged long-term abstinent alcoholics (LTAA) compared with age and gender comparable nonalcoholic controls (NAC). Methods:, Ninety-seven participants (51 LTAA and 46 NAC) underwent cognitive, psychiatric, and structural brain magnetic resonance image evaluations. WMSH were identified and labeled as deep or periventricular by an automated algorithm developed in-house. WMSH volumes were compared between groups, and the associations of WMSH measures with demographic, alcohol use, psychiatric, and cognitive measures were examined within group. Results:, Long-term abstinent alcoholics had more WMSH than NAC. There was a significant group by age interaction, with WMSH increasing with age in LTAA, but not in NAC. Within LTAA, WMSH load was independently positively associated with alcohol burden and with age. No associations were evident between WMSH volumes and abstinence duration, family drinking history, years of education, or psychiatric or cognitive variables. Conclusion:, The magnitude of alcohol abuse was related to increased WMSH volume. The presence of an age effect in the LTAA but not the controls indicates a synergistic effect wherein alcohol advances the onset of aging-related WMSH formation. The increased WMSH load did not appear to have any significant clinical correlates, indicating that the white matter lesions in our sample may not have been severe enough to manifest as cognitive deficits. A limitation of the study is that we did not have data on the presence or severity of lifetime or current indices of vascular risk factors such as hypertension, smoking, or diabetes. [source] An algorithm to derive a numerical daily dose from unstructured text dosage instructions,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 3 2006Anoop D. Shah BSc Abstract Purpose The General Practice Research Database (GPRD) is a database of longitudinal patient records from general practices in the United Kingdom. It is an important data source for pharmacoepidemiology studies, but until now it has been tedious to calculate the daily dose and duration of exposure to drugs prescribed. This is because general practitioners routinely record dosage instructions as free text rather than in a structured way. The objective was to develop and assess the validity of an automated algorithm to derive the daily dose from text dosage instructions. Methods A computer program was developed to derive numerical information from unstructured text dosage instructions. It was tested on dosage texts from a random sample of one million prescription entries. A random sample of 1000 of these converted texts were manually checked for their accuracy. Results Out of the sample of one million prescription entries, 74.5% had text containing the daily dose, 14.5% had text but did not include a quantitative daily dose statement and 11.0% had no text entered. Of the 1000 texts which were checked manually, 767 stated the daily dose. The program interpreted 758 (98.8%) of these correctly, produced errors in four cases and failed to extract the dose from five texts. Conclusions An automated algorithm has been developed which can accurately extract the daily dose from almost 99% of general practitioners' text dosage instructions. It increases the utility of GPRD and other prescription data sources by enabling researchers to estimate the duration of drug exposure more efficiently. Copyright © 2005 John Wiley & Sons, Ltd. [source] An efficient computational approach for prior sensitivity analysis and cross-validationTHE CANADIAN JOURNAL OF STATISTICS, Issue 1 2010Luke Bornn Abstract Prior sensitivity analysis and cross-validation are important tools in Bayesian statistics. However, due to the computational expense of implementing existing methods, these techniques are rarely used. In this paper, the authors show how it is possible to use sequential Monte Carlo methods to create an efficient and automated algorithm to perform these tasks. They apply the algorithm to the computation of regularization path plots and to assess the sensitivity of the tuning parameter in g -prior model selection. They then demonstrate the algorithm in a cross-validation context and use it to select the shrinkage parameter in Bayesian regression. The Canadian Journal of Statistics 38:47,64; 2010 © 2010 Statistical Society of Canada La sensibilité à la loi a priori et la validation croisée sont des outils importants des statistiques bayésiennes. Toutefois, ces techniques sont rarement utilisées en pratique car les méthodes disponibles pour les implémenter sont numériquement très coûteuses. Dans ce papier, les auteurs montrent comment il est possible d'utiliser les méthodes de Monte Carlo séquentielles pour obtenir un algorithme efficace et automatique pour implémenter ces techniques. Ils appliquent cet algorithme au calcul des chemins de régularisation pour un problème de régression et à la sensibilité du paramètre de la loi a priori de Zellner pour un problème de sélection de variables. Ils appliquent ensuite cet algorithme pour la validation croisée et l'utilisent afin de sélectionner le paramètre de régularisation dans un problème de régression bayésienne. La revue canadienne de statistique 38: 47,64; 2010 © 2010 Société statistique du Canada [source] Altered Interatrial Conduction Detected in MADIT II Patients Bound to Develop Atrial FibrillationANNALS OF NONINVASIVE ELECTROCARDIOLOGY, Issue 3 2009Fredrik Holmqvist M.D., Ph.D. Background: Changes in P-wave morphology have recently been shown to be associated with interatrial conduction route used, without noticeable changes of P-wave duration. This study aimed at exploring the association between P-wave morphology and future atrial fibrillation (AF) development in the Multicenter Automatic Defibrillator Trial II (MADIT II) population. Methods: Patients included in MADIT-II without a history of AF with sinus rhythm at baseline who developed AF during the study ("Pre-AF") were compared to matched controls without AF development ("No-AF"). Patients were followed for a mean of 20 months. A 10-minute high-resolution bipolar ECG recording was obtained at baseline. Signal-averaged P waves were analyzed to determine orthogonal P-wave morphology, P-wave duration, and RMS20. The P-wave morphology was subsequently classified into one of three predefined types using an automated algorithm. Results: Thirty patients (age 68 ± 7 years) who developed AF during MADIT-II were compared with 60 patients (age 68 ± 8 years) who did not. P-wave duration and RMS20 in the Pre-AF group was not significantly different from the No-AF group (143 ± 21 vs 139 ± 30 ms, P = 0.26, and 2.0 ± 1.3 vs 2.1 ± 1.0 ,V, P = 0.90). The distribution of P-wave morphologies was shifted away from Type 1 in the Pre-AF group when compared to the No-AF group (Type 1/2/3/atypical; 25/60/0/15% vs 10/63/10/17%, P = 0.04). Conclusions: This study is the first to describe changes in P-wave morphology in patients prior to AF development. The results indicate that abnormal interatrial conduction may play a role in AF development in patients with prior myocardial infarction and congestive heart failure. [source] | ||||||||||