11 research outputs found
Antiseizure medication withdrawal risk estimation and recommendations: A survey of American Academy of Neurology and EpiCARE members
Objective
Choosing candidates for antiseizure medication (ASM) withdrawal in wellâcontrolled epilepsy is challenging. We evaluated (a) the correlation between neurologists' seizure risk estimation (âclinician predictionsâ) vs calculated predictions, (b) how viewing calculated predictions influenced recommendations, and (c) barriers to using risk calculation.MethodsWe asked US and European neurologists to predict 2âyear seizure risk after ASM withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before vs after viewing calculated predictions, using generalized linear models.
Results
Threeâhundred and fortyâsix neurologists responded. There was moderate correlation between clinician and calculated predictions (Spearman coefficient 0.42). Clinician predictions varied widely, for example, predictions ranged 5%â100% for a 2âyear seizureâfree adult without epileptiform abnormalities. Mean clinician predictions exceeded calculated predictions for vignettes with epileptiform abnormalities (eg, childhood absence epilepsy: clinician 65%, 95% confidence interval [CI] 57%â74%; calculated 46%) and surgical vignettes (eg, focal cortical dysplasia 6âmonth seizureâfree mean clinician 56%, 95% CI 52%â60%; calculated 28%). Clinicians overestimated the influence of epileptiform EEG findings on withdrawal risk (26%, 95% CI 24%â28%) compared with calculators (14%, 95% 13%â14%). Viewing calculated predictions slightly reduced willingness to withdraw (â0.8/10 change, 95% CI â1.0 to â0.7), particularly for vignettes without epileptiform abnormalities. The greatest barrier to calculator use was doubting its accuracy (44%).
Significance
Clinicians overestimated the influence of abnormal EEGs particularly for lowârisk patients and overestimated risk and the influence of seizureâfree duration for surgical patients, compared with calculators. These data may question widespread ordering of EEGs or timeâbased seizureâfree thresholds for surgical patients. Viewing calculated predictions reduced willingness to withdraw particularly without epileptiform abnormalities
Accuracy of ultrasound vs computed tomography scan for upper urinary tract malignancies and development of a risk-based diagnostic algorithm for haematuria in a UK tertiary centre
Understanding the retinal basis of vision across species
The vertebrate retina first evolved some 500 million years ago in ancestral marine chordates. Since then, the eyes of different species have been tuned to best support their unique visuoecological lifestyles. Visual specializations in eye designs, large-scale inhomogeneities across the retinal surface and local circuit motifs mean that all species' retinas are unique. Computational theories, such as the efficient coding hypothesis, have come a long way towards an explanation of the basic features of retinal organization and function; however, they cannot explain the full extent of retinal diversity within and across species. To build a truly general understanding of vertebrate vision and the retina's computational purpose, it is therefore important to more quantitatively relate different species' retinal functions to their specific natural environments and behavioural requirements. Ultimately, the goal of such efforts should be to build up to a more general theory of vision
Bullying Panel
This panel will push the boundaries of typical bullying prevention and propose fresh ideas for solutions in schools. Bullying prevention is one of the most pressing topics in education today. With many instances of school violence linked to bullying, schools are actively seeking practical solutions that can curtail this epidemic
Antiseizure medication withdrawal risk estimation and recommendations: A survey of American Academy of Neurology and EpiCARE members
Abstract Objective Choosing candidates for antiseizure medication (ASM) withdrawal in wellâcontrolled epilepsy is challenging. We evaluated (a) the correlation between neurologists' seizure risk estimation (âclinician predictionsâ) vs calculated predictions, (b) how viewing calculated predictions influenced recommendations, and (c) barriers to using risk calculation. Methods We asked US and European neurologists to predict 2âyear seizure risk after ASM withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before vs after viewing calculated predictions, using generalized linear models. Results Threeâhundred and fortyâsix neurologists responded. There was moderate correlation between clinician and calculated predictions (Spearman coefficient 0.42). Clinician predictions varied widely, for example, predictions ranged 5%â100% for a 2âyear seizureâfree adult without epileptiform abnormalities. Mean clinician predictions exceeded calculated predictions for vignettes with epileptiform abnormalities (eg, childhood absence epilepsy: clinician 65%, 95% confidence interval [CI] 57%â74%; calculated 46%) and surgical vignettes (eg, focal cortical dysplasia 6âmonth seizureâfree mean clinician 56%, 95% CI 52%â60%; calculated 28%). Clinicians overestimated the influence of epileptiform EEG findings on withdrawal risk (26%, 95% CI 24%â28%) compared with calculators (14%, 95% 13%â14%). Viewing calculated predictions slightly reduced willingness to withdraw (â0.8/10 change, 95% CI â1.0 to â0.7), particularly for vignettes without epileptiform abnormalities. The greatest barrier to calculator use was doubting its accuracy (44%). Significance Clinicians overestimated the influence of abnormal EEGs particularly for lowârisk patients and overestimated risk and the influence of seizureâfree duration for surgical patients, compared with calculators. These data may question widespread ordering of EEGs or timeâbased seizureâfree thresholds for surgical patients. Viewing calculated predictions reduced willingness to withdraw particularly without epileptiform abnormalities
Structure/function of the inhibition of human 3ÎČ-hydroxysteroid dehydrogenase type 1 and type 2 by trilostane
The functions of key residues in the inhibitor, substrate and cofactor sites of human 3ÎČ-hydroxysteroid dehydrogenase type 1 are validated by mutagenesis
Examining affect and perfectionism in relation to eating disorder symptoms among women with anorexia nervosa
This study examined personality and affective variables in relation to eating disorder symptoms in anorexia nervosa (AN). Women (N=118) with DSM-IV AN completed baseline questionnaires (Beck Depression Inventory, Frost Multidimensional Perfectionism Scale) and interviews (Eating Disorder Examination, Yale-Brown-Cornell Eating Disorder Scale), followed by two weeks of ecological momentary assessment (EMA) involving multiple daily reports of affective states and eating disorder behaviors. Hierarchical regression analyses were conducted using eating disorder symptoms as dependent variables (i.e., EMA binge eating, EMA self-induced vomiting, eating disorder rituals, eating disorder preoccupations, dietary restraint). Predictor variables were maladaptive perfectionism (baseline), depressive symptoms (baseline), and affect lability (EMA). Results revealed that affect lability was independently associated with binge eating, whereas depressive symptoms were independently associated with self-induced vomiting. Depressive symptoms were independently associated with eating disorder rituals, whereas both depressive symptoms and maladaptive perfectionism were independently associated with eating disorder preoccupations. Finally, maladaptive perfectionism and affect lability were both independently associated with dietary restraint. This pattern of findings suggests the importance of affective and personality constructs in relation to eating disorder symptoms in AN and may highlight the importance of targeting these variables in the context of treatment