Patterns of cerebral glucose metabolism detected with positron emission tomography differ in multiple system atrophy and olivopontocerebellar atrophy

We used positron emission tomography with [ 18 F] fluorodeoxyglucose to study local cerebral metabolic rates for glucose (ICMRglc) in patients with multiple system atrophy (MSA), sporadic olivopontocerebellar atrophy (sOPCA), and dominantly inherited olivopontocerebellar atrophy (dOPCA) in comparison with normal control subjects. In MSA, absolute lCMRglc was significantly decreased in the brainstem, cerebellum, putamen, thalamus, and cerebral cortex. In sOPCA, absolute lCMRglc was significantly decreased in the brainstem, cerebellum, putamen, thalamus, and cerebral cortex. In dOPCA, absolute lCMRglc was significantly decreased in the brainstem and cerebellum but not in the other structures. Examination of lCMRglc normalized to the cerebral cortex in comparison with normal controls revealed in MSA significant decreases in the brainstem, cerebellum, and putamen but, in both sOPCA and dOPCA, significant decreases only in the brainstem and cerebellum. The findings indicate that these three disorders all show a marked decrease of lCMRglc in the brainstem and cerebellum but differ in the degree of hypometabolism in forebrain and cerebral cortical structures. The results are consistent with the possibility that, in many cases, sOPCA will evolve into MSA. Moreover, positron emission tomography may provide helpful diagnostic information in these neurodegenerative diseases.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/50356/1/410360208_ftp.pd

Development and Reporting of Prediction Models: Guidance for Authors From Editors of Respiratory, Sleep, and Critical Care Journals

Prediction models aim to use available data to predict a health state or outcome that has not yet been observed. Prediction is primarily relevant to clinical practice, but is also used in research, and administration. While prediction modeling involves estimating the relationship between patient factors and outcomes, it is distinct from casual inference. Prediction modeling thus requires unique considerations for development, validation, and updating. This document represents an effort from editors at 31 respiratory, sleep, and critical care medicine journals to consolidate contemporary best practices and recommendations related to prediction study design, conduct, and reporting. Herein, we address issues commonly encountered in submissions to our various journals. Key topics include considerations for selecting predictor variables, operationalizing variables, dealing with missing data, the importance of appropriate validation, model performance measures and their interpretation, and good reporting practices. Supplemental discussion covers emerging topics such as model fairness, competing risks, pitfalls of “modifiable risk factors”, measurement error, and risk for bias. This guidance is not meant to be overly prescriptive; we acknowledge that every study is different, and no set of rules will fit all cases. Additional best practices can be found in the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) guidelines, to which we refer readers for further details

Diabetic polyneuropathies: update on research definition, diagnostic criteria and estimation of severity

Prior to a joint meeting of the Neurodiab Association and International Symposium on Diabetic Neuropathy held in Toronto, Ontario, Canada, 13‐18 October 2009, Solomon Tesfaye, Sheffield, UK, convened a panel of neuromuscular experts to provide an update on polyneuropathies associated with diabetes (Toronto Consensus Panels on DPNs, 2009). Herein, we provide definitions of typical and atypical diabetic polyneuropathies (DPNs), diagnostic criteria, and approaches to diagnose sensorimotor polyneuropathy as well as to estimate severity. Diabetic sensorimotor polyneuropathy (DSPN), or typical DPN, usually develops on long‐standing hyperglycaemia, consequent metabolic derangements and microvessel alterations. It is frequently associated with microvessel retinal and kidney disease—but other causes must be excluded. By contrast, atypical DPNs are intercurrent painful and autonomic small‐fibre polyneuropathies. Recognizing that there is a need to detect and estimate severity of DSPN validly and reproducibly, we define subclinical DSPN using nerve conduction criteria and define possible, probable, and confirmed clinical levels of DSPN. For conduct of epidemiologic surveys and randomized controlled trials, it is necessary to pre‐specify which attributes of nerve conduction are to be used, the criterion for diagnosis, reference values, correction for applicable variables, and the specific criterion for DSPN. Herein, we provide the performance characteristics of several criteria for the diagnosis of sensorimotor polyneuropathy in healthy subject‐ and diabetic subject cohorts. Also outlined here are staged and continuous approaches to estimate severity of DSPN. Copyright © 2011 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87100/1/1226_ftp.pd