See Morris and Weil (doi: ) for a scientific commentary on this article. In a prospective multicentre study involving 1280 patients with idiopathic RBD, Postuma et al. show that approximately 6% of patients each year (>73.5% over 12 years) convert to full neurodegenerative disease. They test the predictive power of 21 prodromal markers of neurodegeneration, providing a template for planning neuroprotective trials.

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Our study highlights the potential utility of PA and IR as markers to identify patients with low muscularity who may benefit from early and rigorous intervention.

BACKGROUND:Skeletal muscle mass decreases in end-stage heart failure and is predictive of clinical outcomes in several disease states. Skeletal muscle attenuation and quantity as quantified on preoperative chest computed tomographic scans may be predictive of mortality after continuous flow (CF) left ventricular assist device (LVAD) implantation. METHODS AND RESULTS:A single-center continuous flow-LVAD database (n=354) was used to identify patients with chest computed tomographies performed in the 3 months before LVAD implantation (n=143). Among patients with computed tomography data available, unilateral pectoralis muscle mass indexed to body surface area and attenuation (approximated by mean Hounsfield units [PHU m ]) were measured in each patient with a high intrarater and inter-rater reliability (intraclass correlation coefficients 0.98 and 0.97, respectively). Multivariate Cox regression analyses were performed, censoring at cardiac transplantation, to assess the impact of preoperative pectoralis muscle index and pectoralis muscle mean Hounsfield unit on survival after LVAD implantation. Each unit increase in pectoralis muscle index was associated with a 27% reduction in the hazard of death after LVAD (adjusted hazard ratio, 0.73; 95% confidence interval, 0.58-0.92; P=0.007). Each 5-U increase in pectoralis muscle mean Hounsfield unit was associated with a 22% reduction in the hazard of death after LVAD (adjusted hazard ratio, 0.78; 95% confidence interval, 0.68-0.89; P<0.0001). Pectoralis muscle index and pectoralis muscle mean Hounsfield unit outperformed other traditional measures in the data set, including the HeartMate II risk score. CONCLUSIONS:Pectoralis muscle size and attenuation were powerful predictors of outcomes after LVAD implantation in this data set. This one time, repeatable, internal assessment of patient substrate added valuable prognostic information that was not available on standard preoperative testing.

This multilanguage study used simple speech recording and high-end pattern analysis to provide sensitive and reliable noninvasive biomarkers of prodromal versus manifest α-synucleinopathy in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and early-stage Parkinson disease (PD). Methods: We performed a multicenter study across the Czech, English, German, French, and Italian languages at 7 centers in Europe and North America. A total of 448 participants (337 males), including 150 with iRBD (mean duration of iRBD across language groups 0.5-3.4 years), 149 with PD (mean duration of disease across language groups 1.7-2.5 years), and 149 healthy controls were recorded; 350 of the participants completed the 12-month follow-up. We developed a fully automated acoustic quantitative assessment approach for the 7 distinctive patterns of hypokinetic dysarthria. Results: No differences in language that impacted clinical parkinsonian phenotypes were found. Compared with the controls, we found significant abnormalities of an overall acoustic speech severity measure via composite dysarthria index for both iRBD (p = 0.002) and PD (p < 0.001). However, only PD (p < 0.001) was perceptually distinct in a blinded subjective analysis. We found significant group differences between PD and controls for monopitch (p < 0.001), prolonged pauses (p < 0.001), and imprecise consonants (p = 0.03); only monopitch was able to differentiate iRBD patients from controls (p = 0.004). At the 12-month follow-up, a slight progression of overall acoustic speech impairment was noted for the iRBD (p = 0.04) and PD (p = 0.03) groups. Interpretation: Automated speech analysis might provide a useful additional biomarker of parkinsonism for the assessment of disease progression and therapeutic interventions.

ObjectiveTo determine whether REM sleep without atonia (RSWA) during polysomnography (PSG) predicts phenoconversion in patients with idiopathic REM sleep behavior disorder (iRBD), a prodromal feature of a neurodegenerative disease.MethodsWe analyzed RSWA in 60 patients with iRBD, including manual phasic, tonic, and any muscle activity in the submentalis and anterior tibialis muscles and the automated REM atonia index in the submentals. We identified patients who developed parkinsonism or mild cognitive impairment (MCI) during at least 3 years of follow-up after PSG. Kaplan-Meier analysis was performed and receiver operator curves were calculated to determine RSWA cutoffs predicting faster phenoconversion.ResultsTwenty-six (43%) patients developed parkinsonism (n = 17) or MCI (n = 9). Phenoconverters were older at iRBD diagnosis (p = 0.02). Median time to phenoconversion was 3.9 ± 2.5 years. iRBD phenoconverters had significantly more RSWA at diagnosis. Phenoconversion risk from iRBD diagnosis was 20% and 35% at 3 and 5 years, respectively, with greater risk in patients with iRBD with >46.4% any combined RSWA, which increased further to 30% and 55% at 3 and 5 years for patients >65 years of age at diagnosis.ConclusionsPatients with iRBD with higher amounts of polysomnographic RSWA had a greater risk of developing Parkinson disease or MCI. Patients with older age and higher RSWA amounts had more rapid phenoconversion than younger patients with RBD. Our study suggests that RSWA is a potential biomarker for risk stratification of iRBD phenoconversion that could facilitate prognostication for patients with iRBD.Classification of evidenceThis study provides Class II evidence that for patients with iRBD, increased RSWA correlates with increased risk for developing parkinsonism or MCI.

The Academy/ASPEN Consensus and the PG-SGA were in good agreement. It is unclear whether PA and IR can be used as surrogate markers of nutrition status or muscle loss.

Assessment of body composition, both at single time points and longitudinally, is particularly important in clinical nutrition practice. It provides a means for the clinician to characterize nutrition status at a single time point, aiding in the identification and diagnosis of malnutrition, and to monitor changes over time by providing real-time information on the adequacy of nutrition interventions. Objective body composition measurement tools are available clinically but are often underused in nutrition care, particularly in the United States. This is, in part, due to a number of factors concerning their use in a clinical context: cost and accessibility of equipment, as well as interpretability of the results. This article focuses on the factors influencing interpretation of results in a clinical setting. Body composition assessment, regardless of the method, is inherently limited by its indirect nature. Therefore, an understanding of the strengths and limitations of any method is essential for meaningful interpretation of its results. This review provides an overview of body composition technologies available clinically (computed tomography, dual-energy x-ray absorptiometry, bioimpedance, ultrasound) and discusses the strengths and limitations of each device.