Impact of premorbid undernutrition on outcome in stroke patients

Background and Purpose - To assess the prevalence of premorbid undernutrition and its impact on outcomes 1 month after stroke. Methods - The study recruited from consecutive stroke admissions during a 10-month period. Premorbid nutritional status ( using the subjective global assessment [SGA]), premorbid functioning ( modified Rankin scale [MRS]), and stroke severity ( National Institutes of Health Stroke Scale [NIHSS] score) were assessed at admission. The associations between premorbid nutritional status, poor outcome ( defined as MRS greater than or equal to 3), and mortality were examined before and after adjustment for confounding variables, including age, gender, stroke risk factors, stroke severity, and admission serum albumin. Results - Thirty of 185 patients were assessed as having undernutrition at admission. Significant unadjusted associations were observed between undernutrition and poor outcome (odds ratio [OR], 3.4; 95% CI, 1.3 to 8.7; P = 0.01), and mortality (OR, 3.1, 95% CI, 1.3 to 7.7; P = 0.02) at 1 month. NIHSS, age, and premorbid MRS were also significantly associated with poor outcomes. After adjustment for these factors, the effect size of associations remained important but not significant ( poor outcome: OR, 2.4; 95% CI, 0.7 to 9.0, P = 0.18; mortality: OR, 3.2; 95% CI, 1.0 to 10.4, P = 0.05). Conclusions - Premorbid undernutrition, as assessed using the SGA, appears to be an independent predictor of poor stroke outcome. Stroke prevention strategies should target undernutrition in the population at risk for stroke to improve outcomes.

Assessment of disease progression in motor neuron disease

Motor neuron disease (MND) is characterised by progressive deterioration of the corticospinal tract, brainstem, and anterior horn cells of the spinal cord. There is no pathognomonic test for the diagnosis of MND, and physicians rely on clinical criteria-upper and lower motor neuron signs-for diagnosis. The presentations, clinical phenotypes, and outcomes of MND are diverse and have not been combined into a marker of disease progression. No single algorithm combines the findings of functional assessments and rating scales, such as those that assess quality of life, with biological markers of disease activity and findings from imaging and neurophysiological assessments. Here, we critically appraise developments in each of these areas and discuss the potential of such measures to be included in the future assessment of disease progression in patients with MND.

Guidelines for filming digital camera video clips for the assessment of gait and movement disorders by teleneurology

Digital still cameras capable of filming short video clips are readily available, but the quality of these recordings for telemedicine has not been reported. We performed a blinded study using four commonly available digital cameras. A simulated patient with a hemiplegic gait pattern was filmed by the same videographer in an identical, brightly lit indoor setting. Six neurologists viewed the blinded video clips on their PC and comparisons were made between cameras, between video clips recorded with and without a tripod, and between video clips filmed on high- or low-quality settings. Use of a tripod had a smaller effect than expected, while images taken on a high-quality setting were strongly preferred to those taken on a low-quality setting. Although there was some variability in video quality between selected cameras, all were of sufficient quality to identify physical signs such as gait and tremor. Adequate-quality video clips of movement disorders can be produced with low-cost cameras and transmitted by email for teleneurology purposes.

The effect of admission physiological variables on 30 day outcome after stroke

Introduction. Potentially modifiable physiological variables may influence stroke prognosis but their independence from modifiable factors remains unclear. Methods. Admission physiological measures (blood pressure, heart rate, temperature and blood glucose) and other unmodifiable factors were recorded from patients presenting within 48 hours of stroke. These variables were compared with the outcomes of death and death or dependency at 30 days in multivariate statistical models. Results. In the 186 patients included in the study, age, atrial fibrillation and the National Institutes of Health Stroke Score were identified as unmodifiable factors independently associated with death and death or dependency. After adjusting for these factors, none of the physiological variables were independently associated with death, while only diastolic blood pressure (DBP) >= 90 mmHg was associated with death or dependency at 30 days (p = 0.02). Conclusions. Except for elevated DBP, we found no independent associations between admission physiology and outcome at 30 days in an unselected stroke cohort. Future studies should look for associations in subgroups, or by analysing serial changes in physiology during the early post-stroke period.

Circadian blood pressure variation after acute stroke

We aimed to characterise the patterns of circadian blood pressure (BP) variation after acute stroke and determine whether any relationship exists between these patterns and stroke outcome. BP was recorded manually every 4 h for 48 h following acute stroke. Patients were classified according to the percentage fall in mean systolic BP (SBP) at night compared to during the day as: dippers (fall >= 10-= 20%); non-dippers (>= 0-

Motor unit number estimation - A Bayesian approach

All muscle contractions are dependent on the functioning of motor units. In diseases such as amyotrophic lateral sclerosis (ALS), progressive loss of motor units leads to gradual paralysis. A major difficulty in the search for a treatment for these diseases has been the lack of a reliable measure of disease progression. One possible measure would be an estimate of the number of surviving motor units. Despite over 30 years of motor unit number estimation (MUNE), all proposed methods have been met with practical and theoretical objections. Our aim is to develop a method of MUNE that overcomes these objections. We record the compound muscle action potential (CMAP) from a selected muscle in response to a graded electrical stimulation applied to the nerve. As the stimulus increases, the threshold of each motor unit is exceeded, and the size of the CMAP increases until a maximum response is obtained. However, the threshold potential required to excite an axon is not a precise value but fluctuates over a small range leading to probabilistic activation of motor units in response to a given stimulus. When the threshold ranges of motor units overlap, there may be alternation where the number of motor units that fire in response to the stimulus is variable. This means that increments in the value of the CMAP correspond to the firing of different combinations of motor units. At a fixed stimulus, variability in the CMAP, measured as variance, can be used to conduct MUNE using the "statistical" or the "Poisson" method. However, this method relies on the assumptions that the numbers of motor units that are firing probabilistically have the Poisson distribution and that all single motor unit action potentials (MUAP) have a fixed and identical size. These assumptions are not necessarily correct. We propose to develop a Bayesian statistical methodology to analyze electrophysiological data to provide an estimate of motor unit numbers. Our method of MUNE incorporates the variability of the threshold, the variability between and within single MUAPs, and baseline variability. Our model not only gives the most probable number of motor units but also provides information about both the population of units and individual units. We use Markov chain Monte Carlo to obtain information about the characteristics of individual motor units and about the population of motor units and the Bayesian information criterion for MUNE. We test our method of MUNE on three subjects. Our method provides a reproducible estimate for a patient with stable but severe ALS. In a serial study, we demonstrate a decline in the number of motor unit numbers with a patient with rapidly advancing disease. Finally, with our last patient, we show that our method has the capacity to estimate a larger number of motor units.