Heart rate variability (HRV) is commonly used to assess autonomic functions and responses to environmental stimuli. It is usually derived from electrocardiographic signals; however, in the last few ...years, photoplethysmography has been successfully used to evaluate beat-to-beat time intervals and to assess changes in the human heart rate under several conditions. The present work describes a simple design of a photoplethysmograph, using a wearable earlobe sensor. Beat-to-beat time intervals were evaluated as the time between subsequent pulses, thus generating a signal representative of heart rate variability, which was compared to RR intervals from classic electrocardiography. Twenty-minute pulse photoplethysmography and ECG recordings were taken simultaneously from 10 healthy individuals. Ten additional subjects were recorded for 24 h. Comparisons were made of raw signals and on time-domain and frequency-domain HRV parameters. There were small differences between the inter-beat intervals evaluated with the two techniques. The current findings suggest that our wearable earlobe pulse photoplethysmograph may be suitable for short and long-term home measuring and monitoring of HRV parameters.
Parkinson's disease (PD), a progressive neurodegenerative disease, can be misdiagnosed with atypical conditions such as Progressive Supranuclear Paralysis (PSP) due to overlapping clinical features. ...MicroRNAs (miRNAs) are small non-coding RNAs with a key role in post-transcriptional gene regulation. The aim was to identify a set of differential exosomal miRNAs biomarkers, which may aid in diagnosis.
We analyzed the serum level of 188 miRNAs in a discovery set, by using RTqPCR based TaqMan assay, in a small cohort of healthy controls, PD and PSP patients. Subsequently, the differentially expressed miRNAs, between PSP and PD patients, were further tested in a larger and independent cohort of 33 healthy controls, 40 PD and 20 PSP patients. The most accurate diagnostic exosomal miRNAs classifiers were identified in a logistic regression model.
A statistically significant set of three exosomal miRNAs: miR-21-3p, miR-22-3p and miR-223-5p, discriminated PD from HC (area under the curve of 0.75), and a set of three exosomal miRNAs, miR-425-5p, miR-21-3p, and miR-199a-5p, discriminated PSP from PD with good diagnostic accuracy (area under the curve of 0.86). Finally, the classifier that best discriminated PSP from PD consisted of six exosomal miRNAs (area under the curve = 0.91), with diagnostic sensitivity and specificity of 0.89 and 0.90, respectively.
Based on our analysis, these data showed that exosomal miRNAs could act as biomarkers to differentiate between PSP and PD.
•Non-invasive miRNA-based tests could be used for differential diagnosis.•Exosomal microRNAs (miRNAs) in serum are promising biomarker candidates for PSP.•Serum samples were analyzed with RT-qPCR to measure levels of selected miRNAs.•Differential miRNAs were dysregulated between patients groups and healthy controls.
Differentiating clinically progressive supranuclear palsy-parkinsonism (PSP-P) from Parkinson's disease (PD) may be challenging, especially in the absence of vertical supranuclear gaze palsy (VSGP). ...The Magnetic Resonance Parkinsonism Index (MRPI) has been reported to accurately distinguish between PSP and PD, yet few data exist on the usefulness of this biomarker for the differentiation of PSP-P from PD.
Thirty-four patients with PSP-P, 46 with PSP-Richardson's syndrome (PSP-RS), 53 with PD, and 53 controls were enrolled. New consensus criteria for the clinical diagnosis of PSP were used as the reference standard. The MRPI, and a new index termed MRPI 2.0 including the measurement of the third ventricle width (MRPI multiplied by third ventricle width/frontal horns width ratio), were calculated on T1-weighted MR images.
The MRPI differentiated patients with PSP-P from those with PD with sensitivity and specificity of 73.5% and 98.1%, respectively, while the MRPI 2.0 showed higher sensitivity (100%) and similar specificity (94.3%) in differentiating between these two groups. Both biomarkers showed excellent performance in differentiating PSP-P patients with VSGP from those with PD, but the MRPI 2.0 was much more accurate (95.8%) than MRPI in differentiating PSP-P patients with slowness of vertical saccades from PD patients.
The MRPI 2.0 accurately differentiated PSP-P patients from those with PD. This new index was more powerful than MRPI in differentiating PSP patients in the early stage of the disease with slowness of vertical saccades from patients with PD, thus helping clinicians to consolidate the diagnosis based on clinical features, in vivo.
•Distinguishing PSP-P from PD is challenging in the early stages of the disease.•Few data exist on the usefulness of MRPI for diagnosing PSP-P patients.•MRPI 2.0 is a new version of MRPI which includes the 3rd ventricular width.•MRPI 2.0 accurately differentiated patients with PSP-P from those with PD.•MRPI 2.0 accurately diagnosed PSP-P in the absence of vertical ocular palsy.
Background
Rest tremor (RT) can be observed in several positions (seated, standing, lying down) but it is unknown whether the tremor features may vary across them. This study aimed to compare the RT ...electrophysiological features across different positions in tremor-dominant Parkinson’s disease (PD) and essential tremor plus (ET with RT, rET).
Methods
We consecutively enrolled 90 tremor-dominant PD and 24 rET patients. The RT presence was evaluated in three positions: with the patient seated, the arm flexed at 90°, the forearm supported against gravity, and the hand hanging down from the chair armrest (hand-hanging position), in lying down supine and in standing position. RT electrophysiological features (amplitude, frequency, burst duration, pattern) were compared between the two patient groups and across the different positions.
Results
All PD and rET patients showed RT in hand-hanging position. Supine and standing RT were significantly more common in PD (67.8% and 75.6%, respectively) than in rET patients (37.5% and 45.8%, respectively). RT amplitude, frequency and pattern were significantly different between groups in hand-hanging position whereas only pattern was significantly different between PD and rET in both standing and supine positions. In each patient group, all RT electrophysiological features did not significantly vary across different recording positions (
p
> 0.05).
Discussion
In our study, PD and rET showed RT in hand-hanging, supine, and standing positions. RT pattern was the only electrophysiological feature significantly different between PD and rET patients in all these positions, enabling clinicians to perform the RT analysis for diagnostic purposes in different tremor positions.
Tremor is an impairing symptom associated with several neurological diseases. Some of such diseases are neurodegenerative, and tremor characterization may be of help in differential diagnosis. To ...date, electromyography (EMG) is the gold standard for the analysis and diagnosis of tremors. In the last decade, however, several studies have been conducted for the validation of different techniques and new, non-invasive, portable, or even wearable devices have been recently proposed as complementary tools to EMG for a better characterization of tremors. Such devices have proven to be useful for monitoring the efficacy of therapies or even aiding in differential diagnosis. The aim of this review is to present systematically such new solutions, trying to highlight their potentialities and limitations, with a hint to future developments.
Background
The R2 component of blink reflex recovery cycle (R2BRrc) is a simple neurophysiological tool to detect the brainstem hyperexcitability commonly occurring in several neurological diseases ...such as Parkinson’s disease and atypical parkinsonisms. In our study, we investigated for the first time the usefulness of R2BRrc to assess brainstem excitability in patients with idiopathic Normal Pressure Hydrocephalus (iNPH) in comparison with healthy subjects.
Methods
Eighteen iNPH patients and 25 age-matched control subjects were enrolled. R2BRrc was bilaterally evaluated at interstimulus intervals (ISIs) of 100, 150, 200, 300, 400, 500 and 750 ms in all participants. We investigated the diagnostic performance of R2BRrc in differentiating iNPH patients from control subjects using ROC analysis. Midbrain area and Magnetic Resonance Hydrocephalic Index (MRHI), an MRI biomarker for the diagnosis of iNPH, were measured on T1-weighted MR images, and correlations between R2BRrc values and MRI measurements were investigated.
Results
Fourteen (78%) of 18 iNPH patients showed an enhanced R2BRrc at ISIs 100–150–200 ms, while no control subjects had abnormal R2BRrc. The mean amplitude of bilateral R2BRrc at the shortest ISIs (100–150–200 ms) showed high accuracy in differentiating iNPH patients from controls (AUC = 0.89). R2BRrc values significantly correlated with midbrain area and MRHI values.
Conclusions
This study represents the first evidence of brainstem hyperexcitability in iNPH patients. Given its low cost and wide availability, R2BRrc could be a useful tool for selecting elderly subjects with mild gait and urinary dysfunction who should undergo an extensive diagnostic workup for the diagnosis of NPH.
We investigated the disease progression rate in patients with progressive supranuclear palsy-Richardson syndrome (PSP-RS) and PSP-parkinsonism (PSP-P) in comparison with Parkinson disease (PD) ...patients, using MRPI (Magnetic Resonance Parkinsonism Index), and MRPI 2.0.
Fifteen PSP-RS patients (disease duration, y, mean ± SD: 2.5 ± 1.1), 16 PSP-P patients (disease duration, y, mean ± SD: 6.5 ± 3.2) and 19 PD patients (disease duration, y, mean ± SD: 3.2 ± 2.3) were enrolled. All patients underwent clinical assessment and MRI at baseline, 1-year, and 2-year follow-up. MRPI, MRPI 2.0 and clinical scores over 1 and 2-years were used to evaluate disease progression rate, and to calculate sample sizes required to power placebo-controlled trials.
All groups showed increased clinical motor scores over time whereas only PSP groups had increased MRPI and MRPI 2.0 values over T1 and T2 intervals. The percentage increase over 1 and 2-years of MRPI and MRPI 2.0 values was significantly higher in PSP groups than in PD group, and in PSP-RS than in PSP-P patients while no difference between patient groups was observed when clinical motor scores were considered. Sample size estimates showed that MRPI 2.0 performed better than MRPI and clinical scales. Treatment trials with MRPI 2.0 could be performed over 2-years both in PSP-RS and PSP-P with a sample size per treatment arm of 89 and 170 patients, respectively.
Our results demonstrate that MRPI 2.0 was more powerful than MRPI and clinical motor scales in evaluating PSP progression, and in providing the best sample size estimates for clinical trials.
•MRPI and MRPI 2.0 detected disease progression in PSP patients.•MRPI 2.0 was more powerful than MRPI and motor scales in detecting PSP progression.•MRPI 2.0 was the best measure for assessing sample size for clinical trials.
To evaluate circadian fluctuations and night/day ratio of Heart Rate Variability (HRV) spectral components in patients with obstructive sleep apnea (OSA) in comparison with controls.
This is a ...simultaneous HRV-polysomnographic (PSG) study including 29 patients with OSA and 18 age-sex-matched controls. Four patients with OSA dropped out. All participants underwent PSG and HRV analysis. We measured the 24-hour fluctuations and the night/day ratio of low frequency (LF) and high frequency (HF) spectral components of HRV in all subjects and controls. The LF night/day ratio was termed the cardiac sympathetic index while the HF night/day ratio was termed the cardiac parasympathetic index.
All twenty-five OSA patients were PSG positive (presence of OSA) while 18 controls were PSG negative (absence of OSA). There was no significant difference in LF and HF 24-hour fluctuation values between OSA patients and controls. In OSA patients, LF and HF values were significantly higher during night-time than day time recordings (p<0.001). HF night/day ratio (cardiac parasympathetic index) accurately (100%) differentiated OSA patients from controls without an overlap of individual values. The LF night/day ratio (cardiac sympathetic index) had sensitivity of 84%, specificity of 72.2% and accuracy of 79.1% in distinguishing between groups.
The cardiac parasympathetic index accurately differentiated patients with OSA from controls, on an individual basis.
Deep grey nuclei of the human brain accumulate minerals both in aging and in several neurodegenerative diseases. Mineral deposition produces a shortening of the transverse relaxation time which ...causes hypointensity on magnetic resonance (MR) imaging. The physician often has difficulties in determining whether the incidental hypointensity of grey nuclei seen on MR images is related to aging or neurodegenerative pathology. We investigated the hypointensity patterns in globus pallidus, putamen, caudate nucleus, thalamus and dentate nucleus of 217 healthy subjects (ages, 20-79 years; men/women, 104/113) using 3T MR imaging. Hypointensity was detected more frequently in globus pallidus (35.5%) than in dentate nucleus (32.7%) and putamen (7.8%). A consistent effect of aging on hypointensity (
p
< 0.001) of these grey nuclei was evident. Putaminal hypointensity appeared only in elderly subjects whereas we did not find hypointensity in the caudate nucleus and thalamus of any subject. In conclusion, the evidence of hypointensity in the caudate nucleus and thalamus at any age or hypointensity in the putamen seen in young subjects should prompt the clinician to consider a neurodegenerative disease.
Introduction Distinguishing tremor-dominant Parkinson's disease (tPD) from essential tremor with rest tremor (rET) can be challenging and often requires dopamine imaging. This study aimed to ...differentiate between these two diseases through a machine learning (ML) approach based on rest tremor (RT) electrophysiological features and structural MRI data. Methods We enrolled 72 patients including 40 tPD patients and 32 rET patients, and 45 control subjects (HC). RT electrophysiological features (frequency, amplitude, and phase) were calculated using surface electromyography (sEMG). Several MRI morphometric variables (cortical thickness, surface area, cortical/subcortical volumes, roughness, and mean curvature) were extracted using Freesurfer. ML models based on a tree-based classification algorithm termed XGBoost using MRI and/or electrophysiological data were tested in distinguishing tPD from rET patients. Results Both structural MRI and sEMG data showed acceptable performance in distinguishing the two patient groups. Models based on electrophysiological data performed slightly better than those based on MRI data only (mean AUC: 0.92 and 0.87, respectively; p = 0.0071). The top-performing model used a combination of sEMG features (amplitude and phase) and MRI data (cortical volumes, surface area, and mean curvature), reaching AUC: 0.97 ± 0.03 and outperforming models using separately either MRI ( p = 0.0001) or EMG data ( p = 0.0231). In the best model, the most important feature was the RT phase. Conclusion Machine learning models combining electrophysiological and MRI data showed great potential in distinguishing between tPD and rET patients and may serve as biomarkers to support clinicians in the differential diagnosis of rest tremor syndromes in the absence of expensive and invasive diagnostic procedures such as dopamine imaging.
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