Semi-supervised clustering of quaternion time series: Application to gait analysis in multiple sclerosis using motion sensor data.

Recent approaches in gait analysis involve the use of wearable motion sensors to extract spatio-temporal parameters that characterize multiple aspects of an individual's gait. In particular, the medical community could largely benefit from this type of devices as they could provide the clinicians with a valuable tool for assessing gait impairment. Motion sensor data are however complex and there is an urgent unmet need to develop sound statistical methods for analyzing such data and extracting clinically relevant information. In this article, we measure gait by following the hip rotation over time and the resulting statistical unit is a time series of unit quaternions. We explore the possibility to form groups of patients with similar walking impairment by taking into account their walking data and their global decease severity with semi-supervised clustering. We generalize a compromise-based method named hclustcompro to unit quaternion time series by combining it with the proper dissimilarity quaternion dynamic time warping. We apply this method on patients diagnosed with multiple sclerosis to form groups of patients with similar walking deficiencies while accounting for the clinical assessment of their overall disability. We also compare the compromise-based clustering approach with the method mergeTrees that falls into a sub-class of ensemble clustering named collaborative clustering. The results provide a first proof of both the interest of using wearable motion sensors for assessing gait impairment and the use of prior knowledge to guide the clustering process. It also demonstrates that compromise-based clustering is a more appropriate approach in this context.

LeSCoD: a new clinical scale for the detection of Lewy body disease in neurocognitive disorders.

BACKGROUND: Dementia with Lewy bodies remains underdiagnosed in clinical practice mainly because of the low sensitivity of existing diagnostic criteria and a strong overlap with Alzheimer's pathology that can mask the Lewy phenotype. OBJECTIVE: The objective of this study was therefore to develop and validate a new clinical scale designed to detect signs of Lewy body disease, called LeSCoD for Lewy body Screening scale in Cognitive Disorders. METHODS: 128 patients who fulfilled the clinical criteria of dementia with Lewy bodies (DLB; n = 32), Alzheimer's disease (AD; n = 77) or both (n = 19) was prospectively enrolled. 18F-DOPA PET imaging and/or CSF biomarkers were available in some patients. LeSCoD scale was systematically administered and the potential correlation with 18F-DOPA PET imaging was evaluated in a subgroup of patients. RESULTS: LeSCoD scale showed robust internal and external validity. We determined a cut-off of 10 above which the sensitivity and specificity for Lewy body disease diagnosis were 86% and 95%, respectively. The LeSCoD scale correlated with striatal dopamine uptake in 18F-DOPA PET. CONCLUSION: LeSCoD scale is a simple and reliable tool for the evaluation of Lewy body disease in routine clinical practice, with a higher sensitivity and specificity than the existing criteria. It might be an alternative to the use of dopamine-specific imaging.

G-computation, propensity score-based methods, and targeted maximum likelihood estimator for causal inference with different covariates sets: a comparative simulation study.

Controlling for confounding bias is crucial in causal inference. Distinct methods are currently employed to mitigate the effects of confounding bias. Each requires the introduction of a set of covariates, which remains difficult to choose, especially regarding the different methods. We conduct a simulation study to compare the relative performance results obtained by using four different sets of covariates (those causing the outcome, those causing the treatment allocation, those causing both the outcome and the treatment allocation, and all the covariates) and four methods: g-computation, inverse probability of treatment weighting, full matching and targeted maximum likelihood estimator. Our simulations are in the context of a binary treatment, a binary outcome and baseline confounders. The simulations suggest that considering all the covariates causing the outcome led to the lowest bias and variance, particularly for g-computation. The consideration of all the covariates did not decrease the bias but significantly reduced the power. We apply these methods to two real-world examples that have clinical relevance, thereby illustrating the real-world importance of using these methods. We propose an R package RISCA to encourage the use of g-computation in causal inference.

High-dose biotin in progressive multiple sclerosis: A prospective study of 178 patients in routine clinical practice.

BACKGROUND: A recent controlled trial suggested that high-dose biotin supplementation reverses disability progression in patients with progressive multiple sclerosis. OBJECTIVE: To analyze the impact of high-dose biotin in routine clinical practice on disability progression at 12 months. METHODS: Progressive multiple sclerosis patients who started high-dose biotin at Nantes or Rennes Hospital between 3 June 2015 and 15 September 2017 were included in this prospective study. Disability outcome measures, patient-reported outcome measures, relapses, magnetic resonance imaging (MRI) data, and adverse events were collected at baseline, 6, and 12 months. RESULTS: A total of 178 patients were included. At baseline, patients were 52.0 ± 9.4 years old, mean Expanded Disability Status Scale (EDSS) score was 6.1 ± 1.3, mean disease duration was 16.9 ± 9.5 years. At 12 months, 3.8% of the patients had an improved EDSS score. Regarding the other disability scales, scores either remained stable or increased significantly. In total, 47.4% of the patients described stability, 27.6% felt an improvement, and 25% described a worsening. Four patients (2.2%) had a relapse. Of the 74 patients (41.6%) who underwent an MRI, 20 (27.0%) had new T2 lesions, 8 (10.8%) had gadolinium-enhancing lesions. Twenty-five (14%) reported adverse event. CONCLUSION: In this study, high-dose biotin did not seem to be associated with a clear improvement in disability.

Comparative effectiveness of teriflunomide vs dimethyl fumarate in multiple sclerosis.

OBJECTIVE: In this study, we compared the effectiveness of teriflunomide (TRF) and dimethyl fumarate (DMF) on both clinical and MRI outcomes in patients followed prospectively in the Observatoire Français de la Sclérose en Plaques. METHODS: A total of 1,770 patients with relapsing-remitting multiple sclerosis (RRMS) (713 on TRF and 1,057 on DMF) with an available baseline brain MRI were included in intention to treat. The 1- and 2-year postinitiation outcomes were relapses, increase of T2 lesions, increase in Expanded Disability Status Scale score, and reason for treatment discontinuation. Propensity scores (inverse probability weighting) and logistic regressions were estimated. RESULTS: The confounder-adjusted proportions of patients were similar in TRF- compared to DMF-treated patients for relapses and disability progression after 1 and 2 years. However, the adjusted proportion of patients with at least one new T2 lesion after 2 years was lower in DMF compared to TRF (60.8% vs 72.2%, odds ratio [OR] 0.60, p < 0.001). Analyses of reasons for treatment withdrawal showed that lack of effectiveness was reported for 8.5% of DMF-treated patients vs 14.5% of TRF-treated patients (OR 0.54, p < 0.001), while adverse events accounted for 16% of TRF-treated patients and 21% of DMF-treated patients after 2 years (OR 1.39, p < 0.001). CONCLUSIONS: After 2 years of treatment, we found similar effectiveness of DMF and TRF in terms of clinical outcomes, but with better MRI-based outcomes for DMF-treated patients, resulting in a lower rate of treatment discontinuation due to lack of effectiveness. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that for patients with RRMS, TRF and DMF have similar clinical effectiveness after 2 years of treatment.

Comparative efficacy of fingolimod vs natalizumab: A French multicenter observational study.

OBJECTIVE: To compare natalizumab and fingolimod on both clinical and MRI outcomes in patients with relapsing-remitting multiple sclerosis (RRMS) from 27 multiple sclerosis centers participating in the French follow-up cohort Observatoire of Multiple Sclerosis. METHODS: Patients with RRMS included in the study were aged from 18 to 65 years with an Expanded Disability Status Scale score of 0-5.5 and an available brain MRI performed within the year before treatment initiation. The data were collected for 326 patients treated with natalizumab and 303 with fingolimod. The statistical analysis was performed using 2 different methods: logistic regression and propensity scores (inverse probability treatment weighting). RESULTS: The confounder-adjusted proportion of patients with at least one relapse within the first and second year of treatment was lower in natalizumab-treated patients compared to the fingolimod group (21.1% vs 30.4% at first year, p = 0.0092; and 30.9% vs 41.7% at second year, p = 0.0059) and supported the trend observed in nonadjusted analysis (21.2% vs 27.1% at 1 year, p = 0.0775). Such statistically significant associations were also observed for gadolinium (Gd)-enhancing lesions and new T2 lesions at both 1 year (Gd-enhancing lesions: 9.3% vs 29.8%, p < 0.0001; new T2 lesions: 10.6% vs 29.6%, p < 0.0001) and 2 years (Gd-enhancing lesions: 9.1% vs 22.1%, p = 0.0025; new T2 lesions: 16.9% vs 34.1%, p = 0.0010) post treatment initiation. CONCLUSION: Taken together, these results suggest the superiority of natalizumab over fingolimod to prevent relapses and new T2 and Gd-enhancing lesions at 1 and 2 years. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that for patients with RRMS, natalizumab decreases the proportion of patients with at least one relapse within the first year of treatment compared to fingolimod.

Non-homogeneous effect of levodopa on inhibitory circuits in Parkinson's disease and dyskinesia.

INTRODUCTION: Levodopa-induced dyskinesia in patients with Parkinson's disease (PD) has been shown to be associated with an abnormal plasticity in the motor cortex. We investigated whether changes in the excitability of inhibitory and excitatory motor circuits could underlie maladaptive mechanisms associated with dyskinesia. METHODS: Using single and paired transcranial magnetic stimulation (TMS), we studied motor threshold, silent period (SP) duration, intracortical facilitation (ICF), short intracortical inhibition (SICI) and low- and high-intensity long intracortical inhibition (LICI) in 10 dyskinetic and 10 non-dyskinetic patients, matched for disease and treatment duration, before (OFF state) and after (ON state) levodopa, and in 10 healthy controls. RESULTS: In the OFF state, the two groups of patients showed similar motor cortex excitability with a reduced SICI compared to controls. LICI was weaker and increasing stimulation intensity had a lower effect on SP duration in dyskinetic patients than in controls. In dyskinetic patients, in contrast to non-dyskinetic patients, levodopa failed to increase SICI and SP duration, and potentiated to a lesser extent the effect of increasing the stimulation intensity on LICI. Although levodopa improved motor symptoms to a similar extent in both dyskinetic and non-dyskinetic patients, it failed to activate effectively the excitability of the inhibitory systems in dyskinetic patients. DISCUSSION: These findings suggest that dyskinesia is associated with an abnormal effect of levodopa on cortical motor inhibitory circuits.