Validity of the "Drift without pronation" sign in conversion disorder.

BACKGROUND: Conversion disorder (CD) is a psychiatric disorder, yet the diagnosis cannot be established without the expertise of a neurologist, as distinguishing a functional from an organic symptom relies on careful bedside examination. Joseph Babinski considered the absence of pronator drift as a 'positive sign' for hysterical paresis but the validity of this sign has never been evaluated. The aim of this study was to examine the sensitivity and specificity of the "drift without pronation" sign. METHODS: Twenty-six patients with unilateral functional upper limb paresis diagnosed with CD (DSM-IV) and a control group of 28 patients with an organic neurological condition were consecutively included. The arm stabilisation test was performed with arms stretched out in full supination, fingers adducted, eyes closed for 10 seconds. A positive "drift without pronation" sign was defined by the presence of a downward drift without pronation. RESULTS: All CD subjects (100%) displayed a positive sign when only 7.1% of organic subjects did (Fisher's p < 0.001). The sign yielded a sensitivity of 100% (95% CI:84%-100%) and a specificity of 93% (95% CI:76%-98%). CONCLUSION: The observation of a "drift without pronation" sign is specific for Conversion Disorder and can be of help in making a quick distinction between organic and functional paresis at the bedside

The value of 'positive' clinical signs for weakness, sensory and gait disorders in conversion disorder: a systematic and narrative review.

Experts in the field of conversion disorder have suggested for the upcoming DSM-V edition to put less weight on the associated psychological factors and to emphasise the role of clinical findings. Indeed, a critical step in reaching a diagnosis of conversion disorder is careful bedside neurological examination, aimed at excluding organic signs and identifying 'positive' signs suggestive of a functional disorder. These positive signs are well known to all trained neurologists but their validity is still not established. The aim of this study is to provide current evidence regarding their sensitivity and specificity. We conducted a systematic search on motor, sensory and gait functional signs in Embase, Medline, PsycINfo from 1965 to June 2012. Studies in English, German or French reporting objective data on more than 10 participants in a controlled design were included in a systematic review. Other relevant signs are discussed in a narrative review. Eleven controlled studies (out of 147 eligible articles) describing 14 signs (7 motor, 5 sensory, 2 gait) reported low sensitivity of 8-100% but high specificity of 92-100%. Studies were evidence class III, only two had a blinded design and none reported on inter-rater reliability of the signs. Clinical signs for functional neurological symptoms are numerous but only 14 have been validated; overall they have low sensitivity but high specificity and their use should thus be recommended, especially with the introduction of the new DSM-V criteria

Multi-centre classification of functional neurological disorders based on resting-state functional connectivity.

Patients suffering from functional neurological disorder (FND) experience disabling neurological symptoms not caused by an underlying classical neurological disease (such as stroke or multiple sclerosis). The diagnosis is made based on reliable positive clinical signs, but clinicians often require additional time- and cost consuming medical tests and examinations. Resting-state functional connectivity (RS FC) showed its potential as an imaging-based adjunctive biomarker to help distinguish patients from healthy controls and could represent a "rule-in" procedure to assist in the diagnostic process. However, the use of RS FC depends on its applicability in a multi-centre setting, which is particularly susceptible to inter-scanner variability. The aim of this study was to test the robustness of a classification approach based on RS FC in a multi-centre setting. This study aimed to distinguish 86 FND patients from 86 healthy controls acquired in four different centres using a multivariate machine learning approach based on whole-brain resting-state functional connectivity. First, previously published results were replicated in each centre individually (intra-centre cross-validation) and its robustness across inter-scanner variability was assessed by pooling all the data (pooled cross-validation). Second, we evaluated the generalizability of the method by using data from each centre once as a test set, and the data from the remaining centres as a training set (inter-centre cross-validation). FND patients were successfully distinguished from healthy controls in the replication step (accuracy of 74%) as well as in each individual additional centre (accuracies of 73%, 71% and 70%). The pooled cross validation confirmed that the classifier was robust with an accuracy of 72%. The results survived post-hoc adjustment for anxiety, depression, psychotropic medication intake, and symptom severity. The most discriminant features involved the angular- and supramarginal gyri, sensorimotor cortex, cingular- and insular cortex, and hippocampal regions. The inter-centre validation step did not exceed chance level (accuracy below 50%). The results demonstrate the applicability of RS FC to correctly distinguish FND patients from healthy controls in different centres and its robustness against inter-scanner variability. In order to generalize its use across different centres and aim for clinical application, future studies should work towards optimization of acquisition parameters and include neurological and psychiatric control groups presenting with similar symptoms

Oral and intestinal dysbiosis in Parkinson's disease.

The suspicion of an origin of Parkinson's disease (PD) at the periphery of the body and the involvement of environmental risk factors in the pathogenesis of PD have directed the attention of the scientific community towards the microbiota. The microbiota represents all the microorganisms residing both in and on a host. It plays an essential role in the physiological functioning of the host. In this article, we review the dysbiosis repeatedly demonstrated in PD and how it influences PD symptoms. Dysbiosis is associated with both motor and non-motor PD symptoms. In animal models, dysbiosis only promotes symptoms in individuals genetically susceptible to Parkinson's disease, suggesting that dysbiosis is a risk factor but not a cause of Parkinson's disease. We also review how dysbiosis contributes to the pathophysiology of PD. Dysbiosis induces numerous and complex metabolic changes, resulting in increased intestinal permeability, local and systemic inflammation, production of bacterial amyloid proteins that promote α-synuclein aggregation, as well as a decrease in short-chain fatty acid-producing bacteria that have anti-inflammatory and neuroprotective potential. In addition, we review how dysbiosis decreases the efficacy of dopaminergic treatments. We then discuss the interest of dysbiosis analysis as a biomarker of Parkinson's disease. Finally, we give an overview of how interventions modulating the gut microbiota such as dietary interventions, pro-biotics, intestinal decontamination and fecal microbiota transplantation could influence the course of PD

Multi-centre classification of functional neurological disorders based on resting-state functional connectivity.

BACKGROUND Patients suffering from functional neurological disorder (FND) experience disabling neurological symptoms not caused by an underlying classical neurological disease (such as stroke or multiple sclerosis). The diagnosis is made based on reliable positive clinical signs, but clinicians often require additional time- and cost consuming medical tests and examinations. Resting-state functional connectivity (RS FC) showed its potential as an imaging-based adjunctive biomarker to help distinguish patients from healthy controls and could represent a "rule-in" procedure to assist in the diagnostic process. However, the use of RS FC depends on its applicability in a multi-centre setting, which is particularly susceptible to inter-scanner variability. The aim of this study was to test the robustness of a classification approach based on RS FC in a multi-centre setting. METHODS This study aimed to distinguish 86 FND patients from 86 healthy controls acquired in four different centres using a multivariate machine learning approach based on whole-brain resting-state functional connectivity. First, previously published results were replicated in each centre individually (intra-centre cross-validation) and its robustness across inter-scanner variability was assessed by pooling all the data (pooled cross-validation). Second, we evaluated the generalizability of the method by using data from each centre once as a test set, and the data from the remaining centres as a training set (inter-centre cross-validation). RESULTS FND patients were successfully distinguished from healthy controls in the replication step (accuracy of 74%) as well as in each individual additional centre (accuracies of 73%, 71% and 70%). The pooled cross validation confirmed that the classifier was robust with an accuracy of 72%. The results survived post-hoc adjustment for anxiety, depression, psychotropic medication intake, and symptom severity. The most discriminant features involved the angular- and supramarginal gyri, sensorimotor cortex, cingular- and insular cortex, and hippocampal regions. The inter-centre validation step did not exceed chance level (accuracy below 50%). CONCLUSIONS The results demonstrate the applicability of RS FC to correctly distinguish FND patients from healthy controls in different centres and its robustness against inter-scanner variability. In order to generalize its use across different centres and aim for clinical application, future studies should work towards optimization of acquisition parameters and include neurological and psychiatric control groups presenting with similar symptoms

Outcome measurement in functional neurological disorder: a systematic review and recommendations.

OBJECTIVES: We aimed to identify existing outcome measures for functional neurological disorder (FND), to inform the development of recommendations and to guide future research on FND outcomes. METHODS: A systematic review was conducted to identify existing FND-specific outcome measures and the most common measurement domains and measures in previous treatment studies. Searches of Embase, MEDLINE and PsycINFO were conducted between January 1965 and June 2019. The findings were discussed during two international meetings of the FND-Core Outcome Measures group. RESULTS: Five FND-specific measures were identified-three clinician-rated and two patient-rated-but their measurement properties have not been rigorously evaluated. No single measure was identified for use across the range of FND symptoms in adults. Across randomised controlled trials (k=40) and observational treatment studies (k=40), outcome measures most often assessed core FND symptom change. Other domains measured commonly were additional physical and psychological symptoms, life impact (ie, quality of life, disability and general functioning) and health economics/cost-utility (eg, healthcare resource use and quality-adjusted life years). CONCLUSIONS: There are few well-validated FND-specific outcome measures. Thus, at present, we recommend that existing outcome measures, known to be reliable, valid and responsive in FND or closely related populations, are used to capture key outcome domains. Increased consistency in outcome measurement will facilitate comparison of treatment effects across FND symptom types and treatment modalities. Future work needs to more rigorously validate outcome measures used in this population

Sex steroid hormones and epilepsy: Effects of hormonal replacement therapy on seizure frequency of postmenopausal women with epilepsy—A systematic review

Background and purpose: Hormonal replacement therapy (HRT) is used for symptomatic treatment of menopause. Some evidence suggests a proconvulsant effect of estrogen and an anticonvulsant role of progesterone. Thus, the use of exogenous sex steroid hormones might influence the course of epilepsy in peri- and postmenopausal women with epilepsy (WWE). We conducted a systematic review on the impact of HRT on the frequency of seizures of WWE. Methods: PubMed and Scopus were searched for articles published from inception until August 2022. Abstracts from the past 5 years from the European Academy of Neurology and European Epilepsy Congresses were also reviewed. Article reference lists were screened, and relevant articles were retrieved for consultation. Interventional and observational studies on WWE and animal models of estrogen deficiency were included. Critical appraisal was performed using the revised Cochrane risk-of-bias tool for randomized trials and ROBINS-E tool. Results: Of 497 articles screened, 13 studies were included, including three human studies. One cross-sectional study showed a decrease in seizure frequency in WWE using combined HRT, a case–control study showed an increase in comparison with controls, and a randomized clinical trial found a dose-dependent increase in seizure frequency in women with focal epilepsy taking combined HRT. Ten studies addressing the impact of HRT in rat models were also included, which showed conflicting results. Conclusions: There is scarce evidence of the impact of HRT in WWE. Further studies should evaluate the harmful potential, and prospective registries are needed for monitoring this population