Search

Background: Movement disorders are frequent in patients with inborn errors of metabolism (IEMs) but poorly recognized, particularly by nonmovement disorder specialists. We propose an easy‐to‐use clinical screening tool to help recognize movement disorders. Objective: The aim is to develop a user‐friendly rapid screening tool for nonmovement disorder specialists to detect moderate and severe movement disorders in patients aged ≥4 years with IEMs. Methods: Videos of 55 patients with different IEMs were scored by experienced movement disorder specialists (n = 12). Inter‐rater agreements were determined on the presence and subtype of the movement disorder. Based on ranking and consensus, items were chosen to be incorporated into the screening tool. Results: A movement disorder was rated as present in 80% of the patients, with a moderate inter‐rater agreement (κ =0.420, P < 0.001) on the presence of a movement disorder. When considering only moderate and severe movement disorders, the inter‐rater agreement increased to almost perfect (κ = 0.900, P < 0.001). Dystonia was most frequently scored (27.3%) as the dominant phenotype. Treatment was mainly suggested for patients with moderate or severe movement disorders. Walking, observations of the arms, and drawing a spiral were found to be the most informative tasks and were included in the screening tool. Conclusions: We designed a screening tool to recognize movement disorders in patients with IEMs. We propose that this screening tool can contribute to select patients who should be referred to a movement disorder specialist for further evaluation and, if necessary, treatment of the movement disorder. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Copyright of Developmental Medicine & Child Neurology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aim: To investigate the interobserver agreement on phenotypic early-onset ataxia (EOA) assessment and to explore whether the Scale for Assessment and Rating of Ataxia (SARA) could provide a supportive marker.Method: Seven movement disorder specialists provided independent phenotypic assessments of potentially ataxic motor behaviour in 40 patients (mean age 15y [range 5-34]; data derived from University Medical Center Groningen medical records 1998-2012). We determined interobserver agreement by Fleiss' kappa. Furthermore, we compared percentage SARA subscores ([subscore/total score]×100%) between 'indisputable' (primary ataxia recognition by at least six observers) and 'mixed' (ataxia recognition, unfulfilling 'indisputable' criteria) EOA phenotypes.Results: Agreement on phenotypic EOA assessment was statistically significant (p<0.001), but of moderate strength (Fleiss' kappa=0.45; 95% CI 0.38-0.51). During mild disease progression, percentage SARA gait subscores discriminated between 'indisputable' and 'mixed' EOA phenotypes. In patients with percentage SARA gait subscores >30%, primary ataxia was more frequently present than in those with subscores <30% (p=0.001).Interpretation: Among movement-disorder professionals from different disciplines, interobserver agreement on phenotypic EOA recognition is of limited strength. SARA gait subscores can provide a supportive discriminative marker between EOA phenotypes. Hopefully, future phenotypic insight will contribute to the inclusion of uniform, high-quality data in international EOA databases. [ABSTRACT FROM AUTHOR]

Early aetiological diagnosis is of paramount importance for childhood dystonia because some of the possible underlying conditions are treatable. Numerous genetic and non-genetic causes have been reported, and diagnostic workup is often challenging, time consuming and costly. Recently, a paradigm shift has occurred in molecular genetic diagnostics, with next-generation sequencing techniques now allowing us to analyse hundreds of genes simultaneously. To ensure that patients benefit from these new techniques, adaptation of current diagnostic strategies is needed. On the basis of a systematic literature review of dystonia with onset in childhood or adolescence, we propose a novel diagnostic strategy with the aim of helping clinicians determine which patients may benefit by applying these new genetic techniques and which patients first require other investigations. We also provide an up-to-date list of candidate genes for a dystonia gene panel, based on a detailed literature search up to 20 October 2014. While new genetic techniques are certainly not a panacea, possible advantages of our proposed strategy include earlier diagnosis and avoidance of unnecessary investigations. It will therefore shorten the time of uncertainty for patients and their families awaiting a definite diagnosis. [ABSTRACT FROM AUTHOR]

Background In spina bifida aperta (SBA), movements caudal to the meningomyelocele (MMC) are present in utero, but they disappear shortly after birth. Insight in onset and progression of movement loss is therapeutically relevant. Determination of muscle echogenicity (or density (MD)) is used to estimate onset and progression of various neuromuscular disorders in children. In prenatal SBA, we hypothesized that MD assessment could indicate onset and progression of muscle damage in relation to movement loss. Objective: To estimate onset and progression of muscle changes in fetal SBA by MD assessment. Materials and methods MD (muscle/bone pixel-density) was obtained in calibrated images (by standardized ultrasound methods). In SBA (n = 6; GA 22-37 wks) and control fetuses (n = 11; GA 17-36 wks), we assessed MD in gluteus/gastrocnemius (L5-S1), tibialis ant. (L4-5), quadriceps (L2-4), and biceps/triceps (C5-8) muscles. MMCs were at Th12 (n = 1), L4-5 (n = 1) or L5-S1 (n = 4) level. In SBA fetuses, MD was compared between muscles from myotomes caudal and cranial to the MMC. Additionally, MD was compared between SBA fetuses and aged matched controls (n = 6 and median GA 33 wks in both groups), and between pre- and postnatal SBA (<1 week after birth). In succumbed fetuses, MD values were related to histological observations in affected muscles (3 SBA fetuses). Results During MD assessment, movements caudal to the MMC were present in all SBA fetuses. MD values correlated with gestational age, both in controls and in SBA myotomes cranial to the MMC (r = 0.44, p < 0.01; r = 0.50, p < 0.05; resp.). In contrast, MD values in SBA myotomes caudal to the MMC did not correlate with gestational age (r = 0.26, p = 0.13), and were significantly higher than cranial to the MMC (median +19%, p < 0.01) and controls (+45-60%, p < 0.01). Longitudinal pre- and postnatal MD values caudal to the MMC did not significantly differ (mean 14%). MD values in SBA myotomes caudal to the MMC corresponded with histological assessment (extent of atrophic/hypertrophic muscle fibres). Conclusion Despite persisting leg movements in fetal SBA, MD in myotomes caudal to the MMC is increased prenatally. Early postnatal disappearance of leg movements is unrelated to an additional increase in perinatal MD. Present data support the concept that permanent movement loss is related to acute spinal damage rather than to intrinsic muscle impairment. [ABSTRACT FROM AUTHOR]

Early-Onset Ataxia (EOA) and Developmental Coordination Disorder (DCD) are two conditions that affect coordination in children. Phenotypic identification of impaired coordination plays an important role in their diagnosis. Gait is one of the tests included in rating scales that can be used to assess motor coordination. A practical problem is that the resemblance between EOA and DCD symptoms can hamper their diagnosis. In this study we employed inertial sensors and a supervised classifier to obtain an automatic classification of the condition of participants. Data from shank and waist mounted inertial measurement units were used to extract features during gait in children diagnosed with EOA or DCD and age-matched controls. We defined a set of features from the recorded signals and we obtained the optimal features for classification using a backward sequential approach. We correctly classified 80.0%, 85.7%, and 70.0% of the control, DCD and EOA children, respectively. Overall, the automatic classifier correctly classified 78.4% of the participants, which is slightly better than the phenotypic assessment of gait by two pediatric neurologists (73.0%). These results demonstrate that automatic classification employing signals from inertial sensors obtained during gait maybe used as a support tool in the differential diagnosis of EOA and DCD. Furthermore, future extension of the classifier's test domains may help to further improve the diagnostic accuracy of pediatric coordination impairment. In this sense, this study may provide a first step towards incorporating a clinically objective and viable biomarker for identification of EOA and DCD. [ABSTRACT FROM AUTHOR]

In glycogen storage diseases (GSDs), improved longevity has resulted in the need for neuromuscular surveillance. In 12 children and 14 adults with the "hepatic" (GSD-I) and "myopathic" (GSD-III) phenotypes, we cross-sectionally assessed muscle ultrasound density (MUD) and muscle force. Children with both "hepatic" and "myopathic" GSD phenotypes had elevated MUD values (MUD Z-scores: GSD-I > 2.5 SD vs. GSD-III > 1 SD, p < 0.05) and muscle weakness (GSD-I muscle force; p < 0.05) of myopathic distribution. In "hepatic" GSD-I adults, MUD stabilized (GSD-I adults vs. GSD-I children, not significant), concurring with moderate muscle weakness (GSD-I adults vs. healthy matched pairs, p < 0.05). In "myopathic" GSD-III adults, MUD increased with age (MUD-GSD III vs. age: r = 0.71-0.83, GSD-III adults > GSD-III children, p < 0.05), concurring with pronounced muscle weakness (GSD-III adults vs. GSD-I adults, p < 0.05) of myopathic distribution. Children with "hepatic" and "myopathic" GSD phenotypes were both found to have myopathy. Myopathy stabilizes in "hepatic" GSD-I adults, whereas it progresses in "myopathic" GSD-III adults. Muscle ultrasonography provides an excellent, non-invasive tool for neuromuscular surveillance per GSD phenotype. [ABSTRACT FROM AUTHOR]

Myoclonus is a hyperkinetic movement disorder characterized by brief, involuntary muscular jerks. Recognition of myoclonus and determination of the underlying aetiology remains challenging given that both acquired and genetically determined disorders have varied manifestations. The diagnostic work-up in myoclonus is often time-consuming and costly, and a definitive diagnosis is reached in only a minority of patients. On the basis of a systematic literature review up to June 2015, we propose a novel diagnostic eight-step algorithm to help clinicians accurately, efficiently and cost-effectively diagnose myoclonus. The large number of genes implicated in myoclonus and the wide clinical variation of these genetic disorders emphasize the need for novel diagnostic techniques. Therefore, and for the first time, we incorporate next-generation sequencing (NGS) in a diagnostic algorithm for myoclonus. The initial step of the algorithm is to confirm whether the movement disorder phenotype is consistent with, myoclonus, and to define its anatomical subtype. The next steps are aimed at identification of both treatable acquired causes and those genetic causes of myoclonus that require a diagnostic approach other than NGS. Finally, other genetic diseases that could cause myoclonus can be investigated simultaneously by NGS techniques. To facilitate NGS diagnostics, we provide a comprehensive list of genes associated with myoclonus. [ABSTRACT FROM AUTHOR]

Abstract: In spina bifida aperta (SBA), spinal MRI provides a surrogate marker to estimate muscle damage caudal to the myelomeningocele (MMC). This muscle damage by the MMC can be quantified by intra-individual comparison of muscle ultrasound density (MUD) caudal versus cranial to the MMC (dMUD = [MUDcaudal-to-the-MMC] − [MUDcranial-to-the-MMC]). Quantitative dMUD assessment requires time, equipment and expertise, whereas it could also be visually determined by differences in muscle echodensity caudal vs. cranial to the MMC (visual-dMUD). If visual and quantitative dMUD correspond, visual dMUD assessment could provide a clinical screening parameter. In 100 SBA muscle ultrasound recordings of patients with various MMC levels, we aimed to compare quantitative dMUD (dMUD = [MUDcalf-muscle/S1] − [MUDquadriceps-muscle/L2-L4]) with visual dMUD assessments by 20 different observers. Results indicate that quantitative dMUD can be visually detected (sensitivity 86%; specificity 57%), implicating that visual dMUD screening could provide a quick, clinical screening tool for muscle impairment by the MMC. [Copyright &y& Elsevier]