Epidemiological Study of Pediatric Neuromuscular Disorders in South West France Regions

Epidemiological Study of Pediatric Neuromuscular Disorders in South West France Regions | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Epidemiological Study of Pediatric Neuromuscular Disorders in South West France Regions Maelle Biotteau, Claude Messiaen, Elisabeth Wallach, François Rivier, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4343784/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Aim : Very limited epidemiological data on neuromuscular disorders pediatric population exist around the world. In France, such pediatric epidemiological study is seriously lacking. We investigated the pediatric prevalence (under 18) and we described the epidemiological profile of neuromuscular disorders on Southwest regions of France, from May 1, 2001 to June 1, 2022. We screened medical and genetic hospital records in three expert centers (Toulouse, Montpellier and Bordeaux) for neuromuscular disorders. Methods : We performed a retrospective cohort study with data extracted from the French National Rare Disease Databank that gathers a minimal dataset on all patients followed-up in French rare disease expert center in France. We then estimated: (1) Prevalence by diagnosis and age group or by year with Poisson confidence interval (2) survival from birth analyses using Kaplan-Meier for muscular disorders sub-cohort analysis. Results : Over the period, 1,621 children were included with 62% of males. We estimate the regional prevalence at 37.9 (IC95% = 35.3 - 40.7) for 100,000 inhabitants under 18 years old. For muscular disorders sub-cohort analysis, we estimate regional prevalence for Duchene, Becker, Charcot-Marie-Tooth type 1 and Spinal muscular atrophy at 5 (IC95% = 4.1 - 6.1), 1.3 (IC95% = 0.9 - 1.9), 6.2 (IC95 = 5.1 - 7.3) and 3.2 (IC95% = 2.5 - 4.1) respectively. Conclusion : Our findings seem in accordance with previous but scarce other data. Together, all may reflect a consensus among different countries supporting a global neuromuscular disorders’ pediatric prevalence about 38/100000 may, about 5 for Duchene, 1.5 for Becker, 6.2 for Charcot-Marie-Tooth type 1, 3.2 for Spinal muscular atrophy. This is the first time that it’s possible to estimate with robustness French pediatric epidemiological prevalence of neuromuscular disorders, that constitute a strength starting point to be confirmed by the extend of analyze to all French expert centers. Inherited muscle diseases Neuromuscular disorder Epidemiology Prevalence Pediatric Population Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Neuromuscular Disorders (NMD) Inherited muscle diseases (IMD) or Neuromuscular Disorders (NMD) are a broadly heterogeneous defined group of conditions affecting the neuromuscular system by involving injury or dysfunction of peripheral nerves or muscle. The multitude of possible sites of injury (second motor neuron, axons, Schwann cells, neuromuscular junction, muscle, or combination of these sites) lead to clinical presentation heterogeneity. Some forms of NMD are life-limiting while some others can be successfully treated (Yuki & Hartung, 2012). However, a variety of common symptoms can be mentioned include progressive muscle weakness, cramps, stiffness, joint deformities, chronic pain, respiratory and/or cardiac involvement, a broad range of cognitive impairments. This gave rise to a major impact on the quality of life, social, emotional and societal burden and health budgets worldwide. NMD can appear at any age. Some forms manifest at birth or early childhood (D’Amico et al., 2011) whereas the incidence of some other forms increases with age (Turner & Hilton-Jones, 2014). Some forms of NMD are hereditary while others are acquired. In pediatrics, the majority of neuromuscular disorders have a genetic basis, as either a de novo or an inherited pathogenic variant in a single gene (Darras, 2015). Disease genes remain to be discovered, but hundreds of neuromuscular disease genes have already been identified (http://www.musclegenetable.fr). Each NMD condition is defined as rare diseases due to their low prevalence affecting no more than 1 in 2,000 (Nguengang Wakap et al., 2020). Combined NMD entity would however represent a more significant group, with a prevalence close than other neurological diseases as Parkinson or multiple sclerosis for eg. (Deenen et al., 2015). Some recent studies suggest that number of people living with NMD is intrinsically rising (Rose et al. 2019; Carey et al., 2021). In addition, until recently, some NMD were considered to be incurable, treatments have emerging and the research has made notable and steady progress in very few years, changing the disease outcome for many patients. Introduction of new therapeutic approaches therefore increases survival at later age. These two factors should be considered to better understanding the actual and current epidemiology of NMD, to especially estimate future healthcare burden. This can be useful to understand the impact on NMD on the healthcare system to better inform healthcare policy. Thus, we need additional epidemiological studies. They can inform an understanding of the magnitude of NMD at a population level, the natural history of the patients, the symptomatology and the etiology of NMD, the symptoms trend over time, the burden of disease, the healthcare follow-up, the impact of newer management interventions, etc. Some estimates of NMD prevalence exist, but based on highly variable methods (retrospective chart review, surveys, family histories, patient registries, etc.), populations (lifespan, adults or children), pathologies (all NMD, one NMD, a group of NMD). In addition, few studies are conducted using population-based health administration databases for a region or an entire country. French National Rare Disease Databank Over the whole French territory, all French expert centers record a homogeneous collection of data based on a minimum data set (SDM-MR) to document the care and state of health of patients with rare diseases in French expert centers. These data are then gathered in a data warehouse (Jannot et al., 2021). This data warehouse allows the secure collection and de-identified centralization of medical data from all patients followed-up in rare disease expert network and thus provides a robust and reliable epidemiological resource (Messiaen et al., 2021). This data collection enables to promote epidemiological surveillance for rare diseases, to asses feasibility of clinical trials, and to better assess the effect of national plans. The SDM-MR is amongst others composed of patient identification, family information, vital status, care course, care activity (ie, medical consultation, day hospitalization, traditional hospitalization, emergency hospitalization), patient histories, history of the disease, age at first signs, diagnostic, confirmation of diagnosis, treatment, ante and neonatal course... Aim and objective Overall, NMD make up a complex group of clinically and genetically heterogeneous conditions and can make NMD difficult to diagnose, to clearly document and record. Despite the need, few rigorous studies are available, especially in France, and in pediatric population. We conducted a comprehensive multicenter retrospective epidemiological study of pediatric NMD followed up in rare disease expert centers, between 2001 and 2022. A large historical French region provided a strategic framework to this analysis carried out in Southwest France. We conducted a retrospective cohort study using French National Rare Disease Registry to determine the prevalence, incidence, and mortality for children with NMD and its subtypes followed up in rare disease expert center in a large French region and to compare our data to the international studies. Methods We performed a retrospective cohort study following the RECORD Statement (Benchimol et al., 2015 ). Procedure Diagnoses Classification The BNDMR allowed us to identify patients with specific neuromuscular disorders using Orphanet nomenclature [ORPHADATA 2022] ( http://www.orphadata.org/cgi-bin/ORPHAnomenclature.html ). Specified ORPHA diagnoses considered as NMD in this study are listed in Annexe1. We used the 2021 version of the gene table of neuromuscular disorders (Benarroch et al., 2020 ) where NMD’s children were classified into 16 categories: 1) Muscular dystrophies; 2) Congenital muscular dystrophies; 3) Congenital myopathies; 4) Distal myopathies; 5) Other myopathies; 6) Myotonic syndromes;7) Ion channel muscle diseases; 8) Malignant hyperthermias; 9) Metabolic myopathies; 10) Hereditary cardiomyopathies -subdivided into 10A (non-arrhythmogenic) and 10B (arrhythmogenic); 11) Congenital myasthenic syndromes; 12) SMA & Motor neuron diseases; 13) Hereditary ataxias;14) Hereditary motor and sensory neuropathies; 15) Hereditary paraplegias; 16) Other neuromuscular disorders Study population and Participants We selected patients having at least one care activity at pediatric age (under 18) from May 1, 2001 to June 1, 2022 (defined as study endpoint), and having an NMD diagnostic code in BNDMR Datawarehouse and living in Southwest of France (estimated pediatric population of 2,617,994 inhabitants in 2021 census [INSEE 2022] ( https://www.insee.fr/fr/statistiques/1893198 )). Southwest France is organized in two geographic areas: Nouvelle-Aquitaine and Occitanie, which are subdivided in departmental sections (13 for Occitanie and 12 for Nouvelle-Aquitaine). All regional reference expert centers in Southwest France (Toulouse, Montpellier and Bordeaux Hospitals) provided their patients records. Vital status Vital status was retrieved from the Deceased persons file [INSEE 2022] to identify deceased patients and their date of death. Focus on specific diseases subtypes of NMD We detained the annual evolution of 4 NMD specific conditions (DMD, DMB, CMT1 and SMA). We focused on those because they are the most frequently encountered in clinical practice and the most serious. We also focused on those because new very expensive therapeutic solution emerges over the past few years for these specific conditions, which arouses medico-economic interest. Registration and ethics The study was approved by the French National Rare Disease Registry Review Board (IRB00013741). This study was partially supported by the FILNEMUS healthcare chain through the 2021 AAP Program. Convention 2021 − 0253 AP-HM-Filnemus. Statistical method Age, date of first consultation, date of first symptoms leading to consultation, date of confirmed diagnosis were described using median and IQR. The prevalence of patients followed-up in expert centers with NMD in each South-West French department was estimated as the ratio of the number of patients seen in the expert centers and living in the geographic area divided by the population size living in the region during the study period according to the INSEE census (2021). We exclude the five north departments of Nouvelle-Aquitaine because of their geographic proximity to Limoges University Hospital that is not part of the present study. We defined annual incidence of patients followed-up in expert centers with NMD by the ratio of the number of confirmed patients given their year of inclusion on the population estimate living in the region during the study period according to the INSEE census (2021). We use Poisson confidence intervals of 95% for prevalence and incidence. We computed the distance between the residence of the patients and the attended expert center using the great-circle method and described it with median and IQR. We performed survival from birth analyses using Kaplan-Meier estimates, for muscular dystrophies, congenital dystrophies and myopathies and spinal muscular atrophies. The statistical software R for Windows, version 4.2.2 was used to performed analysis. Results Demographic information Over the period, 1,621 children were included (Figure 1) with a median age at last follow-up of 14 years (IQR = 8-17) and a median age at inclusion of 8 years (IQR = 4-13). Age at inclusion varies between the NMD groups (Figure 3). The sex ratio was 1.64 in favor of male. 154 of these patients were deceased with a median age at death of 3 year (IQR = 1-19). Most deaths occurred in patients affected by SMA and motor neuron diseases (63 death, mostly before 1 year), and muscular dystrophies (49 deaths, mostly after 21 years). Patients were followed for a median period of 8 years (IQR = 4-12). The median age at first signs was 4 years (IQR = 1-9) while the median age at diagnosis was 6 years (IQR=2-11) for confirmed diagnoses. Age at first sign deeply varies between groups. For the 1400 patients having a confirmed diagnosis, the median delay to diagnosis was 10 months (IQR = 0-36) showing that diagnosis was confirmed within the first year of follow-up. Prevalence Based on census data and with a total population of 2,045,502 inhabitants under 18 years old, the regional prevalence of NMD patients followed-up in expert centers in Southwest region was 37.9 for 100,000 inhabitants under 18 years old (IC95 = [35.3-40.7]). Figure 2 provides detailed prevalence estimates among French departments. Table 1 provides an overview of NMD included patients according to diagnostic groups and corresponding prevalence. Most prevalent groups of diseases were hereditary motor and sensory neuropathies (9.1; IC95 = [7.9-10.6]) and muscular dystrophies (8.8; IC95 = [7.6-10.2]). Table 2 present prevalence by age class and NMD groups. This prevalence increases with age when looking at the whole cohort. We estimated prevalence at 12.7 (CI95% [9.7-16.2]) in the 0 to 5 age group, at 35.4 (CI95% [30.7-40.6]) in the age group between 5 and 10 years, 51.1 (CI95% [45.6-57.0]) in the 10 to 15 years age group and 53.0 (CI95% [45.8-60.9]) in the 15 to 18 years age group for 100,000 inhabitants of the corresponding age group. As shown by Table 3, the prevalence firstly increases due to ramp-up process, and then progressively decrease after 2018. Muscular disorders sub-cohort analysis Among the 179 patients with SMA, 78 were males (44 %). Becker muscular dystrophy (N=71) and Duchenne muscular dystrophy (N=215) include only five and two women respectively. Among the 236 CMT1 patients, 124 were males (53%). According to table 1, the regional prevalence of patients affected by SMA followed-up in expert centers was 3.2 [2.5-4.1], for BMD was 1.3 [0.9-1.9], for DMD was 5.0 [4.1-6.1] and for CMT1 was 6.2 [5.1-7.3]. Regarding incidence, SMA rise to a median of 8.0 (IQR = 5.0, 10.3), BMD to 3.0 (IQR = 2.0-4.0), DMD to 8.0 (IQR = 2.0-12.0) and CMT1 to 10.0 (IQR = 3.0-17.0). SMA patients at inclusion were younger than BMD, DMD or CMT1 with a median age of 1.4 (IQR = 0.4-8.2) against 8.7 (IQR = 5.3-12.4), 7.5 (IQR = 5.1-10.3) and 8.5 (IQR = 5.1-12.4) respectively. We observed, in Figure 4, for SMA first signs at a median age of 0.8 year (IQR = 0.2 - 2.0) whereas the median age at diagnosis was 0.8 year (IQR = 0.3-2.0). Regarding BMD, we observed a median age of 6.0 years (IQR = 3.5-9.5) whereas the median age at diagnosis was 7.5 years (IQR = 5.0-10.2). For DMD, we observed a median age of 3.0 years (IQR = 1.8-6.9) whereas the median age at diagnosis was 4.0 years (IQR = 2.5-6.0). Finally, for CMT1, we observed a median age of 4.3 years (IQR = 2.0-8.1) whereas the median age at diagnosis was 7 (IQR = 4.0-10.3). Most deaths occurred less than two years after first signs for SMA, more than 7 years after for DMD and none in the BMD group (Figure 5). Discussion Prevalence of Pediatric Neuromuscular Disorders in pediatric patients: a consensus at last? Our overall prevalence is based on a large cohort of patients under 18 years (838 in all and 775 still alive) diagnosed with NMD and followed-up in three experts centers between 2001 and 2022 in Southwest region. Even if this study only includes regional data, our data are current and of good quality and our prevalence could not greatly differ from French national data. We found a regional prevalence of overall NMD patients under 18 years old of 37.9 for 100,000 inhabitants. This prevalence is comparable to those found by Woodcock et al. ( 2016 ), which is one of the few pediatric prevalence studies. In their study done in Yorkshire, authors found an overall prevalence of NMD conditions of 36.9 per 100,000 in a population under 16 years old. NMD included in their studied population is very close to ours, so the similarity in the results adds to their validity. Few other researches addressed the special issue of prevalence in pediatric population of NMD or as part of a larger study on general population (Theadom et al., 2019 ; Pagola-Lorz et al., 2019 ; Rose et al., 2019 ). Our results differ, but the reliabilities of the pediatric prevalence announced in these studies is questionable. Rose et al. ( 2019 ) conducted a very large cohort study based on the population of Ontario (Canada) where adults and children with NMD were rigorously identified using health administrative databases. 27,823 children were eligible for 2014' cohort creation establishing an annual prevalence of 75.9. However, authors accounted ‘cerebral palsy’ (24.1) and ‘spina bifida’ (13.6) in NMD diagnoses, which is quite uncommon in such NMD prevalence studies. Excluding these two categories, annual prevalence in NMD children falls 38.2 for children, very close to ours. Pagola-Lorz et al. ( 2019 ) and Theadom et al. ( 2019 ) report a pediatric prevalence of NMD of 21.87 and 28.11 respectively, but both excluding SMA and regarding data under 14 years, while prevalence greatly increases with age in both. Our pediatric prevalence is also quite different of those identified in Muller et al. study routinely cited in support of NMD prevalence. The total NMD pediatric prevalence in their study (57.8 per 100.000) was higher than the prevalence of NMD related by our study and studies previously cited. But authors themselves added that the prevalence found in their study greatly higher than other, including higher than proposed in epidemiological study that combined populations from different parts of the world (Emery, 1991 for example). If their finding could be due to a small number of children under 18 years old (55), it may also reflect ethnic difference according to the authors. This explanation seems confirmed by the results of several studies (Theadom et al., 2019 ; Woodcook et al., 2016) that highlighted some considerable variation in prevalence by ethnic groups. To date, an NMD’ pediatric prevalence about 38/100000 may reflect a consensus among different countries. However, our work highlights an NMD prevalence fluctuation between studies realized over the last decades. This suggest that significant variation between methodologies or datasets used greatly impact prevalence estimation. The NMD included, the age groups studied, the ethnicities concerned, varied to one study from another. Studies comparisons are therefore problematic. Another point that hindered the possibility of comparison between studies, is the period studied. Innovative therapies are in constant evolution, and compared prevalence before or at the beginning of their availabilities is not rigorous since they progressively increased the useful life of NMD patients, especially for young children. Concerning pediatric, very few researches actually addressed the special issue of prevalence in pediatric population of NMD, intrinsically or as part of a larger study on general population. But the arrival of new very expensive therapies forces us to rigorously estimates the number of patients involved at a territorial, national or world level, to better inform healthcare policy on the burden of such care on the healthcare system. We therefore urgently need rigorous prevalence studies, with a consistent and standardized methodology between countries, applicable and adopted by all. The same observation was previously made on numerous occasions in studies or review for many years, which express the need to greater consistency in the conduct of NMD epidemiological studies to allow and ensure comparisons to be made between studies. However, nothing happens despite concrete and practical proposals (Theadom et al., 2014 ). Accordingly, prevalence studies guidelines should be discussed and adopted by consensus in world conference on NMD. It is essential to homogenize inclusion or exclusion criteria, selection of conditions that have been included or excluded from the definition of NMD, the use of more inclusive or rather the opposite more limited definition, to clearly defined some range-ages of interest used from study to study, to sought and noted the ethnicity of patients, to specified the datasets used (research or clinical or multiple data sources), etc. Only in this way will prevalence rates should be compared across studies. Prevalence temporal trends Two studies in the recent past have underlined the number of people with MNM has been steadily rising (Carey et al., 2021 ; Rose et al., 2019 ). Rose et al. ( 2019 ) used health administrative databases to describe trends in incidence, prevalence, and mortality of adults and children with NMD on a population-based (Ontario, Canada) cohort study (2003 to 2014). Authors observed a rising prevalence of NMD over time among both adults and children (2003 to 2014). Carey et al ( 2021 ) used the Clinical Practice Research Datalink, a primary care database in the UK, to estimate trends in the recording of neuromuscular disease in UK primary care between 2000–2019 based on incidence and prevalence rates in each year. Authors observed overall prevalence grew by 63% since 2000 with temporal trends showing the number of NMD patients is steadily increasing year by year. For Carey et al. ( 2021 ) as for Rose et al. ( 2019 ), new cases cannot solely explain increasing prevalence year by year, as incidence remained constant, but that it may be due to better recording. Our data, which run from 2001 to 2021, support this assumption. We can see a continuous, steady growth in rate of prevalence from 2001 to 2017 (Fig. 6 ). In France, this period corresponds to the historical implanting of centers of rare diseases and to the creation and progressive implementation of national research database, CEMARA (Messiaen et al., 2008 ) at first and then BAMARA (Jannot et al., 2021). 2017 is a crucial point in France with the introduction of BAMARA, its deployment in all rare diseases’ centers, and its used making systematic and compulsory as part as third rare diseases plan, leading de facto to better and reliable healthcare data recording. Since 2017, our data are therefore more reliable. And watching exclusively on research' data specifically covering these last six years, we don’t find an increasing of prevalence of NMD per years but rather a clear stabilization in the number of NMM children followed expert care centers has been recognized. Increasing pointed by Rose et al. ( 2019 ) and Carey et al. ( 2021 ), as by our own data from 2017, might therefore be an artefact being but the reflection of a data filling effect. Our finding concurs with the Carey et al. ( 2021 ) assumption, in believing that this increasing may partially be due to better recording. In addition, most studies that contain substantive pediatric data, found that prevalence increases with age across all diagnoses except SMA. Rose et al. ( 2019 ) found that childhood disease prevalence increased by 10% per year. For authors, the largest increase was in children 0 to 5 years. Theadom et al. ( 2019 ) that found that prevalence remained relatively stable across the lifespan following 5 years of age have enhanced this finding. Our prevalence increases with age, to 12.7/100000 in the age group 0–5 years, from 53 in the 15-18-years age group (Table 2 ). As was already demonstrated, we show a very significant gap forms at the age of 5, with more than a two-fold increase prevalence after 5. Then, the prevalence increases progressively but we note a stabilized trend after 10 years. Incidence and prevalence data years by years in pediatric population will be required, probably by diagnosis, in order to better understand the course of NMD throughout childhood. Focus on DMD, BMD, CMT1 and SMA The most common NMD in our study was dystrophinopathies (17.6%: 13.2% Duchenne and 4.4% Becker), followed by CMT1 (14.5%), SMA (11%) and DM1 (8.5%). These four diagnoses made more than half of the overall prevalence of our NMD population. Few NMD prevalence study exists on pediatric population and distribution of NMD diseases differs between children and adults. However, our results are quite congruent with previous studies on pediatric prevalence of NMD. Woodcock et al. ( 2016 ) found Dystrophin-related NMD as the most prevalent condition of their population of 261 NMD children, 16.9 per 100,000 (61; 23%), followed by CMT1 (31; 12%), congenital myopathies (29; 11%) and SMA (27; 10%). In Thongsing et al. ( 2020 ), in a quite as large pediatric NMD population (217), the most common inherited NMD were the Dystrophinopathies, including Duchenne / Becker muscular dystrophy (58; 27%), followed by SMA (25; 11.5%) and Hereditary Motor Sensory Neuropathy (CMT1) (16; 7%). Our study therefore strengthens its results on a three-time larger sample. Focus DMD/BMD DMD/BMD occurs in males, but in order to calculate the scope of the burden for society, most studies report prevalence estimates in relation to the general population. We did the same and our estimate is rather comparable to most previous studies and to systematic review and meta-analysis of Crisafulli et al. ( 2020 ), Theadom et al. ( 2014 ) and Mah et al. ( 2014 ). Crisafulli et al. ( 2020 ) found a DMD prevalence of 2.8 cases (95% CI: 1.6–4.6) per 100,000 in the general population on about 40 studies reporting the global epidemiology of DMD. Theadom et al. ( 2014 ) found a prevalence for DMD of 1.7–4.2 per 100,000 and for BMD of 0.4–3.6 per 100,000 based on studies classified as having a low risk of bias (15/38). The systematic review and meta-analysis of Mah et al. ( 2014 ) analyzed the prevalence for DMD and BMD but in relation to male population only. Authors found a prevalence of DMD at 4.78 and BMD of 1.53 (95% CI 1.94–11.81) per 100.000 males based on 31 studies. Comparing findings with two alternative methods is a challenge, but Crisafulli et al. ( 2020 ), Theadom et al. ( 2014 ) and Mah et al. ( 2014 ) estimates seems relatively similar, and our prevalence appears little higher -at least for DMD. However, these reviews considered prevalence in all age groups and not in pediatric groups. Difference thus could be probably due to the early mortality of DMD patients. Despite improvement of survival, few affected individuals survive beyond the third decade (Passamano et al., 2012 ) with a median survival of 24 years (Rall & Grimm, 2012 ). Because death occurs in early adulthood, a higher pediatric prevalence seems therefore logical. Parents can identify the first symptoms of DMD early, when physical ability in their children diverges markedly from that of their peers around 2–3 years (Mercuri et al., 2019 ). Significant and visible general motor delays (gait problems, delay in walking, a waddling gate, difficulties with climbing stairs, and frequent falls…), then a little later learning difficulty, and speech problems, are indeed perceptible from early development. In our DMD cohort, ours results are congruent with the recent study of D'Amico et al. ( 2017 ) that have reported mean age at diagnosis was 41 months (range 0.3–135 months), 10 months (range 10 days to 80 months) before the first suspicions (mean age 31 months; range 0–95 months). Authors note that it’s about one year less than the age reported in Bushby et al, ( 2010 , probably related according to them to the fact that in Italy blood tests including transaminases and CK are routinely requested by pediatricians when motor delays is present, as in France (Verloes et al., 2012 ). We agree therefore the authors to say that a CK test screening should be performed in early infancy in order to reduce the delay of diagnosis. Regarding BMD, we observed a median age of 6.0 years at first signs (IQR = 3.6–9.5) whereas the median age at diagnosis was 7.5 years (IQR = 5.0–10.2). Few studies focused on natural history of BMD when the onset is in childhood, which does not allow comparison, but our data seems congruent with clinical practice. BMD is indeed less severe and has a milder clinical course than DMD. The onset of symptoms is usually later than in DMD. The clinical heterogeneity of BMD is extreme, and the age of onset varies widely (Angelini et al. 2019 ). The spectrum of clinical presentations ranges from asymptomatic with screening via a liver test to a loss of ambulation occurring in the teenage years. Focus CMT1 We found a pediatric prevalence of CMT1 at 6.2 (5.1–7.3) per 100.000, without analyzable data between 0 to 5 years and with first reliable epidemiological data after 5 years. Epidemiological studies of CMT disease are scarce, and in the absence of data collection programs, longitudinal or natural history studies, knowledge of CMT pediatric epidemiology is even more limited. Patients have a long history of symptoms before the diagnosis, that come in late in life, with a mean age estimated of 31.8 years (Gudmundsson et al., 2010 ), often caused by discreet symptomatology, slow progression rate, and insidious onset in the first decades of life. The average delay of clinical diagnosis, even in families known to have CMT, is more than 10 years (Jani-Acsadi et al., 2015 ). In a cohort of 39 patients with infantile presentation, the mean age at diagnosis was 8.5 years (Ounpuu et al., 2013). Mean age at diagnosis and mean age for first symptom in the CMT1 subtype for pediatric population is not available to our knowledge, but for our part, we were able to estimate a median age of first symptoms of 4.3 years (IQR = 2.0-8.1) and a median age at diagnosis at 7 years (IQR = 4.0-10.3). With regard to prevalence, Ma et al. (2023) describe the distribution of CMT disease among the worldwide population in a relevant meta-analysis. Authors examine the prevalence of CMT for the general population, as well as the subgroups (age, gender, region, and disease subtypes). 31 included studies are detailed in their meta-analysis but only 2 old studies (1983 and 2000) focused on non-adult populations, and some few conducted on the all-age populations (comprising children). CMT prevalence is logically higher in older than in younger age groups. Extracted from their meta-analysis, only Carey et al. ( 2021 ), Theadom et al. ( 2019 ) and Mladenovic et al. ( 2011 ) provided recent pediatric epidemiological data (post 2010). However, although both Carey et al. ( 2021 ) and Theadom et al. ( 2019 ) indicated the estimates prevalence for different subtypes, they did not discriminate CMT in subtypes for pediatric population. The pediatric prevalence for CMT1 only is not available. Theadom et al. ( 2019 ) found a pediatric prevalence for all CMT at 9.1 (6.1–13.5) quite similar to Carey et al. ( 2021 ) that found a pediatric prevalence for all CMT at 8.9. In literature, CMT1 has been reported to be the most common CMT type, accounting for between 37.6% and 84.0% of cases (Barreto et al. 2016 ). This estimation brings up the CMT1 pediatric population of both studies to 3.4 to 7.6, in line with our finding and those of Mladenovic et al. ( 2011 ). Indeed, in Mladenovic et al. ( 2011 ) study, as in ours, CMT1 prevalence under 5 years old is unavailable and authors found a pediatric prevalence for CMT1 at 5/100000 (1.6–11.6) under 14 years old. Overall, based on previous studies and our data, we can conclude that pediatric prevalence of CMT1 could be endorsed about 5 per 100.000. Focus SMA The regional prevalence of patients affected by SMA followed-up in expert centers was 3.2 [2.5–4.1]. Only a few estimations studies have been performed to assess the prevalence of SMA and most of these have been conducted before 2000. When examining all types of SMA together in these studies, a prevalence of around 1–2 per 100,000 persons is observed (Verhaart et al., 2017 ) for most country. A more recent study was available, conducted by direct contact with two genetic laboratories across Europe (Verhaart et al., 2017 b). In this study, even if there was considerable inter-country variability, SMA prevalence ranged respectively from 0.01 to 2.43 per 100,000 (TREATNMD Global SMA Patient Registry) and 0.00 to 4.11 per 100,000 (Care and Trial Sites Registry CTSR). However, both registries only included patients before 2014 and the launch of innovative therapies that increases significantly the survival of patients with SMA. With a growing number of therapies being developed since 2017, the natural history of SMA has indeed changed. Moreover, pediatric prevalence and overall prevalence (lifespan, children and adults) cannot be easily compared due to high early death for a substantial number of patients. There is therefore an increasing need for others new pediatric SMA incidence and prevalence estimations. The majority of SMA children in our cohort were classified as SMA type I (79/179 or 44%) followed by 59 with SMA2 (33%), 29 with SMA3 (18%), 10 with other SMA. This is in good agreement with the percentages of patient classified into different types of SMA in the Cure SMA database (one of the largest patient-reported data repositories on SMA patients worldwide (Belter et al., 2018 )) that found: SMA1 39%; SMA2 31%; SMA3 19% (Sun et al., 2023 ). The percentages of females of SMA (56.4%) were higher than males for overall SMA cohort (male-to-female sex ratio 0.77) and for all SMA types (male-to-female sex ratio 0.76 for SMA1 and 0.45 for SMA3 and 0.9 for SMA2). This finding is interesting since no consensus has been reached for this question. An old study from Pearn ( 1978 ) reported a male to female ratio of 2.0 in SMA1, but a sex ratio in male disadvantage is commonly admitted. However, these have not been consistent, and several studies have reported no sex differences in sex ratio. This question could be addressed, especially because sex vulnerability in SMA is identified with some studies that have indicated the infantile form of SMA is more severe in males (Sun et al. 2023 ). The first medical visit for SMA patients in the reference center came early with a median age of 1.4 (IQR = 0.4–8.2), which is consistent with the disease evolves and its gravity. In the first year of life, 72 patients (53%) were diagnosed. We observed for overall SMA first signs and age at diagnosis at a median age of 0.8 year, corresponding to a rapid diagnostic. By SMA subtypes, the gap between first signs and diagnosis is quite similar for SMA1 and SMA2 (few weeks) and increased for SMA3 (1.5 years between emerging of first symptoms and diagnosis). In our study, survival for SMA1 children at 1, 2, 4 and 8 years was 36%, 29%, 27% and 27%, respectively. The survival probabilities of SMA2 patients at 1, 2, 4 and 8 years was 100%, 100%, 97% and 93%, while SMA3 patients generally have normal life expectancy. These findings are similar with those from Farrar et al. ( 2013 ) or Chung et al. ( 2004 ) and concordant with clinical experience. We just observed a slight difference for the clinical course and death for SMA1, which probably reflect advances in medical care, and improvement in life expectancy. Conclusion Our study is the first French prevalence estimation of NMD in pediatric population. Based on a large retrospective data collection (1621 NMD children), our results support that an NMD’ pediatric prevalence about 38/100000 might be reflected a consensus among different country. However, an NMD prevalence fluctuation between studies realized over the last decades is too common and rigorous prevalence studies are urgently needed, with a consistent and standardized methodology between countries, applicable and adopted by all. Moreover, we believe that increasing general NMD prevalence pointing in some studies may partially be due to better recording of healthcare data from institutions and is probably an artefact. Regarding NMD by subtypes, we found three interesting findings. First, as expected given clinical and previous studies, French NMD pediatric prevalence increases with age across all diagnoses except SMA. Secondly, pediatric CMT1 suffers from sparse medical literature (epidemiological and long-term natural history studies), but our result support a pediatric prevalence about 6.2 per 100.000. Thirdly, our DMD and BMD pediatric prevalence -respectively 5 and 1.3- is congruent with those reported previously. Importantly, we strongly encourage the use of CK test screening in early infancy for DMD, since this medical practice realized in Italy and France seems to reduce the delay of diagnosis. Our current study only includes regional data, thus prevalence and prognosis could differ from French national data. Regional variations prevalence in other studies, especially according to ethnic differences in population between country' regions, highlight the need to conduct a French national prevalence study in order to ensure accuracy of our prevalence data. This study does, however, provide important details for adjusting healthcare policies within our region, as well as at national level. Abbreviations BNDMR: Banque Nationale de Données Maladies Rares - National Rare Disease Databank BMD: Becker Muscular Dystrophy CMD: Congenital Muscular Dystrophy CMT: Charcot-Marie-Tooth CK: Creatinine Kinase DM1: Myotonic Dystrophy type 1 DMD: Duchenne Muscular Dystrophy FSHD: Facioscapulohumeral Dystrophy ICD: International Classification of Diseases IMDs: Inherited Muscle Diseases INSEE: Institut National de la Statistique et des Études Économiques - National Institute of Statistics and Economic Studies LGMD: Limb Girdle Muscular Dystrophy NMD: Neuromuscular Disorders SDM-MR: Set de Données Minimum Maladies Rares - Minimum Data set for Rare Diseases Declarations Ethics approval and consent to participate The study protocol was approved by the Ethical Committee for Medical Research and the institutional ethics committee (IRB approval number: IRB00013741). Consent for publication Not applicable. Availability of data and materials Data are available from the authors upon reasonable request and with permission of BNDMR. Competing interests / Conflict of Interest / Disclosures The authors declare that they have no competing interests. Funding/Support This study was partially supported by the FILNEMUS healthcare chain through the 2021 AAP Program. Convention 2021-0253 AP-HM-Filnemus Authors’ contributions MB and CC are principal investigator of the study, conceived the idea for the study and the design, and were major contributors in writing the protocol. CM and ASJ analyzed and interpreted the data, wrote the method and results parts and helped to reflected the discussion based on results. EW, FR, UWL, LT, CE and EB was involved in data collect, quality monitoring and scientific expertise. All the authors read, reviewed and approved the final manuscript as submitted and agreed to be accountable for all aspects of the work. 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Male (%) N Cases N. <18 Alive & < 18 Prevalence* (IC95%) Muscular dystrophies All 430 (26.5) 363 (84.4) 409 185 181 8.8 (7.6 - 10.2) DMD 215 (13.2) 213 (99.1) 203 105 102 5 (4.1 - 6.1) BMD 71 (4.4) 66 (93) 67 27 27 1.3 (0.9 - 1.9) LGMD 52 (3.2) 28 (53.8) 52 16 15 0.7 (0.4 - 1.2) FSH 57 (3.5) 31 (54.4) 55 23 23 1.1 (0.7 - 1.7) Other 37 (2.3) 27 (73) 34 16 16 0.8 (0.4 - 1.3) Congenital muscular dystrophies 64 (3.9) 36 (56.2) 60 36 35 1.7 (1.2 - 2.4) Congenital myopathies 82 (5) 45 (54.9) 76 46 41 2 (1.4 - 2.7) Distal myopathies <10 (NC) 4 (NC) <10 <10 <10 NC Other myopathies All 38 (2.3) 8 (21.1) 34 16 15 0.7 (0.4 - 1.2) MAI 32 (2) 5 (15.6) 28 13 12 0.6 (0.3 - 1) Other <10 (NC) 3 (NC) <10 <10 <10 NC Myotonic syndromes All 172 (10.6) 105 (61) 167 74 73 3.6 (2.8 - 4.5) DM1 138 (8.5) 79 (57.2) 134 57 56 2.7 (2.1 - 3.6) Other 34 (2.1) 26 (76.5) 33 17 17 0.8 (0.5 - 1.3) Ion channel diseases 36 (2.2) 25 (69.4) 34 19 19 0.9 (0.6 - 1.5) Malignant hyperthermias <10 (NC) 5 (NC) <10 <10 <10 NC Metabolic myopathies 41 (2.5) 24 (58.5) 39 21 20 1 (0.6 - 1.5) Hereditary cardiomyopathies <10 (NC) 2 (NC) <10 <10 <10 NC Congenital myasthenic syndromes 34 (2.1) 19 (55.9) 32 26 23 1.1 (0.7 - 1.7) SMA & Motor neurone diseases All 179 (11) 78 (43.6) 168 110 66 3.2 (2.5 - 4.1) SMA1 79 (4.9) 34 (43) 73 60 22 1.1 (0.7 - 1.6) SMA2 59 (3.6) 28 (47.5) 56 31 29 1.4 (0.9 - 2) SMA3 32 (2) 10 (31.2) 30 12 12 0.6 (0.3 - 1) Other 10 (0.6) 7 (70) 10 <10 2 0.1 (0 - 0.4) Hereditary ataxias 34 (2.1) 19 (55.9) 34 13 13 0.6 (0.3 - 1.1) Hereditary motor and sensory neuropathies All 360 (22.2) 194 (53.9) 347 188 187 9.1 (7.9 - 10.6) CMT1 236 (14.5) 124 (52.5) 226 127 126 6.2 (5.1 - 7.3) CMT2 and others 125 (7.7) 70 (56) 121 61 61 3 (2.3 - 3.8) Hereditary paraplégias <10 (NC) 3 (NC) <10 <10 <10 NC Other neuromuscular disorders 132 (8.1) 80 (60.6) 129 92 91 4.4 (3.6 - 5.5) Total Overall 1621 (100) 1009 (62.2) 1547 838 775 37.9 (35.3 - 40.7) § Scoped means within Great South-West but not in the five north departments of Nouvelle-Aquitaine; *Prevalence for 100,000 inhabitants under 18 years old Table 2: Characteristics of patients with NMD according to diagnostic subgroups and age class at study endpoint or at death Subgroup Name All [0-5[ [5-10[ [10-15[ [15-18[ N. Cases N Alive Prevalence (IC95%) N. Cases N Alive Prevalence (IC95%) N. Cases N Alive Prevalence (IC95%) N. Cases N Alive Prevalence (IC95%) N. Cases N Alive Prevalence (IC95%) and <18 Muscular dystrophies 185 181 8.8 (7.6 - 10.2) <10 <10 NC 44 43 7.6 (5.5 - 10.2) 81 81 13.1 (10.4 - 16.3) 52 49 13.2 (9.7 - 17.4) DMD 105 102 5 (4.1 - 6.1) <10 <10 NC 20 20 3.5 (2.2 - 5.5) 50 50 8.1 (6 - 10.7) 30 27 7.3 (4.8 - 10.6) BMD 27 27 1.3 (0.9 - 1.9) <10 <10 NC 10 10 1.8 (0.8 - 3.3) <10 <10 NC <10 <10 NC LGMD 16 15 0.7 (0.4 - 1.2) <10 <10 NC <10 <10 NC <10 <10 NC FSH 23 23 1.1 (0.7 - 1.7) <10 <10 NC <10 <10 NC 12 12 1.9 (1 - 3.4) <10 <10 NC Other 16 16 0.8 (0.4 - 1.3) <10 <10 NC <10 <10 NC <10 <10 NC Congenital muscular dystrophies 36 35 1.7 (1.2 - 2.4) <10 <10 NC 15 15 2.7 (1.5 - 4.4) <10 <10 NC 10 <10 NC Congenital myopathies 46 41 2 (1.4 - 2.7) <10 <10 NC 12 10 1.8 (0.8 - 3.3) 17 17 2.7 (1.6 - 4.4) 10 10 2.7 (1.3 - 4.9) Distal myopathies <10 <10 NC <10 <10 NC <10 <10 NC <10 <10 NC Other myopathies 16 15 0.7 (0.4 - 1.2) <10 0 0 (0 - 0.8) <10 <10 NC <10 <10 NC <10 <10 NC MAI 13 12 0.6 (0.3 - 1) <10 0 0 (0 - 0.8) <10 <10 NC <10 <10 NC <10 <10 NC Other <10 <10 NC <10 <10 NC <10 <10 NC Myotonic syndromes 74 73 3.6 (2.8 - 4.5) <10 <10 NC 19 19 3.4 (2 - 5.3) 34 34 5.5 (3.8 - 7.7) 13 13 3.5 (1.9 - 6) DM1 57 56 2.7 (2.1 - 3.6) <10 <10 NC 14 14 2.5 (1.4 - 4.2) 25 25 4 (2.6 - 6) 10 10 2.7 (1.3 - 4.9) Other myotonia 17 17 0.8 (0.5 - 1.3) <10 <10 NC <10 <10 NC <10 <10 NC Ion channel diseases 19 19 0.9 (0.6 - 1.5) <10 <10 NC <10 <10 NC <10 <10 NC Malignant hyperthermias <10 <10 NC <10 <10 NC <10 <10 NC <10 <10 NC Metabolic myopathies 21 20 1 (0.6 - 1.5) <10 <10 NC <10 <10 NC <10 <10 NC <10 <10 NC Hereditary cardiomyopathies <10 <10 NC <10 <10 NC Congenital myasthenic syndromes 26 23 1.1 (0.7 - 1.7) <10 <10 NC <10 <10 NC 10 <10 NC <10 <10 NC SMA & Motor neurone diseases 111 65 3.2 (2.5 - 4.1) 29 18 3.7 (2.2 - 5.8) 26 16 2.8 (1.6 - 4.6) 39 21 3.4 (2.1 - 5.2) 17 10 2.7 (1.3 - 4.9) SMA1 61 22 1.1 (0.7 - 1.6) 20 11 2.2 (1.1 - 4) 15 <10 NC 20 <10 NC <10 0 0 (0 - 1) SMA2 31 29 1.4 (0.9 - 2) <10 <10 NC <10 <10 NC 13 12 1.9 (1 - 3.4) <10 <10 NC SMA3 12 12 0.6 (0.3 - 1) <10 <10 NC <10 <10 NC <10 <10 NC <10 <10 NC Other <10 <10 NC <10 <10 NC <10 0 0 (0 - 0.7) <10 <10 NC <10 0 0 (0 - 1) Hereditary ataxias 13 13 0.6 (0.3 - 1.1) <10 <10 NC <10 <10 NC <10 <10 NC Hereditary motor and sensory neuropathies 188 187 9.1 (7.9 - 10.6) <10 <10 NC 42 41 7.3 (5.2 - 9.8) 82 82 13.3 (10.5 - 16.5) 56 56 15.1 (11.4 - 19.5) CMT1 127 126 6.2 (5.1 - 7.3) <10 <10 NC 33 32 5.7 (3.9 - 8) 55 55 8.9 (6.7 - 11.6) 33 33 8.9 (6.1 - 12.5) CMT2 and others 61 61 3 (2.3 - 3.8) <10 <10 NC <10 <10 NC 27 27 4.4 (2.9 - 6.3) 23 23 6.2 (3.9 - 9.3) Hereditary paraplegias <10 <10 NC <10 <10 NC <10 <10 NC <10 <10 NC Other neuromuscular disorders 92 91 4.4 (3.6 - 5.5) <10 <10 NC 32 32 5.7 (3.9 - 8) 33 33 5.3 (3.7 - 7.5) 19 19 5.1 (3.1 - 8) Whole cohort 838 775 37.9 (35.3 - 40.7) 79 62 12.7 (9.7 - 16.2) 216 200 35.4 (30.7 - 40.6) 335 316 51.1 (45.6 - 57) 209 197 53 (45.8 - 60.9) Table 3: Prevalence of patients with NMD registered in BNDMR for 100 000 inhabitants under 18, by year Year N. alive and < 18 Prevalence (IC95) 2001 66 3.6 (2.8 - 4.6) 2002 87 4.7 (3.8 - 5.8) 2003 110 5.9 (4.8 - 7.1) 2004 127 6.7 (5.6 - 8) 2005 147 7.7 (6.5 - 9.1) 2006 166 8.6 (7.3 - 10) 2007 184 9.6 (8.2 - 11.1) 2008 198 10.1 (8.8 - 11.6) 2009 226 11.5 (10 - 13.1) 2010 419 21.1 (19.1 - 23.2) 2011 506 25.3 (23.1 - 27.6) 2012 552 27.4 (25.2 - 29.8) 2013 586 28.9 (26.6 - 31.3) 2014 627 30.6 (28.3 - 33.1) 2015 658 32 (29.6 - 34.5) 2016 704 34.2 (31.7 - 36.8) 2017 767 37.3 (34.7 - 40) 2018 797 38.7 (36 - 41.5) 2019 818 39.7 (37.1 - 42.6) 2020 840 40.9 (38.2 - 43.7) 2021 843 41.1 (38.4 - 44) 2022 784 38.3 (35.7 - 41.1) Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4343784","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":301999380,"identity":"d8727381-e5e9-4416-9f0e-26f086822114","order_by":0,"name":"Maelle Biotteau","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYHACxgMPGBgS2KA8ORiDH5+eAwlgLcyMDUCOMUyLZAMhLQxQLYkwlTi16LYfPnAgoYIhj4+9//iDDzWH0/uk2x8+rsxhkDDHocfsTFrCgYQzDMVsPIcZG2ccO5zbJnPG2PDsNgYJmQM4tBzIMTiQ2MaQ2CaRzNjMwwbUIpHDJtm4jaFOAofDzM6//3Ag8R9Uy59/h9PZJNKf/wRqkcCp5UYOwwGglyFaGNsOJ7BJJJgx4tfyzOBAwjEJkF8MZ/b2pRsCHWYMdJgEbi3nkx8CA8omT7698cGHH9+s5eVnpD/82LjNBqcWKMCUJqBhFIyCUTAKRgFeAAAp6FykXC3OKQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-5785-7828","institution":"INSERM","correspondingAuthor":true,"prefix":"","firstName":"Maelle","middleName":"","lastName":"Biotteau","suffix":""},{"id":301999381,"identity":"e263262d-2c83-456b-a7bc-0483ab851dd4","order_by":1,"name":"Claude Messiaen","email":"","orcid":"","institution":"AP-HP: Assistance Publique - 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The multitude of possible sites of injury (second motor neuron, axons, Schwann cells, neuromuscular junction, muscle, or combination of these sites) lead to clinical presentation heterogeneity. Some forms of NMD are life-limiting while some others can be successfully treated (Yuki \u0026amp; Hartung, 2012). However, a variety of common symptoms can be mentioned include progressive muscle weakness, cramps, stiffness, joint deformities, chronic pain, respiratory and/or cardiac involvement, a broad range of cognitive impairments. This gave rise to a major impact on the quality of life, social, emotional and societal burden and health budgets worldwide. NMD can appear at any age. Some forms manifest at birth or early childhood (D\u0026rsquo;Amico et al., 2011) whereas the incidence of some other forms increases with age (Turner \u0026amp; Hilton-Jones, 2014).\u003c/p\u003e\n\u003cp\u003eSome forms of NMD are hereditary while others are acquired. In pediatrics, the majority of neuromuscular disorders have a genetic basis, as either a de novo or an inherited pathogenic variant in a single gene (Darras, 2015). Disease genes remain to be discovered, but hundreds of neuromuscular disease genes have already been identified (http://www.musclegenetable.fr).\u003c/p\u003e\n\u003cp\u003eEach NMD condition is defined as rare diseases due to their low prevalence affecting no more than 1 in 2,000 (Nguengang Wakap et al., 2020). Combined NMD entity would however represent a more significant group, with a prevalence close than other neurological diseases as Parkinson or multiple sclerosis for eg. (Deenen et al., 2015). Some recent studies suggest that number of people living with NMD is intrinsically rising (Rose et al. 2019; Carey et al., 2021). In addition, until recently, some NMD were considered to be incurable, treatments have emerging and the research has made notable and steady progress in very few years, changing the disease outcome for many patients. Introduction of new therapeutic approaches therefore increases survival at later age. These two factors should be considered to better understanding the actual and current epidemiology of NMD, to especially estimate future healthcare burden. This can be useful to understand the impact on NMD on the healthcare system to better inform healthcare policy.\u003c/p\u003e\n\u003cp\u003eThus, we need additional epidemiological studies. They can inform an understanding of the magnitude of NMD at a population level, the natural history of the patients, the symptomatology and the etiology of NMD, the symptoms trend over time, the burden of disease, the healthcare follow-up, the impact of newer management interventions, etc.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSome estimates of NMD prevalence exist, but based on highly variable methods (retrospective chart review, surveys, family histories, patient registries, etc.), populations (lifespan, adults or children), pathologies (all NMD, one NMD, a group of NMD). In addition, few studies are conducted using population-based health administration databases for a region or an entire country.\u003c/p\u003e\n\u003ch2\u003eFrench National Rare Disease Databank\u003c/h2\u003e\n\u003cp\u003eOver the whole French territory, all French expert centers record a homogeneous collection of data based on a minimum data set (SDM-MR) to document the care and state of health of patients with rare diseases in French expert centers. These data are then gathered in a data warehouse (Jannot et al., 2021). This data warehouse allows the secure collection and de-identified centralization of medical data from all patients followed-up in rare disease expert network and thus provides a robust and reliable epidemiological resource (Messiaen et al., 2021). This data collection enables to promote epidemiological surveillance for rare diseases, to asses feasibility of clinical trials, and to better assess the effect of national plans. The SDM-MR is amongst others composed of patient identification, family information, vital status, care course, care activity (ie, medical consultation, day hospitalization, traditional hospitalization, emergency hospitalization), patient histories, history of the disease, age at first signs, diagnostic, confirmation of diagnosis, treatment, ante and neonatal course...\u003c/p\u003e\n\u003ch2\u003eAim and objective\u003c/h2\u003e\n\u003cp\u003eOverall, NMD make up a complex group of clinically and genetically heterogeneous conditions and can make NMD difficult to diagnose, to clearly document and record. Despite the need, few rigorous studies are available, especially in France, and in pediatric population. We conducted a comprehensive multicenter retrospective epidemiological study of pediatric NMD followed up in rare disease expert centers, between 2001 and 2022. A large historical French region provided a strategic framework to this analysis carried out in Southwest France. We conducted a retrospective cohort study using French National Rare Disease Registry to determine the prevalence, incidence, and mortality for children with NMD and its subtypes followed up in rare disease expert center in a large French region and to compare our data to the international studies.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe performed a retrospective cohort study following the RECORD Statement (Benchimol et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eProcedure\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003eDiagnoses Classification\u003c/h2\u003e \u003cp\u003eThe BNDMR allowed us to identify patients with specific neuromuscular disorders using Orphanet nomenclature [ORPHADATA 2022] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.orphadata.org/cgi-bin/ORPHAnomenclature.html\u003c/span\u003e\u003cspan address=\"http://www.orphadata.org/cgi-bin/ORPHAnomenclature.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSpecified ORPHA diagnoses considered as NMD in this study are listed in Annexe1. We used the 2021 version of the gene table of neuromuscular disorders (Benarroch et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) where NMD\u0026rsquo;s children were classified into 16 categories: 1) Muscular dystrophies; 2) Congenital muscular dystrophies; 3) Congenital myopathies; 4) Distal myopathies; 5) Other myopathies; 6) Myotonic syndromes;7) Ion channel muscle diseases; 8) Malignant hyperthermias; 9) Metabolic myopathies; 10) Hereditary cardiomyopathies -subdivided into 10A (non-arrhythmogenic) and 10B (arrhythmogenic); 11) Congenital myasthenic syndromes; 12) SMA \u0026amp; Motor neuron diseases; 13) Hereditary ataxias;14) Hereditary motor and sensory neuropathies; 15) Hereditary paraplegias; 16) Other neuromuscular disorders\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy population and Participants\u003c/h2\u003e \u003cp\u003eWe selected patients having at least one care activity at pediatric age (under 18) from May 1, 2001 to June 1, 2022 (defined as study endpoint), and having an NMD diagnostic code in BNDMR Datawarehouse and living in Southwest of France (estimated pediatric population of 2,617,994 inhabitants in 2021 census [INSEE 2022] (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insee.fr/fr/statistiques/1893198\u003c/span\u003e\u003cspan address=\"https://www.insee.fr/fr/statistiques/1893198\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)). Southwest France is organized in two geographic areas: Nouvelle-Aquitaine and Occitanie, which are subdivided in departmental sections (13 for Occitanie and 12 for Nouvelle-Aquitaine).\u003c/p\u003e \u003cp\u003eAll regional reference expert centers in Southwest France (Toulouse, Montpellier and Bordeaux Hospitals) provided their patients records.\u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003eVital status\u003c/h2\u003e \u003cp\u003eVital status was retrieved from the Deceased persons file [INSEE 2022] to identify deceased patients and their date of death.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eFocus on specific diseases subtypes of NMD\u003c/h2\u003e \u003cp\u003eWe detained the annual evolution of 4 NMD specific conditions (DMD, DMB, CMT1 and SMA). We focused on those because they are the most frequently encountered in clinical practice and the most serious. We also focused on those because new very expensive therapeutic solution emerges over the past few years for these specific conditions, which arouses medico-economic interest.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRegistration and ethics\u003c/h2\u003e \u003cp\u003e The study was approved by the French National Rare Disease Registry Review Board (IRB00013741). This study was partially supported by the FILNEMUS healthcare chain through the 2021 AAP Program. Convention 2021\u0026thinsp;\u0026minus;\u0026thinsp;0253 AP-HM-Filnemus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStatistical method\u003c/h2\u003e \u003cp\u003eAge, date of first consultation, date of first symptoms leading to consultation, date of confirmed diagnosis were described using median and IQR.\u003c/p\u003e \u003cp\u003eThe prevalence of patients followed-up in expert centers with NMD in each South-West French department was estimated as the ratio of the number of patients seen in the expert centers and living in the geographic area divided by the population size living in the region during the study period according to the INSEE census (2021). We exclude the five north departments of Nouvelle-Aquitaine because of their geographic proximity to Limoges University Hospital that is not part of the present study.\u003c/p\u003e \u003cp\u003eWe defined annual incidence of patients followed-up in expert centers with NMD by the ratio of the number of confirmed patients given their year of inclusion on the population estimate living in the region during the study period according to the INSEE census (2021).\u003c/p\u003e \u003cp\u003eWe use Poisson confidence intervals of 95% for prevalence and incidence.\u003c/p\u003e \u003cp\u003eWe computed the distance between the residence of the patients and the attended expert center using the great-circle method and described it with median and IQR.\u003c/p\u003e \u003cp\u003eWe performed survival from birth analyses using Kaplan-Meier estimates, for muscular dystrophies, congenital dystrophies and myopathies and spinal muscular atrophies. The statistical software R for Windows, version 4.2.2 was used to performed analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003ch2\u003eDemographic information\u003c/h2\u003e\n\u003cp\u003eOver the period, 1,621 children were included (Figure 1) with a median age at last follow-up of 14 years (IQR = 8-17) and a median age at inclusion of 8 years (IQR = 4-13). Age at inclusion varies between the NMD groups (Figure 3). The sex ratio was 1.64 in favor of male. 154 of these patients were deceased with a median age at death of 3 year (IQR = 1-19). Most deaths occurred in patients affected by SMA and motor neuron diseases (63 death, mostly before 1 year), and muscular dystrophies (49 deaths, mostly after 21 years). Patients were followed for a median period of 8 years (IQR = 4-12).\u003c/p\u003e\n\u003cp\u003eThe median age at first signs was 4 years (IQR = 1-9) while the median age at diagnosis was 6 years (IQR=2-11) for confirmed diagnoses. Age at first sign deeply varies between groups. For the 1400 patients having a confirmed diagnosis, the median delay to diagnosis was 10 months (IQR = 0-36) showing that diagnosis was confirmed within the first year of follow-up.\u003c/p\u003e\n\u003ch2\u003ePrevalence\u003c/h2\u003e\n\u003cp\u003eBased on census data and with a total population of 2,045,502 inhabitants under 18 years old, the regional prevalence of NMD patients followed-up in expert centers in Southwest region was 37.9 for 100,000 inhabitants under 18 years old (IC95 = [35.3-40.7]). Figure 2 provides detailed prevalence estimates among French departments. Table 1 provides an overview of NMD included patients according to diagnostic groups and corresponding prevalence. Most prevalent groups of diseases were hereditary motor and sensory neuropathies (9.1; IC95 = [7.9-10.6]) and muscular dystrophies (8.8; IC95 = [7.6-10.2]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 present prevalence by age class and NMD groups. This prevalence increases with age when looking at the whole cohort. We estimated prevalence at 12.7 (CI95% [9.7-16.2]) in the 0 to 5 age group, at 35.4 (CI95% [30.7-40.6]) in the age group between 5 and 10 years, 51.1 (CI95% [45.6-57.0]) in the 10 to 15 years age group and 53.0 (CI95% [45.8-60.9]) in the 15 to 18 years age group for 100,000 inhabitants of the corresponding age group.\u003c/p\u003e\n\u003cp\u003eAs shown by Table 3, the prevalence firstly increases due to ramp-up process, and then progressively decrease after 2018.\u003c/p\u003e\n\u003ch2\u003eMuscular disorders sub-cohort analysis\u003c/h2\u003e\n\u003cp\u003eAmong the 179 patients with SMA, 78 were males (44 %). Becker muscular dystrophy (N=71) and Duchenne muscular dystrophy (N=215) include only five and two women respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong the 236 CMT1 patients, 124 were males (53%). According to table 1, the regional prevalence of patients affected by SMA followed-up in expert centers was 3.2 [2.5-4.1], for BMD was 1.3 [0.9-1.9], for DMD was 5.0 [4.1-6.1] and for CMT1 was 6.2 [5.1-7.3]. Regarding incidence, SMA rise to a median of 8.0 (IQR = 5.0, 10.3), BMD to 3.0 (IQR = 2.0-4.0), DMD to 8.0 (IQR = 2.0-12.0) and CMT1 to 10.0 (IQR = 3.0-17.0). SMA patients at inclusion were younger than BMD, DMD or CMT1 with a median age of 1.4 (IQR = 0.4-8.2) against 8.7 (IQR = 5.3-12.4), 7.5 (IQR = 5.1-10.3) and 8.5 (IQR = 5.1-12.4) respectively. We observed, in Figure 4, for SMA first signs at a median age of 0.8 year (IQR = 0.2 - 2.0) whereas the median age at diagnosis was 0.8 year (IQR = 0.3-2.0). Regarding BMD, we observed a median age of 6.0 years (IQR = 3.5-9.5) whereas the median age at diagnosis was 7.5 years (IQR = 5.0-10.2). For DMD, we observed a median age of 3.0 years (IQR = 1.8-6.9) whereas the median age at diagnosis was 4.0 years (IQR = 2.5-6.0). Finally, for CMT1, we observed a median age of 4.3 years (IQR = 2.0-8.1) whereas the median age at diagnosis was 7 (IQR = 4.0-10.3). Most deaths occurred less than two years after first signs for SMA, more than 7 years after for DMD and none in the BMD group (Figure 5).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence of Pediatric Neuromuscular Disorders in pediatric patients: a consensus at last?\u003c/h2\u003e \u003cp\u003eOur overall prevalence is based on a large cohort of patients under 18 years (838 in all and 775 still alive) diagnosed with NMD and followed-up in three experts centers between 2001 and 2022 in Southwest region. Even if this study only includes regional data, our data are current and of good quality and our prevalence could not greatly differ from French national data. We found a regional prevalence of overall NMD patients under 18 years old of 37.9 for 100,000 inhabitants. This prevalence is comparable to those found by Woodcock et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), which is one of the few pediatric prevalence studies. In their study done in Yorkshire, authors found an overall prevalence of NMD conditions of 36.9 per 100,000 in a population under 16 years old. NMD included in their studied population is very close to ours, so the similarity in the results adds to their validity.\u003c/p\u003e \u003cp\u003eFew other researches addressed the special issue of prevalence in pediatric population of NMD or as part of a larger study on general population (Theadom et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Pagola-Lorz et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rose et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Our results differ, but the reliabilities of the pediatric prevalence announced in these studies is questionable. Rose et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) conducted a very large cohort study based on the population of Ontario (Canada) where adults and children with NMD were rigorously identified using health administrative databases. 27,823 children were eligible for 2014' cohort creation establishing an annual prevalence of 75.9. However, authors accounted \u0026lsquo;cerebral palsy\u0026rsquo; (24.1) and \u0026lsquo;spina bifida\u0026rsquo; (13.6) in NMD diagnoses, which is quite uncommon in such NMD prevalence studies. Excluding these two categories, annual prevalence in NMD children falls 38.2 for children, very close to ours.\u003c/p\u003e \u003cp\u003ePagola-Lorz et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Theadom et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) report a pediatric prevalence of NMD of 21.87 and 28.11 respectively, but both excluding SMA and regarding data under 14 years, while prevalence greatly increases with age in both.\u003c/p\u003e \u003cp\u003eOur pediatric prevalence is also quite different of those identified in Muller et al. study routinely cited in support of NMD prevalence. The total NMD pediatric prevalence in their study (57.8 per 100.000) was higher than the prevalence of NMD related by our study and studies previously cited. But authors themselves added that the prevalence found in their study greatly higher than other, including higher than proposed in epidemiological study that combined populations from different parts of the world (Emery, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1991\u003c/span\u003e for example). If their finding could be due to a small number of children under 18 years old (55), it may also reflect ethnic difference according to the authors. This explanation seems confirmed by the results of several studies (Theadom et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Woodcook et al., 2016) that highlighted some considerable variation in prevalence by ethnic groups.\u003c/p\u003e \u003cp\u003eTo date, an NMD\u0026rsquo; pediatric prevalence about 38/100000 may reflect a consensus among different countries. However, our work highlights an NMD prevalence fluctuation between studies realized over the last decades. This suggest that significant variation between methodologies or datasets used greatly impact prevalence estimation. The NMD included, the age groups studied, the ethnicities concerned, varied to one study from another. Studies comparisons are therefore problematic. Another point that hindered the possibility of comparison between studies, is the period studied. Innovative therapies are in constant evolution, and compared prevalence before or at the beginning of their availabilities is not rigorous since they progressively increased the useful life of NMD patients, especially for young children. Concerning pediatric, very few researches actually addressed the special issue of prevalence in pediatric population of NMD, intrinsically or as part of a larger study on general population. But the arrival of new very expensive therapies forces us to rigorously estimates the number of patients involved at a territorial, national or world level, to better inform healthcare policy on the burden of such care on the healthcare system. We therefore urgently need rigorous prevalence studies, with a consistent and standardized methodology between countries, applicable and adopted by all. The same observation was previously made on numerous occasions in studies or review for many years, which express the need to greater consistency in the conduct of NMD epidemiological studies to allow and ensure comparisons to be made between studies. However, nothing happens despite concrete and practical proposals (Theadom et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Accordingly, prevalence studies guidelines should be discussed and adopted by consensus in world conference on NMD. It is essential to homogenize inclusion or exclusion criteria, selection of conditions that have been included or excluded from the definition of NMD, the use of more inclusive or rather the opposite more limited definition, to clearly defined some range-ages of interest used from study to study, to sought and noted the ethnicity of patients, to specified the datasets used (research or clinical or multiple data sources), etc. Only in this way will prevalence rates should be compared across studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003ePrevalence temporal trends\u003c/h2\u003e \u003cp\u003eTwo studies in the recent past have underlined the number of people with MNM has been steadily rising (Carey et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Rose et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Rose et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) used health administrative databases to describe trends in incidence, prevalence, and mortality of adults and children with NMD on a population-based (Ontario, Canada) cohort study (2003 to 2014). Authors observed a rising prevalence of NMD over time among both adults and children (2003 to 2014). Carey et al (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) used the Clinical Practice Research Datalink, a primary care database in the UK, to estimate trends in the recording of neuromuscular disease in UK primary care between 2000\u0026ndash;2019 based on incidence and prevalence rates in each year. Authors observed overall prevalence grew by 63% since 2000 with temporal trends showing the number of NMD patients is steadily increasing year by year. For Carey et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) as for Rose et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), new cases cannot solely explain increasing prevalence year by year, as incidence remained constant, but that it may be due to better recording.\u003c/p\u003e \u003cp\u003eOur data, which run from 2001 to 2021, support this assumption. We can see a continuous, steady growth in rate of prevalence from 2001 to 2017 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). In France, this period corresponds to the historical implanting of centers of rare diseases and to the creation and progressive implementation of national research database, CEMARA (Messiaen et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) at first and then BAMARA (Jannot et al., 2021). 2017 is a crucial point in France with the introduction of BAMARA, its deployment in all rare diseases\u0026rsquo; centers, and its used making systematic and compulsory as part as third rare diseases plan, leading de facto to better and reliable healthcare data recording. Since 2017, our data are therefore more reliable. And watching exclusively on research' data specifically covering these last six years, we don\u0026rsquo;t find an increasing of prevalence of NMD per years but rather a clear stabilization in the number of NMM children followed expert care centers has been recognized.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIncreasing pointed by Rose et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Carey et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), as by our own data from 2017, might therefore be an artefact being but the reflection of a data filling effect. Our finding concurs with the Carey et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) assumption, in believing that this increasing may partially be due to better recording.\u003c/p\u003e \u003cp\u003eIn addition, most studies that contain substantive pediatric data, found that prevalence increases with age across all diagnoses except SMA. Rose et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found that childhood disease prevalence increased by 10% per year. For authors, the largest increase was in children 0 to 5 years. Theadom et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) that found that prevalence remained relatively stable across the lifespan following 5 years of age have enhanced this finding. Our prevalence increases with age, to 12.7/100000 in the age group 0\u0026ndash;5 years, from 53 in the 15-18-years age group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As was already demonstrated, we show a very significant gap forms at the age of 5, with more than a two-fold increase prevalence after 5. Then, the prevalence increases progressively but we note a stabilized trend after 10 years. Incidence and prevalence data years by years in pediatric population will be required, probably by diagnosis, in order to better understand the course of NMD throughout childhood.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eFocus on DMD, BMD, CMT1 and SMA\u003c/h2\u003e \u003cp\u003eThe most common NMD in our study was dystrophinopathies (17.6%: 13.2% Duchenne and 4.4% Becker), followed by CMT1 (14.5%), SMA (11%) and DM1 (8.5%). These four diagnoses made more than half of the overall prevalence of our NMD population.\u003c/p\u003e \u003cp\u003eFew NMD prevalence study exists on pediatric population and distribution of NMD diseases differs between children and adults. However, our results are quite congruent with previous studies on pediatric prevalence of NMD. Woodcock et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) found Dystrophin-related NMD as the most prevalent condition of their population of 261 NMD children, 16.9 per 100,000 (61; 23%), followed by CMT1 (31; 12%), congenital myopathies (29; 11%) and SMA (27; 10%). In Thongsing et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), in a quite as large pediatric NMD population (217), the most common inherited NMD were the Dystrophinopathies, including Duchenne / Becker muscular dystrophy (58; 27%), followed by SMA (25; 11.5%) and Hereditary Motor Sensory Neuropathy (CMT1) (16; 7%). Our study therefore strengthens its results on a three-time larger sample.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eFocus DMD/BMD\u003c/h2\u003e \u003cp\u003eDMD/BMD occurs in males, but in order to calculate the scope of the burden for society, most studies report prevalence estimates in relation to the general population. We did the same and our estimate is rather comparable to most previous studies and to systematic review and meta-analysis of Crisafulli et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Theadom et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Mah et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Crisafulli et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found a DMD prevalence of 2.8 cases (95% CI: 1.6\u0026ndash;4.6) per 100,000 in the general population on about 40 studies reporting the global epidemiology of DMD. Theadom et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) found a prevalence for DMD of 1.7\u0026ndash;4.2 per 100,000 and for BMD of 0.4\u0026ndash;3.6 per 100,000 based on studies classified as having a low risk of bias (15/38). The systematic review and meta-analysis of Mah et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) analyzed the prevalence for DMD and BMD but in relation to male population only. Authors found a prevalence of DMD at 4.78 and BMD of 1.53 (95% CI 1.94\u0026ndash;11.81) per 100.000 males based on 31 studies. Comparing findings with two alternative methods is a challenge, but Crisafulli et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Theadom et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and Mah et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) estimates seems relatively similar, and our prevalence appears little higher -at least for DMD. However, these reviews considered prevalence in all age groups and not in pediatric groups. Difference thus could be probably due to the early mortality of DMD patients. Despite improvement of survival, few affected individuals survive beyond the third decade (Passamano et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) with a median survival of 24 years (Rall \u0026amp; Grimm, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Because death occurs in early adulthood, a higher pediatric prevalence seems therefore logical.\u003c/p\u003e \u003cp\u003eParents can identify the first symptoms of DMD early, when physical ability in their children diverges markedly from that of their peers around 2\u0026ndash;3 years (Mercuri et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Significant and visible general motor delays (gait problems, delay in walking, a waddling gate, difficulties with climbing stairs, and frequent falls\u0026hellip;), then a little later learning difficulty, and speech problems, are indeed perceptible from early development. In our DMD cohort, ours results are congruent with the recent study of D'Amico et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) that have reported mean age at diagnosis was 41 months (range 0.3\u0026ndash;135 months), 10 months (range 10 days to 80 months) before the first suspicions (mean age 31 months; range 0\u0026ndash;95 months). Authors note that it\u0026rsquo;s about one year less than the age reported in Bushby et al, (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2010\u003c/span\u003e, probably related according to them to the fact that in Italy blood tests including transaminases and CK are routinely requested by pediatricians when motor delays is present, as in France (Verloes et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). We agree therefore the authors to say that a CK test screening should be performed in early infancy in order to reduce the delay of diagnosis.\u003c/p\u003e \u003cp\u003eRegarding BMD, we observed a median age of 6.0 years at first signs (IQR\u0026thinsp;=\u0026thinsp;3.6\u0026ndash;9.5) whereas the median age at diagnosis was 7.5 years (IQR\u0026thinsp;=\u0026thinsp;5.0\u0026ndash;10.2). Few studies focused on natural history of BMD when the onset is in childhood, which does not allow comparison, but our data seems congruent with clinical practice. BMD is indeed less severe and has a milder clinical course than DMD. The onset of symptoms is usually later than in DMD. The clinical heterogeneity of BMD is extreme, and the age of onset varies widely (Angelini et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The spectrum of clinical presentations ranges from asymptomatic with screening via a liver test to a loss of ambulation occurring in the teenage years.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eFocus CMT1\u003c/h2\u003e \u003cp\u003eWe found a pediatric prevalence of CMT1 at 6.2 (5.1\u0026ndash;7.3) per 100.000, without analyzable data between 0 to 5 years and with first reliable epidemiological data after 5 years. Epidemiological studies of CMT disease are scarce, and in the absence of data collection programs, longitudinal or natural history studies, knowledge of CMT pediatric epidemiology is even more limited. Patients have a long history of symptoms before the diagnosis, that come in late in life, with a mean age estimated of 31.8 years (Gudmundsson et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), often caused by discreet symptomatology, slow progression rate, and insidious onset in the first decades of life. The average delay of clinical diagnosis, even in families known to have CMT, is more than 10 years (Jani-Acsadi et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In a cohort of 39 patients with infantile presentation, the mean age at diagnosis was 8.5 years (Ounpuu et al., 2013). Mean age at diagnosis and mean age for first symptom in the CMT1 subtype for pediatric population is not available to our knowledge, but for our part, we were able to estimate a median age of first symptoms of 4.3 years (IQR\u0026thinsp;=\u0026thinsp;2.0-8.1) and a median age at diagnosis at 7 years (IQR\u0026thinsp;=\u0026thinsp;4.0-10.3).\u003c/p\u003e \u003cp\u003eWith regard to prevalence, Ma et al. (2023) describe the distribution of CMT disease among the worldwide population in a relevant meta-analysis. Authors examine the prevalence of CMT for the general population, as well as the subgroups (age, gender, region, and disease subtypes). 31 included studies are detailed in their meta-analysis but only 2 old studies (1983 and 2000) focused on non-adult populations, and some few conducted on the all-age populations (comprising children). CMT prevalence is logically higher in older than in younger age groups. Extracted from their meta-analysis, only Carey et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), Theadom et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) and Mladenovic et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) provided recent pediatric epidemiological data (post 2010). However, although both Carey et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Theadom et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) indicated the estimates prevalence for different subtypes, they did not discriminate CMT in subtypes for pediatric population. The pediatric prevalence for CMT1 only is not available. Theadom et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) found a pediatric prevalence for all CMT at 9.1 (6.1\u0026ndash;13.5) quite similar to Carey et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) that found a pediatric prevalence for all CMT at 8.9. In literature, CMT1 has been reported to be the most common CMT type, accounting for between 37.6% and 84.0% of cases (Barreto et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This estimation brings up the CMT1 pediatric population of both studies to 3.4 to 7.6, in line with our finding and those of Mladenovic et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Indeed, in Mladenovic et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) study, as in ours, CMT1 prevalence under 5 years old is unavailable and authors found a pediatric prevalence for CMT1 at 5/100000 (1.6\u0026ndash;11.6) under 14 years old. Overall, based on previous studies and our data, we can conclude that pediatric prevalence of CMT1 could be endorsed about 5 per 100.000.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eFocus SMA\u003c/h2\u003e \u003cp\u003eThe regional prevalence of patients affected by SMA followed-up in expert centers was 3.2 [2.5\u0026ndash;4.1]. Only a few estimations studies have been performed to assess the prevalence of SMA and most of these have been conducted before 2000. When examining all types of SMA together in these studies, a prevalence of around 1\u0026ndash;2 per 100,000 persons is observed (Verhaart et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) for most country. A more recent study was available, conducted by direct contact with two genetic laboratories across Europe (Verhaart et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2017\u003c/span\u003eb). In this study, even if there was considerable inter-country variability, SMA prevalence ranged respectively from 0.01 to 2.43 per 100,000 (TREATNMD Global SMA Patient Registry) and 0.00 to 4.11 per 100,000 (Care and Trial Sites Registry CTSR). However, both registries only included patients before 2014 and the launch of innovative therapies that increases significantly the survival of patients with SMA. With a growing number of therapies being developed since 2017, the natural history of SMA has indeed changed. Moreover, pediatric prevalence and overall prevalence (lifespan, children and adults) cannot be easily compared due to high early death for a substantial number of patients. There is therefore an increasing need for others new pediatric SMA incidence and prevalence estimations.\u003c/p\u003e \u003cp\u003eThe majority of SMA children in our cohort were classified as SMA type I (79/179 or 44%) followed by 59 with SMA2 (33%), 29 with SMA3 (18%), 10 with other SMA. This is in good agreement with the percentages of patient classified into different types of SMA in the Cure SMA database (one of the largest patient-reported data repositories on SMA patients worldwide (Belter et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)) that found: SMA1 39%; SMA2 31%; SMA3 19% (Sun et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe percentages of females of SMA (56.4%) were higher than males for overall SMA cohort (male-to-female sex ratio 0.77) and for all SMA types (male-to-female sex ratio 0.76 for SMA1 and 0.45 for SMA3 and 0.9 for SMA2). This finding is interesting since no consensus has been reached for this question. An old study from Pearn (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e1978\u003c/span\u003e) reported a male to female ratio of 2.0 in SMA1, but a sex ratio in male disadvantage is commonly admitted. However, these have not been consistent, and several studies have reported no sex differences in sex ratio. This question could be addressed, especially because sex vulnerability in SMA is identified with some studies that have indicated the infantile form of SMA is more severe in males (Sun et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe first medical visit for SMA patients in the reference center came early with a median age of 1.4 (IQR\u0026thinsp;=\u0026thinsp;0.4\u0026ndash;8.2), which is consistent with the disease evolves and its gravity. In the first year of life, 72 patients (53%) were diagnosed.\u003c/p\u003e \u003cp\u003eWe observed for overall SMA first signs and age at diagnosis at a median age of 0.8 year, corresponding to a rapid diagnostic. By SMA subtypes, the gap between first signs and diagnosis is quite similar for SMA1 and SMA2 (few weeks) and increased for SMA3 (1.5 years between emerging of first symptoms and diagnosis).\u003c/p\u003e \u003cp\u003eIn our study, survival for SMA1 children at 1, 2, 4 and 8 years was 36%, 29%, 27% and 27%, respectively. The survival probabilities of SMA2 patients at 1, 2, 4 and 8 years was 100%, 100%, 97% and 93%, while SMA3 patients generally have normal life expectancy. These findings are similar with those from Farrar et al. (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) or Chung et al. (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and concordant with clinical experience. We just observed a slight difference for the clinical course and death for SMA1, which probably reflect advances in medical care, and improvement in life expectancy.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study is the first French prevalence estimation of NMD in pediatric population. Based on a large retrospective data collection (1621 NMD children), our results support that an NMD\u0026rsquo; pediatric prevalence about 38/100000 might be reflected a consensus among different country. However, an NMD prevalence fluctuation between studies realized over the last decades is too common and rigorous prevalence studies are urgently needed, with a consistent and standardized methodology between countries, applicable and adopted by all. Moreover, we believe that increasing general NMD prevalence pointing in some studies may partially be due to better recording of healthcare data from institutions and is probably an artefact.\u003c/p\u003e \u003cp\u003eRegarding NMD by subtypes, we found three interesting findings. First, as expected given clinical and previous studies, French NMD pediatric prevalence increases with age across all diagnoses except SMA. Secondly, pediatric CMT1 suffers from sparse medical literature (epidemiological and long-term natural history studies), but our result support a pediatric prevalence about 6.2 per 100.000. Thirdly, our DMD and BMD pediatric prevalence -respectively 5 and 1.3- is congruent with those reported previously. Importantly, we strongly encourage the use of CK test screening in early infancy for DMD, since this medical practice realized in Italy and France seems to reduce the delay of diagnosis.\u003c/p\u003e \u003cp\u003eOur current study only includes regional data, thus prevalence and prognosis could differ from French national data. Regional variations prevalence in other studies, especially according to ethnic differences in population between country' regions, highlight the need to conduct a French national prevalence study in order to ensure accuracy of our prevalence data. This study does, however, provide important details for adjusting healthcare policies within our region, as well as at national level.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBNDMR: Banque Nationale de Donn\u0026eacute;es Maladies Rares - \u003cem\u003eNational Rare Disease Databank\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eBMD: Becker Muscular Dystrophy\u003c/p\u003e\n\u003cp\u003eCMD: Congenital Muscular Dystrophy\u003c/p\u003e\n\u003cp\u003eCMT: Charcot-Marie-Tooth\u003c/p\u003e\n\u003cp\u003eCK: Creatinine Kinase\u003c/p\u003e\n\u003cp\u003eDM1: Myotonic Dystrophy type 1\u003c/p\u003e\n\u003cp\u003eDMD: Duchenne Muscular Dystrophy\u003c/p\u003e\n\u003cp\u003eFSHD: Facioscapulohumeral Dystrophy\u003c/p\u003e\n\u003cp\u003eICD: International Classification of Diseases\u003c/p\u003e\n\u003cp\u003eIMDs: Inherited Muscle Diseases\u003c/p\u003e\n\u003cp\u003eINSEE: Institut National de la Statistique et des \u0026Eacute;tudes \u0026Eacute;conomiques - \u003cem\u003eNational Institute of Statistics and Economic Studies\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eLGMD: Limb Girdle Muscular Dystrophy\u003c/p\u003e\n\u003cp\u003eNMD: Neuromuscular Disorders\u003c/p\u003e\n\u003cp\u003eSDM-MR: Set de Donn\u0026eacute;es Minimum Maladies Rares - \u003cem\u003eMinimum Data set for Rare Diseases\u003c/em\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Ethical Committee for Medical Research and the institutional ethics committee (IRB approval number: IRB00013741).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are available from the authors upon reasonable request and with permission of BNDMR.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests /\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eConflict of Interest / Disclosures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding/Support\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was partially supported by the FILNEMUS healthcare chain through the 2021 AAP Program. Convention 2021-0253 AP-HM-Filnemus\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMB and CC are principal investigator of the study, conceived the idea for the study and the design, and were major contributors in writing the protocol. CM and ASJ analyzed and interpreted the data, wrote the method and results parts and helped to reflected the discussion based on results. EW, FR, UWL, LT, CE and EB was involved in data collect, quality monitoring and scientific expertise. All the authors read, reviewed and approved the final manuscript as submitted and agreed to be accountable for all aspects of the work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is dedicated to all the children and their families who are concerned by the study. The authors also thank Pierre Bezebeyrie (Pau Hospital) Leila Llazaro (Bayonne Hospital) Guilhem Sole (Bordeaux Hospital) for their support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eYuki, N., \u0026amp; Hartung, H. P. (2012). Guillain-Barr\u0026eacute; syndrome. \u003cem\u003eThe New England journal of medicine\u003c/em\u003e, \u003cem\u003e366\u003c/em\u003e(24), 2294\u0026ndash;2304. https://doi.org/10.1056/NEJMra1114525\u003c/li\u003e\n \u003cli\u003eD\u0026apos;Amico, A., Mercuri, E., Tiziano, F. D., \u0026amp; Bertini, E. (2011). Spinal muscular atrophy. \u003cem\u003eOrphanet journal of rare diseases\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e, 71. https://doi.org/10.1186/1750-1172-6-71\u003c/li\u003e\n \u003cli\u003eTurner, C., \u0026amp; Hilton-Jones, D. (2014). 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Prevalence of Charcot-Marie-Tooth disease across the lifespan: a population-based epidemiological study. \u003cem\u003eBMJ open\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(6), e029240. https://doi.org/10.1136/bmjopen-2019-029240\u003c/li\u003e\n \u003cli\u003eTheadom, A., Rodrigues, M., Poke, G., O\u0026apos;Grady, G., Love, D., Hammond-Tooke, G., Parmar, P., Baker, R., Feigin, V., Jones, K., Te Ao, B., Ranta, A., Roxburgh, R., \u0026amp; On Behalf of the MDPrev Research Group (2019). A Nationwide, Population-Based Prevalence Study of Genetic Muscle Disorders. \u003cem\u003eNeuroepidemiology\u003c/em\u003e, \u003cem\u003e52\u003c/em\u003e(3-4), 128\u0026ndash;135. https://doi.org/10.1159/000494115\u003c/li\u003e\n \u003cli\u003ePagola-Lorz, I., Vicente, E., Ib\u0026aacute;\u0026ntilde;ez, B., Torn\u0026eacute;, L., Elizalde-Beiras, I., Garcia-Solaesa, V., Garc\u0026iacute;a, F., Delfrade, J., \u0026amp; Jeric\u0026oacute;, I. (2019). Epidemiological study and genetic characterization of inherited muscle diseases in a northern Spanish region. \u003cem\u003eOrphanet journal of rare diseases\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(1), 276. https://doi.org/10.1186/s13023-019-1227-x\u003c/li\u003e\n \u003cli\u003eRose, L., McKim, D., Leasa, D., Nonoyama, M., Tandon, A., Bai, Y. Q., Amin, R., Katz, S., Goldstein, R., \u0026amp; Gershon, A. (2019). Trends in incidence, prevalence, and mortality of neuromuscular disease in Ontario, Canada: A population-based retrospective cohort study (2003-2014). \u003cem\u003ePloS one\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(3), e0210574. https://doi.org/10.1371/journal.pone.0210574\u003c/li\u003e\n \u003cli\u003eEmery A. E. (1991). Population frequencies of inherited neuromuscular diseases--a world survey. \u003cem\u003eNeuromuscular disorders : NMD\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(1), 19\u0026ndash;29. https://doi.org/10.1016/0960-8966(91)90039-u\u003c/li\u003e\n \u003cli\u003eMessiaen, C., Le Mignot, L., Rath, A., Richard, J. B., Dufour, E., Ben Said, M., Jais, J. P., Verloes, A., Le Merrer, M., Bodemer, C., Baujat, G., Gerard-Blanluet, M., Bourdon-Lanoy, E., Salomon, R., Ayme, S., \u0026amp; Landais, P. (2008). CEMARA: a Web dynamic application within a N-tier architecture for rare diseases. \u003cem\u003eStudies in health technology and informatics\u003c/em\u003e, \u003cem\u003e136\u003c/em\u003e, 51\u0026ndash;56.\u003c/li\u003e\n \u003cli\u003eJannot, A. S., Messiaen, C., Khatim, A., Pichon, T., Sandrin, A., \u0026amp; BNDMR infrastructure team (2022). The ongoing French BaMaRa-BNDMR cohort: implementation and deployment of a nationwide information system on rare disease. \u003cem\u003eJournal of the American Medical Informatics Association : JAMIA\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(3), 553\u0026ndash;558. https://doi.org/10.1093/jamia/ocab237\u003c/li\u003e\n \u003cli\u003eThongsing, A., Likasitwattanakula, S., Netsuwan, T., \u0026amp; Sanmaneechai, O. (2020). Pediatric Neuromuscular Diseases Prevalence in Siriraj Hospital, Thailand\u0026rsquo;s Largest Tertiary Referral Hospital. \u003cem\u003eSiriraj Medical Journal\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e(2), 125\u0026ndash;131. https://doi.org/10.33192/Smj.2020.17\u003c/li\u003e\n \u003cli\u003eCrisafulli, S., Sultana, J., Fontana, A., Salvo, F., Messina, S., \u0026amp; Trifir\u0026ograve;, G. (2020). Global epidemiology of Duchenne muscular dystrophy: an updated systematic review and meta-analysis. \u003cem\u003eOrphanet journal of rare diseases\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(1), 141. https://doi.org/10.1186/s13023-020-01430-8\u003c/li\u003e\n \u003cli\u003eMah, J. K., Korngut, L., Dykeman, J., Day, L., Pringsheim, T., \u0026amp; Jette, N. (2014). A systematic review and meta-analysis on the epidemiology of Duchenne and Becker muscular dystrophy. \u003cem\u003eNeuromuscular disorders : NMD\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(6), 482\u0026ndash;491. https://doi.org/10.1016/j.nmd.2014.03.008\u003c/li\u003e\n \u003cli\u003ePassamano, L., Taglia, A., Palladino, A., Viggiano, E., D\u0026apos;Ambrosio, P., Scutifero, M., Rosaria Cecio, M., Torre, V., DE Luca, F., Picillo, E., Paciello, O., Piluso, G., Nigro, G., \u0026amp; Politano, L. (2012). Improvement of survival in Duchenne Muscular Dystrophy: retrospective analysis of 835 patients. \u003cem\u003eActa myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(2), 121\u0026ndash;125.\u003c/li\u003e\n \u003cli\u003eRall, S., \u0026amp; Grimm, T. (2012). Survival in Duchenne muscular dystrophy. \u003cem\u003eActa myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(2), 117\u0026ndash;120.\u003c/li\u003e\n \u003cli\u003eMercuri, E., B\u0026ouml;nnemann, C. G., \u0026amp; Muntoni, F. (2019). Muscular dystrophies. \u003cem\u003eLancet (London, England)\u003c/em\u003e, \u003cem\u003e394\u003c/em\u003e(10213), 2025\u0026ndash;2038. https://doi.org/10.1016/S0140-6736(19)32910-1\u003c/li\u003e\n \u003cli\u003eD\u0026apos;Amico, A., Catteruccia, M., Baranello, G., Politano, L., Govoni, A., Previtali, S. C., Pane, M., D\u0026apos;Angelo, M. G., Bruno, C., Messina, S., Ricci, F., Pegoraro, E., Pini, A., Berardinelli, A., Gorni, K., Battini, R., Vita, G., Trucco, F., Scutifero, M., Petillo, R., \u0026hellip; Bertini, E. (2017). Diagnosis of Duchenne Muscular Dystrophy in Italy in the last decade: Critical issues and areas for improvements. \u003cem\u003eNeuromuscular disorders : NMD\u003c/em\u003e, \u003cem\u003e27\u003c/em\u003e(5), 447\u0026ndash;451. https://doi.org/10.1016/j.nmd.2017.02.006\u003c/li\u003e\n \u003cli\u003eBushby, K., Finkel, R., Birnkrant, D. J., Case, L. E., Clemens, P. R., Cripe, L., Kaul, A., Kinnett, K., McDonald, C., Pandya, S., Poysky, J., Shapiro, F., Tomezsko, J., Constantin, C., \u0026amp; DMD Care Considerations Working Group (2010). Diagnosis and management of Duchenne muscular dystrophy, part 1: diagnosis, and pharmacological and psychosocial management. The Lancet. Neurology, 9(1), 77\u0026ndash;93. https://doi.org/10.1016/S1474-4422(09)70271-6\u003c/li\u003e\n \u003cli\u003eBushby, K., Finkel, R., Birnkrant, D. J., Case, L. E., Clemens, P. R., Cripe, L., Kaul, A., Kinnett, K., McDonald, C., Pandya, S., Poysky, J., Shapiro, F., Tomezsko, J., Constantin, C., \u0026amp; DMD Care Considerations Working Group (2010). Diagnosis and management of Duchenne muscular dystrophy, part 2: implementation of multidisciplinary care. \u003cem\u003eThe Lancet. Neurology\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(2), 177\u0026ndash;189. https://doi.org/10.1016/S1474-4422(09)70272-8\u003c/li\u003e\n \u003cli\u003eFor\u003c/li\u003e\n \u003cli\u003eVerloes, A., H\u0026eacute;ron, D., Billette de Villemeur, T., Afenjar, A., Baumann, C., Bahi-Buisson, N., Charles, P., Faudet, A., Jacquette, A., Mignot, C., Moutard, M. L., Passemard, S., Rio, M., Robel, L., Rougeot, C., Ville, D., Burglen, L., des Portes, V., \u0026amp; R\u0026eacute;seau D\u0026eacute;fiScience (2012). Strat\u0026eacute;gie d\u0026apos;exploration d\u0026apos;une d\u0026eacute;ficience intellectuelle inexpliqu\u0026eacute;e [Diagnostic investigations for an unexplained developmental disability]. \u003cem\u003eArchives de pediatrie : organe officiel de la Societe francaise de pediatrie\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(2), 194\u0026ndash;207. https://doi.org/10.1016/j.arcped.2011.11.014\u003c/li\u003e\n \u003cli\u003eAngelini, C., Marozzo, R., \u0026amp; Pegoraro, V. (2019). Current and emerging therapies in Becker muscular dystrophy (BMD). \u003cem\u003eActa myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(3), 172\u0026ndash;179.\u003c/li\u003e\n \u003cli\u003eGudmundsson, B., Olafsson, E., Jakobsson, F., \u0026amp; L\u0026uacute;thv\u0026iacute;gsson, P. (2010). Prevalence of symptomatic Charcot-Marie-Tooth disease in Iceland: a study of a well-defined population. \u003cem\u003eNeuroepidemiology\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(1), 13\u0026ndash;17. https://doi.org/10.1159/000255461\u003c/li\u003e\n \u003cli\u003eJani-Acsadi, A., Ounpuu, S., Pierz, K., \u0026amp; Acsadi, G. (2015). Pediatric Charcot-Marie-Tooth disease. \u003cem\u003ePediatric clinics of North America\u003c/em\u003e, \u003cem\u003e62\u003c/em\u003e(3), 767\u0026ndash;786. https://doi.org/10.1016/j.pcl.2015.03.012\u003c/li\u003e\n \u003cli\u003e\u0026Otilde;unpuu, S., Garibay, E., Solomito, M., Bell, K., Pierz, K., Thomson, J., Acsadi, G., \u0026amp; DeLuca, P. (2013). A comprehensive evaluation of the variation in ankle function during gait in children and youth with Charcot-Marie-Tooth disease. \u003cem\u003eGait \u0026amp; posture\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(4), 900\u0026ndash;906. https://doi.org/10.1016/j.gaitpost.2013.04.016\u003c/li\u003e\n \u003cli\u003eMladenovic, J., Milic Rasic, V., Keckarevic Markovic, M., Romac, S., Todorovic, S., Rakocevic Stojanovic, V., Kisic Tepavcevic, D., Hofman, A., \u0026amp; Pekmezovic, T. (2011). Epidemiology of Charcot-Marie-Tooth disease in the population of Belgrade, Serbia. \u003cem\u003eNeuroepidemiology\u003c/em\u003e, \u003cem\u003e36\u003c/em\u003e(3), 177\u0026ndash;182. https://doi.org/10.1159/000327029\u003c/li\u003e\n \u003cli\u003eBarreto, L. C., Oliveira, F. S., Nunes, P. S., de Fran\u0026ccedil;a Costa, I. M., Garcez, C. A., Goes, G. M., Neves, E. L., de Souza Siqueira Quintans, J., \u0026amp; de Souza Ara\u0026uacute;jo, A. A. (2016). Epidemiologic Study of Charcot-Marie-Tooth Disease: A Systematic Review. \u003cem\u003eNeuroepidemiology\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e(3), 157\u0026ndash;165. https://doi.org/10.1159/000443706\u003c/li\u003e\n \u003cli\u003eVerhaart, I. E. C., Robertson, A., Wilson, I. J., Aartsma-Rus, A., Cameron, S., Jones, C. C., Cook, S. F., \u0026amp; Lochm\u0026uuml;ller, H. (2017). Prevalence, incidence and carrier frequency of 5q-linked spinal muscular atrophy - a literature review. \u003cem\u003eOrphanet journal of rare diseases\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 124. https://doi.org/10.1186/s13023-017-0671-8\u003c/li\u003e\n \u003cli\u003eB Verhaart, I. E. C., Robertson, A., Leary, R., McMacken, G., K\u0026ouml;nig, K., Kirschner, J., Jones, C. C., Cook, S. F., \u0026amp; Lochm\u0026uuml;ller, H. (2017). A multi-source approach to determine SMA incidence and research ready population. \u003cem\u003eJournal of neurology\u003c/em\u003e, \u003cem\u003e264\u003c/em\u003e(7), 1465\u0026ndash;1473. https://doi.org/10.1007/s00415-017-8549-1\u003c/li\u003e\n \u003cli\u003eBelter, L., Cook, S. F., Crawford, T. O., Jarecki, J., Jones, C. C., Kissel, J. T., Schroth, M., \u0026amp; Hobby, K. (2018). An overview of the Cure SMA membership database: Highlights of key demographic and clinical characteristics of SMA members. \u003cem\u003eJournal of neuromuscular diseases\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(2), 167\u0026ndash;176. https://doi.org/10.3233/JND-170292\u003c/li\u003e\n \u003cli\u003ePearn J. (1978). Incidence, prevalence, and gene frequency studies of chronic childhood spinal muscular atrophy. \u003cem\u003eJournal of medical genetics\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(6), 409\u0026ndash;413. https://doi.org/10.1136/jmg.15.6.409\u003c/li\u003e\n \u003cli\u003eSun, J., Harrington, M. A., Porter, B., \u0026amp; TREAT-NMD Global Registry Network for SMA (2023). Sex Difference in Spinal Muscular Atrophy Patients - are Males More Vulnerable?. \u003cem\u003eJournal of neuromuscular diseases\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(5), 847\u0026ndash;867. https://doi.org/10.3233/JND-230011\u003c/li\u003e\n \u003cli\u003eFarrar, M. A., Vucic, S., Johnston, H. M., du Sart, D., \u0026amp; Kiernan, M. C. (2013). Pathophysiological insights derived by natural history and motor function of spinal muscular atrophy. \u003cem\u003eThe Journal of pediatrics\u003c/em\u003e, \u003cem\u003e162\u003c/em\u003e(1), 155\u0026ndash;159. https://doi.org/10.1016/j.jpeds.2012.05.067\u003c/li\u003e\n \u003cli\u003eChung, B. H., Wong, V. C., \u0026amp; Ip, P. (2004). Spinal muscular atrophy: survival pattern and functional status. \u003cem\u003ePediatrics\u003c/em\u003e, \u003cem\u003e114\u003c/em\u003e(5), e548\u0026ndash;e553. https://doi.org/10.1542/peds.2004-0668\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1: Characteristics of patients with NMD according to diagnostic subgroups\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"710\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.644163150492265%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.814345991561181%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.19127988748242%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhole cohort\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"41.35021097046413%\" colspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eScoped cohort\u0026sect;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroup name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. Cases (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. Male (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. \u0026nbsp;\u0026lt;18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlive \u0026amp; \u0026lt; 18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(IC95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMuscular dystrophies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAll\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e430 (26.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e363 (84.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e409\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e8.8 (7.6 - 10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eDMD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e215 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e213 (99.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e5 (4.1 - 6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eBMD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e71 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e66 (93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e1.3 (0.9 - 1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eLGMD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e52 (3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e28 (53.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.7 (0.4 - 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eFSH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e57 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e31 (54.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (0.7 - 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e37 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e27 (73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.8 (0.4 - 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCongenital muscular dystrophies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e64 (3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e36 (56.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e1.7 (1.2 - 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCongenital myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e82 (5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e45 (54.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e2 (1.4 - 2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistal myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e4 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAll\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e38 (2.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e8 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.7 (0.4 - 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eMAI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e32 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e5 (15.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (0.3 - 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e3 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMyotonic syndromes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAll\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e172 (10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e105 (61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e3.6 (2.8 - 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eDM1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e138 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e79 (57.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e2.7 (2.1 - 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e34 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e26 (76.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.8 (0.5 - 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIon channel diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e36 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e25 (69.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.9 (0.6 - 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant hyperthermias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e5 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetabolic myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e41 (2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e24 (58.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e1 (0.6 - 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary cardiomyopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e2 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCongenital myasthenic syndromes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e34 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e19 (55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (0.7 - 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMA \u0026amp; Motor neurone diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAll\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e179 (11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e78 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e3.2 (2.5 - 4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSMA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e79 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e34 (43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (0.7 - 1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSMA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e59 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e28 (47.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e1.4 (0.9 - 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eSMA3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e32 (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e10 (31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (0.3 - 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e10 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e7 (70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.1 (0 - 0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary ataxias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e34 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e19 (55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e0.6 (0.3 - 1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary motor and sensory neuropathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eAll\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e360 (22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e194 (53.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e9.1 (7.9 - 10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eCMT1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e236 (14.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e124 (52.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e6.2 (5.1 - 7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eCMT2 and others\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e125 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e70 (56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e3 (2.3 - 3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary parapl\u0026eacute;gias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e3 (NC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther neuromuscular disorders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e132 (8.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e80 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e4.4 (3.6 - 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.676056338028168%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.830985915492958%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eOverall\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.112676056338028%\" valign=\"top\"\u003e\n \u003cp\u003e1621 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.971830985915492%\" valign=\"top\"\u003e\n \u003cp\u003e1009 (62.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.169014084507042%\" valign=\"top\"\u003e\n \u003cp\u003e1547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.338028169014085%\" valign=\"top\"\u003e\n \u003cp\u003e838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.43661971830986%\" valign=\"top\"\u003e\n \u003cp\u003e775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.464788732394368%\" valign=\"top\"\u003e\n \u003cp\u003e37.9 (35.3 - 40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/em\u003e\u003cem\u003eScoped means within Great South-West but not in the five north departments of Nouvelle-Aquitaine; *Prevalence for 100,000 inhabitants under 18 years old\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTable 2: Characteristics of patients with NMD according to diagnostic subgroups and age class at study endpoint or at death\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1076\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.511627906976743%\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroup Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.976744186046513%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.86046511627907%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e[0-5[\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.674418604651162%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e[5-10[\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488372093023255%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e[10-15[\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.488372093023255%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e[15-18[\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.411030176899064%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9542143600416235%\"\u003e\n \u003cp\u003e\u003cstrong\u003eN Alive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.758584807492195%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (IC95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.786680541103018%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.37044745057232%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN Alive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.822060353798127%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (IC95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.786680541103018%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.37044745057232%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN Alive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.613943808532778%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (IC95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.411030176899064%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.37044745057232%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN Alive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.781477627471384%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (IC95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.411030176899064%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.37044745057232%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eN Alive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.781477627471384%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (IC95%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eand \u0026lt;18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMuscular dystrophies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e181\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e8.8 (7.6 - 10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e7.6 (5.5 - 10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e13.1 (10.4 - 16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e13.2 (9.7 - 17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eDMD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e5 (4.1 - 6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e3.5 (2.2 - 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e8.1 (6 - 10.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e7.3 (4.8 - 10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eBMD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e1.3 (0.9 - 1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e1.8 (0.8 - 3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eLGMD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.7 (0.4 - 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eFSH\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e1.1 (0.7 - 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e1.9 (1 - 3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.8 (0.4 - 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCongenital muscular dystrophies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e1.7 (1.2 - 2.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e2.7 (1.5 - 4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCongenital myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e2 (1.4 - 2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e1.8 (0.8 - 3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e2.7 (1.6 - 4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e2.7 (1.3 - 4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistal myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.7 (0.4 - 1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003e0 (0 - 0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eMAI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.6 (0.3 - 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003e0 (0 - 0.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMyotonic syndromes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e3.6 (2.8 - 4.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e3.4 (2 - 5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e5.5 (3.8 - 7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e3.5 (1.9 - 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eDM1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e2.7 (2.1 - 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e2.5 (1.4 - 4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e4 (2.6 - 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e2.7 (1.3 - 4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eOther myotonia\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.8 (0.5 - 1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIon channel diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.9 (0.6 - 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant hyperthermias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetabolic myopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e1 (0.6 - 1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary cardiomyopathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCongenital myasthenic syndromes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e1.1 (0.7 - 1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSMA \u0026amp; Motor neurone diseases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e3.2 (2.5 - 4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003e3.7 (2.2 - 5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e2.8 (1.6 - 4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e3.4 (2.1 - 5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e2.7 (1.3 - 4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eSMA1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e1.1 (0.7 - 1.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003e2.2 (1.1 - 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e0 (0 - 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eSMA2\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e1.4 (0.9 - 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e1.9 (1 - 3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eSMA3\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.6 (0.3 - 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eOther\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e0 (0 - 0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e0 (0 - 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary ataxias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e0.6 (0.3 - 1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary motor and sensory neuropathies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e9.1 (7.9 - 10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e7.3 (5.2 - 9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e13.3 (10.5 - 16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e15.1 (11.4 - 19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eCMT1\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e6.2 (5.1 - 7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e5.7 (3.9 - 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e8.9 (6.7 - 11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e8.9 (6.1 - 12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cem\u003eCMT2 and others\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e3 (2.3 - 3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e4.4 (2.9 - 6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e6.2 (3.9 - 9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHereditary paraplegias\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther neuromuscular disorders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e4.4 (3.6 - 5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e\u0026lt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003eNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e5.7 (3.9 - 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e5.3 (3.7 - 7.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e5.1 (3.1 - 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhole cohort\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e838\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.538175046554935%\"\u003e\n \u003cp\u003e775\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.521415270018622%\"\u003e\n \u003cp\u003e37.9 (35.3 - 40.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.683426443202979%\"\u003e\n \u003cp\u003e12.7 (9.7 - 16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.283054003724395%\"\u003e\n \u003cp\u003e216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.497206703910615%\"\u003e\n \u003cp\u003e35.4 (30.7 - 40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e51.1 (45.6 - 57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.8417132216014895%\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.910614525139665%\"\u003e\n \u003cp\u003e197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.752327746741155%\"\u003e\n \u003cp\u003e53 (45.8 - 60.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Prevalence of patients with NMD registered in BNDMR for 100 000 inhabitants under 18, by year\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eN. alive and \u0026lt; 18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (IC95)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e3.6 (2.8 - 4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e4.7 (3.8 - 5.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e5.9 (4.8 - 7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2004\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e6.7 (5.6 - 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e7.7 (6.5 - 9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e8.6 (7.3 - 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e9.6 (8.2 - 11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e10.1 (8.8 - 11.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e11.5 (10 - 13.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e21.1 (19.1 - 23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2011\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e25.3 (23.1 - 27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e27.4 (25.2 - 29.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2013\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e28.9 (26.6 - 31.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e30.6 (28.3 - 33.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e32 (29.6 - 34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e34.2 (31.7 - 36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e767\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e37.3 (34.7 - 40)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e38.7 (36 - 41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e39.7 (37.1 - 42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e40.9 (38.2 - 43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e843\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e41.1 (38.4 - 44)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.41176470588235%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.58823529411765%\"\u003e\n \u003cp\u003e784\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"50%\"\u003e\n \u003cp\u003e38.3 (35.7 - 41.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Inherited muscle diseases, Neuromuscular disorder, Epidemiology, Prevalence, Pediatric Population","lastPublishedDoi":"10.21203/rs.3.rs-4343784/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4343784/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e: Very limited epidemiological data on neuromuscular disorders pediatric population exist around the world. In France, such pediatric epidemiological study is seriously lacking. We investigated the pediatric prevalence (under 18) and we described the epidemiological profile of neuromuscular disorders on Southwest regions of France, from May 1, 2001 to June 1, 2022. We screened medical and genetic hospital records in three expert centers (Toulouse, Montpellier and Bordeaux) for neuromuscular disorders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We performed a retrospective cohort study with data extracted from the French National Rare Disease Databank that gathers a minimal dataset on all patients followed-up in French rare disease expert center in France. We then estimated: (1) Prevalence by diagnosis and age group or by year with Poisson confidence interval (2) survival from birth analyses using Kaplan-Meier for muscular disorders sub-cohort analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Over the period, 1,621 children were included with 62% of males. We estimate the regional prevalence at 37.9 (IC95% = 35.3 - 40.7) for 100,000 inhabitants under 18 years old. For muscular disorders sub-cohort analysis, we estimate regional prevalence for Duchene, Becker, Charcot-Marie-Tooth type 1 and Spinal muscular atrophy at 5 (IC95% = 4.1 - 6.1), 1.3 (IC95% = 0.9 - 1.9), 6.2 (IC95 = 5.1 - 7.3) and 3.2 (IC95% = 2.5 - 4.1) respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Our findings seem in accordance with previous but scarce other data. Together, all may reflect a consensus among different countries supporting a global neuromuscular disorders’ pediatric prevalence about 38/100000 may, about 5 for Duchene, 1.5 for Becker, 6.2 for Charcot-Marie-Tooth type 1, 3.2 for Spinal muscular atrophy. This is the first time that it’s possible to estimate with robustness French pediatric epidemiological prevalence of neuromuscular disorders, that constitute a strength starting point to be confirmed by the extend of analyze to all French expert centers.\u003c/p\u003e","manuscriptTitle":"Epidemiological Study of Pediatric Neuromuscular Disorders in South West France Regions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-29 02:51:24","doi":"10.21203/rs.3.rs-4343784/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"785a3711-4240-4809-bbe4-2143a63ca69e","owner":[],"postedDate":"May 29th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-06T18:40:04+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-29 02:51:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4343784","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4343784","identity":"rs-4343784","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}