The Gaucher Earlier Diagnosis Consensus Point-Scoring System for Children and Young Adults: A Retrospective and Prospective Evaluation in Korea

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The Gaucher Earlier Diagnosis Consensus (GED-C) initiative created a point-scoring system (PSS) to facilitate the early identification of GD based on significant indicators and covariables. This study aimed to evaluate the applicability and utility of the GED-C PSS in pediatric and young adult patients in Korea. Results This study included both retrospective analysis and prospective recruitment. Subject recruitment involved 14 sites across 13 hospitals in Korea, where patients of any age meeting GED-C criteria were recruited, and blood samples were collected. Data of 513 subjects were analyzed and two patients were confirmed to have GD during prospective enrollment. The median age of participants was 10 years (range: 1 month to 40 years). Receiver operating characteristic analysis revealed a cutoff point of 6.5 for GED-C PSS (area under the curve of 0.9883) demonstrated high sensitivity (1.0) and specificity (0.97). A histogram indicated that the PSS scores of the two confirmed GD patients were distinct from those of other participants. Conclusions The study suggests that GED-C PSS shows potential for the early diagnosis of GD, supporting its broader clinical use for both children and adults. Gaucher disease Lysosomal storage disorder Early diagnosis Figures Figure 1 Figure 2 Background Gaucher disease (GD) is an autosomal recessive metabolic disorder that impairs glycolipid recycling in cells[ 1 , 2 ] due to deficient activity of the lysosomal enzyme glucocerebrosidase, leading to the accumulation of glucosylceramide in macrophages[ 1 – 3 ] known as Gaucher cells. This metabolic impairment causes cellular dysfunction and clinical abnormalities, primarily affecting the bone marrow, spleen, and liver, though other organs can also be involved. The enzyme deficiency may also impact cells beyond macrophages, such as hematopoietic progenitor cells, erythrocytes, mesenchymal cells, and hepatocytes, contributing to the diverse presentations of GD[ 2 ]. Over 400 variants of the pathogenic GBA1 gene located on chromosome 1 (1q21) have been identified as causes of GD[ 4 , 5 ]. The phenotype of GD is variable; based on the extent and age of neurological involvement, three phenotypes have been suggested to classify GD: type 1 (nonneuronopathic), type 2 (acute neuronopathic), and type 3 (chronic neuronopathic)[ 1 , 2 ]. Definitive diagnosis of GD can be confirmed by observing decreased glucocerebrosidase enzyme activity in the presence of a biallelic pathogenic GBA variants. While newborn screening (NBS) programs in various countries have demonstrated the feasibility and benefits of early GD detection and intervention[ 6 – 10 ], NBS for GD may lead to identifying individuals who do not require immediate treatment due to the disease's variable presentation, as noted by the Delphi expert panel[ 11 ]. The Gaucher Earlier Diagnosis Consensus (GED-C) initiative suggested major signs and covariables of relevance in early GD to facilitate diagnosis by Delphi methodology[ 12 ]. For type 1 GD, seven major signs (splenomegaly, thrombocytopenia, bone manifestations, anemia, hyperferritinemia, hepatomegaly, and gammopathy) and two major covariables (family history, Ashkenazi-Jewish ancestry) were identified. For type 3 GD, nine major signs (splenomegaly, oculomotor disturbances, thrombocytopenia, epilepsy, anemia, hepatomegaly, bone pain, motor disturbances, and kyphosis) and one major covariable (family history) were identified. These parameters may help non-specialists identify GD and increase their level of suspicion[ 2 , 12 ]. The proposed prototype point scoring system (PSS) by the GED-C panel effectively distinguished GD patients from those with overlapping symptoms [ 13 – 15 ]. According to rare disease registry data from the Korea Disease Control and Prevention Agency, annual newly diagnosed GD patients were only 1 in 2020, and 4 in 2021. Efforts to implement neonatal screening for lysosomal storage diseases, including GD, have only recently begun, and the disease still appears to be underdiagnosed in South Korea. This study aimed to determine the optimal cutoff value for GED-C PSS based on symptoms and test findings for early GD diagnosis in Korean patients. Additionally, we sought to identify the clinical manifestations of GD in Koreans and assess the utility of GED-C PSS, particularly in pediatric, adolescent, and young adult populations, given the limited research on these groups. Methods Point scoring The GED-C PSS was used to estimate scores for each participant suspected of having GD (Table 1 ). Score for each factor was stratified (3 points, 2 points, 1 point, and 0.5 points) based on the likelihood of association with GD as determined by GED-C consensus. Table 1 Gaucher Earlier Diagnosis Consensus (GED-C) regarding signs and co-variables with their scores in point-scoring system (PSS). If the total PSS corresponding is 2 or higher, the individual is eligible to enroll in the prospective or retrospective study. Score Sign or co-variable Major signs and co-variables 3 points Splenomegaly (≥ 3x normal) Disturbed oculomotor function (slow horizontal saccades with unimpaired vision) 2 points Thrombocytopenia, mild or moderate: − 50 x10 3 /µL ≤ platelet count < 150 x10 3 /µL Bone issues, including pain, crises, avascular necrosis and fractures Family history of Gaucher disease Anemia, mild or moderate: − 1 ≤ age < 2: 8.0 g/dL ≤ hemoglobin < 10.5 g/dL − 2 ≤ age < 12: 8.0 g/dL ≤ hemoglobin < 11.5 g/dL − 12 ≤ age < 19: 8.0 g/dL ≤ hemoglobin < 12.0 g/dL − 19 ≤ age: 8.5 g/dL ≤ hemoglobin < 12.0 g/dL) Hyperferritinemia, mild or moderate: − 300 ng/mL ≤ serum ferritin < 1000 ng/mL Jewish ancestry Disturbed motor function (impairment of primary motor development) Hepatomegaly, mild or moderate (≤ 3x normal) Myoclonus epilepsy Kyphosis Gammopathy – monoclonal or polyclonal 1 point Anemia, severe: − 1 ≤ age < 19: hemoglobin < 8.0 g/dL − 19 ≤ age: hemoglobin 3x normal) Thrombocytopenia, severe: − Platelet count < 50 x103/µL) Minor signs and co-variables 0.5 points Gallstones Bleeding, bruising or coagulopathy Leukopenia Cognitive deficit Low bone mineral density Growth retardation including low body weight Asthenia Cardiovascular calcification Dyslipidemia Elevated ACE levels Fatigue Pulmonary infiltrates Age < 19 years Family history of Parkinson’s disease Blood relative who died of fetal hydrops and/or with diagnosis of neonatal sepsis of uncertain etiology Patients and data collection This study involved both retrospective data analysis and prospective patient recruitment. The data collection and patient enrollment were performed between May 2019 and November 2023. Individuals already diagnosed with GD were excluded from the study. In the retrospective study, data from patients below 19 years of age who visited Severance Hospital within the 5 years prior to study approval month (Visit 0) were reviewed. Patients exhibiting symptoms suggestive of GD and meeting GED-C criteria (Table 1 ) were included. If the total PSS corresponding was 2 or higher, the individual was eligible to enroll in the study. When these patients subsequently visited the outpatient clinic (Visit 1), approximately 3 mL of venous blood was drawn using a syringe for a dry blood smear test to confirm GD. Blood was smeared on a filter card and sent to a central laboratory. For the prospective study, 14 sites across 13 hospitals in Korea recruited patients. Patients of pediatric age and young adults who visited outpatient clinics or were hospitalized and exhibited symptoms suggestive of GD and met the GED-C criteria (Table 1 ) were recruited and scored. Subjects with PSS 2 or higher were eligible to enroll in the study. During their visit (Visit 1), blood was drawn and tested. Statistical analysis A receiver operating characteristic (ROC) curve was used to summarize diagnostic performance in terms of sensitivity and specificity of various PSS cutoff values for distinguishing between GD and non-GD cases. The area under the ROC curve (AUC) and the corresponding 95% confidence interval (CI) were calculated using the bootstrapping method. The Youden index (sensitivity + specificity − 1) was used to determine the statistically optimal cutoff on the ROC curve for diagnosing GD [16]. All statistical analyses were performed using R (version 4.3.0). Results Of the 518 registered participants, 513 were analyzed after excluding five due to dropouts and duplicates. The retrospective and prospective groups comprised 162 and 351 participants, respectively. The median age of participants was 10 years (range: 1 month to 40 years). Of the total number of patients, 478 visited for hematologic concerns, and 35 were referred from other specialties for consultation. Most common hematologic abnormalities were thrombocytopenia (55%), anemia (67%), and leukopenia (99%) (Table 2 ). Two patients were confirmed to have GD. Table 2 Patients’ characteristics and demographics according to Gaucher Early Diagnosis Consensus, point-scoring system Characteristic Score Non-Gaucher (N = 511) Gaucher (N = 2) Cohort Prospective 349 (68%) 2 (100%) Retrospective 162 (32%) 0 (0%) Overall PSS score Mean (SD) 3.47 (1.26) 9.00 (3.54) Range 2.00, 9.00 6.50, 11.50 Median (IQR) 3.00 (2.50, 4.50) 9.00 (7.75, 10.25) Assessed GED-C PSS sign or co-variables Splenomegaly (≥ 3× normal) Yes 3 points 17 (3.3%) 1 (50%) No 472 (92%) 1 (50%) Unknown 22 (4.3%) 0 (0%) Disturbed oculomotor function (slow horizontal saccades with unimpaired vision) Yes 3 points 2 (0.4%) 0 (0%) No 507 (99%) 2 (100%) Unknown 2 (0.4%) 0 (0%) Thrombocytopenia Mild or Moderate 2 points 173 (34%) 1 (50%) Severe 1 points 108 (21%) 1 (50%) No 225 (44%) 0 (0%) Unknown 5 (1.0%) 0 (0%) Anaemia Mild or Moderate 2 points 285 (56%) 0 (0%) Severe 1 points 58 (11%) 0 (0%) No 163 (32%) 2 (100%) Unknown 5 (1.0%) 0 (0%) Leukopenia Yes 0.5 points 160 (31%) 1 (50%) No 346 (68%) 1 (50%) Unknown 5 (1.0%) 0 (0%) Hyperferritinaemia Mild or Moderate 2 points 40 (7.8%) 1 (50%) Severe 1 points 25 (4.9%) 0 (0%) No 207 (41%) 1 (50%) Unknown 239 (47%) 0 (0%) Hepatomegaly Mild or Moderate 2 points 59 (12%) 1 (50%) Severe 1 points 2 (0.4%) 0 (0%) No 426 (83%) 1 (50%) Unknown 24 (4.7%) 0 (0%) Dyslipidemia Yes 0.5 points 13 (2.5%) 0 (0%) No 437 (86%) 1 (50%) Unknown 61 (12%) 1 (50%) Elevated angiotensin-converting enzyme levels Yes 0.5 points 2 (0.4%) 0 (0%) No 68 (13%) 0 (0%) Unknown 441 (86%) 2 (100%) Family history of Gaucher disease Yes 2 points 0 (0%) 0 (0%) No 505 (99%) 2 (100%) Unknown 6 (1.2%) 0 (0%) Disturbed motor function (impairment of primary motor development) Yes 2 points 1 (0.2%) 2 (100%) No 509 (100%) 0 (0%) Unknown 1 (0.2%) 0 (0%) Myoclonus epilepsy Yes 2 points 13 (2.5%) 1 (50%) No 496 (97%) 1 (50%) Unknown 2 (0.4%) 0 (0%) Cognitive deficit Yes 0.5 points 5 (1.0%) 1 (50%) No 500 (98%) 0 (0%) Unknown 6 (1.2%) 1 (50%) Gammopathy – monoclonal or polyclonal Yes 2 points 3 (0.6%) 0 (0%) No 94 (18%) 1 (50%) Unknown 414 (81%) 1 (50%) Bone issues, including pain, crises, avascular necrosis, and fractures Yes 2 points 6 (1.2%) 0 (0%) No 492 (96%) 2 (100%) Unknown 13 (2.5%) 0 (0%) Kyphosis Yes 2 points 0 (0%) 0 (0%) No 505 (99%) 2 (100%) Unknown 6 (1.2%) 0 (0%) Low bone mineral density Yes 0.5 points 3 (0.6%) 0 (0%) No 77 (15%) 1 (50%) Unknown 431 (84%) 1 (50%) Jewish ancestry Yes 2 points 0 (0%) 0 (0%) No 505 (99%) 2 (100%) Unknown 6 (1.2%) 0 (0%) Gallstones Yes 0.5 points 5 (1.0%) 0 (0%) No 215 (42%) 2 (100%) Unknown 291 (57%) 0 (0%) Bleeding, bruising, or coagulopathy Yes 0.5 points 55 (11%) 0 (0%) No 453 (89%) 2 (100%) Unknown 3 (0.6%) 0 (0%) Growth retardation including low body weight Yes 0.5 points 10 (2.0%) 1 (50%) No 500 (98%) 1 (50%) Unknown 1 (0.2%) 0 (0%) Asthenia Yes 0.5 points 4 (0.8%) 0 (0%) No 504 (99%) 2 (100%) Unknown 3 (0.6%) 0 (0%) Cardiovascular calcification Yes 0.5 points 0 (0%) 0 (0%) No 109 (21%) 1 (50%) Unknown 402 (79%) 1 (50%) Fatigue 0.5 points Yes 17 (3.3%) 0 (0%) No 488 (95%) 1 (50%) Unknown 6 (1.2%) 1 (50%) Pulmonary infiltrates Yes 0.5 points 0 (0%) 0 (0%) No 179 (35%) 1 (50%) Unknown 332 (65%) 1 (50%) Age ≤ 18 years Yes 0.5 points 448 (88%) 1 (50%) No 63 (12%) 1 (50%) Unknown 0 (0%) 0 (0%) Family history of Parkinson disease Yes 0.5 points 0 (0%) 0 (0%) No 499 (98%) 2 (100%) Unknown 12 (2.3%) 0 (0%) Blood relative who died of fetal hydrops and/or with diagnosis of neonatal sepsis of uncertain etiology Yes 0.5 points 0 (0%) 0 (0%) No 501 (98%) 2 (100%) Unknown 10 (2.0%) 0 (0%) GED-C, Gaucher Early Diagnosis Consensus; PSS, point-scoring system ROC analysis and PSS cutoff value The ROC curve and cutoff value for the GD PSS score were derived from analyzing 513 participants. A histogram showed that the PSS scores of the two GD patients were distinct from those of other participants (Fig. 1 ). The cutoff point was identified as 6.5, with an AUC of 0.9883 (95% CI: 0.9677-1). The sensitivity and specificity at this cutoff were 1.0 and 0.9706, respectively (Fig. 2 ). Prospective diagnosis of GD in two patients Two patients were diagnosed with GD during prospective enrollment. The PSS scores were clearly distinct between GD and non-GD patients, as described in Table 3 . Among the two confirmed cases, the first patient was a 23-year-old male with mild thrombocytopenia, disturbed motor function, myoclonic epilepsy, and cognitive deficit, yielding a PSS score of 6.5. The second was a 7-month-old infant with severe splenomegaly, thrombocytopenia, leukopenia, mild hyperferritinemia, hepatomegaly, disturbed motor function, and growth retardation, resulting in a PSS score of 11.5. Table 3 Comparison between non-Gaucher patients with Gaucher disease patients. Characteristic Non-Gaucher (N = 511) Gaucher (N = 2) Cohort Prospective 349 (68%) 2 (100%) Retrospective 162 (32%) 0 (0%) Overall PSS score Mean (SD) 3.47 (1.26) 9.00 (3.54) Range 2.00, 9.00 6.50, 11.50 Median (IQR) 3.00 (2.50, 4.50) 9.00 (7.75, 10.25) Assessed GED-C PSS sign or co-variables Splenomegaly (≥ 3× normal) 17 (3.3%) 1 (50%) Disturbed oculomotor function (slow horizontal saccades with unimpaired vision) 2 (0.4%) 0 (0%) Thrombocytopenia 281 (55%) 2 (100%) Anaemia 343 (67%) 0 (0%) Leukopenia 160 (31%) 1 (50%) Hyperferritinaemia 65 (13%) 1 (50%) Hepatomegaly 61 (12%) 1 (50%) Dyslipidemia 13 (2.5%) 0 (0%) Elevated angiotensin-converting enzyme levels 2 (0.4%) 0 (0%) Family history of Gaucher disease 0 (0%) 0 (0%) Disturbed motor function (impairment of primary motor development) 1 (0.2%) 2 (100%) Myoclonus epilepsy 13 (2.5%) 1 (50%) Cognitive deficit 5 (1.0%) 1 (50%) Gammopathy – monoclonal or polyclonal 3 (0.6%) 0 (0%) Bone issues, including pain, crises, avascular necrosis, and fractures 6 (1.2%) 0 (0%) Kyphosis 0 (0%) 0 (0%) Low bone mineral density 3 (0.6%) 0 (0%) Jewish ancestry 0 (0%) 0 (0%) Gallstones 5 (1.0%) 0 (0%) Bleeding, bruising, or coagulopathy 55 (11%) 0 (0%) Growth retardation including low body weight 10 (2.0%) 1 (50%) Asthenia 4 (0.8%) 0 (0%) Cardiovascular calcification 0 (0%) 0 (0%) Fatigue 17 (3.3%) 0 (0%) Pulmonary infiltrates 0 (0%) 0 (0%) Age ≤ 18 years 448 (88%) 1 (50%) Family history of Parkinson disease 0 (0%) 0 (0%) Blood relative who died of fetal hydrops and/or with diagnosis of neonatal sepsis of uncertain etiology 0 (0%) 0 (0%) GED-C, Gaucher Early Diagnosis Consensus; PSS, point-scoring system Discussion The GED-C PSS was first validated in the UK with 25 patients[ 13 ] and in a biobank study of Finland[ 14 ]. The UK study found that the mean PSS score in GD patients was 1.08 (standard deviation, 0.25) compared to 0.58 (standard deviation, 0.31) in non-GD individuals, while a PSS score of 0.82 distinguished GD with a sensitivity of 100% and a specificity of 71%[ 13 ]. The Finland study, utilizing both retrospective data from 170,000 adults in collaboration with the Finland Biobank and prospective data from new patients, discovered an indicative PPS of 6-18.5 for confirmed GD patients[ 14 ]. In contrast to the other two earlier studies, this Korean study differed in that most data were collected prospectively based on physicians' suspicions. The number of GD patients diagnosed was low, with only two confirmed cases. The global incidence of type I GD is 1 in 1,000 in Ashkenazi Jews, generally 1 in 30,000 to 40,000 among other ethnicities, and types 2 and 3 occur even less frequently[ 1 , 2 ]. Considering the low incidence rate, statistically, it is possible that no patients would have been diagnosed with GD in the study. However, this study demonstrated that when clinically suspected patients are screened, the diagnosis can be made at a much higher rate. This suggests that the real-world implementation of GED-C PPS allows for determining a diagnosing threshold, as demonstrated in previous studies. One pediatric patient with type 2 GD and one adult with type 3 GD were diagnosed in the study. We observed that the PSS of these two GD patients deviated significantly from that of the non-GD group. As the diverse phenotypes of type 3 GD may hinder a timely diagnosis if not properly suspected, GED-C PSS could be used as a tool to assist diagnosis. This study was also unique in that most of the participants were pediatric patients, demonstrating the applicability of GED-C PSS in this age group. This study has several limitations. First, we established age-specific hemoglobin criteria for anemia, distinct from the original GED-C consensus, in order to diagnose anemia in pediatric patients. Second, the potential for variability in the results could have arisen due to differences in the screening items used among the various physicians involved. However, in real-world clinical practice, this approach can be reflective of it. Lastly, including more patients would have resulted in the identification of more cases and thus more reliable results. Conclusions This study with over five hundred patients was the first of its kind to investigate the clinical use of GED-C PSS prospectively, as opposed to earlier studies. Approaches including newborn screening, diagnostic algorithms, and scoring-based screening as used in this study, should be considered for timely GD diagnosis given its prevalence and available resources. This study provides direct evidence that GED-C scoring can be used for diagnosing GD in both children and adults. Abbreviations GD Gaucher disease GED-C Gaucher Earlier Diagnosis Consensus PSS Point-scoring system NBS Newborn screening IRB Institutional Review Board ROC Receiver operating characteristic AUC Area under the curve CI Confidence interval SD Standard deviation IQR Interquartile range ACE Angiotensin-converting enzyme Declarations Ethics approval and consent to participate All procedures in this study were performed in accordance with the ethical standards of the Institutional Review Board of Severance Hospital and principles set out in the Declaration of Helsinki. The study received the Institutional Review Board approval (Severance Hospital IRB 4-2019-0279), and informed consent was obtained from adult patients and the parents of pediatric participants. Availability of data and materials Data is available upon request to the corresponding author. Competing Interests C.J.L received funding from Takeda to conduct the study. All other authors declare no competing interests related to this study. Funding This research was supported by Takeda Pharmaceuticals Korea Co., Ltd. Authors’ contributions S.M.H and M.K interpreted the data and wrote the manuscript. M.K and J.M.N analyzed the data. C.J.L conceptualized and supervised the study. All authors contributed to data acquisition, manuscript revisions, and approved the final version of the manuscript as submitted. Acknowledgements We thank Songhwa Choi from Takeda Korea for her invaluable support in the research conduct and reporting. References Stirnemann J, Belmatoug N, Camou F, Serratrice C, Froissart R, Caillaud C, et al. A Review of Gaucher Disease Pathophysiology, Clinical Presentation and Treatments. Int J Mol Sci. 2017;18(2). Weinreb NJ, Goker-Alpan O, Kishnani PS, Longo N, Burrow TA, Bernat JA, et al. The diagnosis and management of Gaucher disease in pediatric patients: Where do we go from here? Mol Genet Metab. 2022;136(1):4-21. Orvisky E, Park JK, LaMarca ME, Ginns EI, Martin BM, Tayebi N, et al. Glucosylsphingosine accumulation in tissues from patients with Gaucher disease: correlation with phenotype and genotype. Mol Genet Metab. 2002;76(4):262-70. Lepe-Balsalobre E, Santotoribio JD, Nuñez-Vazquez R, García-Morillo S, Jiménez-Arriscado P, Hernández-Arévalo P, et al. Genotype/phenotype relationship in Gaucher disease patients. Novel mutation in glucocerebrosidase gene. Clinical Chemistry and Laboratory Medicine (CCLM). 2020;58(12):2017-24. Grabowski GA, Zimran A, Ida H. Gaucher disease types 1 and 3: Phenotypic characterization of large populations from the ICGG Gaucher Registry. American Journal of Hematology. 2015;90(S1):S12-S8. Burton BK, Charrow J, Hoganson GE, Waggoner D, Tinkle B, Braddock SR, et al. Newborn Screening for Lysosomal Storage Disorders in Illinois: The Initial 15-Month Experience. The Journal of Pediatrics. 2017;190:130-5. Kang L, Zhan X, Gu X, Zhang H. Successful newborn screening for Gaucher disease using fluorometric assay in China. Journal of Human Genetics. 2017;62(8):763-8. Burlina AB, Polo G, Salviati L, Duro G, Zizzo C, Dardis A, et al. Newborn screening for lysosomal storage disorders by tandem mass spectrometry in North East Italy. Journal of Inherited Metabolic Disease. 2018;41(2):209-19. Chien YH, Lee NC, Chen PW, Yeh HY, Gelb MH, Chiu PC, et al. Newborn screening for Morquio disease and other lysosomal storage diseases: Results from the 8-plex assay for 70,000 newborns. Orphanet Journal of Rare Diseases. 2020;15(1). Sawada T, Kido J, Sugawara K, Yoshida S, Matsumoto S, Shimazu T, et al. Newborn screening for Gaucher disease in Japan. Mol Genet Metab Rep. 2022;31:100850. Kishnani PS, Al-Hertani W, Balwani M, Göker-Alpan Ö, Lau HA, Wasserstein M, et al. Screening, patient identification, evaluation, and treatment in patients with Gaucher disease: Results from a Delphi consensus. Mol Genet Metab. 2022;135(2):154-62. Mehta A, Kuter DJ, Salek SS, Belmatoug N, Bembi B, Bright J, et al. Presenting signs and patient co-variables in Gaucher disease: outcome of the Gaucher Earlier Diagnosis Consensus (GED-C) Delphi initiative. Internal Medicine Journal. 2019;49(5):578-91. Mehta A, Rivero-Arias O, Abdelwahab M, Campbell S, McMillan A, Rolfe MJ, et al. Scoring system to facilitate diagnosis of Gaucher disease. Internal Medicine Journal. 2020;50(12):1538-46. Savolainen MJ, Karlsson A, Rohkimainen S, Toppila I, Lassenius MI, Falconi CV, et al. The Gaucher earlier diagnosis consensus point-scoring system (GED-C PSS): Evaluation of a prototype in Finnish Gaucher disease patients and feasibility of screening retrospective electronic health record data for the recognition of potential undiagnosed patients in Finland. Molecular Genetics and Metabolism Reports. 2021;27:100725. Revel-Vilk S, Shalev V, Gill A, Paltiel O, Manor O, Tenenbaum A, et al. Assessing the diagnostic utility of the Gaucher Earlier Diagnosis Consensus (GED-C) scoring system using real-world data. Orphanet J Rare Dis. 2024;19(1):71. Cite Share Download PDF Status: Published Journal Publication published 10 Nov, 2025 Read the published version in Orphanet Journal of Rare Diseases → Version 1 posted Editorial decision: Minor revision 07 May, 2025 Reviewers agreed at journal 07 Apr, 2025 Reviewers invited by journal 02 Apr, 2025 Editor assigned by journal 23 Mar, 2025 First submitted to journal 21 Mar, 2025 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-6280810","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":437365903,"identity":"f3740089-27d6-4222-96e5-7ef44bd6fbe4","order_by":0,"name":"Seung Min 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Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jiyoung","middleName":"","lastName":"Oh","suffix":""},{"id":437365908,"identity":"ee0f9452-5050-4320-9af0-0d9d81576b57","order_by":5,"name":"SeHee Kim","email":"","orcid":"","institution":"Yonsei University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"SeHee","middleName":"","lastName":"Kim","suffix":""},{"id":437365909,"identity":"6193828b-3717-4a20-9e02-dce191d9c300","order_by":6,"name":"Hong Koh","email":"","orcid":"","institution":"Yonsei University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Koh","suffix":""},{"id":437365910,"identity":"29cf526c-21ec-4be2-9fd3-6145f7e0fc3d","order_by":7,"name":"Sung-Eun Kim","email":"","orcid":"","institution":"KNUH: Kyungpook National University Chilgok Hospital","correspondingAuthor":false,"prefix":"","firstName":"Sung-Eun","middleName":"","lastName":"Kim","suffix":""},{"id":437365911,"identity":"23cf1346-9312-4878-b27d-019e5e059d1c","order_by":8,"name":"Nack-Gyun Chung","email":"","orcid":"","institution":"Catholic University of Korea","correspondingAuthor":false,"prefix":"","firstName":"Nack-Gyun","middleName":"","lastName":"Chung","suffix":""},{"id":437365912,"identity":"ef8dd792-5351-46cd-b5d9-367696e0e542","order_by":9,"name":"Ye Jee Shim","email":"","orcid":"","institution":"Kyungpook National University Chilgok Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ye","middleName":"Jee","lastName":"Shim","suffix":""},{"id":437365913,"identity":"308d67d7-3190-418d-812d-7edb4318d613","order_by":10,"name":"Hawk Kim","email":"","orcid":"","institution":"Gachon University Gil Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Hawk","middleName":"","lastName":"Kim","suffix":""},{"id":437365914,"identity":"30a1c9bf-8603-4b81-96af-63168a59818b","order_by":11,"name":"Jae Min Lee","email":"","orcid":"","institution":"Pusan National University Medical School: Pusan National University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jae","middleName":"Min","lastName":"Lee","suffix":""},{"id":437365915,"identity":"ac91e137-768a-4017-a91d-956218d5c268","order_by":12,"name":"Sung-Soo Yoon","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Sung-Soo","middleName":"","lastName":"Yoon","suffix":""},{"id":437365916,"identity":"ac3ec33e-5aee-427f-a84e-73f76f568269","order_by":13,"name":"Ho Joon Im","email":"","orcid":"","institution":": Asan Medical Center Children's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ho","middleName":"Joon","lastName":"Im","suffix":""},{"id":437365917,"identity":"97d9a963-df33-4ac9-a1a0-2c8fa44f94b7","order_by":14,"name":"Hyoung Jin Kang","email":"","orcid":"","institution":"Seoul National University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hyoung","middleName":"Jin","lastName":"Kang","suffix":""},{"id":437365918,"identity":"0d50c10a-0e23-4da4-8250-137ef34d00d5","order_by":15,"name":"Young Rok Do","email":"","orcid":"","institution":"Keimyung University Dongsan Medical Center","correspondingAuthor":false,"prefix":"","firstName":"Young","middleName":"Rok","lastName":"Do","suffix":""},{"id":437365919,"identity":"d4eff513-9d88-4273-9e14-2bbcf5381570","order_by":16,"name":"Chung Mo Nam","email":"","orcid":"","institution":"Yonsei University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chung","middleName":"Mo","lastName":"Nam","suffix":""},{"id":437365920,"identity":"45455eca-8da6-463b-be10-84bf43ed956d","order_by":17,"name":"Chuhl Joo Lyu","email":"","orcid":"https://orcid.org/0000-0001-7124-7818","institution":"Yonsei University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Chuhl","middleName":"Joo","lastName":"Lyu","suffix":""}],"badges":[],"createdAt":"2025-03-22 01:35:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6280810/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6280810/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13023-025-03891-1","type":"published","date":"2025-11-10T15:58:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82055538,"identity":"d91f22b6-2e43-4158-a9a3-3b6405b5f92a","added_by":"auto","created_at":"2025-05-06 10:24:43","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":131877,"visible":true,"origin":"","legend":"\u003cp\u003eHistogram of proto-type point scoring system\u003c/p\u003e","description":"","filename":"Figure1..jpg","url":"https://assets-eu.researchsquare.com/files/rs-6280810/v1/be91b3fe6fb727e21e2b342b.jpg"},{"id":82055540,"identity":"47cbc255-45cd-4f52-9657-40bf48b5f2cd","added_by":"auto","created_at":"2025-05-06 10:24:43","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":123867,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver-operating characteristic (ROC) curve\u003c/p\u003e","description":"","filename":"Figure2..jpg","url":"https://assets-eu.researchsquare.com/files/rs-6280810/v1/f9d63c6f6063d2204b0e8c86.jpg"},{"id":96105722,"identity":"32d4e924-7227-4398-985e-91ba2b92ccd7","added_by":"auto","created_at":"2025-11-17 16:11:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1721761,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6280810/v1/f10af7f6-46a3-402f-ad87-a7a32880d497.pdf"}],"financialInterests":"","formattedTitle":"The Gaucher Earlier Diagnosis Consensus Point-Scoring System for Children and Young Adults: A Retrospective and Prospective Evaluation in Korea","fulltext":[{"header":"Background","content":"\u003cp\u003eGaucher disease (GD) is an autosomal recessive metabolic disorder that impairs glycolipid recycling in cells[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] due to deficient activity of the lysosomal enzyme glucocerebrosidase, leading to the accumulation of glucosylceramide in macrophages[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] known as Gaucher cells. This metabolic impairment causes cellular dysfunction and clinical abnormalities, primarily affecting the bone marrow, spleen, and liver, though other organs can also be involved. The enzyme deficiency may also impact cells beyond macrophages, such as hematopoietic progenitor cells, erythrocytes, mesenchymal cells, and hepatocytes, contributing to the diverse presentations of GD[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOver 400 variants of the pathogenic \u003cem\u003eGBA1\u003c/em\u003e gene located on chromosome 1 (1q21) have been identified as causes of GD[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The phenotype of GD is variable; based on the extent and age of neurological involvement, three phenotypes have been suggested to classify GD: type 1 (nonneuronopathic), type 2 (acute neuronopathic), and type 3 (chronic neuronopathic)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDefinitive diagnosis of GD can be confirmed by observing decreased glucocerebrosidase enzyme activity in the presence of a biallelic pathogenic \u003cem\u003eGBA\u003c/em\u003e variants. While newborn screening (NBS) programs in various countries have demonstrated the feasibility and benefits of early GD detection and intervention[\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], NBS for GD may lead to identifying individuals who do not require immediate treatment due to the disease's variable presentation, as noted by the Delphi expert panel[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe Gaucher Earlier Diagnosis Consensus (GED-C) initiative suggested major signs and covariables of relevance in early GD to facilitate diagnosis by Delphi methodology[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. For type 1 GD, seven major signs (splenomegaly, thrombocytopenia, bone manifestations, anemia, hyperferritinemia, hepatomegaly, and gammopathy) and two major covariables (family history, Ashkenazi-Jewish ancestry) were identified. For type 3 GD, nine major signs (splenomegaly, oculomotor disturbances, thrombocytopenia, epilepsy, anemia, hepatomegaly, bone pain, motor disturbances, and kyphosis) and one major covariable (family history) were identified. These parameters may help non-specialists identify GD and increase their level of suspicion[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The proposed prototype point scoring system (PSS) by the GED-C panel effectively distinguished GD patients from those with overlapping symptoms [\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to rare disease registry data from the Korea Disease Control and Prevention Agency, annual newly diagnosed GD patients were only 1 in 2020, and 4 in 2021. Efforts to implement neonatal screening for lysosomal storage diseases, including GD, have only recently begun, and the disease still appears to be underdiagnosed in South Korea. This study aimed to determine the optimal cutoff value for GED-C PSS based on symptoms and test findings for early GD diagnosis in Korean patients. Additionally, we sought to identify the clinical manifestations of GD in Koreans and assess the utility of GED-C PSS, particularly in pediatric, adolescent, and young adult populations, given the limited research on these groups.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePoint scoring\u003c/h2\u003e \u003cp\u003eThe GED-C PSS was used to estimate scores for each participant suspected of having GD (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Score for each factor was stratified (3 points, 2 points, 1 point, and 0.5 points) based on the likelihood of association with GD as determined by GED-C consensus.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGaucher Earlier Diagnosis Consensus (GED-C) regarding signs and co-variables with their scores in point-scoring system (PSS). If the total PSS corresponding is 2 or higher, the individual is eligible to enroll in the prospective or retrospective study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSign or co-variable\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMajor signs and co-variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSplenomegaly (\u0026ge;\u0026thinsp;3x normal)\u003c/p\u003e \u003cp\u003eDisturbed oculomotor function (slow horizontal saccades with unimpaired vision)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThrombocytopenia, mild or moderate:\u003c/p\u003e \u003cp\u003e\u0026minus; 50 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L\u0026thinsp;\u0026le;\u0026thinsp;platelet count\u0026thinsp;\u0026lt;\u0026thinsp;150 x10\u003csup\u003e3\u003c/sup\u003e/\u0026micro;L\u003c/p\u003e \u003cp\u003eBone issues, including pain, crises, avascular necrosis and fractures\u003c/p\u003e \u003cp\u003eFamily history of Gaucher disease\u003c/p\u003e \u003cp\u003eAnemia, mild or moderate:\u003c/p\u003e \u003cp\u003e\u0026minus; 1\u0026thinsp;\u0026le;\u0026thinsp;age\u0026thinsp;\u0026lt;\u0026thinsp;2: 8.0 g/dL\u0026thinsp;\u0026le;\u0026thinsp;hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;10.5 g/dL\u003c/p\u003e \u003cp\u003e\u0026minus; 2\u0026thinsp;\u0026le;\u0026thinsp;age\u0026thinsp;\u0026lt;\u0026thinsp;12: 8.0 g/dL\u0026thinsp;\u0026le;\u0026thinsp;hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;11.5 g/dL\u003c/p\u003e \u003cp\u003e\u0026minus; 12\u0026thinsp;\u0026le;\u0026thinsp;age\u0026thinsp;\u0026lt;\u0026thinsp;19: 8.0 g/dL\u0026thinsp;\u0026le;\u0026thinsp;hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;12.0 g/dL\u003c/p\u003e \u003cp\u003e\u0026minus; 19\u0026thinsp;\u0026le;\u0026thinsp;age: 8.5 g/dL\u0026thinsp;\u0026le;\u0026thinsp;hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;12.0 g/dL)\u003c/p\u003e \u003cp\u003eHyperferritinemia, mild or moderate:\u003c/p\u003e \u003cp\u003e\u0026minus; 300 ng/mL\u0026thinsp;\u0026le;\u0026thinsp;serum ferritin\u0026thinsp;\u0026lt;\u0026thinsp;1000 ng/mL\u003c/p\u003e \u003cp\u003eJewish ancestry\u003c/p\u003e \u003cp\u003eDisturbed motor function (impairment of primary motor development)\u003c/p\u003e \u003cp\u003eHepatomegaly, mild or moderate (\u0026le;\u0026thinsp;3x normal)\u003c/p\u003e \u003cp\u003eMyoclonus epilepsy\u003c/p\u003e \u003cp\u003eKyphosis\u003c/p\u003e \u003cp\u003eGammopathy \u0026ndash; monoclonal or polyclonal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 point\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnemia, severe:\u003c/p\u003e \u003cp\u003e\u0026minus; 1\u0026thinsp;\u0026le;\u0026thinsp;age\u0026thinsp;\u0026lt;\u0026thinsp;19: hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;8.0 g/dL\u003c/p\u003e \u003cp\u003e\u0026minus; 19\u0026thinsp;\u0026le;\u0026thinsp;age: hemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;8.5 g/dL\u003c/p\u003e \u003cp\u003eHyperferritinemia, severe:\u003c/p\u003e \u003cp\u003e\u0026minus; serum ferritin\u0026thinsp;\u0026ge;\u0026thinsp;1000 ng/mL)\u003c/p\u003e \u003cp\u003eHepatomegaly, severe (\u0026gt;\u0026thinsp;3x normal)\u003c/p\u003e \u003cp\u003eThrombocytopenia, severe:\u003c/p\u003e \u003cp\u003e\u0026minus; Platelet count\u0026thinsp;\u0026lt;\u0026thinsp;50 x103/\u0026micro;L)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMinor signs and co-variables\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGallstones\u003c/p\u003e \u003cp\u003eBleeding, bruising or coagulopathy\u003c/p\u003e \u003cp\u003eLeukopenia\u003c/p\u003e \u003cp\u003eCognitive deficit\u003c/p\u003e \u003cp\u003eLow bone mineral density\u003c/p\u003e \u003cp\u003eGrowth retardation including low body weight\u003c/p\u003e \u003cp\u003eAsthenia\u003c/p\u003e \u003cp\u003eCardiovascular calcification\u003c/p\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003cp\u003eElevated ACE levels\u003c/p\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003cp\u003ePulmonary infiltrates\u003c/p\u003e \u003cp\u003eAge\u0026thinsp;\u0026lt;\u0026thinsp;19 years\u003c/p\u003e \u003cp\u003eFamily history of Parkinson\u0026rsquo;s disease\u003c/p\u003e \u003cp\u003eBlood relative who died of fetal hydrops and/or with diagnosis of neonatal sepsis of uncertain etiology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatients and data collection\u003c/h3\u003e\n\u003cp\u003eThis study involved both retrospective data analysis and prospective patient recruitment. The data collection and patient enrollment were performed between May 2019 and November 2023. Individuals already diagnosed with GD were excluded from the study.\u003c/p\u003e \u003cp\u003eIn the retrospective study, data from patients below 19 years of age who visited Severance Hospital within the 5 years prior to study approval month (Visit 0) were reviewed. Patients exhibiting symptoms suggestive of GD and meeting GED-C criteria (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were included. If the total PSS corresponding was 2 or higher, the individual was eligible to enroll in the study. When these patients subsequently visited the outpatient clinic (Visit 1), approximately 3 mL of venous blood was drawn using a syringe for a dry blood smear test to confirm GD. Blood was smeared on a filter card and sent to a central laboratory.\u003c/p\u003e \u003cp\u003eFor the prospective study, 14 sites across 13 hospitals in Korea recruited patients. Patients of pediatric age and young adults who visited outpatient clinics or were hospitalized and exhibited symptoms suggestive of GD and met the GED-C criteria (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) were recruited and scored. Subjects with PSS 2 or higher were eligible to enroll in the study. During their visit (Visit 1), blood was drawn and tested.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eA receiver operating characteristic (ROC) curve was used to summarize diagnostic performance in terms of sensitivity and specificity of various PSS cutoff values for distinguishing between GD and non-GD cases. The area under the ROC curve (AUC) and the corresponding 95% confidence interval (CI) were calculated using the bootstrapping method. The Youden index (sensitivity\u0026thinsp;+\u0026thinsp;specificity \u0026minus;\u0026thinsp;1) was used to determine the statistically optimal cutoff on the ROC curve for diagnosing GD [16]. All statistical analyses were performed using R (version 4.3.0).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 518 registered participants, 513 were analyzed after excluding five due to dropouts and duplicates. The retrospective and prospective groups comprised 162 and 351 participants, respectively. The median age of participants was 10 years (range: 1 month to 40 years). Of the total number of patients, 478 visited for hematologic concerns, and 35 were referred from other specialties for consultation. Most common hematologic abnormalities were thrombocytopenia (55%), anemia (67%), and leukopenia (99%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Two patients were confirmed to have GD.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatients\u0026rsquo; characteristics and demographics according to Gaucher Early Diagnosis Consensus, point-scoring system\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNon-Gaucher (N\u0026thinsp;=\u0026thinsp;511)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGaucher\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e349 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e162 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall PSS score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.47 (1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.00 (3.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.00, 9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.50, 11.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003cp\u003e(2.50, 4.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003cp\u003e(7.75, 10.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAssessed GED-C PSS sign or co-variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSplenomegaly (\u0026ge;\u0026thinsp;3\u0026times; normal)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e472 (92%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisturbed oculomotor function\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(slow horizontal saccades with unimpaired vision)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e507 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eThrombocytopenia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild or Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e173 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225 (44%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnaemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild or Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e285 (56%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e163 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeukopenia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHyperferritinaemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild or Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e207 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e239 (47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHepatomegaly\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild or Moderate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSevere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e426 (83%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDyslipidemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e437 (86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eElevated angiotensin-converting enzyme levels\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e441 (86%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily history of Gaucher disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e505 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisturbed motor function\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(impairment of primary motor development)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e509 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMyoclonus epilepsy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e496 (97%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCognitive deficit\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500 (98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGammopathy \u0026ndash; monoclonal or polyclonal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e94 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e414 (81%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBone issues, including pain, crises, avascular necrosis, and fractures\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e492 (96%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKyphosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e505 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLow bone mineral density\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e431 (84%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eJewish ancestry\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e505 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGallstones\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e291 (57%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBleeding, bruising, or coagulopathy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e453 (89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrowth retardation including low body weight\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e500 (98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAsthenia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e504 (99%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCardiovascular calcification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e402 (79%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFatigue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e488 (95%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary infiltrates\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e179 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e332 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;18 years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e448 (88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily history of Parkinson disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e499 (98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlood relative who died of fetal hydrops and/or \u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003ewith diagnosis of neonatal sepsis of uncertain etiology\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5 points\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e501 (98%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eGED-C, Gaucher Early Diagnosis Consensus; PSS, point-scoring system\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eROC analysis and PSS cutoff value\u003c/h3\u003e\n\u003cp\u003eThe ROC curve and cutoff value for the GD PSS score were derived from analyzing 513 participants. A histogram showed that the PSS scores of the two GD patients were distinct from those of other participants (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The cutoff point was identified as 6.5, with an AUC of 0.9883 (95% CI: 0.9677-1). The sensitivity and specificity at this cutoff were 1.0 and 0.9706, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eProspective diagnosis of GD in two patients\u003c/h2\u003e \u003cp\u003eTwo patients were diagnosed with GD during prospective enrollment. The PSS scores were clearly distinct between GD and non-GD patients, as described in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Among the two confirmed cases, the first patient was a 23-year-old male with mild thrombocytopenia, disturbed motor function, myoclonic epilepsy, and cognitive deficit, yielding a PSS score of 6.5. The second was a 7-month-old infant with severe splenomegaly, thrombocytopenia, leukopenia, mild hyperferritinemia, hepatomegaly, disturbed motor function, and growth retardation, resulting in a PSS score of 11.5.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison between non-Gaucher patients with Gaucher disease patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-Gaucher\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;511)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGaucher\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCohort\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProspective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e349 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRetrospective\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOverall PSS score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.47 (1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.00 (3.54)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00, 9.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.50, 11.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.00 (2.50, 4.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.00 (7.75, 10.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAssessed GED-C PSS sign or co-variables\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSplenomegaly (\u0026ge;\u0026thinsp;3\u0026times; normal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisturbed oculomotor function\u003c/p\u003e \u003cp\u003e(slow horizontal saccades with unimpaired vision)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThrombocytopenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e281 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnaemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e343 (67%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukopenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e160 (31%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperferritinaemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (13%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatomegaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated angiotensin-converting enzyme levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of Gaucher disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisturbed motor function\u003c/p\u003e \u003cp\u003e(impairment of primary motor development)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyoclonus epilepsy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive deficit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGammopathy \u0026ndash; monoclonal or polyclonal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBone issues, including pain, crises, avascular necrosis, and fractures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKyphosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow bone mineral density\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (0.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJewish ancestry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGallstones\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBleeding, bruising, or coagulopathy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrowth retardation including low body weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthenia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (0.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular calcification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (3.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePulmonary infiltrates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;18 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e448 (88%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (50%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily history of Parkinson disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood relative who died of fetal hydrops and/or\u003c/p\u003e \u003cp\u003ewith diagnosis of neonatal sepsis of uncertain etiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eGED-C, Gaucher Early Diagnosis Consensus; PSS, point-scoring system\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe GED-C PSS was first validated in the UK with 25 patients[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and in a biobank study of Finland[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The UK study found that the mean PSS score in GD patients was 1.08 (standard deviation, 0.25) compared to 0.58 (standard deviation, 0.31) in non-GD individuals, while a PSS score of 0.82 distinguished GD with a sensitivity of 100% and a specificity of 71%[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The Finland study, utilizing both retrospective data from 170,000 adults in collaboration with the Finland Biobank and prospective data from new patients, discovered an indicative PPS of 6-18.5 for confirmed GD patients[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn contrast to the other two earlier studies, this Korean study differed in that most data were collected prospectively based on physicians' suspicions. The number of GD patients diagnosed was low, with only two confirmed cases. The global incidence of type I GD is 1 in 1,000 in Ashkenazi Jews, generally 1 in 30,000 to 40,000 among other ethnicities, and types 2 and 3 occur even less frequently[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Considering the low incidence rate, statistically, it is possible that no patients would have been diagnosed with GD in the study. However, this study demonstrated that when clinically suspected patients are screened, the diagnosis can be made at a much higher rate. This suggests that the real-world implementation of GED-C PPS allows for determining a diagnosing threshold, as demonstrated in previous studies.\u003c/p\u003e \u003cp\u003eOne pediatric patient with type 2 GD and one adult with type 3 GD were diagnosed in the study. We observed that the PSS of these two GD patients deviated significantly from that of the non-GD group. As the diverse phenotypes of type 3 GD may hinder a timely diagnosis if not properly suspected, GED-C PSS could be used as a tool to assist diagnosis.\u003c/p\u003e \u003cp\u003eThis study was also unique in that most of the participants were pediatric patients, demonstrating the applicability of GED-C PSS in this age group.\u003c/p\u003e \u003cp\u003eThis study has several limitations. First, we established age-specific hemoglobin criteria for anemia, distinct from the original GED-C consensus, in order to diagnose anemia in pediatric patients. Second, the potential for variability in the results could have arisen due to differences in the screening items used among the various physicians involved. However, in real-world clinical practice, this approach can be reflective of it. Lastly, including more patients would have resulted in the identification of more cases and thus more reliable results.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study with over five hundred patients was the first of its kind to investigate the clinical use of GED-C PSS prospectively, as opposed to earlier studies. Approaches including newborn screening, diagnostic algorithms, and scoring-based screening as used in this study, should be considered for timely GD diagnosis given its prevalence and available resources. This study provides direct evidence that GED-C scoring can be used for diagnosing GD in both children and adults.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eGD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eGaucher disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eGED-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eGaucher Earlier Diagnosis Consensus\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003ePSS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003ePoint-scoring system\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eNBS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eNewborn screening\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eIRB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eInstitutional Review Board\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eROC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eReceiver operating characteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eArea under the curve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eConfidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eStandard deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eInterquartile range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 160px;\"\u003e\n \u003cp\u003eACE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 416px;\"\u003e\n \u003cp\u003eAngiotensin-converting enzyme\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll procedures in this study were performed in accordance with the ethical standards of the Institutional Review Board of Severance Hospital and principles set out in the Declaration of Helsinki.\u0026nbsp;The study received the Institutional Review Board approval (Severance Hospital IRB 4-2019-0279), and informed consent was obtained from adult patients and the parents of pediatric participants.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eData is available upon request to the corresponding author.\u003c/p\u003e\n\u003cp\u003eCompeting Interests\u003c/p\u003e\n\u003cp\u003eC.J.L received funding from Takeda to conduct the study. All other authors declare no competing interests related to this study. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFunding\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was supported by Takeda Pharmaceuticals Korea Co., Ltd.\u003c/p\u003e\n\u003cp\u003eAuthors’ contributions\u003c/p\u003e\n\u003cp\u003eS.M.H and M.K interpreted the data and wrote the manuscript. M.K\u0026nbsp;and J.M.N analyzed the data. C.J.L conceptualized and supervised the study.\u0026nbsp;All authors contributed to data acquisition, manuscript revisions, and approved the final version of the manuscript as submitted.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eWe thank Songhwa Choi from Takeda Korea for her invaluable support in the research conduct and reporting.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eStirnemann J, Belmatoug N, Camou F, Serratrice C, Froissart R, Caillaud C, et al. A Review of Gaucher Disease Pathophysiology, Clinical Presentation and Treatments. Int J Mol Sci. 2017;18(2).\u003c/li\u003e\n\u003cli\u003eWeinreb NJ, Goker-Alpan O, Kishnani PS, Longo N, Burrow TA, Bernat JA, et al. The diagnosis and management of Gaucher disease in pediatric patients: Where do we go from here? Mol Genet Metab. 2022;136(1):4-21.\u003c/li\u003e\n\u003cli\u003eOrvisky E, Park JK, LaMarca ME, Ginns EI, Martin BM, Tayebi N, et al. Glucosylsphingosine accumulation in tissues from patients with Gaucher disease: correlation with phenotype and genotype. Mol Genet Metab. 2002;76(4):262-70.\u003c/li\u003e\n\u003cli\u003eLepe-Balsalobre E, Santotoribio JD, Nu\u0026ntilde;ez-Vazquez R, Garc\u0026iacute;a-Morillo S, Jim\u0026eacute;nez-Arriscado P, Hern\u0026aacute;ndez-Ar\u0026eacute;valo P, et al. Genotype/phenotype relationship in Gaucher disease patients. Novel mutation in glucocerebrosidase gene. Clinical Chemistry and Laboratory Medicine (CCLM). 2020;58(12):2017-24.\u003c/li\u003e\n\u003cli\u003eGrabowski GA, Zimran A, Ida H. Gaucher disease types 1 and 3: Phenotypic characterization of large populations from the ICGG Gaucher Registry. American Journal of Hematology. 2015;90(S1):S12-S8.\u003c/li\u003e\n\u003cli\u003eBurton BK, Charrow J, Hoganson GE, Waggoner D, Tinkle B, Braddock SR, et al. Newborn Screening for Lysosomal Storage Disorders in Illinois: The Initial 15-Month Experience. The Journal of Pediatrics. 2017;190:130-5.\u003c/li\u003e\n\u003cli\u003eKang L, Zhan X, Gu X, Zhang H. Successful newborn screening for Gaucher disease using fluorometric assay in China. Journal of Human Genetics. 2017;62(8):763-8.\u003c/li\u003e\n\u003cli\u003eBurlina AB, Polo G, Salviati L, Duro G, Zizzo C, Dardis A, et al. Newborn screening for lysosomal storage disorders by tandem mass spectrometry in North East Italy. Journal of Inherited Metabolic Disease. 2018;41(2):209-19.\u003c/li\u003e\n\u003cli\u003eChien YH, Lee NC, Chen PW, Yeh HY, Gelb MH, Chiu PC, et al. Newborn screening for Morquio disease and other lysosomal storage diseases: Results from the 8-plex assay for 70,000 newborns. Orphanet Journal of Rare Diseases. 2020;15(1).\u003c/li\u003e\n\u003cli\u003eSawada T, Kido J, Sugawara K, Yoshida S, Matsumoto S, Shimazu T, et al. Newborn screening for Gaucher disease in Japan. Mol Genet Metab Rep. 2022;31:100850.\u003c/li\u003e\n\u003cli\u003eKishnani PS, Al-Hertani W, Balwani M, G\u0026ouml;ker-Alpan \u0026Ouml;, Lau HA, Wasserstein M, et al. Screening, patient identification, evaluation, and treatment in patients with Gaucher disease: Results from a Delphi consensus. Mol Genet Metab. 2022;135(2):154-62.\u003c/li\u003e\n\u003cli\u003eMehta A, Kuter DJ, Salek SS, Belmatoug N, Bembi B, Bright J, et al. Presenting signs and patient co-variables in Gaucher disease: outcome of the Gaucher Earlier Diagnosis Consensus (GED-C) Delphi initiative. Internal Medicine Journal. 2019;49(5):578-91.\u003c/li\u003e\n\u003cli\u003eMehta A, Rivero-Arias O, Abdelwahab M, Campbell S, McMillan A, Rolfe MJ, et al. Scoring system to facilitate diagnosis of Gaucher disease. Internal Medicine Journal. 2020;50(12):1538-46.\u003c/li\u003e\n\u003cli\u003eSavolainen MJ, Karlsson A, Rohkimainen S, Toppila I, Lassenius MI, Falconi CV, et al. The Gaucher earlier diagnosis consensus point-scoring system (GED-C PSS): Evaluation of a prototype in Finnish Gaucher disease patients and feasibility of screening retrospective electronic health record data for the recognition of potential undiagnosed patients in Finland. Molecular Genetics and Metabolism Reports. 2021;27:100725.\u003c/li\u003e\n\u003cli\u003eRevel-Vilk S, Shalev V, Gill A, Paltiel O, Manor O, Tenenbaum A, et al. Assessing the diagnostic utility of the Gaucher Earlier Diagnosis Consensus (GED-C) scoring system using real-world data. Orphanet J Rare Dis. 2024;19(1):71.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Gaucher disease, Lysosomal storage disorder, Early diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-6280810/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6280810/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eGaucher disease (GD) is an autosomal recessive condition caused by insufficient glucocerebrosidase activity. The Gaucher Earlier Diagnosis Consensus (GED-C) initiative created a point-scoring system (PSS) to facilitate the early identification of GD based on significant indicators and covariables. This study aimed to evaluate the applicability and utility of the GED-C PSS in pediatric and young adult patients in Korea.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThis study included both retrospective analysis and prospective recruitment. Subject recruitment involved 14 sites across 13 hospitals in Korea, where patients of any age meeting GED-C criteria were recruited, and blood samples were collected. Data of 513 subjects were analyzed and two patients were confirmed to have GD during prospective enrollment. The median age of participants was 10 years (range: 1 month to 40 years). Receiver operating characteristic analysis revealed a cutoff point of 6.5 for GED-C PSS (area under the curve of 0.9883) demonstrated high sensitivity (1.0) and specificity (0.97). A histogram indicated that the PSS scores of the two confirmed GD patients were distinct from those of other participants.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe study suggests that GED-C PSS shows potential for the early diagnosis of GD, supporting its broader clinical use for both children and adults.\u003c/p\u003e","manuscriptTitle":"The Gaucher Earlier Diagnosis Consensus Point-Scoring System for Children and Young Adults: A Retrospective and Prospective Evaluation in Korea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-06 10:24:38","doi":"10.21203/rs.3.rs-6280810/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2025-05-07T11:29:08+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-07T18:56:08+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-02T10:33:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-24T01:36:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2025-03-21T21:34:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b97ccdae-3b13-4fa0-8736-5806f938e2a6","owner":[],"postedDate":"May 6th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:08:54+00:00","versionOfRecord":{"articleIdentity":"rs-6280810","link":"https://doi.org/10.1186/s13023-025-03891-1","journal":{"identity":"orphanet-journal-of-rare-diseases","isVorOnly":false,"title":"Orphanet Journal of Rare Diseases"},"publishedOn":"2025-11-10 15:58:24","publishedOnDateReadable":"November 10th, 2025"},"versionCreatedAt":"2025-05-06 10:24:38","video":"","vorDoi":"10.1186/s13023-025-03891-1","vorDoiUrl":"https://doi.org/10.1186/s13023-025-03891-1","workflowStages":[]},"version":"v1","identity":"rs-6280810","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6280810","identity":"rs-6280810","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}