An expert rule-based approach for identifying infantile-onset Pompe disease patients using retrospective electronic health records

被引:1
作者
Rustamov, Jaloliddin [1 ]
Rustamov, Zahiriddin [2 ,3 ]
Mohamad, Mohd Saberi [7 ,8 ]
Zaki, Nazar [2 ,3 ]
Al Tenaiji, Amal [4 ]
Al Harbi, Mariam [5 ]
Al Jasmi, Fatma [1 ,3 ,6 ]
机构
[1] United Arab Emirates Univ, Coll Med & Hlth Sci, Dept Genet & Genom, Al Ain, U Arab Emirates
[2] United Arab Emirates Univ, Coll Informat Technol, Dept Comp Sci & Software Engn, Al Ain, U Arab Emirates
[3] United Arab Emirates Univ, ASPIRE Precis Med Res Inst Abu Dhabi, Al Ain, U Arab Emirates
[4] Sheikh Khalifa Med City, Dept Pediat, Abu Dhabi, U Arab Emirates
[5] SEHA Corp Med & Clin Affairs, Res Dept, Abu Dhabi, U Arab Emirates
[6] Tawam Hosp, Dept Pediat, Al Ain, U Arab Emirates
[7] United Arab Emirates Univ, Coll Med & Hlth Sci, Hlth Data Sci Lab, Al Ain, U Arab Emirates
[8] Multimedia Univ, Fac Engn & Technol, Ctr Engn Computat Intelligence, Melaka, Malaysia
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
关键词
Pompe disease; Infantile onset Pompe disease; Electronic health records; Expert rule-based screening; PowerBI; Dashboard analytics; RESPIRATORY-FAILURE; DIAGNOSIS;
D O I
10.1038/s41598-024-72259-5
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Pompe disease (OMIM #232300), a rare genetic disorder, leads to glycogen buildup in the body due to an enzyme deficiency, particularly harming the heart and muscles. Infantile-onset Pompe disease (IOPD) requires urgent treatment to prevent mortality, but the unavailability of these methods often delays diagnosis. Our study aims to streamline IOPD diagnosis in the UAE using electronic health records (EHRs) for faster, more accurate detection and timely treatment initiation. This study utilized electronic health records from the Abu Dhabi Healthcare Company (SEHA) healthcare network in the UAE to develop an expert rule-based screening approach operationalized through a dashboard. The study encompassed six diagnosed IOPD patients and screened 93,365 subjects. Expert rules were formulated to identify potential high-risk IOPD patients based on their age, particular symptoms, and creatine kinase levels. The proposed approach was evaluated using accuracy, sensitivity, and specificity. The proposed approach accurately identified five true positives, one false negative, and four false positive IOPD cases. The false negative case involved a patient with both Pompe disease and congenital heart disease. The focus on CHD led to the overlooking of Pompe disease, exacerbated by no measurement of creatine kinase. The false positive cases were diagnosed with Mitochondrial DNA depletion syndrome 12-A (SLC25A4 gene), Immunodeficiency-71 (ARPC1B mutation), Niemann-Pick disease type C (NPC1 gene mutation leading to frameshift), and Group B Streptococcus meningitis. The proposed approach of integrating expert rules with a dashboard facilitated efficient data visualization and automated patient screening, which aids in the early detection of Pompe disease. Future studies are encouraged to investigate the application of machine learning methodologies to enhance further the precision and efficiency of identifying patients with IOPD.
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页数:14
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