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

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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Publication Details

Journal
Scientific Reports
Published
2024-09-14
DOI
https://doi.org/10.1038/s41598-024-72259-5
Citations
1
Primary Topic
Lysosomal Storage Disorders Research
Type
article
Field-Weighted Citation Impact
0.33

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article

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

Amal Al Tenaiji, Jaloliddin Rustamov, Zahiriddin Rustamov, Fatma Al Jasmi et al.
1 citations
Scientific Reports
Lysosomal Storage Disorders Research
0.33
article

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

Amal Al Tenaiji, Jaloliddin Rustamov, Zahiriddin Rustamov, Fatma Al Jasmi, Nazar Zaki, Mariam Al Harbi, Mohd Saberi Mohamad
article en
1 citations

Abstract

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.

Scientific ReportsVol. 14(1)
Multimedia University (MY), United Arab Emirates University (AE), Shaikh Khalifa Medical City (AE), Tawam Hospital (AE), Abu Dhabi Health Services (AE)
Sanofi, Advanced Technology Research Council
Openalex Percentile: Top 38%
Lysosomal Storage Disorders Research
0.33
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