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Screening for lysosomal acid lipase deficiency: A retrospective data mining study and evaluation of screening criteria.

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BACKGROUND AND AIMS Lysosomal acid lipase deficiency (LAL-D) is a lysosomal storage disorder. In severe cases, it can cause life-threatening organ failure due to lipid substrates accumulation. However, mild phenotypes… Click to show full abstract

BACKGROUND AND AIMS Lysosomal acid lipase deficiency (LAL-D) is a lysosomal storage disorder. In severe cases, it can cause life-threatening organ failure due to lipid substrates accumulation. However, mild phenotypes of this disorder are increasingly recognized. The aim of this study is to determine the number of missed LAL-D patients in a large pediatric hospital population. METHODS In a retrospective data mining study, the medical files of children, who visited the outpatient clinic at a university hospital between 2000 and 2016, with high plasma low density lipoprotein cholesterol (LDL-C) levels, were evaluated. Previously developed LAL-D screening criteria, with lipid and alanine aminotransferase (ALT) values adjusted for children, were used to analyze which children are suspect for LAL-D. For suspicion of LAL-D, at least 3 out of 5 screening criteria had to be met. Subsequently data on presentation and follow-up were collected to determine if the clinical picture was compatible with LAL-D. RESULTS We identified 2037 children with high LDL-C levels. Of those, 36 children complied with ≥3 screening criteria. Thirty-one of those had an underlying disorder other than LAL-D that explained the abnormalities and, in the 5 remaining children, ALT and lipid levels normalized spontaneously, thus excluding LAL-D. CONCLUSIONS This study shows that retrospective data mining is unlikely to yield a significant number of LAL-D cases in children. The screening algorithm adjusted for children seems useful and accurate in the selection of children for further testing, suggesting it can be applied prospectively, although further validation is warranted.

Keywords: data mining; retrospective data; lysosomal acid; study; screening criteria

Journal Title: Atherosclerosis
Year Published: 2018

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