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• W4226137890 abstract "The utility of noninvasive tests (NITs) for the diagnosis of advanced fibrosis in nonalcoholic fatty liver disease (NAFLD) is limited by indeterminate results and modest predictive values (PVs). Algorithms of sequential NITs may overcome these shortcomings. Thus, we sought to systematically review the accuracy of sequential algorithms for assessing advanced fibrosis in NAFLD.A systematic review was performed following guidelines in the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. A literature search of PubMed and Embase was performed in July of 2020 to identify studies that evaluated diagnostic characteristics of sequential NIT algorithms in NAFLD.Among 8 studies meeting inclusion criteria, 48 algorithms were studied in 6741 patients. The average sensitivity, specificity, positive PV, negative PV, and proportion of indeterminate values for included algorithms were 72%, 92%, 88%, 82%, and 25%, respectively. Six algorithms achieved sensitivities in the top quartile (≥86.3%) with <25% indeterminate values. Four algorithms achieved specificities in the top quartile (≥98.7%) with <25% indeterminate values. The aforementioned algorithms included combinations of Fibrosis-4, NAFLD fibrosis score, and vibration-controlled transient elastography.Sequential NIT algorithms may reduce indeterminate results while achieving sensitivities comparable to single NITs. Sequential algorithms may also augment the specificities of single NITs, though resulting positive PVs may not be high enough to obviate the need for liver biopsy. Available evidence supports the use of Fibrosis-4, NAFLD fibrosis score, and vibration-controlled transient elastography within sequential algorithms to achieve diagnostic accuracy for advanced fibrosis in NAFLD." @default.
• W4226137890 created "2022-05-05" @default.
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• W4226137890 date "2021-03-12" @default.
• W4226137890 modified "2023-09-30" @default.
• W4226137890 title "Identifying Advanced Fibrosis in NAFLD Using Noninvasive Tests" @default.
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• W4226137890 doi "https://doi.org/10.1097/mcg.0000000000001517" @default.
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