FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2801280192> ?p ?o ?g. }

• W2801280192 endingPage "104" @default.
• W2801280192 startingPage "98" @default.
• W2801280192 abstract "Watch a video presentation of this article Watch the interview with the author Nonalcoholic fatty liver disease (NAFLD) is a global epidemic that ranges from isolated hepatic steatosis (nonalcoholic fatty liver [NAFL]) to steatosis plus inflammation (nonalcoholic steatohepatitis [NASH]) with or without fibrosis (Fig. 1).1 Whereas NAFL generally follows a benign course, NASH carries a significant risk for progression to fibrosis.2 The key diagnostic challenges in NAFLD are to accurately detect NASH and to quantify the degree of fibrosis to identify those at highest risk for liver-related morbidity and mortality. Thus, when seeing a patient with possible NAFLD, the primary questions to answer are: (1) Does this patient have NAFLD? (2) Does this patient have underlying NASH? (3) Does this patient have any fibrosis? and (4) Does this patient have advanced fibrosis (stage 3 or 4)? Serum biomarkers and imaging modalities across the NAFLD spectrum. Abbreviations: APRI, AST-to-platelet ratio index; ARFI, acoustic radiation force impulse; BARD, BMI, AST:ALT ratio, and diabetes status score; CK-18, cytokeratin-18; HAIR, hypertension, age, insulin resistance. Liver biopsy remains the gold standard for diagnosing NAFLD; however, its widespread use is limited by the risk associated with an invasive procedure, cost, and sampling error.3 Thus, noninvasive diagnostic modalities allow for risk stratification of patients with NAFLD to select those who would benefit most from liver biopsy, while potentially avoiding this invasive procedure in others. Not all hepatic steatosis, defined as fat >5% to 10% of the liver parenchyma, is NAFLD.4 It is important to rule out other causes of hepatic steatosis, particularly alcohol (Table 1). NAFLD is typically associated with the features of the metabolic syndrome, which includes central adiposity, hypertension, dyslipidemia, and insulin resistance.4, 5 Thus, presence of one or more metabolic risk factors should raise clinical suspicion for NAFLD. NAFLD Alcoholic liver disease Hepatitis C, genotype 3 Medications Amiodarone Corticosteroids Methotrexate Tamoxifen Wilson's disease Hemochromatosis Starvation Parenteral nutrition Lipodystrophy Abetalipoproteinemia Reye's syndrome Acute fatty liver of pregnancy HELLP syndrome Medications Antiretroviral medications Valproate Inherited metabolic disorders Lysosomal acid lipase deficiency Lecithin-cholesterol acyltransferase deficiency Hepatic steatosis is commonly detected incidentally on imaging such as ultrasound or computed tomography (CT). Notably, these modalities have poor sensitivity, detect fat only when 20% to 33% of the liver parenchyma is involved, and cannot accurately quantify the amount of hepatic fat present. Newer modalities such as magnetic resonance (MR) imaging–based spectroscopy, MR-proton density fat fraction (MR-PDFF), and transient elastography (TE)-based controlled attenuation parameter (CAP) are more sensitive and allow for relatively accurate quantification of hepatic steatosis (Table 2).6 However, each of these imaging modalities has strengths and limitations that must be considered before implementation in the general population (Table 3).4 There are also several panels that have been proposed to diagnose hepatic steatosis, many of which have been used in population-based studies aimed at estimating the epidemiology and natural history of NAFLD (Table 2).6 <0.30 <−1.413 <30 Good for detection of moderate-to-severe steatosis Widely available Low cost Safe Poor sensitivity and negative predictive value Unable to detect mild steatosis Not quantitative Fibrosis and steatosis have similar appearance Operator dependent Accuracy influenced by BMI Good for detection of moderate-to-severe steatosis Better specificity than ultrasound Provides additional anatomic information Poor sensitivity Unable to detect mild steatosis Ionizing radiation exposure Limited by variable amounts of iron Quantitative More sensitive than conventional ultrasound Quantitative Sensitive Limited availability High cost Less accurate with nonhomogeneous fat distribution Correlates with stage of fibrosis Point-of-care test Accuracy reduced in obesity Severe steatosis may lead to false positives Operator dependent Accuracy influenced by BMI Higher failure rates than TE Operator dependent Accuracy influenced by BMI Most accurate test for determining fibrosis stage Accuracy not affected by BMI, degree of steatosis Limited availability High cost Reliable noninvasive methods to detect NASH remain limited. Commonly investigated methods can be grouped into two broad categories: serum biomarkers and predictive models. Serum aminotransferases, which are often used in clinical practice as a surrogate for inflammation, have poor predictive value for NASH.4, 5 Serum alanine aminotransferase (ALT) greater than two times the upper limit of normal (>70 U/L) has only 50% sensitivity and 61% specificity for NASH.7 In addition, patients with NAFLD can have normal ALT levels, particularly as the disease progresses.4 Therefore, although elevated aminotransferases should raise suspicion for NASH, normal levels should not be used to exclude NASH.4, 5 Although serum biomarkers are not currently available for clinical use, many are under investigation (Table 4). These biomarkers broadly reflect the pathways involved in NASH development, including hepatocyte apoptosis, oxidative stress, and inflammation. Several diagnostic panels, such as the NashTest,8 use a combination of biomarkers and clinical factors to predict NASH (Table 4). Given the lack of reliable noninvasive tests, physicians must use clinical factors to risk-stratify patients prior to liver biopsy. The presence of one or more features of the metabolic syndrome in a patient with NAFLD warrants referral to a specialist for consideration of liver biopsy.4, 5 >70 53-71 50 72.2-50 60.7 50.6-60.7 >216 >287 77 65 65 92 >0.2772 >0.3499 95 77 70 87 60 74 97 89 >0.14 >0.83 84 16 86 99 44 90 98 91 oxNASH15 Ballooning Inflammation >55.2 >54.6 79 78 65 67 67 72 77 74 Hepatic fibrosis is the primary predictor of liver-related mortality in NAFLD. Furthermore, this relationship is stage dependent, and higher fibrosis stage is associated with higher liver-related mortality.9 Identifying patients with early-stage fibrosis is key to implementing risk-reduction strategies to prevent disease progression. Unfortunately, most diagnostic tests currently in use are best suited to detect advanced fibrosis. Even the most accurate imaging studies available are relatively insensitive for stage 1 fibrosis (Table 5). Several clinical prediction rules, serum biomarkers, and imaging techniques are available to detect advanced hepatic fibrosis (Table 6). Clinical prediction rules, including the NAFLD Fibrosis Score, the Fibrosis-4 (FIB-4) index, and the aspartate aminotransferase (AST):ALT ratio, have the advantage of using readily available, cost-effective laboratory tests and have recently been shown to correlate with mortality in NAFLD.10 These scoring systems are best suited to rule out the presence of advanced fibrosis with negative predictive values >90%.6 Comparatively, the positive predictive value is modest, ranging from 55% to 79%.6 Thus, values greater than the upper cutoff require liver biopsy for confirmation of fibrosis, whereas a score less than the cutoff is likely sufficient to rule out advanced fibrosis and may reduce the need for liver biopsy by ∼75%.6 <−1.455 >0.676 78 33 58 98 30 79 92 86 0.81 (0.71-0.91) <1.30 >3.25 85 26 65 98 36 75 95 85 0.86 (0.78-0.94) <0.8 1.0 >1.0 74 52 78 90 44 55 93 89 0.83 (0.74-0.91) 2 0.77 (0.68-0.87) 1 0.67 (0.54-0.8) 0.375 >0.462 89 78 96 98 80 87 98 96 0.87 (0.67-1.0) 30 70 77 15 77 98 54 73 90 76 0.81 (0.74-0.86) Several serum biomarkers and panels directly measure by-products of fibrosis formation as a surrogate for hepatic fibrosis. One clinically available complex predictive model is the enhanced liver fibrosis (ELF) panel, which is composed of several individual biomarkers and has been shown to predict mortality in chronic liver disease.11 Similar to the clinical prediction rules, serum biomarkers/panels have good sensitivity to rule out advanced fibrosis, but they are less accurate at detecting early fibrosis with large ranges of indeterminate scores. Several imaging modalities have been developed that allow for quantification of hepatic fibrosis with a higher degree of accuracy than serological tests. Both vibration-controlled TE (VCTE) and MR elastography (MRE) use liver stiffness as a surrogate marker for fibrosis. VCTE, known commercially as FibroScan, is a point-of-care test that can be used in a clinic setting to predict advanced fibrosis with fairly high accuracy.6 VCTE is an appealing screening tool given its ease of use; however, its accuracy is significantly reduced in obese patients.6 MRE, whose accuracy is not as dependent on body mass index (BMI), has been shown in some studies to have better accuracy than VCTE in both obese12 and nonobese13 patients with NAFLD; however, its use is limited by high cost and limited availability. Both the American Association for the Study of Liver Diseases (AASLD) and the European Association for the Study of the Liver (EASL) have published practice guidelines that can assist clinicians in integrating noninvasive methods with clinical factors to make decisions on the utility of liver biopsy (Fig. 2).4, 5 Regardless of the noninvasive method used for risk stratification, it is important to remember that NAFLD is a dynamic disease, and thus ongoing risk assessment for liver disease progression over time is of paramount importance. Diagnostic flow chart to assess and monitor disease severity in the presence of suspected NAFLD and metabolic risk factors based on the most recent AASLD and EASL-EASD-European Association for the Study of Obesity (EASO) Clinical Practice Guidelines for the diagnosis and management of NAFLD. 1See Table 1.4 2See Table 6.5 *Risk factors for NASH include the metabolic syndrome, obesity, hypertension, dyslipidemia, and insulin resistance. In summary, the current imperfect gold standard for the diagnosis of NAFLD/NASH is liver biopsy. A number of serum markers, imaging modalities, and clinical prediction rules are available as noninvasive alternatives to liver biopsy, but most have substantial limitations in clinical practice. To date, MRI-PDFF and MRE seem to be the most accurate modalities for detecting hepatic steatosis and fibrosis, respectively.6 However, widespread use of these modalities is limited by cost and availability in clinical practice. TE is a more widely available tool for fibrosis assessment and offers accuracy close to that of MRE. Noninvasive detection of NASH and accurate determination of fibrosis stage remain key diagnostic challenges in need of further investigation." @default.
• W2801280192 created "2018-05-17" @default.
• W2801280192 creator A5011275616 @default.
• W2801280192 creator A5022570572 @default.
• W2801280192 creator A5045544656 @default.
• W2801280192 date "2018-04-01" @default.
• W2801280192 modified "2023-10-17" @default.
• W2801280192 title "Diagnostic challenges of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis" @default.
• W2801280192 cites W2001454915 @default.
• W2801280192 cites W2014351118 @default.
• W2801280192 cites W2060847352 @default.
• W2801280192 cites W2063437798 @default.
• W2801280192 cites W2111187697 @default.
• W2801280192 cites W2117145345 @default.
• W2801280192 cites W2118655749 @default.
• W2801280192 cites W2121514783 @default.
• W2801280192 cites W2156792510 @default.
• W2801280192 cites W2164252555 @default.
• W2801280192 cites W2171798494 @default.
• W2801280192 cites W2204688218 @default.
• W2801280192 cites W2546306361 @default.
• W2801280192 cites W2554642866 @default.
• W2801280192 cites W2588592564 @default.
• W2801280192 cites W2734724639 @default.
• W2801280192 cites W2774672890 @default.
• W2801280192 cites W2920090955 @default.
• W2801280192 cites W3143409077 @default.
• W2801280192 doi "https://doi.org/10.1002/cld.716" @default.
• W2801280192 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6103635" @default.
• W2801280192 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30147867" @default.
• W2801280192 hasPublicationYear "2018" @default.
• W2801280192 type Work @default.
• W2801280192 sameAs 2801280192 @default.
• W2801280192 citedByCount "49" @default.
• W2801280192 countsByYear W28012801922019 @default.
• W2801280192 countsByYear W28012801922020 @default.
• W2801280192 countsByYear W28012801922021 @default.
• W2801280192 countsByYear W28012801922022 @default.
• W2801280192 countsByYear W28012801922023 @default.
• W2801280192 crossrefType "journal-article" @default.
• W2801280192 hasAuthorship W2801280192A5011275616 @default.
• W2801280192 hasAuthorship W2801280192A5022570572 @default.
• W2801280192 hasAuthorship W2801280192A5045544656 @default.
• W2801280192 hasBestOaLocation W28012801921 @default.
• W2801280192 hasConcept C126322002 @default.
• W2801280192 hasConcept C2776954865 @default.
• W2801280192 hasConcept C2778772119 @default.
• W2801280192 hasConcept C2779134260 @default.
• W2801280192 hasConcept C3018708256 @default.
• W2801280192 hasConcept C71924100 @default.
• W2801280192 hasConcept C90924648 @default.
• W2801280192 hasConceptScore W2801280192C126322002 @default.
• W2801280192 hasConceptScore W2801280192C2776954865 @default.
• W2801280192 hasConceptScore W2801280192C2778772119 @default.
• W2801280192 hasConceptScore W2801280192C2779134260 @default.
• W2801280192 hasConceptScore W2801280192C3018708256 @default.
• W2801280192 hasConceptScore W2801280192C71924100 @default.
• W2801280192 hasConceptScore W2801280192C90924648 @default.
• W2801280192 hasFunder F4320337338 @default.
• W2801280192 hasIssue "4" @default.
• W2801280192 hasLocation W28012801921 @default.
• W2801280192 hasLocation W28012801922 @default.
• W2801280192 hasLocation W28012801923 @default.
• W2801280192 hasLocation W28012801924 @default.
• W2801280192 hasOpenAccess W2801280192 @default.
• W2801280192 hasPrimaryLocation W28012801921 @default.
• W2801280192 hasRelatedWork W2063941454 @default.
• W2801280192 hasRelatedWork W2142454959 @default.
• W2801280192 hasRelatedWork W2312762963 @default.
• W2801280192 hasRelatedWork W2402526617 @default.
• W2801280192 hasRelatedWork W2521682887 @default.
• W2801280192 hasRelatedWork W2618551423 @default.
• W2801280192 hasRelatedWork W2799489097 @default.
• W2801280192 hasRelatedWork W3003636062 @default.
• W2801280192 hasRelatedWork W4206719512 @default.
• W2801280192 hasRelatedWork W4283818330 @default.
• W2801280192 hasVolume "11" @default.
• W2801280192 isParatext "false" @default.
• W2801280192 isRetracted "false" @default.
• W2801280192 magId "2801280192" @default.
• W2801280192 workType "article" @default.