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Development and validation of diagnostic triage criteria for liver disease from a minimum data set enabling the ‘intelligent LFT’ pathway for the automated assessment of deranged liver enzymes
  1. Michael Hugh Miller1,
  2. Andrew Fraser2,
  3. Gillian Leggett2,
  4. Alastair MacGilchrist3,
  5. George Gibson4,
  6. James Orr4,
  7. Ewan H Forrest4,
  8. Ellie Dow5,
  9. William Bartlett5,
  10. Chirstopher Weatherburn5,
  11. Axel Laurell1,
  12. Kirsty Grant1,
  13. Kathryn Scott6,
  14. Ronald Neville5,
  15. John F Dillon1
  1. 1Gut Group, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
  2. 2NHS Grampian, Aberdeen Royal Infirmary, Aberdeen, UK
  3. 3NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK
  4. 4NHS Greater Glasgow and Clyde, Glasgow Royal Infirmary, Glasgow, UK
  5. 5NHS Tayside, Ninewells Hospital and Medical School, Dundee, UK
  6. 6Department of Gastroenterology, University of Dundee, Dundee, UK
  1. Correspondence to Dr Michael Hugh Miller, Gut Group, University of Dundee, Ninewells Hospital and Medical School, Dundee DD1 9SY, UK; michael.miller1{at}


Background Liver function tests (LFTs) are commonly abnormal; most patients with ‘incidental’ abnormal LFTs are not investigated appropriately and for those who are, current care pathways are geared to find an explanation for the abnormality by a lengthy process of investigation and exclusion, with costs to the patient and to the health service.

Objective To validate an intelligent automatable analysis tool (iLFT) for abnormal liver enzymes, which diagnoses common liver conditions, provides fibrosis stage and recommends management

Design A retrospective case note review from three tertiary referral liver centres, with application of the iLFT algorithm and comparison with the clinician’s final opinion as gold standard.

Results The iLFT algorithm in 91.3% of cases would have correctly recommended referral or management in primary care. In the majority of the rest of the cases, iLFT failed safe and recommended referral even when the final clinical diagnosis could have been managed in primary care. Diagnostic accuracy was achieved in 82.4% of cases, consistent with the fail-safe design of the algorithm. Two cases would have remained in primary care as per the algorithm outcome, however on clinical review had features of advanced fibrosis.

Conclusion iLFT analysis of abnormal liver enzymes offers a safe and robust method of risk stratifying patients to the most appropriate care pathway as well as providing reliable diagnostic information based on a single blood draw, without repeated contacts with health services. Offers the possibility of high quality investigation and diagnosis to all patients rather than a tiny minority.

  • liver function test

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  • Contributors All authors contributed to the conception and data collection processes as well as manuscript editing. MHM coordinated the study and performed data analysis and manuscript preparation. JFD maintained study oversight.

  • Funding This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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