Startseite Routine blood test markers for predicting liver disease post HBV infection: precision pathology and pattern recognition
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Routine blood test markers for predicting liver disease post HBV infection: precision pathology and pattern recognition

  • Busayo I. Ajuwon EMAIL logo , Katrina Roper , Alice Richardson und Brett A. Lidbury
Veröffentlicht/Copyright: 20. September 2023
Diagnosis
Aus der Zeitschrift Diagnosis Band 10 Heft 4

Abstract

Background

Early stages of hepatitis B virus (HBV) infection usually involve inflammation of the liver. Patients with chronic infection have an increased risk of progressive liver fibrosis, cirrhosis, and life-threatening clinical complications of end-stage hepatocellular carcinoma (HCC).

Content

Early diagnosis of hepatic fibrosis and timely clinical management are critical to controlling disease progression and decreasing the burden of end-stage liver cancer. Fibrosis staging, through its current gold standard, liver biopsy, improves patient outcomes, but the clinical procedure is invasive with unpleasant post-procedural complications. Routine blood test markers offer promising diagnostic potential for early detection of liver disease without biopsy. There is a plethora of candidate routine blood test markers that have gone through phases of biomarker validation and have shown great promise, but their current limitations include a predictive ability that is limited to only a few stages of fibrosis. However, the advent of machine learning, notably pattern recognition, presents an opportunity to refine blood-based non-invasive models of hepatic fibrosis in the future.

Summary

In this review, we highlight the current landscape of routine blood-based non-invasive models of hepatic fibrosis, and appraise the potential application of machine learning (pattern recognition) algorithms to refining these models and optimising clinical predictions of HBV-associated liver disease.

Outlook

Machine learning via pattern recognition algorithms takes data analytics to a new realm, and offers the opportunity for enhanced multi-marker fibrosis stage prediction using pathology profile that leverages information across patient routine blood tests.

Keywords: hepatitis B virus; liver disease; precision pathology; pattern recognition; machine learning
Corresponding author: Busayo I. Ajuwon, National Centre for Epidemiology and Population Health, ANU College of Health and Medicine, The Australian National University, Acton, Australian Capital Territory 2601, Australia; and Department of Microbiology, Faculty of Pure and Applied Sciences, Kwara State University, Malete, Nigeria, E-mail:

Funding source: Australian National Health and Medical Research Ideas Grant

Award Identifier / Grant number: 1184720

Funding source: Australian Commonwealth Department of Health Quality Use of Pathology Programme

Award Identifier / Grant number: 4-2UJWED1

Funding source: RSTMH Early Career Grants Programme

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Competing interests: The authors state no conflict of interest.

  5. Research funding: BIA was supported by funding from the National Institute for Health Research (NIHR, UK) through the RSTMH Early Career Grants Programme. AR was partly funded by the Australian National Health and Medical Research Ideas Grant (1184720). BAL was supported by funding from the Australian Commonwealth Department of Health Quality Use of Pathology Programme (QUPP) funding (4-2UJWED1).

  6. Data availability: Not applicable.

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Received: 2023-06-28
Accepted: 2023-08-25
Published Online: 2023-09-20

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Reviews
  3. Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors
  4. Routine blood test markers for predicting liver disease post HBV infection: precision pathology and pattern recognition
  5. Opinion Papers
  6. The challenge of clinical reasoning in chronic multimorbidity: time and interactions in the Health Issues Network model
  7. The first diagnostic excellence conference in Japan
  8. Clouds across the new dawn for clinical, diagnostic and biological data: accelerating the development, delivery and uptake of personalized medicine
  9. Original Articles
  10. Towards diagnostic excellence on academic ward teams: building a conceptual model of team dynamics in the diagnostic process
  11. Error codes at autopsy to study potential biases in diagnostic error
  12. Multicenter evaluation of a method to identify delayed diagnosis of diabetic ketoacidosis and sepsis in administrative data
  13. Detection of fake papers in the era of artificial intelligence
  14. Is language an issue? Accuracy of the German computerized diagnostic decision support system ISABEL and cross-validation with the English counterpart
  15. The feasibility of a mystery case curriculum to enhance diagnostic reasoning skills among medical students: a process evaluation
  16. Internal medicine intern performance on the gastrointestinal physical exam
  17. Scaling up a diagnostic pause at the ICU-to-ward transition: an exploration of barriers and facilitators to implementation of the ICU-PAUSE handoff tool
  18. Learned cautions regarding antibody testing in mast cell activation syndrome
  19. Diagnostic properties of natriuretic peptides and opportunities for personalized thresholds for detecting heart failure in primary care
  20. Incomplete filling of spray-dried K2EDTA evacuated blood tubes: impact on measuring routine hematological parameters on Sysmex XN-10
  21. Letters to the Editor
  22. The diagnostic accuracy of AI-based predatory journal detectors: an analogy to diagnosis
  23. Explainable AI for gut microbiome-based diagnostics: colorectal cancer as a case study
  24. Restless X syndrome: a new diagnostic family of nocturnal, restless, abnormal sensations of various body parts
  25. Erratum
  26. Retraction of: Establishing a stable platform for the measurement of blood endotoxin levels in the dialysis population
https://doi.org/10.1515/dx-2023-0078
Schlagwörter für diesen Artikel
hepatitis B virus; liver disease; precision pathology; pattern recognition; machine learning

Artikel in diesem Heft

  1. Frontmatter
  2. Reviews
  3. Diagnostic errors in uncommon conditions: a systematic review of case reports of diagnostic errors
  4. Routine blood test markers for predicting liver disease post HBV infection: precision pathology and pattern recognition
  5. Opinion Papers
  6. The challenge of clinical reasoning in chronic multimorbidity: time and interactions in the Health Issues Network model
  7. The first diagnostic excellence conference in Japan
  8. Clouds across the new dawn for clinical, diagnostic and biological data: accelerating the development, delivery and uptake of personalized medicine
  9. Original Articles
  10. Towards diagnostic excellence on academic ward teams: building a conceptual model of team dynamics in the diagnostic process
  11. Error codes at autopsy to study potential biases in diagnostic error
  12. Multicenter evaluation of a method to identify delayed diagnosis of diabetic ketoacidosis and sepsis in administrative data
  13. Detection of fake papers in the era of artificial intelligence
  14. Is language an issue? Accuracy of the German computerized diagnostic decision support system ISABEL and cross-validation with the English counterpart
  15. The feasibility of a mystery case curriculum to enhance diagnostic reasoning skills among medical students: a process evaluation
  16. Internal medicine intern performance on the gastrointestinal physical exam
  17. Scaling up a diagnostic pause at the ICU-to-ward transition: an exploration of barriers and facilitators to implementation of the ICU-PAUSE handoff tool
  18. Learned cautions regarding antibody testing in mast cell activation syndrome
  19. Diagnostic properties of natriuretic peptides and opportunities for personalized thresholds for detecting heart failure in primary care
  20. Incomplete filling of spray-dried K2EDTA evacuated blood tubes: impact on measuring routine hematological parameters on Sysmex XN-10
  21. Letters to the Editor
  22. The diagnostic accuracy of AI-based predatory journal detectors: an analogy to diagnosis
  23. Explainable AI for gut microbiome-based diagnostics: colorectal cancer as a case study
  24. Restless X syndrome: a new diagnostic family of nocturnal, restless, abnormal sensations of various body parts
  25. Erratum
  26. Retraction of: Establishing a stable platform for the measurement of blood endotoxin levels in the dialysis population
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