Screening patients in general practice for advanced chronic liver disease using an innovative IT solution: The Liver Toolkit

Author:

Prince David S.1234ORCID,Hoque Shakira5,Kim Christy5,Maher Salim15ORCID,Miller Jane6,Chomley Phoebe6,Pritchard-Jones Janice1,Spruce Sally1,McGarry Nathan5,Baker David7,Elix Penelope8,Liu Ken19ORCID,Strasser Simone I.19ORCID,Goodger Brendan6,Zekry Amany45ORCID,McCaughan Geoffrey W.129ORCID

Affiliation:

1. AW Morrow Gastroenterology and Liver Centre, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia

2. Liver Injury and Cancer Program, Centenary Institute, Sydney, New South Wales, Australia

3. Department of Gastroenterology and Liver, Liverpool Hospital, Liverpool, New South Wales, Australia

4. Faculty of Medicine and Health, The University of New South Wales, Sydney, New South Wales, Australia

5. Department of Gastroenterology and Hepatology, St George Hospital, Kogarah, New South Wales, Australia

6. Central and Eastern Sydney Primary Health Network, Mascot, New South Wales, Australia

7. East Sydney Doctors Darlinghurst, New South Wales, Australia

8. Fountain Street General Practice, Alexandria, New South Wales, Australia

9. Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia

Abstract

Background: Identifying patients with undiagnosed advanced chronic liver disease (ACLD) is a public health challenge. Patients with advanced fibrosis or compensated cirrhosis have much better outcomes than those with decompensated disease and may be eligible for interventions to prevent disease progression. Methods: A cloud-based software solution (“the Liver Toolkit”) was developed to access primary care practice software to identify patients at risk of ACLD. Clinical history and laboratory results were extracted to calculate aspartate aminotransferase-to-platelet ratio index and fibrosis 4 scores. Patients identified were recalled for assessment, including Liver Stiffness Measurement (LSM) via transient elastography. Those with an existing diagnosis of cirrhosis were excluded. Results: Existing laboratory results of more than 32,000 adults across nine general practices were assessed to identify 703 patients at increased risk of ACLD (2.2% of the cohort). One hundred seventy-nine patients (26%) were successfully recalled, and 23/179 (13%) were identified to have ACLD (LSM ≥10.0 kPa) (10% found at indeterminate risk [LSM 8.0–9.9 kPa] and 77% low risk of fibrosis [LSM <8.0 kPa]). In most cases, the diagnosis of liver disease was new, with the most common etiology being metabolic dysfunction–associated steatotic liver disease (n=20, 83%). Aspartate aminotransferase-to-platelet ratio index ≥1.0 and fibrosis 4 ≥3.25 had a positive predictive value for detecting ACLD of 19% and 24%, respectively. Patients who did not attend recall had markers of more severe disease with a higher median aspartate aminotransferase-to-platelet ratio index score (0.57 vs. 0.46, p=0.041). Conclusions: This novel information technology system successfully screened a large primary care cohort using existing laboratory results to identify patients at increased risk ACLD. More than 1 in 5 patients recalled were found to have liver disease requiring specialist follow-up.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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