David S Prince, Shakira Hoque, Christy Kim, Salim Maher, Jane Miller, Phoebe Chomley, Janice Pritchard-Jones, Sally Spruce, Nathan McGarry, David Baker, Penelope Elix, Ken Liu, Simone I Strasser, Brendan Goodger, Amany Zekry, Geoffrey W McCaughan
{"title":"利用创新的信息技术解决方案,在全科医生中筛查晚期慢性肝病患者:肝脏工具包。","authors":"David S Prince, Shakira Hoque, Christy Kim, Salim Maher, Jane Miller, Phoebe Chomley, Janice Pritchard-Jones, Sally Spruce, Nathan McGarry, David Baker, Penelope Elix, Ken Liu, Simone I Strasser, Brendan Goodger, Amany Zekry, Geoffrey W McCaughan","doi":"10.1097/HC9.0000000000000482","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":5,"journal":{"name":"ACS Applied Materials & Interfaces","volume":null,"pages":null},"PeriodicalIF":8.3000,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213595/pdf/","citationCount":"0","resultStr":"{\"title\":\"Screening patients in general practice for advanced chronic liver disease using an innovative IT solution: The Liver Toolkit.\",\"authors\":\"David S Prince, Shakira Hoque, Christy Kim, Salim Maher, Jane Miller, Phoebe Chomley, Janice Pritchard-Jones, Sally Spruce, Nathan McGarry, David Baker, Penelope Elix, Ken Liu, Simone I Strasser, Brendan Goodger, Amany Zekry, Geoffrey W McCaughan\",\"doi\":\"10.1097/HC9.0000000000000482\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":5,\"journal\":{\"name\":\"ACS Applied Materials & Interfaces\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2024-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213595/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Materials & Interfaces\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/HC9.0000000000000482\",\"RegionNum\":2,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Materials & Interfaces","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/HC9.0000000000000482","RegionNum":2,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
Screening patients in general practice for advanced chronic liver disease using an innovative IT solution: The Liver Toolkit.
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.
期刊介绍:
ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.