Observational studyBMJ open2019
Validation of an algorithm using inpatient electronic health records to determine the presence and severity of cirrhosis in patients with hepatocellular carcinoma in England: an observational study.
Observational study in BMJ open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Systematic review: development of a consensus code set to identify cirrhosis in electronic health records.Alimentary pharmacology & therapeutics · 2022Pooled it
- Impact of Ascites on Morbidity and Length of Hospital Stay: A Large Retrospective Study from a Tertiary Referral Center.Medicina (Kaunas, Lithuania) · 2026Article
- Identifying emergency presentations of chronic liver disease using routinely collected administrative hospital data.JHEP reports : innovation in hepatology · 2025Article
- Clinical impact of Choosing Wisely Canada hepatology recommendations: an interrupted time-series analysis using data from GEMINI.BMJ open quality · 2025Article
- Observational
- Validating new coding algorithms to improve identification of alcohol-associated and nonalcohol-associated cirrhosis hospitalizations in administrative databases.Hepatology communications · 2024Article
- Routes to diagnosis for hepatocellular carcinoma patients: predictors and associations with treatment and mortality.British journal of cancer · 2024Article
- Cohort study to assess geographical variation in cholangiocarcinoma treatment in England.World journal of gastrointestinal oncology · 2023Article
- Regional variation in routes to diagnosis of cholangiocarcinoma in England from 2006 to 2017.World journal of gastroenterology · 2023Article
- Cost of hepatocellular carcinoma to the national health service in England: a registry-based analysis.BMJ open gastroenterology · 2023Article
- International Classification of Diseases Codes are Useful in Identifying Cirrhosis in Administrative Databases.Digestive diseases and sciences · 2022Article
- Administrative Coding in Electronic Health Care Record-Based Research of NAFLD: An Expert Panel Consensus Statement.Hepatology (Baltimore, Md.) · 2021Article
- Primary liver cancer in the UK: Incidence, incidence-based mortality, and survival by subtype, sex, and nation.JHEP reports : innovation in hepatology · 2021Article
- Association between new-onset liver cirrhosis and suicide risk in South Korea: A nationwide cohort study.Clinical and molecular hepatology · 2021Article
- The Use of Administrative Data to Investigate the Population Burden of Hepatic Encephalopathy.Journal of clinical medicine · 2020Review
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
objectivesOutcomes in hepatocellular carcinoma (HCC) are determined by both cancer characteristics and liver disease severity. This study aims to validate the use of inpatient electronic health records to determine liver disease severity from treatment and procedure codes.
designRetrospective observational study.
settingTwo National Health Service (NHS) cancer centres in England.
participants339 patients with a new diagnosis of HCC between 2007 and 2016. MAIN OUTCOME: Using inpatient electronic health records, we have developed an optimised algorithm to identify cirrhosis and determine liver disease severity in a population with HCC. The diagnostic accuracy of the algorithm was optimised using clinical records from one NHS Trust and it was externally validated using anonymised data from another centre.
resultsThe optimised algorithm has a positive predictive value (PPV) of 99% for identifying cirrhosis in the derivation cohort, with a sensitivity of 86% (95% CI 82% to 90%) and a specificity of 98% (95% CI 96% to 100%). The sensitivity for detecting advanced stage cirrhosis is 80% (95% CI 75% to 87%) and specificity is 98% (95% CI 96% to 100%), with a PPV of 89%.
conclusionsOur optimised algorithm, based on inpatient electronic health records, reliably identifies and stages cirrhosis in patients with HCC. This highlights the potential of routine health data in population studies to stratify patients with HCC according to liver disease severity.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.