Observational studyBMJ open2014
Prediction of liver disease in patients whose liver function tests have been checked in primary care: model development and validation using population-based observational cohorts.
Observational study in BMJ open, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Guideline
- Trial
- Microfluidic point-of-care testing device for multiplexed detection of liver function blood markers.Biomedical optics express · 2024Article
- Comparison of various strategies to define the optimal target population for liver fibrosis screening: A population-based cohort study.United European gastroenterology journal · 2022Article
- Association of gamma-glutamyltransferase levels with total mortality, liver-related and cardiovascular outcomes: A prospective cohort study in the UK Biobank.EClinicalMedicine · 2022Article
- Article
- Comparison of Body Mass Index and Fat Indices in Predicting the Severity of Nonalcoholic Fatty Liver Disease Among Children Who Are Overweight and Obese.Frontiers in pediatrics · 2021Article
- Biochemical markers and lipid profile in nonalcoholic fatty liver disease patients in the PERSIAN Guilan cohort study (PGCS), Iran.Journal of family medicine and primary care · 2019Article
- Development and validation of a prediction model to estimate the risk of liver cirrhosis in primary care patients with abnormal liver blood test results: protocol for an electronic health record study in Clinical Practice Research Datalink.Diagnostic and prognostic research · 2019Article
- GPs' experiences and perceptions of early detection of liver disease: a qualitative study in primary care.The British journal of general practice : the journal of the Royal College of General Practitioners · 2018Article
- Effect of a Cooperation Strategy between Primary Care Physicians and Hospital Liver Units on HBV Care in Campania, Italy.Canadian journal of gastroenterology & hepatology · 2018Article
- Biochemical Profile of Nonalcoholic Fatty Liver Disease Patients in Eastern India with Histopathological Correlation.Indian journal of clinical biochemistry : IJCB · 2017Article
- Screening for hepatocellular carcinoma: patient selection and perspectives.Journal of hepatocellular carcinoma · 2017Review
- Alcoholic liver disease - the extent of the problem and what you can do about it.Clinical medicine (London, England) · 2015Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 6 institutions in 2 countries.
Funding
Abstract
objectiveTo derive and validate a clinical prediction model to estimate the risk of liver disease diagnosis following liver function tests (LFTs) and to convert the model to a simplified scoring tool for use in primary care.
designPopulation-based observational cohort study of patients in Tayside Scotland identified as having their LFTs performed in primary care and followed for 2 years. Biochemistry data were linked to secondary care, prescriptions and mortality data to ascertain baseline characteristics of the derivation cohort. A separate validation cohort was obtained from 19 general practices across the rest of Scotland to externally validate the final model.
settingPrimary care, Tayside, Scotland.
participantsDerivation cohort: LFT results from 310 511 patients. After exclusions (including: patients under 16 years, patients having initial LFTs measured in secondary care, bilirubin >35 μmol/L, liver complications within 6 weeks and history of a liver condition), the derivation cohort contained 95 977 patients with no clinically apparent liver condition. Validation cohort: after exclusions, this cohort contained 11 653 patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Diagnosis of a liver condition within 2 years.
resultsFrom the derivation cohort (n=95 977), 481 (0.5%) were diagnosed with a liver disease. The model showed good discrimination (C-statistic=0.78). Given the low prevalence of liver disease, the negative predictive values were high. Positive predictive values were low but rose to 20-30% for high-risk patients.
conclusionsThis study successfully developed and validated a clinical prediction model and subsequent scoring tool, the Algorithm for Liver Function Investigations (ALFI), which can predict liver disease risk in patients with no clinically obvious liver disease who had their initial LFTs taken in primary care. ALFI can help general practitioners focus referral on a small subset of patients with higher predicted risk while continuing to address modifiable liver disease risk factors in those at lower risk.
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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.