Improving the accuracy of clinical interpretation of serological testing for the diagnosis of acute hepatitis a infection

Rycroft, Julian Anthony; Mullender, Claire; Hopkins, Mark; Cutiño-Moguel, Teresa

doi:10.1016/j.jcv.2022.105239

Cited by 4 publications

(2 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Hepatitis is classified into two types: acute hepatitis [8], in which the liver is rapidly inflamed, and chronic hepatitis [9], in which the liver is gradually inflamed and damaged over time. Although any of the aforementioned factors might induce hepatitis, it is most commonly caused by infection with a virus belonging to the hepatitis virus group.…”

Section: Introductionmentioning

confidence: 99%

Hepatitis C prediction using SVM, logistic regression and decision tree

Anjuman Ara,

Anhar Sami,

Daniel Lucky Michael

et al. 2024

World J. Adv. Res. Rev.

View full text Add to dashboard Cite

Hepatitis C is an infection of the liver brought on by the HCV virus. In this condition, early diagnosis is challenging because of the delayed onset of symptoms. Predicting well enough can spare patients from permeant liver damage. The primary goal of this work is to use several machine learning methods to forecast this disease based on widely available and reasonably priced blood test data in order to diagnose and treat patients early on. Three machine learning techniques support vector machine (SVM), logistic regression, decision tree, has been applied on one dataset in this work. To find a suitable approach for illness prediction, the confusion matrix, precision, recall, F1 score, accuracy, receiver operating characteristics (ROC), performances of different strategies have been assessed. The SVM model's overall accuracy is 0.92, the highest among the three models.

show abstract

Section: Introductionmentioning

confidence: 99%

Hepatitis C prediction using SVM, logistic regression and decision tree

Anjuman Ara,

Anhar Sami,

Daniel Lucky Michael

et al. 2024

World J. Adv. Res. Rev.

View full text Add to dashboard Cite

show abstract

“…Anti-HAV IgG antibodies appear almost concomitantly with anti-HAV IgM antibodies but persist lifelong in most recovered individuals as well as years after vaccination against HAV ( https://www.ecdc.europa.eu/en/hepatitis-A/facts ). Although anti-HAV IgM testing is quite reliable, several false-positive anti-HAV IgM results have been reported, thereby highlighting the need for the cautious interpretation of positive results, always in the context of patient history and other laboratory and clinical parameters, and especially in low-incidence settings ( 2 – 8 ).…”

Section: Introductionmentioning

confidence: 99%

Sporadic Hepatitis A Virus PCR False-Positive Results Observed during Reflex Testing of Serum Samples Previously Tested for Anti-HAV Antibodies and Caused by Contamination with HAV RNA Present in the Reagents of the Commercial Anti-HAV Immunoassay

et al. 2023

View full text Add to dashboard Cite

We present the first report of sporadic HAV PCR false-positive results that have been observed during the reflex testing of serum samples that have previously been tested for anti-HAV antibodies and have been caused by contamination with HAV RNA that is present in the reagents of the commercial anti-HAV immunoassay, with potentially serious clinical consequences. Although HAV RNA was consistently detected in the anti-HAV reagents of all three automated immunoassay analyzers that were in use in our laboratory, only the use of one analyzer and the corresponding commercial anti-HAV immunoassay reagents resulted in contamination that led to false positive HAV RNA results, and this was due to a peculiar pipetting mode of action in which the analyzer uses a single pipette tip to collect both anti-HAV reagents and a sample, which consequently causes the permanent contamination of the original sample with HAV RNA.

show abstract