Evidence map›Paper›PMID 39569979›Full record

ArticleJournal of clinical laboratory analysis2024

Laboratory Biochemical and Hematological Parameters: Early Predictive Biomarkers for Diagnosing Hepatitis C Virus Infection.

Saeede Bagheri, Ghazaleh Behrouzian Fard, Nasrin Talkhi, Davoud Rashidi Zadeh, Naser Mobarra, Seyedmahdi Mousavinezhad, Fatemeh Mirzaeian Khamse, Mahdi Hosseini Bafghi

Abstract read
In one paragraph

Article in Journal of clinical laboratory analysis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Saeede BagheriDepartment of Laboratory Sciences, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
Ghazaleh Behrouzian FardDepartment of Laboratory Sciences, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
Nasrin TalkhiDepartment of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Davoud Rashidi ZadehDepartment of Microbiology, Faculty of Basic Sciences, Mashhad Branch, Islamic Azad University, Mashhad, Iran.
Naser MobarraDepartment of Laboratory Sciences, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID https://orcid.org/0000-0001-7613-8151
Seyedmahdi MousavinezhadDepartment of Laboratory Sciences, School of Paramedical Sciences, Sabzevar University of Medical Sciences, Sabzevar, Iran.
Fatemeh Mirzaeian KhamseDepartment of Laboratory Sciences, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
Mahdi Hosseini BafghiDepartment of Laboratory Sciences, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.ORCID https://orcid.org/0000-0003-3632-3170

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatitis C virus (HCV) infection is a worldwide concern, causing liver damage and necessitating early detection to prevent its spread. Studies indicate that evaluating changes in biochemical and hematological parameters, which serve as suitable predictors of inflammation, can be a reasonable method for diagnosing hepatitis C infection.

methodsThis study analyzed 100 samples from high-risk patients positively identified via quantitative real-time PCR (qPCR). Anti-HCV titers, biochemical and inflammatory tests, and complete blood cell counts (CBCs) were performed for these individuals. Additionally, 100 HCV-negative individuals with normal laboratory results were selected as the control group. Receiver operating characteristic (ROC) curves were plotted to determine the cutoff values of the laboratory parameters.

resultsAccording to the findings, the age, average white blood cell (WBC) count, platelet-to-lymphocyte ratio (PLR), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), lactate dehydrogenase (LDH), total bilirubin (TBIL), direct bilirubin (DBIL), alkaline phosphatase (ALP), serum glutamic-pyruvic transaminase (SGPT), and ferritin levels were significantly higher in HCV patients. On the other hand, red blood cell (RBC) counts, neutrophils, lymphocytes, hemoglobin-to-platelet ratio (HPR), and iron (Fe) levels were significantly lower in the case group compared to those in the control group (p < 0.05). Furthermore, the ROC curve analysis revealed that lymphocyte count, neutrophil count, and PLR were very strong predictors for hepatitis C infection (p < 0.0001, AUC = 1).

conclusionThe study highlights significant biochemical and hematological differences between HCV patients and healthy subjects. These biomarkers are crucial for early diagnosis, potentially preventing liver damage and reducing HCV transmission.

Indexed as

BiomarkersHepatitis CROC CurveAdultAgedBlood Cell CountCase-Control StudiesFemaleHepacivirusHumansMaleMiddle AgedBiomarkersbiochemical parametersHCV infectionhematological parametersinflammationpredictive biomarkers

Identifiers

PMID39569979
PMCPMC11659729

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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.