AI Article Synopsis
- A study involving 241 patients with chronic HCV aimed to explore the relationship between liver fibrosis and various blood indices such as platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet-large cell ratio (P-LCR).
- The research utilized automated hematology analyzers and tests for serum fibrosis markers, revealing that lower PLT counts correlated with higher values of MPV, PDW, and P-LCR, indicating a significant association with liver fibrosis levels.
- Results showed that patients with advanced fibrosis had notably lower PLT counts and higher MPV, PDW, and P-LCR values compared to those with mild fibrosis, suggesting these indices may serve as useful indicators for tracking
Article Abstract
Aim: A total of 241 patients with chronic HCV infection were recruited to investigate the association between liver fibrosis and PLT counts, as well as with MPV, PDW and P-LCR indices.
Methods: The determination of PLT indices was carried out using a Sysmex XT-1800i automated hematology analyzer. Serological tests for HA, LN, C-IV and PIIINP were performed in 210 patients. The liver stiffness was measured in 69 patients by transient elastography (FibroScan).
Results: The analysis showed that the four serum fibrosis markers were negatively correlated with PLT counts, but positively correlated with the MPV, PDW and P-LCR values. Moreover, a similar pattern was found after analyzing the FibroScan measurements, which were negatively correlated with PLT counts, but positively correlated with MPV, PDW and P-LCR values. We subdivided the HCV-infected patients into mild and advanced fibrosis groups. The PLT counts were significantly decreased and the MPV, PDW and P-LCR values were significantly increased in the advanced fibrosis group when compared with the mild fibrosis group.
Conclusions: Our results demonstrate that not only the PLT counts but also the MPV, PDW and P-LCR indices significantly correlate with liver fibrosis in HCV-infected patients. Therefore, these indices may be useful laboratory measures for evaluating liver fibrosis progression.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952095 | PMC |
| http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0227544 | PLOS |
Publication Analysis
Top Keywords
Similar Publications
Preoperative prediction of the selection of the NOTES approach for patients with symptomatic simple renal cysts via an interpretable machine learning model: a retrospective study of 264 patients.
Langenbecks Arch Surg
January 2025
Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.
Background: There are multiple surgical approaches for treating symptomatic simple renal cysts (SSRCs). The natural orifice transluminal endoscopic surgery (NOTES) approach has gradually been applied as an emerging minimally invasive approach for the treatment of SSRCs. However, there are no clear indicators for selecting the NOTES approach for patients with SSRCs.
View Article and Find Full Text PDFDifferential diagnosis of iron deficiency anemia from aplastic anemia using machine learning and explainable Artificial Intelligence utilizing blood attributes.
Sci Rep
January 2025
L&T Technology Services Limited, Mysore, Karnataka, India.
As per world health organization, Anemia is a most prevalent blood disorder all over the world. Reduced number of Red Blood Cells or decrease in the number of healthy red blood cells is considered as Anemia. This condition also leads to the decrease in the oxygen carrying capacity of the blood.
View Article and Find Full Text PDFMonitoring of the trough concentration of valproic acid in pediatric epilepsy patients: a machine learning-based ensemble model.
Front Pharmacol
December 2024
Department of Pharmacy, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
Article Synopsis
- This study developed a machine learning ensemble model for monitoring valproic acid (VPA) in pediatric epilepsy patients to improve clinical accuracy in treatment.
- The model utilized data from 252 patients, using various algorithms like Gradient Boosting Regression Trees and Random Forest Regression, achieving high relative accuracy (87.8%) and low error rates.
- Key factors affecting VPA levels included platelet count and daily dose, indicating the model's potential to enhance clinical decision-making in VPA management.
The clinical indexes and immunological status of HIV/AIDS patients undergoing different highly active antiretroviral treatments.
Front Cell Infect Microbiol
January 2025
Yunnan Key Laboratory of Laboratory Medicine, Kunming, China.
Objective: This study aims to investigate the differences of clinical indices in HIV patients between three different first-line antiretroviral treatment strategies in Yunnan Province, China. Furthermore, the hematologic system, liver function, kidney function, blood lipid levels of HIV patients and its association with CD4+ count, CD8+ count, CD4/CD8 ratio and antiretroviral treatment were also assessed.
Methods: This retrospective cohort study included 81 participants who underwent highly active antiretroviral treatment from September 2009 to September 2019.
Prediction of prognosis in patients with cerebral contusions based on machine learning.
Sci Rep
December 2024
Department of Neurosurgery, The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), Wuhu city, 241000, Anhui Province, China.
Traumatic brain injury (TBI) is a global issue and a major cause of patient mortality, and cerebral contusions (CCs) is a common primary TBI. The haemorrhagic progression of a contusion (HPC) poses a significant risk to patients' lives, and effectively predicting changes in haematoma volume is an urgent clinical challenge that needs to be addressed. As a branch of artificial intelligence, machine learning (ML) can proficiently handle a wide range of complex data and identify connections between data for tasks such as prediction and decision making.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!