Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Feb 21:15:1292828.
doi: 10.3389/fphar.2024.1292828. eCollection 2024.

Prediction of risk factors for linezolid-induced thrombocytopenia based on neural network model

Xian Zhao  1 , Qin Peng  2 , Dongmei Hu  1 , Weiwei Li  1 , Qing Ji  1 , Qianqian Dong  1 , Luguang Huang  3 , Miyang Piao  1 , Yi Ding  1 , Jingwen Wang  1
Affiliations

Prediction of risk factors for linezolid-induced thrombocytopenia based on neural network model

Xian Zhao et al. Front Pharmacol. .

Abstract

Background: Based on real-world medical data, the artificial neural network model was used to predict the risk factors of linezolid-induced thrombocytopenia to provide a reference for better clinical use of this drug and achieve the timely prevention of adverse reactions. Methods: The artificial neural network algorithm was used to construct the prediction model of the risk factors of linezolid-induced thrombocytopenia and further evaluate the effectiveness of the artificial neural network model compared with the traditional Logistic regression model. Results: A total of 1,837 patients receiving linezolid treatment in a hospital in Xi 'an, Shaanxi Province from 1 January 2011 to 1 January 2021 were recruited. According to the exclusion criteria, 1,273 cases that did not meet the requirements of the study were excluded. A total of 564 valid cases were included in the study, with 89 (15.78%) having thrombocytopenia. The prediction accuracy of the artificial neural network model was 96.32%, and the AUROC was 0.944, which was significantly higher than that of the Logistic regression model, which was 86.14%, and the AUROC was 0.796. In the artificial neural network model, urea, platelet baseline value and serum albumin were among the top three important risk factors. Conclusion: The predictive performance of the artificial neural network model is better than that of the traditional Logistic regression model, and it can well predict the risk factors of linezolid-induced thrombocytopenia.

Keywords: ADR; ANN; linezolid; logistic regression; risk factor; thrombocytopenia.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Flowchart of studies predicting risk factors for linezolid-induced thrombocytopenia.
FIGURE 2
FIGURE 2
Structural diagram of ANN model for predicting the risk of thrombocytopenia caused by linezolid.
FIGURE 3
FIGURE 3
Training loss and AUC on validation dataset of ANN model during training process.
FIGURE 4
FIGURE 4
The ROC curves and AUCs of ANN and Logistic models on test dataset.
FIGURE 5
FIGURE 5
The importance and ranking diagram of potential risk factors in ANN model.
See this image and copyright information in PMC

References

    1. An R. F., Wang L. L. (2013). Linezolid-induced thrombocytopenia. Chin. J. New Drugs 22 (12), 1469–1472.
    1. Bernstein W. B., Trotta R. F., Rector J. T., Tjaden J. A., Barile A. J. (2003). Mechanisms for linezolid-induced anemia and thrombocytopenia. Ann. Pharmacother. 37 (4), 517–520. 10.1345/aph.1C361 - DOI - PubMed
    1. Cattaneo D., Marriott D. J., Gervasoni C. (2023). Hematological toxicities associated with linezolid therapy in adults: key findings and clinical considerations. Expert Rev. Clin. Pharmacol. 16 (3), 219–230. 10.1080/17512433.2023.2181160 - DOI - PubMed
    1. Cazavet J., Bounes F. V., Ruiz S., Seguin T., Crognier L., Rouget A., et al. (2020). Risk factor analysis for linezolid-associated thrombocytopenia in critically ill patients. Eur. J. Clin. Microbiol. Infect. Dis. 39 (3), 527–538. 10.1007/s10096-019-03754-1 - DOI - PubMed
    1. Chen C., Guo D. H., Cao X., Cai Y., Xu Y., Zhu M., et al. (2012). Risk factors for thrombocytopenia in adult Chinese patients receiving linezolid therapy. Curr. Ther. Res. Clin. Exp. 73 (6), 195–206. 10.1016/j.curtheres.2012.07.002 - DOI - PMC - PubMed