Development and validation of a risk prediction model for linezolid-induced anemia in elderly patients: a retrospective cohort study

• Published in: Therapeutic advances in drug safety Vol. 15; p. 20420986241279128
• Main Authors: Ma, Hongling, Gong, Zhaotang, Wu, Rihan, SiRi, GuLeng
• Format: Journal Article
• Language: English
• Published: England SAGE Publications 01.01.2024; SAGE Publishing
• Subjects: Original Research; rational use; linezolid; MIMIC-IV; clinical prediction model; anemia
• ISSN: 2042-0986; 2042-0994
• DOI: 10.1177/20420986241279128

Linezolid-induced anemia (LI-AN) is a severe adverse reaction, but risk factors of the LI-AN for elderly patients have not been established. The objective of this study was to develop a nomogram capable of predicting LI-AN in elderly patients. This is a retrospective study to develop and validate a nomogram for anemia prediction in elderly patients treated with linezolid. We retrospectively screened elderly patients treated with linezolid at Inner Mongolia People's Hospital from January 2020 to December 2023 and validated our findings using the MIMIC-IV 2.2 database. Anemia was defined as hemoglobin reduction to 75% of baseline value. Univariate and multivariable logistic regression models were used to identify predictors and construct the nomogram, which was evaluated using receiver operating characteristic (ROC) curve analysis, calibration plot, and decision curve analysis. A total of 231 patients were enrolled in this study. The training set comprised 151 individuals, and anemia occurred in 28 cases (18.54%). In the external validation set of 80 individuals, 26 (32.5%) were diagnosed with anemia. The predictors included duration of linezolid therapy, patient estimated glomerular filtration rate value, and sequential organ failure assessment score ⩾2. The ROC curve for the training set was 0.830 (95% CI: 0.750-0.910), while a similar ROC curve of 0.743 (95% CI: 0.621-0.865) was obtained for the validation set. The calibration curve demonstrated good correlation between predicted and observed results, indicating that this study effectively predicts risk factors associated with LI-AN in elderly patients. The developed prediction model can provide valuable guidance for clinicians to prevent anemia and facilitate rational linezolid use in elderly patients.