Cargando…

A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study

Background: Linezolid-induced thrombocytopenia (LIT) is the main factor limiting the clinical application of linezolid (LZD). The incidence and risk factors of LIT in neonatal patients were possibly different from other populations based on pathophysiological characteristics. The purpose of this stu...

Descripción completa

Detalles Bibliográficos
Autores principales: Duan, Lufen, Zhou, Qin, Feng, Zongtai, Zhu, Chenqi, Cai, Yan, Wang, Sannan, Zhu, Meiying, Li, Jingjing, Yuan, Yunlong, Liu, Xin, Sun, Jiantong, Yang, Zuming, Tang, Lian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850389/
https://www.ncbi.nlm.nih.gov/pubmed/35185555
http://dx.doi.org/10.3389/fphar.2022.710099
_version_ 1784652587391254528
author Duan, Lufen
Zhou, Qin
Feng, Zongtai
Zhu, Chenqi
Cai, Yan
Wang, Sannan
Zhu, Meiying
Li, Jingjing
Yuan, Yunlong
Liu, Xin
Sun, Jiantong
Yang, Zuming
Tang, Lian
author_facet Duan, Lufen
Zhou, Qin
Feng, Zongtai
Zhu, Chenqi
Cai, Yan
Wang, Sannan
Zhu, Meiying
Li, Jingjing
Yuan, Yunlong
Liu, Xin
Sun, Jiantong
Yang, Zuming
Tang, Lian
author_sort Duan, Lufen
collection PubMed
description Background: Linezolid-induced thrombocytopenia (LIT) is the main factor limiting the clinical application of linezolid (LZD). The incidence and risk factors of LIT in neonatal patients were possibly different from other populations based on pathophysiological characteristics. The purpose of this study was to establish a regression model for predicting LIT in neonatal sepsis patients. Methods: We retrospectively included 518 patients and divided them into the LIT group and the non-LIT group. A logistic regression analysis was used to analyze the factors related to LIT, and a regression model was established. A receiver operating characteristic (ROC) curve was drawn to evaluate the model’s predictive value. We prospectively collected 39 patients’ data to validate the model and evaluate the effect of LZD pharmacokinetics on LIT. Results: Among the 518 patients, 103 patients (19.9%) developed LIT. The Kaplan–Meier plot revealed that the overall median time from the initiation of LZD treatment to the onset of LIT in preterm infants was much shorter when compared with term infants [10 (6, 12) vs. 13 (9.75, 16.5), p = 0.004]. Multiple logistic regression analysis indicated that the independent risk factors of LIT were lower weight at medication, younger gestational ages, late-onset sepsis, necrotizing enterocolitis, mechanical ventilation, longer durations of LZD treatment, and lower baseline of platelet level. We established the above seven-variable prediction regression model and calculated the predictive probability. The ROC curve showed that the predicted probability of combined body weight, gestational age, duration of LZD treatment, and baseline of platelet had better sensitivity (84.4%), specificity (74.2%), and maximum AUC (AUC = 0.873). LIT occurred in 9 out of 39 patients (23.1%), and the accuracies of positive and negative predictions of LIT were 88.9 and 76.7%, respectively. Compared with the non-LIT patients, the LIT patients had higher trough concentration [11.49 (6.86, 15.13) vs. 5.51 (2.80, 11.61) mg/L; p = 0.028] but lower apparent volume of distribution (Vd) [0.778 (0.687, 1.421) vs. 1.322 (1.099, 1.610) L; p = 0.010]. Conclusion: The incidence of LIT was high in neonatal sepsis patients, especially in preterm infants. LIT occurred earlier in preterm infants than in term infants. The regression model of seven variables had a high predictive value for predicting LIT. LIT was correlated with higher trough concentration and lower Vd.
format Online
Article
Text
id pubmed-8850389
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-88503892022-02-18 A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study Duan, Lufen Zhou, Qin Feng, Zongtai Zhu, Chenqi Cai, Yan Wang, Sannan Zhu, Meiying Li, Jingjing Yuan, Yunlong Liu, Xin Sun, Jiantong Yang, Zuming Tang, Lian Front Pharmacol Pharmacology Background: Linezolid-induced thrombocytopenia (LIT) is the main factor limiting the clinical application of linezolid (LZD). The incidence and risk factors of LIT in neonatal patients were possibly different from other populations based on pathophysiological characteristics. The purpose of this study was to establish a regression model for predicting LIT in neonatal sepsis patients. Methods: We retrospectively included 518 patients and divided them into the LIT group and the non-LIT group. A logistic regression analysis was used to analyze the factors related to LIT, and a regression model was established. A receiver operating characteristic (ROC) curve was drawn to evaluate the model’s predictive value. We prospectively collected 39 patients’ data to validate the model and evaluate the effect of LZD pharmacokinetics on LIT. Results: Among the 518 patients, 103 patients (19.9%) developed LIT. The Kaplan–Meier plot revealed that the overall median time from the initiation of LZD treatment to the onset of LIT in preterm infants was much shorter when compared with term infants [10 (6, 12) vs. 13 (9.75, 16.5), p = 0.004]. Multiple logistic regression analysis indicated that the independent risk factors of LIT were lower weight at medication, younger gestational ages, late-onset sepsis, necrotizing enterocolitis, mechanical ventilation, longer durations of LZD treatment, and lower baseline of platelet level. We established the above seven-variable prediction regression model and calculated the predictive probability. The ROC curve showed that the predicted probability of combined body weight, gestational age, duration of LZD treatment, and baseline of platelet had better sensitivity (84.4%), specificity (74.2%), and maximum AUC (AUC = 0.873). LIT occurred in 9 out of 39 patients (23.1%), and the accuracies of positive and negative predictions of LIT were 88.9 and 76.7%, respectively. Compared with the non-LIT patients, the LIT patients had higher trough concentration [11.49 (6.86, 15.13) vs. 5.51 (2.80, 11.61) mg/L; p = 0.028] but lower apparent volume of distribution (Vd) [0.778 (0.687, 1.421) vs. 1.322 (1.099, 1.610) L; p = 0.010]. Conclusion: The incidence of LIT was high in neonatal sepsis patients, especially in preterm infants. LIT occurred earlier in preterm infants than in term infants. The regression model of seven variables had a high predictive value for predicting LIT. LIT was correlated with higher trough concentration and lower Vd. Frontiers Media S.A. 2022-02-03 /pmc/articles/PMC8850389/ /pubmed/35185555 http://dx.doi.org/10.3389/fphar.2022.710099 Text en Copyright © 2022 Duan, Zhou, Feng, Zhu, Cai, Wang, Zhu, Li, Yuan, Liu, Sun, Yang and Tang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pharmacology
Duan, Lufen
Zhou, Qin
Feng, Zongtai
Zhu, Chenqi
Cai, Yan
Wang, Sannan
Zhu, Meiying
Li, Jingjing
Yuan, Yunlong
Liu, Xin
Sun, Jiantong
Yang, Zuming
Tang, Lian
A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study
title A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study
title_full A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study
title_fullStr A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study
title_full_unstemmed A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study
title_short A Regression Model to Predict Linezolid Induced Thrombocytopenia in Neonatal Sepsis Patients: A Ten-Year Retrospective Cohort Study
title_sort regression model to predict linezolid induced thrombocytopenia in neonatal sepsis patients: a ten-year retrospective cohort study
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8850389/
https://www.ncbi.nlm.nih.gov/pubmed/35185555
http://dx.doi.org/10.3389/fphar.2022.710099
work_keys_str_mv AT duanlufen aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT zhouqin aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT fengzongtai aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT zhuchenqi aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT caiyan aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT wangsannan aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT zhumeiying aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT lijingjing aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT yuanyunlong aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT liuxin aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT sunjiantong aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT yangzuming aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT tanglian aregressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT duanlufen regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT zhouqin regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT fengzongtai regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT zhuchenqi regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT caiyan regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT wangsannan regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT zhumeiying regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT lijingjing regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT yuanyunlong regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT liuxin regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT sunjiantong regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT yangzuming regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy
AT tanglian regressionmodeltopredictlinezolidinducedthrombocytopeniainneonatalsepsispatientsatenyearretrospectivecohortstudy