抗菌药物使用密度与肺炎克雷伯菌耐药率的因果关联及药物控制阈值

doi:10.6040/j.issn.1671-7554.0.2024.0164

摘要/Abstract

摘要： 目的探讨抗菌药物使用密度与肺炎克雷伯菌耐药率之间的因果关联,并确定抗菌药物使用密度的控制阈值。方法基于山东大学第二医院2015—2023年抗菌药物使用密度和肺炎克雷伯菌耐药率的数据,采用断点回归分析确定抗菌药物总用药密度对肺炎克雷伯菌耐药率的影响。采用广义加性模型(generalized additive models, GAMs)的非线性时间序列分析方法来评估抗菌药物使用密度与肺炎克雷伯菌耐药率之间的关联,并确定抗菌药物使用密度的控制阈值。P<0.05和调整后R²>0.3为差异有统计学意义。结果在研究期间,所有种类药物使用密度在2015—2019年保持稳定,至2021年呈下降趋势,然后至2023年逐步升高。肺炎克雷伯菌耐药率在2015—2019年呈上升趋势,至2022年逐渐下降,然后至2023年逐步升高。断点回归分析结果显示,抗菌药物总用药密度的增加会导致肺炎克雷伯菌总耐药率升高,差异有统计学意义(β=1.071,P=0.041)。非线性时间序列分析结果显示,肺炎克雷伯菌耐药率与碳青霉烯类、氨基糖苷类、青霉素类和糖肽类药物使用密度显著相关(滞后系数为1~5,P均<0.05,调整后R²为0.589~0.808)。碳青霉烯类、氨基糖苷类和第三代头孢菌素类药物使用的控制阈值分别为5.82、0.06和5.62个DDDs/(100人·d)。结论抗菌药物使用密度的增加会导致肺炎克雷伯菌总耐药率上升;本研究确定了抗菌药物使用密度的阈值,为临床实践中采取更合适的治疗策略和有效控制抗菌药物耐药率提供参考。

关键词: 肺炎克雷伯菌, 抗菌药物使用密度, 断点回归, 非线性时间序列分析, 控制阈值

Abstract: Objective To explore the causal association between antimicrobial use density and Klebsiella pneumoniae drug resistance rate, and to determine the control thresholds of antimicrobial use density. Methods Based on the data of antimicrobial use density and Klebsiella pneumoniae resistance rates in the Second Hospital of Shandong University from 2015 to 2023, the effect of total antimicrobial use density on Klebsiella pneumoniae resistance rate was analyzed by breakpoint regression. Nonlinear time-series analyses using generalized additive models(GAMs)were used to assess the association between antimicrobial use density and Klebsiella pneumoniae resistance rate and to determine the control thresholds for antimicrobial use density. P<0.05 and adjusted R² > 0.3 were considered statistically significant differences. Results During the study period, the density of all types of drug use remained stable from 2015 to 2019, trended downward through 2021, and then gradually increased through 2023. Klebsiella pneumoniae drug resistance rates trended upward from 2015 to 2019, gradually declined through 2022, and then gradually increased through 2023. The results of breakpoint regression analysis showed that an increase in total antimicrobial use density led to an increase in the total resistance rate of Klebsiella pneumoniae, and the difference was statistically significant(β=1.071, P=0.041). Nonlinear time-series analyses showed that the resistance rates of Klebsiella pneumoniae were significantly associated with the density of carbapenems, aminoglycosides, penicillins, and glycopeptides(lag coefficient ranged from 1 to 5, all P<0.05, adjusted R² ranged from 0.589 to 0.808). The control thresholds of carbapenems, aminoglycosides, and third-generation cephalosporins use were 5.82, 0.06 and 5.62 DDDs/(100 patient-days), respectively. Conclusion Increased intensity of antimicrobial drug use leads to an increase in the overall resistance rate of Klebsiella pneumoniae; thresholds of antimicrobial use density were identified in this study to inform more appropriate therapeutic strategies and effective control of antimicrobial resistance rates in clinical practice.

Key words: Klebsiella pneumoniae, Antimicrobial use density, Breakpoint regression, Nonlinear time-series analysis, Control thresholds

中图分类号:

R574

钱凤同,李洪凯,于金龙,薛付忠. 抗菌药物使用密度与肺炎克雷伯菌耐药率的因果关联及药物控制阈值[J]. 山东大学学报 (医学版), 2024, 62(5): 103-111.

QIAN Fengtong, LI Hongkai, YU Jinlong, XUE Fuzhong. Causal correlation between antimicrobial use density and durg resistance rates of Klebsiella pneumoniae and drug control thresholds[J]. Journal of Shandong University (Health Sciences), 2024, 62(5): 103-111.

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