Analysis of the incidence and associated factors of cyclosporine-associated acute kidney injury in hospitalized patients based on real-world data
- VernacularTitle:基于真实世界数据的住院患者环孢素相关急性肾损伤发生情况及相关因素分析
- Author:
Yaqing DOU
1
;
Jiahui LAO
2
;
Xue WANG
3
;
Yanying SUN
3
;
Xin HUANG
3
;
Hanbing LI
4
;
Xiao LI
3
Author Information
1. College of Pharmaceutical Sciences，Zhejiang University of Technology，Hangzhou 310014，China;Dept. of Clinical Pharmacy，the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital，Jinan 250014，China
2. Healthcare Big Data Center，the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital，Jinan 250014，China
3. Dept. of Clinical Pharmacy，the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital，Jinan 250014，China
4. College of Pharmaceutical Sciences，Zhejiang University of Technology，Hangzhou 310014，China
- Publication Type:Journal Article
- Keywords:
cyclosporine;
acute kidney injury;
risk factors;
predictive model;
real-world study
- From:
China Pharmacy
2026;37(12):1584-1589
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE To analyze the incidence of cyclosporine （CsA）-associated acute kidney injury （AKI） in hospitalized patients， identify influencing factors， and construct a risk prediction model. METHODS A single-center retrospective study was conducted， enrolling clinical data from hospitalized patients treated with CsA at the First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital from January 2018 to July 2024. The patients were classified into AKI group and non-AKI group based on the occurrence of CsA-related AKI. Univariate analysis and multivariate Logistic regression analysis were used to identify independent risk factors for CsA-related AKI， and a risk prediction model was constructed and its performance was evaluated. RESULTS A total of 439 patients were included， of whom 54 developed CsA-related AKI， with an incidence rate of 12.30%. The occurrence of CsA-associated AKI was positively correlated with concurrent bacterial pulmonary infection， cytomegalovirus viremia， respiratory failure， renal insufficiency， gastrointestinal bleeding， and peripheral central venous catheterization （odds ratios of 763.750， 16.944， 41.933， 236.806， 17.537 and 212.789， respectively； P ＜0.05）； while uric acid， prealbumin， and calcium levels were negatively associated with it （odds ratios of 0.983， 0.967 and 0.058， respectively； P ＜0.05）. The prediction model constructed based on the above factors yielded a χ 2 value of 10.254 （ P ＞0.05） in the Hosmer-Lemeshow test. The average area under the curve （AUC） from 10-fold cross-validation was 0.885. The AUC of the receiver operating characteristic curve was 0.883， with a sensitivity of 84.3% and a specificity of 80.4%， respectively， at the optimal cutoff value of 0.1. CONCLUSIONS Six factors， including concurrent bacterial pulmonary infection and cytomegalovirus viremia， are positively associated with the occurrence of CsA-related AKI； while uric acid， prealbumin， and calcium levels are negatively associated. The Logistic regression model constructed based on these factors demonstrates good predictive performance and can assist clinic in conducting early risk assessment and personalized interventions.
