Vancomycin‐induced acute kidney injury in elderly Chinese patients: a single‐centre cross‐sectional study

Pan, Kunming; Wu, Yi; Chen, Can; Chen, Zhangzhang; Xu, Jianan; Cao, Lu; Qian, Xu; Wu, Wei; Dai, Pei-Fang; Li, Xiaoyu; Lv, Qianzhou

doi:10.1111/bcp.13594

Cited by 18 publications

(34 citation statements)

References 32 publications

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“…Our results showed that the incidence of VA-AKI was 14.3%, however, this could be an underestimate as 998 patients were excluded due to insufficient SCr measurements, which is consistent with our previous research ( Pan et al, 2018 ). Therefore, our results may have missed a number of VA-AKI patients.…”

Section: Discussionsupporting

confidence: 92%

“…For instance, vancomycin and piperacillintazobactam are among the most commonly prescribed antibiotics in American hospitals, which are associated with significant increases in the incidence of AKI compared to vancomycin monotherapy or other empirical combinations (Balci et al, 2018;Carreno et al, 2018;Ide et al, 2019;Avedissian et al, 2020;Ciarambino et al, 2020). In contrast, previous studies have shown that, in China, the most common antibiotic combinations with vancomycin are carbapenems (Pan et al, 2017;Pan et al, 2018). Liang et al found that vancomycin nephrotoxicity was significantly correlated with the trough concentration and reported the first cut-point as 13 mg/L for the Chinese population (Liang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

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Vancomycin Associated Acute Kidney Injury: A Longitudinal Study in China

Pan

Chen

et al. 2021

Front. Pharmacol.

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Background: Vancomycin-associated acute kidney injury (VA-AKI) is a recognizable condition with known risk factors. However, the use of vancomycin in clinical practices in China is distinct from other countries. We conducted this longitudinal study to show the characteristics of VA-AKI and how to manage it in clinical practice.Patients and Methods: We included patients admitted to hospital, who received vancomycin therapy between January 1, 2016 and June 2019. VA-AKI was defined as a patient having developed AKI during vancomycin therapy or within 48 h following the withdrawal of vancomycin therapy.Results: A total of 3719 patients from 7058 possible participants were included in the study. 998 patients were excluded because of lacking of serum creatinine measurement. The incidence of VA-AKI was 14.3%. Only 32.3% (963/2990) of recommended patients performed therapeutic drug monitoring of vancomycin. Patients with VA-AKI were more likely to concomitant administration of cephalosporin (OR 1.55, 95% CI 1.08–2.21, p = 0.017), carbapenems (OR 1.46, 95% CI 1.11–1.91, p = 0.006) and piperacillin-tazobactam (OR 3.12, 95% CI 1.50–6.49, p = 0.002). Full renal recovery (OR 0.208, p = 0.005) was independent protective factors for mortality. Compared with acute kidney injury stage 1, AKI stage 2 (OR 2.174, p = 0.005) and AKI stage 3 (OR 2.210, p = 0.005) were independent risk factors for fail to full renal recovery.Conclusion: Lack of a serum creatinine measurement for the diagnosis of AKI and lack of standardization of vancomycin therapeutic drug monitoring should be improved. Patient concomitant with piperacillin-tazobactam are at higher risk. Full renal recovery was associated with a significantly reduced morality.

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Section: Discussionsupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Vancomycin Associated Acute Kidney Injury: A Longitudinal Study in China

Pan

Chen

et al. 2021

Front. Pharmacol.

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“…The incidence of VANT in the general adult patients was 4.7-15.4%, [8][9][10][11] whereas the rate was 15.8-29% in elderly patients. 6,12 With the aging of our society, VANT in elderly patients is worthy of more attention. 12 Previous studies indicate that age, 7 mechanical ventilation, 12 intensive care unit (ICU) admittance, 13 vancomycin trough concentration, 9,14-17 dose, 15 length of therapy, 9,17 infusion method (continuous or intermittent infusions), 18,19 cirrhosis, 14 hypertension, 20 hyperuricemia, 12 shock, 6 heart failure, 6 concomitant medications, vasopressor drugs, 16,17 aminoglycosides, 9,21 contrast agents, 22,23 piperacillin/tazobactam (PTZ), 24,25 furosemide, 3,11 amphotericin B, 26 and the Acute Physiology and Chronic Health Evaluation II (APACHE-II) 21,27 are risk factors associated with VANT.…”

mentioning

confidence: 99%

Development and Validation of a Risk Prediction Model of Vancomycin‐Associated Nephrotoxicity in Elderly Patients: A Pilot Study

Pan

Wen

et al. 2020

Clinical Translational Sci

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This exploratory study aimed to develop a risk prediction model of vancomycin-associated nephrotoxicity (VANT) in elderly patients. Clinical information of elderly patients who received vancomycin therapy from January 2016 to June 2018 was retrieved. A total of 255 patients were included in this study. Univariate analysis and multivariable logistic regression analysis revealed that vancomycin trough concentration ≥ 20 mg/L (odds ratio (OR) = 3.009; 95% confidence interval (CI) 1.345-6.732), surgery (OR = 3.357; 95% CI 1.309-8.605), the Charlson Comorbidities Index ≥ 4 points (OR = 2.604; 95% CI 1.172-5.787), concomitant use of cardiotonic drug (OR = 3.283; 95% CI 1.340-8.042), plasma volume expander (OR = 3.459; 95% CI 1.428-8.382), and piperacillin/tazobactam (OR = 2.547; 95% CI 1.680-6.007) were risk factors for VANT in elderly patients. Furthermore, a VANT risk prediction model was developed, which had good discriminative power and was well-calibrated.Vancomycin is used to treat methicillin-resistant Staphylococcus aureus (MRSA) infections. 1,2 Vancomycinassociated nephrotoxicity (VANT) 3 is a common adverse drug reaction, and is linked to the need for renal replacement therapy, prolonged hospitalization, higher healthcare costs, and increased mortality. 4 Elderly patients are more likely to develop VANT 5-7 due to multiple illnesses and complicated medications. The incidence of VANT in the general adult patients was 4.7-15.4%, [8][9][10][11] whereas the rate was 15.8-29% in elderly patients. 6,12 With the aging of our society, VANT in elderly patients is worthy of more attention. 12 Previous studies indicate that age, 7 mechanical ventilation, 12 intensive care unit (ICU) admittance, 13 vancomycin trough concentration, 9,14-17 dose, 15 length of therapy, 9,17 infusion method (continuous or intermittent infusions), 18,19 cirrhosis, 14 hypertension, 20 hyperuricemia, 12 shock, 6 heart failure, 6 concomitant medications, vasopressor drugs, 16,17 aminoglycosides, 9,21 contrast agents, 22,23 piperacillin/tazobactam (PTZ), 24,25 furosemide, 3,11 amphotericin B, 26 and the Acute Physiology and Chronic Health Evaluation II (APACHE-II) 21,27 are risk factors associated with VANT. However, only two studies reported VANT risk factors in elderly patients. 6,12 Additionally, there are few reports on developing risk prediction models of VANT in elderly patients. Therefore, we attempted to explore clinical predictors of VANT to construct a risk prediction model of VANT in elderly patients.

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“…Interestingly, as seen in this study, certain biochemical markers were inferred to be important in the established vancomycin dose prediction model, including UA, PLT, TP, CRP, WBC, RBC, HCT, and Hb. Among them, UA was considered as a marker of kidney disease [33], and hyperuricemia was revealed as an independent risk factor for vancomycininduced acute kidney injury [34]. Thrombocytopenia can be caused by vancomycin-dependent antibodies produced by immune mechanisms [35].…”

Section: Discussionmentioning

confidence: 99%

Prediction of vancomycin dose on high-dimensional data using machine learning techniques

Huang

Yu²,

Wei

et al. 2021

Expert Review of Clinical Pharmacology

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Objectives: Despite therapeutic vancomycin is regularly monitored, its dose requirements vary considerably between individuals. Various innovative vancomycin dosing strategies have been developed for dose optimization; however, the utilization of individual factors and extensibility is insufficient. We aimed to develop an optimal dosing algorithm for vancomycin based on the high-dimensional data using the proposed variable engineering and machine-learning methods. Methods: This study proposed a variable engineering process that automatically generates secondorder variable interactions. We performed an initial examination of independent variables and interactive variables using eXtreme Gradient Boosting. The vancomycin dose prediction model was established based on the derived variables. Results: Based on the evaluation of the model performance in the validation cohort, our algorithm accounted for 67.5% of variations in the vancomycin doses. Subgroup analysis showed better performance in patients with medium and high body weight (with the ideal predictive percentage of 72.7% and 73.7%), and low and medium levels of serum creatinine (with the ideal predictive percentage of 77.8% and 73.1%) than in other groups. Conclusion:The new vancomycin dose prediction model is potentially useful for patients whose population profiles are similar to those of our patients and yielded desired reference of clinical indicators with specific breakpoints.

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Vancomycin‐induced acute kidney injury in elderly Chinese patients: a single‐centre cross‐sectional study

Cited by 18 publications

References 32 publications

Vancomycin Associated Acute Kidney Injury: A Longitudinal Study in China

Vancomycin Associated Acute Kidney Injury: A Longitudinal Study in China

Development and Validation of a Risk Prediction Model of Vancomycin‐Associated Nephrotoxicity in Elderly Patients: A Pilot Study

Prediction of vancomycin dose on high-dimensional data using machine learning techniques

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