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Predicting the risk of nephrotoxicity in patients receiving colistimethate sodium: a multicentre, retrospective,
Kady Phe1, Ryan K Shields2, Frank P Tverdek3
1Department of Pharmacy, Baylor St Luke's Medical Center, Houston, TX, USA.
Objectives:
With increasing rates of infections caused by MDR Gram-negative organisms, clinicians resort to older agents such as colistimethate sodium (CMS) despite a significant risk of nephrotoxicity. Several risk factors for CMS-associated nephrotoxicity have been reported, but they have yet to be validated. We compared the performance of published mathematical models in predicting the risk of CMS-associated nephrotoxicity.
Methods:
In a multicentre, retrospective, cohort study, adult patients (≥18 years of age) were evaluated from five large academic medical centres in the USA. Patients with normal renal function (baseline serum creatinine ≤1.5 mg/dL) who received intravenous CMS for ≥72 h were followed for up to 30 days. The development of nephrotoxicity was as defined by the RIFLE criteria. Each published model was conditioned using patient-specific variables to predict the risk of nephrotoxicity. The predictive performance of the models was evaluated using the observed-to-expected (O/E) ratio. The most significant cut-off threshold for stratifying patients into high and low risk of nephrotoxicity was identified using classification and regression tree analysis.
Results:
A total of 106 patients were examined (mean age 53.3 ± 14.9 years, 66% male); the overall observed nephrotoxicity rate was 52.8%. We identified a simple model demonstrating reasonable overall nephrotoxicity risk assessment [O/E ratio of 1.07 (95% CI = 0.81-1.39)] and high sensitivity (92.9%) in predicting nephrotoxicity development in patients on CMS therapy.
Conclusions:
We identified a model that could be incorporated into patient management strategies to reduce the risk of nephrotoxicity in patients requiring CMS therapy.
Insights
A validated model can predict colistimethate sodium (CMS) nephrotoxicity risk in patients. This aids in managing patients requiring CMS therapy and reduces kidney damage risk.
Area of Science:
- Pharmacology
- Nephrology
- Infectious Diseases
Background:
- Rising infections from multidrug-resistant (MDR) Gram-negative organisms necessitate using older antibiotics like colistimethate sodium (CMS).
- CMS use carries a significant risk of nephrotoxicity, a serious side effect impacting kidney function.
- Existing risk factors for CMS-associated nephrotoxicity lack validation, creating a need for reliable predictive tools.
Purpose of the Study:
- To evaluate and compare the performance of existing mathematical models in predicting the risk of CMS-induced nephrotoxicity.
- To identify a validated model for assessing nephrotoxicity risk in patients treated with CMS.
- To inform clinical practice and patient management strategies for CMS therapy.
Main Methods:
- A multicentre, retrospective cohort study involving adult patients from five US academic medical centres.
- Patients with normal baseline renal function receiving intravenous CMS for at least 72 hours were followed for 30 days.
- Nephrotoxicity was defined by RIFLE criteria; predictive models were assessed using observed-to-expected (O/E) ratios and classification and regression tree analysis.
Main Results:
- The study included 106 patients (mean age 53.3 years, 66% male) with an overall observed nephrotoxicity rate of 52.8%.
- A simple model demonstrated a reasonable overall nephrotoxicity risk assessment with an O/E ratio of 1.07 (95% CI: 0.81–1.39).
- This model achieved high sensitivity (92.9%) in predicting nephrotoxicity development in patients on CMS therapy.
Conclusions:
- A validated predictive model for CMS-associated nephrotoxicity has been identified.
- This model can be integrated into clinical practice to guide patient management strategies.
- Implementation of this model may help mitigate the risk of kidney damage in patients requiring CMS treatment.
