• Luisa Sorlí, Sonia Luque, Santiago Grau, Núria Berenguer, Concepción Segura, María Milagro Montero, Francisco Alvarez-Lerma, Hernando Knobel, Natividad Benito, and Juan P Horcajada.
• Infectious Diseases Service, Parc de Salut Mar, Passeig Marítim 25-29, E-08003 Barcelona, Spain. LSorli@parcdesalutmar.cat.
• Bmc Infect Dis. 2013 Jan 1;13:380.

BackgroundData regarding the most efficacious and least toxic schedules for the use of colistin are scarce. The aim of this study was to determine the incidence and the potential risk factors of colistin-associated nephrotoxicity including colistin plasma levels.MethodsA prospective observational cohort study was conducted for over one year in patients receiving intravenous colistin methanesulfonate sodium (CMS). Blood samples for colistin plasma levels were collected immediately before (Cmin) and 30 minutes after CMS infusion (Cmax). Renal function was assessed at baseline, on day 7 and at the end of treatment (EOT). Severity of acute kidney injury (AKI) was defined by the RIFLE (risk, injury, failure, loss, and end-stage kidney disease) criteria.ResultsOne hundred and two patients met the inclusion criteria. AKI related to CMS treatment on day 7 and at the end of treatment (EOT) was observed in 26 (25.5%) and 50 (49.0%) patients, respectively. At day 7, Cmin (OR, 4.63 [2.33-9.20]; P < 0.001) was the only independent predictor of AKI. At EOT, the Charlson score (OR 1.26 [1.01-1.57]; P = 0.036), Cmin (OR 2.14 [1.33-3.42]; P = 0.002), and concomitant treatment with ≥ 2 nephrotoxic drugs (OR 2.61 [1.0-6.8]; P = 0.049) were independent risk factors for AKI. When Cmin was evaluated as a categorical variable, the breakpoints that better predicted AKI were 3.33 mg/L (P < 0.001) on day 7 and 2.42 mg/L (P < 0.001) at EOT.ConclusionsWhen using the RIFLE criteria, colistin-related nephrotoxicity is observed in a high percentage of patients. Cmin levels are predictive of AKI. Patients who receive intravenous colistin should be closely monitored and Cmin might be a new useful tool to predict AKI.

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