Dataset Information

Polymyxin Acute Kidney Injury: Dosing and Other Strategies to Reduce Toxicity.

ABSTRACT: Polymyxins are valuable antimicrobials for the management of multidrug-resistant Gram-negative bacteria; however, nephrotoxicity associated with these drugs is a very common side effect that occurs during treatment. This article briefly reviews nephrotoxic mechanisms and risk factors for polymyxin-associated acute kidney injury (AKI) and discusses dosing strategies that may mitigate kidney damage without compromising antimicrobial activity. Polymyxins have a very narrow therapeutic window and patients requiring treatment with these drugs are frequently severely ill and have multiple comorbidities, which increases the risk of AKI. Notably, there is a significant overlap between therapeutic and toxic plasma polymyxin concentrations that substantially complicates dose selection. Recent dosing protocols for both colistin and polymyxin B have been developed and may help fine tune dose adjustment of these antibiotics. Minimizing exposure to modifiable risk factors, such as other nephrotoxic agents, is strongly recommended. The dose should be carefully selected, particularly in high-risk patients. The administration of oxidative stress-reducing drugs is a promising strategy to ameliorate polymyxin-associated AKI, but still requires support from clinical studies.

SUBMITTER: Nation RL

PROVIDER: S-EPMC6466603 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Polymyxin Acute Kidney Injury: Dosing and Other Strategies to Reduce Toxicity.

Nation Roger L RL Rigatto Maria Helena P MHP Falci Diego R DR Zavascki Alexandre P AP

Antibiotics (Basel, Switzerland) 20190314 1

Polymyxins are valuable antimicrobials for the management of multidrug-resistant Gram-negative bacteria; however, nephrotoxicity associated with these drugs is a very common side effect that occurs during treatment. This article briefly reviews nephrotoxic mechanisms and risk factors for polymyxin-associated acute kidney injury (AKI) and discusses dosing strategies that may mitigate kidney damage without compromising antimicrobial activity. Polymyxins have a very narrow therapeutic window and pa ...[more]

PMID: 30875778

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Project description:BackgroundPostoperative acute kidney injury is common after major vascular surgery and is associated with increased morbidity, mortality, and cost. High-performance risk stratification using a machine learning model can inform strategies that mitigate harm and optimize resource use. It is hypothesized that incorporating intraoperative data would improve machine learning model accuracy, discrimination, and precision in predicting acute kidney injury among patients undergoing major vascular surgery.MethodsA single-center retrospective cohort of 1,531 adult patients who underwent nonemergency major vascular surgery, including open aortic, endovascular aortic, and lower extremity bypass procedures, was evaluated. The validated, automated MySurgeryRisk analytics platform used electronic health record data to forecast patient-level probabilistic risk scores for postoperative acute kidney injury using random forest models with preoperative data alone and perioperative data (preoperative plus intraoperative). The MySurgeryRisk predictions were compared with each other as well as with the American Society of Anesthesiologists physical status classification.ResultsMachine learning models using perioperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification (accuracy: 0.70 vs 0.64 vs 0.62, area under the receiver operating characteristics curve: 0.77 vs 0.68 vs 0.61, area under the precision-recall curve: 0.70 vs 0.58 vs 0.48).ConclusionIn predicting acute kidney injury after major vascular surgery, machine learning approaches that incorporate dynamic intraoperative data had greater accuracy, discrimination, and precision than models using either preoperative data alone or the American Society of Anesthesiologists physical status classification. Machine learning methods have the potential for real-time identification of high-risk patients who may benefit from personalized risk-reduction strategies.

Dataset Information

Polymyxin Acute Kidney Injury: Dosing and Other Strategies to Reduce Toxicity.

Publications

Polymyxin Acute Kidney Injury: Dosing and Other Strategies to Reduce Toxicity.

Similar Datasets

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