Acute Kidney Injury in the Surgical Patient

Hobson, Charles; Singhania, Girish; Bïhorac, Azra

doi:10.1016/j.ccc.2015.06.007

Cited by 45 publications

(35 citation statements)

References 156 publications

(142 reference statements)

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“…Numerous risk factors have been identified for the development of pediatric CS-AKI, in the pre-operative, intra-operative, and post-operative phases [31,32]. The most consistently identified independent risk factors for pediatric CS-AKI include younger age, longer duration of CPB, higher surgical complexity (as reflected by the risk-adjusted classification for congenital heart surgery [RACHS-1] score), preoperative ventilator support, and lower preoperative serum creatinine [1,12,15].…”

Section: Incidence and Etiology Of Cardiac Surgery-associated Acutmentioning

confidence: 99%

Early detection of acute kidney injury after pediatric cardiac surgery

Jefferies

Devarajan

2016

Progress in Pediatric Cardiology

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Acute kidney injury (AKI) is increasingly recognized as a common problem in children undergoing cardiac surgery, with well documented increases in morbidity and mortality in both the short and the long term. Traditional approaches to the identification of AKI such as changes in serum creatinine have revealed a large incidence in this population with significant negative impact on clinical outcomes. However, the traditional diagnostic approaches to AKI diagnosis have inherent limitations that may lead to under-diagnosis of this pathologic process. There is a dearth of randomized controlled trials for the prevention and treatment of AKI associated with cardiac surgery, at least in part due to the paucity of early predictive biomarkers. Novel non-invasive biomarkers have ushered in a new era that allows for earlier detection of AKI. With these new diagnostic tools, a more consistent approach can be employed across centers that may facilitate a more accurate representation of the actual prevalence of AKI and more importantly, clinical investigation that may minimize the occurrence of AKI following pediatric cardiac surgery. A thoughtful management approach is necessary to mitigate the effects of AKI after cardiac surgery, which is best accomplished in close collaboration with pediatric nephrologists. Long-term surveillance for improvement in kidney function and potential development of chronic kidney disease should also be a part of the comprehensive management strategy.

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Section: Incidence and Etiology Of Cardiac Surgery-associated Acutmentioning

confidence: 99%

Early detection of acute kidney injury after pediatric cardiac surgery

Jefferies

Devarajan

2016

Progress in Pediatric Cardiology

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“…Postoperative complications increase odds of 30-day mortality, lead to higher readmission rates, and greater resource utilization. [1][2][3][4][5][6][7][8] Accurate prediction of postoperative complications for individual patients is increasingly complex due to the need for rapid decisionmaking coupled with the constant influx of dynamic physiologic data in electronic health records (EHR).…”

Section: Introductionmentioning

confidence: 99%

Comparing clinical judgment with the MySurgeryRisk algorithm for preoperative risk assessment: A pilot usability study

Brennan

Puri

Ozrazgat‐Baslanti

et al. 2019

Surgery

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Background: Major postoperative complications are associated with increased short and longterm mortality, increased healthcare cost, and adverse long-term consequences. The large amount of data contained in the electronic health record (EHR) creates barriers for physicians to recognize patients most at risk. We hypothesize, if presented in an optimal format, information from data-driven predictive risk algorithms for postoperative complications can improve physician risk assessment.Methods: Prospective, non-randomized, interventional pilot study of twenty perioperative physicians at a quarterly academic medical center. Using 150 clinical cases we compared physicians' risk assessment before and after interaction with MySurgeryRisk, a validated machine-learning algorithm predicting preoperative risk for six major postoperative complications using EHR data. Results:The area under the curve (AUC) of MySurgeryRisk algorithm ranged between 0.73 and 0.85 and was significantly higher than physicians' risk assessments (AUC between 0.47 and 0.69) for all postoperative complications except cardiovascular complications. The AUC for repeated physician's risk assessment improved by 2% to 5% for all complications with the exception of thirty-day mortality. Physicians' risk assessment for acute kidney injury and intensive care unit admission longer than 48 hours significantly improved after knowledge exchange, resulting in net reclassification improvement of 12.4% and 16%, respectively. Conclusions:The validated MySurgeryRisk algorithm predicted postoperative complications with equal or higher accuracy than pilot cohort of physicians using available clinical preoperative data. The interaction with algorithm significantly improved physicians' risk assessment.

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“…correctly identify that the preoperative risk is modified by the response to the events experienced during surgery. The intraoperative haemodynamic and anaesthetic management can either exacerbate or ameliorate surgery‐related stress. Without dynamic adjustment of the risk at the end of surgery, the opportunity to initiate preventative therapies for high‐risk patients, such as triage to intensive care unit for early haemodynamic optimisation, sepsis protocol, non‐opioid analgesia and early mobilisation, may be missed.…”

Section: Disclosure Of Interestsmentioning

confidence: 99%