Risk prediction models for acute kidney injury following major noncardiac surgery: systematic review

Wilson, Todd; Quan, Samuel; Cheema, Kim; Zarnke, Kelly B.; Quinn, Rob; Koning, Lawrence de; Dixon, Elijah; Pannu, Neesh; James, Matthew T.

doi:10.1093/ndt/gfv415

Cited by 56 publications

(56 citation statements)

References 26 publications

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“…In this study, among the patients who survived to hospital discharge after major surgery, 46.8% patients without prior CKD experienced AKI, whereas significantly higher percentage (67.0%) of patients with prior CKD did. In addition, Wilson et al conducted a systematic review of risk prediction models for AKI following major non-cardiac surgery and found that renal insufficiency was an important risk factor of AKI occurrence 25 . In animal models, there is evidence that ischemic AKI is significantly more severe in diabetic mice than in non-diabetic mice 26, 27 .…”

Section: The Aki-ckd Connectionmentioning

confidence: 99%

AKI on CKD: heightened injury, suppressed repair, and the underlying mechanisms

Wei

Liu

et al. 2017

Kidney International

311

222

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Acute kidney injury (AKI) and chronic kidney disease (CKD) are inter-connected. While AKI-to-CKD transition has been intensively studied, the information of AKI on CKD is very limited. Nonetheless, AKI, when occurring in CKD patients, is known to be more severe and difficult to recover. CKD is associated with significant changes in cell signaling in kidney tissues, including the activation of TGF-β, p53, HIF, and major developmental pathways. At the cellular level, CKD is characterized by mitochondrial dysfunction, oxidative stress, and aberrant autophagy. At the tissue level, CKD is characterized by chronic inflammation and vascular dysfunction. These pathological changes may contribute to the heightened sensitivity of, and non-recovery from, AKI in CKD patients.

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Section: The Aki-ckd Connectionmentioning

confidence: 99%

AKI on CKD: heightened injury, suppressed repair, and the underlying mechanisms

Wei

Liu

et al. 2017

Kidney International

311

222

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“…Prediction models exist for a wide variety of health outcomes, such as cardiovascular disease [5], lung cancer [6], acute kidney injury [7], and infertility treatment success [8]. There is an overwhelming number of models for the prediction of specific outcomes, with, for example, more than 350 prediction models developed for cardiovascular disease in the general population [5].…”

Section: Introductionmentioning

confidence: 99%

Prediction Models for Early Childhood Obesity: Applicability and Existing Issues

et al. 2018

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Statistical models have been developed for the prediction or diagnosis of a wide range of outcomes. However, to our knowledge, only 7 published studies have reported models to specifically predict overweight and/or obesity in early childhood. These models were developed using known risk factors and vary greatly in terms of their discrimination and predictive capacities. There are currently no established guidelines on what constitutes an acceptable level of risk (i.e., risk threshold) for childhood obesity prediction models, but these should be set following consideration of the consequences of false-positive and false-negative predictions, as well as any relevant clinical guidelines. To date, no studies have examined the impact of using early childhood obesity prediction models as intervention tools. While these are potentially valuable to inform targeted interventions, the heterogeneity of the existing models and the lack of consensus on adequate thresholds limit their usefulness in practice.

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“…Several risk stratification systems exist for cardiac surgery patients but the best validated scores predict severe AKI requiring dialysis [14,15] and new studies are needed to validate scores to predict less severe AKI after cardiac surgery [16]. On the other side, non-cardiac surgery has received much less attention and most of the predictive scores predict AKI requiring renal replacement therapy (RRT) following liver transplantation or liver surgery [17]. Kheterpal et al [18] developed a system for non-cardiac surgery for predicting AKI.…”

Section: Clinical Prediction Scoresmentioning

confidence: 99%

Perioperative Acute Kidney Injury: Prevention, Early Recognition, and Supportive Measures

Romagnoli

Ricci

Ronco

2018

Nephron

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Background: Acute kidney injury (AKI) is a frequent complication of both cardiac and major non-cardiac surgery. AKI is independently associated with morbidity, mortality, and long-term adverse events including chronic kidney disease in postsurgical patients. Since specific treatment options for kidney failure are very limited, early identification, diagnosis, and renal support strategies are key steps to improve patients’ outcome. Summary: According to current Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, AKI diagnosis is based on 2 functional markers, serum creatinine increase and urine output decrease, that are not renal-specific and have important limitations. However, preoperative risk stratification for postoperative AKI and/or early diagnosis after surgery could be the best way to apply preventive or timely supportive therapeutic measures. Clinical prediction scores, renal functional reserve assessment, and new biomarkers of kidney stress (suppression of tumorigenicity-2, insulin-like growth factor binding protein-7, tissue inhibitor metalloproteinase-2) may help the clinicians to identify patients at risk of AKI and that could benefit from the application of nephroprotective bundles suggested by the KDIGO guidelines. In severe AKI patients with oligoanuria and fluid accumulation, renal replacement therapy is the only supportive measure even if mode and timing remain open to investigation. Key messages: Perioperative AKI is an important and underdiagnosed complication. Identifying patients at high risk of AKI and diagnosing AKI early are major goals. Preventive interventions are mainly based on the KDIGO guidelines and bundles. Furthermore, a personalized multidisciplinary approach should always be considered to minimize the progression of disease and the complications related to kidney damage.

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Risk prediction models for acute kidney injury following major noncardiac surgery: systematic review

Cited by 56 publications

References 26 publications

AKI on CKD: heightened injury, suppressed repair, and the underlying mechanisms

AKI on CKD: heightened injury, suppressed repair, and the underlying mechanisms

Prediction Models for Early Childhood Obesity: Applicability and Existing Issues

Perioperative Acute Kidney Injury: Prevention, Early Recognition, and Supportive Measures

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