A novel risk assessment model of contrast‐induced nephropathy after percutaneous coronary intervention in patients with diabetes

Yao, Zhifeng; Shen, Hong; Tang, Min; Yan, Yan; Ge, Junbo

doi:10.1111/bcpt.13501

Cited by 15 publications

(24 citation statements)

References 35 publications

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“…Moreover, the worse outcomes of DM patients with ACS could be mediated by the increased risk for AKI hence further emphasizing the great importance of preventive measures for AKI in this group of patients. The independent predictors of AKI in the current study are overall consistent with previously reported risk scores, with the most prominent parameters being CKD, older age and CHF [10,12,28].…”

Section: Discussionsupporting

confidence: 89%

“…Acute kidney injury (AKI) is a common complication in patients presenting with acute coronary syndrome (ACS), particularly following percutaneous coronary intervention (PCI) [5][6][7][8][9]. Furthermore, when AKI occurs in patients with ACS, it is associated with significantly worse short-and long-term outcomes that include increased risk for renal replacement therapy, prolonged hospitalization, greater mortality and economic burden [5][6][7][8][9][10]. Patients with DM are considered to be at increased risk for AKI in the setting of ACS and PCI [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, when AKI occurs in patients with ACS, it is associated with significantly worse short-and long-term outcomes that include increased risk for renal replacement therapy, prolonged hospitalization, greater mortality and economic burden [5][6][7][8][9][10]. Patients with DM are considered to be at increased risk for AKI in the setting of ACS and PCI [10][11][12][13]. Moreover, the treatment for AKI in this scenario is rather preventive and consists mostly of supportive care or hemodialysis.…”

Section: Introductionmentioning

confidence: 99%

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Acute Kidney Injury Following Admission with Acute Coronary Syndrome: The Role of Diabetes Mellitus

Shiyovich

Skalsky

Steinmetz

et al. 2021

JCM

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Purpose: To evaluate the role of diabetes mellitus in the incidence, risk factors, and outcomes of AKI (acute kidney injury) in patients admitted with ACS (acute coronary syndrome). Methods: We performed a comparative evaluation of ACS patients with vs. without DM who developed AKI enrolled in the biennial ACS Israeli Surveys (ACSIS) between 2000 and 2018. AKI was defined as an absolute increase in serum creatinine (³0.5 mg/dL) or above 1.5 mg/dL or new renal replacement therapy upon admission with ACS. Outcomes included 30-day major adverse cardiovascular events (MACE) and 1-year all-cause mortality. Results: The current study included a total of 16,879 patients, median age 64 (IQR 54–74), 77% males, 36% with DM. The incidence of AKI was significantly higher among patients with vs. without DM (8.4% vs. 4.7%, p < 0.001). The rates of 30-day MACE (40.8% vs. 13.4%, p < 0.001) and 1-year mortality (43.7% vs. 10%, p < 0.001) were significantly greater among diabetic patients who developed vs. those who did not develop AKI respectively, yet very similar among patients that developed AKI with vs. without DM (30-day MACE 40.8% vs. 40.3%, p = 0.9 1-year mortality 43.7 vs. 44.8%, p = 0.8, respectively). Multivariate analyses adjusted to potential confounders, showed similar independent predictors of AKI among patients with and without DM, comprising; older age, chronic kidney disease, congestive heart failure, and peripheral arterial disease. Conclusions: Although patients with DM are at much greater risk for AKI when admitted with ACS, the independent predictors of AKI and the worse patient outcomes when AKI occurs, are similar irrespective to DM status.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Acute Kidney Injury Following Admission with Acute Coronary Syndrome: The Role of Diabetes Mellitus

Shiyovich

Skalsky

Steinmetz

et al. 2021

JCM

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“…A decrease of LVEF indicated the loss of contractility due to acute ischemia or myocardial necrosis [ 21 , 22 ]. Several studies have indicated that worsened LVEF was a predictor of CI-AKI [ 23 – 26 ]. In accordance with the previous study [ 23 , 27 , 28 ], our study demonstrated that the age and basal creatinine were independently correlated with CI-AKI.…”

Section: Discussionmentioning

confidence: 99%

“…Several studies have indicated that worsened LVEF was a predictor of CI-AKI [ 23 – 26 ]. In accordance with the previous study [ 23 , 27 , 28 ], our study demonstrated that the age and basal creatinine were independently correlated with CI-AKI. Cinar T et al also indicated that the age, creatinine and ejection fraction score correlated with ST-elevation myocardial infarction-related cardiogenic shock [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

Predictive value of creatine kinase MB for contrast-induced acute kidney injury among myocardial infarction patients

Wei

Zhang²,

Zhang

et al. 2021

BMC Cardiovasc Disord

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Background Predictive value of creatine kinase MB (CK-MB) for contrast-induced acute kidney injury (CI-AKI) among myocardial infarction (MI) patients has rarely been reported. We aim to evaluate the predictive value of CK-MB for CI-AKI among MI patients. Methods Totally, 1131 MI patients were included from the REduction of rIsk for Contrast-Induced Nephropathy (REICIN) study. The peak CK-MB before coronary angiography (CAG) was chosen. The study population was divided into two groups by log-transformed CK-MB cut-off point. The association between CK-MB and CI-AKI was tested by multivariable logistic regression. CK-MB was integrated with Age, creatinine and ejection fraction (ACEF) score and Mehran risk score (MRS) to evaluate the additive value of CK-MB. The integrated models were validated internally by the bootstrap method and externally by the PREdictive Value of COntrast voluMe to creatinine Clearance Ratio (PRECOMIN) study data set. Results Overall, 62(5.48%) patients developed CI-AKI, patients with CK-MB point > 4.7 displayed a higher incidence of CI-AKI than those without (11.9% vs. 4.0%, p < 0.001). CK-MB point > 4.7 was independently associated with CI-AKI (adjusted OR: 3.40, 95% CI: 1.93–5.98, p < 0.001). The additions of CK-MB to ACEF score, Mehran score A and Mehran score B resulted in increases in C-statistics, which ranged from 0.680 to 0.733 (p = 0.046), 0.694 to 0.727 (p = 0.091), 0.704 to 0.734 (p = 0.102), respectively. Internal validation also showed increases in C-statistics, and external validation performed well in discrimination and calibration. Conclusions Preprocedural peak CK-MB was a predictor of CI-AKI among MI patients.

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Characterization of Risk Prediction Models for Acute Kidney Injury

et al. 2023

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ImportanceDespite the expansion of published prediction models for acute kidney injury (AKI), there is little evidence of uptake of these models beyond their local derivation nor data on their association with patient outcomes.ObjectiveTo systematically review published AKI prediction models across all clinical subsettings.Data SourcesMEDLINE via PubMed (January 1946 to April 2021) and Embase (January 1947 to April 2021) were searched using medical subject headings and text words related to AKI and prediction models.Study SelectionAll studies that developed a prediction model for AKI, defined as a statistical model with at least 2 predictive variables to estimate future occurrence of AKI, were eligible for inclusion. There was no limitation on study populations or methodological designs.Data Extraction and SynthesisTwo authors independently searched the literature, screened the studies, and extracted and analyzed the data following the Preferred Reporting Items for Systematic Review and Meta-analyses guideline. The data were pooled using a random-effects model, with subgroups defined by 4 clinical settings. Between-study heterogeneity was explored using multiple methods, and funnel plot analysis was used to identify publication bias.Main Outcomes and MeasuresC statistic was used to measure the discrimination of prediction models.ResultsOf the 6955 studies initially identified through literature searching, 150 studies, with 14.4 million participants, met the inclusion criteria. The study characteristics differed widely in design, population, AKI definition, and model performance assessments. The overall pooled C statistic was 0.80 (95% CI, 0.79-0.81), with pooled C statistics in different clinical subsettings ranging from 0.78 (95% CI, 0.75-0.80) to 0.82 (95% CI, 0.78-0.86). Between-study heterogeneity was high overall and in the different clinical settings (eg, contrast medium–associated AKI: I2 = 99.9%; P &lt; .001), and multiple methods did not identify any clear sources. A high proportion of models had a high risk of bias (126 [84.4%]) according to the Prediction Model Risk Of Bias Assessment Tool.Conclusions and RelevanceIn this study, the discrimination of the published AKI prediction models was good, reflected by high C statistics; however, the wide variation in the clinical settings, populations, and predictive variables likely drives the highly heterogenous findings that limit clinical utility. Standardized procedures for development and validation of prediction models are urgently needed.

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A novel risk assessment model of contrast‐induced nephropathy after percutaneous coronary intervention in patients with diabetes

Cited by 15 publications

References 35 publications

Acute Kidney Injury Following Admission with Acute Coronary Syndrome: The Role of Diabetes Mellitus

Acute Kidney Injury Following Admission with Acute Coronary Syndrome: The Role of Diabetes Mellitus

Predictive value of creatine kinase MB for contrast-induced acute kidney injury among myocardial infarction patients

Characterization of Risk Prediction Models for Acute Kidney Injury

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