scholarly journals Impact of nutritional index on contrast-associated acute kidney injury and mortality after percutaneous coronary intervention

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Miyeun Han ◽  
Hye Won Lee ◽  
Han Cheol Lee ◽  
Hyo Jin Kim ◽  
Eun Young Seong ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Percutaneous Coronary Intervention ◽  
Logistic Regression ◽  
Significant Risk ◽  
Multivariate Logistic Regression Analysis ◽  
Kidney Injury ◽  
Coronary Intervention ◽  
Nutritional Index ◽  
Increased Risk ◽  
Percutaneous Coronary

AbstractThe risk of malnutrition in acute kidney injury and mortality in coronary artery disease patients has not been studied. This study aimed to evaluate whether nutritional status assessed by Onodera’s prognostic nutritional index (PNI) was related to percutaneous coronary intervention (PCI) outcomes. A total of 3731 patients who received PCI between January 2010 and December 2018 were included. The relationship between PNI at the time of PCI and the occurrence of contrast-associated acute kidney injury (AKI) and all-cause death was evaluated using logistic regression and Cox proportional hazards models, respectively. AKI occurred in 271 patients (7.3%). A low PNI was independently associated with an increased risk of AKI on multivariate logistic regression analysis (OR 0.96, 95% CI 0.94–0.98, P = 0.001). During the median follow-up of 4.3 years, Kaplan–Meier analysis showed that patients with AKI/low PNI < 47.8 had a higher death rate. After adjusting for various risk factors, a low PNI was a significant risk factor for mortality (HR 0.98, CI 0.96–0.99, P = 0.003). A low level of PNI was associated with increased mortality, especially in the group aged over 70 years and female sex. PNI was closely associated with acute kidney outcomes and patient mortality after PCI.

Contrast Volume to Glomerular Filtration Ratio and Acute Kidney Injury among ST-Segment Elevation Myocardial Infarction Patients Treated with Primary Percutaneous Coronary Intervention

2019 ◽  
Vol 10 (2) ◽  
pp. 108-115
Author(s):  
David Zahler ◽  
Keren-Lee Rozenfeld ◽  
Ilan Merdler ◽  
Yogev Peri ◽  
Yacov Shacham
Keyword(s):  
Myocardial Infarction ◽  
Acute Kidney Injury ◽  
Percutaneous Coronary Intervention ◽  
Logistic Regression ◽  
Kidney Injury ◽  
Coronary Intervention ◽  
Primary Pci ◽  
Optimal Cutoff ◽  
Cutoff Value ◽  
Percutaneous Coronary

Introduction: The ratio of contrast media volume to glomerular filtration rate (contrast/GFR) has been shown to correlate with the occurrence of contrast-induced acute kidney injury (CI-AKI) in unselected patient populations who underwent percutaneous coronary intervention (PCI). Objective: We evaluated the possible utilization of this marker and optimal cutoff among ST-elevation myocardial infarction (STEMI) patients undergoing primary PCI. Methods: We retrospectively included 419 patients with STEMI treated with primary PCI. The occurrence of CI-AKI was defined by the KDIGO criteria as an increase in serum creatinine of ≥0.3 mg/dL within 48 h following PCI. A receiver-operator characteristic (ROC) curve was used to identify the optimal cutoff value of contrast/GFR ratio to predict CI-AKI. This value was then assessed using multivariable logistic regression. Results: The overall incidence of CI-AKI was 9%. The contrast/GFR ratio was significantly higher among patients with CI-AKI (2.7 ± 1.2 vs. 1.9 ± 0.9; p < 0.001). According to the ROC curve analysis, the optimal cutoff value of contrast/GFR ratio to predict AKI was measured as ≥2.13, with 70% sensitivity and 60% specificity (AUC 0.65, 95% CI 0.56–0.74; p = 0.002). In a multivariate logistic regression model, contrast/GFR ratio ≥2.13 was independently associated with CI-AKI (OR 2.46, 95% CI 1.09–5.57; p = 0.03). Conclusions: Among STEMI patients undergoing primary PCI, contrast/GFR ratio ≥2.13 was independently associated with CI-AKI.

scholarly journals Calculated Serum Osmolality, Acute Kidney Injury, and Relationship to Mortality after Percutaneous Coronary Intervention

2019 ◽  
Vol 9 (3) ◽  
pp. 160-167 ◽  
Author(s):  
Serdar Farhan ◽  
Birgit Vogel ◽  
Usman Baber ◽  
Samantha Sartori ◽  
Melissa Aquino ◽  
...  
Keyword(s):  
Acute Kidney Injury ◽  
Percutaneous Coronary Intervention ◽  
Kidney Injury ◽  
Coronary Intervention ◽  
Serum Osmolality ◽  
Multivariate Logistic Regression Model ◽  
Increased Risk ◽  
Percutaneous Coronary ◽  
Secondary Endpoints ◽  
Artery Disease

Background: Data on the associations between serum osmolality (sOsmo) and acute kidney injury (AKI) as well as short- and long-term mortality in patients with coronary artery disease (CAD) undergoing percutaneous coronary intervention (PCI) are limited. Objectives: To investigate the association between sOsmo and development of AKI and clinical outcomes in patients undergoing PCI. Methods: We investigated 1,927 consecutive patients undergoing PCI from the registry of a single center. Patients were divided into quartiles according to sOsmo at admission (Q1–Q4). sOsmo was calculated using the following equation: (1.86 × serum sodium [mmol/L]) + (glucose [mg/dL] / 18) + (blood urea nitrogen [mg/dL] / 2.8) + 9. The primary endpoint was AKI, per Kidney Disease: Improving Global Outcomes (KDIGO) definition. The secondary endpoints were 30-day and 1-year all-cause mortality. Results: Patients with the highest sOsmo (Q4) were older and more likely female, with significantly more cardiovascular risk factors and comorbidities compared to those with lower sOsmo (Q1–Q3). Incidence of AKI was highest in Q4 and lowest in Q2. In the multivariate logistic regression model, high sOsmo independently predicted the development of AKI (OR 2.00, 95% CI 1.26–3.19, p = 0.003). Patients with Q4 had a higher risk of 1-year mortality compared to patients with Q2 (HR 2.11, 95% CI 1.10–4.15; p = 0.031), but not after adding AKI to the multivariate model (HR 1.71, 95% CI 0.87–3.39; p = 0.12). Conclusion: sOsmo is a valid and easily obtainable predictor of AKI after PCI. High sOsmo is associated with increased risk of AKI and 1-year mortality in patients undergoing PCI. Further research is warranted to clarify whether the use of an sOsmo-directed hydration protocol might reduce the incidence of AKI in patients undergoing PCI.

scholarly journals Machine learning prediction model of acute kidney injury after percutaneous coronary intervention

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Toshiki Kuno ◽  
Takahisa Mikami ◽  
Yuki Sahashi ◽  
Yohei Numasawa ◽  
Masahiro Suzuki ◽  
...  
Keyword(s):  
Machine Learning ◽  
Myocardial Infarction ◽  
Acute Kidney Injury ◽  
Percutaneous Coronary Intervention ◽  
Logistic Regression ◽  
Risk Model ◽  
Kidney Injury ◽  
Coronary Intervention ◽  
Percutaneous Coronary ◽  
St Elevation

AbstractAcute kidney injury (AKI) after percutaneous coronary intervention (PCI) is associated with a significant risk of morbidity and mortality. The traditional risk model provided by the National Cardiovascular Data Registry (NCDR) is useful for predicting the preprocedural risk of AKI, although the scoring system requires a number of clinical contents. We sought to examine whether machine learning (ML) techniques could predict AKI with fewer NCDR-AKI risk model variables within a comparable PCI database in Japan. We evaluated 19,222 consecutive patients undergoing PCI between 2008 and 2019 in a Japanese multicenter registry. AKI was defined as an absolute or a relative increase in serum creatinine of 0.3 mg/dL or 50%. The data were split into training (N = 16,644; 2008–2017) and testing datasets (N = 2578; 2017–2019). The area under the curve (AUC) was calculated using the light gradient boosting model (GBM) with selected variables by Lasso and SHapley Additive exPlanations (SHAP) methods among 12 traditional variables, excluding the use of an intra-aortic balloon pump, since its use was considered operator-dependent. The incidence of AKI was 9.4% in the cohort. Lasso and SHAP methods demonstrated that seven variables (age, eGFR, preprocedural hemoglobin, ST-elevation myocardial infarction, non-ST-elevation myocardial infarction/unstable angina, heart failure symptoms, and cardiogenic shock) were pertinent. AUC calculated by the light GBM with seven variables had a performance similar to that of the conventional logistic regression prediction model that included 12 variables (light GBM, AUC [training/testing datasets]: 0.779/0.772; logistic regression, AUC [training/testing datasets]: 0.797/0.755). The AKI risk model after PCI using ML enabled adequate risk quantification with fewer variables. ML techniques may aid in enhancing the international use of validated risk models.

scholarly journals Nutritional status and risk of contrast-associated acute kidney injury in elderly patients undergoing percutaneous coronary intervention

2021 ◽  
Author(s):  
Xiaoqi Wei ◽  
Hanchuan Chen ◽  
Zhebin You ◽  
Jie Yang ◽  
Haoming He ◽  
...  
Keyword(s):  
Risk Factors ◽  
Acute Kidney Injury ◽  
Percutaneous Coronary Intervention ◽  
Nutritional Status ◽  
Elderly Patients ◽  
Kidney Injury ◽  
Coronary Intervention ◽  
Severe Malnutrition ◽  
Percutaneous Coronary ◽  
Conut Score

Abstract Background This study aimed to investigate the connection between malnutrition evaluated by the Controlling Nutritional Status (CONUT) score and the risk of contrast-associated acute kidney injury (CA-AKI) in elderly patients who underwent percutaneous coronary intervention (PCI). Methods A total of 1308 patients aged over 75 years undergoing PCI was included. Based on the CONUT score, patients were assigned to normal (0–1), mild malnutrition (2–4), moderate-severe malnutrition group (≥ 5). The primary outcome was CA-AKI (an absolute increase in ≥ 0.3 mg/dL or ≥ 50% relative serum creatinine increase 48 h after contrast medium exposure). Results Overall, the incidence of CA-AKI in normal, mild, moderate-severe malnutrition group was 10.8%, 11.0%, and 27.2%, respectively (p < 0.01). Compared with moderate-severe malnutrition group, the normal group and the mild malnutrition group showed significant lower risk of CA-AKI in models adjusting for risk factors for CA-AKI and variables in univariate analysis (odds ratio [OR] = 0.48, 95% confidence interval [CI]: 0.26–0.89, p = 0.02; OR = 0.46, 95%CI: 0.26–0.82, p = 0.009, respectively). Furthermore, the relationship were consistent across the subgroups classified by risk factors for CA-AKI except anemia. The risk of CA-AKI related with CONUT score was stronger in patients with anemia. (overall interaction p by CONUT score = 0.012). Conclusion Moderate-severe malnutrition is associated with higher risk of CA-AKI in elderly patients undergoing PCI.

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