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Wang X, Fu X. Predicting AKI in patients with AMI: Development and assessment of a new predictive nomogram. Medicine (Baltimore) 2023; 102:e33991. [PMID: 37327276 PMCID: PMC10270522 DOI: 10.1097/md.0000000000033991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Accepted: 05/23/2023] [Indexed: 06/18/2023] Open
Abstract
Acute kidney injury (AKI) is a common complication of acute myocardial infarction (AMI) and is associated with both long- and short-term consequences. This study aimed to investigate relevant risk variables and create a nomogram that predicts the probability of AKI in patients with AMI, so that prophylaxis could be initiated as early as possible. Data were gathered from the medical information mart for the intensive care IV database. We included 1520 patients with AMI who were admitted to the coronary care unit or the cardiac vascular intensive care unit. The primary outcome was AKI during hospitalization. Independent risk factors for AKI were identified by applying least absolute shrinkage and selection operator regression models and multivariate logistic regression analyses. A multivariate logistic regression analysis was used to build a predictive model. The discrimination, calibration, and clinical usefulness of the prediction model were assessed using C-index, calibration plot, and decision curve analysis. Internal validation was assessed using bootstrapping validation. Of 1520 patients, 731 (48.09%) developed AKI during hospitalization. Hemoglobin, estimated glomerular filtration rate, sodium, bicarbonate, total bilirubin, age, heart failure, and diabetes were identified as predictive factors for the nomogram construction (P < .01). The model displayed good discrimination, with a C-index of 0.857 (95% CI:0.807-0.907), and good calibration. A high C-index value of 0.847 could still be reached during interval validation. Decision curve analysis showed that the AKI nomogram was clinically useful when the intervention was determined at an AKI possibility threshold of 10%. The nomogram constructed herein can successfully predict the risk of AKI in patients with AMI early and provide critical information that can facilitate prompt and efficient interventions.
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Affiliation(s)
- Xun Wang
- Department of Cardiology. The Second Hospital of Hebei Medical University, Shijiazhuang, China
- Department of Cardiology. The First Hospital of Qinhuangdao, Qinhuangdao, China
| | - Xianghua Fu
- Department of Cardiology. The Second Hospital of Hebei Medical University, Shijiazhuang, China
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Nong Y, Wei X, Qiu H, Yang H, Yang J, Lu J, Cao J, Fu Y, Yu D. Analysis of risk factors for severe acute kidney injury in patients with acute myocardial infarction: A retrospective study. FRONTIERS IN NEPHROLOGY 2023; 3:1047249. [PMID: 37675384 PMCID: PMC10479598 DOI: 10.3389/fneph.2023.1047249] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2022] [Accepted: 01/24/2023] [Indexed: 09/08/2023]
Abstract
Background Patients with acute myocardial infarction (AMI) complicated by acute kidney injury (AKI) tend to have a poor prognosis. However, the exact mechanism of the co-occurrence of the two diseases is unknown. Therefore, this study aims to determine the risk factors for severe AKI in patients with AMI. Methods A total of 2022 patients were included in the Medical Information Mart for Intensive Care. Variables were identified via univariate logistic regression, and the variables were corrected via multivariate logistic regression. Restricted cubic splines were used to examine the risks associated with the variables. The Kaplan-Meier method was used to compare the risk of severe AKI among the patients. Results Patients with severe AKI had a higher in-hospital mortality rate (28.6% vs. 9.0%, P < 0.001) and a longer duration of intensive care (6.5 days vs. 2.9 days, P < 0.001). In patients with AMI, the mean systolic blood pressure (SBP); international normalized ratio (INR); the levels of blood urea nitrogen (BUN), glucose, and calcium; and a history of liver disease were found to be the independent risk factors for developing severe AKI after their admission. Increased levels of BUN and blood glucose and a high INR increased the risk of severe AKI; however, increased levels of calcium decreased the risk; SBP presented a U-shaped curve relationship. Conclusions Patients with severe AKI have a poor prognosis following an episode of AMI. Furthermore, in patients with AMI, SBP; INR; a history of liver disease; and the levels of BUN, glucose, and calcium are the independent risk factors for developing severe AKI after their admission.
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Affiliation(s)
- Yuxin Nong
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xuebiao Wei
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Department of Geriatric Intensive Medicine, Guangdong Provincial Geriatrics Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China
| | - Hongrui Qiu
- Department of Thoracic Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Honghao Yang
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Jiale Yang
- Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Junquan Lu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Jianfeng Cao
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yanbin Fu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Danqing Yu
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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