Population attributable risk estimates of risk factors for contrast-induced acute kidney injury following coronary angiography: a cohort study

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Abstract

Background

Contrast-induced acute kidney injury (CI-AKI) is a common complication with poor outcomes following coronary angiography (CAG) or percutaneous coronary intervention (PCI). However, no study has explored the population attributable risks (PARs) of the CI-AKI risk factors. Therefore, we aimed to identify the independent risk factors of CI-AKI and estimate their PARs.

Methods

We analyzed 3450 consecutive patients undergoing CAG/PCI from a prospective cohort in Guangdong Provincial People’s Hospital. CI-AKI was defined as a serum creatinine elevation ≥50% or 0.3 mg/dL from baseline within the first 48 to 72 h after the procedure. Independent risk factors for CI-AKI were evaluated through stepwise approach and multivariable logistic regression analysis, and those that are potentially modifiable were of interest. PARs of independent risk factors were calculated with their odds ratios and prevalence among our cohort.

Results

The overall incidence of CI-AKI was 7.19% ( n = 248), which was associated with increased long-term mortality. Independent risk factors for CI-AKI included heart failure (HF) symptoms, hypoalbuminemia, high contrast volume, hypotension, hypertension, chronic kidney disease stages, acute myocardial infarction and age > 75 years. Among the four risk factors of interest, the PAR of HF symptoms was the highest (38.06%), followed by hypoalbuminemia (17.69%), high contrast volume (12.91%) and hypotension (4.21%).

Conclusions

These modifiable risk factors (e.g., HF symptoms, hypoalbuminemia) could be important and cost-effective targets for prevention and treatment strategies to reduce the risk of CI-AKI. Intervention studies targeting these risk factors are needed.

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Most cited references 20

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A simple risk score for prediction of contrast-induced nephropathy after percutaneous coronary intervention: development and initial validation.

Roxana Mehran, Eve Aymong, Eugenia Nikolsky … (2004)

We sought to develop a simple risk score of contrast-induced nephropathy (CIN) after percutaneous coronary intervention (PCI). Although several risk factors for CIN have been identified, the cumulative risk rendered by their combination is unknown. A total of 8,357 patients were randomly assigned to a development and a validation dataset. The baseline clinical and procedural characteristics of the 5,571 patients in the development dataset were considered as candidate univariate predictors of CIN (increase >or=25% and/or >or=0.5 mg/dl in serum creatinine at 48 h after PCI vs. baseline). Multivariate logistic regression was then used to identify independent predictors of CIN with a p value 75 years, anemia, and volume of contrast) were assigned a weighted integer; the sum of the integers was a total risk score for each patient. The overall occurrence of CIN in the development set was 13.1% (range 7.5% to 57.3% for a low [ or=16] risk score, respectively); the rate of CIN increased exponentially with increasing risk score (Cochran Armitage chi-square, p < 0.0001). In the 2,786 patients of the validation dataset, the model demonstrated good discriminative power (c statistic = 0.67); the increasing risk score was again strongly associated with CIN (range 8.4% to 55.9% for a low and high risk score, respectively). The risk of CIN after PCI can be simply assessed using readily available information. This risk score can be used for both clinical and investigational purposes.

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The burden of child and maternal malnutrition and trends in its indicators in the states of India: the Global Burden of Disease Study 1990–2017

Soumya Swaminathan, Rajkumar Hemalatha, Anamika Pandey … (2019)

Summary Background Malnutrition is a major contributor to disease burden in India. To inform subnational action, we aimed to assess the disease burden due to malnutrition and the trends in its indicators in every state of India in relation to Indian and global nutrition targets. Methods We analysed the disease burden attributable to child and maternal malnutrition, and the trends in the malnutrition indicators from 1990 to 2017 in every state of India using all accessible data from multiple sources, as part of Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. The states were categorised into three groups using their Socio-demographic Index (SDI) calculated by GBD on the basis of per capita income, mean education, and fertility rate in women younger than 25 years. We projected the prevalence of malnutrition indicators for the states of India up to 2030 on the basis of the 1990–2017 trends for comparison with India National Nutrition Mission (NNM) 2022 and WHO and UNICEF 2030 targets. Findings Malnutrition was the predominant risk factor for death in children younger than 5 years of age in every state of India in 2017, accounting for 68·2% (95% UI 65·8–70·7) of the total under-5 deaths, and the leading risk factor for health loss for all ages, responsible for 17·3% (16·3–18·2) of the total disability-adjusted life years (DALYs). The malnutrition DALY rate was much higher in the low SDI than in the middle SDI and high SDI state groups. This rate varied 6·8 times between the states in 2017, and was highest in the states of Uttar Pradesh, Bihar, Assam, and Rajasthan. The prevalence of low birthweight in India in 2017 was 21·4% (20·8–21·9), child stunting 39·3% (38·7–40·1), child wasting 15·7% (15·6–15·9), child underweight 32·7% (32·3–33·1), anaemia in children 59·7% (56·2–63·8), anaemia in women 15–49 years of age 54·4% (53·7–55·2), exclusive breastfeeding 53·3% (51·5–54·9), and child overweight 11·5% (8·5–14·9). If the trends estimated up to 2017 for the indicators in the NNM 2022 continue in India, there would be 8·9% excess prevalence for low birthweight, 9·6% for stunting, 4·8% for underweight, 11·7% for anaemia in children, and 13·8% for anaemia in women relative to the 2022 targets. For the additional indicators in the WHO and UNICEF 2030 targets, the trends up to 2017 would lead to 10·4% excess prevalence for wasting, 14·5% excess prevalence for overweight, and 10·7% less exclusive breastfeeding in 2030. The prevalence of malnutrition indicators, their rates of improvement, and the gaps between projected prevalence and targets vary substantially between the states. Interpretation Malnutrition continues to be the leading risk factor for disease burden in India. It is encouraging that India has set ambitious targets to reduce malnutrition through NNM. The trends up to 2017 indicate that substantially higher rates of improvement will be needed for all malnutrition indicators in most states to achieve the Indian 2022 and the global 2030 targets. The state-specific findings in this report indicate the effort needed in each state, which will be useful in tracking and motivating further progress. Similar subnational analyses might be useful for other low-income and middle-income countries. Funding Bill & Melinda Gates Foundation; Indian Council of Medical Research, Department of Health Research, Ministry of Health and Family Welfare, Government of India.

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Point and interval estimates of partial population attributable risks in cohort studies: examples and software.

E Hertzmark, D Spiegelman, H Wand (2007)

The concept of the population attributable risk (PAR) percent has found widespread application in public health research. This quantity describes the proportion of a disease which could be prevented if a specific exposure were to be eliminated from a target population. We present methods for obtaining point and interval estimates of partial PARs, where the impact on disease burden for some presumably modifiable determinants is estimated in, and applied to, a cohort study. When the disease is multifactorial, the partial PAR must, in general, be used to quantify the proportion of disease which can be prevented if a specific exposure or group of exposures is eliminated from a target population, while the distribution of other modifiable and non-modifiable risk factors is unchanged. The methods are illustrated in a study of risk factors for bladder cancer incidence (Michaud DS et al., New England J Med 340 (1999) 1390). A user-friendly SAS macro implementing the methods described in this paper is available via the worldwide web.

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Author and article information

Contributors

Jiyan Chen: chenjiyandr@126.com

Yong Liu:

ORCID: http://orcid.org/0000-0003-2224-4885

liuyong@gdph.org.cn

Journal

Journal ID (nlm-ta): BMC Cardiovasc Disord

Journal ID (iso-abbrev): BMC Cardiovasc Disord

Title: BMC Cardiovascular Disorders

Publisher: BioMed Central (London )

ISSN (Electronic): 1471-2261

Publication date (Electronic): 12 June 2020

Publication date PMC-release: 12 June 2020

Publication date Collection: 2020

Volume: 20

Electronic Location Identifier: 289

Affiliations

[1 ]GRID grid.284723.8, ISNI 0000 0000 8877 7471, The Second School of Clinical Medicine, , Southern Medical University, ; Guangzhou, 510515 Guangdong China

[2 ]Department of Cardiology, Provincial Key Laboratory of Coronary Heart Disease, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Affiliated Guangdong Provincial People’s Hospital of South China University of Technology, Guangdong Academy of Medical Sciences, Guangzhou, 510080 Guangdong China

[3 ]GRID grid.410652.4, ISNI 0000 0004 6003 7358, Department of Cardiology, , the People’s Hospital of Guangxi Zhuang Autonomous Region, ; Nanning, Guangxi China

[4 ]GRID grid.79703.3a, ISNI 0000 0004 1764 3838, Guangdong Provincial People’s Hospital, School of Medicine, , South China University of Technology, ; Guangzhou, Guangdong China

[5 ]GRID grid.410643.4, Department of Emergency and Critical Care Medicine, , Guangdong Provincial People’s Hospital and Guangdong Academy of Medical Sciences, ; Guangzhou, Guangdong China

[6 ]Department of Cardiology, Longyan First Affiliated Hospital of Fujian Medical University, Longyan, 364000 Fujian China

[7 ]GRID grid.411847.f, ISNI 0000 0004 1804 4300, School of Pharmacy, , Guangdong Pharmaceutical University, ; Guangzhou, Guangdong China

Author information

Yong Liu http://orcid.org/0000-0003-2224-4885

Article

Publisher ID: 1570

DOI: 10.1186/s12872-020-01570-6

PMC ID: 7291532

SO-VID: 6f47f691-3381-4d3a-9e75-b1e451aed20d

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 5 March 2020

Date accepted : 3 June 2020

Funding

Funded by: Beijing Lisheng Cardiovascular Pilot Foundation

Award ID: LHJJ201612127

Award Recipient : Jiyan Chen

Funded by: “Lixin Yangfan” Optimized Anti-thrombus Research Fund

Award ID: BJUHFCSOARF201801-10

Award Recipient : Yong Liu

Funded by: The Progress in Science and Technology Project of Guangzhou

Award ID: 201904010470

Award Recipient : Yong Liu

Funded by: The Access Research Fund

Award ID: 2018-CCA-AF-037

Award Recipient : Yong Liu

Funded by: The China Youth Clinical Research Fund

Award ID: 2017-CCA-VG-020

Award Recipient : Yong Liu

Custom metadata

ScienceOpen disciplines: Cardiovascular Medicine

Keywords: catheterization,acute renal disease,risk factors,population attributable risk

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ScienceOpen disciplines: Cardiovascular Medicine

Keywords: catheterization, acute renal disease, risk factors, population attributable risk

Population attributable risk estimates of risk factors for contrast-induced acute kidney injury following coronary angiography: a cohort study

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Abstract

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Conclusions

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Cardiovascular Innovations and Applications

Most cited references 20

A simple risk score for prediction of contrast-induced nephropathy after percutaneous coronary intervention: development and initial validation.

The burden of child and maternal malnutrition and trends in its indicators in the states of India: the Global Burden of Disease Study 1990–2017

Point and interval estimates of partial population attributable risks in cohort studies: examples and software.

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