Original Research ArticleDetermining risk factors for triple whammy acute kidney injury
Introduction
With cardiovascular disease being the leading cause of death in adults worldwide, prescribing safe and effective anti-hypertensive therapies is of great concern. However, a common combination of renin-angiotensin system (RAS) inhibitors, such as angiotensin converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB), with diuretics and easily accessible over the counter non-steroidal anti-inflammatory drugs (NSAIDs) can cause kidney damage. This triple therapy, known as “triple whammy”, was associated with a 31% increased risk for acute kidney injury (AKI), compared to patients treated with diuretic and ACEI/ARB only (95% confidence interval 1.12–1.53) [1]. Triple whammy AKI occurs in 0.88%–22% of triple treatment patients [1], [2]. AKI may be a serious health condition and has major economic impacts. For instance, AKI accounts for 5% of hospital budget [3], [4] and 1% of overall health expenditure [5]. Mortality among AKI patients can be as high as 50%–80% of cases in specific populations, such as critically ill patients. Understanding how each of these drugs affect renal autoregulation individually and in combination can help medical providers avoid prescribing dangerous combinations in at risk individuals and administer them with confidence to low risk patients, especially to those who may benefit from pain killers for acute or chronic pain relief.
A goal of this study is to better understand the mechanism by which triple whammy increases the risk of AKI. AKI is marked by higher serum creatinine levels, which indicate a critically low glomerular filtration rate (GFR), according to internationally recognized definitions (i.e. KDIGO) [6] and may be accompanied by low urine flow (less than 400 ml/day) [7]. ACEI and diuretics lower blood pressure through increasing urine flow to reduce blood volume. Combined with NSAIDs, these drugs can prevent the body from properly reacting to hypovolemic states, resulting in dangerously low GFR. In fact, RAS inhibitors and NSAIDs interfere with and thus uncouple the renal afferent and efferent arteriole contractility demand generated by diuretic-induced volume loss to maintain GFR, giving rise to a hemodynamic, pre-renal form of AKI [8]. Triple whammy leads to AKI in some patients but not others. Thus, another goal of this study is to identify which individuals may be particularly susceptible to AKI following triple whammy, and which factors may individually render them so.
To achieve these goals, we apply previously published computational models of blood pressure regulation [9]. Computational models have long been used to describe interactions between blood pressure regulation and kidney function. In 1972, Guyton and Coleman [10] published their seminal circulation model, concluding that integral to the blood pressure regulation is the pressure-natriuresis curve, whereby higher blood pressure leads to higher sodium excretion in the urine. In 2005, Karaaslan et al. [11] used incorporated renal sympathetic nervous activity (RSNA) into major components of the Guyton to model to investigate how RSNA contributes to hypertension, and how renal denervation can treat it. In 2014, Hallow et al. [12] extended Karaaslan’s model to include the renin-angiotensin system to investigate efficacy of various antihypertensive therapies. Recognizing that major sex differences exist in blood pressure regulation, Leete and Layton [9] tailored these models to be sex specific. The models were parameterized separately for men and women, and include variables describing circulation, renal function, sodium and water transport through the nephron, and the RAS.
In this study, the mechanisms affected by ACEI, diuretics, and NSAIDs are included and the model is able to directly predict GFR, which is often difficult to obtain experimentally. To identify risk factors for development of AKI, we simulate single, double, and triple drug treatments for normotensive, hypertensive, male, and female humans. Our simulation results reveal a key role of the myogenic response in determining the risk of AKI. Myogenic response, the mechanism by which afferent arteriole resistance is manipulated to maintain appropriate flow through the nephron, is one of the few regulators of GFR untouched by ACEI, diuretics, and NSAIDs. As such, during triple treatment the myogenic response plays a larger than usual role in GFR regulation [8]. We hypothesize that individuals with an impaired myogenic response may be particularly susceptible to triple whammy AKI. Additionally, increased drug sensitivity or low water intake can predispose patients to triple whammy AKI.
Section snippets
Methods
The present blood pressure regulation models represent the interactions among the cardiovascular system, the renal system, the renal sympathetic nervous system, and the RAS (Fig. 1). A large system of coupled nonlinear algebraic differential equations is used to describe how these systems regulate blood pressure and respond to perturbations. For instance, renal blood flow is adjusted, in part, via renal autoregulatory mechanisms [11], [13] (Eqs. (17), (18) in the Appendix), according to
Results
The model is run forward in time for 2 simulated days. To simulate the administration of ACEI or furosemide, the relevant parameters (, , ) are gradually increased over the initial 30 min from the baseline values to their target values. Average GFR, MAP, and PRA as well as total urine volume for each day are then calculated.
Discussion
AKI is typically associated with elevated serum creatinine levels and a severe drop in urine output. The present study is concerned with “pre-renal AKI”, which results from altered renal hemodynamics leading to critically lowered GFR. (“Renal AKI” is caused by drug or ischemia-induced parenchymal injury, whereas “post-AKI” is a result of urinary tract obstruction.) Pre-renal AKI may develop as a result of hypotension, dehydration, heart failure, renal microangiopathy, or following the
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgments
This research was supported by the Canada 150 Research Chair program and by the Natural Sciences and Engineering Research Council of Canada , via a Discovery award (RGPIN-2019-03916).
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