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University of Groningen

Acute Kidney Injury in critically ill patients

Wiersema, Renske

DOI:

10.33612/diss.133211862

IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.

Document Version

Publisher's PDF, also known as Version of record

Publication date: 2020

Link to publication in University of Groningen/UMCG research database

Citation for published version (APA):

Wiersema, R. (2020). Acute Kidney Injury in critically ill patients: a seemingly simple syndrome. University of Groningen. https://doi.org/10.33612/diss.133211862

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Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum.

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CHAPTER 1

General introduction

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General introduction and thesis outline

General introduction

The quality of care for critically ill patients has improved substantially over the past decades and mortality rates have gradually decreased.1 Preserving quality of life after the Intensive Care Unit

(ICU) has become more important including the long-term consequences of chronic illnesses and their treatments.2 Also, the development of new comorbidities during ICU stay, contributes

to quality of life impairment and longer-term mortality.

Patients at the ICU are at risk of chronic organ failure. The kidneys are vulnerable organs that endure severe illnesses and treatments. Both may contribute to a sudden decrease in renal function; i.e. Acute Kidney Injury (AKI). AKI is one of the most frequently developing complications during ICU stay and reported incidences vary between 20% and 60% in the critically ill, depending on selection criteria.3 Exact pathophysiological mechanisms remain largely unclear and importantly

there is no other treatment besides prevention and support. While AKI is independently associated with increased morbidity and mortality4, AKI is specifically associated with Chronic Kidney Disease

(CKD), which heavily impacts quality of life if requiring dialysis.5

AKI is currently defined by an abrupt decrease in urine output or a rise in creatinine following the Kidney Disease Improving Global Outcome (KDIGO) definition.6 Since there is no causative

treatment of AKI, most studies focus on early recognition and (secondary) prevention. The central diagnostic issue with AKI is that creatinine usually only rises one or two days after the kidney insult has occurred, potentially diagnosing AKI after the harm has been done. The second diagnostic issue is that increases in creatinine vary with patient age and muscular status. Also, ideally creatinine is calculated based on a baseline value, which is often unavailable. Multiple formulas available for estimation of baseline creatinine values seem to either over- or underestimate creatinine, influencing reported AKI incidences.7 In contrast, urine output may drop quickly, also

physiologically, and so many patients will fulfil the AKI stage I criteria at any time point during hospital admission even in absence of rises in serum creatinine. All these definition and criteria issues result in differences between patient groups both in clinical practice and in research reports.8

Studies have taught us that AKI is influenced by multiple risk factors and that it is likely that different pathophysiological mechanisms (subphenotypes) play a role in the development of AKI. While some biomarkers have been suggested for prediction or diagnosis of AKI in specific patient groups, no prediction models for AKI have been established in the general critically ill population. Improved prognostic models may guide future treatment of AKI. Also, tools for timely accurate detection of abrupt renal failure opposed to cases with steadily rises in serum creatinine are yet to be discovered.9 Therefore, most studies focus on identifying risk factors for AKI, so that preventive

measures may be applied before a rise in serum creatinine arises.

Risk factors for AKI include age, comorbidities, severity of illness, and (septic) shock. Decreased renal perfusion may induce local changes in the kidney endothelium.10 Renal perfusion

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impairment was assumed to be an immediate consequence of shock, but today evidence is accumulating that reduced venous outfl ow and increased venous pressure may also aggravate renal perfusion.11 Venous congestion is conceptualised as (relative) venous fl uid accumulation and

congestion, which may arise e.g., due to right ventricular failure with increased pressures in the vena cava (i.e. right ventricular failure as a cause). Conversely, a build-up of fl uid due to aggressive fl uid therapy, may induce right ventricular failure (i.e. right ventricular failure as a consequence). Such increased venous volumes can lead to increased venous pressures, causing raised renal tubular pressure, which may in turn reduce renal venous blood fl ow (fi gure 1).12 Increased kidney

afterload may reduce the driving pressure diff erence between arterial and venous renal pressures, resulting in decreased perfusion pressure. Evaluation of this concept may contribute to the pathophysiological understanding of changes in critically ill patients at risk of AKI. No defi nition of venous congestion exists and mostly single proxies such as CVP, fl uid balance or Inferior Vena Cava (IVC) diameter have been evaluated for venous congestion. Reliable variables for assessment of venous congestion and its association with organ failure have not been established.

Figure 1. Increased venous pressure leading to reduced ultrafi ltration gradient through (5) Increased renal venous pressure and (7) Increased extrinsic pressure, leading to(6) raised interstitial pressure and (8) Increased tubular pressure. Chapter 1 LV function Congested IVC Tubular pressure Extrinsic pressure Pulmonary edema

Renal venous pressure RV function 1 2 4 Interstitial pressure 5 6 8 7

Glomerular filtration rate9

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Thesis outline

Ultrasonography is widely used for the evaluation of patients with cardiovascular shock. Critical care ultrasound (CCUS) is however only scarcely reported for the evaluation of venous congestion. The previously suggested proxies that may be associated with venous congestion could potentially assist in identifying the patients at risk of this mechanism. CCUS is an increasingly available non-invasive tool which may also assist in the prediction of patients at risk of AKI. Within the Simple Intensive Care Studies I (SICS-I) cohort study the diagnostic and prognostic value of CCUS was evaluated. More specifically, the SICS-I cohort study was established to evaluate the accuracy of clinical examination for cardiac index, while the occurrence of AKI was studied as a sub study. Additionally, right ventricular function was measured and in chapter 2 we describe the association between right ventricular function and AKI. These hypothesis generating observations led to the design for the Simple Intensive Care Studies II (SICS-II).

As stated, it is likely that multiple risk factors influence the occurrence of AKI in the critically ill. In agreement with epidemiological principles it is essential to study the additive value of a new factor in comparison with established risk factors, also when considering new technologies, such as CCUS. However, advanced technologies may not be available everywhere. Therefore, chapter 3 describes an AKI prediction model based on only readily available variables first, to guide which clinical variables should be included when investigating the additive value of new advanced measures, and second, to investigate the predictive value of readily available variables in settings where resources are limited.

The objective of the SICS-II was to accurately study the association between venous congestion and AKI. To establish this association, it is essential to start with a definition for both concepts. No definition exists for venous congestion and only proxies have been described. The purpose of chapter 4 was to describe the protocol and purpose of SICS-II, and to define all potential proxies for venous congestion.

Before describing the associations between signs of congestion and AKI, not only venous congestion but also AKI needs to be defined unambiguously. While there is a consensus definition from the Kidney Disease Improving Global Outcomes (KDIGO), there are multiple possibilities how to interpret and apply these criteria. Various combinations of options lead to large discrepancies and ranges in incidences. In chapter 5 we illustrate the various options for AKI definitions and criteria and how the choices impact the observed consequences for AKI incidences. The aim of this chapter is to evaluate how different choices of definitions and criteria explain the variability in incidences of AKI reported in literature.

AKI could be associated with venous congestion through impaired renal perfusion. In that case, envisioning renal perfusion could provide information about patients at risk. Some studies have shown that the renal resistive index (RRI), a CCUS variable reflecting the arterial component of renal perfusion, is associated with AKI. The predictive value of the RRI however appeared limited

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compared to other previously investigated tools, which may be partially explained by the fact that RRI only reflects the arterial component. In chapter 6 we investigate the diagnostic accuracy of renal ultrasound for AKI, in which we also include the Venous Impedance Index (VII), a measure similar to the RRI, but reflecting the venous component of perfusion.

In the SICS-II cohort study we studied several proxies for venous congestion, including right ventricular function, the presence of pulmonary edema, the collapsibility of the IVC and the RRI and VII. In chapter 7, we performed an explorative hypothesis generating analysis of associations between potential signs of venous congestion and AKI.

Incidences and outcomes of AKI vary by population and the prediction models typically perform poor, likely because AKI is a very heterogeneous syndrome in an also heterogeneous population. In chapter 8, we performed an exploratory analysis in the FINNAKI cohort using latent class modelling to assess whether different subphenotypes of septic AKI exist. In addition, we analysed if these subphenotypes were associated with different outcomes.

In chapter 9, we explicate the association between AKI and mortality. In most studies, AKI is assessed as a dichotomous outcome, whereas likely multiple subphenotypes exist. We propose a method to calculate AKI burden, which represents a combination of the duration of AKI with the severity of an AKI episode to better appreciate the heterogeneity of AKI events among critically ill patients. The application of AKI burden or any other more granular method may be helpful in the comparison of future cohort studies reporting on AKI.

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References

Zimmerman JE, Kramer AA, Knaus WA. Changes in hospital mortality for United States intensive care unit admissions from 1988 to 2012.Crit Care 2013 Apr 27; 17. doi: 10.1186/cc12695.

Gerth AMJ, Hatch RA, Young JD, Watkinson PJ. Changes in health-related quality of life after discharge from an intensive care unit: a systematic review.Anaesthesia 2019; 74: 100–8.

Hoste EA, Bagshaw SM, Bellomo R, Cely CM, Colman R, Cruz DN, Edipidis K, Forni LG, Gomersall CD, Govil D, Honore PM, Joannes-Boyau O, Joannidis M, Korhonen AM, Lavrentieva A, Mehta RL, Palevsky P, Roessler E, Ronco C, Uchino S, Vazquez JA, Andrade EV, Webb S, Kellum JA. Epidemiology of acute kidney injury in critically ill patients: the multinational AKI-EPI study. Intensive Care Med 2015; 41: 1411–23. Poukkanen M, Vaara ST, Reinikainen M, Selander T, Nisula S, Karlsson S, Parviainen I, Koskenkari J, Pettilä V, FINNAKI Study Group. Predicting one-year mortality of critically ill patients with early acute kidney injury: data from the prospective multicenter FINNAKI study.Crit Care 2015; 19: 125.

Fiorentino M, Grandaliano G, Gesualdo L, Castellano G. Acute Kidney Injury to Chronic Kidney Disease Transition.Contrib Nephrol 2018; 193: 45–54.

Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney Int Suppl. 2012;2:1–138.

Zavada J, Hoste E, Cartin-Ceba R, Calzavacca P, Gajic O, Clermont G, Bellomo R, Kellum JA. A comparison of three methods to estimate baseline creatinine for RIFLE classification.Nephrol Dial Transplant 2010; 25: 3911–8.

Koeze J, Keus F, Dieperink W, van der Horst IC, Zijlstra JG, van Meurs M. Incidence, timing and outcome of AKI in critically ill patients varies with the definition used and the addition of urine output criteria.BMC Nephrol 2017; 18: 70–8.

Kellum JA. Why are patients still getting and dying from acute kidney injury?Curr Opin Crit Care 2016; 22: 513–9.

Nisula S, Kaukonen K-M, Vaara ST, Korhonen A-M, Poukkanen M, Karlsson S, Haapio M, Inkinen O, Parviainen I, Suojaranta-Ylinen R, Laurila JJ, Tenhunen J, Reinikainen M, Ala-Kokko T, Ruokonen E, Kuitunen A, Pettilä V. Incidence, risk factors and 90-day mortality of patients with acute kidney injury in Finnish intensive care units: the FINNAKI study.Intensive Care Med 2013; 39: 420–8.

Chen C, Lee J, Johnson AE, Mark RG, Celi LA, Danziger J. Right Ventricular Function, Peripheral Edema, and Acute Kidney Injury in Critical Illness.Kidney Int reports 2017; 2: 1059–65.

Prowle JR, Kirwan CJ, Bellomo R, Prowle J. R.and Kirwan CJ and BR. Fluid management for the prevention and attenuation of acute kidney injury.Nat Rev 2014; 10: 37–47.

General introduction and thesis outline

1 2 3 4 5 6 7 8 9 10 11 12

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