Our study was the first to develop a CA-AKI risk stratification model in a population with hypoalbuminemia. We established a simple nomogram that included four powerful predictors for clinical use (IABP, ALB, eGFR, age). Compared to the classical Mehran score, the new model had good discrimination and calibration in predicting CA-AKI.
Hypoalbuminemia is associated with several pathological conditions. Yu et al. [10] showed that hypoalbuminemia often was observed in elderly patients and in patients having many comorbidities. Similarly, in our cohort, most patients were older and accompanying CKD, AMI, anemia and CHF, which may lead to the status of low serum albumin level. In our study, the incidence of CA-AKI was 9.36%, which was relatively high but similar to the high-risk population, such as patients with CKD or AMI [21, 22]. Several studies have demonstrated that hypoalbuminemia is an independent risk factor for CA-AKI [8] and is closely related to poor prognosis in coronary heart disease [23]. Yu et al. [10] reported that patients with hypoalbuminemia had a high incidence of AKI in the hospital. Furthermore, in our study, the development of AKI in patients was associated with a long-term mortality according to the results of the 7-year follow-up, which was similar to a previous study[10]. Due to the poor prognosis of CA-AKI in patients with known hypoalbuminemia, it is necessary for clinicians to early identify the high-risk individual of CA-AKI, leading to prompt management and intervention.
Risk assessment in high-risk groups is a primary aim and important for the prevention of CA-AKI, so a large number of models have been proposed [11]. Although the classic Mehran score or other models had good predictive efficiency, most models included 5-8 variables, and some factors required the subjective judgment of clinicians. In recent years, predictive models have been established for different populations at high risk of CA-AKI, such as patients with CKD [24], AMI [25] or diabetes mellitus [26]. However, there was no predictive model for patients with hypoalbuminemia. Because of the high incidence of CA-AKI in patients with hypoalbuminemia, it is important to develop a simple risk score for these patients undergoing CAG/PCI.
For predicting CA-AKI, the currently available models seldom included albumin [11] because serum albumin was a novel laboratory risk factor. Murat et al. [8] suggested that albumin is an independent and good predictor of CA-AKI among patients with ACS undergoing PCI. Low serum albumin concentrations reflect the inflammatory state of the body, which may lead to CA-AKI [9].
The use of IABP was the strongest predictor of CA-AKI in the present model. IABP, a reflection of hemodynamics, was an independent predictor of CA-AKI, which has been reported in previous studies [24, 27]. Bartholomew et al. [28]first reported a close association between the use of IABP and CA-AKI, and then Mehran et al. [16] first included IABP in a model of CA-AKI prediction. Perioperative hemodynamic disorders may lead to ischemia-reperfusion injury, which may have a potential contribution to AKI.
In the present risk model, age was an independent predictor of the occurrence of CA-AKI [16, 29]. This independent predictive ability may be related to a degenerative change in the structure and function of kidneys with increasing age. Baseline eGFR was also a common risk factor for CA-AKI following CAG [30]. eGFR represents worse kidney function and a higher risk of acute kidney injury [31].
Diabetes and contrast volume were not included in our nomogram, although these variables were included in previous models [32]. In our study, diabetes and contrast volume were not independent risk factors for CA-AKI based on statistical analysis. Similar to our finding, Sabeti et al. [33] showed that diabetes mellitus was not an independent risk factor for CA-AKI. A recent review concluded that diabetes is not independently associated with the risk of developing CA-AKI and only increases susceptibility in patients with underlying kidney disease [34]. Regarding contrast volume, current studies suggested that the development of AKI after contrast exposure is significantly determined by the presence of comorbidities and hemodynamic instability rather than contrast volume [35, 36]. Besides, Mehran et al. conducted a recent review and adapted the concept of contrast-associated AKI instead of contrast-induced AKI [1]. In our cohort, the association between contrast volume and CA-AKI showed no statistically significant difference. One of possible reasons for this result is that hypoalbuminemia patients tend to have more comorbidities and unstable hemodynamics[10]. As for anemia and LVEF, these factors were associated with CA-AKI in univariable, but not in multivariable analysis, which was similar to other studies[11, 37]. Our results suggested that the impact of anemia on CA-AKI may be potentially affected by confounding factors, like renal dysfunction or age. Similarly, Gao et al. showed the LVEF was not independently associated with CA-AKI after adjusting for age or IABP[38]. The KDIGO guidelines[39] suggest that eGFR should be used instead of Scr to assess baseline renal function in patients before the administration of contrast medium because Scr is also affected by age, gender, and race. Hydration has been considered an effective treatment for CA-AKI, but the actual effect of this strategy is still controversial. Perioperative hydration can expand plasma volume with suppression of the renin-angiotensin-aldosterone system, down-regulation of tubuloglomerular feedback, a decrease of contrast medium concentration in the tubule lumen and vasa recta, and counteraction of medullary vasoconstriction activation[40]. It is still the cornerstone of CA-AKI prevention. But, the rate and duration of hydration remain inconsistent. Meanwhile, the AMACING trial challenged the tenet that intravenous fluids are effective. There was no significant difference in the incidence of CA-AKI between the hydration group and the non-hydration group (2.7% vs 2.6%)[41]. In our study, the volume of hydration was not significantly different in multivariate regression, so this variable was not included in our model. By using our nomogram, clinicians can identify high-risk patients with CA-AKI early and treat them in a timely manner.
Limitations
Our study had some limitations. First, this study was based on data from a single center. However, our cohort is one of the largest CA-AKI databases among patients with hypoalbuminemia.
Second, our model is not as effective as other models, but it has fewer objective variables and higher clinical operability. Importantly, our model has good predictive and evaluative effectiveness in hypoalbuminemia populations.
Third, the nomogram established has not been externally verified. However, we randomly divided all the patients into a development group and a validation group according to a 2:1 ratio, which showed that our model had good stability.
Finally, several patients were discharged 3 days after the operation, so serum creatinine was not measured after 3 days in these patients. This might decrease the development of CA-AKI.