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Acute kidney injury (AKI) in cardiac intensive care unit patients: a real challenge to overcome

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Abstract Introduction Acute kidney injury (AKI) is a major cause of morbidity and mortality in intensive care units (ICUs), but in cardiac intensive care unit (CICU), despite the evidence of a causal link between cardiac illness and AKI, few data are available (1). Purpose We analyzed the predictive factors of AKI in CICU, as well as the impact of AKI on the long-term prognosis of patients admitted to CICU. Methods We reviewed the medical data of patients admitted to our CICU over a 2-year period. We excluded patients with chronic kidney disease prior to admission. We defined AKI according to the KDIGO (Kidney Disease Improving Global Outcomes) classification based on serum creatinine and urine output. To determine the predictive factors, we performed a logistic regression analysis, and to determine the prognostic impact of AKI, we performed a Cox proportional hazards regression, taking all-cause mortality at 30 months as the main study outcome. p-values less than 0.05 were considered statistically significant Results We included in our study 1581 patients hospitalized in our unit over a 2-year period, 70.4% of whom were men and 29.6% women. Among these patients, 291 presented with AKI (18.4%), 35.5% classified as KDIGO 1, 42% as KDIGO 2, and 22.5% as KDIGO 3. For the admission diagnosis of patients with AKI, STEMI came first at 56.3%, followed by NSTEMI at 17.3%, acute heart failure at 9.3%, pulmonary embolism at 2.1%, severe arrhythmias at 7.9%, and valvular disease at 1.1%. Among patients in the KDIGO 3 group, 54% benefited from a renal replacement strategy. La morta For factors predictive of AKI, and after adjustment for variables significant in univariate analysis, we objectified the following factors: arterial hypertension (OR=1.92, p<0.001), Diabetes (OR=1.50, p=0.007), KILLIP>2 at admission (OR=1.75, p=0.003), Ejection fraction<40% at admission (OR=1. 93, p<0.001), right ventricular systolic dysfunction (OR=2.95, p<0.001), anemia with Hb<10g/dl (OR=2.95, p<0.001), cardiogenic shock (OR=3.02, p<0.001), high-grade conduction disorder (OR=2.7, p=0.003) and bleeding events (OR=5.93, p<0.001) (Table 1-figure 1). For all-cause mortality at 30 months, 204 events were observed, 104 in the AKI group (35%), and 100 in the non-AKI group (7.75%) (p<0.001), and AKI was independently associated with the outcome studied for all KDIGO classes with for stage 1 (HR = 1.33; p=0.03), stage 2 (HR = 2.28; p<0. 001), and stage 3 (HR = 5.71; p<0.001), adding to this diabetes (HR = 1.96; p<0.001), cardiogenic shock (HR = 2.27; p<0.001) and finally EF<35% at discharge (HR = 1.53; p=0.001) (Table 2-figure 1). The Kaplein-Meier survival analysis showed a significant difference between the rates of mortality between the different KDIGO at 30-months, with a log-rank test p<0.001 (Figure 2). Conclusion We can conclude that AKI remains a real challenge for admitted patients, since long-term mortality in this group is very high.Figure 1.Figure 2.
Title: Acute kidney injury (AKI) in cardiac intensive care unit patients: a real challenge to overcome
Description:
Abstract Introduction Acute kidney injury (AKI) is a major cause of morbidity and mortality in intensive care units (ICUs), but in cardiac intensive care unit (CICU), despite the evidence of a causal link between cardiac illness and AKI, few data are available (1).
Purpose We analyzed the predictive factors of AKI in CICU, as well as the impact of AKI on the long-term prognosis of patients admitted to CICU.
Methods We reviewed the medical data of patients admitted to our CICU over a 2-year period.
We excluded patients with chronic kidney disease prior to admission.
We defined AKI according to the KDIGO (Kidney Disease Improving Global Outcomes) classification based on serum creatinine and urine output.
To determine the predictive factors, we performed a logistic regression analysis, and to determine the prognostic impact of AKI, we performed a Cox proportional hazards regression, taking all-cause mortality at 30 months as the main study outcome.
p-values less than 0.
05 were considered statistically significant Results We included in our study 1581 patients hospitalized in our unit over a 2-year period, 70.
4% of whom were men and 29.
6% women.
Among these patients, 291 presented with AKI (18.
4%), 35.
5% classified as KDIGO 1, 42% as KDIGO 2, and 22.
5% as KDIGO 3.
For the admission diagnosis of patients with AKI, STEMI came first at 56.
3%, followed by NSTEMI at 17.
3%, acute heart failure at 9.
3%, pulmonary embolism at 2.
1%, severe arrhythmias at 7.
9%, and valvular disease at 1.
1%.
Among patients in the KDIGO 3 group, 54% benefited from a renal replacement strategy.
La morta For factors predictive of AKI, and after adjustment for variables significant in univariate analysis, we objectified the following factors: arterial hypertension (OR=1.
92, p<0.
001), Diabetes (OR=1.
50, p=0.
007), KILLIP>2 at admission (OR=1.
75, p=0.
003), Ejection fraction<40% at admission (OR=1.
93, p<0.
001), right ventricular systolic dysfunction (OR=2.
95, p<0.
001), anemia with Hb<10g/dl (OR=2.
95, p<0.
001), cardiogenic shock (OR=3.
02, p<0.
001), high-grade conduction disorder (OR=2.
7, p=0.
003) and bleeding events (OR=5.
93, p<0.
001) (Table 1-figure 1).
For all-cause mortality at 30 months, 204 events were observed, 104 in the AKI group (35%), and 100 in the non-AKI group (7.
75%) (p<0.
001), and AKI was independently associated with the outcome studied for all KDIGO classes with for stage 1 (HR = 1.
33; p=0.
03), stage 2 (HR = 2.
28; p<0.
001), and stage 3 (HR = 5.
71; p<0.
001), adding to this diabetes (HR = 1.
96; p<0.
001), cardiogenic shock (HR = 2.
27; p<0.
001) and finally EF<35% at discharge (HR = 1.
53; p=0.
001) (Table 2-figure 1).
The Kaplein-Meier survival analysis showed a significant difference between the rates of mortality between the different KDIGO at 30-months, with a log-rank test p<0.
001 (Figure 2).
Conclusion We can conclude that AKI remains a real challenge for admitted patients, since long-term mortality in this group is very high.
Figure 1.
Figure 2.

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