A risk prediction model for acute kidney injury following acute heart failure in an emergency department cohort in China

doi:10.5847/wjem.j.1920-8642.2025.068

Abstract

Abstract:

BACKGROUND: Acute kidney injury (AKI) is a severe and fatal complication of acute heart failure (AHF). Existing studies on AKI following AHF in the Chinese population have scarce insights available from the emergency department (ED). This study aimed to investigate the predictive factors of patients with AHF complicated with AKI in a Chinese ED cohort, and to establish a risk prediction model.

METHODS: Hospitalized patients diagnosed with AHF in the ED from December 2016 to September 2023 were included. The overall dataset were divided into the training set and the testing set at a 7:3 ratio. Univariate and multivariate logistic regression analyses were performed to identify the risk factors for AKI in patients with AHF in the training set, leading to the development of a risk prediction model. The performance of the model was further assessed.

RESULTS: A total of 789 patients with AHF were enrolled, with an AKI incidence of 29.7%. The mortality rates of the AKI and non-AKI groups were 23.1% and 7.6%, respectively. Logistic regression analysis showed that the levels of white blood cell (OR=2.368; 95%CI: 1.502-3.733, P<0.001), albumin (OR=2.669; 95%CI: 1.601-4.451, P<0.001), serum creatinine (OR=3.221; 95%CI: 1.935-5.363, P<0.001), and hemoglobin (OR=2.009; 95%CI: 1.259-3.205, P=0.003), maximum 24-h furosemide dosage (OR=2.196; 95%CI: 1.346-3.582, P=0.002), the use of non-invasive ventilation (OR=2.419; 95%CI: 1.454-4.024, P=0.001), and diabetes mellitus (OR=3.192; 95%CI: 2.014-5.059, P<0.001) were independent risk factors for AKI after AHF. These factors were subsequently incorporated into a risk prediction model. The area under the receiver operating characteristic (AUROC) curve for the predictive model was 0.815 (95%CI: 0.776-0.854) and 0.802 (95%CI: 0.776-0.854) in the training set and the testing set, respectively.

CONCLUSION: This risk prediction model might assist physician to predict AKI following AHF effectively in the emergency setting.

Key words: Acute heart failure, Acute kidney injury, Risk factor, Predictive model

Lingjie Cao, Yuanyuan Pei, Xiaolu Ma, Liping Guo, Fengtao Yang, Fange Shi, Pengfei Wang, Dilu Li, Kunyu Yang, Jihong Zhu. A risk prediction model for acute kidney injury following acute heart failure in an emergency department cohort in China[J]. World Journal of Emergency Medicine, 2025, 16(4): 348-356.

Figures/Tables 8

Table 1.

Baseline characteristics of the patients with AHF grouped according to AKI incidence in the training set

Variables	Total (n = 552)	AKI group (n =155)	Non-AKI group (n = 397)	Statistics	P-value
Male, n (%)	305 (55.3)	85 (54.8)	220 (55.4)	0.015	0.903
Age, years (n=551)	79 (68,85)	79 (67,85)	79 (68,85)	-0.041	0.967
Systolic pressure, mmHg (n=549)	139 (120,157)	142 (124,159)	138 (119.75,155)	-1.508	0.132
Diastolic pressure, mmHg (n=549)	79 (68,88)	80 (70,90)	78.5 (68,88)	-0.919	0.358
Heart rate, beats/min (n=550)	97 (81,115)	100 (84,120)	96 (79,114)	-2.096	0.036*
Comorbidities, n (%)
Hypertension	425 (77)	120 (77.4)	305 (76.8)	0.022	0.882
Diabetes mellitus	246 (44.6)	97 (62.6)	149 (37.5)	28.313	<0.001
Prior MI	143 (25.9)	38 (24.7)	120 (265.7)	0.033	0.855
Previous AHF	158 (28.7)	38 (24.7)	120 (30.2)	1.672	0.196
CKD	118 (21.4)	46 (29.7)	72 (18.1)	8.835	0.003
Cerebral infarction	120 (21.7)	42 (27.1)	78 (19.6)	3.636	0.057
COPD	88 (15.9)	26 (16.8)	62 (15.6)	0.111	0.739
Previous PCI	108 (19.6)	35 (22.6)	73 (18.4)	1.245	0.264
Previous CABG	46 (8.3)	10 (6.5)	36 (9.1)	0.999	0.318
DCM	16 (2.9)	14 (2.6)	12 (3.0)	0.077	0.781
CPHD	17 (3.1)	5 (3.2)	12 (3.0)	0.015	0.901
HCM	11 (2.0)	1 (0.6)	10 (2.5)	2.044	0.157
RHD	23 (4.2)	6 (3.9)	27 (4.3)	0.047	0.828
Type of AHF, n (%) Left-sided heart failure Right-sided heart failure Total heart failure	195 (35.3) 36 (6.5) 321 (58.2)	49 (31.6) 4 (2.6) 102 (65.8)	146 (37.0) 31 (7.8) 219 (55.2)	8.145	0.017*
NYHA class (n=435), n (%) II III IV	79 (18.2) 194 (44.6) 162 (37.2)	16 (13.3) 51 (42.5) 53 (44.2)	63 (20.0) 143 (45.4) 109 (34.6)	0.424	0.109
Killip class (n = 117), n (%) II III-IV	72 (61.5) 45 (38.5)	17 (48.6) 18 (51.4)	55 (67.1) 27 (32.9)	7.108	0.008*
Laboratory tests
CRP, mg/L (n =425)	14.92 (4.12,52.35)	26 (6.4,78.8)	13 (4,45.78)	-2.949	0.003*
WBC, × 10⁹/L	8.23 (6.19,11.95)	10.92 (7.3,14.75)	7.56 (5.99,10.54)	-6.348	<0.001*
Hemoglobin, g/L	111.09±27.443	101.40±28.1	114.88±26.263	-5.311	<0.001*
ALT, U/L (n=550)	22 (14,39)	23 (14,47.75)	21 (14,36)	-1.339	0.181
AST, U/L (n=550)	29 (19,43)	32.5 (20.75,57)	28 (18,40)	-2.591	0.010*
Albumin, g/L (n=550)	34.17±5.63	32.16±5.93	34.95±5.32	-5.342	<0.001*
Na, mmol/L (n=551)	140.3 (136.9,143.1)	141.65 (136.9,145.03)	140.1 (136.75,142.3)	-3.334	<0.001*
K, mmol/L (n=551)	4.3 (3.9,4.8)	4.6 (4.1,5.2)	4.3 (3.9,4.7)	-4.871	<0.001*
BUN, mmol/L	8.7 (6.34,12.48)	11.52 (7.62,15.3)	8 (5.9,11.22)	-6.666	<0.001*
Cr, μmol/L	96 (74,131.75)	120 (89,164)	89 (72,115.5)	-6.513	<0.001*
eGFR, ml/min per 1.73 m²	57.92 (39.56,79.68)	44.61 (30.67,62.95)	64.37 (44.16,82.81)	-6.657	<0.001*
First of BNP, pg/mL, (n=396)	794.5 (451,1590)	949 (479.25,1954.25)	725.5 (410.25,1452.25)	-2.481	0.013*
Maximum of BNP, pg/mL, (n=351)	1070 (571,1920)	1405 (806.25,2349)	894 (506,1965)	-4.659	<0.001*
First of NT-proBNP, pg/mL (n=191)	4610 (2238,10200)	9032.5 (4378.5,21574.75)	3950 (2020,7815)	-3.920	<0.001*
Maximum of NT-proBNP, pg/mL (n=163)	5800 (2730,11421)	11610.5 (5877.5,25983.75)	4490 (2309,8895)	-4.549	<0.001*
cTnI, ng/mL (n=318)	0.0325 (0,2)	1 (0,3)	0 (0,2)	-3.168	0.010*
hs-TnI, pg/mL (n=77)	40 (12.5,202)	135 (32.75,780.75)	29 (7,98)	-3.026	<0.001*
CK-MB, ng/mL (n=460)	3.5 (2.0,7.4)	4.7 (2.6,13.2	3.0 (2.0,6.0)	-4.039	<0.001*
LVEF (n=499) <40% 40%-49% ≥50%	109 (21.8) 121 (24.2) 269 (53.9)	38 (27.7) 31 (22.6) 68 (49.6)	71 (19.6) 90 (25.0) 201 (55.5)	3.919	0.141
Lactic acid, mmol/L (n=313)	1.60 (1.00,2.90)	1.70 (1.15,3.75)	1.50 (1.00,2.70)	-3.755	0.099
Contrast volume, mL (n=41)	300 (150,400)	350 (225,475)	210 (135,400)	-1.125	0.261
Treatment, n (%)
Initial dose of furosemide at 24 h, mg/d (n=729)	20 (20,40)	20 (20,40)	20 (20,40)	-1.291	0.197
Maximum dose of furosemide at 24 h, mg/d	40 (20,80)	60 (20,100)	40 (20,60)	-5.857	<0.001*
Rh-BNP	118 (21.4)	42 (27.1)	76 (19.1)	4.195	0.041*
Levosimendan	123 (22.3)	37 (23.9)	86 (21.7)	0.314	0.575
Digitalis	213 (38.6)	67 (43.2)	146 (36.8)	1.957	0.162
Nitrates	370 (67)	111 (71.6)	259 (65.2)	2.049	0.152
ACEI/ARB/ARNI	221 (40.0)	52 (33.5)	169 (42.6)	3.779	0.052
SGLT2i	48 (8.7)	14 (9.0)	34 (8.6)	0.031	0.861
β-blockers	325 (58.9)	94 (60.6)	231 (58.2)	0.278	0.598
Spironolactone	172 (31.2)	46 (29.7)	126 (31.7)	0.221	0.639
Iron supplements	58 (10.5)	24 (15.5)	34 (8.6)	5.676	0.017*
Dopamine	43 (7.8)	18 (11.6)	25 (6.3)	4.385	0.036*
Norepinephrine	36 (6.5)	20 (12.9)	16 (4.0)	14.396	<0.001*
Metaraminol	30 (5.4)	16 (10.3)	14 (3.5)	10.018	0.002*
IABP	5 (0.9)	1 (0.6)	4 (1.0)	0.163	0.686
CRRT	12 (2.2)	6 (3.9)	6 (1.5)	2.919	0.088
Non-invasive ventilation	130 (23.6)	60 (38.7)	70 (17.6)	27.507	<0.001*
Variables	Total (n = 552)	AKI group (n =155)	Non-AKI group (n = 397)	Statistics	P-value
Invasive ventilation	32 (5.8)	15 (9.7)	17 (4.3)	5.942	0.015*
CPR	31 (5.6)	9 (5.8)	22 (5.5)	0.015	0.903
PCI	53 (9.6)	9 (5.8)	44 (11.1)	3.576	0.059

Table 1.

Table 2.

Table 3.

Table 4.

Figure 1.

Table 5.

Figure 2.

Figure 3.

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Variables	Assigned values
Heart rate, beats/min	<97=0, ≥97=1
CRP, mg/L	<15=0, ≥15=1
WBC, × 10⁹/L	<8.2=0, ≥8.2=1
Hemoglobin, g/L	≥110=0, <110=1
AST, U/L	<29=0, ≥29=1
Albumin, g/L	>30=0, ≤30=1
Na, mmol/L	<140=0, ≥140=1
K, mmol/L	<4.3=0, ≥4.3=1
BUN, mmol/L	<8.7=0, ≥8.7=1
sCr, μmol/L Maximum dose of furosemide at 24 h, mg/d	<96=0, ≥96=1 <40=0, ≥40=1

Variables	Classification	Points
WBC, × 10⁹/L	<8.2 ≥8.2	0 2
Hemoglobin, g/L	≥110 <110	0 2
Albumin, g/L	>30 ≤30	0 3
sCr, μmol/L	<96 ≥96	0 3
Maximum dose of furosemide at 24 h, mg/d	<40 ≥40	0 2
Non-invasive ventilation	No Yes	0 2
Diabetes mellitus	No Yes	0 3

Datasets	Calibration			Discrimination
Datasets	Goodness-of-fit	df	P-value	AUROC±SE	95%CI	P-value
Training set	6.529	8	0.588	0.815±0.02	0.776-0.854	<0.001
Testing set	12.351	8	0.136	0.802±0.03	0.742-0.862	<0.001

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