Introduction: This study aimed to investigate the effect of dapagliflozin in preventing post-contrast acute kidney injury (PC-AKI) in patients with type 2 diabetes (T2DM) and chronic kidney disease (CKD) who underwent an elective coronary procedure. Methods: Data of patients with T2DM and CKD undergoing an elective coronary procedure at Civil Aviation General Hospital from October 2020 to April 2023 were collected from the electronic medical records. Based on dapagliflozin usage, patients were classified as dapagliflozin users and nonusers. 1:1 nearest-neighbor propensity matching was performed to compare dapagliflozin users with nonusers. The primary endpoint was the first PC-AKI observed. Univariate and multivariate COX regression models were used to determine the independent risk/preventive factors for PC-AKI. Thereafter, subgroup analyses were performed to evaluate the interaction between subgroup and dapagliflozin usage. Changes in the serum creatinine (SCr) and cystatin C (CysC) levels were monitored at 24 h, 48 h, and 72 h after the procedure. Results: 256 pairs (256 dapagliflozin users in the dapagliflozin group and 256 dapagliflozin nonusers in the control group) were identified in the cohort. The incidence of PC-AKI in dapagliflozin group (10.9%) was lower than that in control group (22.3%). COX regression analyses showed that dapagliflozin use was associated with a lower risk of PC-AKI (HR 0.81, 95% CI: 0.69–0.95, p = 0.01) after adjustment for covariates. In the subgroup analyses, similar HRs of the dapagliflozin usage on the PC-AKI outcome were observed in patients across different patients’ characteristics which revealed its consistent benefit of preventing PC-AKI. The estimated glomerular filtration rate levels at post-48 h and 72 h were significant higher in the dapagliflozin group than those in the control group, while levels of SCr (post-48 h and 72 h) and CysC (post-24 h and 48 h) in the dapagliflozin group were lower compared with the control group. Conclusion: Our findings suggest dapagliflozin effectively decreases PC-AKI risk and exerts reno-protective effects in patients with T2DM and CKD undergoing an elective coronary procedure.

Post-contrast acute kidney injury (PC-AKI) is a kind of acute kidney injury after the administration of contrast media for an elective coronary procedure. The episode of PC-AKI is closely associated with prolonged hospital stays, more frequent readmissions, and enhanced risk of short- and long-term morbidity and mortality [1]. Chronic kidney disease (CKD) and type 2 diabetes (T2DM) are conventional risk factor for PC-AKI [2, 3]. In CKD patients, a relative high PC-AKI incidence of almost 10–20% has been reported [4, 5]. A recent epidemiological study has revealed that between 27.1% and 83.6% of T2DM patients have concurrent CKD, thus enhancing these patients’ risk of developing PC-AKI [6]. Therefore, patients with CKD and T2DM should be carefully monitored and appropriate preventive strategies need to be investigated to mitigate the risk of this potentially serious complication to improve patients’ clinical prognosis.

Though various approaches have been studied for preventing PC-AKI, including hydration, N-acetylcysteine, sodium bicarbonate, and statins, the optimal approach in patients with CKD and T2DM has not been determined yet [7‒9]. Dapagliflozin, a sodium-glucose cotransporter-2 (SGLT2) inhibitor represents a new generation of hypoglycemic agents in T2DM patients [10, 11]. In addition to its glucose-lowering activity, dapagliflozin usage is associated with hemodynamic function normalization, and anti-hypoxia and anti-oxidation effects in kidney, making it a potentially promising preventive option of PC-AKI. Our study was to investigate the clinical benefits of dapagliflozin in prevention against PC-AKI in patients with T2DM and CKD.

Study Population

This study was a retrospective matched cohort analysis of patients with T2DM and CKD admitted to our hospital from October 2020 to April 2023. T2DM was diagnosed according to the American Diabetes Association 2019 [12]. CKD was defined and classified based on the KDIGO guidelines [13]. A total of 1,161 patients admitted at Civil Aviation General Hospital (Beijing, China) were considered for analyses with ages between 18 and 75 years and estimated glomerular filtration rates (eGFRs) between 45 and 89 mL/(min·1.73 m2), and receiving coronary angiography or percutaneous coronary intervention procedures at our hospital. eGFR was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula. All the coronary procedures were performed based on the standard practice in China and patients received standard hydration with an intravenous infusion of 0.9% saline at a rate of 1 mL/kg/h for 6 h before and 12 h after the procedure [7, 14].

Patients were excluded from the analyses based on the following criteria: acute myocardial infarction, acute renal dysfunction, history of kidney transplant, severe heart failure (HF, New York Heart Association IV), malignancy, administration of other PC-AKI preventive medications such as N-acetylcysteine and sodium bicarbonate, or incomplete medical records. In our present study, 1,063 patients were included in the analyses (Fig. 1). This retrospective and single-center study got approved by the Ethical Committee of Civil Aviation General Hospital and patients’ informed consents were waived as part of the study approval by the Ethical Committee of Civil Aviation General Hospital.

Fig. 1.

Flowchart of study cohort to outline the selection of unmatched and propensity score-matched patients of our study. T2DM, type 2 diabetes; CKD, chronic kidney disease.

Fig. 1.

Flowchart of study cohort to outline the selection of unmatched and propensity score-matched patients of our study. T2DM, type 2 diabetes; CKD, chronic kidney disease.

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Clinical, laboratory, and primary outcome data of all the participants were obtained from the electronic medical records. Baseline clinical characteristics including age, sex, body mass index (BMI), diabetes duration, smoking status, comorbidities, and medications history were identified. All patients underwent routine blood examinations and renal function tests at 24 h before and 24 h, 48 h, and 72 h after the procedure.

Dapagliflozin Exposure

The dapagliflozin exposure was defined as a new prescription of dapagliflozin for more than 2 weeks till the date of procedure. The cut-off value of 2 weeks was determined based on dapagliflozin study in CKD patients indicating its reno-protective effect after 2 weeks [15]. Control participants were defined as the subjects with T2DM and CKD who were nonusers of SGLT2 inhibitors. The medication history was checked by the prescription in the electronic medical record. Meanwhile, in our hospital, the medication history of any individual was recorded on the first day of admission, and then double-checked on the day of procedure by a separate physician.

Primary Clinical Outcome

The primary outcome was defined as the PC-AKI event during the hospitalization. We identified PC-AKI as an serum creatinine (SCr) level ≥1.25 times of the baseline level and/or increase by 44.2 μmol/L or 0.5 mg/dL within 72 h after exposure to the contrast medium [16]. Only the first PC-AKI was included for the analysis.

Statistical Analysis

Propensity score-matched analysis was conducted to explore the association between dapagliflozin usage and the occurrence of PC-AKI to minimize biases resulting from different distribution of confounding factors among study patients. A 1-to-1 match was built using the propensity score analysis. Propensity scores (probability of being prescribed dapagliflozin) were calculated using multivariable logistic regression conditional on age, sex, BMI, diabetes duration, the baseline medications including insulin use, glucagon-like peptide receptor agonist (GLP-1RA) use, antihypertensive medication use, and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker use, laboratory variables including SCr, eGFR, and HbA1c, matching with previous visit, and comorbid conditions including hypertension and coronary artery diseases (CAD) to generate a separate score for control subjects, which were described in previous studies [17, 18]. Subjects were matched with nearest neighbor matching without replacement, with a 1:1 matching ratio for dapagliflozin users (dapagliflozin group) and nonusers (control group). Absolute standardized differences were calculated for all baseline characteristics and a <10% standardized difference with all variables between two groups was considered to achieve balance after matching. Various caliper widths were assessed iteratively to achieve the minimal between-group standardized differences. The final caliper width was determined as 0.05.

Continuous data were reported as either means ± standard deviation or medians (interquartile range). The normality of continuous data was assessed using the Kolmogorov-Smirnov test. Comparisons between continuous variables were made by the Student’s t test, Mann-Whitney U test, or Wilcoxon rank-sum test, depending on the distribution of the data. Categorical data were expressed as frequencies and percentages, and compared using the χ2 test. After propensity score matching, McNemar’s test was used to investigate the correlation between the presence of PC-AKI event and the use of dapagliflozin over nonusers. Univariate and multivariate COX regression models were performed to evaluate the independent risk/preventive factors for time to PC-AKI. The covariates with p value <0.10 were included in the multivariate model. Additionally, to avoid the potential bias introduced by patients who died before they could develop PC-AKI, those patients who died post-72 h of the elective coronary procedure were manually censored at 72 h (the last day PC-AKI diagnosis was observed). Subgroup analyses were performed by including a subgroup as a fixed factor to evaluate the interaction between the subgroup and dapagliflozin usage. A 2-tailed p value <0.05 was considered statistically significant. Statistical analyses were conducted using SPSS software.

Study Population

During the study period, a total of 1,063 patients with T2DM and CKD underwent elective coronary procedures in our hospital, which consisted of 259 dapagliflozin users and 804 dapagliflozin nonusers. Compared with nonusers, dapagliflozin users were with older ages, lower BMI, and lower percentage of hypertension.

After 1-to-1 matching, 256 dapagliflozin users and 256 dapagliflozin nonusers were finally included in the dapagliflozin group and control group, respectively. Their clinical characteristics are summarized in Table 1. Among these patients, the majority was male (63.5%) with an average age of 63.5 years and a BMI of 27.7 kg/m2. 56.3% of patients had hypertension and 74.0% had established CAD. The baseline duration of diabetes was 10.7 years, and the mean HbA1c was 7.5%. The mean procedure time was 51.0 min with the average 129.4 mL of contrast medium used. Two groups were similar in terms of demographic characteristics, medications, baseline laboratory results, and procedure characteristics. Additionally, in the dapagliflozin group, the duration of dapagliflozin usage was from 3 to 8 weeks, with a median of 5 weeks.

Table 1.

Clinical characteristics before matching and after matching

VariablesBefore matchingAfter matching
dapagliflozin users (n = 259)nonusers (n = 804)p valuedapagliflozin group (n = 256)control group (n = 256)p value
Age, years 64.6±10.8 62.1±13.5 0.01 64.3±10.9 62.7±12.5 0.12 
Male 167 (64.5) 545 (67.8) 0.32 166 (64.8) 159 (62.1) 0.52 
BMI, kg/m2 26.5±5.9 27.8±7.1 0.01 26.4±5.5 27.3±6.8 0.10 
Smoking history 87 (33.6) 226 (28.1) 0.09 85 (33.2) 78 (30.5) 0.51 
Diabetes duration, years 11.2±6.1 10.5±6.2 0.11 11.1±6.2 10.3±6.4 0.13 
CKD stage   0.10   0.84 
 G2 185 (71.4) 530 (65.9)  182 (71.1) 184 (71.9)  
 G3a 74 (28.6) 274 (34.1)  74 (28.9) 72 (28.1)  
Comorbidities 
 Established CAD 190 (73.4) 601 (74.8) 0.66 187 (73.0) 192 (75.0) 0.61 
 HF NYHA II–III 66 (25.5) 235 (29.2) 0.24 64 (25.0) 59 (23.0) 0.61 
 Hypertension history 152 (58.7) 535 (66.5) 0.02 150 (58.6) 138 (53.9) 0.29 
 Hyperlipidemia 199 (76.8) 625 (77.7) 0.76 198 (77.3) 202 (78.9) 0.67 
Laboratory variables 
 HbA1c, % 7.2±2.9 7.5±3.5 0.21 7.3±2.9 7.7±3.1 0.13 
 hs-CRP, mg/L 2.45±0.75 2.53±0.98 0.23 2.43±0.76 2.54±0.91 0.14 
 Hemoglobin, g/L 126.8±45.4 123.7±52.6 0.39 126.9±46.9 121.8±45.8 0.21 
 FPG, mmol/L 6.8±1.9 7.1±2.8 0.11 6.8±1.6 7.0±1.9 0.20 
 TC, mmol/L 4.45±1.25 4.62±1.36 0.07 4.43±1.21 4.56±1.12 0.21 
 LDL, mmol/L 2.86±0.87 2.76±0.92 0.12 2.83±0.82 2.71±0.87 0.11 
 BNP, ng/L 87.6±36.3 82.8±38.9 0.08 87.8±33.7 82.9±36.9 0.12 
 eGFR, mL/min/1.73 m2 70.8±21.6 69.9±22.8 0.58 70.9±21.6 69.3±22.9 0.42 
 SCr, µmol/L 109.7±22.7 106.5±26.9 0.08 109.6±22.5 107.9±23.9 0.41 
 CysC, mg/L 1.06±0.38 1.11±0.45 0.11 1.06±0.37 1.07±0.38 0.76 
Medications 
 Metformin 203 (78.4) 665 (82.7) 0.12 201 (78.5) 211 (82.4) 0.26 
 GLP-1RA 81 (31.3) 215 (26.7) 0.16 80 (31.3) 85 (33.2) 0.64 
 Insulin 138 (53.3) 469 (58.3) 0.15 137 (53.5) 130 (50.8) 0.54 
 Aspirin 198 (76.4) 625 (77.7) 0.67 196 (76.6) 193 (75.4) 0.76 
 ACEI/ARB 133 (51.4) 456 (56.7) 0.13 132 (51.6) 125 (48.8) 0.54 
 Calcium channel blockers 87 (33.6) 298 (37.1) 0.31 85 (33.2) 89 (34.8) 0.71 
 β-blockers 151 (58.3) 516 (64.2) 0.09 150 (58.6) 135 (52.7) 0.18 
 Statins 218 (84.2) 703 (87.4) 0.18 216 (84.4) 225 (87.9) 0.25 
Procedure variables 
 Procedure type   0.20   0.72 
  CAG 103 (39.8) 356 (44.3)  102 (39.8) 98 (38.3)  
  PCI 156 (60.2) 448 (55.7)  154 (60.2) 158 (61.7)  
 Contrast volume, mL 125.8±33.1 128.9±35.1 0.21 125.7±32.9 129.8±36.5 0.57 
 Procedure time, min 51.7±15.7 49.8±13.9 0.06 51.8±16.2 50.9±14.7 0.76 
VariablesBefore matchingAfter matching
dapagliflozin users (n = 259)nonusers (n = 804)p valuedapagliflozin group (n = 256)control group (n = 256)p value
Age, years 64.6±10.8 62.1±13.5 0.01 64.3±10.9 62.7±12.5 0.12 
Male 167 (64.5) 545 (67.8) 0.32 166 (64.8) 159 (62.1) 0.52 
BMI, kg/m2 26.5±5.9 27.8±7.1 0.01 26.4±5.5 27.3±6.8 0.10 
Smoking history 87 (33.6) 226 (28.1) 0.09 85 (33.2) 78 (30.5) 0.51 
Diabetes duration, years 11.2±6.1 10.5±6.2 0.11 11.1±6.2 10.3±6.4 0.13 
CKD stage   0.10   0.84 
 G2 185 (71.4) 530 (65.9)  182 (71.1) 184 (71.9)  
 G3a 74 (28.6) 274 (34.1)  74 (28.9) 72 (28.1)  
Comorbidities 
 Established CAD 190 (73.4) 601 (74.8) 0.66 187 (73.0) 192 (75.0) 0.61 
 HF NYHA II–III 66 (25.5) 235 (29.2) 0.24 64 (25.0) 59 (23.0) 0.61 
 Hypertension history 152 (58.7) 535 (66.5) 0.02 150 (58.6) 138 (53.9) 0.29 
 Hyperlipidemia 199 (76.8) 625 (77.7) 0.76 198 (77.3) 202 (78.9) 0.67 
Laboratory variables 
 HbA1c, % 7.2±2.9 7.5±3.5 0.21 7.3±2.9 7.7±3.1 0.13 
 hs-CRP, mg/L 2.45±0.75 2.53±0.98 0.23 2.43±0.76 2.54±0.91 0.14 
 Hemoglobin, g/L 126.8±45.4 123.7±52.6 0.39 126.9±46.9 121.8±45.8 0.21 
 FPG, mmol/L 6.8±1.9 7.1±2.8 0.11 6.8±1.6 7.0±1.9 0.20 
 TC, mmol/L 4.45±1.25 4.62±1.36 0.07 4.43±1.21 4.56±1.12 0.21 
 LDL, mmol/L 2.86±0.87 2.76±0.92 0.12 2.83±0.82 2.71±0.87 0.11 
 BNP, ng/L 87.6±36.3 82.8±38.9 0.08 87.8±33.7 82.9±36.9 0.12 
 eGFR, mL/min/1.73 m2 70.8±21.6 69.9±22.8 0.58 70.9±21.6 69.3±22.9 0.42 
 SCr, µmol/L 109.7±22.7 106.5±26.9 0.08 109.6±22.5 107.9±23.9 0.41 
 CysC, mg/L 1.06±0.38 1.11±0.45 0.11 1.06±0.37 1.07±0.38 0.76 
Medications 
 Metformin 203 (78.4) 665 (82.7) 0.12 201 (78.5) 211 (82.4) 0.26 
 GLP-1RA 81 (31.3) 215 (26.7) 0.16 80 (31.3) 85 (33.2) 0.64 
 Insulin 138 (53.3) 469 (58.3) 0.15 137 (53.5) 130 (50.8) 0.54 
 Aspirin 198 (76.4) 625 (77.7) 0.67 196 (76.6) 193 (75.4) 0.76 
 ACEI/ARB 133 (51.4) 456 (56.7) 0.13 132 (51.6) 125 (48.8) 0.54 
 Calcium channel blockers 87 (33.6) 298 (37.1) 0.31 85 (33.2) 89 (34.8) 0.71 
 β-blockers 151 (58.3) 516 (64.2) 0.09 150 (58.6) 135 (52.7) 0.18 
 Statins 218 (84.2) 703 (87.4) 0.18 216 (84.4) 225 (87.9) 0.25 
Procedure variables 
 Procedure type   0.20   0.72 
  CAG 103 (39.8) 356 (44.3)  102 (39.8) 98 (38.3)  
  PCI 156 (60.2) 448 (55.7)  154 (60.2) 158 (61.7)  
 Contrast volume, mL 125.8±33.1 128.9±35.1 0.21 125.7±32.9 129.8±36.5 0.57 
 Procedure time, min 51.7±15.7 49.8±13.9 0.06 51.8±16.2 50.9±14.7 0.76 

ACEI/ARB, angiotensin converting enzyme inhibitor/angiotensin receptor blocker; BMI, body mass index; BNP, B-type natriuretic peptide; CAD, coronary artery disease; CAG, coronary angiography; NYHA, New York Heart Association; CKD, chronic kidney disease; CysC, serum cystatin C; eGFR, estimated glomerular filtration rate; FPG, fasting plasma glucose; GLP-1RA, glucagon-like peptide-1 receptor agonist; hs-CRP, high-sensitivity C-reactive protein; LDL, low-density lipoprotein cholesterol; PCI, percutaneous coronary intervention; SCr, serum creatinine; TC, total cholesterol.

Association between Dapagliflozin Usage and PC-AKI

During the hospitalization, a total of 85 patients were diagnosed with PC-AKI, with 28 patients in the dapagliflozin group and 57 patients in the control group. The incidence of PC-AKI was lower in the dapagliflozin group than in the control group (p = 0.005). In the univariate COX regression analyses, age, diabetes duration, CKD G3a stage, HbA1c, eGFR, SCr, procedure type, and dapagliflozin usage were shown to be related with PC-AKI occurrence (p < 0.10). The univariate COX regression analyses are summarized in online supplementary Table S1 (for all online suppl. material, see https://doi.org/10.1159/000535208). These covariates were included in the multivariate COX regression analysis. Results showed that age (HR 1.19, 95% CI: 1.03–1.36, p = 0.02), diabetes duration (HR 1.15, 95% CI: 1.01–1.31, p = 0.04), eGFR (HR 1.20, 95% CI: 1.01–1.42, p = 0.04), and dapagliflozin usage (HR 0.81, 95% CI: 0.69–0.95, p = 0.01) remained to be significant predictors for PC-AKI occurrence (Table 2).

Table 2.

Univariate and multivariate COX regression analyses for PC-AKI occurrence

VariableUnivariateMultivariate
HR (95% CI)p valueHR (95% CI)p value
Age 1.26 (1.04–1.53) 0.02 1.19 (1.03–1.36) 0.02 
Diabetes duration 1.28 (1.04–1.59) 0.02 1.15 (1.01–1.31) 0.04 
CKD G3a stage 1.38 (0.99–1.92) 0.06 1.35 (0.84–2.17) 0.25 
HbA1c 1.88 (1.06–3.33) 0.03 2.18 (0.89–5.39) 0.09 
eGFR 1.17 (1.03–1.34) 0.02 1.20 (1.01–1.42) 0.04 
SCr 2.05 (1.03–4.08) 0.04 1.81 (0.89–3.67) 0.10 
PCI 1.92 (1.05–3.49) 0.03 2.15 (0.79–5.83) 0.13 
Dapagliflozin Usage 0.72 (0.59–0.88) 0.001 0.81 (0.69–0.95) 0.01 
VariableUnivariateMultivariate
HR (95% CI)p valueHR (95% CI)p value
Age 1.26 (1.04–1.53) 0.02 1.19 (1.03–1.36) 0.02 
Diabetes duration 1.28 (1.04–1.59) 0.02 1.15 (1.01–1.31) 0.04 
CKD G3a stage 1.38 (0.99–1.92) 0.06 1.35 (0.84–2.17) 0.25 
HbA1c 1.88 (1.06–3.33) 0.03 2.18 (0.89–5.39) 0.09 
eGFR 1.17 (1.03–1.34) 0.02 1.20 (1.01–1.42) 0.04 
SCr 2.05 (1.03–4.08) 0.04 1.81 (0.89–3.67) 0.10 
PCI 1.92 (1.05–3.49) 0.03 2.15 (0.79–5.83) 0.13 
Dapagliflozin Usage 0.72 (0.59–0.88) 0.001 0.81 (0.69–0.95) 0.01 

No censoring occurred in the present study.

eGFR, estimated glomerular filtration rate.

Subgroup analyses were used to investigate whether the effect of dapagliflozin on the PC-AKI outcome was consistent across different patients’ characteristics (Fig. 2). In the subgroup analyses, similar HRs of the dapagliflozin usage on the PC-AKI outcome were observed in patients analyzed according to age, gender, BMI, diabetes duration, HF NYHA grade, HbA1c, hs-CRP, in patients with and without established CAD, in metformin users versus nonusers, and in GLP-1RA users versus nonusers.

Fig. 2.

PC-AKI outcome in various demographic and clinical subgroups. Prespecified COX regression analyses were performed for subgroups of patients with respect to the PC-AKI occurrence. p values indicates the homogeneity of dapagliflozin usage effect across levels of subgroups. BMI, body mass index; CAD, coronary artery disease; NYHA, New York Heart Association; CKD chronic kidney disease; GLP-1RA, glucagon-like peptide-1 receptor agonist; hs-CRP, high-sensitivity C-reactive protein.

Fig. 2.

PC-AKI outcome in various demographic and clinical subgroups. Prespecified COX regression analyses were performed for subgroups of patients with respect to the PC-AKI occurrence. p values indicates the homogeneity of dapagliflozin usage effect across levels of subgroups. BMI, body mass index; CAD, coronary artery disease; NYHA, New York Heart Association; CKD chronic kidney disease; GLP-1RA, glucagon-like peptide-1 receptor agonist; hs-CRP, high-sensitivity C-reactive protein.

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Renal Function Indicators Changes

Changes in the renal function indicators post-24 h, 48 h, and 72 h of the elective coronary procedure are summarized in Table 3. The eGFR levels at post-48 h and 72 h were significantly higher in the dapagliflozin group than those in the control group, while the corresponding levels of SCr in the dapagliflozin group were lower compared with the control group. Though the levels of cystatin C (CysC) at post-24 h and 48 h were lower in the dapagliflozin group than those in the control group, no significant difference was observed at post-72 h between two groups.

Table 3.

Levels of CysC, SCr, and eGFR between two groups at baseline 24 h, 48 h, and 72 h after the elective coronary procedure

VariablesDapagliflozin group (n = 256)Control group (n = 256)p value
SCr, µmol/L 
 Baseline 107.9±23.9 109.6±22.5 0.41 
 24 h 110.8±28.7 112.4±29.5 0.53 
 48 h 113.1±31.6 119.5±32.8 0.02 
 72 h 116.9±26.9 121.9±25.2 0.03 
CysC, mg/L 
 Baseline 1.06±0.37 1.07±0.38 0.76 
 24 h 1.11±0.42 1.20±0.49 0.03 
 48 h 1.14±0.48 1.24±0.52 0.02 
 72 h 1.09±0.31 1.15±0.41 0.06 
eGFR, mL/min/1.73 m2 
 Baseline 67.9±21.6 66.3±22.9 0.42 
 24 h 67.3±20.6 64.7±20.3 0.15 
 48 h 65.1±20.1 61.3±19.8 0.03 
 72 h 63.5±23.6 58.6±25.9 0.03 
VariablesDapagliflozin group (n = 256)Control group (n = 256)p value
SCr, µmol/L 
 Baseline 107.9±23.9 109.6±22.5 0.41 
 24 h 110.8±28.7 112.4±29.5 0.53 
 48 h 113.1±31.6 119.5±32.8 0.02 
 72 h 116.9±26.9 121.9±25.2 0.03 
CysC, mg/L 
 Baseline 1.06±0.37 1.07±0.38 0.76 
 24 h 1.11±0.42 1.20±0.49 0.03 
 48 h 1.14±0.48 1.24±0.52 0.02 
 72 h 1.09±0.31 1.15±0.41 0.06 
eGFR, mL/min/1.73 m2 
 Baseline 67.9±21.6 66.3±22.9 0.42 
 24 h 67.3±20.6 64.7±20.3 0.15 
 48 h 65.1±20.1 61.3±19.8 0.03 
 72 h 63.5±23.6 58.6±25.9 0.03 

CysC, serum cystatin C; eGFR, estimated glomerular filtration rate; SCr, serum creatinine.

In the present study, we investigated the effect of dapagliflozin in patients with T2DM and CKD to explore whether it could reduce the risk of PC-AKI occurrence after an elective coronary procedure. The major findings of our study were as follows: (1) dapagliflozin usage was associated with decreased PC-AKI risk in patients with T2DM and CKD after an elective coronary procedure as the incidence of PC-AKI in the dapagliflozin group was lower than that in control group after a propensity-matched analysis and dapagliflozin usage was demonstrated to be the independent protective factor for PC-AKI occurrence; (2) dapagliflozin exhibited consistent benefit associated with PC-AKI across different patients’ characteristics in subgroup analyses, suggesting its general benefits for the broad patient population; (3) dapagliflozin displayed reno-protective effect, as levels of SCr, CysC, and eGFR were differed between two groups.

PC-AKI has become one of the leading causes of iatrogenic renal injury, which is closely associated with poorer prognosis in patients and greater general health costs. Multiple meta-analyses and systematic reviews have reported to identify the possible patient-related risk factors for PC-AKI including age, impaired renal function, and diabetes. Thus, patients with T2DM and CKD are at higher risk of developing PC-AKI after an elective coronary procedure, which should be paid special attention. To the best of our knowledge, our study was the first study to investigate PC-AKI in these patients. Currently, the exact pathophysiology of PC-AKI has not been elucidated yet. Potential mechanisms of underlying PC-AKI include the following: (1) the direct cytotoxic effect of contrast mediums on the renal tubular cells resulting in impaired alteration in the mitochondrial enzyme and tubular epithelial cellular dysfunction; (2) abnormal release of vasoconstrictor factors followed by injection of contrast mediums leading to the vascular constriction and then ischemia and hypoxia in the renal cortex and medulla; (3) red blood cell congestion and decrease in medullary blood flow induced by contrast mediums contributing to respiratory dysfunction of renal tubular cells and thereafter kidney injury [19].

Dapagliflozin, as a relatively novel class of antihyperglycemic agents, is a highly elective SGLT2 inhibitor for the treatment of T2DM. Dapagliflozin can decrease glucose reabsorption in the renal tubules and promote glucose clearance through urine by blocking the activity of high-capacity glucose transporter SGLT2 present in the proximal convoluted tubule. In addition to the glucose-lowering activity, dapagliflozin has been demonstrated to have the favorable renal benefits. On one hand, dapagliflozin can lower renal oxygen consumption via directly inhibiting SGLT2-mediated sodium reabsorption in the proximal tubule, and attenuate renal hypoxia by elevating blood ketone level to enable having more substrates for mitochondrial energy metabolism. On the other hand, it can ameliorate the glomerular hyperfiltration to up-regulate the responses of tubuloglomerular feedback and vasodilation of afferent arterioles to exert the reno-protective effect [20]. Recently, Huang et al. [21] conducted in vivo study in a rat model and underlined the potential molecular mechanism that dapagliflozin might attenuate PC-AKI by regulating the HIF-1a/HE4/NF-kB pathway.

Though the risk of PC-AKI with SGLT2 inhibitors was mentioned by a few commentaries [22], some studies have shown no increased risk, even lower risk of AKI found in T2DM patients receiving SGLT2 inhibitor treatment [23]. In the DECLARE-TIMI 58 study, dapagliflozin was identified with a 46% reduction in sustained decline in eGFR by at least 40% to less than 60 mL/min per 1.73 m2, and associated with lower risk of end-stage renal disease or death from renal reasons [24]. DAPA-CKD trial data also supported the reno-protective effect of dapagliflozin in the patients with CKD, regardless the presence or absence of diabetes which resulted in a 39% relative risk decrease in the eGFR decline, end-stage kidney disease, or renal or cardiovascular death [15]. In a large-cohort propensity-matched analysis of T2DM patients, Nadkarni et al. [18] aimed to assess the AKI risk in response to the SGLT2 inhibitors compared with matched nonusers, and observed no increased risk of AKI in T2DM patients receiving a SGLT2 inhibitor compared with nonusers over an 18-month follow-up period. Furthermore, the study even found a reduced AKI risk trend in SGLT2 inhibitor-treated group. Hua et al. [17] performed a propensity-matched analysis in T2DM patients and found real-life SGLT2 inhibitor users were with decreased risk of PC-AKI. Overall, data from various clinical trials and propensity-matched analyses of data from real-world evidence both unambiguously support that SGLT2 inhibitors do not predispose to AKI and contribute to kidney protection.

Consistent with previous studies, we did not observe increased risk of AKI in T2DM receiving dapagliflozin treatment, and even found decreased risk of PC-AKI. Further subgroup analyses revealed that dapagliflozin displayed similar renal benefits across different categories, including age, gender, BMI, diabetes duration, HF NYHA grade, levels of HbA1c and hs-CRP, history of established CAD, and metformin/GLP-1RA usage. The precise nature of interaction between any baseline characteristics and reno-protective benefit of SGLT2 inhibitors remains to be established. DAPA-CKD trial data reported generally consistent effect of dapagliflozin on the primary renal outcome [15]. Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial also confirmed no significant interaction between canagliflozin usage and renal preventive outcomes across different prespecified baseline characteristics [25]. Similar with previous studies, our data supported the reno-protective effect of dapagliflozin for the general patient population.

SCr, as the traditional indicator of renal function, has been employed in multiple studies related to PC-AKI, but which is easily influenced by age, gender, diet, and muscle mass [26]. CysC is a protein secreted primarily by nucleated cells, other than renal tubular cells, and independent of typical confounders, has been suggested as a reliable marker of AKI. Various recent studies also have shown that CysC exerts a more sensitive and specific value, and can be considered as an earlier index for reflecting renal function, compared with SCr [27‒29]. In our present study, compared with the control group, the dapagliflozin group exhibited elevated eGFR and decreased SCr levels at post-48 h and 72 h of the procedure, which indicated the role of dapagliflozin in maintaining renal health function. Additionally, CysC levels at post-24 h and 48 h were already lower in the dapagliflozin, which suggested its reno-protective role against PC-AKI throughout the perioperative period. These findings supported the clinical significance of dapagliflozin usage in patients with T2DM and CKD undergoing an elective coronary procedure.

However, our findings need to be interpreted with some limitations. First, the retrospective nature of the study could not avoid the selection bias, even though we conducted propensity score-matched analysis to minimize the impact of confounding factors. Thus, a larger sample size and multicenter studies would be needed to further confirm the effectiveness of dapagliflozin on reducing PC-AKI risk for patients with T2DM and CKD scheduled for an elective coronary procedure. Second, there was no follow-up data of the participants to ascertain the impact of dapagliflozin on patients’ long-term prognosis. Third, we focused on dapagliflozin use only in the present study, as which was not only the first SGLT2 inhibitor approved in China, but also the first SGLT2 inhibitor available in our hospital starting from the year 2019. When we get sufficient usage data of other SGLT2 inhibitors, for example, canagliflozin and empagliflozin, we will conduct the assessment. Finally, dapagliflozin showed its reno-protective effect after 2 weeks. But the duration was varied from 3 to 8 weeks among dapagliflozin subjects which could lead to some bias.

Our data suggest that dapagliflozin is associated with decreased PC-AKI risk in patients with T2DM and CKD undergoing an elective coronary procedure. Dapagliflozin is an important and promising option for the clinical management of PC-AKI in general population with T2DM and CKD.

We would like to thank all the patients included in this study.

This study complied with the World Medical Association Declaration of Helsinki and was approved by the Ethical Committee of Civil Aviation General Hospital (approval number: 2022LK33). Patients’ informed consents were waived as part of the study approval by the Ethical Committee of Civil Aviation General Hospital.

The authors have no conflicts of interest to declare.

This work was supported by the Safety Capability Building for Civil Aviation (Grant No.: DFS20180601).

Tao Liu, Xinwen Jian, and Zeyuan Fan conceived and designed the study; Tao Liu, Xinwen Jian, and Shan Chu collected the data; Tao Liu, Li Li, and Zeyuan Fan conducted the data analyses; and Tao Liu and Zeyuan Fan drafted the manuscript. All the authors approved the manuscript for submission.

All data generated or analyzed during this study are included in this article and its online supplementary material. Further inquiries can be directed to the corresponding author.

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