Protective Effect of SGLT2i on contrast-induced AKI after Angiography in Patients with Type 2 Diabetes Mellitus and Chronic Coronary Syndrome: A 6-year Ambispective Cohort Study and Meta-analysis

doi:10.21203/rs.3.rs-5244417/v1

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Research Article

Protective Effect of SGLT2i on contrast-induced AKI after Angiography in Patients with Type 2 Diabetes Mellitus and Chronic Coronary Syndrome: A 6-year Ambispective Cohort Study and Meta-analysis

https://doi.org/10.21203/rs.3.rs-5244417/v1

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Background SGLT2 inhibitor (SGLT2i) may reduce the risk of contrast-induced acute kidney injury (CI-AKI) in patients with type 2 diabetes mellitus (T2DM) with chronic coronary syndrome (CCS) undergoing angiography. However, the evidence is still inconclusive. We aimed to conduct a real world study and systematically review to provide updated and larger-scale evidence.

Study design: Ambispective Cohort Study and Meta-analysis.

Setting & population: Patients with T2DM and CCS.

Methods The data was obtained from December 2017 to July 2024. Propensity score techniques were applied to enhance between-group comparability. We analyzed CI-AKI_ESUR and CI-AKI_KDIGO and conducted subgroup analyses based on the types of angiographic procedures, including percutaneous coronary interventions (PCI), coronary arteriography (CAG), and Coronary Computed Tomographic Angiography (CCTA). We retrieved similar cohort studies from the literature to perform a meta-analysis. Results from trials reporting CI-AKI_ESUR and/or CI-AKI_KDIGO rates among patients randomized to SGLT2i versus placebo were also meta-analysed.

Results A total of 2,350 patients receiving dapagliflozin and 16,251 patients did not receiving any SGLT2i were included before PSM. 2,071 SGLT2i users were matched with 2,071 control patients. The incidence of primary outcome 1 and 2 were both significant lower in SGLT2i group than in the control group, which were both confirmed before and after PSM analysis. Subgroup analysis showed that the incidence of CI-AKI in the SGLT2i group was significantly lower after either PCI, CAG or CCTA. The meta-analysis of cohort studies further confirmed this result, that is, the rate of CI-AKI occurrence after angiography in the SGLT2i group was significantly lower than in the control group regardless of which criterion for CI-AKI was used.

Limitations Results may be limited by single-center nature, inevitable sample selection bias, etc. and subgroup analysis of angiography operation types was conducted.

Conclusion In real-world T2DM patients, SGLT2i was associated with lower CI-AKI risk.

Clinical trial registration: Chinese Clinical Trial Registry, identifier: ChiCTR2300076484

Dapagliflozin

SGLT2 inhibitors

contrast-induced AKI

Type 2 diabetes mellitus

Chronic coronary syndrome

Angiography

Diabetes mellitus is a common chronic disease, and its complications seriously affect the quality of life and prognosis of patients. Cardiovascular disease is one of the main complications of diabetes, and angiography and interventional therapy are important diagnostic and treatment methods for cardiovascular diseases. However, the contrast agents used in these procedures may lead to contrast-induced acute kidney injury (CI-AKI), especially in diabetic patients, who have a higher risk of developing this condition.^1–3

Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are a new class of hypoglycemic drugs⁴ that have been proven to have various cardiovascular and renal protective effects.^5–9 Numerous studies have shown that SGLT2i can reduce the risk of cardiovascular events, delay the progression of kidney disease, and lower the mortality rate in diabetic patients.^10–12 However, the evidence regarding the protective effect of SGLT2i on CI-AKI during angiography is still insufficient.

Some studies suggest that SGLT2i may be beneficial in preventing CI-AKI. For example, Hua et al.¹³ found that SGLT2i could reduce the risk of CI-AKI in diabetic patients undergoing PCI. Paolisso et al.¹⁴ also demonstrated the potential renal protective effect of SGLT2i in patients with acute myocardial infarction (AMI). However, there are also studies that have raised different opinions on this matter. A randomized controlled trial by Feitosa et al.¹⁵ did not find a significant advantage of SGLT2 inhibitors in preventing CI-AKI.

Therefore, we aim to conduct a cohort study to investigate the potential protective effect of SGLT2i against CI-AKI in patients with T2DM undergoing percutaneous coronary interventions (PCI) or coronary arteriography (CAG) or Coronary Computed Tomographic Angiography (CCTA). Furthermore, we plan to perform a meta-analysis to combine the results of relevant studies and provide a more comprehensive assessment of the efficacy of SGLT2i in preventing CI-AKI in this patient population. By doing so, we hope to provide more robust evidence to guide clinical decision-making and optimize the management of T2DM patients undergoing angiography.

Study design and data sources

This was a cross-sectional analysis of patients with T2DM and CCS undergoing PCI or CAG or CCTA. Data was extracted from the hospital information system (HIS) of Beijing hospital (a tertiary general hospital) from December 1, 2017 to July 31, 2024. The database encompassed comprehensive details on admission and discharge, age, sex, drinking status, medications, procedures, and laboratory test results of the patients.

Patient recruitment criteria

Eligibility criteria included the following: inpatients with complete data sets, aged 18 years, diagnosis of T2DM with CCS, documentation of dapagliflozin use > 2 days before PCI or CAG or CCTA (study group) or no SGLT2 inhibitors during PCI or CAG or CCTA (control group), normal or mildly impaired liver function, and normal or mildly impaired renal function. For multiple related admissions, each admission data was recorded to avoid any omission.

Exclusion criteria were as follows: drug allergies and ketoacidosis that occurred after taking dapagliflozin; serious diseases that affect life span, such as malignant tumors, organ failure caused by various causes, severe immune system diseases, hemodynamic instability, severe anemia, and severe infections; taking drugs with clear nephrotoxicity, incomplete information (illogical data and missing or insufficient data); and lost to follow-up; and any patients with such history was excluded.

Definition of Outcome

We identified contrast-induced acute kidney injury (CI-AKI) events using a laboratory based algorithm, which identifies events based on the European Society of Urogenital Radiology (ESUR) serum creatinine criteria (increase in serum creatinine by ≥ 44.2 µmol/L or 0.5 mg/dL within 72 h or increase in serum creatinine by ≥ 1.25 times baseline value; hereafter referred to as CI-AKI_ESUR).¹⁶ As part of a sensitivity analysis, we additionally identified inpatient episodes of acute kidney injury (AKI) using Kidney Disease: Improving Global Outcomes (KDIGO) serum creatinine criteria (increase in serum creatinine by ≥ 26.52 µmol/L (0.3 mg/dL) within 48 h or increase in serum creatinine by ≥ 1.5 times baseline value before CAG; hereafter referred to as AKI_KDIGO) and recorded the corresponding dates.¹⁷ The final laboratory values before patients underwent CAG were used as the baseline data for analysis. This approach aimed to accurately represent each patient’s baseline condition before the procedure. The renal functions (serum creatinine and urea nitrogen) of patients with CCS were collected and measured upon admission and at 24, 48, and 72 h after PCI or CAG or CCTA.

Statistical analysis

All baseline characteristics data did not show normal distribution, so quantitative data were expressed as median and interquartile range (IQR) and qualitative data were expressed as numbers and percentages. To make baseline characteristics similar between the groups, we conducted a matched cohort-study based on propensity-score matching (PSM) with a matching ratio of 1:1 (caliper value 0.05). Propensity scores were estimated by age, gender, BMI, smoking and drinking status, and renal function. We excluded the patients for whom no matched control patients were found. The Chi-square test and Fisher's exact probability test were used for categorical variables. Spearman correlation test was used to evaluate the correlation between two sets of continuous variables. All statistical analyses were performed using the SPSS statistics software (version 26.0, IBM). P < 0.05 was considered statistically significant and 0.05 divided by the number of times of comparison was termed as the adjusted p value. All reported p-values were two-sided.

Ethics and Trial registration

The study protocol complied with Good Clinical Practice standards for drugs and the ethical guidelines specified in the revised Declaration of Helsinki (2013). Beijing Hospital Ethics Committee approved this study (Approval Letter Number: 2023BJYYEC-266-01) and the study was registered at Chinese Clinical Trial Registry (Registration number: ChiCTR2300076484). Data extracted from medical records was retrospected, de-identified and anonymized before analysis; therefore, the requirement for informed consent was waived for this study.

Meta-analysis

We further performed a meta-analysis on renal outcomes (CI-AKI_ESUR and CI-AKI_KDIGO) by pooling the results from prior studies and the present study. Two reviewers (Zhao and Zhang) independently searched studies from the PubMed, Embase, and Cochrane Library from the inception of database to August 2nd, 2024 that reported the prevention of contrast-induced AKI. The search strategy and key terms were listed in Additional File: Supplementary File eTable 1. We previously registered the protocol in PROSPERO.

We included observational studies without imposing any language restrictions. Data were presented as mean diference with 95% CIs. The fix and random effect model was used to obtained pooled risk ratios (RR). The statistical heterogeneity was assessed by the statistic I². Data were analyzed by Review Manager version 5.3.

We assessed the risk of bias using the Newcastle-Ottawa scale (NOS)¹⁸ for cohort studies. We examined the publication bias using funnel plots.

Cohort study

A total of 18,601 patients with T2DM undergoing PCI/CAG/CCTA were admitted from December 2017 to July 2024 in Beijing Hospital. Out of the admitted patients, a total of 2,350 were taking dapagliflozin and and 16,251 did not take any SGLT2i. After PSM, 2.071 cases and 2,071 controls were finally paired. The selection process is summarized in Fig. 1.

Baseline demographic and clinical characteristics before and after matching are described in Table 1 and Table 2. Each patient taking dapagliflozin was matched to a patient without taking any SGLT2i using clinical baseline variables and/or factors that may affect renal function. After PSM, the 2,071 matched pair of patients showed no significant difference in baseline characteristics such as age, gender, and BMI. There was no statistically significant difference in eGFR, BUN, AST, ALT, and others between the two groups either.

Table 1

Basic characteristics of patients in two groups before propensity matching.
Parameter	DAPA users (n = 2,350)	Control (n = 16,251)	P-value
Baseline characteristics
Age, years (IQR)	66 (59–72)	66 (59–73)	0.077
Female gender, n (%)	601 (25.57)	5,110 (31.44)	0.078
BMI, kg/m²	25.69 (23.70−27.99)	25.54 (23.44–27.78)	0.230
SBP, mmHg	135 (120–148)	135 (121–148)	0.979
DBP, mmHg	79 (68–86)	79 (68–87)	0.255
HR, bpm	74 (66–82)	74 (65–83)	0.281
Comorbidities
Smoking, n (%)	931 (39.62)	7,056 (43.42)	0.049
Drinking, n (%)	790 (33.62)	6,073 (37.37)	0.211
Hypertension, n (%)	1,274 (54.21)	10,194 (62.74)	0.884
Dyslipidemia, n (%)	1,481 (63.02)	12,088 (74.38)	0.119
COPD, n (%)	131 (5.57)	909 (5.59)	0.123
Angina, n (%)	664 (28.26)	4,794 (29.50)	0.004
Prior PCI, n (%)	402 (17.11)	2,851 (17.54)	0.015
Prior CABG, n (%)	29 (1.23)	228 (1.40)	0.939
Prior MI, n (%)	288 (12.26)	2,026 (12.47)	0.032
Prior CI, n (%)	70 (2.98)	492 (3.03)	0.312
AF, n (%)	63 (2.68)	377 (2.32)	0.032
HF, n (%)	116 (4.94)	749 (4.61)	0.029
Laboratory variables
eGFR, ml/min/1.73 m²	86.20 (67.73−106.31)	85.41 (66.95−105.49)	0.109
HbA1c, %	6.80 (6.20–7.80)	7.10 (6.10–8.10)	0.097
hs-TNI, pg/mL	4.50 (0.13–12.70)	0.55 (0.01−7.00)	0.003
CK, U/L	75.00 (56.00−105.00)	73.00 (52.00−107.00)	0.061
CK-MB, U/L	1.30 (0.90–2.10)	1.40 (0.90–2.30)	0.136
Total cholesterol, mg/dL	134.38 (111.76−161.64)	134.96 (113.69−162.03)	0.069
LDL-c, mg/dL	74.63 (57.62–97.84)	75.02 (56.84−99.00)	0.085
HDL-c, mg/dL	40.22 (34.42–47.18)	40.22 (34.42–47.56)	0.328
Triglyceride, mg/dL	45.24 (31.71–63.03)	47.18 (34.03–66.51)	0.182
Hemoglobin, g/L	16.00 (124.00−146.00)	135.08 ± 16.58	0.127
C-reactive protein, mg/L	0.68 (0.30–2.10)	0.60 (0.20–1.90)	0.121
BUN, mg/dL	15.49 (12.60−19.16)	15.23 (12.54–18.68)	0.078
ALT, U/L	18.00 (13.00–26.00)	18.00 (13.00–26.00)	0.545
AST, U/L	19.00 (16.00–24.00)	18.00 (15.00–23.00)	0.207
Medications, n (%)
Metformin	862 (36.68)	6,808 (41.89)	0.704
Sulfonylureas	129 (5.49)	1,160 (7.14)	0.183
DPP−4i	278 (11.83)	1,934 (11.90)	0.022
GLP−1RA	87 (3.70)	512 (3.15)	0.007
Glitazone	56 (2.38)	339 (2.09)	0.052
Insulin	460 (19.57)	3206 (19.73)	0.002
Anti platelets	1,876 (79.83)	14,734 (90.67)	0.044
Anti coagulation	47 (2.00)	259 (1.59)	0.018
ACEI	98 (4.71)	953 (5.86)	0.055
ARB	1,096 (46.64)	7,113 (43.77)	< 0.000
β-blockers	1,165 (49.57)	8,129 (50.02)
CCB	701 (29.83)	5,641 (34.71)	0.802
Diuretics	463 (19.70)	3,021 (18.59)	< 0.000
Statins	1,845 (78.51)	14,280 (87.87)	0.001
Ezetimibe	500 (21.28)	3,082 (18.96)	< 0.000
DAPA, Dapagliflozin; BMI, Body Mess Index; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; HR, Heart Rate; COPD, Chronic Obstructive Pulmonary Disease; PCI, Percutaneous Coronary Intervention; CABG, Coronary Artery Bypass Grafting; MI, Myocardial Infarction; CI, Cerebral Infarction; AF, Atrial Fibrillation; HF, Heart Failure; eGFR, estimated Glomerular Filtration Rate; HbA1c, glycated Hemoglobin A1c; hs-TnI, high-sensitivity Troponin I; CK, Creatine Kinase; CK-MB, Creatine Kinase-MB; LDL-c, Low-Density Lipoprotein Cholesterol; HDL-c, High-Density Lipoprotein Cholesterol; BUN, Blood Urea Nitrogen; ALT, Alanine Aminotransferase; AST, Aspartate Aminotransferase; DPP-4i, Dipeptidyl Peptidase-4 inhibitor; GLP-1RA, Glucagon-like Peptide-1 Receptor Agonist; ACEI, Angiotensin-Converting Enzyme Inhibitor; ARB, Angiotensin Receptor Blocker; CCB, Calcium Channel Blocker.

Table 2

Basic characteristics of patients in two groups in propensity-matched dataset.
Parameter	DAPA users (n = 2,071)	Control (n = 2,071)	P-value
Baseline characteristics
Age, years	66 (59–72)	66 (58–72)	0.490
Female gender, n (%)	601 (29.02)	549 (26.51)	0.071
BMI, kg/m²	26.69 (23.74–27.99)	25.71 (23.59–27.99)	0.620
SBP, mmHg	135 (121−148.5)	134 (120–148)	0.999
DBP, mmHg	79 (69–86)	79 (67–87)	0.108
HR, bpm	74 (66–82)	74 (64–83)	0.863
Comorbidities
Smoking, n (%)	931 (44.95)	964 (46.55)	0.303
Drinking, n (%)	790 (38.15)	832 (40.17)	0.181
Hypertension, n (%)	1,274 (61.52)	1,232 (59.49)	0.182
Dyslipidemia, n (%)	1,481 (71.51)	1,521 (73.44)	0.164
COPD, n (%)	131 (6.33)	108 (5.21)	0.125
Angina, n (%)	664 (32.06)	650 (31.39)	0.640
Prior PCI, n (%)	402 (19.41)	374 (18.06)	0.265
Prior CABG, n (%)	29 (1.40)	28 (1.35)	0.894
Prior MI, n (%)	288 (13.91)	238 (11.49)	0.020
Prior CI, n (%)	70 (3.38)	60 (2.90)	0.373
AF, n (%)	63 (3.04)	56 (2.70)	0.515
HF, n (%)	116 (5.60)	92 (4.44)	0.088
Laboratory variables
eGFR, ml/min/1.73 m²	86.17 (67.28−106.43)	87.19 (68.53−107.65)	0.647
HbA1c, %	6.90 (6.20–7.90)	7.10 (6.20–8.10)	0.066
hs-TNI, pg/mL	4.80 (1.04–13.59)	0.94 (0.01–7.59)	0.063
CK, U/L	75.00 (56.00−104.00)	73.00 (53.00−109.00)	0.045
CK-MB, U/L	1.30 (0.90–2.10)	1.40 (0.90–2.30)	0.229
Total cholesterol, mg/dL	133.02 (110.60−160.09)	134.18 (112.92−161.64)	0.700
LDL-c, mg/dL	73.86 (56.46–96.49)	75.02 (56.84−99.00)	0.595
HDL-c, mg/dL	39.83 (34.42–46.79)	39.44 (33.64–47.18)	0.233
Triglyceride, mg/dL	45.63 (32.10−63.23)	47.56 (34.80–66.90)	0.049
Hemoglobin, g/L	137.00 (124.50–147.00)	137.00 (126.00−148.00)	0.547
C-reactive protein, mg/L	0.70 (0.30–2.19)	0.60 (0.20−2.00)	0.408
BUN, mg/dL	15.74 (12.85–19.54)	15.34 (12.67–18.83)	0.076
ALT, U/L	18.00 (13.00–26.00)	18.00 (13.00–26.00)	0.775
AST, U/L	19.00 (16.00–24.00)	18.00 (15.00–23.00)	0.294
Medications, n (%)
Metformin	862 (41.62)	856 (41.33)	0.850
Sulfonylureas	129 (6.23)	138 (6.66)	0.569
DPP−4i	278 (13.42)	222 (10.72)	0.008
GLP−1RA	87 (4.20)	68 (3.28)	0.120
Glitazone	56 (2.70)	35 (1.69)	0.026
Insulin	460 (22.21)	419 (20.23)	0.119
Anti platelets	1,876 (90.58)	1,852 (89.43)	0.214
Anti coagulation	47 (2.27)	42 (2.03)	0.592
ACEI	98 (4.73)	110 (5.31)	0.393
ARB	1096 (52.92)	905 (43.70)	< 0.000
β-blockers	1,165 (56.25)	1,019 (49.20)	< 0.000
CCB	701 (33.85)	694 (33.51)	0.818
Diuretics	463 (22.36)	372 (17.96)	< 0.000
Statins	1845 (89.09)	1,793 (86.58)	0.013
Ezetimibe	500 (24.14)	386 (18.64)	< 0.000

Before PSM, the unadjusted ORs of patients with CI-AKI_ESUR were 59.8% lower in the dapagliflozin user group [OR 0.402, 95%CI 0.322–0.501, P < 0.000] compared with the control group. Correlation analysis using KDIGO definition also rendered similar results [OR 0.306, 95% CI 0.235–0.399, P < 0.000]. After PSM, the adjusted OR of CI-AKI_ESUR remained 57.3% lower in the dapagliflozin group [OR 0.427, 95% CI 0.329–0.554, P < 0.000] than the control group. We also conducted subgroup analyses for different operation methods, including PCI, CAG and CCTA. The unadjusted and adjusted point estimates were qualitatively similar to the overall results. Results are shown in Table 3.

Table 3

Renal outcomes in the dapagliflozin group and control group.
Parameter	Unmatched population			Matched population
Parameter	OR	95% CI	P-value	OR	95% CI	P-value
CI-AKI_ESUR
Total	0.402	0.322–0.501	< 0.000	0.427	0.329–0.554	< 0.000
PCI	0.432	0.320–0.582	< 0.000	0.503	0.348–0.726	< 0.000
CAG	0.384	0.275–0.535	< 0.000	0.381	0.261–0.559	< 0.000
CCTA	0.125	0.016–0.947	< 0.000	0.119	0.013–1.067	0.029
CI-AKI_KDIGO
Total	0.306	0.235–0.399	< 0.000	0.316	0.234–0.427	< 0.000
PCI	0.319	0.222–0.458	< 0.000	0.354	0.232–0.540	0.006
CAG	0.310	0.210–0.458	< 0.000	0.306	0.197–0.473	< 0.000
CCTA	0.833	0.780–0.891	< 0.000	0.408	0.291–0.572	< 0.000
CAG, Coronary Angiography; CCTA, Coronary Computed Tomography Angiography; OR, Odd Ratio; CI, Confidence Interval.

Meta-analysis of cohorts

Study Selection. Including the present study, we considered 6 studies with up to a total of 1,933 T2DM patients for meta-analysis. Data extraction flow was detailed in Additional File: PRISMA 2020 flow diagram. Initially, we conducted a meta-analysis, including 6 cohort studies.^{13, 14, 19–22}

Study Characteristics. The characteristics of the included studies are provided in Additional File: Supplementary File eTable 2. Of the 6 studies in this meta-analysis, two were prospective cohort studies (PCS)^{19, 13} and four were retrospective cohort studies (RCS).^{13, 14, 19, 22} Regarding outcome treatment, one study used both ESUR and KDIGO criteria simultaneously.¹³ Two studies used the ESUR criteria.^{14, 19} One article used the KDIGO criteria.²¹ Another two articles adopted other standards.^{20, 22}

GRADE assessment. We upgraded the level of CoE as all the studies included in the meta-analysis showed a low risk of bias. For details, please refer to the Additional File: Supplementary File eTable 3. Indirectness (the included studies compared similar interventions, similar populations, and similar outcomes), imprecision (this meta-analysis included 6,075 patients with diabetes undergoing CAG or PCI, 2,735 SGLT2i users, and 3,340 events of CI-AKI), publication bias, and inconsistency (I² = 0) did not impact significantly the CoE. We assessed the CoE according to GRADE criteria as moderate.

Meta-analysis. Due to the different definition criteria of the outcome indicator CI-AKI in the included studies, some studies selected both ESUR and KDIGO criteria. This meta-analysis conducted two sets of analyses. In one set of analyses, when a study had both standards simultaneously, the results corresponding to the ESUR standard were selected for inclusion in the meta-analysis (Primary Outcome A). In the other set of analyses, when a study had both standards simultaneously, the results corresponding to the KDIGO criteria were selected for inclusion in the meta-analysis (Primary Outcome B).

Primary Outcomes. Among 6,075 patients in the 7 cohort studies, the use of SGLT2i were associated with significantly reduced CI-AKI outcomes [Primary Outcome A: RR 0.42, 95%CI 0.35–0.52, P < 0.000; Primary Outcome B: RR 0.37, 95%CI 0.30–0.45, P < 0.000] in T2DM patients after PCI/CAG/CCTA. The results are shown in detail in Fig. 2A and B.

Secondary Outcomes. In this meta-analysis, four included studies used the ESUR criteria for result statistics. A subgroup analysis was conducted based on the outcome treatment with the ESUR criteria. The results showed that SGLT2i could significantly reduce the incidence of CI-AKI_ESUR [RR 0.43, 95%CI 0.35–0.53, P < 0.000]. Three included studies used the KDIGO criteria for result statistics. A subgroup analysis was conducted based on the outcome treatment with the KDIGO criteria, and the results indicated that SGLT2i could significantly reduce the incidence of CI-AKI_KDIGO [RR 0.36, 95%CI 0.28–0.47, P < 0.000]. Please refer to Additional File: Supplementary File eFigure 1 (A, B) in the attachment for details.

Publication Bias. The funnel plot of the included studies in our final metaanalysis did not suggest a publication bias. The Funnel plot of the included studies in the meta-analysis on the effect of developing CI-AKI after PCI/CAG/CCTA were shown in Additional File: Supplementary File eFigure 2 (A, B).

Key Results

This large, real-world comparative effectiveness study of SGLT2i in a Chinese population with T2DM and CCS in a single medical institution comprehensively evaluated the benefits of SGLT2i on CI-AKI. We found that dapagliflozin was associated with a much lower risk of CI-AKI in patients with T2DM after PCI/CAG/CCTA no matter using ESUR or KDIGO criteria. Moreover, across all pre-specified subgroups, whether dapagliflozin is administered prior to PCI, CAG, or CCTA, it can significantly reduce the occurrence risk of CI-AKI. The meta-analysis of the same type of cohort studies further confirmed the main result of this study, that is, SGLT2i can significantly reduce the risk of CI-AKI in patients with T2DM and CCS undergoing angiography.

Comparison with Previous Studies

Our study demonstrated that SGLT2i significantly reduce the risk of CI-AKI by up to 6.38% in patients with T2DM undergoing PCI/CAG/CCTA, compared to those not using any SGLT2i. This finding is consistent with several previous studies that have shown the potential nephroprotective effects of SGLT2i in this patient population.

However, there are some differences in the study populations and the definition of CI-AKI. For example, Hua et al.¹³ conducted a study on patients with T2DM undergoing PCI and defined CI-AKI based on the ESUR and KDIGO criteria. They found that SGLT2 inhibitors were associated with a lower risk of CI-AKI through a propensity - matched analysis, which is consistent with our finding.

Paolisso et al.¹⁴ And Çabuk et al.¹⁹ focused on diabetic patients with AMI undergoing PCI and used ESUR criteria. They found that SGLT2i users had a lower rate of CI-AKI, especially in patients without chronic kidney disease, supporting the nephroprotective effect of SGLT2i.

Özkan et al.²⁰ specifically studied diabetic patients with non-ST segment elevation myocardial infarction (NSTEMI) and defined CI-AKI as a 0.5 mg/dL (absolute) or 25% (relative) increase in creatinine value within 48 h, an increase in creatinine level of more than 1.5 times the baseline within 7 days, or a urinary output of less than 0.5 mL/kg/h for at least 6 h after using the contrast agent compared to its level before the procedure. They found that the use of SGLT2i significantly reduced the risk of CI-AKI, which is in line with our conclusion.

Our study differs from some previous studies in terms of study design. For example, Bernardini et al.¹⁵ included patients undergoing PCI and divided them into three groups: those treated with new-antidiabetic drugs (including SGLT2 inhibitors), those treated with traditional antidiabetic drugs, and non-diabetic patients. They found that patients treated with new-antidiabetic drugs had a similar incidence of CI-AKI compared to non-diabetic patients, suggesting a possible protective role of these drugs.

The study by Feitosa et al.²¹ was a randomized controlled trial (RCT) that aimed to evaluate the safety of empagliflozin in diabetic patients submitted to elective PCI regarding kidney function. Although they found that the use of empagliflozin was safe regarding kidney function, the incidence of CI-AKI was similar between the empagliflozin group and the control group. Our study, on the other hand, is a meta-analysis that combines the results of multiple studies, providing a more comprehensive assessment of the effect of SGLT2 inhibitors on CI-AKI.

Our study is consistent with previous studies that have shown the potential nephroprotective effects of SGLT2i in patients with T2DM undergoing angiography. However, further studies are needed to confirm our findings and to explore the optimal dose, type, and duration of SGLT2 inhibitor therapy to prevent CI-AKI.

Study Limitations

Several limitations of this study should be acknowledged. First, this was a single-center study and sample selection bias was inevitable. Besides, the construction of the study model was based on a cohort study with the risk of observation and confounding biases, which were minimized by applying the PSM protocol. Furthermore, as an observational study, some information was not available, such as dosage of contrast agent. To reduce the research bias caused by the unavailability of this data, we conducted a subgroup analysis of the types of angiography operations, namely, PCI, CAG, or CCTA.

Our study provided more information on the protective effect of SGLT2i on CI-AKI in patients with T2DM after angiography. In real-world patients, SGLT2i was associated with much lower CI-AKI risk no matter undergoing PCI or CAG or CCTA.

Author Acknowledgements

None.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships.

Funding

This work was financially supported by National High Level Hospital Clinical Research Funding (Grant number: BJ-2023-199).

Author Contribution

Deping LIU, Xin HU, Pengfei JIN and Zinan ZHAO designed the research. Tianqi ZHANG, Yatong ZHANG, Ming LAN and Chao TIAN performed experiments and collected data. Chenguang YANG, Chi ZHANG and Zinan ZHAO analyzed the data. Zinan ZHAO wrote the manuscript. Deping LIU, Pengfei JIN, and Zinan ZHAO participated in the discussion of the results. All authors have read and approved the final manuscript.

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No competing interests reported.

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Protective Effect of SGLT2i on contrast-induced AKI after Angiography in Patients with Type 2 Diabetes Mellitus and Chronic Coronary Syndrome: A 6-year Ambispective Cohort Study and Meta-analysis

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Abstract

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INTRODUCTION

MATERIALS AND METHODS

Study design and data sources

Patient recruitment criteria

Definition of Outcome

Statistical analysis

Ethics and Trial registration

Meta-analysis

RESULTS

Cohort study

Meta-analysis of cohorts

DISCUSSION

Key Results

Comparison with Previous Studies

Study Limitations

CONCLUSION

Declarations

Author Acknowledgements

Conflict of interest

Funding

Author Contribution

References

Additional Declarations

Supplementary Files

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