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Review

Impact of SGLT2 Inhibitors on Mortality Across Different Populations: A Systematic Review and Meta-Analysis

by
Dana Emilia Movila
1,2,
Alexandru Catalin Motofelea
3,*,
Simona Ruxanda Dragan
1,2,
Adalbert Schiller
3,
Adina Ionac
4,
Nadica Motofelea
5 and
Florina Caruntu
6,7
1
University Clinic of Internal Medicine and Ambulatory Care, Prevention and Cardiovascular Recovery, Department VI-Cardiology, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
2
Research Centre of Timisoara Institute of Cardiovascular Diseases, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
3
Centre for Molecular Research in Nephrology and Vascular Disease/MOL-NEPHRO-VASC, “Victor Babes” University of Medicine and Pharmacy Timisoara, 300041 Timisoara, Romania
4
Department of Cardiology, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
5
Department of Obstetrics and Gynecology, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
6
First Department of Internal Medicine, Medical Semiology II, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
7
Multidisciplinary Heart Research Center, “Victor Babes” University of Medicine and Pharmacy, 300041 Timisoara, Romania
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2026, 27(7), 3168; https://doi.org/10.3390/ijms27073168
Submission received: 5 February 2026 / Revised: 15 March 2026 / Accepted: 20 March 2026 / Published: 31 March 2026
(This article belongs to the Special Issue Effects of Bioactive Compounds in Cardiovascular and Neurological Diseases)
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Abstract

Sodium-glucose cotransporter-2 (SGLT2) inhibitors offer glucose-lowering, cardio-protective and reno-protective properties. Mortality rates constitute a central endpoint for understanding the overall clinical value of SGLT2 inhibitors. This systematic review and meta-analysis aims to compare mortality outcomes associated with SGLT2 inhibitors across different populations. A systematic search was performed in four databases—PubMed, Scopus, Web of Science (WOS) and Cochrane CENTRAL—in March 2025. We strictly included randomized controlled trials (RCTs) that compared patients who received SGLT2is to control patients regarding mortality outcomes. All-cause mortality up to one year, all-cause mortality more than one year, cardiovascular mortality, renal mortality and in-hospital mortality were the extracted outcomes. Finally, RevMan (5.4) was adopted for meta-analysis, and OpenMeta analyst software was adopted for meta-regression. Fifty clinical trials met the eligibility criteria of the current systematic review and meta-analysis. SGLT2 inhibitors significantly reduced all-cause mortality in studies with follow-up of up to one year (RR = 0.89, 95% CI [0.80–0.99], p = 0.03). This early survival benefit was primarily driven by the subgroup of patients treated during acute cardiac decompensation (RR = 0.76, 95% CI [0.60–0.97], p = 0.03). Furthermore, long-term follow-up beyond one year showed a significant reduction in all-cause mortality (RR = 0.89, 95% CI [0.85–0.94], p < 0.0001), particularly among patients with chronic heart failure, chronic kidney disease (CKD), and diabetes mellitus (DM) with established cardiovascular disease (CVD) (following sensitivity analyses). Cardiovascular mortality was also significantly reduced overall (RR = 0.88, 95% CI [0.84–0.94], p < 0.0001), with the greatest benefit observed in chronic heart failure and CKD subgroups. SGLT2 inhibitors as a class provide a consistent and significant reduction in all-cause mortality across both short-term (up to one year) and long-term follow-up. The early survival benefit is particularly evident when initiated during acute cardiac decompensation, while the long-term benefit extends to chronic heart failure, CKD, and high-risk DM. Future well-designed trials are needed to address the impact of less-explored SGLT2 inhibitors and understudied populations.

1. Introduction

Sodium-glucose cotransporter-2 (SGLT2) inhibitors have emerged as a treatment for various medical conditions in the past decade, due to their glucose-lowering, cardio-protective and reno-protective properties [1]. Canagliflozin was the first SGLT2 inhibitor to be approved by the United States Food and Drug Administration (US FDA) for the treatment of type 2 diabetes mellitus (DM) hyperglycemia in 2013 [2]. In addition to canagliflozin, various SGLT2 inhibitors were approved in subsequent years, such as empagliflozin, dapagliflozin and ertugliflozin [3]. In 2021, dapagliflozin was the first SGLT2 inhibitor to be approved by the US FDA for chronic kidney disease (CKD) regardless of diabetes/hyperglycemia status [4]. In 2020, the US FDA approved dapagliflozin for adult patients suffering from heart failure with reduced ejection fraction (HFrEF) regardless of diabetes/hyperglycemia status [5].
The American Diabetes Association (ADA) currently recommends SGLT2 inhibitors as a first choice for patients with heart failure, patients with atherosclerotic cardiovascular disease and those at high risk of cardiovascular diseases [6]. SGLT2 inhibitors are also recommended by the European Society of Cardiology (ESC) and the ACC/AHA/HFSA 2022 Heart Failure Guideline as a class I therapy for HFrEF [7,8,9]. The BMJ CKD SGLT2 inhibitors guidelines strongly recommended the class for adults at high or very-high risk of CKD progression and complications [10]. Data from 2015 and 2020 indicated that 9,900,981 individuals in the United States met the KDIGO guidelines as eligible patients for SGLT2 inhibitors [11]. In 2020, the KDIGO guidelines recommended SGLT2 inhibitors for patients with CKD and type 2 DM; however, the eligibility criteria were expanded in 2024 to include any adult patient with CKD, irrespective of glycemic status [12,13]. SGLT2 inhibitors have been endorsed as a part of the treatment protocol during acute cardiac decompensation [14]. Additionally, the class has been investigated as an add-on therapy in critically ill and COVID-19 patients [15,16,17].
Mortality rates constitute a central endpoint for understanding the overall clinical value of SGLT2 inhibitors as an emerging treatment class. A previously published systematic review and meta-analysis concluded that SGLT2 inhibitor therapy significantly reduced morbidity and mortality among patients with cardiovascular and renal diseases [18]. The growing literature investigating the effects of SGLT2 inhibitors across diverse populations, along with the guidelines expanding the eligibility criteria for SGLT2 inhibitor therapy, has warranted the need for an updated meta-analysis. Accordingly, this study aims to conduct an up-to-date systematic review and double-arm meta-analysis to compare mortality outcomes associated with SGLT2 inhibitors across different populations, with subgroup analyses evaluating how mortality effects differ according to the underlying disease status.

2. Methods

2.1. Protocol and Registration

The current systematic review and meta-analysis concerning the effect of sodium-glucose cotransporter-2 inhibitors (SGLT2is) on mortality outcomes among different populations was registered with PROSPERO (CRD420261281179). This systematic review was designed and reported in alignment with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines [19].

2.2. Literature Search

We systemically searched four electronic databases including PubMed, Web of Science, Scopus and Cochrane CENTRAL for research work related to mortality outcomes among populations who have received SGLT2is. Our electronic search was conducted on 12 March 2026, using the following search strategy: (SGLT2 OR SGLT-2 OR “sodium glucose transport” OR “sodium-glucose transport” OR “sodium glucose cotransporter” OR “sodium-glucose cotransporter” OR “sodium glucose co-transporter” OR “sodium-glucose co-transporter” OR Empagliflozin OR Dapagliflozin OR Canagliflozin OR Ertugliflozin OR Sotagliflozin OR Ipragliflozin OR Luseogliflozin OR Tofogliflozin OR Bexagliflozin OR Licogliflozin) AND (Mortality OR mortalities OR death* OR Fatality). The detailed search strategy for each database is outlined in Supplementary Table S1.

2.3. Study Selection

EndNote X9, the reference manager software, was adopted to remove duplicates, keeping only one original record. The final set of records was imported to Microsoft Excel, where two authors independently screened titles and abstracts of these records. The full texts of records that were potentially eligible for inclusion were sought for retrieval to be further examined for eligibility. Clinical trials that compared patients who received SGLT2is to control patients regarding mortality outcomes were considered eligible for inclusion. Excluded studies included review articles, observational studies, protocols, studies written in languages other than English, conference abstracts, studies with no available full texts, and studies that did not report mortality as a separate outcome suitable for pooling as risk ratios. In addition, studies in which the entire population initially received SGLT2is and then comparisons were made between adherent and non-adherent patients were excluded. Disagreements were resolved through discussion with a senior author.

2.4. Data Extraction

General characteristics of the included studies, baseline characteristics of their population and mortality outcomes were extracted to a Microsoft Excel sheet by two authors independently. General characteristics included last name of the first author, year of publication, trial name, the country/countries where the trial was carried out, the included population of each study and SGLT2i intervention details along with control details and number of included participants in each study group. Baseline characteristics included age, sex, weight, body mass index (BMI), smoking status and the reported comorbidities. All-cause mortality up to one year, all-cause mortality more than one year, cardiovascular mortality, renal mortality and in-hospital mortality were extracted. For temporal stratification, follow-up durations of exactly 12 months (or 52 weeks) and under were categorized as short-term (up to one year). Follow-up durations strictly greater than 12 months were categorized as long-term (more than one year).

2.5. Analytical Approach

Double-arm meta-analysis was conducted using RevMan 5.4 software. Random-effect model was the adopted model for all outcomes because different populations were included in the current meta-analysis. Outcomes were pooled as risk ratios and 95% confidence intervals (CIs). Heterogeneity between studies was concluded whenever χ2 test showed a p value less than 0.1. By removing one study in each scenario, leave-one-out test was adopted to resolve heterogeneity between studies in a specific outcome or within subgroups. Subgroup analyses were conducted according to the specific SGLT2i used in each study and the population receiving the SGLT2i intervention, as defined by the inclusion criteria of the included studies. A p value below 0.05 was considered a statistically significant finding [20]. Open Meta-Analyst software [21] was also used to perform meta-regression analyses for the incidence of mortality based on the mean differences in baseline weight and BMI values between study groups. Means and standard deviations of weight and BMI were estimated, whenever applicable, according to Luo et al. (2018) [22] and Wan et al. (2014) [23] for inclusion in the meta-regression models. If the population of a given study exhibited skewness according to Shi et al. (2023) [24] regarding weight or BMI, that study was excluded from the meta-regression model for the corresponding variable. Potential publication bias and small-study effects were evaluated via visual inspection of funnel plots and Egger’s regression test. In accordance with Cochrane methodological guidelines [25,26], these assessments were strictly reserved for meta-analyses including 10 or more studies, as tests for asymmetry are substantially underpowered to distinguish chance from true asymmetry when fewer studies are included.

Quality Assessment

The quality of included clinical trials was assessed using either Cochrane risk-of-bias tool for randomized trials (RoB2) [27] or Risk Of Bias In Non-randomized Studies—of Interventions (ROBINS-I) tool [28] based on the design of each trial. The domains of the suitable tool were assessed for each included study by two authors independently, and the lead author resolved conflicts. The five domains of RoB2 domains were assessed for each randomized clinical trial, including (1) randomization process, (2) deviations from intended interventions, (3) missing outcome data, (4) measurement of the outcome and (5) selection of the reported result. The signaling questions were answered as yes (Y), probably yes (PY), no (N), probably no (PN) or no information (NI). Bias in each domain was judged accordingly as high risk, low risk or some concerns. The seven domains of ROBINS-I were also assessed for each non-randomized clinical trial by two independent authors as well, including (1) bias due to confounding, (2) bias in the selection of participants, (3) bias in classification of the intervention, (4) bias due to deviations from intended interventions, (5) bias due to missing outcome data, (6) bias in measurement of the outcome, and (7) bias in selection of the reported results.

3. Results

3.1. Data Collection and Study Selection

Our systematic search retrieved 24,465 results from different databases, which was reduced to 15,905 records after duplicate records were removed. After screening of the titles and abstracts of the 15,905 records, only 1425 were eligible for full-text screening. Finally, 50 reports were included after data synthesis [15,16,17,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75]. The detailed selection process is illustrated in the PRISMA flow diagram (Figure 1).

3.2. Characteristics of the Included Studies

All of the included studies were clinical trials with 50 randomized controlled trials [15,16,17,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74]. The included studies adopted various SGLT2 inhibitors including dapagliflozin (n = 24) [17,36,38,39,40,41,44,46,52,53,54,56,57,58,59,61,63,64,67,71,72,75], empagliflozin (n = 17) [16,29,31,34,37,45,49,50,51,55,60,65,66,68,69,70,73], canagliflozin (n = 2) [43,62], sotagliflozin (n = 2) [32,33], tofogliflozin (n = 2) [42,47], ertugliflozin (n = 1) [35], ipragliflozin (n = 1) [74] and janagliflozin (n = 1) [52]. Patients in one study adopted various SGLT2 inhibitors instead of a single drug, with no outcome data regarding each drug separately [48].
The included studies included diverse populations including acute cardiac decompensation (n = 17) [29,33,36,37,38,40,44,53,55,58,65,68,69,70,72,75], chronic heart failure (n = 11) [31,34,45,51,54,56,57,59,60,61,64,67], DM or high-risk DM (n = 8) [42,43,46,47,49,52,71,74], DM with established CVD (n = 4) [35,50,73], CKD (n = 6) [30,32,39,62,68], COVID-19 (n = 3) [15,16,48], cardiac procedures (n = 2) [63,66], critically ill patients (n = 1) [17] and functional mitral regurgitation (MR) (n = 1) [41]. Summaries of the included studies and baseline characteristics are provided in Table 1 and Table 2, respectively. The reported comorbidities of the population of the included studies are presented in Supplementary Table S2.

3.3. Quality Assessment

The quality of the included RCTs was assessed using the RoB2 tool. Most of the included RCTs showed a low risk of bias; however, ten studies raised some concerns [29,36,37,43,50,53,55,58,64,72], and two studies showed a high risk of bias [40,74]. Of the ten trials that raised some concerns, four trials raised concerns regarding the randomization process [36,37,43,58], and eight trials raised concerns regarding the selection of the reported results [29,36,50,53,55,58,64,72]. Of the two trials that showed a high risk of bias, one raised some concerns regarding the randomization process and showed a high risk of bias regarding the domain of deviations from the intended outcome [40]. The other one showed a high risk of bias regarding the selection of the reported results [74]. The RoB2 summary is shown in Figure 2, while the detailed RoB2 figure for the 50 trials is provided in Supplementary Figure S1.

3.4. Mortality Outcomes

3.4.1. Mortality (Up to One Year)

Of the included studies, 34 studies [15,16,30,33,36,37,38,40,41,42,43,44,45,46,48,49,50,51,52,53,55,56,58,59,63,64,65,66,69,70,72,74,75] reported the outcome of mortality up to one year. The SGLT2 inhibitors group included 10,981 patients, while the control group included 9979 patients. The pooled risk ratio showed that SGLT2 inhibitors significantly reduced mortality as compared to the control group (RR = 0.89, 95% CI [0.80, 0.99], p = 0.03). The included studies showed no heterogeneity (I2 = 0%, p = 0.57) (Supplementary Figure S2). This significant short-term mortality benefit was maintained in a sensitivity analysis excluding the two trials with a high risk of bias (Heshmat et al. 2025 and Kaku et al. 2019) [40,74]. Kaku et al. 2019 [74] reported zero events in both arms and did not contribute statistical weight, while the exclusion of Heshmat et al. 2025 [40] did not alter the pooled estimates, which confirms that our findings are driven by high-quality RCTs (Supplementary Figure S3). In a meta-regression model, mortality up to one year showed no significant correlation with baseline weight or BMI mean difference (p = 0.630 and 0.603, respectively).
Visual inspection of the funnel plot for mortality up to one year revealed a symmetrical distribution of the included studies. Furthermore, Egger’s regression test indicated no significant small-study effects or publication bias (p = 0.734) (Supplementary Figure S4).
In a subgroup analysis based on study population, 14 studies [33,36,37,38,40,44,53,55,58,65,69,70,72,75] were included in the subgroup of acute cardiac decompensation, while the subgroup of chronic heart failure included five studies [45,51,56,59,64]. SGLT2 inhibitors significantly reduced mortality in the subgroup of acute cardiac decompensation (RR = 0.76, 95% CI [0.60, 0.97], p = 0.03). However, no significant difference was observed among the groups in the chronic heart failure group (RR = 1.65, 95% CI [0.57, 4.80], p = 0.36). No heterogeneity was observed in either subgroup (I2 = 14%, p = 0.3; I2 = 0%, p = 0.88, respectively). Two studies [45,64] of the five studies included in the subgroup of chronic heart failure showed no events in either the SGLT2 inhibitor or control groups, with no estimable RRs for them. The subgroup of DM/high-risk DM included six studies [42,43,46,49,52,74], while the subgroup of DM with established CVD included only one study [50]. Both subgroups showed no significant difference between the two groups (RR = 1.98, 95% CI [0.22, 17.59], p = 0.54; RR = 0.63, 95% CI [0.20, 1.19], p = 0.41, respectively). Five studies [42,43,46,52,74] of the six studies included in the subgroup of DM/high-risk DM showed no events in both study groups; therefore, the RRs of these studies were not estimable.
The subgroup of COVID-19/critically ill patients included three studies [15,16,48] and showed no significant difference between the two groups as well (RR = 0.93, 95% CI [0.81, 1.06], p = 0.27). Two studies [63,66] were included in the subgroup of cardiac procedures, with no significant difference between the two groups (RR = 0.89, 95% CI [0.61, 1.29], p = 0.53). Only one study [41] was included in the subgroup of functional MR, and another one [30] was included in subgroup of CKD. The RR of each one showed no significant difference between the two groups (RR = 2.00, 95% CI [0.19, 21.38], p = 0.57; RR = 6.90, 95% CI [0.36, 132.85], p = 0.20, respectively) (Supplementary Figure S5).
Another subgroup analysis was performed based on the SGLT2 inhibitor adopted in each study. The subgroups of dapagliflozin and empagliflozin included 16 [36,38,40,41,44,46,48,52,53,56,58,59,63,64,72,75] and 12 studies [16,30,37,45,49,50,51,55,65,66,69,70], respectively. The pooled RR of the dapagliflozin subgroup significantly favored it over the control (RR = 0.83, 95% CI [0.69, 1.00], p = 0.05). However, analysis of the empagliflozin subgroup did not favor either the SGLT2 inhibitor group or the control group (RR = 0.84, 95% CI [0.51, 1.38], p = 0.14). Three [46,52,64] and two [45,65] studies in the dapagliflozin and empagliflozin subgroups, respectively, showed no events in either study group; therefore, no estimable RRs were available for them. Both subgroups showed no evident heterogeneity (I2 = 0%, p = 0.81; I2 = 34%, p = 0.14, respectively).
Sotagliflozin subgroup included only one study [33], and its RR did not favor either of the two groups (RR = 0.86, 95% CI [0.63, 1.18], p = 0.36). The subgroup of multiple SGLT2 inhibitors also included one study [48], and its RR showed no significant difference between the two groups (RR = 0.89, 95% CI [0.59, 1.34], p = 0.56). Canagliflozin [43], ipragliflozin [74], janagliflozin [52] and tofogliflozin [42] included only one study each with zero events in either the intervention or the control; therefore, the risk ratio was not estimable (Supplementary Figure S6).

3.4.2. Mortality (More than One Year)

Of the included studies, 14 studies [31,32,34,35,39,47,54,57,60,62,67,68,71,73] reported the outcome of mortality more than one year. The SGLT2 inhibitors group included 45,611 patients, while the control group included 40,502 patients. The pooled risk ratio favored the SGLT2 inhibitors group over the control group (RR = 0.89, 95% CI [0.85, 0.94], p < 0.0001). The included studies were heterogeneous (I2 = 37%, p = 0.08); however, heterogeneity was resolved after removing the results of Zinman et al. 2015 (EMPA-REG OUTCOME Trial) [73] (I2 = 29%, p = 0.14). The pooled RR remained in favor of SGLT2 inhibitors after the leave-one-out test (RR = 0.91, 95% CI [0.87, 0.96], p = 0.0002) (Figure 3).
Visual inspection of the funnel plot for mortality more than one year revealed a symmetrical distribution of the included studies. Furthermore, Egger’s regression test indicated no significant small-study effects or publication bias (p = 0.1994) (Supplementary Figure S7).
In a subgroup analysis based on population, four studies [32,39,62,68] were included in the subgroup of CKD, and the pooled RR of the subgroup favored the SGLT2 inhibitors subgroup over the control group (RR = 0.86, 95% CI [0.74, 0.99], p = 0.004). The pooled studies within the subgroup were homogeneous (I2 = 52%, p = 0.1). In a meta-regression model, no significant correlation was observed between mortality more than one year and baseline BMI mean difference among patients with CKD.
Five studies [31,54,57,60,67] were included in the subgroup of chronic heart failure, while only one study [34] was included in the subgroup of acute cardiac decompensation. The pooled RR of the subgroup of chronic heart failure favored the SGLT2 inhibitors group over the control group (RR = 0.92, 95% CI [0.85, 0.99], p = 0.02), with no heterogeneity (I2 = 0%, p = 0.56), while the RR of the acute cardiac compensation study did not favor either of the two groups (RR = 0.95, 95% CI [0.77, 1.17], p = 0.62).
Each of the subgroups of DM/high-risk DM [47,71] and DM with established CVD included two studies [35,73]. One of the studies in the DM/high-risk DM subgroup showed no events in either study group; therefore, it showed no estimable RR [47]. The RR of the other study showed no significant difference between the two groups (RR = 0.93, 95% CI [0.83, 1.04], p = 0.2). The pooled RR of the subgroup of DM with established CVD showed no significant difference between the two groups (RR = 0.80, 95% CI [0.60, 1.08], p = 0.15), with high heterogeneity (I2 = 85%, p = 0.01) (Figure 4).
Another subgroup analysis was performed based on the adopted SGLT2 inhibitor in each study. Five studies [39,54,57,67,71] were included in the dapagliflozin subgroup, and another five studies [31,34,60,68,73] were included in the empagliflozin subgroup. The pooled RR of the dapagliflozin subgroup favored the SGLT2 inhibitors group over the control group, while the pooled RR of the empagliflozin subgroup did not favor either of the two groups (RR = 0.86, 95% CI [0.79, 0.94], p = 0.001; RR = 0.89, 95% CI [0.78, 1.01], p = 0.07, respectively). The dapagliflozin subgroup showed no heterogeneity, while heterogeneity was evident in the empagliflozin subgroup (I2 = 21%, p = 0.28; I2 = 64%, p = 0.02, respectively). Heterogeneity was best resolved in the empagliflozin subgroup after removing Zinman et al. 2015—EMPA-REG OUTCOME trial [73] (I2 = 0%, p = 0.86). The pooled RR did not favor either of the two groups after the leave-one-out test (RR = 0.95, 95% CI [0.88, 1.03], p = 0.25).
The subgroups of canagliflozin [62], ertugliflozin [35] and sotagliflozin [32] included only one study each, with a risk ratio that did not favor either of the two groups in each subgroup (RR = 0.83, 95% CI [0.69, 1.02], p = 0.07; RR = 0.93, 95% CI [0.80, 1.08], p = 0.33; RR = 1.00, 95% CI [0.84, 1.19], p = 1.00, respectively). The subgroup of tofogliflozin also included one study only [47], but it showed no events in either of the study groups, with no estimable RR (Figure 5).

3.5. Cardiovascular Mortality

The outcome of cardiovascular mortality was reported by 25 studies [29,31,32,33,34,35,37,39,41,44,47,50,51,57,59,60,61,62,63,67,68,70,71,73,75], with a pooled RR that favored the SGLT2 inhibitor group over the control group (RR = 0.88, 95% CI [0.84, 0.94], p < 0.0001). No heterogeneity was observed among the included studies (I2 = 0%, p = 0.51) (Supplementary Figure S8). In a meta-regression model, cardiovascular mortality showed no significant correlation with baseline BMI mean difference (p = 0.536).
Visual inspection of the funnel plot for cardiovascular mortality revealed a symmetrical distribution of the included studies. Furthermore, Egger’s regression test indicated no significant small-study effects or publication bias (p = 0.778) (Supplementary Figure S9).
In a subgroup analysis based on population, seven studies [29,33,34,37,44,70,75] were included in the subgroup of acute cardiac compensation, while the subgroup of chronic heart failure included seven studies [31,51,57,59,60,61,67]. The pooled RR of the subgroup of acute cardiac decompensation did not favor either of the two groups, while the pooled RR of the subgroup of chronic heart failure favored the SGLT2 inhibitors group over the control group (RR = 0.96, 95% CI [0.81, 1.14], p = 0.61; RR = 0.91, 95% CI [0.84, 0.98], p = 0.01, respectively). Both subgroups showed no heterogeneity between studies (I2 = 0%, p = 0.71; I2 = 0%, p = 0.82, respectively).
The subgroup of DM/high-risk DM included two studies [47,71], while the subgroup of DM with established CVD included three studies [35,50,73]. The pooled RR of both subgroups did not favor either of the two groups (RR = 0.98, 95% CI [0.83, 1.17], p = 0.85; RR = 0.75, 95% CI [0.52, 1.06], p = 0.11, respectively). One of the two studies in the subgroups of DM/high-risk DM reported no events in either study group, with no estimable RR [47]. The subgroup of DM with established CVD showed high heterogeneity (I2 = 75%, p = 0.02), which was best resolved after removing Cannon et al. 2020 (VERTIS-CV Trial) (I2 = 0%, p = 0.75) [35]. The pooled RR after the leave-one-out test favored the SGLT2 inhibitors group over the control group (RR = 0.62, 95% CI [0.50, 0.77], p < 0.0001).
The subgroup of CKD included four studies [32,39,62,68] with a pooled RR that favored the SGLT2 inhibitors group over the control group (RR = 0.85, 95% CI [0.74, 0.97], p = 0.01). No heterogeneity was observed within the subgroup (I2 = 0%, p = 0.82). In a meta-regression model, no significant correlation was observed between cardiovascular mortality and baseline BMI mean difference among patients with CKD (p = 0.787). The subgroups of cardiac procedures [63] and functional MR [41] included only one study each, with pooled RRs that did not favor either SGLT2 inhibitors or control (RR = 0.83, 95% CI [0.51, 1.37], p = 0.47; RR = 2.00, 95% CI [0.19, 21.38], p = 0.57, respectively) (Supplementary Figure S10).
Another subgroup analysis was performed based on the SGLT2 inhibitor adopted by each study. The dapagliflozin subgroup included ten studies [39,41,44,57,59,61,63,67,71,75], while the empagliflozin subgroup included ten studies [29,31,34,37,50,51,60,68,70,73]. The pooled RR of both subgroups favored the SGLT2 inhibitors group over the control group (RR = 0.92, 95% CI [0.85, 0.99], p = 0.03; RR = 0.85, 95% CI [0.73, 0.98], p = 0.03, respectively). Both subgroups showed no heterogeneity between studies (I2 = 0%, p = 0.85; I2 = 36%, p = 0.12, respectively).
The subgroups of canagliflozin [62] and ertugliflozin [35] included only one study each, while the sotagliflozin subgroup included two studies [32,33], with a risk ratio that did not favor either of the two groups in each subgroup (RR = 0.78, 95% CI [0.62, 1.00], p = 0.05; RR = 0.93, 95% CI [0.78, 1.10], p = 0.38; RR = 0.91, 95% CI [0.75, 1.09], p = 0.29, respectively). The subgroup of tofogliflozin also included one study only, but it showed no events in either of the study groups, with no estimable RR [47] (Supplementary Figure S11).

3.6. In-Hospital Mortality

Five included studies [17,36,38,48,58] reported the outcome of in-hospital mortality. The pooled RR did not favor either of the two groups (RR = 1.03, 95% CI [0.84, 1.28], p = 0.76), with no heterogeneity between studies (I2 = 0%, p = 0.58) (Supplementary Figure S12).
In a subgroup analysis based on the population who received the treatment, three studies were included in the subgroup of acute cardiac decompensation [36,38,58], while two studies were included in the subgroup of COVID-19/critical illness [17,48]. The pooled RR of both subgroups did not favor either SGLT2 inhibitors or the control (RR = 0.63, 95% CI [0.16, 2.54], p = 0.52; RR = 1.05, 95% CI [0.84, 1.30], p = 0.66, respectively), with no heterogeneity between studies within each subgroup (I2 = 27%, p = 0.24; I2 = 0%, p = 0.73, respectively) (Supplementary Figure S13).
Another subgroup analysis was performed based on the adopted SGLT2 inhibitor in each study. Four studies adopted dapagliflozin [17,36,38,58], while one study adopted multiple SGLT2 inhibitors [48]. The pooled RR did not favor the SGLT2 inhibitor group or the control group in either subgroup (RR = 1.02, 95% CI [0.80, 1.28], p = 0.90; RR = 1.14, 95% CI [0.67, 1.95], p = 0.63, respectively). The dapagliflozin subgroup showed no heterogeneity (I2 = 0%, p = 0.40) (Supplementary Figure S14).

Renal Mortality

Three studies reported the outcome of renal mortality [35,39,62]. The pooled RR did not favor either of the study groups (RR = 0.37, 95% CI [0.12, 1.14], p = 0.08). The outcome showed no heterogeneity between the included studies (I2 = 0%, p = 0.88) (Supplementary Figure S15). One of the included studies showed no events in either of the two groups, with no estimable RR [35]. The other two studies included patients with CKD: one of them adopted dapagliflozin [39], and the other adopted canagliflozin [62].

4. Discussion

The current systematic review and meta-analysis aims to provide a comprehensive review, analyzing the effect of SGLT2 inhibitors on mortality outcomes across different clinical populations. In addition to the overall pooled results of the included studies, the adoption of subgroup analyses allowed us to provide separate pooled results for each population including acute cardiac compensation, chronic heart failure, CKD, DM/high-risk DM, DM with established CVD, COVID-19/critically ill patients, cardiac procedures and functional MR. The subgroup analyses also allowed for synthesizing the pooled results for each SGLT2 inhibitor medication separately including dapagliflozin, empagliflozin, canagliflozin, ertugliflozin, janagliflozin, sotagliflozin, and tofogliflozin.
A major finding of the current updated meta-analysis is that SGLT2 inhibitors significantly reduce all-cause mortality within the first year of treatment (RR = 0.89, 95% CI [0.80, 0.99], p = 0.03). Subgroup analysis revealed that this early survival benefit is predominantly driven by patients receiving SGLT2 inhibitors in the setting of acute cardiac decompensation (RR = 0.76, 95% CI [0.60, 0.97], p = 0.03).
Similarly, the outcome of all-cause mortality more than one year showed consistent reduced mortality rates among patients who received SGLT2 inhibitors compared to control patients (RR = 0.89, 95% CI [0.85, 0.94], p < 0.0001). The consistency between the short-term and long-term outcomes could be explained by the immediate hemodynamic, diuretic, and natriuretic relief contributing to early survival in acute settings, followed by cumulative cardio-protective and reno-protective effects that sustain survival over the years [76].
A previously published meta-analysis reported that SGLT2 inhibitors significantly reduced all-cause mortality (hazard ratio (HR) = 0.86, 95% CI [0.80, 0.93]) [77]. Also, another systematic review and meta-analysis reported that SGLT2 inhibitors significantly reduced all-cause mortality among various populations (RR = 0.89, 95% CI [0.84, 0.95], p = 0.0006) [18].
While large cardiovascular outcome trials have established SGLT2 inhibitors as foundational therapies for heart failure and chronic kidney disease, individual trials are typically powered for composite endpoints rather than isolated mortality. The current meta-analysis provides incremental knowledge beyond these existing trials in several ways. First, by synthesizing data from 50 trials involving over 85,000 patients in recent years, we provide a highly powered and definitive quantification of mortality reduction as a standalone clinical endpoint. Second, our temporal stratification of up to one year versus beyond one year introduces a crucial clinical insight. It demonstrates that the survival benefits of SGLT2 inhibitors are not strictly dependent on long-term structural disease modification or cumulative renoprotection. Instead, our findings highlight a distinct early survival benefit that is particularly driven in patients with acute cardiac decompensation. This early divergence in mortality curves strongly reinforces recent shifts in clinical practice advocating the prompt in-hospital initiation of SGLT2 inhibitors during acute vulnerability rather than deferring treatment to the stable outpatient setting.
Synthesizing cardiovascular mortality outcomes in the current study revealed a significantly lower cardiovascular mortality among patients who received SGLT2 inhibitors compared to control patients (RR = 0.88, 95% CI [0.84, 0.94], p < 0.0001). A previously published meta-analysis reported a significantly lower cardiovascular mortality among diverse populations (HR = 0.8, 95% CI [0.78, 0.92]) [77]. Another more recent meta-analysis confirmed the same results, which aligned with our findings [18]. The lower cardiovascular mortality rates are attributed to the cardio-protective impact of SGLT2 inhibitors, such as decreasing preload and afterload and improving endothelial function and left ventricular function [78].
Our findings also revealed that patients who suffered from DM with established CVD showed significantly lower cardiovascular mortality (RR = 0.62, 95% CI [0.50, 0.77], p < 0.0001) following sensitivity analysis to resolve heterogeneity. These findings support the current guideline recommendations to adopt SGLT2 inhibitors for patients with atherosclerotic cardiovascular disease and those at high risk of cardiovascular diseases [6]. Conversely, patients who suffered from DM/high-risk DM showed no significant difference regarding cardiovascular mortality (RR = 0.98, 95% CI [0.83, 1.17], p = 0.85). The lack of significant difference regarding cardiovascular mortality can be attributed to the lack of statistical power or the competing risks of non-cardiovascular deaths. However, this insignificant difference warrants cautious interpretations and highlights the need for RCTs that study the effect of SGLT2 inhibitors on mortality outcomes among diabetic patients with different background illnesses.
Among patients with chronic heart failure, those who received SGLT2 inhibitors showed significantly lower all-cause mortality beyond one-year follow-up and significantly lower cardiovascular mortality (RR = 0.92, 95% CI [0.85, 0.99], p = 0.02 and RR = 0.91, 95% CI [0.84, 0.98], p = 0.01, respectively). These findings go in alignment with the current recommendations of ESC 2021, the ESC 2023 update and the ACC/AHA/HFSA 2022 guidelines to consider SGLT2 inhibitors a class I therapy, especially for HFrEF [7,8,9].
While SGLT2 inhibitors demonstrate robust mortality benefits across the general heart failure spectrum, their disease-modifying efficacy appears to be attenuated in patients with advanced heart failure. A recent study by Nuzzi et al. compared the initiation of SGLT2 inhibitors in advanced versus non-advanced HFrEF outpatients [79]. The authors found that while the drugs were highly tolerated and safe regarding kidney function, patients with advanced heart failure did not experience the significant improvements in NT-proBNP levels, left ventricular ejection fraction (LVEF), or NYHA functional class that were observed in the non-advanced cohort. This blunted response in the advanced stages is likely due to diminished biological reserves, extensive myocardial fibrosis, and extreme baseline neurohormonal activation that resists further pharmacological modulation [79]. These observational findings underscore the critical importance of early therapy initiation, as highlighted by our short-term mortality findings, to maximize survival benefits before irreversible cardiac structural alterations and end-stage disease progression occur.
Among patients with CKD, those who received SGLT2 inhibitors showed significantly lower all-cause mortality beyond one-year follow-up and significantly lower cardiovascular mortality as well (RR = 0.86, 95% CI [0.74, 0.99], p = 0.004 and RR = 0.85, 95% CI [0.74, 0.97], p = 0.01, respectively). These findings support the recent recommendation by the KDIGO 2024 guidelines to consider SGLT2 inhibitors for any adult patient with CKD, irrespective of glycemic status [13]. Meta-regression models have been conducted in the current study to explore the potential correlation between baseline weight and BMI mean difference and mortality outcomes. All of the conducted meta-regression models showed insignificant correlations including the meta-regression model that was specified for patients with CKD in correlation with baseline BMI mean difference. Future studies should consider reporting the baseline characteristics of patients with CKD, including weight, BMI and sarcopenic obesity, to allow for a comprehensive meta-regression that explores how these baseline variables can influence the impact of SGLT2 inhibitors on mortality outcomes.
The pooled results of dapagliflozin in all-cause mortality beyond one year and cardiovascular mortality were significantly in favor of dapagliflozin (RR = 0.86, 95% CI [0.79, 0.94], p = 0.001; RR = 0.92, 95% CI [0.85, 0.99], p = 0.03, respectively). Furthermore, dapagliflozin also demonstrated a significant reduction in short-term mortality up to one year (RR = 0.83, 95% CI [0.69, 1.00], p = 0.05). The findings of all-cause mortality align with the meta-analysis of Mukhopadhyay et al. 2022 [77], where dapagliflozin significantly differed from the control group (HR = 0.83, 95% CI [0.72, 0.97]. On the other hand, our findings regarding dapagliflozin in cardiovascular mortality contradict the findings of Mukhopadhyay et al. 2022, where dapagliflozin did not offer better outcomes compared to the control (HR = 0.88, 95% CI [0.78, 1.00]) [77].
In the current study, empagliflozin offered no significant difference compared to the control regarding all-cause mortality (RR = 0.89, 95% CI [0.78, 1.01], p = 0.07); however, it showed significantly lower cardiovascular mortality rates (RR = 0.85, 95% CI [0.73, 0.98], p = 0.03). The insignificant results regarding empagliflozin in all-cause mortality align with the findings of Mukhopadhyay et al. 2022 (HR = 0.86, 95% CI [0.69, 1.08]; however, the significantly lower cardiovascular mortality rates in our meta-analysis contradict those of Mukhopadhyay et al. 2022 (HR = 0.81, 95% CI [0.63, 1.03]) [77]. The rest of the included SGLT2 inhibitors showed a very limited number of studies, with minimal statistical power, which may be responsible for the insignificant findings.

Strengths and Limitations

The current systematic review offers a comprehensive, up-to-date evaluation of the literature related to the impact of SGLT2 inhibitors on mortality outcomes, incorporating meta-analysis and subgroup analyses. A major strength of this updated study is the strict exclusion of observational and non-randomized post hoc data, which ensured the strict inclusion of RCTs. Most of the included RCTs were judged as having a low risk of bias using RoB2, provided by Cochrane, which constitutes a major strength of the current work. In addition, the inclusion of diverse populations and different SGLT2 inhibitors allowed for comparison of the benefits of these interventions across various populations. In most cases, heterogeneity, when evident, was successfully resolved after leave-one-out analysis. Meta-regression was also performed as a statistical tool to explore the effect of baseline weight and BMI mean differences on mortality outcomes.
Despite these strengths, several limitations were apparent. The limited number of studies examining canagliflozin, ertugliflozin, janagliflozin, sotagliflozin, and tofogliflozin hindered the ability to draw specific conclusions and provide tailored recommendations for these interventions. Furthermore, certain populations, such as patients with structural cardiac abnormalities and those with critical illness, were rarely examined in the available clinical trials. Additionally, despite subgrouping by underlying baseline pathology, pooling diverse clinical scenarios inherently introduces clinical heterogeneity, and overall pooled estimates must be interpreted alongside disease-specific subgroup findings. Therefore, well-designed randomized controlled trials are recommended in the future to better evaluate less-studied SGLT2 inhibitors and under-represented populations.

5. Conclusions

The present strictly RCT-based systematic review and meta-analysis demonstrates that SGLT2 inhibitors, as a class, provide a consistent and significant reduction in both all-cause and cardiovascular mortality. Crucially, this survival benefit is evident not only during long-term follow-up for patients with chronic heart failure, chronic kidney disease (CKD), and high-risk diabetes mellitus but also in the short term (up to one year). The early mortality reduction is particularly pronounced when SGLT2 inhibitors are promptly initiated during acute cardiac decompensation. Furthermore, cardiovascular mortality benefits are evident across multiple clinical profiles, though the magnitude of the effect varies across subgroups and specific pharmacological agents. Future well-designed RCTs are needed to address the impact of less-explored SGLT2 inhibitors and understudied populations.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/ijms27073168/s1.

Author Contributions

D.E.M.: Conceptualization, Methodology, Data curation, Writing—original draft; A.C.M.: Conceptualization, Formal analysis, Writing—review and editing, Supervision; S.R.D.: Investigation, Data curation, Validation, Writing—review and editing; A.S.: Methodology, Resources, Writing—review and editing, Project administration; A.I.: Investigation, Data extraction, Validation, Visualization; N.M.: Software, Formal analysis, Methodology, Data curation; F.C.: Writing—review and editing, Resources, Supervision, Funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

We would like to acknowledge Victor Babes University of Medicine and Pharmacy Timișoara for their support in covering the costs of publication for this research paper.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

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Ijms 27 03168 g001
Figure 1. PRISMA flow diagram.
Figure 1. PRISMA flow diagram.
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Figure 2. Risk of Bias 2 (RoB2) summary.
Figure 2. Risk of Bias 2 (RoB2) summary.
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Figure 3. Sensitivity analysis of all-cause mortality beyond one year [31,32,34,35,39,47,54,57,60,62,67,68,71,73].
Figure 3. Sensitivity analysis of all-cause mortality beyond one year [31,32,34,35,39,47,54,57,60,62,67,68,71,73].
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Figure 4. Subgroup analysis based on population with sensitivity analysis of the subgroup of DM with established CVD [31,32,34,35,39,47,54,57,60,62,67,68,71,73].
Figure 4. Subgroup analysis based on population with sensitivity analysis of the subgroup of DM with established CVD [31,32,34,35,39,47,54,57,60,62,67,68,71,73].
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Figure 5. Subgroup analysis based on the adopted SGLT2 inhibitors with sensitivity analysis of the subgroup of empagliflozin [31,32,34,35,39,47,54,57,60,62,67,68,71,73].
Figure 5. Subgroup analysis based on the adopted SGLT2 inhibitors with sensitivity analysis of the subgroup of empagliflozin [31,32,34,35,39,47,54,57,60,62,67,68,71,73].
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Table 1. Summary of the included studies.
Table 1. Summary of the included studies.
Study ID (Trial Name)Study DesignCountry/RegionPopulationInterventionControlTotal Sample SizeFollow-Up Duration
Berg et al. 2025 (DAPA ACT HF-TIMI 68 Trial) [75]RCTMulti-national (North America, Europe)Acute heart failureDapagliflozin: 10 mg/dPlacebo24012 months
Agarwal et al. 2025 [30](CONFIDENCE Trial)RCTMulti-national (Europe, Asia, North America)Chronic kidney disease with type 2 diabetesEmpagliflozin: 10 mg/d
Finerenone: 10 or 20 mg/d		Finerenone 10 or 20 mg/d5337.0 months
Heshmat et al. 2025 [40]RCTEgyptAcute myocardial infarction (STEMI) with diabetesDapagliflozin: 10 mg/dStandard therapy541 month
Huang et al. 2025 [41] (DEFORM Trial)RCTChinaFunctional mitral regurgitationDapagliflozin: 10 mg/dGuideline-directed medical therapy1043 months
Mocan et al. 2025 [58]RCTRomaniaAcute heart failureDapagliflozin: 10 mg/d + structured intravenous furosemideStructured intravenous furosemide981 month
Raposeiras-Roubin et al. 2025 (DapaTAVI Trial) [63]RCTSpainTranscatheter Aortic Valve Implantation with a prior episode of aortic stenosis-related heart failureDapagliflozin: 10 mg/dStandard therapy122212 months
Snel et al. 2025 [66]RCTThe NetherlandsElective cardiopulmonary bypass (CPB) assisted cardiac surgeryEmpagliflozin: 10 mg/dStandard perioperative care551 week
Zhou et al. 2025 [72]RCTChinaAcute myocardial infarction with early heart failureDapagliflozin: 10 mg/dStandard therapy9812 months
Butler et al. 2024 [34](EMPACT-MI Trial)RCTMulti-national (South America, Europe, Asia, North America, Australia)High-risk patients with acute myocardial infarctionEmpagliflozin: 10 mg/dPlacebo652217.9 months
James et al. 2024 (DAPA-MI Trial) [44]RCTSweden, United KingdomAcute myocardial infarctionDapagliflozin: 10 mg/dPlacebo401711.6 months (IQR 6.8–16.9; max 29)
Kosiborod et al. 2024 [48] (ACTIV-4a Trial)RCTMulti-national (South America, Europe, North America)COVID-19 hospitalized populationDapagliflozin: 10 mg/d,
Empagliflozin: 10 mg/d,
Canagliflozin: 100 mg/d or
Ertugliflozin: 5 mg/d		Standard therapy5733.0 months
Kumar et al. 2024 [50]RCTIndiaType 2 diabetes with established cardiovascular diseaseEmpagliflozin: 10 or 25 mg/dPlacebo2501.0 month
Li et al. 2020 [52]RCTChinaType 2 diabetes patients following healthcare provider guidance around diet and physical exercise or using metformin therapyDapagliflozin: 10 mg/d
Janagliflozin: 25 or 50 mg/d		Placebo362.9 weeks
Liang et al. 2024 [53]RCTChinaAcute myocardial infarction with new-onset HFDapagliflozin (an initial dosage of 5 mg/d, which was then increased to 10 mg/d) + sacubitril/valsartanStandard therapy + sacubitril/valsartan606 months
Lin et al. 2024 [54]RCTChinaChronic heart failure (HFrEF with hyperuricemia)Dapagliflozin: 10 mg/dPlacebo20024 months
McMurray et al. 2024 [56] (DETERMINE-preserved Trial)RCTMulti-national (South America, Europe, Asia, Africa, North America)Chronic heart failure (HFpEF)Dapagliflozin: 10 mg/dPlacebo5043.7 months
McMurray et al. 2024 [56] (DETERMINE-reduced Trial) RCTMulti-national (South America, Europe, North America)Chronic heart failure (HFrEF)Dapagliflozin: 10 mg/dPlacebo3133.7 months
Pastore et al. 2024 [61] (DAPA-ECHO Trial)RCTItalyChronic heart failure (non-diabetic HFrEF/HFmrEF)Dapagliflozin: 10 mg/dOptimal Medical Therapy886 months
Tavares et al. 2024 [17] (DEFENDER Trial)RCTBrazilCritical illness/ICU populationDapagliflozin: 10 mg/dStandard therapy5074 weeks
Emara et al. 2023 [38] (DAPA-RESPONSE-AHF Trial)RCTEgyptAcute heart failureDapagliflozin: 10 mg/dPlacebo872.0 months
Liu et al. 2023 [55]RCTChinaAcute heart failureEmpagliflozin: 10 mg/dStandard therapy1052.0 months
RECOVERY Collaborative Group 2023 (RECOVERY Trial) [16]RCTMulti-national (Asia, Africa)COVID-19 hospitalized populationEmpagliflozin: 10 mg/dUsual therapy42714 weeks
EMPA-KIDNEY Collaborative Group 2023 (EMPA-KIDNEY) [68]RCTMulti-national (Asia, Europe, North America)Chronic kidney disease (with or without diabetes)Empagliflozin: 10 mg/dPlacebo660924.0 months (IQR 18.0–28.8)
Adel et al. 2022 [29]RCTIranAcute coronary syndrome with diabetesEmpagliflozin: low dosePlacebo936 months
Charaya et al. 2022 [36]RCTRussiaAcute heart failureDapagliflozin: 10 mg/dStandard therapy1021 month
Reis et al. 2022 [64]RCTPortugalChronic heart failure (non-diabetic HFrEF)Dapagliflozin: 10 mg/dOptimal Medical Therapy406 months
Solomon et al. 2022 [67] (DELIVER Trial)RCTMulti-national (South America, Europe, Asia, North America)Chronic heart failureDapagliflozin: 10 mg/dPlacebo623627.6 months (IQR 20.4–33.6)
Von Lewinski et al. 2022 [70] (EMMY Trial)RCTAustriaAcute myocardial infarctionEmpagliflozin: 10 mg/dPlacebo4766.0 months
Voors et al. 2022 [69]
(EMPULSE Trial)		RCTMulti-national (Europe, Asia, North America)Acute heart failureEmpagliflozin: 10 mg/dPlacebo5303.0 months
Anker et al. 2021 [31] (EMPEROR-Preserved Trial)RCTMulti-national (South America, Europe, Asia, Africa, North America)Chronic heart failure (HFpEF)Empagliflozin: 10 mg/dPlacebo598826.2 months (IQR 18.1–33.1)
Bhatt et al. 2021 [32] (SCORED Trial)RCTMulti-national (South America, Europe, Asia, North America)Type 2 diabetes with chronic kidney diseaseSotagliflozin: 200–400 mg/dPlacebo10,58416.0 months (IQR 12.0–20.3)
Bhatt et al. 2021 [33]
(SOLOIST-WHF Trial)		RCTMulti-national (South America, Europe, Asia, North America)Acute heart failure with diabetesSotagliflozin: 200–400 mg/dPlacebo12229.0 months
Kosiborod et al. 2021 [15] (DARE-19 Trial)RCTMulti-national (South America, Europe, North America)COVID-19 with cardiometabolic riskDapagliflozin: 10 mg/dPlacebo12502.0 months
Lee et al. 2021 [51] (SUGAR-DM-HF Trial)RCTUnited KingdomChronic heart failure (HFrEF with diabetes/prediabetes)Empagliflozin: 10 mg/dPlacebo1058.3 months
Cannon et al. 2020 [35] (VERTIS-CV Trial)RCT(blank)Type 2 diabetes with established atherosclerotic cardiovascular diseaseErtugliflozin: 5 or 15 mg/dPlacebo824642.0 months
Damman et al. 2020 [37] (EMPA-RESPONSE-AHF Trial)RCTThe NetherlandsAcute heart failureEmpagliflozin: 10 mg/dPlacebo792.0 months
Heerspink et al. 2020 [39] (DAPA-CKD Trial)RCTMulti-national (South America, Europe, Asia, North America)Chronic kidney disease (with or without diabetes)Dapagliflozin: 10 mg/dPlacebo430428.8 months (IQR 24.0–32.4)
Jensen et al. 2020 [45] (EMPIRE-HF Trial)RCTDenmarkChronic heart failure (HFrEF)Empagliflozin: 10 mg/dPlacebo1902.8 months
Katakami et al. 2020 [47] (UTOPIA Trial)RCTJapanType 2 diabetesTofogliflozin 20 mg/dConventional therapy34024 months
Packer et al. 2020 [60] (EMPEROR-Reduced Trial)RCTMulti-national (South America, Europe, Asia, North America)Chronic heart failure (HFrEF)Empagliflozin: 10 mg/dPlacebo373016 months
Shimizu et al. 2020 [65] (EMBODY Trial)RCTJapanAcute myocardial infarction with diabetesEmpagliflozin: 10 mg/dPlacebo965.5 months
Kaku et al. 2019 [74]RCTJapanType 1 diabetesIpragliflozin 50 mg/dPlacebo1745.5 months
McMurray et al. 2019 [57] (DAPA-HF Trial)RCTMulti-national (South America, Europe, Asia, North America)Chronic heart failure (HFrEF)Dapagliflozin: 10 mg/dPlacebo474418.2 months (range 0–27.8)
Nassif et al. 2019 [59] (DEFINE-HF Trial)RCTUnited StatesChronic heart failure (HFrEF)Dapagliflozin: 10 mg/dPlacebo2632.8 months
Perkovic et al. 2019 [62] (CREDENCE Trial)RCTMulti-national (South America, Europe, Asia, North America)Chronic kidney disease with type 2 diabetesCanagliflozin 100 mg/dPlacebo440131.4 months (range 0.24–54.4)
Wiviott et al. 2019 [71] (DECLARE–TIMI 58 Trial)RCTMulti-national (South America, Europe, Asia, North America)Type 2 diabetes with cardiovascular riskDapagliflozin: 10 mg/dPlacebo17,16050.4 months (IQR 46.8–52.8)
Ikeda et al. 2015 [42]RCTJapanType 2 diabetes eligible patients treated with diet and exercise alone or with diet and exercise and a stable dose of metformin Tofogliflozin: 2.5, 5, 10, 20 or 40 mg/dPlacebo3942.8 months
Kovacs et al. 2015 [49]RCTMulti-national (North America, Europe, Asia)Type 2 diabetes who were receiving pioglitazone monotherapy or pioglitazone plus metforminEmpagliflozin: 10 or 25 mg/dPlacebo4985.5 months
Zinman et al. 2015 [73] (EMPA-REG OUTCOME Trial)RCTMulti-national (South America, Europe, Asia, North America)Type 2 diabetes with established cardiovascular diseaseEmpagliflozin: 10 or 25 mg/dPlacebo702037.2 months
Ji et al. 2014 [46]RCTChina, Korea, Taiwan, IndiaType 2 diabetesDapagliflozin 5 or 10 mg/dPlacebo3935.5 months
Inagaki et al. 2013 [43]RCTJapanType 2 diabetesCanagliflozin 50, 100, 200 or 300 mg/dPlacebo3822.8 months
Abbreviations: RCT, randomized controlled trial; HF, heart failure; HFrEF, heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; HFmrEF, heart failure with mildly reduced ejection fraction; CKD, chronic kidney disease; DM, diabetes mellitus; STEMI, ST-elevation myocardial infarction; ICU, intensive care unit; CPB, cardiopulmonary bypass; COVID-19, coronavirus disease 2019; IQR, interquartile range; mg/d, milligrams per day.
Table 2. Baseline characteristics of the included studies.
Table 2. Baseline characteristics of the included studies.
Study IDTrial NameGroupAge (Year)Male n (%)Weight (kg)BMI (kg/m2)Smoking
Berg et al. 2025 [75]DAPA ACT HF-TIMI 68Dapagliflozin 10 mg/day69 [58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77]815 (66.9%) 29.0 [24.9–34.7]
Placebo68 [58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76]771 (65.2%) 29.5 [25.4–35.4]
Agarwal et al. 2025 [30]CONFIDENCEEmpagliflozin 10 mg/day + Finerenone 10 or 20 mg/day67.7 ± 10.0202 (75.1)83.0 ± 21.729.8 ± 6.7
Finerenone 10 or 20 mg/day65.5 ± 10.7203 (76.9)81.9 ± 20.329.1 ± 5.7
Heshmat et al. 2025 [40] Dapagliflozin52.1 ± 8.522 (81.5)83.4 ± 12.928.3 ± 4.217 (63)
Standard therapy56 ± 6.421 (77.8)80.7 ± 9.727.2 ± 3.514 (51.9)
Huang et al. 2025 [41]DEFORMDapagliflozin 10 mg/day61.98 ± 13.7145 (86.5) 23.74 ± 2.44
Guideline-directed medical therapy65.31 ± 13.8738 (73.1) 24.21 ± 2.42
Mocan et al. 2025 [58] Dapagliflozin 10 mg/day + structured intravenous furosemide63.63 ± 10.9540 (81.6)86.55 ± 20.35Male: 28.49 ± 5.65
Female: 27.39 ± 5.08
Structured intravenous furosemide65.31 ± 10.8242 (85.7)85.68 ± 25.33Male: 29.12 ± 9.03
Female: 23.73 ± 2.67
Raposeiras-Roubin et al. 2025 [63]DapaTAVIDapagliflozin 10 mg/day82.4 ± 5.6306 (50.6)
Standard therapy82.4 ± 5.5313 (50.6)
Snel et al. 2025 [66] Empagliflozin 10 mg/day69 ± 818 (72) 27.6 ± 3.4
Standard therapy63 ± 1022 (73) 28.2 ±5.1
Zhou et al. 2025 [72] Dapagliflozin 10 mg/day65.27 ± 11.8730 (60) 12 (24)
Standard therapy68.05 ± 9.7928 (58.33) 16 (33.33)
Butler et al. 2024 [34]EMPACT-MIEmpagliflozin 10 mg/day63.6 ± 11.02448 (75.1)
Placebo63.7 ± 10.82449 (75.1)
James et al. 2024 [44]DAPA MIDapagliflozin 10 mg/day63.0 ± 11.061631 (80.8)85.5 ± 15.87
Placebo62.8 ± 10.641579 (79.0)85.5 ± 16.54
Kosiborod et al. 2024 [48]The Accelerating COVID-19 Therapeutic Interventions and Vaccines 4 ACUTE (ACTIV-4a) trialSGLT2i72.6 ± 12.0168 (58.5) 27.7 [23.8–33.0]
Standard therapy71.0 ± 13.0165 (57.3) 28.3 [23.7–34.5]
Kumar et al. 2024 [50] Empagliflozin 10 or 20 mg/day
Placebo
Li et al. 2020 [52] Janagliflozin 25 mg/day49.0 ± 4.337 (78)69.4 ± 5.9525.3 ± 1.80
Janagliflozin 50 mg/day48.0 ± 5.558 (89)71.9 ± 9.3626.1 ± 2.42
Dapagliflozin 10 mg/day44.9 ± 6.687 (78)72.4 ± 12.0526.7 ± 2.65
Placebo46.9 ± 4.287 (78)68.8 ± 7.0424.2 ± 2.54
Liang et al. 2024 [53] Dapagliflozin + sacubitril/valsartan63 ± 12.218 (60) 25.9 ± 2.216 (53.3)
Standard therapy + sacubitril/valsartan64 ± 12.416 (53.3) 25.1 ± 2.713 (43.3)
Lin et al. 2024 [54] Dapagliflozin 10 mg/day62.3 ± 9.868 (68)
Placebo63.1 ± 10.266 (66)
McMurray et al. 2024 [56]DETERMINE-preservedDapagliflozin 10 mg/day73 [67,68,69,70,71,72,73,74,75,76,77,78]162 (64) 29 [25,26,27,28,29,30,31,32,33,34]
Placebo73 [73,74,75,76,77,78,79]158 (62.9) 28 [25,26,27,28,29,30,31,32,33]
McMurray et al. 2024 [56]DETERMINE-reducedDapagliflozin 10 mg/day69 [62,63,64,65,66,67,68,69,70,71,72,73,74,75,76]111 (71.2) 28 [24,25,26,27,28,29,30,31,32,33,34]
Placebo69 [60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76]122 (77.7) 29 [24,25,26,27,28,29,30,31,32,33]
Pastore et al. 2024 [61]DAPA ECHODapagliflozin 10 mg/day68 ± 1582 (36) 26.5 ± 314 (6)
Optimal Medical Therapy68 ± 1284 (37) 28 ± 610 (4)
Tavares et al. 2024 [17]DEFENDERDapagliflozin 10 mg/day63.3 ± 14.9139 (56) 25.1 [22.1–28.7]46 (18.5)
Standard therapy64.5 ± 15.2130 (50.2) 25.4 [22.1–29.3]40 (15.4)
Emara et al. 2023 [38]DAPA-RESPONSE-AHFDapagliflozin 10 mg/day61.1 ± 11.835 (77.8) 21 (46.7)
Placebo63.9 ± 1027 (64.3) 15 (35.7)
Liu et al. 2023 [55] Empagliflozin 10 mg/day67.42 ± 1.8130 (55.56) 23.53 ± 2.14
Standard therapy67.48 ± 1.8531 (57.41) 24.03 ± 2.08
RECOVERY Collaborative Group 2023 [16]RECOVERYEmpagliflozin61.1 (16.3)1326 (63)
Usual care61.8 (16.4)1339 (62)
The EMPA-KIDNEY Collaborative Group 2023 [68]EMPA-KIDNEY trialEmpagliflozin 10 mg/day63.9 ± 13.92207 (66.8) 29.7 ± 6.7
Placebo63.8 ± 13.92210 (66.9) 29.8 ± 6.8
Adel et al. 2022 [29] Empagliflozin55 [45.5–64]27 (60)75 [67.5–84.5]
Placebo57 [50–66.75]29 (60.4)69.5 [65–83.75]
Charaya et al. 2022 [36] Dapagliflozin72.6 ± 12.229 (58)
Standard therapy74.2 ± 11.327 (52)
Solomon et al. 2022 [67]DELIVERDapagliflozin 10 mg/day71.8 ± 9.61767 (56.4)
Placebo71.5 ± 9.51749 (55.8)
Reis et al. 2022 [64] Dapagliflozin 10 mg/day + Optimal Medical Therapy60.3 ± 11.617 (85) 17 (85)
Optimal Medical Therapy61.7 ± 14.816 (80) 11 (55)
Von Lewinski et al. 2022 [70]EMMYEmpagliflozin 10 mg/day57 [52,53,54,55,56,57,58,59,60,61,62,63,64]195 (82) 27.7 [25.3–30.3]171 (72)
Placebo57 [52,53,54,55,56,57,58,59,60,61,62,63,64,65]197 (82) 27.2 [24.9–30.2]170 (72)
Voors et al. 2022 [69]EMPULSEEmpagliflozin 10 mg/day71 [62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78]179 (67.5) 28.35 [24.54–32.46]
Placebo70 [59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78]172 (64.9) 29.08 [24.69–33.60]
Anker et al. 2021 [31]EMPEROR-PreservedEmpagliflozin 10 mg/day71.8 ± 9.31659 (55.4) 29.77 ± 5.8
Placebo71.9 ± 9.61653 (55.3) 29.90 ± 5.9
Bhatt et al. 2021 [32]SCOREDSotagliflozin 200–400 mg/day69 [63,64,65,66,67,68,69,70,71,72,73,74]2945 (55.7) 31.9 [28.1–36.2]
Placebo69 [63,64,65,66,67,68,69,70,71,72,73,74]2885 (54.5) 31.7 [28.0–36.1]
Bhatt et al. 2021 [33]SOLOIST-WHFSotagliflozin 200–400 mg/day69 [63,64,65,66,67,68,69,70,71,72,73,74,75,76]410 (67.4) 30.4 [26.3–34.3]
Placebo70 [64,65,66,67,68,69,70,71,72,73,74,75,76]400 (65.1) 31.1 [27.3–34.5]
Kosiborod et al. 2021 [15]DARE-19Dapagliflozin 10 mg/day61 ± 13.4365 (58.4) 30.6 ± 6.229 (4.6)
Placebo61.8 ± 13.5352 (56.3) 30.9 ± 6.420 (3.2)
Lee et al. 2021 [51]SUGAR-DM-HFEmpagliflozin 10 mg/day68.2 ± 11.734 (65.4) 30.9 ± 5.9
Placebo69.2 ± 10.643 (81.1) 30.4 ± 5.1
Cannon et al. 2020 [35]VERTIS CVErtugliflozin 5 or 15 mg/day64.4 ± 8.13866 (70.3) 31.9 ± 5.4
Placebo64.4 ± 81903 (69.3) 32.0 ± 5.5
Damman et al. 2020 [37]EMPA-RESPONSE-AHFEmpagliflozin 10 mg/day79 (73–83)24 (60)87 ± 23
Placebo73 (61–83)29 (74.4)83 ± 20
Heerspink et al. 2020 [39]DAPA-CKDDapagliflozin 10 mg/day61.8 ± 12.11443 (67.1)81.5 ± 20.129.4 ± 6.0283 (13.2)
Placebo61.9 ± 12.11436 (66.7)82.0 ± 20.929.6 ± 6.3301 (14.0)
Jensen et al. 2020 [45]EMPIRE-HFEmpagliflozin64 [57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73]79 (83) 29 [27,28,29,30,31,32,33]
Placebo63 [55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72]83 (87) 29 [26,27,28,29,30,31,32,33]
Katakami et al. 2020 [47]UTOPIATofogliflozin 20 mg/day61.3 ± 9.399 (58.6) 27.0 ± 5.838 (22.6)
Conventional therapy60.9 ± 9.799 (58.2) 27.0 ± 4.629 (17.1)
Packer et al. 2020 [60]EMPEROR-ReducedEmpagliflozin 10 mg/day67.2 ± 10.81426 (76.5) 28.0 ± 5.5
Placebo66.5 ± 11.21411 (75.6) 27.8 ± 5.3
Shimizu et al. 2020 [65]EMBODYEmpagliflozin 10 mg/day63.9 ± 10.438 (82.6)70.1 ± 13.725.2 ± 3.724 (52.2)
Placebo64.6 ± 11.639 (78)68.1 ± 14.425.2 ± 4.127 (54.0)
Kaku et al. 2019 [74] Ipragliflozin 50 mg/day49.7 ± 13.154 (47.0)66.06 ± 11.3924.67 ± 2.95
Placebo48.3 ± 12.827 (45.8)64.68 ± 9.0724.21 ± 2.82
McMurray et al. 2019 [57]DAPA-HFDapagliflozin 10 mg/day66.2 ± 11.01809 (76.2) 28.2 ± 6.0
Placebo66.5 ± 10.81826 (77) 28.1 ± 5.9
Nassif et al. 2019 [59]DEFINE-HFDapagliflozin 10 mg/day62.2 ± 11.095 (72.5) 30.7 [27.3, 35.9]
Placebo60.4 ± 12.098 (74.2) 30.6 [27.6, 36.4]
Perkovic et al. 2019 [62]CREDENCECanagliflozin 100 mg/day62.9 ± 9.21440 (65.4) 31.4 ± 6.2341 (15.5)
Placebo63.2 ± 9.21467 (66.7) 31.3 ± 6.2298 (13.6)
Wiviott et al. 2019 [71]DECLARE–TIMI 58Dapagliflozin 10 mg/day63.9 ± 6.85411 (63.1) 32.1 ± 6.0
Placebo64.0 ± 6.85327 (62.1) 32.0 ± 6.1
Ikeda et al. 2015 [42] Tofogliflozin 2.5 mg/day53.3 ± 10.8634 (51.5)85.23 ± 16.46531.33 ± 4.878
Tofogliflozin 5 mg/day54.8 ± 10.5331 (47.7)82.15 ± 16.34630.56 ± 5.230
Tofogliflozin 10 mg/day54.5 ± 10.7034 (51.5)83.41 ± 16.56330.4 ± 4.910
Tofogliflozin 20 mg/day56.3 ± 9.7943 (67.2)84.91 ± 17.30530.09 ± 4.652
Tofogliflozin 40 mg/day57.5 ± 9.3131 (46.3)81.68 ± 18.69230.36 ± 4.892
Placebo53.9 ± 11.1236 (54.5)83.73 ± 19.20130.37 ± 5.466
Kovacs et al. 2015 [49] Empagliflozin 10 mg/day54.7 ± 9.985 (50.6)78.0 ± 19.229.2 ± 5.6
Empagliflozin 25 mg/day54.2 ± 8.983 (50.3)78.9 ± 19.929.1 ± 5.5
Placebo54.6 ± 10.573 (44.2)78.1 ± 20.129.3 ± 5.4
Zinman et al. 2015 [73]EMPA-REG OUTCOMEEmpagliflozin 10 mg/day63.0 ± 8.6)1653 (70.5)85.9 ± 18.830.6 ± 5.2
Empagliflozin 25 mg/day63.2 ± 8.61683 (71.9)86.5 ± 1930.6 ± 5.3
Empagliflozin 10 or 25 mg/day63.1 ± 8.63336 (71.2)86.2 ± 18.930.6 ± 5.3
Placebo63.2 ± 8.81680 (72.0)86.6 ± 19.130.7 ± 5.2
Ji et al. 2014 [46] Dapagliflozin 5 mg/day53.0 ± 11.0784 (65.6)68.89 ± 11.4325.17 ± 3.29
Dapagliflozin 10 mg/day51.2 ± 9.8986 (64.7)70.92 ± 11.6425.76 ± 3.43
Placebo49.9 ± 10.8787 (65.9)72.18 ± 13.2325.93 ± 3.64
Inagaki et al. 2013 [43] Canagliflozin 50 mg/day57.4 ± 10.850 (61.0)65.77 ± 13.5626.41 ± 4.34
Canagliflozin 100 mg/day57.7 ± 10.552 (70.3)68.61 ± 14.8625.11 ± 4.13
Canagliflozin 200 mg/day57.0 ± 10.749 (64.5)68.97 ± 14.5025.61 ± 4.64
Canagliflozin 300 mg/day57.1 ± 10.155 (73.3)71.30 ± 12.1925.51 ± 4.30
Placebo57.7 ± 11.054 (72.0)72.56 ± 15.3625.89 ± 3.68
BMI, body mass index; IQR, interquartile range; kg, kilogram; m2, square meter; mg/day, milligrams per day. Data are presented as mean ± SD, median [IQR], or n (%), as reported.
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Movila, D.E.; Motofelea, A.C.; Dragan, S.R.; Schiller, A.; Ionac, A.; Motofelea, N.; Caruntu, F. Impact of SGLT2 Inhibitors on Mortality Across Different Populations: A Systematic Review and Meta-Analysis. Int. J. Mol. Sci. 2026, 27, 3168. https://doi.org/10.3390/ijms27073168

AMA Style

Movila DE, Motofelea AC, Dragan SR, Schiller A, Ionac A, Motofelea N, Caruntu F. Impact of SGLT2 Inhibitors on Mortality Across Different Populations: A Systematic Review and Meta-Analysis. International Journal of Molecular Sciences. 2026; 27(7):3168. https://doi.org/10.3390/ijms27073168

Chicago/Turabian Style

Movila, Dana Emilia, Alexandru Catalin Motofelea, Simona Ruxanda Dragan, Adalbert Schiller, Adina Ionac, Nadica Motofelea, and Florina Caruntu. 2026. "Impact of SGLT2 Inhibitors on Mortality Across Different Populations: A Systematic Review and Meta-Analysis" International Journal of Molecular Sciences 27, no. 7: 3168. https://doi.org/10.3390/ijms27073168

APA Style

Movila, D. E., Motofelea, A. C., Dragan, S. R., Schiller, A., Ionac, A., Motofelea, N., & Caruntu, F. (2026). Impact of SGLT2 Inhibitors on Mortality Across Different Populations: A Systematic Review and Meta-Analysis. International Journal of Molecular Sciences, 27(7), 3168. https://doi.org/10.3390/ijms27073168

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