Introduction: This meta-analysis aimed to investigate the effect of SGLT2 inhibitors on the prognosis of patients with heart failure (HF) or at risk of HF across different body mass index (BMI). Methods: We searched PubMed, Embase, Web of Science, and Cochrane Library for all randomized controlled trials comparing SGLT2 inhibitors with placebo in patients with HF or at risk of HF and extracted relevant data up to April 2023 for meta-analysis. Results: A total of 29,500 patients were enrolled in the selected five studies. The results showed that patients treated with SGLT2 inhibitors had lower HF hospitalization (HHF) or cardiovascular (CV) mortality compared to those taking placebo (hazard ratio [HR] = 0.73, p < 0.001). Patients taking SGLT2 inhibitors also had a lower all-cause mortality rate than those taking placebo (HR = 0.85, p = 0.017). In BMI subgroup analysis, the HHF rate in the experimental group was lower than that in the control group at BMI ≤24.9 kg/m2, 25.0–29.9 kg/m2, and ≥30.0 kg/m2. There was no significant difference in CV mortality between the two groups at BMI ≤24.9 kg/m2 (HR = 0.91, p = 0.331) and 25.0–29.9 kg/m2 (HR = 0.92, p = 0.307). However, when the BMI was ≥30.0 kg/m2, CV mortality with SGLT2 inhibitors was lower than in the control group (HR = 0.79, p = 0.002). When patients had a BMI ≤24.9 kg/m2 (HR = 0.85, p = 0.033) and 25.0–29.9 kg/m2 (HR = 0.83, p = 0.046), the all-cause mortality was lower in the experimental group than in the control group. However, there was no significant difference between the 2 groups in patients with a BMI ≥30.0 kg/m2 (HR = 0.87, p = 0.094). Conclusion: SGLT2 inhibitors improve the prognosis in patients with HF or at risk of HF. This effect is affected by BMI.

More than 64 million people worldwide suffer from heart failure (HF). In developed nations, the prevalence of HF ranges from 1–2% of the adult population, rising to 10% among people over the age of 70 [1]. With increasing age, HF hospitalization (HHF) and mortality rates increase in both acute and chronic HF patients [1, 2]. In many European countries, the direct costs of HF account for more than 2% of the overall healthcare budget [3, 4]. Treatment of HF with reduced ejection fraction is mainly based on diuretics and neurohormonal antagonists, which include angiotensin converting enzyme inhibitors, angiotensin receptor blockers, β-blockers, and mineralocorticoid receptor antagonists. In patients with cardiovascular (CV) mortality risk factors, treatment with a renin-angiotensin aldosterone system antagonist can reduce the incidence of HF. However, the efficacy of these drugs needs to be further developed [5, 6]. A recently emerged class of drug called SGLT2 inhibitors treats type 2 diabetes by decreasing glucose reabsorption and increasing glucose excretion in the kidneys. Studies have found that SGLT2 inhibitors can be used to treat not only type 2 diabetes but also HF. A large number of randomized controlled trials (RCTs) have shown a reduction in CV mortality with SGLT2 inhibitor agonists. SGLT2 inhibitors may have a positive impact on HF by reducing the cardiac burden on the heart through lowering blood pressure and altering proximal tubular diuresis in the kidneys.

Patients with HF often have underlying conditions such as type 2 diabetes, hypertension, and renal insufficiency. Previous studies have shown that SGLT2 inhibitors alone can treat obesity, type 2 diabetes, and HF [7]. Several meta-analyses have determined that HF patients with or without type 2 diabetes can benefit from SGLT2 inhibitors. Patients with HF or at risk of HF can be obese, and the extent of benefit of SGLT2 inhibitors for those with HF or at risk of HF of different weights is unclear. To explore this issue, this meta-analysis investigated the effect of SGLT2 inhibitors on patients with HF or at risk of HF across different body mass index (BMI) by reviewing relevant RCTs.

Search Strategy

This study was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Statement: Updated Guidelines for Systematic Review Reporting and had been registered in PROSPERO 2023 (CRD42023418581). The objective was to determine how SGLT2 inhibitors affect the prognosis of patients with HF or at risk of HF and to further investigate their relationship with BMI.

From the establishment of the library to April 2023, two researchers searched four databases, including PubMed, Web of Science, Embase, and Cochrane Library, for the following search terms: (cardiac failure OR heart decompensation OR HF, right-sided OR myocardial failure OR HF, left-sided OR HF) and (sodium-glucose transporter 2 inhibitors OR SGLT2 inhibitors OR sodium-glucose transporter 2 inhibitor OR SGLT2 inhibitor OR inhibitor, SGLT2 OR gliflozin OR canagliflozin OR dapagliflozin OR empagliflozin OR ertugliflozin). The reference lists included in all retrieved articles were also searched. The primary outcome was the prognosis for patients with HF or at risk of HF, including all-cause mortality, CV mortality, and HHF.

Inclusion and Exclusion Criteria

The included studies were based on the PICOS principles: (1) patients suffered from HF or at risk of HF; (2) the intervention group received SGLT2 inhibitors; (3) the control group received placebo; (4) the primary outcomes were all-cause mortality, CV mortality, and HHF; (5) the study fell into the RCT category. Compliant with PICOS, the exclusion criteria were: (1) no complete text available; (2) no data reported on the relationship between the BMI status and prognosis with HF or at risk of HF post-intervention; (3) no data reported or accessible; and (4) non-English article. When updating published articles for the same study cohort, the most recent study with the largest population participation was selected.

Data Extraction and Quality Assessment

Two researchers extracted the data separately using a predesigned form. The following data were extracted from eligible studies: (1) the author, year of publication, sample size by nation, and registration number of the study; (2) subject characteristics, such as BMI stage, age, follow-up duration, left ventricular ejection fraction, and New York Heart Association (NYHA) classification; and (3) prognostic outcomes.

Two review writers used tools from the Cochrane Collaboration Network to assess the quality of RCT. The labels “high risk,” “low risk,” and “unclear risk” were used to describe different levels of bias, which included random serial generation, allocation concealment, participant and staff blinding, outcome assessment blinding, insufficient outcome data, selective reporting, and others. Disagreements between the two reviewers were resolved after discussion, with the involvement of a third author when necessary.

Statistical Methods

This meta-analysis was completed using Stata Software 12.0 and Review Manager 5.3. Hazard ratios (HR) and 95% confidence intervals (CIs) were used to assess the association between the use of SGLT2 inhibitors and the prognosis of patients with HF or at risk of HF. The χ2 test with I2 was applied to examine heterogeneity. I2 > 50% was considered significant heterogeneity, 25–50% indicated moderate heterogeneity, and I2 < 25% was considered low heterogeneity [8]. Randomized models were used to increase the robustness of the results due to different baselines of patients with HF or at risk of HF, as well as differences in intervention regimens described in the included studies. Begg’s tests were used to check for publication bias if more than ten papers were included, and sensitivity analyses were used to determine the reliability of the findings. A p value of <0.05 in the test was considered to indicate statistically significant differences [9].

Description of the Studies

Based on the search principles, a large number of records totaling 4,983 articles were found from the four databases, and no additional information was found from other sources. After eliminating duplicate articles, a large number of 3,443 records were retained and 3,292 irrelevant articles were eliminated by browsing the article titles and abstracts. 146 papers were excluded after reading the full text, of which 92 were not RCTs, 49 did not have BMI-related information, 4 because no results of interest were reported, and 1 because no data were readily available. Finally, five articles were used in the final meta-analysis [10‒14]. The flowchart in Figure 1 depicts the selection procedure.

Fig. 1.

Flow diagram of selection.

Fig. 1.

Flow diagram of selection.

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Six RCTs were drawn from five articles published between 2021 and 2023 on the effects of SGLT2 inhibitors on patients with HF or at risk of HF. In each of these studies, the patients were over the age of 18. Most patients fell into classes II–IV of the NYHA Classification of HF. All patients had a glomerular filtration rate of more than 20%. All patients were divided into three groups based on their BMI: ≤24.9 kg/m2, 25.0–29.9 kg/m2, and ≥30.0 kg/m2. All studies included information on all-cause mortality, CV mortality, or HHF. SGLT2 inhibitors included dapagliflozin, canagliflozin, and empagliflozin. Three RCTs were followed for at least 5 years. All articles were multicenter studies. Table 1 and online supplementary Table 1 (for all online suppl. material, see https://doi.org/10.1159/000535297) list the characteristics of the studies analyzed in this meta-analysis.

Table 1.

Characteristics of all the studies included in the meta-analysis

Author, yearCountryStudy drugRecruitment timeMean age, yearsPatients per BMI group, nNYHA classLVEFFollow-up, years
≤24.9 kg/m225.0–29.9 kg/m2≥30.0 kg/m2
Adamson et al., 2021 [11UK Dapagliflozin 2017–2019 ≥18 1,348 1,722 1,672 II–IV ≤40% 
Adamson et al., 2022 [13UK Dapagliflozin NA ≥40 1,343 2,073 2,797 II–IV >40% NA 
Ohkuma et al., 2020 [10Australia Canagliflozin 2009–2017 ≥30 966 3,153 6,009 NA NA 
2013–2018 
Anker et al., 2023 [14Germany Empagliflozin 2017–2019 ≥18 1,218 1,345 1,167 II–IV ≤40% 
Ji et al., 2021 [12China Empagliflozin 2009–2018 ≥18 633 1,646 2,408 I–IV NA >5 
Author, yearCountryStudy drugRecruitment timeMean age, yearsPatients per BMI group, nNYHA classLVEFFollow-up, years
≤24.9 kg/m225.0–29.9 kg/m2≥30.0 kg/m2
Adamson et al., 2021 [11UK Dapagliflozin 2017–2019 ≥18 1,348 1,722 1,672 II–IV ≤40% 
Adamson et al., 2022 [13UK Dapagliflozin NA ≥40 1,343 2,073 2,797 II–IV >40% NA 
Ohkuma et al., 2020 [10Australia Canagliflozin 2009–2017 ≥30 966 3,153 6,009 NA NA 
2013–2018 
Anker et al., 2023 [14Germany Empagliflozin 2017–2019 ≥18 1,218 1,345 1,167 II–IV ≤40% 
Ji et al., 2021 [12China Empagliflozin 2009–2018 ≥18 633 1,646 2,408 I–IV NA >5 

NA, not available; BMI, body mass index; NYHA, New York Heart Association; LVEF, left ventricular ejection fraction.

Quality Evaluation

The results of the assessment of the included studies are displayed in online supplementary figures 1 and 2. The Cochrane Collaboration methods were used to assess the quality of each RCT. All trials were rated as low risk in three areas: random sequence generation, allocation concealment, and blinding of outcome assessment. With regard to incomplete selective reporting of outcome data, most studies were rated as low risk, while only few were rated as high risk. However, when considering the interventions, the risk of blinding of participants and staff was unclear in three studies, high in the rest of studies and low in one study. For other biases, the included studies were assessed as being at unclear risk.

Prognostic Analysis

Three studies reported on the effect of SGLT2 inhibitors compared to the placebo on HHF or CV mortality. Based on the pooled data, patients taking SGLT2 inhibitors had lower rates of HHF or CV mortality than those taking placebo (HR = 0.73, 95% CI = 0.67–0.80, p < 0.001, I2 = 0%) (Fig. 2a). According to four studies reporting the effects of SGLT2 inhibitors, all-cause mortality was lower in patients taking SGLT2 inhibitors than in those taking placebo (HR = 0.85, 95% CI = 0.74–0.97, p = 0.017, I2 = 66%) (Fig. 2b).

Fig. 2.

Forest plot of meta-analysis of HHF or CV mortality and all-cause mortality (a: HHF or CV mortality, p < 0.001; b: all-cause mortality, p = 0.017).

Fig. 2.

Forest plot of meta-analysis of HHF or CV mortality and all-cause mortality (a: HHF or CV mortality, p < 0.001; b: all-cause mortality, p = 0.017).

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Three studies reported on HHF in patients with HF or at risk of HF, and compared to the control groups, participants using SGLT2 inhibitors had a decreased incidence of HHF (HR = 0.69, 95% CI = 0.62–0.78, p < 0.001, I2 = 0%) (Fig. 3a). Investigation reports on CV mortality and statistical analysis revealed that the experimental group had a lower CV mortality than the control group (HR = 0.88, 95% CI = 0.79–0.97, p = 0.014, I2 = 0%) (Fig. 3b).

Fig. 3.

Forest plot of meta-analysis of HHF and CV mortality (a: HHF, p < 0.001; b: CV mortality, p = 0.014).

Fig. 3.

Forest plot of meta-analysis of HHF and CV mortality (a: HHF, p < 0.001; b: CV mortality, p = 0.014).

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Subgroup Analysis

BMI typing was taken into consideration for the subgroup analyses of HHF, CV mortality, and all-cause mortality. Patients with BMI ≤24.9 kg/m2 (HR = 0.69, p < 0.001) (Fig. 4a), BMI 25.0–29.9 kg/m2 (HR = 0.71, p < 0.001) (Fig. 4b), and BMI ≥30.0 kg/m2 (HR = 0.76, p < 0.001) (Fig. 4c) on SGLT2 inhibitors had statistically significant lower rates of HHF or CV mortality than patients taking placebo.

Fig. 4.

Forest plot of meta-analysis of HHF or CV mortality in the subgroup (a: BMI ≤24.9 kg/m2, p < 0.001; b: BMI 25.0–29.9 kg/m2, p < 0.001; c: BMI ≥30.0 kg/m2, p < 0.001).

Fig. 4.

Forest plot of meta-analysis of HHF or CV mortality in the subgroup (a: BMI ≤24.9 kg/m2, p < 0.001; b: BMI 25.0–29.9 kg/m2, p < 0.001; c: BMI ≥30.0 kg/m2, p < 0.001).

Close modal

The experimental group had a greater decline than the control group in all-cause mortality, when patients had a BMI less than 24.9 kg/m2 (HR = 0.85, p = 0.033) (Fig. 5a) and a BMI 25.0–29.9 kg/m2 (HR = 0.83, p = 0.046) (Fig. 5b). However, for patients with a BMI over 30.0 kg/m2, there was no statistically significant difference between the experimental and control groups (HR = 0.87, p = 0.094) (Fig. 5c).

Fig. 5.

Forest plot of meta-analysis of all-cause mortality in the subgroup (a: BMI ≤24.9 kg/m2, p = 0.033; b: BMI 25.0–29.9 kg/m2, p = 0.046; c: BMI ≥30.0 kg/m2, p = 0.094).

Fig. 5.

Forest plot of meta-analysis of all-cause mortality in the subgroup (a: BMI ≤24.9 kg/m2, p = 0.033; b: BMI 25.0–29.9 kg/m2, p = 0.046; c: BMI ≥30.0 kg/m2, p = 0.094).

Close modal

When patients had a BMI less than 24.9 kg/m2 (HR = 0.62, p < 0.001) (Fig. 6a), 25.0–29.9 kg/m2 (HR = 0.75, p = 0.006) (Fig. 6b), or greater than 30.0 kg/m2 (HR = 0.70, p < 0.001) (Fig. 6c), the incidence of HHF was lower in the experimental group than in the control group. Using an observation index for CV mortality, there was no significant difference between SGLT2 inhibitors and placebo at both BMI ≤24.9 kg/m2 (HR = 0.91, p = 0.331) (Fig. 7a) and 25.0–29.9 kg/m2 (HR = 0.92, p = 0.307) (Fig. 7b). However, CV mortality was lower on SGLT2 inhibitors than controls when the BMI exceeded 30.0 kg/m2 (HR = 0.79, p = 0.002) (Fig. 7c).

Fig. 6.

Forest plot of meta-analysis of HHF in the subgroup (a: BMI ≤24.9 kg/m2, p < 0.001; b: BMI 25.0–29.9 kg/m2, p = 0.006; c: BMI ≥30.0 kg/m2, p < 0.001).

Fig. 6.

Forest plot of meta-analysis of HHF in the subgroup (a: BMI ≤24.9 kg/m2, p < 0.001; b: BMI 25.0–29.9 kg/m2, p = 0.006; c: BMI ≥30.0 kg/m2, p < 0.001).

Close modal
Fig. 7.

Forest plot of meta-analysis of CV mortality in the subgroup (a: BMI ≤24.9 kg/m2, p = 0.331; b: BMI 25.0–29.9 kg/m2, p = 0.307; c: BMI ≥30.0 kg/m2, p = 0.002).

Fig. 7.

Forest plot of meta-analysis of CV mortality in the subgroup (a: BMI ≤24.9 kg/m2, p = 0.331; b: BMI 25.0–29.9 kg/m2, p = 0.307; c: BMI ≥30.0 kg/m2, p = 0.002).

Close modal

This study indicated that SGLT2 inhibitors can reduce HHF, CV mortality, and all-cause mortality in patients with HF or at risk of HF compared to placebo. A previous study by Shah et al. [15] also demonstrated that SGLT2 inhibitors are more useful than placebo in lowering HHF and CV mortality. Kato et al. [16] found that dapagliflozin reduced CV mortality and all-cause mortality in patients with HF compared to placebo.

SGLT2 inhibitors can improve the prognosis of patients with HF by modulating cardiac hemodynamics and enhancing cardiac function [17, 18]. In diabetic patients, SGLT2 inhibitors can increase blood glucose excretion through osmotic diuresis and lower blood pressure, thereby improving HF in patients [19]. By raising the glucagon to insulin ratio and promoting enhanced lipid mobilization, which can lead to weight loss, SGLT2 inhibitors can improve the prognosis of patients with HF [20]. Hemoglobin enhances the oxygen supply to the myocardium, while erythropoietin exerts cardioprotective benefits. The prognosis of CV diseases may be improved if patients with HF or at risk of HF take SGLT2 inhibitors since SGLT2 inhibitors can elevate erythropoietin levels, RBC quality, and hematocrit.

The CV benefits of SGLT2 inhibitor therapies may be related to a shift in cardiac metabolism from fatty acid and glucose oxidation to more oxygen-efficient ketone bodies, thereby resulting in improved cardiac efficiency. SGLT2 inhibitor treatment reduces cytoplasmic sodium content by inhibiting sodium hydrogen exchange protein 1 and SGLT1 transporters in diabetic rat and mouse cardiomyocytes, thereby reversing calcium overload. It may improve the electrochemical properties of failing myocardium and may thus protect the heart. Various SGLT2 inhibitor treatments upregulate the expression of AMPK, SIRT1, and HIF-1α to induce autophagy to deal with dysfunctional mitochondria and promote oxidative stress, as well as inflammation with beneficial effects on the heart. SGLT2 inhibition decreases serum leptin and increases adiponectin concentrations, which is considered to be a cardioprotective substance and may have a protective effect on the heart [21].

This study showed that HHF rates were significantly lower in the experimental group than in the control group in the BMI-based subgroup analysis and that SGLT2 inhibitors were able to reduce HHF. Adamson et al. [11] agreed that SGLT2 inhibitors have positive impacts on clinical CV outcomes and patient-reported quality of life, irrespective of obesity. Lazzaroni et al. [22] showed that SGLT2 inhibitors reduced HHF in patients with HF by improving renal and CV functions. These results were confirmed in our statistics.

Our study showed no difference in CV mortality between the SGLT2 inhibitor group and the placebo group in patients with HF or at risk of HF with a BMI ≤30.0 kg/m2. When BMI was ≥30.0 kg/m2, SGLT2 inhibitors reduced CV mortality compared to placebo. SGLT2 inhibitors improved CV mortality in patients with HF or at risk of HF, with heavier participants benefiting more. One possible mechanism is that SGLT2 inhibitors are lipophilic, and obese participants tend to have more fatty tissue. Therefore, their accumulation in adipose tissue may impede drug elution and cause changes in bioavailability, thereby enhancing the effect of SGLT2 inhibitors [23]. Another possible mechanism may be the higher risk of CV death in patients with a higher BMI. Patients with HF or at risk of HF with a lower weight have a lower risk of CV death than obese participants. With the adoption of SGLT2 inhibitors, improvement was more pronounced in heavier patients with CV diseases. Therefore, obese participants are more likely to reap benefits than other patients in terms of CV causes of mortality. This result is also consistent with the “obesity paradox,” in which overweight and mild to moderate obesity are associated with significantly higher survival in HF patients compared to normal-weight patients [24]. Previous studies have shown that the absolute benefit of SGLT2 inhibitors is increased in patients at high CV risk, particularly those HHF [25]. The combination of SGLT2 inhibitors and drugs that treat HF in patients with HF significantly reduces CV mortality, whereas SGLT2 inhibitors alone reduce HHF rates more than drugs which specifically aim to treat HF [26, 27]. Our study found that SGLT2 inhibitors can significantly reduce CV mortality in people with a higher BMI. Obesity is one of the risk factors for CV diseases.

Our study showed that SGLT2 inhibitors significantly reduced all-cause mortality in patients with HF or at risk of HF and a BMI ≤30.0 kg/m2 compared to controls. When the BMI of patients with HF or at risk of HF patients was ≥30.0 kg/m2, there was no significant difference in all-cause mortality between the experimental and control groups. Therefore, in terms of all-cause mortality, SGLT2 inhibitors are effective in patients with HF or at risk of HF with a lower BMI. The greater the BMI, the more comorbidities in patients with HF or at risk of HF and the more frequent and complex the causes of death in patients, which leads to a relative reduction in the proportion of CV causes of death to total deaths in obese participants. Underweight patients with HF or at risk of HF have lesser comorbidities than obese participants, and therefore underweight patients have a higher proportion of CV mortality as a percentage of total deaths. Therefore, SGLT2 inhibitors are more effective in those with a lower BMI. In contrast, obese participants tend to have worse NYHA grades, with nearly twice as many patients in functional class III or IV as normal-weight participants [28]. This resulted in poorer outcomes for obese participants than for those with a low BMI. These results suggest that SGLT2 inhibitors significantly reduced CV mortality in people with a higher BMI, as well as all-cause mortality in those with a lower BMI. Therefore, the efficacy of SGLT2 inhibitors in patients with HF is related to BMI. The results of this study can guide the selection of SGLT2 inhibitors as HF drugs for people with different BMIs and bring them different efficacies.

Our review is based on complementary analyses of RCTs on the prognosis of patients with HF or at risk of HF with SGLT2 inhibitor therapies, and this is also the first meta-analysis that focuses on BMI. However, this study has some limitations: first, only five RCTs were used to compare SGLT2 inhibitors with placebo in people with HF or at risk of HF, and the limited number included did not allow further possible analyses. Second, although BMI is the most commonly used criterion to distinguish obesity; however, there are still disparities between patients with different levels of obesity. In addition, the etiology of the disease varies between patients with HF or at risk of HF, so there can be differences in prognoses. Due to the limited data from the primary studies, additional subgroup analyses could not be conducted. Unfortunately, publication bias and sensitivity analysis were not performed in this meta-analysis as there were fewer than 10 publications.

SGLT2 inhibitors reduce HHF, CV mortality, and all-cause mortality in patients with HF or at risk of HF. In particular, SGLT2 inhibitors acted on patients with a higher BMI and showed more benefit in reducing CV mortality. Conversely, patients with lower BMI values benefit more in terms of all-cause mortality.

An ethics statement is not applicable because this study is based exclusively on the published literature. This study did not use human participant data, so written informed consent was not required.

The authors declare that they have no conflict of interest.

This study was supported by the Ningbo Natural Science Foundation (No. 2022J039 and 2022J266), the Medical and Health Research Project of Zhejiang Province (No. 2022KY343), and the Science and Technology Program for Public Wellbeing of Ningbo (No. 2022AS069).

Each author contributed significantly to the concept and development of the present paper. Y.Z., B.C., M.D., and L.G. designed the research process. T.H. and Z.X. searched the database for corresponding articles and extracted useful information from the articles above. J.T. and M.Z. used statistical software for analysis. Y.Z., B.C., and M.D. drafted the meta-analysis. All authors had read and approved the manuscript and ensured that this was the case.

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

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