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. 2022 Nov 14;9:973129. doi: 10.3389/fcvm.2022.973129

Risk of hypovolemia associated with sodium–glucose cotransporter-2 inhibitors treatment: A meta-analysis of randomized controlled trials

Xi Rong 1,†, Yawen Zhu 2,†, Bo Wen 3,†, Kai Liu 4,*, Xinran Li 4, Qiling Gou 4, Xiaoping Chen 4,*
PMCID: PMC9701837  PMID: 36451919

Abstract

Aim of the review

To assess the risk of hypovolemia for sodium–glucose cotransporter-2 (SGLT2) inhibitors treatment.

Method

A systematic literature retrieval was performed in PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, and Scopus from inception up to 4 October 2022, Data for study characteristics and outcomes of interest were extracted from each eligible study. Risk ratios (RRs) with a 95% confidence interval (CI) for hypovolemia were calculated using a random-effect model.

Results

A total of 57 studies (n = 68,622) were included in our meta-analysis, with a result of 1,972 hypovolemia incidents (1,142 in the SGLT2 inhibitors group and 830 in the control group). The pooled RR was 1.12 (95% CI: 1.02–1.22). It is evident that receiving SGLT2 inhibitors increased the risk of hypovolemia. When stratified by category of SGLT2 inhibitors the result was consistent; when the subgroup was analyzed by age, the pooled RR was 1.07 (95% CI: 0.94–1.23) in patients aged ≥65 years and 1.14 (95% CI: 1.02–1.28) in those aged <65 years. When comparing the baseline estimated glomerular filtration rate (eGFR) of less than or equal to 60 mL/min/1.73 m2 with a baseline eGFR greater than 60 mL/min/1.73 m2, the pooled RR was 1.21, (95% CI: 1.00–1.46) and 1.08, (95%CI: 0.98–1.20), respectively.

Conclusion

Our meta-analysis has demonstrated that SGLT2 inhibitors increased the risk of hypovolemia in patients with Type 2 Diabetes Mellitus (T2DM). It is necessary to pay attention to the risk of hypovolemia associated with SGLT2 inhibitors, especially in older individuals and those with moderate renal impairment.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/], identifier [CRD42020156254].

Keywords: sodium-glucose cotransporter-2 inhibitors, adverse event (AE), volume depletion, meta-analysis, RCTs, hypovolemia

Introduction

Type 2 diabetes mellitus (T2DM) is an important health problem worldwide, which is characterized by insulin resistance, β-cell dysfunction, and impaired glucose tolerance (1). The prevalence of diabetes has been increasing dramatically. It is estimated that the overall prevalence of adult diabetes patients was 10.9% in China (2). Diabetes will be the 7th leading cause of death in 2030 (3). Optimal control of plasma glucose is the crucial treatment for T2DM (4).

Sodium–glucose cotransporter-2 (SGLT2) inhibitors are a new class of drugs, which improves glycemia by enhancing glycosuria, subsequently reducing blood pressure by osmotic diuresis and natriuresis (5). There are multiple large-scale randomized control trials demonstrating that SGLT2 inhibitors had a salutary effect on the cardiovascular-renal outcomes, especially on heart failure (6). Although SGLT2 inhibitors exhibited promising potential value in treatment for type 2 diabetes mellitus (T2DM) with cardiovascular-renal comorbidities, the potential adverse events (AEs) related to osmotic diuresis such as hypovolemia should not be neglected. Moreover, older individuals, those with moderate renal impairment, and those aged ≥65 years are susceptible to adverse events related to hypovolemia.

As for the above reasons, our systematic review targeted to investigate the hypovolemia incidents related to SGLT2 inhibitors by meta-analyzing, and we also performed subgroup analysis depended on the category of SGLT2 inhibitors, patients’ age, and baseline estimated glomerular filtration rate (eGFR) to evaluate whether the risk of hypovolemia could be affected by clinical variables.

Materials and methods

Literature search

We performed a systematic and comprehensive literature search in PubMed, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, and Scopus from inception up to 4 October 2022. And we adhered to the 2020 PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) statement in conducting this study and reporting the results (Supplementary material 1). The search strategy combined the Medical Subject Heading and the text words canagliflozin, dapagliflozin, empagliflozin, ipragliflozin, remogliflozin, ertugliflozin, sergliflozin, luseogliflozin, Sotagliflozin, Tofogliflozin, Sodium glucose co-transporter, SGLT2, SGLT-2, and SGLT 2 (Supplementary material 2). These terms were adjusted to conform with the searching principle of each database; citations without any limits were searched. This systematic review was registered in PROSPERO (CRD42020156254).

Study selection

Two authors (Xinran Li and Qiling Gou) independently reviewed all relevant studies according to prespecified criteria. Inclusion criteria were: (a) RCTs reported in the English language and included adult patients with T2DM; (b) SGLT2 inhibitors compared with placebo or active comparator; (c) duration of follow-up of at least 12 weeks; and (d) the hypovolemia adverse events, which were investigated using a pre-specified list of Medical Dictionary for Regulatory Activities (MedDRA) preferred terms to identify events of hypotension, dehydration, or hypovolemia in the database (Supplementary material 3). Data from completed published manuscripts were considered for inclusion in this analysis.

Data extraction and validity assessment

Two researchers (Xinran Li and Qiling Gou) independently screened and extracted the data using a previously defined standardized Microsoft excel sheet; the following information was extracted from each eligible trial: first author, year of publication, trial identifier, study duration, intervention drug, control drug, sample size, patients characteristics, duration of T2DM, and incident of hypovolemia events. These data were further examined by another investigator (Xi Rong), and any discrepancies were resolved by discussion. If hypovolemia events were not reported in the published paper, then these data were instead extracted from the trial register website. If the trial register website also did not provide the data on hypovolemia events, we attempted to contact the author to get the data. Two reviewers independently applied Cochrane risk-of-bias tool (7) to assess the quality of included RCTs based on the following domains: random sequence generation, allocation concealment, blinding of study participants and personnel, incomplete outcome data, selective reporting, and other biases.

Data synthesis and statistical analysis

Most of the analyses were performed by using RevMan (version 5.3.5; Cochrane Collaboration). For dichotomous data, risk ratios (RRs) and 95% confidence interval (CI) were calculated to appraise the risk of hypovolemia with SGLT2 inhibitors treatment. Furthermore, subgroup analyses were conducted on the category of SGLT2 inhibitors, patients’ age, and baseline estimated glomerular filtration rate (eGFR) to evaluate whether the risk of hypovolemia could be modified by clinical variables. Sensitivity analysis was assessed by omitting one study at a time and re-estimated the combined RR for the remaining studies yielding consistent results to determine whether the result of the original analysis was robust. The Chi-square test (χ2) and I2 statistics were used to assess heterogeneity, Heterogeneity was assessed as low, moderate, and high with I2 values of 25, 50, and 75%, respectively. A random-effects model was adopted if there was evidence of statistical heterogeneity or clinical diversity (P<0.01, I2>50%); otherwise, a fixed-effects model was used if there was no statistical significance of heterogeneity (P>0.01, I2<50%). The presence of publication bias was evaluated by visual inception for funnel plot asymmetry; Begg’s test and trim-and-fill method were also performed using STATA (version15.0; STATA software) to assess publication bias.

Results

Eligible studies and characteristics

Figure 1 shows the result of our literature retrieval; in brief, 11,727 citations were initially screened and 7,606 duplications were excluded. An additional 3,137 articles were excluded based on their titles and abstracts. The remaining 984 citations were evaluated by inclusion criteria, further removing 927 citations. At last, there were 55 papers (57 studies) involving 68,622 patients that met the inclusion criteria at last (8–62). In the paper reported by Barnett (20), patients were recruited and randomized by the stage of chronic kidney disease, and the incident of hypovolemia was presented separately, thus each of them was considered as a separate study in this meta-analysis. Twelve RCTs (n = 11,576) evaluated canagliflozin, 22 RCTs (n = 36,508) evaluated dapagliflozin, 13 RCTs (n = 17,284) evaluated empagliflozin, four RCTs (n = 970) evaluated luseogliflozin, two RCTs (n = 310) evaluated ipragliflozin, two RCTs (n = 440) evaluated tofogliflozin, and the remaining one RCT (n = 312) evaluated bexagliflozin. The last one RCTs (n = 1,222) evaluated sotagliflozin. Among those 57 studies 51 studies compared SGLT2 inhibitors with a placebo, and another six studies compared SGLT2 inhibitors with other antidiabetic drugs. All eligible studies were randomized and double-blind design, and the publication year of studies ranged from 2009 to 2022, The follow-up duration of studies varies from 12 weeks to 208 weeks. The overview of the characteristics of included studies is presented in Table 1.

FIGURE 1.

FIGURE 1

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Flowchart showing identification of the included studies.

TABLE 1.

Characteristics of the randomized controlled studies (RCTs) included in the meta-analysis.

Author Trial identifier Study duration Intervention control Patients (n)
 Age (years)
 Duration of T2DM (years)
 HbA1c (%)
 Case of hypovolemia
Intervention Control Intervention control Intervention control Intervention control Intervention control
Strojek et al. (10) NCT00263276 12weeks DAPA 2.5mg, 5mg, 10mg, 20mg, 50mg PLA 59, 58, 47, 59, 56 54 55 ± 11, 55 ± 12, 54 ± 9, 55 ± 10, 53 ± 10 53 ± 11 NR NR 7.6 ± 0.7, 8.0 ± 0.9, 8.0 ± 0.8, 7.7 ± 0.9, 7.8 ± 1.0 7.9 ± 0.9 0, 0, 0, 0, 2 1
Nauck et al. (11) NCT00528879 24weeks DAPA 2.5mg, 5mg, 10mg PLA 137, 137, 135 137 55 ± 9.3, 54.3 ± 9.4, 52.7 ± 9.9 53.7 ± 10.3 6 ± 6.2, 6.4 ± 5.8, 6.1 ± 5.4 5.8 ± 5.1 7.99 ± 0.9, 8.17 ± 0.96, 7.92 ± 0.82 8.11 ± 0.96 0, 2, 0 1
Bailey et al. (12) NCT00680745 24weeks DAPA 2.5mg, 5mg, 10mg PLA 154, 142, 151 145 59.9 ± 10.14, 60.2 ± 9.73, 58.9 ± 8.32 60.3 ± 10.16 7.7 ± 6.0, 7.4 ± 5.7, 7.2 ± 5.5 7.4 ± 5.7 8.11 ± 0.75, 8.12 ± 0.78, 8.07 ± 0.79 8.15 ± 0.74 1, 0, 1 0
Wilding et al. (13) NCT00660907 52weeks DAPA 10mg GLIP 20mg 406 408 58 ± 9 59 ± 10 6 ± 5 7 ± 6 7.7 ± 0.9 7.7 ± 0.9 6 3
Cefalu et al. (14) NR 24weeks DAPA 1mg, 2.5mg, 5mg PLA 72, 74, 68 68 53.7 ± 9.04, 53.5 ± 10.61, 51.3 ± 11.51 53.5 ± 11.08 1.6 ± 2.55, 1.5 ± 2.19, 1.4 ± 3.24 1.1 ± 1.95 7.8 ± 0.98, 8.1 ± 1.07, 7.9 ± 1.03 7.8 ± 1.12 0, 0, 1 0
Wilding et al. (15) NCT00673231 24weeks DAPA 2.5mg, 5mg, 10mg PLA 202, 211, 194 193 59.8 ± 7.6, 59.3 ± 7.9, 59.3 ± 8.8 58.8 ± 8.6 13.6 ± 6.6, 13.1 ± 7.8, 14.2 ± 7.3 13.5 ± 7.3 8.46 ± 0.78, 8.62 ± 0.89, 8.57 ± 0.82 8.47 ± 0.77 5, 5, 4 2
Lavalle-Gonzalez et al. (16) NCT00968812 52weeks CANA 100mg, 300mg GLIM 6/8mg 483, 485 482 56.4 ± 9.5, 55.8 ± 9.2 56.3 ± 9.0 6.5 ± 5.5, 6.7 ± 5.5 6.6 ± 5.0 7.8 ± 0.8, 7.8 ± 0.8 7.8 ± 0.8 4, 3 3
Schernthaner et al. (17) NCT01106625 52weeks CANA 100mg, 300mg PLA 157, 156 156 57.4 ± 10.5, 56.1 ± 8.9 56.8 ± 8.3 9.0 ± 5.7, 9.4 ± 6.4 10.3 ± 6.7 8.1 ± 0.9, 8.1 ± 0.9 8.1 ± 0.9 1, 6 3
Stenlof et al. (18) NCT01106677 52weeks CANA 100mg, 300mg SITA 100mg 368, 367 366 55.5 ± 9.4, 55.3 ± 9.2 55.5 ± 9.6 6.7 ± 5.4, 7.1 ± 5.4 6.8 ± 5.2 7.9 ± 0.9, 7.9 ± 0.9 7.9 ± 0.9 0, 0, 1 1
Bode et al. (19) NCT01137812 52weeks CANA 300mg SITA 100mg 377 378 56.6 ± 9.6 56.7 ± 9.3 9.4 ± 6.1 9.7 ± 6.3 8.1 ± 0.9 8.1 ± 0.9 0 1
Barnett et al. (20) NCT01081834 26weeks CANA 100mg, 300mg PLA 195, 197 192 55.1 ± 10.8, 55.3 ± 10.2 55.7 ± 10.9 4.5 ± 4.4, 4.3 ± 4.7 4.2 ± 4.1 8.1 ± 1.0, 8.0 ± 1.0 8.0 ± 1.0 0, 2 0
Bolinder et al. (21) NCT01106651 26weeks CANA 100mg, 300mg PLA 241, 236 237 64.3 ± 6.5, 63.4 ± 6.0 63.2 ± 6.2 12.3 ± 7.8, 11.3 ± 7.2 11.4 ± 7.3 7.8 ± 0.8, 7.7 ± 0.8 7.8 ± 0.8 2, 1 0
Forst et al. (22) NCT01164501 52weeks EMPA 10mg, 25mg PLA 98, 97 95 63.2 ± 8.5, 62 ± 8.4 62.6 ± 8.1 NR NR 8.02 ± 0.84, 7.96 ± 0.73 8.09 ± 0.8 1, 0 1
Jabbour et al. (23) NCT00855166 24weeks DAPA 10mg PLA 89 91 60.6 ± 8.2 60.8 ± 6.9 6.0 ± 4.5 5.5 ± 5.3 7.19 ± 0.44 7.16 ± 0.53 1 0
Interven-tion Control Interven-tion control Intervention control Interven-tion control Interven-tion control
Kadowaki et al. (24) NCT01106690 52weeks CANA 100mg, 300mg PLA 113, 114 115 56.7 ± 10.4, 57 ± 10.2 58.3 ± 9.6 10.5 ± 6.6, 11 ± 7.6 10.1 ± 6.6 8.0 ± 0.9, 7.9 ± 0.9 8.0 ± 1.0 9, 5 4
Kohan et al. (25) NCT00984867 24weeks DAPA 10mg PLA 223 224 54.8 ± 10.4 55.0 ± 10.2 5.70 ± 4.87 5.64 ± 5.4 7.9 ± 0.8 8.0 ± 0.8 3 2
Leiter et al. (26) NCT01193218 12weeks EMPA 5mg, 10mg, 25mg, 50mg PLA 110, 109, 109, 110 109 57.3 ± 11.2, 57.9 ± 9.4, 57.2 ± 9.7, 56.6 ± 10.3 58.7 ± 8.7 NR NR 7.92 ± 0.70, 7.93 ± 0.71, 7.93 ± 0.78, 8.02 ± 0.65 7.94 ± 0.74 0, 1, 1, 0 0
Seino et al. (27) NCT00663260 104weeks DAPA 5mg, 10mg PLA 83, 85 84 66 ± 8.9, 68 ± 7.7 67 ± 8.6 16.9 ± 9.0, 18.2 ± 10.1 15.7 ± 9.5 8.30 ± 1.04, 8.22 ± 0.98 8.53 ± 1.28 8, 11 5
Seino et al. (28) NCT01042977 24weeks DAPA 10mg PLA 480 482 63.9 ± 7.6 63.6 ± 7.0 13.5 ± 8.2 13.0 ± 8.4 8.0 ± 0.8 8.1 ± 0.8 7 13
Inagaki et al. (29) JapicCTI-090908 12weeks LUSE 0.5mg, 2.5mg, 5mg PLA 60, 61, 61 54 55.2 ± 10.1, 58.3 ± 9.4, 56.8 ± 9.3 57.6 ± 11.0 4.90 ± 4.49, 6.15 ± 6.50, 5.77 ± 5.55 7.30 ± 6.43 8.16 ± 0.93, 8.07 ± 0.90, 8.16 ± 0.96 7.88 ± 0.72 1, 1, 0 0
Kaku et al. (30) Japic CTI-101191 12weeks LUSE 1mg, 2.5mg, 5mg, 10mg PLA 55, 56, 54, 58 57 58.5 ± 9.1, 57.4 ± 9.3, 57.3 ± 11.4, 59.6 ± 7.8 57.1 ± 10.0 4.7 ± 4.1, 4.6 ± 4.4, 4.5 ± 4.2, 6.2 ± 5.4 5.1 ± 4.6 7.77 ± 0.79, 8.05 ± 0.75, 7.86 ± 0.69, 7.95 ± 0.67 7.92 ± 0.84 0, 2, 1, 3 0
Yale et al. (31) NCT01413204 24weeks CANA 100mg, 200mg PLA 90, 88 93 58.4 ± 10.4, 57.4 ± 11.1 58.2 ± 11.0 4.72 ± 4.59, 5.88 ± 5.93 5.63 ± 5.76 7.98 ± 0.73, 8.04 ± 0.77 8.04 ± 0.70 0, 2 0
Ridderstrale et al. (32) JapicCTI-101349 24weeks TOFO 10mg, 20mg, 40mg PLA 57, 58, 58 56 58.6 ± 9.8, 56.6 ± 10.2, 57.0 ± 9.1 56.8 ± 9.9 6.3 ± 7.1, 6.4 ± 5.1, 6.7 ± 5.5 6.0 ± 6.1 8.45 ± 0.75, 8.34 ± 0.81, 8.37 ± 0.77 8.41 ± 0.78 0, 0, 1 0
Cefalu et al. (33) NCT01064414 26weeks CANA 100mg, 300mg PLA 90, 89 90 69.5 ± 8.2, 67.9 ± 8.2 68.2 ± 8.4 15.6 ± 7.4, 17.0 ± 7.8 16.4 ± 10.1 7.9 ± 0.9, 8.0 ± 0.8 8.0 ± 0.9 0, 1 0
Ji et al. (34) NCT01167881 208weeks EMPA 25mg GLIM 1-4mg 765 780 56.2 ± 10.3 55.7 ± 10.4 NR NR 7.92 ± 0.81 7.92 ± 0.86 20 15
Kovacs et al. (35) NCT01031680 52weeks DAPA 10mg PLA 455 459 62.8 ± 7.0 63.0 ± 7.7 12.6 ± 8.7 12.3 ± 8.2 8.18 ± 0.84 8.08 ± 0.80 13 2
Merker et al. (36) NCT01381900 18weeks CANA 100mg, 300mg PLA 223, 227 226 56.5 ± 8.3, 56.4 ± 9.2 55.8 ± 9.4 6.8 ± 4.5, 6.9 ± 4.9 6.4 ± 4.6 8.0 ± 0.9, 8.0 ± 0.9 7.9 ± 0.9 0, 1 0
Roden et al. (37) NCT01210001 24weeks EMPA 10mg, 25mg PLA 165, 168 165 54.7 ± 9.9, 54.2 ± 8.9 54.6 ± 10.5 NR NR 8.07 ± 0.89, 8.06 ± 0.82 8.16 ± 0.92 0, 2 0
Ross et al. (38) NCT01159600 24weeks EMPA 10mg, 25mg PLA 217, 213 207 55.5 ± 9.9, 55.6 ± 10.2 56.0 ± 9.7 NR NR 7.9 ± 0.8, 7.9 ± 0.9 7.9 ± 0.9 2, 1 0
Seino et al. (39) NCT01289990 24weeks EMPA 10mg, 25mg PLA 224, 224 228 56.2 ± 11.6, 53.8 ± 11.6 54.9 ± 10.9 NR NR 7.87 ± 0.88, 7.86 ± 0.85 7.91 ± 0.78 6, 2 1
Zinman et al. (40) NR 16weeks EMPA 12.5mg bid, 25mg, 5mg bid, 10mg PLA 215, 214, 215, 214 107 57.6 ± 9.9, 58.2 ± 10.2, 58.8 ± 9.8, 58.5 ± 10.8 57.9 ± 11.2 NR NR 7.78 ± 0.79, 7.73 ± 0.79, 7.79 ± 0.88, 7.84 ± 0.75 7.69 ± 0.72 1, 0, 0, 2 0
Matthaei et al. (41) JapicCTI-111507 24weeks LUSE 2.5mg PLA 150 71 61.2 ± 8.4 59.9 ± 10.5 7.4 ± 5.6 7.9 ± 6.6 8.07 ± 0.85 8.01 ± 0.73 1 0
Tikkanen et al. (42) NCT01131676 148.8we-eks EMPA 10mg, 25mg PLA 2345, 2342 2333 63.0 ± 8.6, 63.2 ± 8.6 63.2 ± 8.8 NR NR 8.07 ± 0.86, 8.06 ± 0.84 8.08 ± 0.84 115, 124 115
Bailey (43) NCT01392677 24weeks DAPA 10mg PLA 109 109 61.1 ± 9.7 60.9 ± 9.2 9.3 ± 6.5 9.6 ± 6.2 8.08 ± 0.91 8.24 ± 0.87 1 0
Ishihara et al. (44) NCT01370005 12weeks EMPA 10mg, 25mg PLA 276, 276 271 60.6 ± 8.5, 59.9 ± 9.7 60.3 ± 8.8 NR NR 7.87 ± 0.77, 7.92 ± 0.72 7.90 ± 0.72 0, 0 1
Rodbard et al. (45) NCT00528372 102weeks DAPA 2.5mg, 5mg, 10mg PLA 65, 64, 70 75 53.0 ± 11.7, 52.6 ± 10.9, 50.6 ± 10.0 52.7 ± 10.3 2.1 ± 3.2, 1.0 ± 1.6, 2.3 ± 3.7 2.1 ± 3.1 7.92 ± 0.9, 7.86 ± 0.94, 8.01 ± 0.96 7.84 ± 0.87 0, 0, 1 1
Weber et al. (46) NCT02175784 16weeks IPRA 50mg PLA 175 87 58.7 ± 11.1 59.2 ± 9.3 12.59 ± 7.79 14.28 ± 8.54 8.67 ± 0.77 8.62 ± 0.86 4 1
Wan Seman et al. (47) NR 26weeks CANA 100mg, 300mg PLA 107 106 57.4 ± 9.3 57.5 ± 10.1 9.8 ± 5.4 10.1 ± 5.9 8.5 ± 0.9 8.4 ± 0.8 1 2
Weber et al. (48) NCT01195662 12weeks DAPA 10mg PLA 225 224 NR NR 7⋅7 ± 5⋅9 7⋅3 ± 5⋅0 8.1 ± 0.9 8.0 ± 1.0 1 0
Fioretto et al. (49) NR 12weeks DAPA 10mg SU 58 52 53 ± 9.1 56 ± 9.1 5.0(3.0, 9.0)* 6.0(3.0, 10.3)* 7.7(7.08, 8.43)* 7.6 (6.9, 8.1)* 11 5
Seino et al. (50) NCT01137474 12weeks DAPA 10mg PLA 302 311 55.6 ± 8.4 56.2 ± 8.9 8.2 ± 6.4 7.6 ± 6.2 8.1 ± 1.0 8.0 ± 0.9 1 0
Terauchi et al. (51) NCT02413398 24weeks DAPA 10mg PLA 160 161 NR NR 14.3 ± 8.1 14.5 ± 8.3 8.33 ± 1.08 8.03 ± 1.08 3 0
Yang et al. (52) JapicCTI-
142582		 16weeks LUSE 2.5mg PLA 159 74 57.4 ± 10.3 57.1 ± 10.9 11.7 ± 7.6 12.1 ± 6.8 8.70 ± 0.83 8.84 ± 0.83 7 1
Allegretti et al. (53) NCT02201004 16weeks TOFO 20mg PLA 141 70 59.1 ± 10.8 56.4 ± 10.0 15.02 ± 9.36 12.39 ± 7.34 8.53 ± 0.75 8.40 ± 0.65 11 2
Wiviott et al. (54) NCT02096705 24weeks DAPA 10mg PLA 139 133 56.5 ± 8.4 58.6 ± 8.9 12.7 ± 7.2 12.2 ± 6.7 8.52 ± 0.76 8.58 ± 0.81 1 0
Mahaffey et al. (55) NCT02836873 24weeks BEXA 20mg PLA 157 155 69.3 ± 8.36 69.9 ± 8.29 15.54 ± 9.198 16.28 ± 8.977 8.01 ± 0.786 7.95 ± 0.812 6 5
Pollock et al. (56) NCT01730534 201.6we-eks DAPA 10mg PLA 8582 8578 63.9 ± 6.8 64 ± 6.8 NR NR NR NR 213 207
Inoue et al. (57) NCT02065791 26weeks CANA 100mg PLA 2202 2199 62.85 ± 8.95 63.15 ± 9.15 15.55 ± 8.65 16 ± 8.55 8.25 ± 1.3 8.3 ± 1.3 144 115
McMurray et al. (58) NCT02547935 24weeks DAPA 10mg PLA 145 148 64.7 ± 8.6 64.7 ± 8.5 17.55 ± 7.7 17.71 ± 9.5 8.44 ± 1.0 8.57 ± 1.2 4 4
Packer et al. (59) UMIN0000
18839		 24weeks IPRA 50mg PLA 24 24 60.5 ± 9.8 60.8 ± 12.1 15.9 ± 7.7 19.1 ± 10.7 8.12 ± 0.93 8.30 ± 0.65 1 0
Lee et al. (60) NCT03036124 72.8weeks DAPA 10mg PLA 2373 2371 66.2 ± 11.0 66.5 ± 10.8 NR NR NR NR 2 5
Bhatt et al. (61) NCT03057977 64weeks EMPA 10mg PLA 1863 1867 67.2 ± 10.8 66.5 ± 11.2 NR NR NR NR 197 184
Solomon et al. (62) NCT03485092 36 weeks EMPA 10mg PLA 52 53 68.7 ± 11.1 68.2 ± 11.7 9.7 ± 6.8 9.0 ± 6.2 7.2 ± 1.5 7.5 ± 1.6 29 31
Neal et al. (63) NCT03521934 36weeks SOTA 200mg PLA 608 614 69(63–76)* 70(64–76)* NR NR 7.1(6.4–8.3)* 7.2(6.4–8.2)* 57 54
O’Meara et al. (64) NCT03619213 110.4weeks DAPA 10mg PLA 3131 3132 71.8 ± 9.6 71.5 ± 9.5 NR NR NR NR 42 32
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Data are the number of patients (n)or mean (sd) unless stated otherwise; *Median (IQR). BMI, body mass index; HbA1c, glycated hemoglobin; IQR, interquartile range; s.d., standard deviation; DAPA, dapagliflozin; CANA, canagliflozin; IPRA, ipragliflozin; TOFO, tofogliflozin; EMPA, empagliflozin; BEXA, bexagliflozi; LUSE, luseogliflozin; SOTA, Sotagliflozin; PLA, placebo; GLIM, glimepiride; GLIP, glipizide; SITA, sitagliptin; SEMA, semaglutide; SU, sulphonylurea; NR, not report.

Quality assessment

We applied Cochrane risk-of-bias tool to assess the study quality. Detailed information about risk-of-bias is presented in Figure 2. Overall, taking the risk of sponsorship bias into consideration, all studies’ other sources of bias were assessed as high. With respect to methods of sequence generation, allocation concealment, and/or blinding of patients and personnel, 25 RCTs had not provided enough information to evaluate.

FIGURE 2.

FIGURE 2

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Risk of bias and methodologic quality of the randomized controlled trials. Green represents low risk of bias, red represents high risk of bias, and yellow indicates unclear risk.

Publication bias and sensitivity analysis

A symmetrical funnel plot of SGLT2 inhibitors vs. placebo for hypovolemia indicated no evidence of publication bias (Figure 3). Begg’s test signified there was no publication bias in the included studies (z = 0.06; P = 0.954). We performed the trim-and-fill method to detect and adjust for publication bias; after trim-and-fill, the pooled RR was 1.117 (95% CI: 1.025; 1.218), which was approximately equal to the original pooled RR (1.12). Collectively, in the result of the funnel plot, Begg’s test, and trim-and-fill method, there was no evidence of publication bias. The result of sensitivity analyses indicated that the combined RRs were all not statistically significant and were similar to one another, with a range from 1.14 (95% CI: 1.052; 1.253) to 1.20 (95% CI: 1.088; 1.326). This implied that the result of our meta-analysis was robust.

FIGURE 3.

FIGURE 3

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Funnel plot of publication bias for hypovolemia comparing the SGLT2 inhibitors group vs. the placebo group.

Sodium–glucose cotransporter-2 inhibitors and hypovolemia

Compared to the placebo, the combined RR of SGLT2 inhibitors was 1.12 (95% CI:1.02–1.22). The heterogeneity, as assessed by I2, was 0% (P = 0.99), suggesting there was no significant heterogeneity between studies (Figure 4). Additional subgroup analyses were performed to assess the effect of the category of SGLT2 inhibitors, patients’ age, and baseline eGFR on the risk of hypovolemia. When stratified by category of SGLT2 inhibitors, the pooled RRs of sotagliflozin, luseogliflozin, Tofogliflozin, ipragliflozin, canagliflozin, bexagliflozin, dapagliflozin, and empagliflozin were 1.07 (95% CI:0.75–1.52), 2.44 (95% CI:0.64–9.28), 2.28 (95% CI:0.60–8.71), 2.27 (95% CI:0.38–13.61), 1.28 (95% CI:1.02–1.59), 1.18 (95% CI:0.37–3.80), 1.11 (95% CI:0.95–1.30), and 1.06 (95% CI:0.93–1.20), respectively (Figure 5). When the subgroup was analyzed by age, the pooled RR of patients with age ≥65 years and those with age < 65 years were (1.07; 95% CI: 0.94–1.23) and (1.14; 95% CI: 1.02–1.28), respectively (Figure 6). The pooled RR (1.21, 95% CI: 1.00–1.46) was slightly higher in the subgroup with a baseline eGFR less than or equal to 60 mL/min/1.73 m2 than in the subgroup with a baseline eGFR greater than 60 mL/min/1.73 m2 (RR, 1.08; 95% CI: 0.98–1.20), but there was no statistical significance for eGFR subgroup differences (p = 0.30) (Figure 7).

FIGURE 4.

FIGURE 4

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Comparisons of hypovolemia events between the SGLT2 inhibitors group vs. the placebo group.

FIGURE 5.

FIGURE 5

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Subgroup analysis of the hypovolemia events between the SGLT2 inhibitors group vs. placebo group stratified by category of SGLT2 inhibitors. DAPA, dapagliflozin; CANA, canagliflozin; IPRA, ipragliflozin; TOFO, Tofogliflozin; EMPA, empagliflozin; BEXA, bexagliflozin; LUSE, luseogliflozin; SOTA, Sotagliflozin.

FIGURE 6.

FIGURE 6

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Subgroup analysis of the hypovolemia events between the SGLT2 inhibitors group vs. the placebo group stratified by age.

FIGURE 7.

FIGURE 7

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Subgroup analysis of the hypovolemia events between the SGLT2 inhibitors group vs. the placebo group stratified by eGFRs.

Discussion

With 57 included RCTs involving 68,622 patients, this meta-analysis indicated that SGLT2 inhibitors increased the risk of hypovolemia, especially in patients with older age and lower eGFR. Both EMPA-REG OUTCOME trial and the CANVAS trial demonstrated that prescribing SGLT2 inhibitors reduces the risk of hospitalization for heart failure (40, 63). Researchers subsequently conducted a serial clinical trial to confirm this prevailing benefit. The recently finished DAPA-HF trial suggests that dapagliflozin decreases the risk of worsening heart failure or death from cardiovascular causes among those with or without T2DM (58). Although the 2020 CCS/CHFS heart failure guidelines recommended applicating SGLT2 inhibitors to heart failure patients with or without T2DM (64), the mechanisms underpinning the cardioprotective effects of SGLT2 inhibitors remain in debate (65). Natriuresis and osmotic diuresis of SGLT2 inhibitors was thought to play a crucial role in cardioprotective effects (66). Just like every coin has two sides, depending on the osmotic diuresis of SGLT2 inhibitors, it is plausible to consider the possibility of the increased risk of volume depletion with caution. Although individual large multicentral RCTs reported the frequency of adverse events related to volume depletion did not differ between SGLT2 inhibitors and control groups (59, 62). Because of the low statistical power of individual studies and the heterogeneity of the population included in studies (e.g., with or without diabetes), the conclusion remained to be discussed. There is also a lot of meta-analysis evaluating the efficacy and safety of SGLT2 inhibitors, the majority of them focuses on analyzing the risk of hypoglycemia, and genital and urinary tract infections (67). Some of them threw light on the osmotic diuresis-related adverse event, with the result of there being no evidence of SGLT2 inhibitors increasing the risk of hypovolemia (68). This conclusion is not consistent with our meta-analysis. We thought there are three explanations for this inconsistency. First, in contrast to the earlier analysis, our meta-analysis covered a wider spectrum of the category of SGLT2 inhibitors. Second, adopting different analysis methods could impact the result. At last, the differences in included RCTs could also contribute to the inconsistency.

Our meta-analysis also investigated the category of SGLT2 inhibitors, patients’ age, and baseline eGFR impact on the risk of hypovolemia associated with SGLT2 inhibitors treatment. When stratified by category of SGLT2 inhibitors, luseogliflozin, Tofogliflozin and ipragliflozin had RRs greater than 2. It should be noted that they exist a broad 95% CIs as well, which implies the imprecision of statistics. It should be cautious to interpret this point. Canagliflozin showed an increased risk of hypovolemia compared with dapagliflozin or empagliflozin. This might be explained by canagliflozin having the lowest SGLT2/SGLT1 affinity ratio and empagliflozin the highest (69). People aged ≥65 years and with baseline eGFR <60 mL/min/1.73 m2 were more predisposed to hypovolemia; the deteriorative kidney function could be responsible for the conclusion.

We further noticed that our meta-analysis included several trials that tested high doses of SGLT2 inhibitors, such as Dapagliflozin 50 mg, Empagliflozin 12.5 mg, Empagliflozin 25 mg, and so on. With the concerns of whether the result may be influenced by these dosages, we performed an additional subgroup analysis depending on the dosage of SGLT2 with U.S. Food and Drug Administration (FDA) approval. As presented in Figure 8, even though excluded the study arms of dosages that were without FDA approval, the combined RR of SGLT2 was 1.11(95% CI:1.02–1.22), which means SGLT2 inhibitors increase the risk of hypovolemia. So, we conclude that the result could not be influenced by high doses of SGLT2 inhibitors.

FIGURE 8.

FIGURE 8

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Subgroup analysis of the hypovolemia events between the SGLT2 inhibitors group vs. the placebo group stratified by FDA approval dosage.

Because diuretics might augment the effect of SGLT2 inhibitors, with increasing risk of hypovolemia. The issue of whether the increased risk of hypovolemia associated with SGLT2 inhibitors ascribes to the diuretic treatment should be examined. Among the included 57 studies, there were 15 citations (20, 24, 29, 31, 38, 39, 49, 51, 53–55, 60, 61) providing the information on SGLT2 inhibitors add-on to the background diuretic treatment. Figure 9 shows that the pooled RR of interest in patients not treated without a diuretic at baseline is 1.14 (95% CI: 1.01–1.29) vs. 1.09 (95%CI: 0.96–1.23) in patients treated with a diuretic and the P for interaction is 0.57, which implied the difference of subgroup did not be attributed to diuretic treatment.

FIGURE 9.

FIGURE 9

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Subgroup analysis of the hypovolemia events between the SGLT2 inhibitors group vs. the placebo group stratified by diuretics treatment.

Collectively, the result of our meta-analysis, that SGLT2 inhibitors increased the risk of hypovolemia, was robust.

This meta-analysis also had some limitations. First, the assessment of hypovolemia was based on a predefined list of preferred terms. This strategy may underestimate the risk of hypovolemia associated with SGLT2 inhibitors. Second, the pooled data was basically drawn from 22 RCTs evaluating dapagliflozin,12 RCTs with canagliflozin, and 13 RCTs with empagliflozin, it should be cautious to extrapolate the conclusion to another category of SGLT2 inhibitors. Finally, we were unable to further stratify the concomitant drug, due to the paucity of data provided by eligible RCTs.

In conclusion, our present meta-analysis indicated that increased risk of hypovolemia associated with SGLT2 inhibitors in T2DM patients. The incidence of hypovolemia is different among the category of SGLT2 inhibitors and may keep rising with the age, and degeneration of renal function. To achieve an optimal fluid volume in patients with heart failure is an exquisite skill, hypovolemia in HF patients may be detrimental (70). Our meta-analysis unveils the increasing risk of hypovolemia associated with SGLT2 inhibitors, if ignoring this risk, hypovolemia resulting in hypotension and renal hypoperfusion may overwhelm the benefit of SGLT2 inhibitors treatment. It is necessary to pay attention for the risk of hypovolemia associated with SGLT2 inhibitors under the context of some heart failure guidelines recommending prescribe SGLT2 inhibitors for heart failure patients with or without T2DM. The interrelation between SGLT2 inhibitors and hypovolemia and the underlying mediating mechanisms of cardio-protection deserves to be further investigated. It is important to take the advantage of the cardio-protection effect of SGLT2 inhibitors to the maximum extent and avoid the risk of hypovolemia associated with SGLT2 inhibitors to the utmost. It is also intriguing to conduct large-scale, multicenter, double-blind, head-to-head RCTs to compare the efficacy and safety of SGLT2 inhibitors with diuretics.

Conclusion

In summary, the present meta-analysis indicated that SGLT2 inhibitors increased the risk of hypovolemia in patients with T2DM. The incidence of hypovolemia may increase with the decreasing of eGFR and growth of age. It is important to pay attention to the potential adverse event, except the common adverse event such as hypoglycemia, and genitourinary infection. Our meta-analysis indicates that there is an increase in hypovolemia associated with SGLT2 inhibitors treatment. It is necessary to be concerned about the risk of hypovolemia associated with SGLT2 inhibitors, especially in older individuals and those with moderate renal impairment.

Data availability statement

The original contributions presented in this study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author/s.

Author contributions

XR was involved in designing the study, literature retrieval, quality assessment, and manuscript writing. YZ, BW, XL, and QG contributed to the extract data. KL provided suggestions on carrying out the study. XC was involved in manuscript preparation. All authors contributed to the study’s conception and design.

Acknowledgments

The meta-analysis had been accepted by ESC Congress 2020 as an ePoster abstract.

Funding

This analysis received a grant from the Science and Technology Pillar Program in Sichuan Province, China (grant no. 2022YFS0356).

Conflict of interest

Author BW was employed by dMed Biopharmaceutical Company Limited. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcvm.2022.973129/full#supplementary-material

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Supplementary Materials

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Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author/s.

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