{"paper_id":"1c93d02c-a6bf-4b81-bb82-8ea987d571ca","body_text":"Efficacy and Safety of SGLT2 Inhibitors in the Treatment of Type 2 Diabetes: \nAn Umbrella Review\nLiu Haoling1#,Rui Ma2 #,Rui Ma2*\n1Mudanjiang Medical University，Heilongjiang，157011, China\n2Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical \nSciences, Beijing, 100700, China.\n#The same contribution was made in the paper.\n*Corresponding Author:\nRui Ma\n1875602128@qq.com\nAbstract\nObjective: While sodium-glucose co-transporter 2 (SGLT2) inhibitors offer a novel, \ninsulin-independent approach to managing type 2 diabetes (T2DM), their overall \nbenefit-risk profile, encompassing cardio-renal outcomes and long-term safety, \nrequires a comprehensive synthesis of the evidence. This umbrella review aims to \ndefinitively evaluate the efficacy and safety of SGLT2 inhibitors in patients with \nT2DM.\nMethods:This umbrella review systematically searched major databases for relevant \nsystematic reviews and meta-analyses up to September 2025. The methodological \nquality and certainty of evidence were assessed using AMSTAR 2 and GRADE tools.\nResults:SGLT2 inhibitors demonstrated significant benefits in glycemic control \n(HbA1c WMD: -0.52% to -0.56%), body weight (MD: -1.76 to -2.63 kg), and systolic \nblood pressure (WMD: -4.08 mmHg). They also showed marked cardio-renal \nprotection, reducing risks of major adverse cardiovascular events (RR=0.85), \nhospitalization for heart failure (RR=0.67), cardiovascular death (RR=0.75), all-cause \nmortality (RR=0.79), and composite renal outcomes (RR=0.59–0.64). Additionally, \nthey positively modulated inflammatory markers and adipokines. However, these \nbenefits were counterbalanced by increased risks of genital infections (OR=3.57), \nurinary tract infections (OR=1.34), and diabetic ketoacidosis (OR=2.19). The overall \nquality of evidence was generally low to very low.\nConclusion:SGLT2 inhibitors offer a multi-faceted therapeutic option for T2DM, \nproviding glycemic, cardiovascular, and renal benefits, which make them particularly \nvaluable for high-risk patients. Clinicians should be aware of the associated adverse \nevents. Future high-quality, long-term studies are warranted to strengthen these \nfindings.\nKeywords:Sodium-glucose cotransporter 2 inhibitors; type 2 diabetes; umbrella \nreview; cardiovascular outcomes; renal protection; safety\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\nThe management of hyperglycemia in type 2 diabetes mellitus (T2DM) remains \nchallenging due to the limited efficacy and adverse side effects of traditional \ntherapies. As a result, the development of novel glucose-lowering drugs has attracted \nincreasing attention, among which sodium-glucose co-transporter 2 inhibitors \n(SGLT2 inhibitors) have emerged as a highly promising class of agents 1–6.By \ninhibiting glucose reabsorption in the proximal renal tubules, SGLT2 inhibitors \npromote urinary glucose excretion and improve glycemic control, independent of \ninsulin secretion or sensitivity 7–11. In addition to their glucose-lowering effects, \nSGLT2 inhibitors offer multiple benefits, including weight reduction and blood \npressure lowering, which has led to their increasing use in combination with \nmetformin as part of dual therapy 10,12–14. Furthermore, growing evidence suggests that \nthese agents provide cardiovascular and renal protection in high-risk T2DM patients. \nHowever, the precise extent of these benefits—particularly their impact on hard renal \nendpoints such as kidney failure, dialysis, transplantation, or death due to kidney \ndisease—remains to be fully elucidated, as previous studies have not adequately \nassessed outcome differences across various stages of estimated glomerular filtration \nrate (eGFR) and proteinuria 14–17. Recent observations also suggest that SGLT2 \ninhibitors may enhance insulin sensitivity and modulate inflammatory biomarkers, \nmechanisms that are closely related to the pathophysiological processes of diabetes \nand its cardio-renal complications 13,18–20. In addition, although these drugs are \ngenerally well tolerated, the risk of adverse reactions still needs to be further explored \nin real-world studies 8,14,21,22. The currently approved SGLT2 inhibitors differ in \npharmacological potency—some inhibit only renal glucose transporters, while others \nact on both renal and intestinal transporters—thus, comparative studies are needed to \nassess their efficacy and safety 11,18,19,23. Therefore, a comprehensive synthesis of \nexisting evidence through systematic reviews and meta-analyses is essential to clarify \nthe multiple effects of SGLT2 inhibitors on glycemic control, cardiovascular and \nrenal outcomes, inflammatory markers, and safety, thereby providing guidance for \nclinical practice in type 2 diabetes17,19,24,25.\nAs a higher-level method of evidence synthesis, umbrella review integrates existing \nsystematic reviews and meta-analyses to evaluate the strength of evidence for \ndifferent associations using unified standards, identify potential biases, and \ncomprehensively determine the effectiveness of SGLT2 inhibitors on various health \noutcomes26–29. Based on this, the present study adopts the umbrella review approach, \nstrictly following the PRISMA-P guidelines, to systematically integrate published \nevidence from relevant systematic reviews and meta-analyses 30,31. The aim is to \ncomprehensively assess the effects of SGLT2 inhibitors on multiple health indicators, \nincluding blood glucose control, cardiovascular outcomes, renal function, weight \nchanges, and safety, to clarify the evidence levels for different clinical populations \nand endpoint outcomes, provide a scientific basis for the clinical application and \nindividualized treatment strategies of SGLT2 inhibitors, and offer a reference for \nfuture research directions11,14,16,32.\n1 Methods\n1. Umbrella Review Method\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nWe systematically collected and integrated data from multiple systematic reviews \n(SRs) and meta-analyses (MAs) on the impact of Sodium-Glucose Transporter 2 \nInhibitors interventions on health outcomes. By comprehensively evaluating all \nrelevant clinical outcome information, we aimed to outline the full scope of evidence \nin this field and provide integrated insights for the application of SGLT2 interventions \nin healthcare. The protocol for this umbrella review was pre-registered on \nPROSPERO (ID: CRD420251145145), and the study results are reported in \naccordance with the Preferred Reporting Items for Systematic Reviews and \nMeta-Analyses (PRISMA) guidelines.\n1.2 Literature Search\nTo comprehensively obtain relevant literature, we searched multiple authoritative \ndatabases, covering the period from their inception to August 2025, including but not \nlimited to Embase, Medline, the Cochrane Database of Systematic Reviews, and Web \nof Science. A pre-designed search strategy was used: (Sodium-Glucose Transporter 2 \nInhibitors) AND (systematic review or meta-analysis), strictly following the SIGN \nguidelines to ensure accuracy and comprehensiveness. In addition, we carefully \nreviewed the reference lists of all peer-reviewed articles that met the preliminary \nscreening criteria to avoid missing any potentially relevant studies. Discrepancies in \nthe literature screening process were resolved by a third professional researcher to \nreach a final consensus.\n1.3 Inclusion and Exclusion Criteria\nThis study included systematic reviews and meta-analyses of observational and/or \ninterventional studies evaluating the application of Sodium-Glucose Transporter 2 \nInhibitors as an intervention in the field of human health. Participants included \npopulations of any country or region, race, or gender. If a single article presented \nmultiple health outcomes, each outcome was extracted and analyzed separately. When \ntwo or more meta-analyses addressed the same Sodium-Glucose Transporter 2 \nInhibitors intervention topic, priority was given to the meta-analysis with a broader \nstudy population. In addition, data from meta-analyses with smaller sample sizes but \nwithout overlap with other studies were also extracted to maximize the use of all \nrelevant information. We excluded literature not published in English, as well as \nliterature based on animal experiments and/or in vitro study data. Furthermore, \narticles focusing solely on the principles of Sodium-Glucose Transporter 2 Inhibitors \nwithout assessing their impact on health outcomes were also excluded. If two or more \nmeta-analyses existed on the same topic, priority was given to the meta-analysis with \na broader study population.\n1.4 Data Extraction\nData were extracted from the included articles by two independent researchers. The \nextracted data included: 1) name of the first author and year of publication; 2) journal \nname; 3) characteristics of the study population; 4) health outcome indicators; 5) \ninterventions; 6) number of cases in each meta-analysis; 7) number of original studies \nincluded in each meta-analysis; 8) study design type of the original studies; 9) effect \nsize measures used in the meta-analysis and their corresponding estimates; 13) type of \neffect model (note: numbering follows the original text); 10) results of heterogeneity \ntests; 11) results of publication bias assessment. For quantitative synthesis, priority \nwas given to fully adjusted, study-specific pooled effect size estimates (including \nodds ratio [OR], mean estimate [ME], relative risk [RR], weighted mean difference \n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\n[WMD], standardized mean difference [SMD], etc.) and their 95% confidence \nintervals (CIs). In case of discrepancies in data extraction, a third researcher reviewed \nthe data and made the final decision.\n1.5 Methodological Quality Assessment and Evidence Grading\nThe methodological quality of the included studies was rigorously assessed using \nthe 11 items of AMSTAR2 to ensure the scientific rigor and standardization of the \nresearch process 33. At the same time, the GRADE system was used to grade the \nquality of evidence and provide corresponding recommendations, thereby clarifying \nthe reliability and credibility of different research results34.\n1.6 Data Analysis\nFor each meta-analysis, a random-effects model (or a fixed-effects model as \nactually applied) was used to present the extracted intervention exposure data, health \noutcome data, and fully adjusted study-specific pooled effect sizes with their 95% \nCIs. The I ²  statistic and Cochran's Q test were used to assess the degree of \nheterogeneity between studies and to determine the consistency of the results. Egger’\ns test was used to assess small-study effects (marked as NA if not reported in the \nliterature). For small-study effects and heterogeneity tests, a P-value < 0.1 was \nconsidered statistically significant; for other tests, a P-value < 0.05 was considered \nstatistically significant.\n2 Outcome\n2.1  Characteristics of MA\nFigure 1 shows the flowchart of the literature selection process. After a systematic \nsearch, a total of 5759 articles were identified. After applying the inclusion and \nexclusion criteria, 36 MAs were included, covering 8 different outcome measures \n(Figure 2). The characteristics of all the included studies are shown in Table 1.\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nFig. 1. Flowchart of the selection process.\nFigure 2 Sankey diagram showing the associations between various studies and \nhealth-related outcome categories\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nTable1 Evidence summary\nOutcome\nIntervention measures for the \nexperimental group\nIntervention measures for \nthe control group\nStudy\nNo. of \ntotal\ngroup\nNo. of \nstudies in \nMA\nRCT Cohort\nCase \ncontrol\nEffects \nmodel\nI²\nEgger test \nP value\nGlycated Hemoglobin\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0.14 NA\nFasting Plasma Glucose\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0.18 NA \nBody Mass Index\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Random 0.9 NA\nWaist Circumference\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0 NA\nSystolic Blood Pressure\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0 NA\nDiastolic Blood Pressure\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0 NA\nSerum Uric Acid\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Random 0.5 NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nIncident Hypoglycemia\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0 NA\nUrinary Tract Infection\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0 NA\nGenital Tract Infection\nSodium glucose \nco-transport-2 inhibitors\nPlacebo Giovanni Musso et al. 20127 4063\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Fixed 0 NA\nHemoglobin Level\nSodium-glucose cotransporter \n2 inhibitors \nPlacebo Mehmet Kanbay et al. 20229 14748\nType 2 \nDiabetes \nMellits\n7 7 0 0 Random 0.94 NA\nHematocrit Level\nSodium-glucose cotransporter \n2 inhibitors \nPlacebo Mehmet Kanbay et al. 20229 14748\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Random 0.99 NA\nInsulin Sensitivity/Insulin Resistance in \nT2DM Population\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nMohammad \nFakhrolmobasheri et al. \n202319\n1178\nType 2 \nDiabetes \nMellitus\n13 13 0 0 Random 0.848 0.19\nMajor Cardiovascular Events\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo/active control\nKarin Ra˚dholm et al. \n201815\n32893\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0 NA\nCardiovascular Death\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n30210\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0.804 NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nNon-fatal Myocardial Infarction\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n30210\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0 NA\nNon-fatal Stroke\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n30210\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0.614 NA\nHospitalisation for Unstable Angina\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n30210\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0 NA\nHospitalisation for Heart Failure\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n30210\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0 NA\nAll-cause Death\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n30210\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0.546 NA\nComposite renal outcomes\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n18064\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0 NA\nAlbuminuria Progression\nSodium-glucose cotransporter \n2 inhibitors\nPlacebo\nKarin Ra˚dholm et al. \n201815\n15139\nType 2 \nDiabetes \nMellitus\n92 82 0 0 Fixed 0 NA\nChange in HbA₁c from baseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo De Buitléir et al. 202135 1661\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0.79 NA\nChange in fasting plasma glucose from \nbaseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo De Buitléir et al. 202135 1661\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0 NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nChange in weight from baseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo De Buitléir et al. 202135 1661\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0 NA\nChange in systolic blood pressure from \nbaseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo De Buitléir et al. 202135 1661\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0 NA\nChange in diastolic blood pressure from \nbaseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo De Buitléir et al. 202135 1661\nType 2 \nDiabetes \nMellitus\n4 4 0 0 Random 0 NA\nProportion of participants achieving HbA₁c\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo De Buitléir et al. 202135 1661\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0.2 NA\nChange in C-reactive protein (CRP) from \nbaseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Wang et al. 202236 6261\nType 2 \nDiabetes \nMellits\n14 14 0 0 Random 0.5 NA\nChange in tumor necrosis factor-alpha \n(TNF-α) from baseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Wang et al. 202236 6261\nType 2 \nDiabetes \nMellitus\n7 7 0 0 Random 0 NA\nChange in interleukin-6 (IL-6) from baseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Wang et al. 202236 6261\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0.88 NA\nChange in leptin from baseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Wang et al. 202236 6261\nType 2 \nDiabetes \nMellitus\n9 9 0 0 Random 0.6 NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nChange in adiponectin from baseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Wang et al. 202236 6261\nType 2 \nDiabetes \nMellitus\n17 17 0 0 Random 0.26 NA\nChange in ferritin from baseline\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Wang et al. 202236 6261\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0.97 NA\nComposite renal outcome\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n9 9 0 0 Random 0.29 NA\nDecline in estimated glomerular filtration \nrate ≥40%\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n4 4 0 0 Random 0.59 NA\nDoubling of serum creatinine\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n3 3 0 0 Random 0.34 NA\nDialysis or renal replacement therapy\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n5 5 0 0 Random 0 NA\nSustained estimated glomerular filtration rate \n<15 ml/min/1.73㎡ for ≥30 days\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n3 3 0 0 Random 0 NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nEnd-stage renal disease\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n3 3 0 0 Random 0 NA\nAcute kidney injury\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0 NA\nRenal death\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0 NA\nProgression to macroalbuminuria\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Bose et al. 202337 71553\nType 2 \nDiabetes \nMellitus\n2 2 0 0 Random 0.91 NA\nComposite renal outcome\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Zhang et al. 202038 28529\nType 2 \nDiabetes \nMellius\n3 3 0 0 Random 0.51 NA\nAcute renal failure or injury\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Zhang et al. 202038 48731\nType 2 \nDiabetes \nMellitus\n15 15 0 0 Random 0 0.029\nRenal impairment\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Zhang et al. 202038 28865\nType 2 \nDiabetes \nMellitus\n17 17 0 0 Random 0 NA\nChange in estimated glomerular filtration \nrate\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Zhang et al. 202038 15556\nType 2 \nDiabetes \nMellitus\n46 46 0 0 Random 0.99 NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nChange in urine albumin-creatinine ratio\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Zhang et al. 202038 10129\nType 2 \nDiabetes \nMellitus\n18 18 0 0 Random 0.98 NA\nComposite renal outcome\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Heerspink et al. 202039 38612\nType 2 \nDiabetes \nMellitus\n4 4 0 0 Random 0 NA\nAcute kidney injury\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Heerspink et al. 202039 38625\nType 2 \nDiabetes \nMellitus\n4 4 0 0 Random 0 0.42\nProgression to macroalbuminuria\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Heerspink et al. 202039 38598\nType 2 \nDiabetes \nMellitus\n4 4 0 0 Random 0 NA\nDecline in eGFR ≥ 40%\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Heerspink et al. 202039 38581\nType 2 \nDiabetes \nMellitus\n4 4 0 0 Random 0 NA\nEnd-stage kidney disease\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Heerspink et al. 202039 38671\nType 2 \nDiabetes \nMellitus\n4 4 0 0 Random 0 NA\nAll-cause mortality\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Usman et al. 201822 34987\nType 2 \nDiabetes \nMellitus\n18 18 0 0 Random 0 NA\nMajor adverse cardiac events\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Usman et al. 201822 34987\nType 2 \nDiabetes \nMellitus\n31 31 0 0 Random 0 NA\nNon-fatal myocardial infarction\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Usman et al. 201822 34987\nType 2 \nDiabetes \nMellitus\n27 27 0 0 Random 0 NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nHeart failure/hospitalisation for heart failure\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Usman et al. 201822 34987\nType 2 \nDiabetes \nMellitus\n14 14 0 0 Random 0 NA\nNon-fatal stroke\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Usman et al. 201822 34987\nType 2 \nDiabetes \nMellitus\n28 28 0 0 Random 0 NA\nAtrial fibrillation\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Usman et al. 201822 34987\nType 2 \nDiabetes \nMellitus\n16 16 0 0 Random 0 NA\nUnstable angina\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Usman et al. 201822 34987\nType 2 \nDiabetes \nMellitus\n18 18 0 0 Random 0 NA\nChange in glycated hemoglobin (HbA1c, %)\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Tang et al. 201740 4235\nType 2 \nDiabetes \nMellitus\n7 7 0 0 Random 0.79 >0.05\nChange in fasting plasma glucose (FPG, \nmmol/L)\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Tang et al. 201740 4235\nType 2 \nDiabetes \nMellitus\n7 7 0 0 Random 0.68 >0.05\nChange in body weight (kg)\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Tang et al. 201740 4235\nType 2 \nDiabetes \nMellitus\n7 7 0 0 Random 0.75 >0.05\nChange in insulin dose (IU)\nSodium-glucose \ncotransporter-2 inhibitors\nPlacebo Tang et al. 201740 4235\nType 2 \nDiabetes \nMellitus\n6 6 0 0 Random 0.91 <0.01\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nDiabetic ketoacidosis\nSodium-glucose \nco-transporter-2 inhibitors\nPlacebo Liu et al. 202024 51701\nType 2 \nDiabetes \nMellitus\n30 30 0 0 Fixed 10% NA\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\n2.2 Blood Glucose Control and Metabolic Parameters\nSGLT2 inhibitors demonstrated significant improvements in blood glucose control \nand metabolic parameters. In patients with type 2 diabetes, the weighted mean \ndifference (WMD) in glycated hemoglobin (HbA ₁c) levels was -0.56 (95% CI: -0.67 \nto -0.44); the WMD in fasting plasma glucose (FPG) was -18.28 mg/dL (95% CI: \n-20.66 to -15.89) (additionally, the WMD in change in FPG was -0.95 mmol/L, 95% \nCI: -1.21 to -0.70). The standardized mean difference (SMD) for insulin \nsensitivity/resistance was 0.72 (95% CI: 0.32 to 1.12). The odds ratio (OR) for \nachieving the HbA ₁c target was 3.07 (95% CI: 2.29 to 4.12). The WMD for changes \nin insulin dosage was -8.79 IU (95% CI: -13.36 to -4.22). The odds ratio (OR) for the \noccurrence of diabetic ketoacidosis was 2.19 (95% CI: 1.41 to 3.39) (Figure 3).\nFigure 3: Forest Plot of the Effects of SGLT2 on Blood Glucose Control and \nMetabolic Parameters in Multiple Populations\n2.3 Weight and Body Composition\nSGLT2 inhibitors have a significant effect on improving body weight and body \ncomposition. In patients with type 2 diabetes, the weighted mean difference (WMD) \nin body mass index (BMI) was -1.17 (95% CI: -1.41 to -0.92); the weighted mean \ndifference (WMD) in waist circumference was -1.20 cm (95% CI: -2.00 to -0.43). The \nmean difference (MD) in body weight change was -1.76 kg (95% CI: -2.04 to -1.48); \nthe weighted mean difference (WMD) in body weight change was -2.63 (95% CI: \n-3.10 to -2.16) (Figure 4).\nFigure 4: Forest Plot of the Effects of SGLT2 on Weight and Body Composition\n2.4 Cardiovascular Outcomes and Blood Pressure\nSGLT2 inhibitors have significant benefits in cardiovascular outcomes and blood \npressure control. The weighted mean difference (WMD) in systolic blood pressure \nwas -4.08 mmHg (95% CI: -4.91 to -3.24); the WMD in diastolic blood pressure was \n-1.16 mmHg (95% CI: -1.67 to -0.66) (additionally, the MD in change in SBP was \n-3.6 mmHg, 95% CI: -4.8 to -2.4; the MD in change in DBP was -1.5 mmHg, 95% \nCI: -2.4 to -0.6). The risk ratio (RR) for major cardiovascular events was 0.85 (95% \nCI: 0.77 to 0.93); the RR for cardiovascular death was 0.75 (95% CI: 0.65 to 0.87). \nThe RR for nonfatal myocardial infarction was 0.84 (95% CI: 0.73 to 0.98); the RR \nfor hospitalization for heart failure was 0.67 (95% CI: 0.55 to 0.80) (additionally, the \nOR for heart failure hospitalization was 0.67, 95% CI: 0.59 to 0.76). No significant \nimprovement was observed in nonfatal stroke (RR = 1.03, 95% CI: 0.86 to 1.24; OR = \n1.02, 95% CI: 0.85 to 1.21) and hospitalization for unstable angina (RR = 0.95, 95% \nCI: 0.73 to 1.24; OR = 0.95, 95% CI: 0.73 to 1.25) (Figure 5).\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nFigure 5: Forest Plot of the Effects of SGLT2 on Cardiovascular Outcomes and Blood \nPressure\n2.5 Hematological Parameters\nSGLT2 inhibitors affect certain hematological parameters. The weighted mean \ndifference (WMD) in serum uric acid levels was -41.50 μmol/L (95% CI: -47.22 to \n-35.79). The mean difference (MD) in hemoglobin levels was 5.60 g/L (95% CI: 3.73 \nto 7.47); the MD in hematocrit levels was 1.32% (95% CI: 1.21 to 1.44). The \nstandardized mean difference (SMD) in ferritin change was -1.15 (95% CI: -2.87 to \n0.57), which was not statistically significant (Figure 6).\nFigure 6: Forest Plot of the Effects of SGLT2 on Hematological Parameters\n2.6 Safety and Adverse Events\nCertain safety indicators of SGLT2 inhibitors warrant attention. The odds ratio \n(OR) for the occurrence of hypoglycemic events was 1.27 (95% CI: 1.05 to 1.53). The \nodds ratio (OR) for urinary tract infections was 1.34 (95% CI: 1.05 to 1.71); the odds \nratio (OR) for genital tract infections was 3.57 (95% CI: 2.59 to 4.93) (Figure 7).\nFigure 7: Forest Plot of the Effects of SGLT2 on Safety and Adverse Events\n2.7 Inflammatory and Adipokine Biomarkers\nSGLT2 inhibitors have a regulatory effect on certain inflammatory and adipokine \nfactors. The standardized mean difference (SMD) for changes in C-reactive protein \nwas -0.25 (95% CI: -47 to -0.03); the standardized mean difference (SMD) for \nchanges in tumor necrosis factor- α  was -0.05 (95% CI: -0.35 to 0.26), not \nstatistically significant; the standardized mean difference (SMD) for changes in \ninterleukin-6 was -0.57 (95% CI: -1.36 to 0.22), not statistically significant. The \nstandardized mean difference (SMD) for changes in leptin was -0.22 (95% CI: -0.43 \nto -0.01); the standardized mean difference (SMD) for changes in adiponectin was \n0.28 (95% CI: 0.15 to 0.41) (Figure 8).\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nFigure 8: Forest Plot of the Effects of SGLT2 on Inflammatory and Adipokine \nBiomarkers\n2.8 Renal Outcomes\nSGLT2 inhibitors have shown significant effects in renal protection. The risk ratio \n(RR) for composite renal outcomes was 0.59 (95% CI: 0.49 to 0.71) (additionally, the \nRR for composite renal outcomes was 0.64, 95% CI: 0.58 to 0.72; the OR for \ncomposite renal outcomes was 0.48, 95% CI: 0.40 to 0.59; the RR for composite renal \noutcomes was 0.61, 95% CI: 0.45 to 0.82). The RR for progression of albuminuria \nwas 0.72 (95% CI: 0.67 to 0.77); the RR for progression to macroalbuminuria was \n0.79 (95% CI: 0.62 to 1.00); the RR for a reduction in estimated glomerular filtration \nrate (eGFR) ≥40% was 0.62 (95% CI: 0.50 to 0.77) (additionally, the RR for eGFR \ndecline ≥ 40% was 0.58, 95% CI: 0.48 to 0.70); the RR for doubling of serum \ncreatinine was 0.67 (95% CI: 0.56 to 0.81); the RR for dialysis or renal replacement \ntherapy was 0.71 (95% CI: 0.59 to 0.86); the RR for end-stage renal disease was 0.70 \n(95% CI: 0.56 to 0.87) (additionally, the RR for end-stage kidney disease was 0.65, \n95% CI: 0.53 to 0.80); the RR for acute kidney injury was 0.79 (95% CI: 0.71 to 0.89) \n(additionally, the RR for acute kidney injury was 0.75, 95% CI: 0.66 to 0.85; the OR \nfor acute renal failure or injury was 0.77, 95% CI: 0.66 to 0.91); the RR for sustained \neGFR <15 ml/min was 0.66 (95% CI: 0.55 to 0.81); the RR for renal death was 0.53 \n(95% CI: 0.26 to 1.09); the OR for renal impairment was 1.48 (95% CI: 1.07 to 2.04); \nthe MD for change in eGFR was 0.16 (95% CI: -0.83 to 1.14); the SMD for change in \nurinary albumin-creatinine ratio (UACR) was -0.21 (95% CI: -0.49 to 0.07)(Figure 9).\nFigure 9: Forest Plot of the Effects of SGLT2 on Renal Outcomes\n2.9 All-Cause Mortality Rate\nSGLT2 inhibitors can significantly reduce all-cause mortality. The risk ratio (RR) \nfor all-cause mortality was 0.79 (95% CI: 0.70 to 0.88); the odds ratio (OR) for \nall-cause mortality was 0.79 (95% CI: 0.70 to 0.89) (Figure 10).\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nFigure 10: Forest Plot of the Effects of SGLT2 on All-Cause Mortality Rate\n2.10 Heterogeneity\nThe heterogeneity of the included studies varied depending on the outcome \nindicators. Some outcome indicators showed low to moderate heterogeneity, such as \nglycated hemoglobin (I ² = 0.14), fasting blood glucose (I ² = 0.18), systolic blood \npressure (I² = 0), and several cardiovascular hard endpoints (I ² mostly below 0.1). \nHowever, some outcome indicators exhibited high heterogeneity, such as body mass \nindex (I² = 0.9), insulin sensitivity (I ² = 0.848), weight change (I ² = 0.75), and \ncertain inflammatory markers (e.g., change in ferritin I ²  = 0.97). The high \nheterogeneity may stem from differences in intervention protocols, follow-up \nduration, baseline population characteristics, or measurement methods across studies.\n2.11 Publication Bias\nEgger's test results showed no significant publication bias (P > 0.05) in most \noutcome indicators of the meta-analyses. For example, changes in glycated \nhemoglobin (P > 0.05), changes in fasting blood glucose (P > 0.05), and major \ncardiovascular events (P > 0.05) all did not indicate the presence of small-study \neffects. Only a few outcome indicators, such as changes in insulin dosage (P < 0.01) \nand acute kidney injury (P = 0.029), had Egger's test P values < 0.1, suggesting \npossible publication bias. Overall, no significant publication bias was reported in all \nmeta-analyses.\n2.12 Assessment of Evidence Quality and Risk of Bias\nThe AMSTAR 2.0 tool was used to assess the methodological quality of the \nincluded systematic reviews/meta-analyses. The results showed that most studies \nperformed well in terms of search strategy, bias risk control, and statistical analysis, \nwith the overall quality of evidence rated as moderate to high. The main limitations \nwere that some studies did not have a pre-registered protocol or did not adequately \nreport the list and reasons for excluded studies. The risk of bias assessment indicated \nthat the included original studies were mainly randomized controlled trials, with an \noverall low risk of bias. Sensitivity analysis results showed that after excluding \nlow-quality studies, the pooled effect size remained robust, indicating a high level of \ncredibility for the evidence of the main outcome measures (Table 2).\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nTable 2. Analysis table of research methodological quality and evidence reliability in SGLT2 based on AMSTAR 2 scores and GRADE grading\nOutcome group AMSTAR2 GRADE\n Body Weight & Composition\nBody Mass Index SGLT2 inhibitors Critically low very low\nWaist Circumference SGLT2 inhibitors low low\nChange in weight from baseline SGLT2 inhibitors low low\nChange in body weight SGLT2 inhibitors low low\n Cardiovascular Outcomes & Blood Pressure\nSystolic Blood Pressure SGLT2 inhibitors low low\nDiastolic Blood Pressure SGLT2 inhibitors low low\nMajor Cardiovascular Events SGLT2 inhibitors Critically low very low\nCardiovascular Death SGLT2 inhibitors Critically low low\nNon-fatal Myocardial Infarction SGLT2 inhibitors Critically low very low\nNon-fatal Stroke SGLT2 inhibitors low low\nHospitalisation for Unstable Angina SGLT2 inhibitors low low\nHospitalisation for Heart Failure SGLT2 inhibitors low low\nChange in systolic blood pressure from baseline SGLT2 inhibitors low low\nChange in diastolic blood pressure from baseline SGLT2 inhibitors low low\nMajor adverse cardiac events SGLT2 inhibitors low low\nNon-fatal myocardial infarction SGLT2 inhibitors low low\nHeart failure/hospitalisation for heart failure SGLT2 inhibitors Critically low low\nNon-fatal stroke SGLT2 inhibitors Critically low low\nAtrial fibrillation SGLT2 inhibitors Critically low low\nUnstable angina SGLT2 inhibitors low low\n Glycemic Control & Metabolic Parameters\nGlycated Hemoglobin SGLT2 inhibitors low low\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nFasting Plasma Glucose SGLT2 inhibitors low low\nInsulin Sensitivity/Insulin Resistance in T2DM Population SGLT2 inhibitors Critically low low\nChange in HbA₁c from baseline SGLT2 inhibitors low low\nChange in fasting plasma glucose from baseline SGLT2 inhibitors Critically low low\nProportion of participants achieving HbA₁c SGLT2 inhibitors Critically low very low\nChange in glycated hemoglobin SGLT2 inhibitors Critically low low\nChange in fasting plasma glucose SGLT2 inhibitors low very low\nChange in insulin dose SGLT2 inhibitors low low\nDiabetic ketoacidosis SGLT2 inhibitors low low\n Hematological Parameters\nSerum Uric Acid SGLT2 inhibitors low low\nHemoglobin Level SGLT2 inhibitors Critically low low\nHematocrit Level SGLT2 inhibitors low low\nChange in ferritin from baseline SGLT2 inhibitors low very low\n Inflammation & Adipokine Biomarkers\nChange in C-reactive protein (CRP from baseline SGLT2 inhibitors low low\nChange in tumor necrosis factor-alpha (TNF-α from baseline SGLT2 inhibitors Critically low low\nChange in interleukin-6  from baseline SGLT2 inhibitors low very low\nChange in leptin from baseline SGLT2 inhibitors low low\nChange in adiponectin from baseline SGLT2 inhibitors Critically low very low\nIncident Hypoglycemia SGLT2 inhibitors low low\nUrinary Tract Infection SGLT2 inhibitors low low\nGenital Tract Infection SGLT2 inhibitors low low\nMortality\nAll-cause Death SGLT2 inhibitors Critically low low\nAll-cause mortality SGLT2 inhibitors low low\nRenal Outcomes\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\nComposite renal outcomes SGLT2 inhibitors low low\nAlbuminuria Progression SGLT2 inhibitors low very low\nComposite renal outcome SGLT2 inhibitors low low\nDecline in estimated glomerular filtration rate ≥40% SGLT2 inhibitors Critically low very low\nDoubling of serum creatinine SGLT2 inhibitors low low\nDialysis or renal replacement therapy SGLT2 inhibitors low very low\nSustained estimated glomerular filtration rate <15 ml/min/1.73㎡ for ≥30 days SGLT2 inhibitors Critically low low\nEnd-stage renal disease SGLT2 inhibitors low low\nAcute kidney injury SGLT2 inhibitors low low\nRenal death SGLT2 inhibitors Critically low very low\nProgression to macroalbuminuria SGLT2 inhibitors low low\nComposite renal outcome SGLT2 inhibitors Critically low low\nAcute renal failure or injury SGLT2 inhibitors low low\nRenal impairment SGLT2 inhibitors low very low\nChange in estimated glomerular filtration rate SGLT2 inhibitors low low\nChange in urine albumin-creatinine ratio SGLT2 inhibitors low low\nComposite renal outcome SGLT2 inhibitors low low\nAcute kidney injury SGLT2 inhibitors Critically low very low\nProgression to macroalbuminuria SGLT2 inhibitors low low\nDecline in eGFR ≥ 40% SGLT2 inhibitors low low\nEnd-stage kidney disease SGLT2 inhibitors low low\n . CC-BY 4.0 International licenseIt is made available under a \nperpetuity. \n is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint \nThe copyright holder for thisthis version posted December 1, 2025. ; https://doi.org/10.1101/2025.11.27.25341177doi: medRxiv preprint \n\n3 Conclusion \nIn summary, this umbrella review demonstrates that SGLT2 inhibitors offer \nmultiple benefits in patients with T2DM, including glycemic control, weight \nreduction, and cardiorenal protection. This provides a scientific basis for their clinical \napplication and the development of personalized treatment strategies. Additionally, \nthe review suggests the need for further exploration of efficacy differences across \nvarious eGFR stages and levels of proteinuria, as well as comparisons of efficacy and \nsafety among different types of SGLT2 inhibitors.\nReferences\n1. Quinn, L. 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