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Effectiveness and safety of empagliflozin: final results from the EMPRISE study

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Abstract

Aims/hypothesis

Limited evidence exists on the comparative safety and effectiveness of empagliflozin against alternative glucose-lowering medications in individuals with type 2 diabetes with the broad spectrum of cardiovascular risk. The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) cohort study was designed to monitor the safety and effectiveness of empagliflozin periodically for a period of 5 years with data collection from electronic healthcare databases.

Methods

We identified individuals ≥18 years old with type 2 diabetes who initiated empagliflozin or dipeptidyl peptidase-4 inhibitors (DPP-4i) from 2014 to 2019 using US Medicare and commercial claims databases. After 1:1 propensity score matching using 143 baseline characteristics, we identified four a priori-defined effectiveness outcomes: (1) myocardial infarction (MI) or stroke; (2) hospitalisation for heart failure (HHF); (3) major adverse cardiovascular events (MACE); and (4) cardiovascular mortality or HHF. Safety outcomes included lower-limb amputations, non-vertebral fractures, diabetic ketoacidosis (DKA), acute kidney injury (AKI), severe hypoglycaemia, retinopathy progression, and short-term kidney and bladder cancers. We estimated HRs and rate differences (RDs) per 1000 person-years, overall and stratified by age, sex, baseline atherosclerotic cardiovascular disease (ASCVD) and heart failure.

Results

We identified 115,116 matched pairs. Compared with DPP-4i, empagliflozin was associated with lower risks of MI/stroke (HR 0.88 [95% CI 0.81, 0.96]; RD −2.08 [95% CI (−3.26, −0.90]), HHF (HR 0.50 [0.44, 0.56]; RD −5.35 [−6.22, −4.49]), MACE (HR 0.73 [0.62, 0.86]; RD −6.37 [−8.98, −3.77]) and cardiovascular mortality/HHF (HR 0.57 [0.47, 0.69]; RD −10.36 [−12.63, −8.12]). Absolute benefits were larger in older individuals and in those with ASCVD/heart failure. Empagliflozin was associated with an increased risk of DKA (HR 1.78 [1.44, 2.19]; RD 1.59 [1.08, 2.09]); decreased risks of AKI (HR 0.62 [0.54, 0.72]; RD −2.39 [−3.08, −1.71]), hypoglycaemia (HR 0.75 [0.67, 0.84]; RD −2.46 [−3.32, −1.60]) and retinopathy progression (HR 0.78 [0.63, 0.96)]; RD −9.49 [−16.97, −2.10]); and similar risks of other safety events.

Conclusions/interpretation

Empagliflozin relative to DPP-4i was associated with risk reductions of MI or stroke, HHF, MACE and the composite of cardiovascular mortality or HHF. Absolute risk reductions were larger in older individuals and in those who had history of ASCVD or heart failure. Regarding the safety outcomes, empagliflozin was associated with an increased risk of DKA and lower risks of AKI, hypoglycaemia and progression to proliferative retinopathy, with no difference in the short-term risks of lower-extremity amputation, non-vertebral fractures, kidney and renal pelvis cancer, and bladder cancer.

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Abbreviations

AKI:

Acute kidney injury

ASCVD:

Atherosclerotic cardiovascular disease

CIF:

Cumulative incidence function

CKD:

Chronic kidney disease

DKA:

Diabetic ketoacidosis

DPP-4i:

Dipeptidyl peptidase-4 inhibitors

EMPRISE:

EMPagliflozin compaRative effectIveness and SafEty

ESKD:

End-stage kidney disease

GLP-1RA:

Glucagon-like peptide-1 receptor agonists

HF:

Heart failure

HHF:

Hospitalisation for heart failure

MACE:

Major adverse cardiovascular events

MI:

Myocardial infarction

NNH:

Number needed to harm

NNT:

Number needed to treat

PPV:

Positive predictive value

PS:

Propensity score

PY:

Person-years

RD:

Rate difference

SGLT2i:

Sodium–glucose cotransporter 2 inhibitor

References

  1. Emerging Risk Factors Collaboration, Di Angelantonio E, Kaptoge S et al (2015) Association of cardiometabolic multimorbidity with mortality. JAMA 314(1):52–60. https://doi.org/10.1001/jama.2015.7008

    Article  CAS  Google Scholar 

  2. Zinman B, Wanner C, Lachin JM et al (2015) Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes. N Engl J Med 373(22):2117–2128. https://doi.org/10.1056/NEJMoa1504720

    Article  CAS  PubMed  Google Scholar 

  3. Anker SD, Butler J, Filippatos G et al (2021) Empagliflozin in heart failure with a preserved ejection fraction. N Engl J Med 385(16):1451–1461. https://doi.org/10.1056/nejmoa2107038

    Article  CAS  PubMed  Google Scholar 

  4. Packer M, Anker SD, Butler J et al (2020) Cardiovascular and renal outcomes with empagliflozin in heart failure. N Engl J Med 383(15):1413–1424. https://doi.org/10.1056/nejmoa2022190

    Article  CAS  PubMed  Google Scholar 

  5. D’Andrea E, Kesselheim AS, Franklin JM, Jung EH, Hey SP, Patorno E (2020) Heterogeneity of antidiabetic treatment effect on the risk of major adverse cardiovascular events in type 2 diabetes: a systematic review and meta-analysis. Cardiovasc Diabetol 19(1):154. https://doi.org/10.1186/s12933-020-01133-1

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Zelniker TA, Wiviott SD, Raz I et al (2019) SGLT2 inhibitors for primary and secondary prevention of cardiovascular and renal outcomes in type 2 diabetes: a systematic review and meta-analysis of cardiovascular outcome trials. Lancet 393(10166):31–39. https://doi.org/10.1016/s0140-6736(18)32590-x

    Article  CAS  PubMed  Google Scholar 

  7. Nyström T, Toresson Grip E, Gunnarsson J et al (2023) Empagliflozin reduces cardiorenal events, healthcare resource use and mortality in Sweden compared to dipeptidyl peptidase-4 inhibitors: real world evidence from the Nordic EMPRISE study. Diabetes Obes Metab 25(1):261–271. https://doi.org/10.1111/dom.14870

    Article  CAS  PubMed  Google Scholar 

  8. Karasik A, Lanzinger S, Chia-Hui Tan E et al (2023) Empagliflozin cardiovascular and renal effectiveness and safety compared to dipeptidyl peptidase-4 inhibitors across 11 countries in Europe and Asia: results from the EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) study. Diabetes Metab 49(2):101418. https://doi.org/10.1016/j.diabet.2022.101418

    Article  CAS  PubMed  Google Scholar 

  9. Htoo PT, Tesfaye H, Schneeweiss S et al (2022) Comparative effectiveness of empagliflozin vs liraglutide or sitagliptin in older adults with diverse patient characteristics. JAMA Netw Open 5(10):e2237606. https://doi.org/10.1001/jamanetworkopen.2022.37606

    Article  PubMed  PubMed Central  Google Scholar 

  10. Desai RJ, Glynn RJ, Everett BM et al (2022) Comparative effectiveness of Empagliflozin in reducing the burden of recurrent cardiovascular hospitalizations among older adults with diabetes in routine clinical care. Am Heart J 254:203–215. https://doi.org/10.1016/j.ahj.2022.09.008

    Article  CAS  PubMed  Google Scholar 

  11. Patorno E, Pawar A, Franklin JM et al (2019) Empagliflozin and the risk of heart failure hospitalization in routine clinical care. Circulation 139(25):2822–2830. https://doi.org/10.1161/circulationaha.118.039177

    Article  CAS  PubMed  Google Scholar 

  12. Patorno E, Pawar A, Wexler DJ et al (2022) Effectiveness and safety of empagliflozin in routine care patients: results from the EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) study. Diabetes Obes Metab 24(3):442–454. https://doi.org/10.1111/dom.14593

    Article  CAS  PubMed  Google Scholar 

  13. D’Andrea E, Wexler DJ, Kim SC, Paik JM, Alt E, Patorno E (2023) Comparing effectiveness and safety of SGLT2 inhibitors vs DPP-4 inhibitors in patients with type 2 diabetes and varying baseline HbA1c levels. JAMA Intern Med 183(3):242–254. https://doi.org/10.1001/jamainternmed.2022.6664

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Fu EL, Patorno E, Everett BM et al (2023) Sodium-glucose cotransporter 2 inhibitors vs. sitagliptin in heart failure and type 2 diabetes: an observational cohort study. Eur Heart J 44(24):2216–2230. https://doi.org/10.1093/eurheartj/ehad273

    Article  CAS  PubMed  Google Scholar 

  15. Patorno E, Najafzadeh M, Pawar A et al (2020) The EMPagliflozin compaRative effectIveness and SafEty (EMPRISE) study programme: design and exposure accrual for an evaluation of empagliflozin in routine clinical care. Endocrinol Diabetes Metab 3(1):e00103. https://doi.org/10.1002/edm2.103

    Article  PubMed  Google Scholar 

  16. Karter AJ, Warton EM, Lipska KJ et al (2017) Development and validation of a tool to identify patients with type 2 diabetes at high risk of hypoglycemia-related emergency department or hospital use. JAMA Int Med 177(10):1461. https://doi.org/10.1001/jamainternmed.2017.3844

    Article  Google Scholar 

  17. Bobo WV, Cooper WO, Epstein RA Jr, Arbogast PG, Mounsey J, Ray WA (2011) Positive predictive value of automated database records for diabetic ketoacidosis (DKA) in children and youth exposed to antipsychotic drugs or control medications: a Tennessee Medicaid study. BMC Med Res Methodol 11:157. https://doi.org/10.1186/1471-2288-11-157

    Article  PubMed  PubMed Central  Google Scholar 

  18. Newton KM, Wagner EH, Ramsey SD et al (1999) The use of automated data to identify complications and comorbidities of diabetes: a validation study. J Clin Epidemiol 52(3):199–207. https://doi.org/10.1016/s0895-4356(98)00161-9

    Article  CAS  PubMed  Google Scholar 

  19. Waikar SS, Wald R, Chertow GM et al (2006) Validity of international classification of diseases, ninth revision, clinical modification codes for acute renal failure. J Am Soc Nephrol 17(6):1688–1694. https://doi.org/10.1681/asn.2006010073

    Article  PubMed  Google Scholar 

  20. Wright NC, Daigle SG, Melton ME, Delzell ES, Balasubramanian A, Curtis JR (2019) The design and validation of a new algorithm to identify incident fractures in administrative claims data. J Bone Miner Res 34(10):1798–1807. https://doi.org/10.1002/jbmr.3807

    Article  PubMed  Google Scholar 

  21. Setoguchi S, Solomon DH, Glynn RJ, Cook EF, Levin R, Schneeweiss S (2007) Agreement of diagnosis and its date for hematologic malignancies and solid tumors between medicare claims and cancer registry data. Cancer Causes Control 18(5):561–569. https://doi.org/10.1007/s10552-007-0131-1

    Article  PubMed  Google Scholar 

  22. Jones SA, Gottesman RF, Shahar E, Wruck L, Rosamond WD (2014) Validity of hospital discharge diagnosis codes for stroke: the Atherosclerosis Risk in Communities Study. Stroke 45(11):3219–3225. https://doi.org/10.1161/strokeaha.114.006316

    Article  PubMed  PubMed Central  Google Scholar 

  23. Kiyota Y, Schneeweiss S, Glynn RJ, Cannuscio CC, Avorn J, Solomon DH (2004) Accuracy of Medicare claims-based diagnosis of acute myocardial infarction: estimating positive predictive value on the basis of review of hospital records. Am Heart J 148(1):99–104. https://doi.org/10.1016/j.ahj.2004.02.013

    Article  PubMed  Google Scholar 

  24. Birman-Deych E, Waterman AD, Yan Y, Nilasena DS, Radford MJ, Gage BF (2005) Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors. Med Care 43(5):480–485. https://doi.org/10.1097/01.mlr.0000160417.39497.a9

    Article  PubMed  Google Scholar 

  25. Hill ME, Rosenwaike I (2001) The Social Security Administration’s Death Master File: the completeness of death reporting at older ages. Soc Secur Bull 64(1):45–51

    PubMed  Google Scholar 

  26. Research Data Assistance Center (ResDAC) (2020) Death information in the Research Identifiable Medicare Data. Available from https://resdac.org/articles/death-information-research-identifiable-medicare-data2021. Accessed 20 Mar 2023

  27. Olubowale OT, Safford MM, Brown TM et al (2017) Comparison of expert adjudicated coronary heart disease and cardiovascular disease mortality with the national death index: results from the REasons for Geographic And Racial Differences in Stroke (REGARDS) Study. J Am Heart Assoc 6(5):e004966. https://doi.org/10.1161/jaha.116.004966

    Article  PubMed  PubMed Central  Google Scholar 

  28. Gagne JJ, Glynn RJ, Avorn J, Levin R, Schneeweiss S (2011) A combined comorbidity score predicted mortality in elderly patients better than existing scores. J Clin Epidemiol 64(7):749–759. https://doi.org/10.1016/j.jclinepi.2010.10.004

    Article  PubMed  PubMed Central  Google Scholar 

  29. Kim DH, Patorno E, Pawar A, Lee H, Schneeweiss S, Glynn RJ (2020) Measuring frailty in administrative claims data: comparative performance of four claims-based frailty measures in the U.S. Medicare data. J Gerontol A Biol Sci Med Sci 75(6):1120–1125. https://doi.org/10.1093/gerona/glz224

    Article  PubMed  Google Scholar 

  30. Rosenbaum PR, Rubin DB (1983) The central role of the propensity score in observational studies for causal effects. Biometrika 70(1):41–55. https://doi.org/10.1093/biomet/70.1.41

    Article  MathSciNet  Google Scholar 

  31. Ripollone JE, Huybrechts KF, Rothman KJ, Ferguson RE, Franklin JM (2018) Implications of the propensity score matching paradox in pharmacoepidemiology. Am J Epidemiol 187(9):1951–1961. https://doi.org/10.1093/aje/kwy078

    Article  PubMed  PubMed Central  Google Scholar 

  32. Schneeweiss S, Gagne JJ, Glynn RJ, Ruhl M, Rassen JA (2011) Assessing the comparative effectiveness of newly marketed medications: methodological challenges and implications for drug development. Clin Pharmacol Ther 90(6):777–790. https://doi.org/10.1038/clpt.2011.235

    Article  CAS  PubMed  Google Scholar 

  33. Austin PC (2009) Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med 28(25):3083–3107. https://doi.org/10.1002/sim.3697

    Article  MathSciNet  PubMed  PubMed Central  Google Scholar 

  34. Franklin JM, Rassen JA, Ackermann D, Bartels DB, Schneeweiss S (2014) Metrics for covariate balance in cohort studies of causal effects. Stat Med 33(10):1685–1699. https://doi.org/10.1002/sim.6058

    Article  MathSciNet  PubMed  Google Scholar 

  35. Borenstein M, Hedges LV, Higgins JPT, Rothstein HR (2011) Introduction to meta-analysis. Wiley, Hoboken

    Google Scholar 

  36. Lash TL, Rothman KJ, VanderWeele TJ, Haneuse S (2020) Modern epidemiology. Wolters Kluwer, Philadelphia

    Google Scholar 

  37. ElSayed NA, Aleppo G, Aroda VR et al (2022) 9. Pharmacologic approaches to glycemic treatment: standards of care in diabetes—2023. Diabetes Care 46(Suppl 1):S140–S157. https://doi.org/10.2337/dc23-S009

    Article  PubMed Central  Google Scholar 

  38. Schneeweiss S, Rassen JA, Glynn RJ, Avorn J, Mogun H, Brookhart MA (2009) High-dimensional propensity score adjustment in studies of treatment effects using health care claims data. Epidemiology 20(4):512–522. https://doi.org/10.1097/EDE.0b013e3181a663cc

    Article  PubMed  PubMed Central  Google Scholar 

  39. Schneeweiss S (2006) Sensitivity analysis and external adjustment for unmeasured confounders in epidemiologic database studies of therapeutics. Pharmacoepidemiol Drug Saf 15(5):291–303. https://doi.org/10.1002/pds.1200

    Article  PubMed  Google Scholar 

  40. Monami M, Ahrén B, Dicembrini I, Mannucci E (2013) Dipeptidyl peptidase-4 inhibitors and cardiovascular risk: a meta-analysis of randomized clinical trials. Diabetes Obes Metab 15(2):112–120. https://doi.org/10.1111/dom.12000

    Article  CAS  PubMed  Google Scholar 

  41. Wang SV, Verpillat P, Rassen JA, Patrick A, Garry EM, Bartels DB (2016) Transparency and reproducibility of observational cohort studies using large healthcare databases. Clin Pharmacol Ther 99(3):325–332. https://doi.org/10.1002/cpt.329

    Article  CAS  PubMed  Google Scholar 

  42. Thomsen RW, Knudsen JS, Kahlert J et al (2021) Cardiovascular events, acute hospitalizations, and mortality in patients with type 2 diabetes mellitus who initiate empagliflozin versus liraglutide: a comparative effectiveness study. J Am Heart Assoc 10(11):e019356. https://doi.org/10.1161/jaha.120.019356

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Rau M, Thiele K, Hartmann NK et al (2022) Effects of empagliflozin on markers of calcium and phosphate homeostasis in patients with type 2 diabetes - data from a randomized, placebo-controlled study. Bone Rep 16:101175. https://doi.org/10.1016/j.bonr.2022.101175

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Zhuo M, Hawley CE, Paik JM et al (2021) Association of sodium-glucose cotransporter–2 inhibitors with fracture risk in older adults with type 2 diabetes. JAMA Netw Open 4(10):e2130762. https://doi.org/10.1001/jamanetworkopen.2021.30762

    Article  PubMed  PubMed Central  Google Scholar 

  45. Inzucchi SE, Iliev H, Pfarr E, Zinman B (2018) Empagliflozin and assessment of lower-limb amputations in the EMPA-REG OUTCOME trial. Diabetes Care 41(1):e4–e5. https://doi.org/10.2337/dc17-1551

    Article  PubMed  Google Scholar 

  46. Fralick M, Schneeweiss S, Redelmeier DA, Razak F, Gomes T, Patorno E (2021) Comparative effectiveness and safety of sodium-glucose cotransporter-2 inhibitors versus metformin in patients with type 2 diabetes: an observational study using data from routine care. Diabetes Obes Metab 23(10):2320–2328. https://doi.org/10.1111/dom.14474

    Article  CAS  PubMed  Google Scholar 

  47. Lytvyn Y, Bjornstad P, van Raalte DH, Heerspink HL, Cherney DZI (2020) The new biology of diabetic kidney disease—mechanisms and therapeutic implications. Endocr Rev 41(2):202–231. https://doi.org/10.1210/endrev/bnz010

    Article  PubMed  Google Scholar 

  48. Nadkarni GN, Ferrandino R, Chang A et al (2017) Acute kidney injury in patients on SGLT2 inhibitors: a propensity-matched analysis. Diabetes Care 40(11):1479–1485. https://doi.org/10.2337/dc17-1011

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Inzucchi SE, Wanner C, Hehnke U et al (2019) Retinopathy outcomes with empagliflozin versus placebo in the EMPA-REG OUTCOME trial. Diabetes Care 42(4):e53–e55. https://doi.org/10.2337/dc18-1355

    Article  PubMed  Google Scholar 

  50. Patorno E, Gopalakrishnan C, Franklin JM et al (2018) Claims-based studies of oral glucose-lowering medications can achieve balance in critical clinical variables only observed in electronic health records. Diabetes Obes Metab 20(4):974–984. https://doi.org/10.1111/dom.13184

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

    Phyo T. Htoo, Helen Tesfaye, Sebastian Schneeweiss, Robert J. Glynn, Julie M. Paik & Elisabetta Patorno

  2. Massachusetts General Hospital Diabetes Center, Harvard Medical School, Boston, MA, USA

    Deborah J. Wexler

  3. Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Brendan M. Everett

  4. Global Epidemiology, Boehringer Ingelheim International GmbH, Ingelheim am Rhein, Germany

    Niklas Schmedt & Anouk Déruaz-Luyet

  5. Global Medical Affairs, Lilly Deutschland GmbH, Bad Homburg vor der Höhe, Germany

    Lisette Koeneman

  6. Division of Renal (Kidney) Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    Julie M. Paik

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  1. Phyo T. Htoo
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Correspondence to Elisabetta Patorno.

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Acknowledgements

Some of the data were presented as an abstract at the 38th International Conference on Pharmacoepidemiology and Therapeutic Risk Management (ICPE) in 2022.

Data availability

Raw data used in the manuscript are not available to share due to the data user agreements in place but are available for purchase through the data vendors.

Funding

This study was supported by a research grant to the Brigham and Women’s Hospital from Boehringer Ingelheim. The authors had full control of the design and conduct of the study and the interpretation of the study’s findings. The authors retained the right of publication and determined the final wording of the manuscript. PTH was supported by a training grant (5T32DK007527) from the National Institute of Diabetes and Digestive and Kidney Diseases and is currently supported by a post-doctoral grant (4-22-PDFPM-15) from the American Diabetes Association. EP was supported by a career development grant (K08AG055670) from the National Institute on Aging and research grants from the Patient-Centered Outcomes Research Institute (DB-2020C2-20326) and the Food and Drug Administration (5U01FD007213).

Authors’ relationships and activities

PTH previously worked at Johnson & Johnson on unrelated work. SS reports investigator-initiated grants to the Brigham and Women’s Hospital from Boehringer Ingelheim International Gmbh, and owns equity in a software manufacturer, Aetion, Inc. DJW reports serving on data monitoring committees for Novo Nordisk, consulting for Elsevier and UpToDate, and grants from PCORI. BME reports consulting for Janssen, Eli Lilly and Company, Provention Bio, Ipsen Pharmaceuticals, the NIDDK, the American Heart Association and UptoDate; and grants from PCORI and Novo Nordisk outside the submitted work. RJG reports grants from Amgen, AstraZeneca, Kowa, Novartis and Pfizer outside the submitted work. LK is an employee of Eli Lilly and Company, and owns stock in Eli Lilly and Company. NS and AD-L are employees of Boehringer Ingelheim International GmbH. The authors declare that there are no other relationships or activities that might bias, or be perceived to bias, their work.

Contribution statement

All authors approved the final version to be published. PTH contributed to the study design, data analysis and initial development of the manuscript, and is the guarantor of this work. HT contributed to the data analysis and critical review of the manuscript. EP contributed to the study conception and design and critical review of the manuscript. DJW, JMP and BME contributed to the study conception and critical review of the manuscript. RJG and SS contributed to the study design, statistical input and critical review of the manuscript. NS, LK and AD-L participated in the study design, study conception and critical review of the manuscript. PTH and EP are responsible for the integrity of the work as a whole and are guarantors of the study.

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Htoo, P.T., Tesfaye, H., Schneeweiss, S. et al. Effectiveness and safety of empagliflozin: final results from the EMPRISE study. Diabetologia (2024). https://doi.org/10.1007/s00125-024-06126-3

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