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Interventional Cardiology
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Outcomes of Prediabetes Compared with Normoglycaemia and Diabetes Mellitus in Patients Undergoing Percutaneous Coronary Intervention: A Systematic Review and Meta-analysis

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Published Online: Jun 21st 2023 Heart International. 2023;17(1):45–53 DOI: https://doi.org/10.17925/HI.2023.17.1.45
Authors: Muhammad Junaid Ahsan, Azka Latif, Soban Ahmad, Claire Willman, Noman Lateef, Muhammad Asim Shabbir, Mohammad Zoraiz Ahsan, Amman Yousaf, Maria Riasat, Magdi Ghali, Jolanta Siller-Matula, Yeongjin Gwon, Mamas A Mamas, Emmanouil S Brilakis, J Dawn Abbott, Deepak L Bhatt, Poonam Velagapudi
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Abstract
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Abstract:
Overview

Background

Patients with prediabetes are at increased risk of coronary artery disease (CAD). However, the association between prediabetes and adverse clinical outcomes following percutaneous coronary intervention (PCI) is inconsistent, in contrast to outcomes in patients with diabetes mellitus (DM). Thus, this meta-analysis evaluated the impact of dysglycaemia on PCI outcomes.

Methods

The PubMed, Embase, Cochrane, and ClinicalTrials.gov databases were systematically reviewed from inception of databases until June 2022. In 17 studies, outcomes of PCI in patients with prediabetes were compared with patients who were normoglycaemic, and patients with DM. The primary outcome was all-cause mortality at the longest follow-up.

Results

Included were 12 prospective and five retrospective studies, with 11,868, 14,894 and 13,536 patients undergoing PCI in the prediabetes, normoglycaemic and DM groups, respectively. Normoglycaemic patients had a statistically lower risk of all-cause mortality, (risk ratio [RR] 0.66, 95% confidence interval [CI] 0.52–0.84), myocardial infarction (MI; RR 0.76, 95% CI 0.61–0.95) and cardiac mortality (RR 0.58, 95% CI 0.39–0.87) compared with prediabetic patients undergoing PCI at the longest follow-up. Patients with prediabetes had a lower risk of all-cause mortality (RR=0.72 [95% CI 0.53–0.97]) and cardiac mortality (RR =0.47 [95% CI 0.23–0.93]) compared with patients with DM who underwent PCI.

Conclusion

Among patients who underwent PCI for CAD, the risk of all-cause and cardiac mortality, major adverse cardiovascular events and MI in prediabetic patients was higher compared with normoglycaemic patients but lower compared with patients with DM.

Keywords

Coronary artery disease, diabetes mellitus, impaired glucose tolerance, normoglycaemia, percutaneous coronary intervention, prediabetes

Article:

The American Diabetes Association (ADA) defines prediabetes as glycated haemoglobin (HbA1c) 5.7–6.4% or fasting plasma glucose (FPG) 100–125 mg/dL or 5.6–6.9 mmol/L.1 Patients with prediabetes have up to a 70% chance of developing diabetes and a two-fold higher risk of cardiovascular disease than normoglycaemic patients. Studies show results varying from no association to a strong association between prediabetes and major adverse cardiovascular events (MACE) following percutaneous coronary intervention (PCI).2–4 Choi et al. reported a higher incidence of coronary restenosis and mortality in the prediabetic cohort after PCI compared with patients with normoglycaemia.5 Retrospective subgroup analysis of two randomized controlled trials of drug-eluting stents (DES) showed higher cardiovascular mortality in prediabetic patients versus normoglycaemic patients, but no difference in bleeding rates.6 Another interesting analysis depicted higher mortality with both low (<5.5%) and high (>8.0%) HbA1c among patients admitted for PCI.7 The results were compared with the reference group, whose HbA1c ranged from 6.1% to 7.0%; which represented the fraction of the reference group that met criterion for prediabetes and had better outcomes. Owing to contradictory literature, the PCI outcomes of prediabetic patients remains debatable. We performed a meta-analysis of 17 studies to better understand the outcomes of PCI across the spectrum of glycaemic control, i.e. normal glucose metabolism, prediabetes and diabetes mellitus (DM).

Methods

We conducted a systematic review and meta-analysis according to Cochrane collaboration guidelines and reported the results using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Figure 1).8 We searched the PubMed, Embase, Cochrane and Google Scholar databases using the terms “prediabetes”, “diabetes mellitus”, “percutaneous coronary intervention” or “PCI”, “ischaemic heart disease”, and “coronary artery disease” from inception until June 2022 without any language restrictions. All relevant publications, review articles and their references were manually screened to retrieve additional eligible studies.

We included only full manuscripts of studies that met the following inclusion criteria: 1) compared patients with prediabetes and normoglycaemia undergoing PCI; 2) compared patients with prediabetes and DM in patients undergoing PCI. Prediabetes and DM were defined according to the ADA (2021) definitions:9 prediabetes was defined as HbA1c 5.7–6.4%, FPG 100–125 mg/dL, or an oral glucose tolerance test 2 hour plasma glucose 140–199 mg/dL; DM was defined as HbA1c ≥6.5%, FPG ≥126 mg/dL (7 mmol/L) or 2 hour plasma glucose ≥200 mg/dL (11.1 mmol/L). The following studies were excluded: 1) duplicates of previous publications; 2) studies reporting the same patient population as another included study; 3) studies without data on PCI outcomes; 4) studies reporting in-hospital outcomes only; 5) studies comparing PCI outcomes of normoglycaemic or diabetic patients only; 6) abstracts, editorials, reviews and commentaries; 7) animal studies.

The primary outcome of interest was all-cause mortality, and secondary outcomes were myocardial infarction (MI), cardiac death, target-vessel revascularization (TVR), target-lesion revascularization, stent thrombosis and stroke. Two reviewers independently extracted data from the eligible studies using a standardized data-collection form. The quality of the included studies was assessed using the Newcastle-Ottawa Scale. Any discrepancies regarding extracted data by the two reviewers were resolved by discussion among all the authors.

For all outcomes in our analyses, pooled risk ratios (RR) with their corresponding 95% confidence intervals (CIs) were calculated using the Mantel-Haenszel random-effects model for dichotomous variables. The Z-test was used to determine the significance of the pooled RRs. Heterogeneity across the studies was assessed using the chi-square-based Cochran’s Q test, and quantified using Higgins and Thompson’s I2 statistics. A Cochran Q statistic with a p-value ≤0.05 was considered significant. I2 statistic values of 25%, 50% and 75% were used to define low, moderate and high heterogeneity, respectively. Finally, we constructed funnel plots to assess for potential publication bias by plotting the standard error against the log RR (Suppl File 1). The meta-analysis was performed using Review Manager (RevMan) Version 5.3 (The Nordic Cochrane Center, Cochran Collaboration, Copenhagen, Denmark). Lastly, meta-regression analysis was performed using STATA 17.0 (StataCorp, College Station, TX, USA) to measure the influence of DES use on all-cause mortality and MI. A p-value of <0.05 was considered significant for all pooled analyses.

Results

Of the 1,139 studies initially identified in the search, 17 studies3,5,10–23 (12 prospective and five retrospective) with 11,868 (76.5% male), 14,894 (78.5% male) and 13,536 (71.1% male) patients in the prediabetes, normoglycaemia and DM groups, respectively, were included in the final analysis. Seventeen studies compared outcomes for prediabetes versus normoglycaemia, while 12 studies compared outcomes for prediabetes versus DM at the longest follow-up. The mean follow-up duration was 2.6 years. Mean age (standard deviation) in each group was 62.1 (± 10.6) years, 60.2 (± 11.4) years and 69.0 (± 9.6) years, respectively. Table 1 summarizes baseline patient characteristics. A summary of study characteristics, definitions of prediabetes and DM, and PCI indications are included in Suppl Table 1.

Details about target vessel and use of DES stratified by prediabetes status across the studies are shown in Suppl Table 2. Discharge medications are outlined in Suppl Table 3.

Among patients undergoing PCI, the normoglycaemic group had lower risk of all-cause mortality, MI, cardiac mortality, revascularization and TVR compared with the prediabetic group (Figures 2 and 3Suppl Figure 1). There was no difference between the prediabetes and normoglycaemia groups for post-PCI stent thrombosis and stroke. The findings are outlined in Table 2(A).

In the subgroup analysis for patients included in prospective studies, normoglycaemic patients who underwent PCI had lower all-cause mortality (RR=0.71 [95% CI 0.51–0.99]; p=0.04; I2=44%), MI (RR=0.74 [95% CI 0.57–0.97]; p=0.05; I2=0%) and TVR (RR=0.66 [95% CI 0.48–0.90]; p=0.009; I2=39%) compared with patients in the prediabetes group, while there was no difference in cardiac death (RR=0.76 [95% CI 0.33–1.71]; p=0.50; I2=41%) between the two groups. Similarly, subgroup analysis of prospective studies showed that patients in the prediabetes group had lower all-cause mortality (RR=0.64 [95% CI 0.51–0.80]; p<0.0001; I2=0%), MI (RR=0.75 [95% CI 0.62–0.92]; p=0.05; I2=0%) and cardiac death (RR=0.47 [95% CI 0.23–0.93]; p=0.03; I2=80%) compared with the DM group, with no difference in TVR (RR=0.88 [95% CI 0.59–1.33]; p=0.55; I2=70%) between groups (Suppl Figures 3–6).

Our meta-regression analysis showed that DES use during PCI was associated with a significant increase in the incidence of MI in the prediabetes group when compared with DM groups (p=0.048). However, DES use did not affect the incidence of MI in patients with prediabetes versus normoglycaemia (p=0.80). Similarly, there was no significant association between DES use and the incidence of all-cause mortality in patients with prediabetes versus normoglycaemia (p=0.36) or prediabetes versus DM (p=0.52) (Suppl File 2).

Discussion

In this meta-analysis, we evaluated the impact of the degree of dysglycaemia on cardiovascular morbidity and mortality in patients undergoing PCI. Our findings suggest that, when compared with normoglycaemic patients, prediabetic patients undergoing PCI had higher risk of all-cause mortality, MI and revascularization, with no difference in risk of post-PCI stent thrombosis and stroke. Compared with patients with DM, patients with prediabetes undergoing PCI had lower risk of all-cause mortality, cardiac mortality, recurrent MI and revascularization, with no difference in stent thrombosis or stroke between the two groups.

Multiple studies have reported prediabetes to be associated with an increased risk of mortality in the general population and in patients with CAD. Although data about the risk of mortality in prediabetic patients undergoing PCI are inconsistent, our study reports that these patients are at increased risk of all-cause mortality in this subgroup of CAD patients compared with normoglycaemic patients. These findings are consistent with the meta-analysis of Cai et al. that analysed 129 studies and reported that prediabetes was associated with an increased risk of mortality in the general population and in patients with atherosclerotic cardiovascular disease.26 Another recent meta-analysis of 12 studies showed that prediabetes is an independent prognostic factor of MACE after PCI.2 It highlighted that prediabetic patients undergoing PCI have a higher risk of adverse outcomes compared with normoglycaemic patients. However, it did not compare the outcomes of prediabetic patients with those of patients with DM. Our meta-analysis fills in the gap to understand the impact of glycaemic control on PCI outcomes for CAD.

Although prediabetic patients undergoing PCI have an increased risk of mortality compared with normoglycaemic patients, this risk was lower compared with patients with DM. Our findings are similar to those reported in the analysis by Zhong et al. who found that the curves for mortality were relatively flat when HbA1c levels were less than approximately 5.7%, and rose steeply thereafter.27 These findings can be explained by the fact that cardiovascular risk factors begin to impact the patient long before the diagnosis of DM. The duration of impaired glucose tolerance (IGT) not only influences CAD risk, but is also associated with insulin resistance. IGT contributes to a spectrum of risk factors that contribute to the development of metabolic syndrome, thus increasing the risk of CAD long before the onset of DM.28,29 Secondly, this can partly be due to the fact that when prediabetic patients present with acute MI, they often receive less-aggressive treatment than those with DM, as prediabetes is perceived by the treating physicians to be a less aggressive disease requiring only lifestyle modifications and exercise.30 Thus, these findings support screening for abnormal glycaemic metabolism in CAD patients undergoing PCI, and treating patients with impaired glucose metabolism aggressively with antidiabetic medications with cardiovascular benefits, such as sodium–glucose co-transporter-2 inhibitors31–34 and glucagon-like peptide-1 receptor agonists.35,36 Since prediabetes is an established risk factor for MACE, lowering HbA1c can potentially have a preventive value.37

Prediabetes has been attributed to an increased risk of MACE in patients with CAD.38 Our study showed that prediabetic patients undergoing PCI had a higher incidence of recurrent MI and revascularization compared with normoglycaemic patients, and that these risks were lower compared with patients with DM. These findings are relatable to the study by Kim et al. that reported that prediabetes could have a similar impact to DM on major clinical outcomes in patients with ST-elevation MI and multi-vessel disease.39 A likely explanation of these findings is the pathophysiological mechanism: prediabetes is associated with systemic inflammation, insulin resistance and production of reactive oxygen species by hyperglycaemia, which leads to endothelial dysfunction, impaired microvascular function, increased prevalence of multi-vessel disease, and likely progression to DM over time.40 Amano et al. confirmed this hypothesis and performed an intravascular ultrasound study, which showed that patients with IGT were more likely to have lipid-rich coronary plaque as compared with normoglycaemic patients.41 Similarly, Ertan et al. also reported patients with prediabetes had smaller coronary size and diffuse coronary narrowing compared with normoglycaemic patients, which may increase the risk of adverse cardiac events like MI, and the need for revascularization after PCI.42

Although DM has been associated with increased incidence of stent thrombosis after PCI,43 our study reported there was no difference in the incidence of post-PCI stent thrombosis between the prediabetic versus normoglycaemic groups, and prediabetic versus DM groups. Similarly, we reported there was no difference in risk of stroke between the prediabetic versus normoglycaemic groups, and prediabetic versus DM groups. This is similar to findings of Mitsios et al., who reported that there was no difference in the risk of first stroke when patients with normoglycaemia and prediabetes were compared.44 However, this contrasts with the findings of a meta-analysis by Lee et al., who reported that prediabetes was associated with a higher risk of stroke and stroke-related morbidity, but the relative risks were modest, associated with significant heterogeneity and not consistent when different definitions of prediabetes were used.45

There are several important limitations of our meta-analysis. The definitions of prediabetes and DM across studies were based on different criteria and, due to this, only a limited number of studies were available for comparison. Therefore, we were not able to perform a meta-analysis according to varying definition criteria of prediabetes/DM separately. Although the included studies did not all use the same criteria, each study met one of the three ADA-specified criteria for prediabetes/DM.9 Similarly, we did not include metabolic syndrome, as the definition varies from study to study. Additionally, although patients with prediabetes are more likely to progress to DM than those with normoglycaemia, most of the included studies did not adjust for progression to DM. However, the mean follow-up duration of 2.8 years was not long enough to attribute all the associated increased risk of mortality from progression of prediabetes to DM. Finally, no details about treatments were available for post-PCI patients in the included studies, so the effect of treatment on outcomes post-PCI cannot be evaluated.

Conclusions

Among CAD patients who underwent PCI, the risk of all-cause and cardiac mortality, MI and revascularization in prediabetic patients was higher compared with normoglycaemic patients, but lower compared with patients with DM. Thus, patients undergoing PCI should be screened for prediabetes and treated optimally.

Article Information:
Disclosure

Jolanta Siller-Matula received lecture fees from Bayer, Bristol Myers Squibb, Chiesi and Daiichi Sankyo. Mamas A Mamas received an unrestricted educational grant from Terumo. Emmanouil S Brilakis received honoraria from Abbott Vascular, Asahi, Cardinal Health, Elsevier, GE Healthcare and St Jude Medical; research support from Boston Scientific and InfraRedx; and their spouse is an employee of Medtronic. J Dawn Abbott discloses Alpert Medical School of Brown University and Lifespan Cardiovascular Institute; research funding from Boston Scientific and MicroPort; advisory boards with Medtronic and Philips; consulting for Abbott and Recor. Deepak L Bhatt reports advisory boards for Cardax, CellProthera, Cereno Scientific, Elsevier Practice Update Cardiology, Janssen, Level Ex, Medscape Cardiology, MyoKardia, NirvaMed, Novo Nordisk, PhaseBio, PLx Pharma and Regado Biosciences; is on the board of directors for Boston VA Research Institute, Society of Cardiovascular Patient Care and TobeSoft; is the inaugural chair of the AHA Quality Oversight Committee and chair of the ACC Accreditation Oversight Committee, NCDR-ACTION Registry Steering Committee and VA CART Research and Publications Committee; is on the Data Monitoring Committee for Baim Institute for Clinical Research, Cleveland Clinic, Contego Medical, Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine and Population Health Research Institute; honoraria from ACC, Baim Institute for Clinical Research, Belvoir Publications, Canadian Medical and Surgical Knowledge Translation Research Group, Duke Clinical Research Institute, HMP Global, JACC, K2P, Level Ex, Medtelligence/ReachMD, MJH Life Sciences, Population Health Research Institute, Slack Publications, Society of Cardiovascular Patient Care, WebMD; is Deputy Editor of Clinical Cardiology; research funding from Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol Myers Squibb, Cardax, CellProthera, Cereno Scientific, Chiesi, CSL Behring, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, Garmin, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Lilly, Medtronic, MyoKardia, NirvaMed, Novartis, Novo Nordisk, Owkin, Pfizer, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic and The Medicines Company and 89Bio; royalties from Elsevier; was site co-investigator for Abbott, Biotronik, Boston Scientific, CSI, Philips, St. Jude Medical and Svelte; trustee of ACC; unfunded research with FlowCo, Merck and Takeda. Poonam Velagapudi received speaker’s fees from Abiomed, Medtronic, Opsens and Shockwave; advisory boards with Abiomed and Sanofi. Azka Latif, Soban Ahmad, Claire Willman, Noman Lateef, Muhammad Asim Shabbir, Mohammad Zoraiz Ahsan, Amman Yousaf, Maria Riasat, Magdi Ghali and Yeongjin Gwon have no financial or non-financial relationships or activities to declare in relation to this article.

Compliance With Ethics

This article involves a review of the literature and did not involve any studies with human or animal subjects performed by any of the authors.

Authorship

Double-blind peer review.

Correspondence

Muhammad Junaid AhsanMercyOneIowa Heart Center, 5880 University AveWest Des MoinesIA, 50266USAJunaidahsan333@gmail.com

Support

No funding was received in the publication of this article.

Access

This article is freely accessible at touchCARDIO.com © Touch Medical Media 2023

Digital Features

All data generated or analysed during this study are included in this published article/as supplementary information files.

Data Availability

All data generated or analysed during this study are included in this published article/as supplementary information files.

Received

2023-01-28

References

1. American Diabetes AssociationPrevention or delay of type 2 diabetes: Standards of medical care in Diabetes-2020Diabetes Care2020;43:S326DOI10.2337/dc20-S003.

2. Kim YHHer A-YJeong MHet alOutcomes in prediabetes vs. diabetes in patients with non-ST-segment elevation myocardial infarction undergoing percutaneous interventionCoron Artery Dis. 2021;32:21123. DOI: 10.1097/MCA.0000000000000969

3. Zhao YGuo MShi GPrediabetes predicts adverse cardiovascular outcomes after percutaneous coronary intervention: A meta-analysisBiosci Rep. 2020;40:BSR20193130. DOI: 10.1042/BSR20193130

4. Cueva-Recalde JFRuiz-Arroyo JRRoncalés García-Blanco FPrediabetes and coronary artery disease: Outcome after revascularization proceduresEndocrinol Nutr2016;63:10612DOI: 10.1016/j.endoen.2016.02.010.

5. Choi WGRha SWChoi BGet alThe impact of prediabetes on two-year clinical outcomes in patients undergoing elective percutaneous coronary interventionYonsei Med J2018;59:48994DOI: 10.3349/ymj.2018.59.4.489

6. Ploumen EHPinxterhuis THZocca Pet alImpact of prediabetes and diabetes on 3-year outcome of patients treated with new-generation drug-eluting stents in two large-scale randomized clinical trials. Cardiovasc Diabetol2021;20:217DOI10.1186/s12933-021-01405-4

7. Baber UAzzalini LMasoomi Ret alHemoglobin A1c and cardiovascular outcomes following percutaneous coronary intervention: Insights from a large single-center registryJACC Cardiovasc Interv. 2021;14:38897. DOI: 10.1016/j.jcin.2020.10.008

8. Moher DShamseer LClarke Met alPreferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statementSyst Rev2015;4:1DOI10.1186/2046-4053-4-1

9. American Diabetes Association2. Classification and diagnosis of diabetes: Standards of medical care in Diabetes-2020Diabetes Care2020;43 (Suppl. 1):S1431DOI10.2337/dc20-S002.

10. Çiçek GKorkmaz ATwo-year prognosis of admission hemoglobin A1c following a primary percutaneous coronary interventionCoron Artery Dis2016;27:67381DOI: 10.1097/MCA.0000000000000411

11. de la Hera JMDelgado EHernández Eet alPrevalence and outcome of newly detected diabetes in patients who undergo percutaneous coronary interventionEur Heart J2009;30:261421DOI: 10.1093/eurheartj/ehp278

12. Dibra ANdrepepa GMehilli Jet alPrognostic value of impaired fasting glucose for outcomes of patients with stable angina pectoris treated with percutaneous coronary interventionsAm J Cardiol. 2005;96:11135. DOI: 10.1016/j.amjcard.2005.06.041

13. El-Hammady WShawky AEl-Annany AShort term follow-up of prediabetics undergoing elective percutaneous coronary interventionJ Saudi Heart Assoc2013;25:5765DOI: 10.1016/j.jsha.2012.12.003

14. Ploumen EHBuiten RAKok MMet alThree-year clinical outcome in all-comers with “silent” diabetes, prediabetes, or normoglycemia, treated with contemporary coronary drug-eluting stents: From the BIO-RESORT silent diabetes studyCatheter Cardiovasc Interv2020;96:E1108DOI: 10.1002/ccd.28536

15. Farhan SRedfors BMaehara Aet alImpact of pre-diabetes on coronary plaque composition and clinical outcome in patients with acute coronary syndromes: An analysis from the PROSPECT studyJACC Cardiovasc Imaging. 2019;12:73341DOI10.1016/j.jcmg.2017.06.023

16. Jiménez-Navarro MFFernández-Pastor JGarrido-Sánchez Let alNewly impaired glucose metabolism and prognosis after percutaneous revascularizationCardiol J2015;22:4451DOI: 10.5603/CJ.a2014.0024

17. Kim YHHer A-YJeong MHet alEffects of prediabetes on long-term clinical outcomes of patients with acute myocardial infarction who underwent PCI using new-generation drug-eluting stentsDiabetes Res Clin Pract. 2020;160:107994DOI10.1016/j.diabres.2019.107994

18. Kok MMvon Birgelen CSattar Net alPrediabetes and its impact on clinical outcome after coronary intervention in a broad patient populationEuroIntervention2018;14:e104956DOI10.4244/EIJ-D-17-01067

19. Samir SNaseem MEffect of admission glycometabolic state on clinical outcome in non diabetic subjects with acute ST segment elevation myocardial infarctionEgypt J Crit Care Med2016;4:738. DOI: 10.1016/j.ejccm.2016.03.003

20. Shin DAhn JCha KSet alImpact of initial glycosylated hemoglobin level on cardiovascular outcomes in prediabetic patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary interventionCoron Artery Dis2016;27:406DOI: 10.1097/MCA.0000000000000305

21. Kuramitsu SYokoi HDomei Tet alImpact of post-challenge hyperglycemia on clinical outcomes in Japanese patients with stable angina undergoing percutaneous coronary interventionCardiovasc Diabetol. 2013;12:19. DOI10.1186/1475-2840-12-74

22. Wang HSong YTang Xet alImpact of unknown diabetes and prediabetes on clinical outcomes in “nondiabetic” Chinese patients after a primary coronary interventionNutr Metab Cardiovasc Dis. 2020;30:64451. DOI: 10.1016/j.numecd.2019.11.013

23. Porter AAssali ARZahalka Aet alImpaired fasting glucose and outcomes of ST-elevation acute coronary syndrome treated with primary percutaneous intervention among patients without previously known diabetes mellitusAm Heart J2008;155:2849DOI10.1016/j.ahj.2007.10.010

24. Aggarwal BShah GKRandhawa Met alUtility of glycated hemoglobin for assessment of glucose metabolism in patients with ST-segment elevation myocardial infarctionAm J Cardiol2016;117:74953DOI: 10.1016/j.amjcard.2015.11.060

25. Giraldez RRClare RMLopes RDet alPrevalence and clinical outcomes of undiagnosed diabetes mellitus and prediabetes among patients with high-risk non-ST-segment elevation acute coronary syndrome. Am Heart J2013;165:91825DOI10.1016/j.ahj.2013.01.005

26. Cai XZhang YLi Met alAssociation between prediabetes and risk of all cause mortality and cardiovascular disease: Updated meta-analysisBMJ2020;370:m2297DOI10.1136/bmj.m2297

27. Zhong GCYe MXCheng JHet alHbA1c and risks of all-cause and cause-specific death in subjects without known diabetes: A dose-response meta-analysis of prospective cohort studiesSci Rep. 2016;6:24071. DOI: 10.1038/srep24071

28. Haffner SMStern MPHazuda HPet alCardiovascular risk factors in confirmed prediabetic individuals. Does the clock for coronary heart disease start ticking before the onset of clinical diabetes? JAMA. 1990;263:28938DOI: 10.1001/jama.263.21.2893

29. Chattopadhyay SGeorge AJohn JSathyapalan TAdjustment of the GRACE score by 2-hour post-load glucose improves prediction of long-term major adverse cardiac events in acute coronary syndrome in patients without known diabetesEur Heart J2018;39:27405DOI10.1093/eurheartj/ehy233

30. Li GZhang PWang Jet alCardiovascular mortality, all-cause mortality, and diabetes incidence after lifestyle intervention for people with impaired glucose tolerance in the Da Qing diabetes prevention study: A 23-year follow-up studyLancet Diabetes Endocrinol2014;2:47480DOI10.1016/S2213-8587(14)70057-9

31. Anker SDButler JFilippatos Get alEffect of empagliflozin on cardiovascular and renal outcomes in patients with heart failure by baseline diabetes status: Results from the EMPEROR-Reduced trial. Circulation. 2021;143:33749DOI10.1161/CIRCULATIONAHA.120.051824

32. Kang AJardine MJSGLT2 inhibitors may offer benefit beyond diabetesNat Rev Nephrol. 2021;17:834. DOI: 10.1038/s41581-020-00391-2

33. Herrington WGSavarese GHaynes Ret alCardiac, renal, and metabolic effects of sodium-glucose co-transporter 2 inhibitors: A position paper from the European Society of Cardiology ad-hoc task force on sodium-glucose co-transporter 2 inhibitorsEur J Heart Fail2021;23:126075DOI: 10.1002/ejhf.2286

34. Caparrotta TMBlackbourn LAKMcGurnaghan SJet alPrescribing paradigm shift? Applying the 2019 European Society of Cardiology-led guidelines on diabetes, prediabetes, and cardiovascular disease to assess eligibility for sodium-glucose cotransporter 2 inhibitors or glucagon-like peptide 1 receptor agonists as first-line monotherapy (or add-on to metformin monotherapy) in type 2 diabetes in Scotland. Diabetes Care. 2020;43:203441DOI: 10.2337/dc20-0120

35. le Roux CWAstrup AFujioka Ket al3 years of liraglutide versus placebo for type 2 diabetes risk reduction and weight management in individuals with prediabetes: A randomised, double-blind trial. Lancet. 2017;389:1399409DOI10.1016/S0140-6736(17)30069-7

36. Udell JASteg PGScirica BMet alMetabolic syndrome, diabetes mellitus, or both and cardiovascular risk in outpatients with or at risk for atherothrombosisEur J Prev Cardiol2014;21:153140. DOI: 10.1177/2047487313500541

37. Mando RWaheed MMichel Aet alPrediabetes as a risk factor for major adverse cardiovascular events. Ann Med. 2021;53:20908DOI10.1080/07853890.2021.2000633

38. Kim YHHer A-YJeong MHet alTwo-year clinical outcomes between prediabetic and diabetic patients with STEMI and multivessel disease who underwent successful PCI using drug-eluting stents. Angiology. 2021;72:5061DOI10.1177/0003319720949311

39. Guo JBreen DMPereira TJet alThe effect of insulin to decrease neointimal growth after arterial injury is endothelial nitric oxide synthase-dependentAtherosclerosis2015;241:11120DOI: 10.1016/j.atherosclerosis.2015.04.799

40. Komatsu TYaguchi IKomatsu Set alImpact of insulin resistance on neointimal tissue proliferation after 2nd-generation drug-eluting stent implantationTex Heart Inst J2015;42:32732DOI: 10.14503/THIJ-14-4393

41. Amano TMatsubara TUetani Tet alAbnormal glucose regulation is associated with lipid-rich coronary plaque: Relationship to insulin resistanceJACC Cardiovasc Imaging2008;1:3945DOI: 10.1016/j.jcmg.2007.09.003

42. Ertan COzeke OGul Met alAssociation of prediabetes with diffuse coronary narrowing and small-vessel diseaseJ Cardiol2014;63:2934DOI10.1016/j.jjcc.2013.06.015

43. Nogic JNerlekar NSoon Ket alDiabetes mellitus is independently associated with early stent thrombosis in patients undergoing drug eluting stent implantation: Analysis from the Victorian Cardiac Outcomes Registry. Catheter Cardiovasc Interv2022;99:55462DOI10.1002/ccd.29913.

44. Mitsios JPEkinci EIMitsios GPet alRelationship between glycated hemoglobin and stroke risk: A systematic review and meta-analysisJ Am Heart Assoc. 2018;7:e007858. DOI: 10.1161/JAHA.117.007858

45. Lee MSaver JLHong KSet alEffect of pre-diabetes on future risk of stroke: Meta-analysis. BMJ. 2012;344:e3564. DOI10.1136/bmj.e3564

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