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• W3136237248 abstract "The treatment algorithm for the management of hyperglycemia in type 2 diabetes (T2DM) was recently updated based on large cardiovascular outcomes trials (CVOTs).1American Diabetes Association9. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes-2021.Diabetes Care. 2021; 44: S111-S124https://doi.org/10.2337/dc21-S009Crossref PubMed Scopus (472) Google Scholar Obviously, these recommendations, endorsed by experts, are excellent and vital for guiding the worldwide management of diabetes. Nevertheless, they do not address the heterogeneity of T2DM. Ahlqvist et al2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar proposed a revolutionary new classification of adult, recent-onset, T2DM into subtypes (clusters). It is founded on 6 rather simple variables: glutamate decarboxylase (GAD) antibodies, age at diagnosis, body mass index (BMI), HbA1c levels, and homoeostatic model assessment estimates of β-cell function (HOMA2-B) and insulin resistance (HOMA2-IR). This landmark study included a large cohort (n = 8980) of an adult Swedish population with new-onset T2DM (All New Diabetics in Scania [ANDIS]).2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar The median follow-up period was 4 years. A cluster analysis based on these 6 variables identified 5 groups of patients: severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD). These clusters included 6.4%, 17.5%, 15.3%, 21.6%, and 39.1% of the total cohort, respectively. Four independent cohorts in Sweden and Finland confirmed these findings.2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar Importantly, the clusters differed not only in their baseline characteristics, but the groups also varied in their risk to develop diabetes-related acute and chronic complications (Table 1). First, a quarter of the patients in the SIDD cluster of the ANDIS cohort presented with diabetic ketoacidosis (DKA), an acute, life-threatening condition.Table 1Diabetes Complications in ANDIS, SDR and the German Diabetes Study Cohorts Stratified by the Cluster Approach2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar,3Zaharia OP Strassburger K Strom A et al.Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study.Lancet Diabetes Endocrinol. 2019; 7: 684-694https://doi.org/10.1016/S2213-8587(19)30187-1Abstract Full Text Full Text PDF PubMed Scopus (186) Google ScholarDiabetes-Related Complications, %SAIDSIDDSIRDMODMARDANDIS cohort(n = 8980) DKA at diagnosis3025352 CKD 3A682233 CKD 3B23914 Macroalbuminuria34632 Coronary events45736 NAFLD71224227SDR cohort(n = 1466) Retinopathy6064354940 Coronary events817231119German Diabetes Study cohort*Patients who had 5 years of follow-up. ANDIS = all new diabetics in Scania; CKD = chronic kidney disease; DKA = diabetic ketoacidosis; DSPN = diabetic sensorimotor polyneuropathy; eGFR = estimated glomerular filtration rate; MARD = moderate age-related diabetes; MOD = moderate obesity-related diabetes; NAFLD = nonalcoholic fatty liver disease; SAID = severe autoimmune diabetes; SDR = Scania Diabetes Registry; SIDD = severe insulin deficient diabetes; SIRD = severe insulin resistant diabetes.(n = 367) eGFR < 60 mL/min/1.73m2 at baseline101212 At follow-up002745 Confirmed DSPN at baseline536171115 At follow-up125012179 Liver fibrosis at follow-up70261512 Patients who had 5 years of follow-up.ANDIS = all new diabetics in Scania; CKD = chronic kidney disease; DKA = diabetic ketoacidosis; DSPN = diabetic sensorimotor polyneuropathy; eGFR = estimated glomerular filtration rate; MARD = moderate age-related diabetes; MOD = moderate obesity-related diabetes; NAFLD = nonalcoholic fatty liver disease; SAID = severe autoimmune diabetes; SDR = Scania Diabetes Registry; SIDD = severe insulin deficient diabetes; SIRD = severe insulin resistant diabetes. Open table in a new tab Second, this cluster was also associated with an elevated risk of diabetic retinopathy. Hence, the SIDD subgroup of 2 large cohorts, the ANDIS and the All New Diabetics in Uppsala (ANDIU), had an elevated hazard ratio (HR) of this chronic complication, up to 1.6 (1.3-1.9) and 4.6 (3.0-7.0), respectively. Patients within the SIDD cluster had also an elevated rate of sensorimotor polyneuropathy.2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar Third, the SIRD cluster had a remarkably high risk of another serious diabetes-related complication, chronic kidney disease (CKD). It was documented both at baseline and during follow-up, with an HR of 3.3 (2.6-4.3) compared with the MOD cluster. Fourth, the SIRD subgroup had a high risk of developing coronary artery disease and nonalcoholic fatty liver disease (NAFLD). Taken together, 2 important implications can be drawn. First, about a third of patients with T2DM, those within the SIDD and SIRD clusters, are especially prone to develop diabetes-related complications. Second, each of the 2 subgroups has a unique profile of complications. The data of the German Diabetes Study confirm and even strengthen the results of this cluster approach.3Zaharia OP Strassburger K Strom A et al.Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study.Lancet Diabetes Endocrinol. 2019; 7: 684-694https://doi.org/10.1016/S2213-8587(19)30187-1Abstract Full Text Full Text PDF PubMed Scopus (186) Google Scholar Partition of this cohort into clusters included additional assessment tools: evaluation of insulin sensitivity and secretion by hyperinsulinemic-euglycemic clamp and intravenous glucose tolerance test as well as liver lipid content determination by magnetic resonance spectroscopy and fibrosis by noninvasive scores. Their findings established the high-risk of the SIRD cluster to develop CKD, with a complication rate of up to 27% 5 years of follow-up. Moreover, the SIRD cluster was characterized by a high prevalence of advanced form of NAFLD and a quarter of them developed liver fibrosis (Table 1). Surprisingly, the cluster distribution was also confirmed in a population of completely a different genetic background. As reported by Li et al,4Li X Yang S Cao C et al.Validation of the Swedish diabetes re-grouping scheme in adult-onset diabetes in China.J Clin Endocrinol Metab. 2020; 105: e3519-e3528https://doi.org/10.1210/clinem/dgaa524Crossref Scopus (13) Google Scholar application of the cluster-analysis approach was valid in a large cohort of 15,772 patients with newly diagnosed, adult-onset, diabetes in China. 5Knobler H Toledano Y Letter to the editor from Knobler and Toledano: Validation of the Swedish diabetes regrouping scheme in adult-onset diabetes in China.J Clin Endocrinol Metab. 2021; 106: e1064-e1065https://doi.org/10.1210/clinem/dgaa827Crossref PubMed Scopus (1) Google Scholar This novel classification may have a paramount importance on our treatment decisions, mainly adopting a more aggressive approach for patients within the SIDD and SIRD clusters. The large CVOTs inclusion criteria were based on the traditional uniform diagnosis of T2DM. Therefore, the current consensus reports originating from those trials may provide a treatment algorithm that is too generalized. It stratifies each patient with T2DM according to existing clinical characteristics: established cardiovascular disease, cardiovascular risk factors, heart failure, nephropathy, obesity, high risk of hypoglycemia, and cost issues.1American Diabetes Association9. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes-2021.Diabetes Care. 2021; 44: S111-S124https://doi.org/10.2337/dc21-S009Crossref PubMed Scopus (472) Google Scholar However, based on the intriguing and important recent data derived from the aforementioned trials,2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar,3Zaharia OP Strassburger K Strom A et al.Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study.Lancet Diabetes Endocrinol. 2019; 7: 684-694https://doi.org/10.1016/S2213-8587(19)30187-1Abstract Full Text Full Text PDF PubMed Scopus (186) Google Scholar we suggest also to stratify according to the appropriate cluster of T2DM. Hence, some important questions regarding the current therapy algorithm arise (Table 2):1.CKD and the SIRD cluster: Currently, sodium-glucose linked transporter type-2 (SGLT2) inhibitors are recommended for patients with T2DM and CKD. Shouldn't we consider this treatment in the SIRD cluster, long before the development of CKD? Notably, progression of this complication was halted by SGLT2 inhibitors even in patients with relatively preserved kidney function.6Chilton RJ Effects of sodium-glucose cotransporter-2 inhibitors on the cardiovascular and renal complications of type 2 diabetes.Diabetes Obes Metab. 2020; 22: 16-29https://doi.org/10.1111/dom.13854Crossref PubMed Scopus (22) Google Scholar2.Established atherosclerotic cardiovascular disease (ASCVD), and the SIRD cluster: The algorithm proposes glucagon-like peptide-1 receptor agonists (GLP-1RA) as the first-choice therapy in patients with established ASCVD. Shouldn't we consider early administration of GLP-1RA to patients with SIRD clusters' characteristics, even before they have evidence of ASCVD? GLP-1RA has been shown in animal models, supported by human data, to have numerous advantageous effects on atherosclerosis through direct and indirect mechanisms.7Drucker DJ The cardiovascular biology of glucagon-like peptide-1.Cell Metab. 2016; 24: 15-30https://doi.org/10.1016/j.cmet.2016.06.009Abstract Full Text Full Text PDF PubMed Scopus (326) Google Scholar Although not fully adopted mainly due to side effects, pioglitazone has also a favorable effect on ASCVD as shown in the PROactive trial.8Betteridge DJ DeFronzo RA Chilton RJ PROactive: time for a critical appraisal.Eur Heart J. 2008; 29: 969-983https://doi.org/10.1093/eurheartj/ehn114Crossref PubMed Scopus (43) Google Scholar3.DKA and the SIDD cluster: The SGLT2 inhibitors have been shown to increase DKA risk.4Li X Yang S Cao C et al.Validation of the Swedish diabetes re-grouping scheme in adult-onset diabetes in China.J Clin Endocrinol Metab. 2020; 105: e3519-e3528https://doi.org/10.1210/clinem/dgaa524Crossref Scopus (13) Google Scholar They may be even more hazardous in the SIDD cluster, especially prone to develop DKA (Table 1).2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar Therefore, how safe are SGLT2 inhibitors in this subgroup?4.Retinopathy and the SIDD cluster: Administration of insulin or insulin secretagogues treatment is capable of effectively controlling the marked hyperglycemia in patients within the SIDD cluster. Moreover, these therapies may also reduce retinopathy both within a short- and a long-term follow-up.9Holman RR Paul SK Bethel MA et al.10-year follow-up of intensive glucose control in type 2 diabetes.N Engl J Med. 2008; 359: 1577-1589https://doi.org/10.1056/NEJMoa0806470Crossref PubMed Scopus (5091) Google Scholar Thus, shouldn't we initiate these treatment modalities earlier in the SIDD cluster?5.NAFLD and the SIRD cluster: As already mentioned, the SIRD cluster has a high risk of developing advanced form of NAFLD. Therefore, shouldn't we consider including this serious complication in our treatment algorithm? NAFLD and its more severe form nonalcoholic steatohepatitis (NASH) is currently a major worldwide health problem. Diabetes promotes not only the development of NASH but also cirrhosis and hepatocellular carcinoma. Although none of the current antihyperglycemic medications have been approved for the treatment of NAFLD, there are several trials showing a beneficial effect of pioglitazone, liraglutide, and SGLT2 inhibitors in reducing liver fat accumulation. Moreover, pioglitazone has been found to reduce liver fibrosis, while metformin and insulin have not been proven to have a beneficial effect.10Iogna Prat L Tsochatzis EA The effect of antidiabetic medications on non-alcoholic fatty liver disease (NAFLD).Hormones (Athens). 2018; 17: 219-229https://doi.org/10.1007/s42000-018-0021-9Crossref PubMed Scopus (32) Google ScholarTable 2Suggested Recommendations for Pharmacologic Treatment of Diabetes Mellitus Based on the Cluster Approach2Ahlqvist E Storm P Käräjämäki A et al.Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables.Lancet Diabetes Endocrinol. 2018; 6: 361-369https://doi.org/10.1016/S2213-8587(18)30051-2Abstract Full Text Full Text PDF PubMed Scopus (849) Google Scholar,3Zaharia OP Strassburger K Strom A et al.Risk of diabetes-associated diseases in subgroups of patients with recent-onset diabetes: a 5-year follow-up study.Lancet Diabetes Endocrinol. 2019; 7: 684-694https://doi.org/10.1016/S2213-8587(19)30187-1Abstract Full Text Full Text PDF PubMed Scopus (186) Google ScholarCohort's ClusterRisk of ComplicationPotential Unsafe/Unrecommended MedicationsRecommended Group of MedicationsSIDDDiabetic ketoacidosisSGLT2 inhibitorsInsulin; insulin secretagoguesSAIDDiabetic ketoacidosisSGLT2 inhibitorsInsulinSIDDDiabetic retinopathySemaglutide?*Under current study.Insulin; insulin secretagoguesSIRDChronic kidney diseaseSGLT2 inhibitorsSIRDASCVDGLP-1 RA; PioglitazoneSIRDNAFLDPioglitazone, GLP-1 RA; SGLT2 inhibitorsASCVD = atherosclerotic cardiovascular disease; GLP-1 RA = glucagon-like peptide-1 receptor agonist; NAFLD = nonalcoholic fatty liver disease; SAID = severe autoimmune diabetes; SGLT2 = sodium glucose co-transporter 2; SIDD = severe insulin deficient diabetes; SIRD = severe insulin resistant diabetes. Under current study. Open table in a new tab ASCVD = atherosclerotic cardiovascular disease; GLP-1 RA = glucagon-like peptide-1 receptor agonist; NAFLD = nonalcoholic fatty liver disease; SAID = severe autoimmune diabetes; SGLT2 = sodium glucose co-transporter 2; SIDD = severe insulin deficient diabetes; SIRD = severe insulin resistant diabetes. Suggested recommendations that are based on the cluster-approach findings are provided in Table 2. The recommendations focus on the more aggressive clusters SIDD and SIRD with their high risk of developing diabetes-related complications, as discussed. We acknowledge that currently there is no evidence as to whether this approach enables a more precise choice of treatment. Therefore, the time has come to conduct further studies aimed to evaluate the effect of different treatment modalities on diabetes complications using these newly defined T2DM subclasses. This can be performed by reanalyzing previous CVOTs populations using the cluster approach. Furthermore, we call to apply this classification in planning future trials." @default.
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• W3136237248 title "Not All Patients with Type 2 Diabetes Are Equal" @default.
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