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Standards of Medical Care in Diabetes—2007 American Diabetes Association ABI, ankle-brachial index AMI, acute myocardial infarction ARB, angiotensin receptor blocker CAD, coronary artery disease CBG, capillary blood glucose CHD, coronary heart disease CHF, congestive heart failure CKD, chronic kidney disease CMS, Centers for Medicare and Medicaid Services CSII, continuous subcutaneous insulin infusion CVD, cardiovascular disease DCCB, dihydropyridine calcium channel blocker DCCT, Diabetes Control and Complications Trial DKA, diabetic ketoacidosis DMMP, diabetes medical management plan DPN, distal symmetric polyneuropathy DPP, Diabetes Prevention Program DRI, dietary reference intake DRS, Diabetic Retinopathy Study DSME, diabetes self-management education DSMT, diabetes self-management training ECG, electrocardiogram ESRD, end-stage renal disease ETDRS, Early Treatment Diabetic Retinopathy Study FDA, Food and Drug Administration FPG, fasting plasma glucose GDM, gestational diabetes mellitus GFR, glomerular filtration rate HRC, high-risk characteristic ICU, intensive care unit IFG, impaired fasting glucose IGT, impaired glucose tolerance MNT, medical nutrition therapy NDEP, National Diabetes Education Program NPDR, nonproliferative diabetic retinopathy OGTT, oral glucose tolerance test PAD, peripheral arterial disease PDR, proliferative diabetic retinopathy PPG, postprandial plasma glucose RDA, recommended dietary allowance SMBG, self-monitoring of blood glucose TZD, thiazolidinedione UKPDS, U.K. Prospective Diabetes Study Diabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to refs. 1–3. The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E. I. CLASSIFICATION AND DIAGNOSIS A. Classification In 1997, ADA issued new diagnostic and classification criteria (4); in 2003, modifications were made regarding the diagnosis of impaired fasting glucose (IFG) (5). The classification of diabetes includes four clinical classes: Type 1 diabetes (results from β-cell destruction, usually leading to absolute insulin deficiency) Type 2 diabetes (results from a progressive insulin secretory defect on the background of insulin resistance) Other specific types of diabetes due to other causes, e.g., genetic defects in β-cell function, genetic defects in insulin action, diseases … [Full Text of this Article]

Introduction and aimDiabetes is a global health emergency with increasing prevalence and diabetes-associated morbidity and mortality. One of the challenges in optimising diabetes care is translating research advances in this heterogeneous disease into clinical care. A potential solution is the introduction of precision medicine approaches into diabetes care.We aim to develop a digital platform called ‘intelligent Diabetes’ (iDiabetes) to support a precision diabetes care model in Scotland and assess its impact on the primary composite outcome of all-cause mortality, hospitalisation rate, renal function decline and glycaemic control.Methods and analysisThe impact of iDiabetes will be evaluated through a cluster-randomised controlled study, recruiting up to 22 500 patients with diabetes. Primary care general practices (GPs) in the National Health Service (NHS) Scotland Tayside Health Board are the units (clusters) of randomisation. Each primary care GP will form one cluster (approximately 400 patients per cluster), with up to 60 clusters recruited. Randomisation will be to iDiabetes (guideline support), iDiabetesPlus or usual diabetes care (control arm). Patients of participating primary care GPs are automatically enrolled on the study when they attend for their annual diabetes screening or are newly diagnosed with diabetes. A composite hierarchical primary outcome, evaluated using Win-Ratio statistical methodology, will consist of (1) all-cause mortality, (2) all-cause hospitalisation rate, (3) proportion with >40% estimated glomerular filtration rate [eGFR] reduction from baseline or new development of end-stage renal disease, (4) proportion with absolute HbA1C reduction >0.5%. Outcomes will be evaluated after a 2-year median follow-up period. Comprehensive qualitative and health economic analyses will be conducted, assessing the cost-effectiveness, budget impact and user acceptability of the iDiabetes platform.Ethics and disseminationThis study was reviewed by the NHS Health Research Authority and approved by the East of Scotland Research Ethics Committee (reference: 23/ES/0008). Study findings will be disseminated via publications, presented at scientific conferences and shared with patients and the public on the study website and social media.Trial registration numberISRCTN18000901.

The severity of the metabolic abnormality can progress, regress, or stay the same. [...] the degree of hyperglycemia reflects the severity of the underlying metabolic process and its treatment more than the nature of the process itself.

The oral glucose tolerance test identifies high-risk subjects for diabetes, but it is costly and inconvenient. To find better predictors of type 2 diabetes, we evaluated two different definitions of the metabolic syndrome because insulin resistance, which is commonly associated with this clustering of metabolic factors, frequently precedes the onset of type 2 diabetes. We compared the ability of the National Cholesterol Education Program (NCEP) definition, a modified version of the 1999 World Health Organization (WHO) definition that excludes the 2-h glucose requirement, and impaired glucose tolerance (IGT) to predict incident type 2 diabetes. In the San Antonio Heart Study, 1734 participants completed a 7- to 8-year follow-up examination. IGT and the NCEP definition had higher sensitivity than the modified WHO definition (51.9, 52.8, and 42.8%, respectively). IGT had a higher positive predictive value than the NCEP and modified WHO definitions (43.0, 30.8, and 30.4%, respectively). The combination of the IGT and NCEP definitions increased the sensitivity to 70.8% with an acceptable positive predictive value of 29.7%. Risk for incidence of type 2 diabetes using the NCEP definition was independent of other risk factors, including IGT and fasting insulin (odds ratio 3.30, 95% CI 2.27-4.80). The NCEP definition performed better with fasting glucose >or=5.4 mmol/l (sensitivity 62.0% and positive predictive value 30.9%). The metabolic syndrome predicts diabetes independently of other factors. However, the NCEP definition performs better than the modified 1999 WHO definition. Lowering the fasting glucose cutoff to 5.4 mmol/l improves the prediction of diabetes by the metabolic syndrome.

Long-term complications of diabetes include retinopathy with potential loss of vision; nephropathy leading to renal failure; peripheral neuropathy with risk of foot ulcers, amputations, and Charcot joints; and autonomic neuropathy causing gastrointestinal, genitourinary, and cardiovascular symptoms and sexual dysfunction.

Aims/hypothesisThis is an update of the results from the previous report of the CORONADO (Coronavirus SARS-CoV-2 and Diabetes Outcomes) study, which aims to describe the outcomes and prognostic factors in patients with diabetes hospitalised for coronavirus disease-2019 (COVID-19).MethodsThe CORONADO initiative is a French nationwide multicentre study of patients with diabetes hospitalised for COVID-19 with a 28-day follow-up. The patients were screened after hospital admission from 10 March to 10 April 2020. We mainly focused on hospital discharge and death within 28 days.ResultsWe included 2796 participants: 63.7% men, mean age 69.7 ± 13.2 years, median BMI (25th–75th percentile) 28.4 (25.0–32.4) kg/m2. Microvascular and macrovascular diabetic complications were found in 44.2% and 38.6% of participants, respectively. Within 28 days, 1404 (50.2%; 95% CI 48.3%, 52.1%) were discharged from hospital with a median duration of hospital stay of 9 (5–14) days, while 577 participants died (20.6%; 95% CI 19.2%, 22.2%). In multivariable models, younger age, routine metformin therapy and longer symptom duration on admission were positively associated with discharge. History of microvascular complications, anticoagulant routine therapy, dyspnoea on admission, and higher aspartate aminotransferase, white cell count and C-reactive protein levels were associated with a reduced chance of discharge. Factors associated with death within 28 days mirrored those associated with discharge, and also included routine treatment by insulin and statin as deleterious factors.Conclusions/interpretationIn patients with diabetes hospitalised for COVID-19, we established prognostic factors for hospital discharge and death that could help clinicians in this pandemic period.Trial registrationClinicaltrials.gov identifier: NCT04324736

5% are likely at the highest risk for progression to diabetes, but this range should not be considered an absolute threshold at which preventative measures are initiated. * The classification of subdiabetic hyperglycemia as pre-diabetes is problematic because it suggests that all individuals so classified will develop diabetes and that individuals who do not meet these glycemia-driven criteria (regardless of other risk factor values) are unlikely to develop diabetes - neither of which is the case. [...] the categorical classification of individuals as high risk (e.g., IFG or IGT) or low risk, based on any measure of glycemia, is less than ideal because the risk for progression to diabetes appears to be a continuum.

Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence Based Laboratory Medicine Committee of the AACC jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A(1c) (Hb A(1c)) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of Hb A(1c). The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.

BACKGROUND: Multiple laboratory tests are used to diagnose and manage patients with diabetes mellitus. The quality of the scientific evidence supporting the use of these tests varies substantially. APPROACH: An expert committee compiled evidence-based recommendations for the use of laboratory testing for patients with diabetes. A new system was developed to grade the overall quality of the evidence and the strength of the recommendations. Draft guidelines were posted on the Internet and presented at the 2007 Arnold O. Beckman Conference. The document was modified in response to oral and written comments, and a revised draft was posted in 2010 and again modified in response to written comments. The National Academy of Clinical Biochemistry and the Evidence-Based Laboratory Medicine Committee of the American Association for Clinical Chemistry jointly reviewed the guidelines, which were accepted after revisions by the Professional Practice Committee and subsequently approved by the Executive Committee of the American Diabetes Association. CONTENT: In addition to long-standing criteria based on measurement of plasma glucose, diabetes can be diagnosed by demonstrating increased blood hemoglobin A₁c (HbA₁c) concentrations. Monitoring of glycemic control is performed by self-monitoring of plasma or blood glucose with meters and by laboratory analysis of HbA₁c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of autoantibodies, urine albumin, insulin, proinsulin, C-peptide, and other analytes are addressed. SUMMARY: The guidelines provide specific recommendations that are based on published data or derived from expert consensus. Several analytes have minimal clinical value at present, and their measurement is not recommended.