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Torsten Roed,1 Ulrik Sloth Kristoffersen,2 Andreas Knudsen,1,2 Niels Wiinberg,3 Anne-Mette Lebech,1 Thomas Almdal,4 Reimar W Thomsen,5 Andreas Kjær,2 Nina Weis1,61Department of Infectious Diseases, Copenhagen University Hospital, Hvidovre, Denmark; 2Department of Clinical Physiology, Nuclear Medicine and PET and Cluster for Molecular Imaging, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark; 3Department of Clinical Physiology, Frederiksberg Hospital, Copenhagen, Denmark; 4Steno Diabetes Center, Copenhagen, Denmark; 5Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark; 6Faculty of Health Sciences, University of Copenhagen, Copenhagen, DenmarkObjective: Chronic hepatitis C is a global health problem and has been associated with coronary artery disease. Our aim was to examine the prevalence of coronary artery disease risk markers including endothelial biomarkers in patients with chronic hepatitis C and matched comparisons without manifest cardiovascular disease or diabetes in a cross-sectional design.Methods: Sixty patients with chronic hepatitis C (mean age 51 years) were recruited from the Department of Infectious Diseases at Copenhagen University Hospital, and compared with 60 age-matched non-hepatitis C virus-infected individuals from a general population survey. We examined traditional coronary artery disease risk factors, metabolic syndrome, carotid intima media thickness, and a range of endothelial biomarkers.Results: Patients with chronic hepatitis C had more hypertension (40% versus 25%, prevalence ratio [PR] 1.6; 95% confidence interval [CI] 0.9–2.7) and smoked more (53% versus 38%, PR 1.4; 95% CI 0.9–2.1). The two groups had similar body mass index (mean 25.0 versus 25.7 kg/m2), whereas those with chronic hepatitis C had less dyslipidemia (including significantly lower low-density lipoprotein and cholesterol/high-density lipoprotein ratio), higher glycosylated hemoglobin level (mean 6.2 versus 5.7, difference of means 0.5; 95% CI 0.3–0.8), and a higher prevalence of metabolic syndrome (28% versus 18%, PR 1.6; 95% CI 0.8–3.0). Increased carotid intima media thickness above the standard 75th percentile was seen more frequently in chronic hepatitis C (9% versus 3%, PR 1.7; 95% CI 0.4–6.7), though difference of means was only 0.04 mm (95% CI 0.00–0.10). Patients with chronic hepatitis C had increased hsCRP (high-sensitivity C-reactive protein), sICAM-1 (soluble intercellular adhesion molecule-1), sVCAM-1 (soluble vascular cell adhesion molecule-1), and soluble E-selectin, but lower levels of tPAI-1 (tissue-type plasminogen activator inhibitor-1), MMP9 (matrix metallopeptidase 9), and MPO (myeloperoxidase) than their comparisons.Conclusion: Our findings indicate that patients with chronic hepatitis C have increased prevalence of several coronary artery disease risk markers. These results may be important when evaluating the appropriateness of screening for coronary artery disease and its risk factors in chronic hepatitis C.Keywords: risk factors, atherosclerosis, endothelial dysfunction, biomarkers, metabolic syndrome, intima media thickness

Introduction: Hemodialysis (HD) induces several physiological changes that can affect plasma glucose levels in patients with diabetes and in turn their glycemic control. Studies using continuous glucose monitoring (CGM) to assess glucose variations on dialysis days compared with nondialysis days report conflicting results. Here, we used CGM to examine glucose variations induced by HD in patients with type 2 diabetes., Methods: Patients with type 2 diabetes undergoing maintenance HD were included. CGM (Ipro2®, Medtronic) was performed at baseline and Week 4, 8, 12, and 16 for up to 7 days at each visit. CGM profiles on days where participants received HD were compared with days without HD using a linear mixed model., Findings: Twenty-seven patients were included. The median number of CGM days performed was 8 (interquartile range [IQR] 6-10) for dialysis days and 16 (IQR 12-17) for nondialysis days. The median sensor glucose was 9.4 (95% confidence interval [CI] 8.8-10.2) mmol/L on dialysis days compared with 9.5 (95% CI 8.9-10.2) mmol/L on nondialysis days (p = 0.58). Nocturnal mean sensor glucose was higher on dialysis days compared with nondialysis days: 8.8 (95% CI 8.0-9.6) mmol/L versus 8.4 (95% CI 7.7-9.2) mmol/L (p = 0.029)., Discussion: Similar median sensor glucose values were found for days on and off HD. Nocturnal glucose levels were modestly increased on dialysis days. Our findings indicate that antidiabetic treatment does not need to be differentiated on dialysis versus nondialysis days in patients with type 2 diabetes undergoing maintenance HD., (© 2023 The Authors. Hemodialysis International published by Wiley Periodicals LLC on behalf of International Society for Hemodialysis.)

Background: Nonalcoholic fatty liver disease (NAFLD) is suggested as a risk factor for chronic kidney disease (CKD). The incidence of NAFLD is rising globally in parallel to the increasing incidences of obesity and type 2 diabetes. Diabetes remains the leading cause of CKD, but the co-existence of NAFLD, CKD, and type 2 diabetes is not well elucidated. Here, we evaluated the prevalence of NAFLD in patients with type 2 diabetes with and without CKD., Methods: This was a cross-sectional study including 50 patients with type 2 diabetes and CKD stages 3-5 (no dialysis), and 50 patients with type 2 diabetes without CKD. Liver fat content was estimated by proton magnetic resonance spectroscopy and magnetic resonance imaging proton density fat fraction. NAFLD was defined as liver fat fraction ≥5.6% according to guidelines., Results: Mean age was 72 ± 4.9 years in patients with CKD and 65.9 ± 7.8 years in patients without CKD (p < 0.0001). Three out of four participants were men. BMI was 28.6 ± 3.5 kg/m2 and 27 ± 4.0 kg/m2 in patients with and without CKD, respectively (p = 0.0087). NAFLD was identified in 22 (44%) patients with CKD and 19 (38%) patients without CKD (p = 0.6845). Median (IQR) liver fat fraction was 4.7% (3.0-8.5) and 4.1% (2.9-7.7) in patients with and without CKD, respectively (difference in geometric means 5.3%, 95% CI -23; 45, p = 0.7463)., Conclusion: These findings do not support any association between NAFLD and CKD (stages 3-5) in patients with type 2 diabetes., (© 2023 S. Karger AG, Basel.)

Background: Non-alcoholic fatty liver disease (NAFLD), and particularly liver fibrosis, has been suggested as a risk factor of chronic kidney disease (CKD). Given that NAFLD affects every fourth person globally, better insight is needed. Our aim was to investigate the association between hepatic fibrosis and CKD in patients with type 2 diabetes and to compare different methods for diagnosing liver fibrosis in this study population., Methods: Cross-sectional study including patients with type 2 diabetes with CKD stages 3-5 (N = 50) or without CKD (N = 50). CKD was defined as estimated glomerular filtration rate &lt;60 mL/min/1.73 m2 with or without proteinuria. Three methods were used to detect significant liver fibrosis defined as either ≥8 kilopascal measured by transient elastography (FibroScan®), fibrosis-4 (FIB-4) score ≥2.67, or NAFLD fibrosis score (NFS) &gt;0.675., Results: Significant liver fibrosis was found in 38% and 28% of the patients with and without CKD, respectively, using at least one of the three methods. Both FIB-4 score and NFS were significantly higher in patients with CKD (p &lt; 0.0009 and p &lt; 0.0001, respectively), although insignificant after adjustments for age, sex, body mass index, and duration of diabetes. In patients without CKD, a significant association between steatosis and fibrosis was observed (p = 0.0007)., Conclusion: Our data do not support any strong independent association between liver fibrosis and established CKD as assessed by FibroScan, FIB-4 score, and NFS, respectively., (© 2023 S. Karger AG, Basel.)

Objective: A systematic review of the prevalence and prognosis of posttransplant diabetes mellitus (PTDM) following the transplantation of heart, lung, liver and kidney and a metaanalysis of randomised studies of glucose-lowering treatment is reported., Methods: We searched for publications on solid organ transplants and PTDM in relation to the risk and total mortality of PTDM and randomized controlled trials aiming at reducing glucose levels., Results: PTDM prevalence one year after transplantation was reported to be 9-40%. Ten years after transplantation, 60-85% of people without PTDM and 30-76% of people with PTDM were alive. Following kidney transplantation, we identified six randomized controlled trials on the treatment of PTDM. Intervention ranged from 3 to 12 months. Four studies used intervention with oral glucose-lowering drugs, one used dietician appointments and exercise, and one used insulin treatment. Among the intermediate results reported, a reduction in HbA1c of 2.7 mmol/mol, and an increase in the odds ratio of serious adverse events of 3.0 was significant., Conclusion: In conclusion, information on the prevalence and effect on survival of PTDM is heterogeneous, and the randomized studies on the effect of treatment available are short and lack information on clinically important endpoints, such as mortality or morbidity., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Metformin has been shown to have both neuroprotective and neurodegenerative effects. The aim of this study was to investigate the effect of metformin in combination with insulin on cardiovascular autonomic neuropathy (CAN) and distal peripheral neuropathy (DPN) in individuals with type 2 diabetes (T2DM). Methods: The study is a sub-study of the CIMT trial, a randomized placebo-controlled trial with a 2 × 3 factorial design, where 412 patients with T2DM were randomized to 18 months of metformin or placebo in addition to open-labelled insulin. Outcomes were measures of CAN: Changes in heart rate response to deep breathing (beat-to-beat), orthostatic blood pressure (OBP) and heart rate and vibration detection threshold (VDT) as a marker DPN. Serum levels of vitamin B12 and methyl malonic acid (MMA) were analysed. Results: After 18 months early drop in OBP (30 s after standing) was increased in the metformin group compared to placebo: systolic blood pressure drop increased by 3.4 mmHg (95% CI 0.6; 6.2, p = 0.02) and diastolic blood pressure drop increased by 1.3 mmHg (95% CI 0.3; 2.6, p = 0.045) compared to placebo. Beat-to-beat variation decreased in the metformin group by 1.1 beats per minute (95% CI − 2.4; 0.2, p = 0.10). Metformin treatment did not affect VDT group difference − 0.33 V (95% CI − 1.99; 1.33, p = 0.39) or other outcomes. Changes in B12, MMA and HbA1c did not confound the associations. Conclusions: Eighteen months of metformin treatment in combination with insulin compared with insulin alone increased early drop in OBP indicating an adverse effect of metformin on CAN independent of vitamin B12, MMA HbA1c. Trial registration The protocol was approved by the Regional Committee on Biomedical Research Ethics (H–D-2007-112), the Danish Medicines Agency and registered with ClinicalTrials.gov (NCT00657943). [ABSTRACT FROM AUTHOR]

Introduction: Shortened erythrocyte life span and erythropoietin-stimulating agents may affect hemoglobin A1c (HbA1c) levels in patients receiving peritoneal dialysis (PD). We compared HbA1c with interstitial glucose measured by continuous glucose monitoring (CGM) in patients with type 2 diabetes receiving PD., Methods: Fourteen days of CGM (Ipro2, Medtronic) were performed in 23 patients with type 2 diabetes receiving PD and in 23 controls with type 2 diabetes and an estimated glomerular filtration rate over 60 mL/min/1.73 m2. Patients were matched on gender and age (±5 years). HbA1c (mmol/mol), its derived estimate of mean plasma glucose (eMPGA1c) (mmol/L), and fructosamine (µmol/L) were measured at the end of the CGM period and compared with the mean sensor glucose (mmol/L) from CGM., Results: In the PD group, mean sensor glucose was 0.98 (95% con-fidence interval (CI): 0.43-1.54) mmol/L higher than the eMPGA1c compared with the control group (p = 0.002) where glucose levels were nearly identical (-0.05 (95% CI: -0.35-0.25) mmol/L). A significant association was found between fructosamine and mean sensor glucose using linear regression with no difference between slopes (p = 0.89) or y-intercepts (p = 0.28)., Discussion/conclusion: HbA1c underestimates mean plasma glucose levels in patients with type 2 diabetes receiving PD. However, the clinical significance of this finding is undetermined. Fructosamine seems to more accurately reflect glycemic status. CGM or fructosamine could complement HbA1c to increase the accuracy of glycemic monitoring in the PD population., (© 2021 S. Karger AG, Basel.)

Introduction: The accuracy of hemoglobin A1c (HbA1c) as a glycemic marker in patients with type 2 diabetes (T2D) receiving hemodialysis (HD) remains unknown. To assess accuracy, we compared HbA1c and fructosamine levels with interstitial glucose measured by continuous glucose monitoring (CGM) in patients with T2D receiving HD., Methods: Thirty patients in the HD group and 36 patients in the control group (T2D and an estimated glomerular filtration rate >60 mL/min/1.73 m2) completed the study period of 17 weeks. CGM (Ipro2®, Medtronic) was performed 5 times for periods of up to 7 days (with 4-week intervals) during a 16-week period. HbA1c (mmol/mol), the estimated mean plasma glucose from HbA1c (eMPGA1c [mmol/L]) and fructosamine (μmol/L) was measured at week 17 and compared with mean sensor glucose levels from CGM., Findings: In the HD group, mean sensor glucose was 1.4 mmol/L (95% confidence interval [CI]: 1.0-1.8) higher than the eMPGA1c, whereas the difference for controls was 0.1 mmol/L (95% CI: -0.1-[0.4]; p < 0.001). Adjusted for mean sensor glucose, HbA1c was lower in the HD group (-7.3 mmol/mol, 95% CI: -10.0-[-4.7]) than in the control group (p < 0.001), with no difference detected for fructosamine (p = 0.64)., Discussion: HbA1c evaluated by CGM underestimates plasma glucose levels in patients receiving HD. The underestimation represents a clinical challenge in optimizing glycemic control in the HD population. Fructosamine is unaffected by the factors affecting HbA1c and appears to be more accurate for glycemic monitoring. CGM or fructosamine could thus complement HbA1c in obtaining more accurate glycemic control in this patient group., (© 2021 S. Karger AG, Basel.)

Aims/hypothesis: We aimed to compare the effects of intermittently scanned continuous glucose monitoring (isCGM) and carbohydrate counting with automated bolus calculation (ABC) with usual care., Methods: In a randomised, controlled, open-label trial carried out at five diabetes clinics in the Capital Region of Denmark, 170 adults with type 1 diabetes for ≥1 year, multiple daily insulin injections and HbA 1c  > 53 mmol/mol (7.0%) were randomly assigned 1:1:1:1 with centrally prepared envelopes to usual care (n = 42), ABC (n = 41), isCGM (n = 48) or ABC+isCGM (n = 39). Blinded continuous glucose monitoring data, HbA 1c and patient-reported outcomes were recorded at baseline and after 26 weeks. The primary outcome was change in time in range using isCGM vs usual care., Results: Baseline characteristics were comparable across arms: mean age 47 (SD 13.7) years, median (IQR) diabetes duration 18 (10-28) years and HbA 1c 65 (61-72) mmol/mol (8.1% [7.7-8.7%]). Change in time in range using isCGM was comparable to usual care (% difference of 3.9 [-12-23], p = 0.660). The same was true for the ABC and ABC+isCGM arms and for hypo- and hyperglycaemia. Also compared with usual care, using ABC+isCGM reduced HbA 1c (4 [95% CI 1, 8] mmol/mol) (0.4 [0.1, 0.7] %-point) and glucose CV (11% [4%, 17%]) and improved treatment satisfaction, psychosocial self-efficacy and present life quality. Treatment satisfaction also improved by using isCGM alone vs usual care. Statistical significance was maintained after multiple testing adjustment concerning glucose CV and treatment satisfaction with ABC+isCGM, and treatment satisfaction with isCGM. Discontinuation was most common among ABC only users, and among completers the ABC was used 4 (2-5) times/day and the number of daily isCGM scans was 5 (1-7) at study end., Conclusions/interpretation: isCGM alone did not improve time in range, but treatment satisfaction increased in technology-naive people with type 1 diabetes and suboptimal HbA 1c . The combination of ABC+isCGM appears advantageous regarding glycaemic variables and patient-reported outcomes, but many showed resistance towards ABC., Trial Registration: ClinicalTrials.gov NCT03682237., Funding: The study is investigator initiated and financed by the Capital Region of Denmark., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Introduction: Hyperglycaemia during hospitalisation is associated with a longer and more complicated admission and with increased mortality. Therefore, guidelines suggest that blood glucose should be less than 10 mmol/l. In this audit, we aimed to describe the prevalence of diabetes patients at four orthopaedic departments in the Capital Region of Denmark and to measure the quality of in-hospital diabetes management., Methods: We conducted audits of medical records in the electronic health record system for two months in 2019. All patients admitted were included in the audit. We gathered information on diabetes status, orthopaedic diagnosis, glycosylated haemoglobin and diabetes management., Results: Among 2,463 included patients, 10% had diabetes. The three most frequent diagnosis groups were infection, fracture of lower extremity and hospitalised for alloplastic surgery. The number of blood glucose measurements during 24-hour perioperative care was 6.5. Among patients analysed, 10-20% did not have their blood glucose measured in the days following surgery. Among patients, 64% received insulin 1-50% of the required times., Conclusion: We demonstrated that 10% of hospitalised patients suffer from diabetes. The audit also showed that blood glucose is generally measured according to guidelines, whereas the treatment of an elevated blood glucose is far from being given according to guidelines. This may potentially delay recovery and prolong hospitalisation., Funding: none., Trial Registration: not relevant., (Articles published in the DMJ are “open access”. This means that the articles are distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits any non-commercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.)

Aims To test whether concomitant use of an automated bolus calculator for people with Type 1 diabetes carrying out advanced carbohydrate counting would induce further improvements in metabolic control. Methods We conducted a 12-month, randomized, parallel-group, open-label, single-centre, investigator-initiated clinical study. We enrolled advanced carbohydrate counting-naïve adults with Type 1 diabetes and HbA1c levels 64-100 mmol/mol (8.0-11.3%), who were receiving multiple daily insulin injection therapy. In a 1:1-ratio, participants were randomized to receive training in either advanced carbohydrate counting using mental calculations ( MC group) or advanced carbohydrate counting using an automated bolus calculator ( ABC group) during a 3.5-h group training course. For 12 months after training, participants attended a specialized diabetes centre quarterly. The primary outcome was change in HbA1c from baseline to 12 months. Results Between August 2012 and September 2013, 168 participants (96 men and 72 women) were recruited and randomly assigned to the MC group ( n = 84) and the ABC group ( n = 84). Drop-out rates were 23.8 and 21.4%, respectively ( P = 0.712); 130 participants completed the study. The baseline HbA1c was 75 ± 9 mmol/mol (9.0 ± 0.8%) in the MC group and 74 ± 8 mmol/mol (8.9 ± 0.7%) in the ABC group. At 12 months, change in HbA1c was significant within both groups: MC group: -2 mmol/mol (95% CI -4 to -1) or -0.2% (95% CI -0.4 to -0.1; P = 0.017) and ABC group: -5 mmol/mol (95% CI -6 to -3) or -0.5% (95% CI -0.6 to -0.3; P < 0.0001), but HbA1c reductions were significantly greater in the ABC group ( P = 0.033). No episodes of severe hypoglycaemia were reported. Conclusions People with Type 1 diabetes initiating advanced carbohydrate counting obtained significantly greater HbA1c reductions when guided by an automated bolus calculator ( NCT02084498). [ABSTRACT FROM AUTHOR]

Introduction: A reduced erythrocyte lifespan potentially explains the low hemoglobin A1c values found in hemodialysis patients. However, data supporting this notion in patients with type 2 diabetes is unclear. We evaluated the erythrocyte lifespan in patients with type 2 diabetes undergoing long-term hemodialysis and investigated potential predictors of erythrocyte lifespan., Methods: Long-term hemodialysis patients with type 2 diabetes and type 2 diabetes patients without nephropathy (estimated glomerular filtration rate > 60 mL/min/1.73 m 2 ) were included. The erythrocyte lifespan was measured using chromium-51 ( 51 Cr)-labeled erythrocytes. Blood radiotracer activity was measured six to nine times over a period of 3-5 weeks to determine the erythrocyte lifespan of each patient. Biochemical markers were obtained five times over 16 weeks and associated with the erythrocyte lifespan., Findings: Type 2 diabetes patients undergoing hemodialysis (N = 13) had a significantly shorter median erythrocyte lifespan of 49.7 (interquartile range [IQR] = 44.1-58.6) days compared with 64.2 (IQR = 62.6-83.5) days in the control group (N = 10) (P ˂ 0.001) with a difference between medians of 14.5 (95% confidence interval = 8.1-38.8) days. In the hemodialysis group, no association could be detected between the erythrocyte lifespan and markers of hemolysis, level of inflammation, or urea., Discussion: A reduced erythrocyte lifespan was detected in type 2 diabetes patients undergoing long-term hemodialysis. This may contribute to the reduced hemoglobin A1c values observed in the type 2 diabetic hemodialysis population. An association could not be detected between the erythrocyte lifespan and biochemical markers of hemolysis or inflammation., (© 2020 International Society for Hemodialysis.)