Tight versus less tight 1-hour postprandial glycemic target in women with gestational diabetes mellitus - a single-center cohort study.

OBJECTIVES: We aimed to assess the impact of the change of 1-hour postprandial glycemic target from < 6.7 mmol/L (120 mg/dL) to < 7.8 mmol/L (140 mg/dL) on gestational diabetes mellitus (GDM) treatment and pregnancy outcomes. MATERIAL AND METHODS: In a retrospective analysis of 1021 GDM patients from the Department of Metabolic Diseases, University Hospital in Cracow, Poland, we compared insulin therapy regimens and pregnancy outcomes between women admitted in 2014-2016 (before the change) and in 2018-2019 (after it). RESULTS: A total of 377 patients were admitted between 2014 and 2016 (TIGHT group) and 644 between 2018 and 2019 (LESS TIGHT group). Women from the LESS TIGHT group were older (32 vs 30 years, p < 0.001) and gained less weight during pregnancy (7.0 vs 9.0 kg, p < 0.001). There was no change in the frequency of any insulin therapy (51.6% vs 56.1%, p = 0.168). In the LESS TIGHT group, the basal insulin-only model was used more frequently (32.5% vs 10.2%, p < 0.001), while the prandial insulin and basal-bolus model less frequently (23.6% vs 42.6% and 21.4% vs 36.7%, p < 0.001, respectively) than in the TIGHT group. There were no differences in the frequency of cesarean sections, preterm births, Hbd of delivery, mean birth weight or prevalence of perinatal complications. CONCLUSIONS: Less tight glycemic targets in women with GDM, compared to tighter targets, were associated with less frequent use of prandial insulin, with insulin therapy often limited to basal administration. The change in glycemic targets did not affect the prevalence of adverse pregnancy outcomes, providing evidence supporting new recommendations.

Diabetes distress and diabetes burnout explored in various areas of life in patients with type 1 diabetes: effect of short-term psychological intervention.

INTRODUCTION: Diabetes distress (DD) and diabetes burnout (DB) are recognized psychological phenomena in patients with T1DM (type 1 diabetes mellitus). Still, there is an urgent need to create professional psychological intervention procedures to provide patients with adequate care. AIM: The aim of the study was to assess the level of DD and DB in T1DM patients at baseline and after 5 of sessions psychological intervention in the group of participants who applied for help. METHODS: 34 T1DM patients who requested psychological support (22 females, 12 males) and 30 patients in a control group (14 females, 16 males) participated in the study. At baseline clinical test results between groups were compared. Next, in the studied group measurements were repeated after a set of five psychological face-to-face individual interventions which lasted 30-60 min each. They were support sessions with elements of cognitive-behavioral interventions done by clinical psychologists. Session 1: introduction, interview and collection of test results; session 2-4: work on the indicated by the patient and test results most problematic aspect of diabetes, session 5: a summary and plan for further treatment if needed. The control group results were obtained only at baseline. Research tools: DDS; PAID, Diabetes Burnout test by Polonsky. RESULTS: At the baseline, significant differences were observed between the studied group and control group: in DB/DD levels: DB (3.9 ± 1.7 vs 2.4 ± 1.6; p < 0.001); DDS (3.2 ± 1.0 vs 2.7 ± 1.0; p = 0.064); PAID (62.3 ± 14.1vs 34.4 ± 21.0; p < 0.001). There were also group differences in HbA1c levels (8.7 ± 2.4 vs 7.3 ± 1.5; p = 0.028). After psychological interventions, there was a significant improvement in DB (3.9 ± 1.7vs 2.9 ± 1.2; p < 0.001; DDS (3.2 ± 1 vs 3.0 ± 0.7; p = 0.03); PAID (62.3 ± 14.1 vs 51.8 ± 12.5; p < 0.001). CONCLUSIONS: DD and DB constitute a significant problem in the group of T1DM patients, but providing appropriate specialist care may help them accept diabetes and improve life satisfaction, as well as regain control over their diabetes management.

Predictors of ≥15% Weight Reduction and Associated Changes in Cardiometabolic Risk Factors With Tirzepatide in Adults With Type 2 Diabetes in SURPASS 1-4.

OBJECTIVE: To identify predictors of body weight (BW) reduction of ≥15% with tirzepatide treatment and to describe associated clinical parameters of participants with type 2 diabetes (T2D) who achieved different categorical measures of BW reduction (<5%, ≥5 to <10%, ≥10 to <15%, and ≥15%) across four studies from the phase 3 SURPASS clinical trial program for T2D. RESEARCH DESIGN AND METHODS: The multivariate model for predictor of a BW reduction of ≥15% included age, sex, race, BW, HbA1c, tirzepatide dose and baseline metformin use, fasting serum glucose, and non-HDL cholesterol. Baseline characteristics and change from baseline to week 40/42 for efficacy parameters were described and analyzed in treatment-adherent participants (≥75% doses administered and on treatment at week 40/42) receiving once weekly tirzepatide (5 mg, 10 mg, or 15 mg) (N = 3,188). RESULTS: Factors significantly associated with achieving a BW reduction of ≥15% with tirzepatide were higher tirzepatide doses, female sex, White or Asian race, younger age, metformin background therapy, and lower HbA1c, fasting serum glucose, and non-HDL cholesterol at baseline. With higher categorical BW reduction, there were greater reductions in HbA1c, triglycerides, ALT, waist circumference, and blood pressure. CONCLUSIONS: Baseline factors associated with a higher likelihood of achieving a BW reduction of ≥15% with tirzepatide were higher tirzepatide doses, female sex, White or Asian race, younger age, metformin background therapy, better glycemic status, and lower non-HDL cholesterol. With greater BW reduction, participants with T2D achieved larger improvements in glycemia and cardiometabolic risk parameters. These findings help inform which people with T2D are most likely to achieve greater BW reduction with improved cardiometabolic risk factors with tirzepatide.

Quality of life in the course of a one-year use of an advanced hybrid closed-loop system in adults with type 1 diabetes previously naïve to advanced diabetes technology.

Aim: To evaluate the effect of a one-year use of an advanced hybrid closed-loop (AHCL) system on the quality of life, level of anxiety, and level of self-efficacy in adults with type 1 diabetes (T1D) previously treated with multiple daily injections (MDI) and naïve to advanced diabetes technology. Methods: A total of 18 participants of a previously published 3-month randomized trial (10 men, 8 women; age 40.9 ± 7.6 years) who were switched directly from MDI/BMG to AHCL completed 12 months of MiniMed 780G™system use (a 3-month randomized trial followed by a 9-month follow-up phase). At month 6 of the study, patients were switched from the sensor GS3 (Continuous Glucose Monitoring) system, powered by Guardian™ Sensor 3) to GS4. Quality of life was assessed using the Polish validated version of the 'QoL-Q Diabetes' questionnaire. The level of anxiety was evaluated with the use of the State-Trait Anxiety Inventory (STAI). Self-efficacy was assessed with the General Self-Efficacy Scale (GSES). Results were obtained at baseline and at the end of the study. Results: Significant increase in QoL was reported in the global score (p=0.02, Cohen d=0.61) and in as many as 11 out of 23 analyzed areas of life: being physically active (p=0.02, Cohen d = 0.71); feeling well (p<.01, Cohen d = 0.73); feeling in control of my body (p<.01, Cohen d = 0.72); looking good (p<.01, Cohen d = 1.07); working (p<.01, Cohen d = 1.12); sleeping (p=0.01, Cohen d = 0.66); eating as I would like (p<.01, Cohen d = 0.79); looking after or being useful to others (p= 0.02, Cohen d = 0.65); being active with pets/animals (p<.01, Cohen d = 0.95); being spontaneous (p=0.02, Cohen d = 0.67); and doing "normal" things (p=0.02, Cohen d = 0.67). Both state (p=0.04, Cohen d = 0.56) and trait (p=0.02, Cohen d = 0.60) anxiety decreased while the general self-efficacy increased (p=0.03, Cohen d = 0.76). No participant stopped the use of the pump. Conclusion: Adult patients with T1D previously treated with MDI and naïve to modern technologies experienced significant improvement in their psychological well-being after transitioning to the AHCL system after 12 months of treatment.

Assessment of selected muscle damage markers and zonulin concentration after maximum-intensity exercise in men with type 1 diabetes treated with a personal insulin pump.

AIM: Exercise-induced muscle damage depends on exercise intensity and duration and on individual susceptibility. Mechanical and metabolic stress may disturb the intestinal microflora. The study evaluated selected muscle damage markers and zonulin concentration after maximum-intensity exercise in type 1 diabetes (T1D) men compared with healthy controls. METHODS: The study involved 16 T1D participants and 28 controls matched by age (22.7 [21.3-25.1] vs. 22.6 [20.9-26.3] years), body mass index (24.2 ± 1.6 vs. 24.2 ± 1.9 kg/m2), and body fat percentage (16.1 ± 5.2 vs. 14.9 ± 4.6%). The T1D group had 11.3 ± 5.1 years of diabetes duration and a suboptimal mean glycated haemoglobin level of 7.2 ± 1.1%. The subjects underwent a graded running treadmill test until exhaustion. Lactate concentration was assessed in arterialized blood at baseline and 3 and 20 min after the test. Cortisol, testosterone, tumour necrosis factor α, myoglobin, lactate dehydrogenase, zonulin, and vitamin D levels were evaluated in cubital fossa vein blood before and 60 min after the test. RESULTS: T1D patients presented higher baseline zonulin, myoglobin concentration, testosterone/cortisol ratio, and lower maximal oxygen uptake. On adjusting for the baseline values, the groups differed in zonulin, lactate dehydrogenase, and myoglobin levels, testosterone/cortisol ratio, and lactate concentration determined 20 min after exercise (P < 0.05). CONCLUSION: Maximum-intensity exercise increased muscle and intestinal damage in T1D participants. In patients with lower physical activity, very-high-intensity exercise should be recommended with caution. Observing the anabolic-catabolic index may help individualize effort intensity in T1D individuals.

Prior Diagnosis of Diabetes but Not Its Control is Associated with Higher Depression Score Among Older Individuals.

Purpose: The study assessed the relationship between prior diagnosis of diabetes and its control with depression score, differences in socioeconomic, lifestyle, health characteristics and diabetes control by adherence to treatment in population-based sample of older individuals. Patients and Methods: The analysis of the sub-sample of Polish cohort of the HAPIEE (Health, Alcohol, and Psychosocial Factors in Eastern Europe) study was conducted; 464 participants were interviewed and random first 360 (78%) underwent physical examination and blood sample tests. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale. The robust regression method was applied to assess the association between depression score and diabetes diagnosis as well as diabetes control. Results: There were 97 participants (21.0%) at mean age of 73.6 years (SD=6.31 years) with prior diagnosis of diabetes. Mean HbA1c concentration was 6.65% (SD=1.0) The majority of patients (55.7%) used oral medication with diet. Nearly 20% declared the use of oral treatment alone, and 10.3% used combined treatment of oral medications, insulin, and diet. In this study, 86.6% of the participants with diabetes confirmed self-monitoring of blood glucose levels and 58.8% were on high-quality diet. No differences in socioeconomic, lifestyle, health characteristics or control of diabetes by adherence to diabetes treatment were found. After adjustment for age and gender, diagnosis of diabetes was associated with greater depressive score by about 2 points (ß=2.02, 95% CI=0.16;3.88). However, no significant association between depression score and any indicator of diabetes control was found. Conclusion: In older individuals with diabetes, depression score was higher compared to those without diabetes, but it was not related to poorer diabetes control. No differences in socioeconomic, lifestyle, health characteristics and control of diabetes by adherence to diabetes treatment may suggest that in this age group some other, less known factors are substantial for achievement of treatment targets.

Corrigendum: Diabetes as a risk factor of death in hospitalized COVID-19 patients - an analysis of a National Hospitalization Database from Poland, 2020.

[This corrects the article DOI: 10.3389/fendo.2023.1161637.].

Expanding the Role of Continuous Glucose Monitoring in Modern Diabetes Care Beyond Type 1 Disease.

Application of continuous glucose monitoring (CGM) has moved diabetes care from a reactive to a proactive process, in which a person with diabetes can prevent episodes of hypoglycemia or hyperglycemia, rather than taking action only once low and high glucose are detected. Consequently, CGM devices are now seen as the standard of care for people with type 1 diabetes mellitus (T1DM). Evidence now supports the use of CGM in people with type 2 diabetes mellitus (T2DM) on any treatment regimen, not just for those on insulin therapy. Expanding the application of CGM to include all people with T1DM or T2DM can support effective intensification of therapies to reduce glucose exposure and lower the risk of complications and hospital admissions, which are associated with high healthcare costs. All of this can be achieved while minimizing the risk of hypoglycemia and improving quality of life for people with diabetes. Wider application of CGM can also bring considerable benefits for women with diabetes during pregnancy and their children, as well as providing support for acute care of hospital inpatients who experience the adverse effects of hyperglycemia following admission and surgical procedures, as a consequence of treatment-related insulin resistance or reduced insulin secretion. By tailoring the application of CGM for daily or intermittent use, depending on the patient profile and their needs, one can ensure the cost-effectiveness of CGM in each setting. In this article we discuss the evidence-based benefits of expanding the use of CGM technology to include all people with diabetes, along with a diverse population of people with non-diabetic glycemic dysregulation.

Novel methods of continuous glucose monitoring and telehealth in the improvement of diabetes care: a narrative review.

Standard markers of glycaemic control, such as glycated haemoglobin (HbA1c) and self-measurement of blood glucose (SMBG), have proven insufficient. HbA1c is an averaged measurement that does not give information about glucose variability. SMBG provides limited, intermittent blood glucose (BG) values over the day and is associated with poor compliance because of the invasiveness of the method and social discomfort. In contrast to glucometers, continuous glucose monitoring (CGM) devices do not require finger-stick blood samples, but instead measure BG via percutaneous or subcutaneous sensors. The immediate benefits of CGM include prevention of hypoglycaemia or hyperglycaemia, and automated analysis of long-term glycaemic data enables reliable treatment adjustments. This review describes the principles of CGM and how CGM data have changed diabetes treatment standards by introducing new glycaemic control parameters. It also compares different CGM devices and examines how the convenience of sharing CGM data in telehealth applies to the current coronavirus-19 pandemic.

One-Year Follow-Up of Advanced Hybrid Closed-Loop System in Adults with Type 1 Diabetes Previously Naive to Diabetes Technology: The Effect of Switching to a Calibration-Free Sensor.

The aim of this study was to observe the 1-year clinical outcomes of people with type 1 diabetes who switched from multiple daily injection + blood glucose meter to an advanced hybrid closed-loop (AHCL) system (Medtronic MiniMed™ 780G system [MM 780G]). In addition, the effect of changing at month 6 to a calibration-free sensor (Guardian™ 4 Sensor [G4S]) was evaluated. Eighteen participants (10 men, age 40.9 ± 7.6 years) completed 1 year of MM 780G use. Time in range (TIR; 70-180 mg/dL) remained stable and ranged from 83.2% in month 9 to 84.8% in month 3. There was no difference between TIR at 3 months before switching versus 3 months after switching to G4S (P = 0.614). AHCL system in adults significantly improves glycemic outcomes. This improved glycemic control was maintained over the 12 months. Switching to a calibration-free sensor (G4S) did not affect outcomes but required less patient involvement.

Diabetes as a risk factor of death in hospitalized COVID-19 patients - an analysis of a National Hospitalization Database from Poland, 2020.

Introduction: Diabetes is one of the comorbidities associated with poor prognosis in hospitalized COVID-19 patients. In this nationwide retrospective study, we evaluated the risk of in-hospital death attributed to diabetes. Methods: We analyzed data from discharge reports of patients hospitalized with COVID-19 in 2020 as submitted to the Polish National Health Fund. Several multivariate logistic regression models were used. In each model, in-hospital death was estimated with explanatory variables. Models were built either on the whole cohorts or cohorts matched with propensity score matching (PSM). The models examined either the main effects of diabetes itself or the interaction of diabetes with other variables. Results: We included 174,621 patients with COVID-19 who were hospitalized in the year 2020. Among them, there were 40,168 diabetic patients (DPs), and the proportion of DPs in this group was higher than in the general population (23.0% vs. 9.5%, p<0.001). In this group of COVID-19 hospitalizations, 17,438 in-hospital deaths were recorded, and the mortality was higher among DPs than non-diabetics (16.3% vs. 8.1%, p<0.001). Multivariate logistic regressions showed that diabetes was a risk factor of death, regardless of sex and age. In the main effect analysis, odds of in-hospital death were higher by 28.3% for DPs than for non-diabetic patients. Similarly, PSM analysis including 101,578 patients, of whom 19,050 had diabetes, showed that the risk of death was higher in DPs regardless of sex with odds higher by 34.9%. The impact of diabetes differed among age groups and was the highest for patients aged 60-69. Conclusions: This nationwide study confirmed that diabetes was an independent risk factor of in-hospital death in the course of COVID-19 infection. However, the relative risk differed across the age groups.

Comparison of the clinical characteristics, glycemic control, and pregnancy outcomes between women with gestational diabetes mellitus in waves I and III of the COVID-19 pandemic: a reference center report.

OBJECTIVES: The medical care of patients with gestational diabetes mellitus (GDM) during the COVID-19 pandemic was influenced by changing epidemiological conditions and government regulations. Aim - To compare the clinical pregnancy data of GDM women between waves I and III of the pandemic. MATERIAL AND METHODS: We performed a retrospective analysis of medical records from the GDM clinic and compared the periods of March-May 2020 (wave I) and March-May 2021 (wave III). RESULTS: Women with GDM during wave I (n = 119) compared to wave III (n = 116) were older (33.0 ± 4.7 vs 32.1 ± 4.8 years; p = 0.07), booked later (21.8 ± 8.4 vs 20.3 ± 8.5 weeks; p = 0.17), and had their last appointment earlier (35.5 ± 2.0 vs 35.7 ± 3.2 weeks; p < 0.01). Telemedicine consultations were used more frequently during wave I (46.8% vs 24.1%; p < 0.01), while insulin therapy was used less often (64.7% vs 80.2%; p < 0.01). Mean fasting self-measured glucose did not differ (4.8 ± 0.3 vs 4.8 ± 0.3 mmol/L; p = 0.49), but higher postprandial glucose was reported during wave I (6.6 ± 0.9 vs 6.3 ± 0.6 mmol/l; p < 0.01). Pregnancy outcome data were available for 77 wave I pregnancies and 75 wave III pregnancies. The groups were similar in terms of gestational week of delivery (38.3 ± 1.4 vs 38.1 ± 1.6 weeks), cesarean sections (58.4% vs 61.3%), APGAR scores (9.7 ± 1.0 vs 9.7 ± 1.0 pts), and birth weights (3306.6 ± 457.6 g vs 3243.9 ± 496.8 g) (p = NS for all). The mean wave I neonate length was slightly higher (54.3 ± 2.6 cm vs 53.3 ± 2.6 cm; p = 0.04). CONCLUSIONS: We identified differences between wave I and wave III pregnancies for several clinical characteristics. However, nearly all pregnancy outcomes were found to be similar.

Characteristics, Mortality, and Clinical Outcomes of Hospitalized Patients with COVID-19 and Diabetes: A Reference Single-Center Cohort Study from Poland.

Background: Diabetes is a risk factor for a severe course of COVID-19. We evaluated the characteristics and risk factors associated with undesirable outcomes in diabetic patients (DPs) hospitalized due to COVID-19. Materials and Methods: The data analysis of patients admitted between March 6, 2020, and May 31, 2021, to the University Hospital in Krakow (Poland), a reference center for COVID-19, was performed. The data were gathered from their medical records. Results: A total number of 5191 patients were included, of which 2348 (45.2%) were women. The patients were at the median age of 64 (IQR: 51-74) years, and 1364 (26.3%) were DPs. DPs, compared to nondiabetics, were older (median age: 70 years, IQR: 62-77 vs. 62, IQR: 47-72, and p < 0.001) and had a similar gender distribution. The DP group had a higher mortality rate (26.2% vs. 15.7%, p < 0.001) and longer hospital stays (median: 15 days, IQR: 10-24 vs. 13, IQR: 9-20, and p < 0.001). DPs were admitted to the ICU more frequently (15.7% vs. 11.0%, p < 0.001) and required mechanical ventilation more often (15.5% vs. 11.3%, p < 0.001). In a multivariate logistic regression, factors associated with a higher risk of death were age >65 years, glycaemia >10 mmol/L, CRP and D-dimer level, prehospital insulin and loop diuretic use, presence of heart failure, and chronic kidney disease. Factors contributing to lower mortality were in-hospital use of statin, thiazide diuretic, and calcium channel blocker. Conclusion: In this large COVID-19 cohort, DPs constituted more than a quarter of hospitalized patients. The risk of death and other outcomes compared to nondiabetics was higher in this group. We identified a number of clinical, laboratory, and therapeutic variables associated with the risk of hospital death in DPs.

Improvement of Selected Psychological Parameters and Quality of Life of Patients With Type 1 Diabetes Mellitus Undergoing Transition From Multiple Daily Injections and Self-Monitoring of Blood Glucose Directly to the MiniMed 780G Advanced Hybrid Closed-Loop System: Post hoc Analysis of a Randomized Control Study.

BACKGROUND: While introducing new technologies and methods of treatment for type 1 diabetes mellitus (T1DM), it seems essential to monitor whether modern technologies in diabetes treatment may improve the psychological and emotional status of patients. OBJECTIVE: This study aims to assess the baseline psychological parameters of patients with T1DM during investigation of the direct transition from multiple daily injections (MDI) and self-monitoring of blood glucose (SMBG) to the MiniMed 780G advanced hybrid closed-loop (AHCL) system and to evaluate changes in the psychological well-being and quality of life (QoL) after the transition in these individuals versus the control group. METHODS: The trial was a 2-center, randomized controlled, parallel group study. In total, 41 patients with T1DM managed with MDI or SMBG were enrolled and randomized either to the AHCL or the MDI+SMBG group. Of these, 37 (90%) participants (mean age 40.3 years, SD 8.0 years; mean duration of diabetes 17.3, SD 12.1 years; mean hemoglobin A1c [HbA1c] 7.2%, SD 1.0%) completed the study (AHCL: n=20, 54%; MDI+SMBG: n=17, 46%). Psychological parameters (level of stress, coping mechanisms, level of anxiety, self-efficacy level, acceptance of illness, locus of control of illness, life satisfaction, QoL) were measured at baseline and at the end of the study using 10 psychological questionnaires. RESULTS: At baseline, the general level of stress of the examined patients was higher than in the general healthy Polish population (P=.001), but coping strategies used in stressful situations were significantly more effective and the level of self-efficacy (P<.001) was much higher than in the general population. The patients in this study accepted their illness more than patients with diabetes from the general Polish population (P<.001), but they felt that their health does not depend on them compared to the general population (P<.001). The overall life satisfaction was similar to that of the general population (P=.161). After 3 months from transition, the AHCL group reported an increase in 4 scales of the QoL-feeling well (P=.042), working (P=.012), eating as I would like (P=.011), and doing normal things (P=.034)-in comparison to the control group, where no significant change occurred. The level of both state anxiety and trait anxiety decreased in the AHCL group: State-Trait Anxiety Inventory (STAI) X1 scores (P=.009), STAI X1 stens (P=.013), and STAI X2 scores (P=.022). The AHCL group became more emotion oriented in stressful situations (Coping Inventory for Stressful Situations [CISS] E; P=.043) and significantly less self-blaming after 3 months of the study (P=.020). CONCLUSIONS: The results indicate that the patients who decided to take part in the transition study were characterized by higher levels of stress than the general healthy population but had better coping strategies and self-efficacy. Furthermore, transitioning from MDI+SMBG treatment to the AHCL in patients naive to technology may significantly improve psychological well-being and QoL within 3 months. The rapidity of these changes suggests that they may be related to the significant improvement in glycemic outcomes but also significantly less burdened diabetes self-management. TRIAL REGISTRATION: ClinicalTrials.gov NCT04616391; https://clinicaltrials.gov/ct2/show/NCT04616391.

Type 1 diabetes outpatient care and treatment effectiveness during COVID-19: A single-center cohort study.

PURPOSE: COVID-19 has brought many challenges for providing quality healthcare for type 1 diabetes (T1DM). We evaluated the impact of the COVID-19 pandemic on the medical care, glycemic control, and selected outcomes in T1DM patients. METHODS: We retrospectively analyzed medical records from 357 T1DM adults enrolled in the Program of Comprehensive Outpatient Specialist Care at the University Hospital in Krakow, and assessed differences in patient data from before the COVID-19 period (March 2019-February 2020) and after it started COVID-19 (March 2020-February 2021). RESULTS: The median HbA1c levels and the percentage of patients within the HbA1c target of <7 % (53 mmol/mol) were similar in both periods: before and after the beginning of the pandemic (6.86 % [51.5 mmol/mol], IQR 6.23-7.58 % [44.6-59.3 mmol/mol] vs. 6.9 % [51.9 mmol/mol], IQR 6.2-7.61 % [44.3-59.7 mmol/mol]; p = 0.50 and 56.3 % vs. 57.1 %, p = 0.42, respectively). However, we observed a rise in BMI and body weight (median 24.25, IQR 21.97-27.05 vs. 24.82, IQR 22.17-27.87 and median weight 71.0 IQR 61-82 vs. 72.55, IQR 55-85; p < 0.001 for both comparisons). There was no reduction in the numbers of total diabetes-related visits (median 4, IQR 4-5 vs. 5, IQR 4-5; p = 0.065), but the frequency of other specialist consultations decreased (2, IQR 0-2 vs. 1, IQR 0-2). During the pandemic, telehealth visits constituted of 1191 out of 1609 (71.6 %) total visits. CONCLUSIONS: In this single-center observation, the COVID-19 pandemic did not have a negative impact on glycemic control in T1DM patients, but the patients' weight did increase. Telemedicine proved to be a valuable tool for T1DM care.

Type 1 Diabetes Mellitus and Lipohypertrophy - Impact of the Intervention on Glycemic Control via Patient's Examination and Retraining on Change of Infusion Set.

OBJECTIVE: Lipohypertrophy (LH) is a common complication of insulin therapy in type 1 diabetes mellitus (T1DM). We examined whether an intervention consisting of LH assessment and retraining on insulin infusion set use improves glycemic control on subcutaneous insulin infusion (CSII) in patients with T1DM. METHODS: The intervention was conducted in 79 consecutive patients with T1DM. Data on glucose levels, glycated hemoglobin (HbA1c), and insulin doses were collected at baseline and after a median of 22 weeks (20-31.75 weeks). RESULTS: A total of 46 patients with T1DM (23 [50%] women) participating in the follow-up were characterized by a median age of 29 years (25-33.8 years), body mass index of 24.6 ± 3.3 kg/m2, T1DM duration of 16.5 years (8.3-20 years), and subcutaneous insulin infusion duration of 7 years (4-10.8 years). Patients' median HbA1c fell from 7.4% (6.7%-8.2%) to 7.05% (6.4%-7.6%) (P < .001), daily insulin dose/kg decreased (0.7 ± 0.20 vs 0.68 ± 0.15 IU/kg; P = .017) together with the total daily insulin dose (50.3 [40.5-62.7] vs 47.6 [39.8-62.1] IU; P = .019]. Furthermore, the percentage of basal insulin dose increased (43.0% [36-50] vs 44.0% [39.0-50.0]; P = .010], whereas the percentage of bolus dose decreased (57% [50-64] vs 56% [50-61], P = .010). CONCLUSIONS: The structured LH-related intervention in patients with T1DM on insulin pumps resulted in better glycemic control and a decrease in total daily insulin dose.

Higher scanning frequency is correlated with less fear of hypoglycemia in type 1 diabetes patients using isCGM.

Background: Frequent scanning of intermittently scanned continuous glucose monitoring (isCGM) devices is associated with improvements in glycemic indices. Limited data is available for its correlation with fear of hypoglycemia (FOH), an established factor affecting quality of life and glycemic control in type 1 diabetes (T1DM). Aim: The aim of the study was to analyze the association of sensor scanning frequency with FOH and glycemic indices in T1DM patients using isCGM. Subjects and methods: T1DM patients using isCGM were eligible. Clinical data and Ambulatory Glucose Profile (AGP) reports were obtained from medical records. At outpatient visits, AGP of last 14 days prior to visit were analyzed and FOH was assessed using Hypoglycemia Fear Survey II (HFS II). Results: We included 77 consecutive T1DM patients (58 females, 19 males). Mean age was 34.1 ± 10.2 years and mean T1DM duration was 14.7 ± 12.0 years. Baseline mean glycemic indices were as follows: mean glucose - 155.8 ± 29.8 mg/dL; GMI - 53.3 ± 7.5 mmol/mol; TIR - 66.4 ± 17.8%; TBR70 - 4.5 ± 4.1%; TBR54 - 0.6 ± 1.2%; TAR180 - 29.2 ± 17.9%; TAR250 - 9.6 ± 10.4%; %CV - 36.7 ± 8.3. Average scanning frequency was 13.8 ± 7.8 scans/day. Mean HFS II scores were 16.1 ± 7.2 and 18.7 ± 12.2 in behavior and worry subscale, respectively. Correlation was confirmed between scanning frequency and mean glucose, GMI, TIR, TBR70, TAR180, TAR250, %CV and HFS II total, and HFS II - B (p<0.05 for all statistics). Conclusions: For the first time, we report that higher scanning frequency is associated not only with better glycemic indices but also with less FOH in T1DM adult patients using isCGM.

Impact of Arterial Hypertension and Use of Antihypertensive Pharmacotherapy on Mortality in Patients Hospitalized due to COVID-19: The CRACoV-HHS Study.

BACKGROUND: Cardiovascular diseases including arterial hypertension are common comorbidities among patients hospitalized due to COVID-19. We assessed the influence of preexisting hypertension and its pharmacological treatment on in-hospital mortality in patients hospitalized with COVID-19. METHODS: We studied all consecutive patients who were admitted to the University Hospital in Krakow, Poland, due to COVID-19 between March 2020 and May 2021. Data of 5191 patients (mean age 61.9±16.7 years, 45.2% female) were analyzed. RESULTS: The median hospitalization time was 14 days, and the mortality rate was 18.4%. About a quarter of patients had an established cardiovascular disease including coronary artery disease (16.6%) or stroke (7.6%). Patients with hypertension (58.3%) were older and had more comorbidities than patients without hypertension. In multivariable logistic regression analysis, age above median (64 years), male gender, history of heart failure or chronic kidney disease, and higher C-reactive protein level, but not preexisting hypertension, were independent risk factors for in-hospital death in the whole study group. Patients with hypertension already treated (n=1723) with any first-line antihypertensive drug (angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta-blockers, calcium channel blockers, or thiazide/thiazide-like diuretics) had a significantly lower risk of in-hospital death (odds ratio, 0.25 [95% CI, 0.2-0.3]; P<0.001) compared to nontreated hypertensives (n=1305). CONCLUSIONS: Although the diagnosis of preexisting hypertension per se had no significant impact on in-hospital mortality among patients with COVID-19, treatment with any first-line blood pressure-lowering drug had a profound beneficial effect on survival in patients with hypertension. These data support the need for antihypertensive pharmacological treatment during the COVID-19 pandemic.

Variants influencing age at diagnosis of HNF1A-MODY.

BACKGROUND: HNF1A-MODY is a monogenic form of diabetes caused by variants in the HNF1A gene. Different HNF1A variants are associated with differences in age of disease onset, but other factors are postulated to influence this trait. Here, we searched for genetic variants influencing age of HNF1A-MODY onset. METHODS: Blood samples from 843 HNF1A-MODY patients from Czech Republic, France, Poland, Slovakia, the UK and the US were collected. A validation set consisted of 121 patients from the US. We conducted a genome-wide association study in 843 HNF1A-MODY patients. Samples were genotyped using Illumina Human Core arrays. The core analysis was performed using the GENESIS package in R statistical software. Kinship coefficients were estimated with the KING and PC-Relate algorithms. In the linear mixed model, we accounted for year of birth, sex, and location of the HNF1A causative variant. RESULTS: A suggestive association with age of disease onset was observed for rs2305198 (p = 2.09E-07) and rs7079157 (p = 3.96E-06) in the HK1 gene, rs2637248 in the LRMDA gene (p = 2.44E-05), and intergenic variant rs2825115 (p = 2.04E-05). Variant rs2637248 reached nominal significance (p = 0.019), while rs7079157 (p = 0.058) and rs2825115 (p = 0.068) showed suggestive association with age at diabetes onset in the validation set. CONCLUSIONS: rs2637248 in the LRMDA gene is associated with age at diabetes onset in HNF1A-MODY patients.

Transitioning of People With Type 1 Diabetes From Multiple Daily Injections and Self-Monitoring of Blood Glucose Directly to MiniMed 780G Advanced Hybrid Closed-Loop System: A Two-Center, Randomized, Controlled Study.

OBJECTIVE: The aim of this study was to evaluate the outcomes of transitioning to the MiniMed 780G advanced hybrid closed-loop (AHCL) system in adult individuals with type 1 diabetes mellitus (T1DM) naive to continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) technologies. RESEARCH DESIGN AND METHODS: This was a two-center, randomized, controlled, parallel-group trial with evaluation of individuals with T1DM aged 26-60 years managed with multiple daily injections (MDI) and self-monitoring of blood glucose (BGM) with HbA1c <10%. RESULTS: A total of 41 participants were recruited and randomized to either the AHCL (n = 20) or the MDI+BGM (n = 21) group, and 37 participants (mean ± SD age 40.3 ± 8.0 years, duration of diabetes 17.3 ± 12.1 years, BMI 25.1 ± 3.1 kg/m2, HbA1c 7.2 ± 1.0%) completed the study. Time spent with glucose levels in target range increased from 69.3 ± 12.3% at baseline to 85.0 ± 6.3% at 3 months in the AHCL group, while remaining unchanged in the control group (treatment effect 21.5% [95% CI 15.7, 27.3]; P < 0.001). The time with levels below range (<70 mg/dL) decreased from 8.7 ± 7.3% to 2.1 ± 1.7% in the AHCL group and remained unchanged in the MDI+BGM group (treatment effect -4.4% [95% CI -7.4, -2.1]; P < 0.001). Participants from the AHCL group also had significant improvements in HbA1c levels (treatment effect -0.6% [95% CI -0.9, -0.2]; P = 0.005) and in quality of life (QoL) in specific subscales compared with the MDI+BGM group. CONCLUSIONS: People with T1DM naive to CSII and CGM technologies initiating AHCL significantly and safely improved their glycemic control, as well as their QoL and psychological well-being.