Severe combined hyperlipidaemia and retinal lipid infiltration in a patient with Type 2 diabetes mellitus

Severe combined hyperlipidaemia has occasionally been associated with infiltration of tissues in addition to arteries and the skin. We report a woman with Type 2 diabetes mellitus (DM) and severe combined hyperlipidaemia who developed retinal lipid infiltration, resulting in blindness. A 61-year-old woman with a 15-year history of Type 2 DM was admitted following a two-week history of progressive visual loss. Examination identified lipid infiltration into the retina. Phenotypically she had severe combined hyperlipidaemia with elevated IDL cholesterol and a broad beta band on lipoprotein electrophoresis, raising the possibility of familial dysbetalipoproteinaemia. However, gene sequencing analysis indicated that the patient was homozygous for the E3/E3 allele of the ApoE gene with no mutations detected in either the coding region or intron-exon boundaries. Her lipid profile improved following dietary therapy and gemfibrozil treatment, but this had little effect on either her fundal appearances or her visual acuity. Type 2 DM plays a vital role both in allowing expression of severe combined hyperlipoproteinaemia, in addition to serving as a risk factor for complications such as tissue infiltration

HbA1c variability in adults with type 1 diabetes on continuous subcutaneous insulin infusion (CSII) therapy compared to multiple daily injection (MDI) treatment

Objective To determine if continuous subcutaneous insulin infusion (CSII) therapy is associated with lower glycated haemoglobin (HbA1c) variability (long-term glycaemic variability; GV) relative to multiple daily injection (MDI) treatment in adults with type 1 diabetes mellitus (T1DM). Design Retrospective audit. Setting and participants Clinic records from 506 adults with T1DM from two tertiary Australian hospitals. Outcome measures Long-term GV was assessed by HbA1c SD and coefficient of variation (CV) in adults on established MDI or CSII therapy, and in a subset changing from MDI to CSII. Results Adults (n=506, (164 CSII), 50% women, mean±SD age 38.0±15.3 years, 17.0±13.7 years diabetes, mean HbA1c 7.8%±1.2% (62±13 mmol/mol) on CSII, 8.0%±1.5% (64±16 mmol/mol) on MDI) were followed for 4.1±3.6 years. CSII use was associated with lower GV (HbA1c SD: CSII vs MDI 0.5%±0.41% (6±6 mmol/mol) vs 0.7%±0.7% (9±8 mmol/mol)) and CV: CSII vs MDI 6.7%±4.6% (10±10 mmol/mol) vs 9.3%±7.3% (14±13 mmol/mol), both p<0.001. Fifty-six adults (73% female, age 36±13 years, 16±13 years diabetes, HbA1c 7.8%±0.8% (62±9 mmol/mol)) transitioned from MDI to CSII. Mean HbA1c fell by 0.4%. GV from 1 year post-CSII commencement decreased significantly, HbA1c SD pre-CSII versus post-CSII 0.7%±0.5% (8±5 mmol/mol) vs 0.4%±0.4% (5±4 mmol/mol); p<0.001, and HbA1c CV 9.2%±5.5% (13±8 mmol/mol) vs 6.1%±3.9% (9±5 mmol/mol); p<0.001. Conclusions In clinical practice with T1DM adults relative to MDI, CSII therapy is associated with lower HbA1c GV

Increased serum kallistatin levels in type 1 diabetes patients with vascular complications

BACKGROUND: Kallistatin, a serpin widely produced throughout the body, has vasodilatory, anti-angiogenic, anti-oxidant, and anti-inflammatory effects. Effects of diabetes and its vascular complications on serum kallistatin levels are unknown. METHODS: Serum kallistatin was quantified by ELISA in a cross-sectional study of 116 Type 1 diabetic patients (including 50 with and 66 without complications) and 29 non-diabetic controls, and related to clinical status and measures of oxidative stress and inflammation. RESULTS: Kallistatin levels (mean(SD)) were increased in diabetic vs. control subjects (12.6(4.2) vs. 10.3(2.8) μg/ml, p = 0.007), and differed between diabetic patients with complications (13.4(4.9) μg/ml), complication-free patients (12.1(3.7) μg/ml), and controls; ANOVA, p = 0.007. Levels were higher in diabetic patients with complications vs. controls, p = 0.01, but did not differ between complication-free diabetic patients and controls, p > 0.05. On univariate analyses, in diabetes, kallistatin correlated with renal dysfunction (cystatin C, r = 0.28, p = 0.004; urinary albumin/creatinine, r = 0.34, p = 0.001; serum creatinine, r = 0.23, p = 0.01; serum urea, r = 0.33, p = 0.001; GFR, r = -0.25, p = 0.009), total cholesterol (r = 0.28, p = 0.004); LDL-cholesterol (r = 0.21, p = 0.03); gamma-glutamyltransferase (GGT) (r = 0.27, p = 0.04), and small artery elasticity, r = -0.23, p = 0.02, but not with HbA1c, other lipids, oxidative stress or inflammation. In diabetes, geometric mean (95%CI) kallistatin levels adjusted for covariates, including renal dysfunction, were higher in those with vs. without hypertension (13.6 (12.3-14.9) vs. 11.8 (10.5-13.0) μg/ml, p = 0.03). Statistically independent determinants of kallistatin levels in diabetes were age, serum urea, total cholesterol, SAE and GGT, adjusted r2 = 0.24, p < 0.00001. CONCLUSIONS: Serum kallistatin levels are increased in Type 1 diabetic patients with microvascular complications and with hypertension, and correlate with renal and vascular dysfunction

Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline.

This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes

Imaging-based clusters in former smokers of the COPD cohort associate with clinical characteristics: the SubPopulations and intermediate outcome measures in COPD study (SPIROMICS)

Background: Quantitative computed tomographic (QCT) imaging-based metrics enable to quantify smoking induced disease alterations and to identify imaging-based clusters for current smokers. We aimed to derive clinically meaningful sub-groups of former smokers using dimensional reduction and clustering methods to develop a new way of COPD phenotyping. Methods: An imaging-based cluster analysis was performed for 406 former smokers with a comprehensive set of imaging metrics including 75 imaging-based metrics. They consisted of structural and functional variables at 10 segmental and 5 lobar locations. The structural variables included lung shape, branching angle, airway-circularity, airway-wall-thickness, airway diameter; the functional variables included regional ventilation, emphysema percentage, functional small airway disease percentage, Jacobian (volume change), anisotropic deformation index (directional preference in volume change), and tissue fractions at inspiration and expiration. Results: We derived four distinct imaging-based clusters as possible phenotypes with the sizes of 100, 80, 141, and 85, respectively. Cluster 1 subjects were asymptomatic and showed relatively normal airway structure and lung function except airway wall thickening and moderate emphysema. Cluster 2 subjects populated with obese females showed an increase of tissue fraction at inspiration, minimal emphysema, and the lowest progression rate of emphysema. Cluster 3 subjects populated with older males showed small airway narrowing and a decreased tissue fraction at expiration, both indicating air-trapping. Cluster 4 subjects populated with lean males were likely to be severe COPD subjects showing the highest progression rate of emphysema. Conclusions: QCT imaging-based metrics for former smokers allow for the derivation of statistically stable clusters associated with unique clinical characteristics. This approach helps better categorization of COPD sub-populations; suggesting possible quantitative structural and functional phenotypes.NIH [U01-HL114494, R01-HL112986, S10-RR022421]; Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [NRF-2017R1D1A1B03034157]; Korea Ministry of Environment (MOE) [RE201806039]; NIH/NHLBI [HHSN268200900013C, HHSN268200900014C, HHSN268200900015C, HHSN268200900016C, HHSN268200900017C, HHSN268200900018C, HHSN268200900019C, HHSN268200900020C]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

LSPM J1112+7626: detection of a 41-day M-dwarf eclipsing binary from the MEarth transit survey

We report the detection of eclipses in LSPM J1112+7626, which we find to be a moderately bright (I_C = 12.14 +/- 0.05) very low-mass binary system with an orbital period of 41.03236 +/- 0.00002 days, and component masses M_1 = 0.395 +/- 0.002 Msol and M_2 = 0.275 +/- 0.001 Msol in an eccentric (e = 0.239 +/- 0.002) orbit. A 65 day out of eclipse modulation of approximately 2% peak-to-peak amplitude is seen in I-band, which is probably due to rotational modulation of photospheric spots on one of the binary components. This paper presents the discovery and characterization of the object, including radial velocities sufficient to determine both component masses to better than 1% precision, and a photometric solution. We find that the sum of the component radii, which is much better-determined than the individual radii, is inflated by 3.8 +0.9 -0.5 % compared to the theoretical model predictions, depending on the age and metallicity assumed. These results demonstrate that the difficulties in reproducing observed M-dwarf eclipsing binary radii with theoretical models are not confined to systems with very short orbital periods. This object promises to be a fruitful testing ground for the hypothesized link between inflated radii in M-dwarfs and activity.Comment: 23 pages, 11 figures, 12 tables, emulateapj format. Accepted for publication in Ap

Consensus Recommendations for the Use of Automated Insulin Delivery (AID) Technologies in Clinical Practice

International audienceThe significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past six years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments