Faculty Bibliography

Background/Purpose: APS ACTION is an international Clinical Database and Repository of persistently antiphospholipid antibody (aPL)-positive subjects, collecting demographic, medical history, and aPL data.This study focused on the prevalence of antinuclear antibodies (ANA) in aPL positive patients without a defined concomitant autoimmune disease. The objective of this study was to evaluate potential differences when stratifying patients by ANA, and to better phenotype aPL positive patients.
Method(s): Data from aPL positive patients with or without APS classification criteria were retrieved from the APS ACTION Database. Patients with a diagnosis of systemic lupus erythematosus (SLE) or other connective tissue disease were excluded. Patients were divided in two groups (ANA+ and ANA-), based on ANA status at registry entry. Subsequently, Table 1. Demographic, clinical and serological characteristics of the patients. demographic, clinical (including 1997 ACR SLE classification criteria), and serological data were compared between the two subgroups.
Result(s): 521 aPL-positive patients were included in the study (meanage 52.1+/-13 years, 70% female). Among them, 224 patients were ANA+ and 297 ANA-. Patients characteristics are displayed in Table 1. ANA positivity was significantly associated with previous history of hematologicalmanifestations as a whole, including hemolytic anemia, thrombocytopenia, and leukopenia, (19.3% ANA+ vs. 8.4% ANA-, p < 0.01) and livedo reticularis (15.1% ANA+ vs. 10% ANA-, p < 0.05). A positive association with the number of unexplained fetal deaths beyond 10 weeks of gestation was also noted (p < 0.05), and a trend was observed for lower platelet count, aPL-related nephropathy and arthritis, though these associations were not statistically significant. No significant association was found for extra-criteria manifestations such as haemolytic anemia and history of thrombocytopenia, when considered individually. When sub-analysing the ANA-group, a significant association with any history of arterial thromboses (29.4% ANA+ vs. 38.8% ANA-, p < 0.02) and the number of arterial events was observed (p < 0.01). When evaluating ANA positivity in aPL carriers and primary APS (PAPS) individually, the association between ANA+ and previous hematologic disorder remained significant for both groups, with stronger significance for PAPS patients. In addition, ANA positivity in PAPS patients was significantly associated with livedo reticularis and previous history of small vessel disease (p < 0.05).
Conclusion(s): In this large international cohort, ANA positivity was associated with a higher rate of hematologic manifestations in aPL-positive patients without connective tissue disease. ANA+ patients, especially those with PAPS, showed a tendency toward a higher rate of microvascular manifestations and arthritis. ANA-subjects showed a significantly higher rate of arterial thrombosis, without any other significant association with clinical, serological or demographic data

PURPOSE/OBJECTIVE:Five quality of life (QoL) domains are particularly important to patients with type 2 diabetes (T2D) using basal insulin-sense of physical well-being, sense of safety regarding hypoglycemia, sense of diabetes as burdensome, feelings of freedom and flexibility, and sleep quality. METHODS:An online survey assessed these QoL domains in adult patients with T2D in the USA who had switched from a previous basal insulin to insulin degludec (IDeg): modified versions of the World Health Organization (Five) Well-Being Index (WHO-5), Hypoglycemia Attitudes and Behavior Scale (HABS; confidence and anxiety subscales only), and Diabetes Distress Scale (DDS; emotional burden and regimen-related distress subscales only); three items assessing feelings of freedom and flexibility; and one item assessing sleep quality (hours of restful sleep). Patients rated each item for their previous basal insulin and currently while using IDeg. Correlations between sleep quality and the other QoL scales were also assessed. RESULTS:In total, 152 patients completed the survey and were included in the study sample. Patients reported significantly improved scores while using IDeg on all WHO-5, DDS, HABS, feelings of freedom and flexibility item scores, and total raw/mean subscale scores (P < 0.0001). Patients also reported a significantly greater number of hours of restful sleep [mean (SD) 6.6 (2.0) vs. 5.5 (1.8); P < 0.0001]. Better sleep quality statistically significantly correlated with improved QoL in all other domains assessed. CONCLUSIONS:Treatment with IDeg after switching from a previous basal insulin was associated with statistically significant improvements in all QoL domains assessed.

Purpose/UNASSIGNED:The prevalence of hypoglycemia in patients with diabetes mellitus is likely underreported, particularly with regard to non-severe episodes, and representative estimates require more detailed data than claims or typical electronic health record (EHR) databases provide. This study examines the prevalence of hypoglycemia as identified in a medical transcription database. Patients and Methods/UNASSIGNED:The Amplity Insights database contains medical content dictated by providers detailing patient encounters with health care professionals (HCPs) from across the United States. Natural language processing (NLP) was used to identify episodes of hypoglycemia using both symptom-based and non-symptom-based definitions of hypoglycemic events. This study examined records of 41,688 patients with type 1 diabetes mellitus and 317,399 patients with type 2 diabetes mellitus between January 1, 2016, and April 30, 2018. Results/UNASSIGNED:Using a non-symptom-based definition, the prevalence of hypoglycemia was 18% among patients with T1DM and 8% among patients with T2DM. These estimates show the prevalence of hypoglycemia to be 2- to 9-fold higher than the 1% to 4% prevalence estimates suggested by claims database analyses. Conclusion/UNASSIGNED:In this exploration of a medical transcription database, the prevalence of hypoglycemia was considerably higher than what has been reported via retrospective analyses from claims and EHR databases. This analysis suggests that data sources other than claims and EHR may provide a more in-depth look into discrepancies between the mention of hypoglycemia events during a health care visit and documentation of hypoglycemia in patient records.

Objective: Most acute-care hospitals have transitioned from sliding-scale to basal-bolus insulin therapy to manage hyperglycemia during hospitalization, but there is limited scientific evidence demonstrating better short-term clinical outcomes using the latter approach. The present study sought to determine if using basal-bolus insulin therapy favorably affects these outcomes in noncritical care settings and, if so, whether the magnitude of benefit differs in patients with known vs. newly diagnosed type 2 diabetes. Methods: This natural experiment compared outcomes in 10,120 non-critically ill adults with type 2 diabetes admitted to an academic teaching hospital before and after hospital-wide implementation of a basal-bolus insulin therapy protocol. A group of 30,271 inpatients without diabetes (type 1 or 2) served as controls. Binomial models were used to compare percentages of patients with type 2 diabetes who were transferred to intensive care, experienced complications, or died in the hospital before and after implementation of the protocol, controlling for changes in the control group. The analysis also evaluated before-after changes in length of stay and glucometric indicators. Results: Implementation of basal-bolus therapy did not reduce intensive care use (the primary outcome), complications, mortality, or median length of stay, except in patients with newly diagnosed diabetes (n=234), who experienced a statistically significant decline in the incidence of complications (p<0.01). The absence of effect in previously diagnosed patients was observed in spite of a 32% decline (from 3.7% to 2.5%) in the proportion of inpatient days with hypoglycemia <70 mg/dL (p<0.01) and a 16% decline (from 13.5% to 11.3%) in the proportion of days with hyperglycemia >300 mg/dL (p<0.01). Conclusions: Despite achieving significant reductions in both hyperglycemia and hypoglycemia, use of basal-bolus insulin therapy to manage hyperglycemia in non-critically ill hospitalized patients did not improve short-term clinical outcomes, except in the small minority of patients with newly diagnosed diabetes. The optimal management of hyperglycemia for improving these outcomes has yet to be determined.

BACKGROUND:Gestational diabetes mellitus (GDM) affects approximately 7-17 % of all pregnancies and has been recognized as a significant risk factor to neonatal and maternal health. Postpartum, GDM significantly increases the likelihood of developing type 2 diabetes (T2D). While it is well established that insulin resistance and impaired β-cell function contribute to GDM development, the role of active β-cell loss remains unknown. Differentially methylated circulating free DNA (cfDNA) is a minimally invasive biomarker of β-cell loss in type 1 diabetes mellitus. Here we use cfDNA to examine the levels of β-cell death in women with GDM. METHODS:Second to third-trimester pregnant women with GDM were compared with women with normal pregnancy (PRG), women at postpartum (PP), and non-pregnant (NP) women. Fasting glucose levels, insulin, and C-peptide levels were measured. Serum samples were collected and cfDNA purified and bisulfite treated. Methylation-sensitive probes capable of differentiating between β-cell-derived DNA (demethylated) and non-β-cell-derived DNA (methylated) were used to measure the presence of β-cell loss in the blood. RESULTS:GDM was associated with elevated fasting glucose levels (GDM = 185.9 ± 5.0 mg/dL) and reduced fasting insulin and c-peptide levels when compared with NP group. Interestingly, β-cell derived insulin DNA levels were significantly lower in women with GDM when compared with PRG, NP, and PP groups (demethylation index: PRG = 7.74 × 10(-3) ± 3.09 × 10(-3), GDM = 1.01 × 10(-3) ± 5.86 × 10(-4), p < 0.04; NP = 4.53 × 10(-3) ± 1.62 × 10(-3), PP = 3.24 × 10(-3) ± 1.78 × 10(-3)). CONCLUSIONS:These results demonstrate that β-cell death is reduced in women with GDM. This reduction is associated with impaired insulin production and hyperglycemia, suggesting that β-cell death does not contribute to GDM during the 2nd and 3rd trimester of pregnancy.

Since the beginning of clinical use in the 1970s, hemoglobin A1c (A1c) has become the standard tool for monitoring glycemic control in patients with diabetes. The role of the A1c test was broadened in 2010, when the American Diabetes Association added A1c as a diagnostic criterion for diabetes. Because of hemoglobin A1c's integral role in diagnosis and treatment, it is important to recognize clinical scenarios and interfering factors that yield false results. The purpose of this review is to describe the A1c measurement, outline clinical scenarios or factors that may yield false results, and describe alternative laboratory biomarkers.