1) Develop a Patient and Stakeholder Advisory Committee (PASAC) to design, evaluate, and revise a prediabetes shared decision aid, and 2) evaluate the feasibility and experience of implementing the tool within primary care practice.

A prediabetes decision aid (double-sided infographic with decision questions) was created by a PASAC that included patients, primary care clinicians, diabetes educators, endocrinologists, and pharmacists. Five clinicians within 3 primary care practices tested the prediabetes tool with 50 adult patients with prediabetes. Patients completed 2 surveys immediately after the office visit and 6 weeks later. Clinicians and PASAC members completed a postintervention survey.

The prediabetes shared decision aid was created through a deliberative process over 3 PASAC meetings. Ninety-six percent of patients felt the tool prepared them to decide on a diabetes prevention plan, and 100% of clinicians would use the tool again and felt the tool did not extend visit length.

It was feasible to cocreate a prediabetes shared decision aid within a PASAC and implement the tool within a primary care setting. Patients and clinicians reported a prediabetes discussion, which may mitigate rates of progression to diabetes and associated complications. Future research should evaluate which of the intervention components most effectively promotes discussion of prediabetes within a primary care setting.

Research coordinators interviewed 33 patients aged 25 to 65 diagnosed with type 2 diabetes mellitus or prediabetes at medical centers in Augusta, Georgia, and Las Vegas, Nevada. Retrospective interview technique and turning point analysis was employed to plot health or diabetes management changes from diagnosis up to the present day. The constant comparative method was used to conduct a thematic analysis. Axial coding identified properties characterizing each turning point.

Patients reported 5 interrelated turning points occurring at various times after diagnosis: 1) gaining knowledge, either through patients own research and/or a health care class; 2) making lifestyle changes, including exercising and healthier eating; 3) encountering a life-changing event/transition, including events that derailed healthy behavior, motivated health behavior, and removed barriers to enacting healthy behavior; 4) receiving social support, either through holding patients accountable or encouraging them to enact healthy behavior; and 5) interacting with clinicians, such as medication changes or behavior changes critical to disease management.

These turning points provide specific moments throughout diabetes care in which family physicians can effectively partner with patients. By prompting, facilitating, or attending to these turning points, family physicians can partner with patients throughout diabetes care.

Our historic control study design included 2 years of preintervention data, then 6 months of physician and staff training in prenatal weight gain counseling in accordance with 2009 Institute of Medicine guidelines, and finally, 2 more years of data collection for postintervention outcomes. Seven family medicine residency clinics monitored 1571 continuity prenatal cases. Counseling recommendations were noted and the following outcomes were analyzed: gestational age, birth weight, route of delivery, and the incidences of hypertension and gestational diabetes. Multiple logistic regression was used to control for demographic variables and body mass index at enrollment.

Institute of Medicine congruent counseling increased from 10% to 63% (P < .01). Excess weight gain decreased from 46.4% to 41.5% (adjusted odds ratio [AOR] = 0.85; 95% CI, 0.63–1.16; P = .10). Gestational diabetes decreased significantly from 11.5% to 7.3% (P = .008). The difference remained statistically significant even after adjusting for prepregnancy obesity and other clinical and demographic characteristics (AOR = 0.54; 95% CI, 0.32–0.91; P = .02). Differences in gestational age, birth weight, hypertension, primary cesarean, and shoulder dystocia were not statistically significant.

Improved weight gain counseling of prenatal patients by physicians did reduce the pregnancy complication of gestational diabetes. This occurred even though the trend toward less excess weight gain was not statistically significant.

CV response and distance walked during the 6MWT were assessed in 30 people with type 2 diabetes, matched for age, body composition, physical activity, and estimated aerobic capacity with 34 control subjects (type 2 diabetes group: 16 men, 59.8 ± 8.8 years of age, 33.3 ± 10.9% body fat, physical activity of 7,968 ± 3,236 steps·day^–1, estimated aerobic capacity 31.9 ± 11.1 mLO₂·kg^–1·min^–1; control group: 19 men, 59.3 ± 8.8 years of age, 32.7 ± 8.5% body fat, physical activity 8,228 ± 2,941 steps·day^–1, estimated aerobic capacity 34.9 ± 15.4 mLO₂·kg^–1·min^–1).

People with type 2 diabetes walked a similar distance (590 ± 75 vs. 605 ± 69 m; P = 0.458) compared with control subjects during the 6MWT and had similar ratings of perceived exertion (RPE) after the 6MWT (4.19 ± 1.56 vs. 3.65 ± 1.54, P = 0.147). However, at the end of the 6MWT, people with type 2 diabetes had a higher heart rate (108 ± 23 vs. 95 ± 18 beats·min^–1; P = 0.048), systolic blood pressure (169 ± 26 vs. 147 ± 22 mmHg, P = 0.003), and rate-pressure product (18,762 ± 5,936 vs. 14,252 ± 4,330, P = 0.009) than control subjects.

Although people with type 2 diabetes had similar performance and RPE during the 6MWT compared with control subjects, the CV response was greater for people with type 2 diabetes, indicating greater cardiac effort for similar perceived effort and performance of 6MWT. These data suggest that observation and prescription of exercise intensity should include both perceived effort and CV response.

An anonymous ICT survey (examining access and use of mobile phones, computers, tablets, and the Internet and attitudes toward e-mail, Web-based consultations, and online peer-support) was conducted at the Royal Prince Alfred Hospital Diabetes Centre in Sydney, Australia. Survey deployment occurred during 4-month periods in 2012 and 2017. Respondents were stratified by current age (<40 or ≥40 years).

A total of 614 unselected patients (20% with type 1 diabetes, 55% with type 2 diabetes, 13% with gestational diabetes mellitus, and 12% with an undisclosed type of diabetes) completed the survey. Access to ICT increased from 89% in 2012 to 97% in 2017. The most commonly owned device was a mobile phone (87% ownership in 2017). Increase in mobile Internet usage in the <40 years of age subgroup was significant (P = 0.04). Significant increases in Internet access and smartphone feature use were observed in patients aged ≥40 years (P ≤0.001 for all). Overall use of short message service (SMS, or text messaging) was high (90 and 80% for ages <40 and ≥40 years, respectively). Use of digital applications was low, even among the young (45% in 2017). Comfort with online consultations (40%) and support groups (32%) was also low.

Access to and acceptance and use of ICT is high, especially in those <40 years of age; however, the greatest increases were seen in those aged ≥40 years. High penetrance of mobile phones and text messaging in all age-groups would suggest that innovations involving an SMS platform have the greatest potential to enhance diabetes care.

All patients meeting inclusion criteria on the general medicine service of a tertiary care hospital were invited to participate. Subjects were asked about their access to dental care and perceptions of their oral health. A dental hygienist conducted examinations, including decayed, missing, and filled teeth (DMFT) and periodontal screening and recording (PSR) indices on a subset of subjects.

The 105 subjects had a mean age of 69 ± 12 years and a median A1C of 7.5 ± 2.1%. Rates of comorbidity and polypharmacy were high. The mean number of DMFT was 23.0 ± 7.2, with 10.1 ± 7.2 missing teeth. Forty- four percent of subjects had a removable prosthesis. Sixty-eight percent had a PSR index ≥4 in at least one sextant, indicating moderate periodontal disease.

Rates of missing teeth, removable prostheses, and periodonal inflammation were high among hospitalized patients with diabetes, but patients did not perceive their oral health to be poor. Health care providers should be aware of the oral health risks of patients with diabetes during hospitalization, and dentists should consider screening patients with diabetes for recent hospitalization.

We systematically reviewed for baseline sex differences in cardiovascular (CV) risk factors and CV protection therapy in diabetes CVOTs.

Randomized placebo-controlled trials examining the effect of diabetes medications on major adverse cardiovascular events in people ≥18 years of age with type 2 diabetes.

Included trials reported baseline sex-specific CV risks and use of CV protection therapy.

Two reviewers independently abstracted study data.

We included five CVOTs with 46,606 participants. We summarized sex-specific data using mean differences (MDs) and relative risks (RRs) and pooled estimates using random effects meta-analysis. There were fewer women than men in included trials (28.5–35.8% women). Women more often had stroke (RR 1.28; 95% CI 1.09, 1.50), heart failure (RR 1.30; 95% CI 1.21,1.40), and chronic kidney disease (RR 1.33; 95% CI 1.17; 1.51). They less often used statins (RR 0.90; 95% CI 0.86, 0.93), aspirin (RR 0.82; 95% CI 0.71, 0.95), and β-blockers (RR 0.93; 95% CI 0.88, 0.97) and had a higher systolic blood pressure (MD 1.66 mmHg; 95% CI 0.90, 2.41), LDL cholesterol (MD 0.34 mmol/L; 95% CI 0.29, 0.39), and hemoglobin A_1c (MD 0.11%; 95% CI 0.09, 0.14 [1.2 mmol/mol; 1.0, 1.5]) than men.

We could not carry out subgroup analyses due to the small number of studies. Our study is not generalizable to low CV risk groups nor to patients in routine care.

There were baseline sex disparities in diabetes CVOTs. We suggest efforts to recruit women into trials and promote CV management across the sexes.

We performed a meta-analysis of randomized controlled trials (RCTs) comparing CGM with usual care for parameters of glycemic control in both type 1 and type 2 diabetes.

Many electronic databases were searched for articles published from inception until 30 June 2019.

We selected RCTs that assessed both changes in HbA_1c and time in target range (TIR), together with time below range (TBR), time above range (TAR), and glucose variability expressed as coefficient of variation (CV).

Data were extracted from each trial by two investigators.

All results were analyzed by a random effects model to calculate the weighted mean difference (WMD) with the 95% CI. We identified 15 RCTs, lasting 12–36 weeks and involving 2,461 patients. Compared with the usual care (overall data), CGM was associated with modest reduction in HbA_1c (WMD –0.17%, 95% CI –0.29 to –0.06, I² = 96.2%), increase in TIR (WMD 70.74 min, 95% CI 46.73–94.76, I² = 66.3%), and lower TAR, TBR, and CV, with heterogeneity between studies. The increase in TIR was significant and robust independently of diabetes type, method of insulin delivery, and reason for CGM use. In preplanned subgroup analyses, real-time CGM led to the higher improvement in mean HbA_1c (WMD –0.23%, 95% CI –0.36 to –0.10, P < 0.001), TIR (WMD 83.49 min, 95% CI 52.68–114.30, P < 0.001), and TAR, whereas both intermittently scanned CGM and sensor-augmented pump were associated with the greater decline in TBR.

Heterogeneity was high for most of the study outcomes; all studies were sponsored by industry, had short duration, and used an open-label design.

CGM improves glycemic control by expanding TIR and decreasing TBR, TAR, and glucose variability in both type 1 and type 2 diabetes.

An observational evaluation of possible factors related to glycemic management and performance in six male professional cyclists with type 1 diabetes (HbA_1c 6.4 ± 0.6%) during the 2019 Tour of California.

In-ride time spent in euglycemia (3.9–10.0 mmol/L glucose) was 63 ± 11%, with a low percentage of time spent in level 1 (3.0–3.9 mmol/L; 0 ± 1% of time) and level 2 (<3.0 mmol/L; 0 ± 0% of time) hypoglycemia over the 7-day race. Riders spent 25 ± 9% of time in level 1 (10.1–13.9 mmol/L) and 11 ± 9% in level 2 (>13.9 mmol/L) hyperglycemia during races. Bolus insulin use was uncommon during races, despite high carbohydrate intake (76 ± 23 g ⋅ h^–1). Overnight, the riders spent progressively more time in hypoglycemia from day 1 (6 ± 12% in level 1 and 0 ± 0% in level 2) to day 7 (12 ± 12% in level 1 and 2 ± 4% in level 2) (²[1] > 4.78, P < 0.05).

Professional cyclists with type 1 diabetes have excellent in-race glycemia, but significant hypoglycemia during recovery overnight, throughout a 7-day stage race.

In the population-based Maastricht Study (n = 2,107; mean ± SD age 59 ± 8 years; 52% men; normal glucose metabolism [n = 1,226], prediabetes [n = 331], and type 2 diabetes [n = 550, oversampled]), we determined 24-h electrocardiogram-derived HRV in time and frequency domains (individual z-scores, based upon seven and six variables, respectively). We used linear regression with adjustments for age, sex, and major cardiovascular risk factors.

After adjustments, both time and frequency domain HRV were lower in prediabetes and type 2 diabetes as compared with normal glucose metabolism (standardized β [95% CI] for time domain: –0.15 [–0.27; –0.03] and –0.34 [–0.46; –0.22], respectively, P for trend <0.001; for frequency domain: –0.14 [–0.26; –0.02] and –0.31 [–0.43; –0.19], respectively, P for trend <0.001). In addition, 1-SD higher glycated hemoglobin, fasting plasma glucose, and 2-h postload glucose were associated with lower HRV in both domains (time domain: –0.16 [–0.21; –0.12], –0.16 [–0.21; –0.12], and –0.15 [–0.20; –0.10], respectively; frequency domain: –0.14 [–0.19; –0.10], –0.14 [–0.18; –0.09], and –0.13 [–0.18; –0.08], respectively).

Both prediabetes and type 2 diabetes were independently associated with lower HRV. This is further substantiated by independent continuous associations between measures of hyperglycemia and lower HRV. These data strongly suggest that cardiac autonomic dysfunction is already present in prediabetes.

The study monitored 9,969,848 participants who underwent a National Health Insurance Service health checkup in 2009 from baseline to the date of diagnosis of ESRD during a follow-up period of ~8.2 years. Obesity was categorized by World Health Organization recommendations for Asian populations, and glycemic status was categorized into the following five groups: normal, impaired fasting glucose (IFG), newly diagnosed diabetes, diabetes <5 years, and diabetes ≥5 years.

Underweight was associated with a higher risk of ESRD in all participants after adjustment for all covariates. In the groups with IFG, newly diagnosed type 2 diabetes, diabetes duration <5 years, and diabetes ≥5 years, the hazard ratio (HR) of the underweight group increased with worsening glycemic status (HR 1.431 for IFG, 2.114 for newly diagnosed diabetes, 4.351 for diabetes <5 years, and 6.397 for diabetes ≥5 years), using normal weight with normal fasting glucose as a reference. The adjusted HRs for ESRD were also the highest in the sustained underweight group regardless of the presence of type 2 diabetes (HR 1.606 for nondiabetes and 2.14 for diabetes).

Underweight showed more increased HR of ESRD according to glycemic status and diabetes duration in the Korean population. These associations also persisted in the group with sustained BMI during the study period.

The Study of Latinos–Investigation of Neurocognitive Aging (SOL-INCA) is an ancillary study of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). HCHS/SOL is a multisite (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA), probability-sampled (i.e., representative of targeted populations), and prospective cohort study. Between 2016 and 2018, SOL-INCA enrolled diverse Hispanics/Latinos aged ≥50 years (n = 6,377). Global cognitive decline and mild cognitive impairment (MCI) were the primary outcomes.

Prevalent diabetes at visit 1, but not incident diabetes at visit 2, was associated with significantly steeper global cognitive decline (β_GC = –0.16 [95% CI –0.25; –0.07]; P < 0.001), domain-specific cognitive decline, and higher odds of MCI (odds ratio 1.74 [95% CI 1.34; 2.26]; P < 0.001) compared with no diabetes in age- and sex-adjusted models.

Diabetes was associated with cognitive decline and increased MCI prevalence among diverse Hispanics/Latinos, primarily among those with prevalent diabetes at visit 1. Our findings suggest that significant cognitive decline and MCI may be considered additional disease complications of diabetes among diverse middle-aged and older Hispanics/Latinos.

A total of 2,953 Japanese patients with type 2 diabetes and estimated glomerular filtration rate (eGFR) ≥30 mL/min/1.73 m², enrolled in an observational cohort study in 2004, were followed until 2015. On the basis of albuminuria (>30 mg/g creatinine) and reduced eGFR (<60 mL/min/1.73 m²) at baseline, participants were classified into the four DKD phenotypes—no-DKD, albuminuric DKD without reduced eGFR, nonalbuminuric DKD with reduced eGFR, and albuminuric DKD with reduced eGFR—to assess the risks of mortality, cardiovascular disease (CVD), and renal function decline.

During the mean follow-up of 9.7 years, 113 patients died and 263 developed CVD. In nonalbuminuric DKD, the risks of death or CVD were not higher than those in no-DKD (adjusted hazard ratio 1.02 [95% CI 0.66, 1.60]) and the annual decline in eGFR was slower than in other DKD phenotypes. The risks of death or CVD in nonalbuminuric DKD without prior CVD were similar to those in no-DKD without prior CVD, whereas the risks in nonalbuminuric DKD with prior CVD as well as other DKD phenotypes were higher.

Nonalbuminuric DKD did not have a higher risk of mortality, CVD events, or renal function decline than the other DKD phenotypes. In nonalbuminuric DKD, the presence of macrovascular complications may be a main determinant of prognosis rather than the renal phenotype.

This study includes 22,335 individuals with diagnosed diabetes from the 2011 to 2016 Behavioral Risk Factor Surveillance System. It uses a difference-in-differences approach to evaluate the impact of the Medicaid expansion on self-reported access to health care, self-reported diabetes management, and self-reported health status. Additionally, it performs a triple-differences analysis to compare the impact between Medicaid expansion and nonexpansion states considering diabetes rates of the states.

Significant improvements in Medicaid expansion states as compared with non–Medicaid expansion states were evident in self-reported access to health care (0.09 score; P = 0.023), diabetes management (1.91 score; P = 0.001), and health status (0.10 score; P = 0.026). Among states with large populations with diabetes, states that expanded Medicaid reported substantial improvements in these areas in comparison with those that did not expand.

The Medicaid expansion has significant positive effects on self-reported diabetes management. While states with large diabetes populations that expanded Medicaid have experienced substantial improvements in self-reported diabetes management, non–Medicaid expansion states with high diabetes rates may be facing health inequalities. The findings provide policy implications for the diabetes care community and policy makers.

Satiety and Clinical Adiposity—Liraglutide Evidence (SCALE) Insulin was a 56-week, randomized, double-blind, placebo-controlled, multinational, multicenter trial in individuals with overweight or obesity and type 2 diabetes treated with basal insulin and ≤2 oral antidiabetic drugs.

Individuals were randomized to liraglutide 3.0 mg (n = 198) or placebo (n = 198), combined with intensive behavioral therapy (IBT). At 56 weeks, mean weight change was –5.8% for liraglutide 3.0 mg versus –1.5% with placebo (estimated treatment difference –4.3% [95% CI –5.5; –3.2]; P < 0.0001). With liraglutide 3.0 mg, 51.8% of individuals achieved ≥5% weight loss versus 24.0% with placebo (odds ratio 3.41 [95% CI 2.19; 5.31]; P < 0.0001). Liraglutide 3.0 mg was associated with significantly greater reductions in mean HbA_1c and mean daytime glucose values and less need for insulin versus placebo, despite a treat-to-glycemic-target protocol. More hypoglycemic events were observed with placebo than liraglutide 3.0 mg. No new safety or tolerability issues were observed.

In individuals with overweight or obesity and insulin-treated type 2 diabetes, liraglutide 3.0 mg as an adjunct to IBT was superior to placebo regarding weight loss and improved glycemic control despite lower doses of basal insulin and without increases in hypoglycemic events.

In the dal-OUTCOMES trial, 15,871 patients were randomly assigned to treatment with dalcetrapib 600 mg daily or placebo, beginning 4–12 weeks after an acute coronary syndrome. Absence of diabetes at baseline was based on medical history, no use of antihyperglycemic medication, and hemoglobin A_1c and serum glucose levels below diagnostic thresholds. Among these patients, incident diabetes after randomization was defined by any diabetes-related adverse event, new use of antihyperglycemic medication, hemoglobin A_1c ≥6.5%, or a combination of at least two measurements of serum glucose ≥7.0 mmol/L (fasting) or ≥11.1 mmol/L (random).

At baseline, 10,645 patients (67% of the trial cohort) did not have diabetes. During a median follow-up of 30 months, incident diabetes was identified in 403 of 5,326 patients (7.6%) assigned to dalcetrapib and in 516 of 5,319 (9.7%) assigned to placebo, corresponding to absolute risk reduction of 2.1%, hazard ratio of 0.77 (95% CI 0.68–0.88; P < 0.001), and a need to treat 40 patients for 3 years to prevent 1 incident case of diabetes. Considering only those with prediabetes at baseline, the number needed to treat for 3 years to prevent 1 incident case of diabetes was 25. Dalcetrapib also decreased the number of patients who progressed from normoglycemia to prediabetes and increased the number who regressed from diabetes to no diabetes.

In patients with a recent acute coronary syndrome, incident diabetes is common and is reduced substantially by treatment with dalcetrapib.

There were 443 adolescents with type 1 diabetes recruited into the Adolescent Type 1 Diabetes Cardio-Renal Intervention Trial (AdDIT) and exposed to treatment with two oral drugs—an ACE inhibitor and a statin—as well as combinations of both or placebo for 2–4 years. Adherence was assessed every 3 months with the Medication Event Monitoring System (MEMS) and pill count.

Median adherence during the trial was 80.2% (interquartile range 63.6–91.8) based on MEMS and 85.7% (72.4–92.9) for pill count. Adherence based on MEMS and pill count dropped from 92.9% and 96.3%, respectively, at the first visit to 76.3% and 79.0% at the end of the trial. The percentage of study participants with adherence ≥75% declined from 84% to 53%. A good correlation was found between adherence based on MEMS and pill count (r = 0.82, P < 0.001). Factors associated with adherence were age, glycemic control, and country.

We report an overall good adherence to ACE inhibitors and statins during a clinical trial, although there was a clear decline in adherence over time. Older age and suboptimal glycemic control at baseline predicted lower adherence during the trial, and, predictably, reduced adherence was more prevalent in subjects who subsequently dropped out.

We analyzed data from 1 January 2006 through 30 September 2015 from the Nationwide Emergency Department Sample and National Inpatient Sample to characterize ED visits and inpatient admissions with DKA and HHS. We used corresponding year cross-sectional survey data from the National Health Interview Survey to estimate the number of adults ≥18 years with diagnosed diabetes to calculate population-based rates for DKA and HHS in both ED and inpatient settings. Linear trends from 2009 to 2015 were assessed using Joinpoint software.

In 2014, there were a total of 184,255 and 27,532 events for DKA and HHS, respectively. The majority of DKA events occurred in young adults aged 18–44 years (61.7%) and in adults with type 1 diabetes (70.6%), while HHS events were more prominent in middle-aged adults 45–64 years (47.5%) and in adults with type 2 diabetes (88.1%). Approximately 40% of the hyperglycemic events were in lower-income populations. Overall, event rates for DKA significantly increased from 2009 to 2015 in both ED (annual percentage change [APC] 13.5%) and inpatient settings (APC 8.3%). A similar trend was seen for HHS (APC 16.5% in ED and 6.3% in inpatient). The increase was in all age-groups and in both men and women.

Causes of increased rates of hyperglycemic events are unknown. More detailed data are needed to investigate the etiology and determine prevention strategies.

Latent class analysis was conducted on a retrospective cohort of 71,125 T2DM patients. Latent class indicators included patient’s age, ethnicity, comorbidities, and duration of T2DM. Outcomes evaluated included health care use, diabetes-related complications, and 4-year all-cause mortality. The relationship between class membership and outcomes was evaluated with the appropriate regression models.

Five classes of T2DM patients were identified. The prevalence of depression was high among patients in class 3 (younger females with short-to-moderate T2DM duration and high psychiatric and neurological disease burden) and class 5 (older patients with moderate-to-long T2DM duration and high disease burden with end-organ complications). They were the highest tertiary health care users. Class 5 patients had the highest risk of myocardial infarction (hazard ratio [HR] 12.05, 95% CI 10.82–13.42]), end-stage renal disease requiring dialysis initiation (HR 25.81, 95% CI 21.75–30.63), stroke (HR 19.37, 95% CI 16.92–22.17), lower-extremity amputation (HR 12.94, 95% CI 10.90–15.36), and mortality (HR 3.47, 95% CI 3.17–3.80).

T2DM patients can be segmented into classes with differential health care use and outcomes. Depression screening should be considered for the two identified classes of patients.

The study included 4,758 individuals with T1D from the Finnish Diabetic Nephropathy (FinnDiane) Study and 12,710 nondiabetic control individuals. The autoimmune diseases (ADs) were identified by linking the data with the Finnish nationwide health registries from 1970 to 2015.

The median age of the FinnDiane individuals at the end of follow-up in 2015 was 51.4 (interquartile range 42.6–60.1) years, and the median duration of diabetes was 35.5 (26.5–44.0) years. Of individuals with T1D, 22.8% had at least one additional AD, which included 31.6% of women and 14.9% of men. The odds ratios for hypothyroidism, hyperthyroidism, celiac disease, Addison disease, and atrophic gastritis were 3.43 (95% CI 3.09–3.81), 2.98 (2.27–3.90), 4.64 (3.71–5.81), 24.13 (5.60–104.03), and 5.08 (3.15–8.18), respectively, in the individuals with T1D compared with the control individuals. The corresponding ORs for women compared with men were 2.96 (2.53–3.47), 2.83 (1.87–4.28), 1.52 (1.15–2.02), 2.22 (0.83–5.91), and 1.36 (0.77–2.39), respectively, in individuals with T1D. Late onset of T1D and aging increased the risk of hypothyroidism, whereas young age at onset of T1D increased the risk of celiac disease.

This is one of the largest studies quantifying the risk of coexisting AD in adult individuals with T1D in the country with the highest incidence of T1D in the world. The results highlight the importance of continuous screening for other ADs in individuals with T1D.

Using Veterans Health Administration (VHA) electronic medical records from 1 October 2004 to 30 September 2016, we determined risk of subsequent ipsilateral minor and major amputation within 1 year after an initial toe/ray amputation among veterans with diabetes. To assess changes in the annual rate of subsequent amputation over time, we estimated age-adjusted incidence of minor and major subsequent ipsilateral amputation for each year, separately for African Americans (AAs) and whites. Geographic variation was assessed across VHA markets (n = 89) using log-linear Poisson regression models adjusting for age and ethnoracial category.

Among 17,786 individuals who had an initial toe amputation, 34% had another amputation on the same limb within 1 year, including 10% who had a major ipsilateral amputation. Median time to subsequent ipsilateral amputation (minor or major) was 36 days. One-year risk of subsequent major amputation decreased over time, but risk of subsequent minor amputation did not. Risk of subsequent major ipsilateral amputation was higher in AAs than whites. After adjusting for age and ethnoracial category, 1-year risk of major subsequent amputation varied fivefold across VHA markets.

Nearly one-third of individuals require reamputation following an initial toe amputation, although risks of subsequent major ipsilateral amputation have decreased over time. Nevertheless, risks remain particularly high for AAs and vary substantially geographically.

Four cohorts comprising 2,499 patients with diabetes (643 all-cause deaths) were analyzed. The improvement of mortality prediction was addressed using two well-established prediction models, namely, EstimatioN oF mORtality risk in type 2 diabetiC patiEnts (ENFORCE) and Risk Equations for Complications of Type 2 Diabetes (RECODe).

Both hs-CRP and SAP were independently associated with all-cause mortality (hazard ratios [HRs] [95% CIs]: 1.46 [1.34–1.58] [P < 0.001] and 0.82 [0.76–0.89] [P < 0.001], respectively). Patients with SAP ≤33 mg/L were at increased risk of death versus those with SAP >33 mg/L only if hs-CRP was relatively high (>2 mg/L) (HR 1.96 [95% CI 1.52–2.54] [P < 0.001] and 1.20 [0.91–1.57] [P = 0.20] in hs-CRP >2 and ≤2 mg/L subgroups, respectively; hs-CRP-by-SAP strata interaction P < 0.001). The addition of hs-CRP and SAP significantly (all P < 0.05) improved several discrimination and reclassification measures of both ENFORCE and RECODe all-cause mortality prediction models.

In type 2 diabetes, hs-CRP and SAP show opposite and synergic associations with all-cause mortality. The use of both markers, possibly in combination with others yet to be unraveled, might improve the ability to predict the risk of death in the real-life setting.