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Medical research continues to progress in its ability to identify treatments and characteristics associated with benefits and adverse outcomes. The principal engine for the evaluation of treatment efficacy is the randomized controlled trial (RCT). Due to the cost and other considerations, RCTs cannot address all clinically important decisions. Observational research often is used to address issues not addressed or not addressable by RCTs. This article provides an overview of the benefits and limitations of observational research to serve as a guide to the interpretation of this category of research designs in diabetes investigations. The potential for bias is higher in observational research but there are design and analysis features that can address these concerns although not completely eliminate them. Pharmacoepidemiologic research may provide important information regarding relative safety and effectiveness of diabetes pharmaceuticals. Such research must effectively address the important issue of confounding by indication in order to produce clinically meaningful results. Other methods such as instrumental variable analysis are being employed to enable stronger causal inference but these methods also require fulfillment of several key assumptions that may or may not be realistic. Nearly all clinical decisions involve probabilistic reasoning and confronting uncertainly, so a realistic goal for observational research may not be the high standard set by RCTs but instead the level of certainty needed to influence a diagnostic or treatment decision.

Although overweight/obesity is a major risk factor for the development of type 2 diabetes mellitus, there is increasing evidence that overweight or obese patients with type 2 diabetes mellitus experience lower mortality compared with patients of normal weight. This paradoxical finding, known as the \"obesity paradox,\" occurs in other chronic diseases, and in type 2 diabetes mellitus is particularly perplexing given that lifestyle intervention with one goal being weight reduction is an important feature of the management of this condition. We summarize in this review the findings from clinical and epidemiologic studies that have investigated the association between overweight and obesity (usually assessed using body mass index [BMI]) and mortality in type 2 diabetes mellitus and discuss potential causes of the obesity paradox. We conclude that most studies show evidence of an obesity paradox, but important conflicting findings still exist. We also evaluate if potential bias might explain the obesity paradox in diabetes, including, for example, the presence of confounding factors, measurement error due to use of BMI as an index of obesity, and reverse causation.

To examine public health impacts of Long COVID on long-term hyperglycemia and metabolic health. We conducted a retrospective cohort study using US Veterans Health Administration electronic health records data to examine associations of Long COVID documentation (International Statistical Classification of Diseases, Tenth Revision code U09.9) with clinical outcomes (number of primary care visits, receipt of new classes of glucose-lowering medications, weight change, hemoglobin A1c, initiation of insulin, initiation of dialysis, hospitalization, and mortality) among U.S. Veterans with diabetes (1 October 2021-1 October 2023; n = 1,896,080). Veterans were 69.7 years old on average at cohort entry, 6% female, and 1% had U09.9 documentation. Compared to Veterans without U09.9, those with U09.9 had 39% more primary care visits per year after the index date (incidence rate ratio [IRR] 1.36, 95%CI 1.36; 1.37), 21% more glucose-lowering medication classes added per year (IRR 1.21, 95%CI 1.18; 1.24), a 0.62 kg greater weight gain (95%CI 0.52; 0.72), a 0.10-point lower mean HbA1c (95%CI -0.12; -0.08), a 43% greater odds of starting insulin (odds ratio [OR] 1.43, 95%CI 1.32; 1.54), a 34% greater odds of starting dialysis (OR 1.34, 95%CI 1.11; 1.62), a 102% greater odds of VA hospitalization (OR 2.02, 95%CI 1.95; 2.09), and a 13% lower odds of mortality (OR 0.87, 95%CI 0.83; 0.91). In Veterans with diabetes, Long COVID documentation was associated with greater medication use, odds of starting dialysis, and odds of hospitalization, but with lower odds of mortality. Individuals with Long COVID documentation did not have more weight gain or higher HbA1c, suggesting that adverse effects of Long COVID on medication changes and kidney function in persons with diabetes may be due to other factors. Future studies should examine mechanisms by which Long COVID might contribute to progression of kidney disease and more intensive diabetes treatment.

To examine the impact of SARS-CoV-2 on long-term glycemia. We conducted a retrospective inception cohort study using Veterans Health Administration data (March 1, 2020-May 31, 2022) among individuals with ≥ 1 positive nasal swab for SARS-CoV-2 and individuals with ≥ 1 laboratory test of any type but no positive swab. Two incident diabetes cohorts were defined based on: 1) a computable phenotype using a combination of diagnosis codes, laboratory tests, and receipt of glucose-lowering medications (n = 17,754); and 2) the presence of ≥ 2 HbA1c results ≥ 6.5% (n = 4,768). We fit log-binomial models examining associations of SARS-CoV-2 with diabetes remission, defined as ≥ 2 HbA1c measurements < 6.5% ≥ 90 days apart after cessation of any glucose-lowering medications. To help equalize laboratory surveillance of glycemia, we conducted a subgroup analysis among non-hospitalized participants. In cohorts 1 and 2 respectively, 25% and 29% had ≥ 1 positive test for SARS-CoV-2 prior to enrollment, and 21% and 11% had remission. SARS-CoV-2 was associated with a higher chance of remission by both definitions (1: RR 1.22 [95%CI 1.14-1.29]; 2: RR 1.27 [95%CI 1.07-1.50]) over an average 503 (±202) and 494 (±184) days. The association was attenuated among non-hospitalized participants (1: RR 1.11 [1.04-1.20]; 2: R: 1.17 [95%CI 0.97-1.42]). Diabetes remission was more common in Veterans with new-onset diabetes after SARS-CoV-2. In non-hospitalized participants, who were likely to have more similar laboratory surveillance, the association was diminished. Differences in surveillance or transient hyperglycemia may explain the observed association.

We examined whether key sociodemographic and clinical risk factors for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and mortality changed over time in a population-based cohort study. In a cohort of 9,127,673 persons enrolled in the United States Veterans Affairs (VA) healthcare system, we evaluated the independent associations of sociodemographic and clinical characteristics with SARS-CoV-2 infection (n = 216,046), SARS-CoV-2-related mortality (n = 10,230), and case fatality at monthly intervals between February 1, 2020 and March 31, 2021. VA enrollees had a mean age of 61 years (SD 17.7) and were predominantly male (90.9%) and White (64.5%), with 14.6% of Black race and 6.3% of Hispanic ethnicity. Black (versus White) race was strongly associated with SARS-CoV-2 infection (adjusted odds ratio [AOR] 5.10, [95% CI 4.65 to 5.59], p-value <0.001), mortality (AOR 3.85 [95% CI 3.30 to 4.50], p-value < 0.001), and case fatality (AOR 2.56, 95% CI 2.23 to 2.93, p-value < 0.001) in February to March 2020, but these associations were attenuated and not statistically significant by November 2020 for infection (AOR 1.03 [95% CI 1.00 to 1.07] p-value = 0.05) and mortality (AOR 1.08 [95% CI 0.96 to 1.20], p-value = 0.21) and were reversed for case fatality (AOR 0.86, 95% CI 0.78 to 0.95, p-value = 0.005). American Indian/Alaska Native (AI/AN versus White) race was associated with higher risk of SARS-CoV-2 infection in April and May 2020; this association declined over time and reversed by March 2021 (AOR 0.66 [95% CI 0.51 to 0.85] p-value = 0.004). Hispanic (versus non-Hispanic) ethnicity was associated with higher risk of SARS-CoV-2 infection and mortality during almost every time period, with no evidence of attenuation over time. Urban (versus rural) residence was associated with higher risk of infection (AOR 2.02, [95% CI 1.83 to 2.22], p-value < 0.001), mortality (AOR 2.48 [95% CI 2.08 to 2.96], p-value < 0.001), and case fatality (AOR 2.24, 95% CI 1.93 to 2.60, p-value < 0.001) in February to April 2020, but these associations attenuated over time and reversed by September 2020 (AOR 0.85, 95% CI 0.81 to 0.89, p-value < 0.001 for infection, AOR 0.72, 95% CI 0.62 to 0.83, p-value < 0.001 for mortality and AOR 0.81, 95% CI 0.71 to 0.93, p-value = 0.006 for case fatality). Throughout the observation period, high comorbidity burden, younger age, and obesity were consistently associated with infection, while high comorbidity burden, older age, and male sex were consistently associated with mortality. Limitations of the study include that changes over time in the associations of some risk factors may be affected by changes in the likelihood of testing for SARS-CoV-2 according to those risk factors; also, study results apply directly to VA enrollees who are predominantly male and have comprehensive healthcare and need to be confirmed in other populations. In this study, we found that strongly positive associations of Black and AI/AN (versus White) race and urban (versus rural) residence with SARS-CoV-2 infection, mortality, and case fatality observed early in the pandemic were ameliorated or reversed by March 2021.

OBJECTIVE: Insulin resistance is a suspected causative factor in a wide variety of diseases. We aimed to determine whether insulin resistance, estimated by the homeostasis model assessment for insulin resistance (HOMA-IR), is associated with all-cause or disease-specific mortality among nondiabetic persons in the U.S. RESEARCH DESIGN AND METHODS: We determined the association between HOMA-IR and death certificate-based mortality among 5,511 nondiabetic, adult participants of the third U.S. National Health and Nutrition Examination Survey (1988-1994) during up to 12 years of follow-up, after adjustment for potential confounders (age, sex, BMI, waist-to-hip ratio, alcohol consumption, race/ethnicity, educational attainment, smoking status, physical activity, C-reactive protein, systolic and diastolic blood pressure, plasma total and HDL cholesterol, and triglycerides). RESULTS: HOMA-IR was significantly associated with all-cause mortality (adjusted hazard ratio 1.16 [95% CI 1.01-1.3], comparing successive quartiles of HOMA-IR in a linear model and 1.64 [1.1-2.5], comparing the top [HOMA-IR >2.8] to the bottom [HOMA-IR [less-than or equal to]1.4] quartile). HOMA-IR was significantly associated with all-cause mortality only in subjects with BMI <25.2 kg/m² (the median value) but not in subjects with BMI ≥25.2 kg/m². Subjects in the second, third, and fourth quartile of HOMA-IR appeared to have higher cardiovascular mortality than subjects in the lowest quartile of HOMA-IR. HOMA-IR was not associated with cancer-related mortality. CONCLUSIONS: HOMA-IR is associated with all-cause mortality in the nondiabetic U.S. population but only among persons with normal BMI. HOMA-IR is a readily available measure that can be used in the future to predict mortality in clinical or epidemiological settings.

Up-to-date estimates of COVID-19 vaccine effectiveness (VE) are needed to inform COVID-19 vaccination strategies and recommendations. This target trial emulation study aimed to estimate the long-term vaccine effectiveness (VE) of the 2024-2025 COVID-19 vaccines targeting the KP.2 Omicron variant within the Veterans Health Administration. The study population (90.9% male, mean age 70.7 years) included 538,631 pairs of vaccinated (i.e., received the KP.2 COVID-19 vaccine) and matched unvaccinated (i.e., did not receive the KP.2 COVID-19 vaccine) persons enrolled from August 2024 to January 2025. Over a mean follow-up of 172 days (range 97-232) extending to April 12, 2025, VE was low against laboratory-diagnosed SARS-CoV-2 infection (16.60%, 95% confidence interval [CI], 11.92-21.44), SARS-CoV-2-associated emergency department/urgent care (ED/UC) visit (21.05%, 95% CI, 14.22-27.21), SARS-CoV-2-associated hospitalization (19.53%, 95% CI 6.56-30.10) and much higher against SARS-CoV-2-associated death (65.53%, 95% CI 27.79-83.37). VE declined from 60 to 90 to 120 days against infection (31.28%, 25.81%, 22.44% respectively), ED/UC visit (34.40%, 29.19%, 25.71% respectively), hospitalization (37.39%, 28.98%, 22.52% respectively) and death (75.02%, 71.02%, 63.08% respectively). In conclusion, COVID-19 vaccines targeting the KP.2 variant used in the 2024-2025 season offered high protection against death and modest protection against infection, ED/UC visits or hospitalization, and VE declined over time. Vaccinations against the SARS-CoV-2 KP.2 variant were introduced for the 2024-25 season in the United States. Here, the authors investigate the effectiveness of these vaccines up to April 2025 through a target trial emulation study using electronic health record data.

Obstructive sleep apnea (OSA) and diabetes has been known to be closely related to each other and both diseases impact highly on the public health. There are many evidence of reports that OSA is associated with diabetes with a bidirectional correlation. A possible causal mechanism of OSA to diabetes is intermittent hypoxemia and diabetes to OSA is microvascular complication. However, OSA and diabetes have a high prevalence rate in public and shares the common overlap characteristic and risk factors such as age, obesity, and metabolic syndrome that make it difficult to establish the exact pathophysiologic mechanism between them. In addition, studies demonstrating that treatment of OSA may help prevent diabetes or improve glycemic control have not shown convincing result but have become a great field of interest research. This review outlines the bidirectional correlation between OSA and diabetes and explore the pathophysiologic mechanisms by approaching their basic etiologies.

Background To compare cause-specific mortality between an occupational cohort of U.S. service members and veterans and the general civilian adult population. Methods Dates and cause of death of deceased Millennium Cohort Study participants from 2001 to 2018 were extracted from federal and military databases. Standardized mortality ratios (SMRs) were calculated for cause-specific mortality compared with the general population overall and by sex and deployment history. Results Among 201,618 participants, 3,017 (1.5%) had a recorded cause of death by December 31, 2018. Compared with the U.S. general population, deaths due to natural causes (SMR = 0.36; 95% CI: 0.34–0.38), accidents (SMR = 0.47; 95% CI: 0.44–0.51), and homicides (SMR = 0.22; 95% CI: 0.17–0.29) were lower among service members and veterans. When stratified by sex, deaths by suicide overall were higher for military women (SMR = 1.65, 95% CI: 1.31–2.05) compared with women in the U.S. general population but not for men (SMR = 0.96, 95% CI 0.87–1.05). Deaths from suicide by firearms were elevated for both military women (SMR = 2.83, 95% CI: 2.04–3.82) and men (SMR = 1.33, 95% CI: 1.18–1.49) compared to the U.S. general population. Conclusions Service members and veterans had lower overall mortality but higher mortality attributed to suicide by firearms compared with the U.S. general population. Military women specifically had higher mortality rates from suicide overall. These findings warrant increased attention to reducing suicide deaths in military populations.

OBJECTIVE:--We sought to determine whether an oral disposition index (DIO) predicts the development of diabetes over a 10-year period. First, we assessed the validity of the DIO by demonstrating that a hyperbolic relationship exists between oral indexes of insulin sensitivity and β-cell function. RESEARCH DESIGN AND METHODS--A total of 613 Japanese-American subjects (322 men and 291 women) underwent a 75-g oral glucose tolerance test (OGTT) at baseline, 5 years, and 10 years. Insulin sensitivity was estimated as 1/fasting insulin or homeostasis model assessment of insulin sensitivity (HOMA-S). Insulin response was estimated as the change in insulin divided by change in glucose from 0 to 30 min (ΔI₀₋₃₀/ΔG₀₋₃₀). RESULTS:--ΔI₀₋₃₀/ΔG₀₋₃₀ demonstrated a curvilinear relationship with 1/fasting insulin and HOMA-S with a left and downward shift as glucose tolerance deteriorated. The confidence limits for the slope of the loge-transformed estimates included -1 for ΔI₀₋₃₀/ΔG₀₋₃₀ versus 1/fasting insulin for all glucose tolerance groups, consistent with a hyperbolic relationship. When HOMA-S was used as the insulin sensitivity measure, the confidence limits for the slope included -1 only for subjects with normal glucose tolerance (NGT) or impaired fasting glucose (IFG)/impaired glucose tolerance (IGT) but not diabetes. On the basis of this hyperbolic relationship, the product of ΔI₀₋₃₀/ΔG₀₋₃₀ and 1/fasting insulin was calculated (DIO) and decreased from NGT to IFG/IGT to diabetes (P < 0.001). Among nondiabetic subjects at baseline, baseline DIO predicted cumulative diabetes at 10 years (P < 0.001) independent of age, sex, BMI, family history of diabetes, and baseline fasting and 2-h glucose concentrations. CONCLUSIONS:--The DIO provides a measure of β-cell function adjusted for insulin sensitivity and is predictive of development of diabetes over 10 years.