Slight autonomic secretion of predominant cortisol

1. Mild autonomic cortisol secretion mainly affects women, associated with risk of hypertension, diabetes

Summary: https://www.acpjournals.org/doi/10.7326/M21-1737

Editorial: https://www.acpjournals.org/doi/10.7326/M21-4526

The URL is put online when the embargo is lifted

A multicenter cross-sectional study of patients with adrenal tumors found that mild autonomic cortisol secretion (MACS) primarily affects women and is associated with an increased frequency and severity of hypertension and type 2 diabetes compared to non-functioning adrenal tumors (NFAT). The study was conducted using the largest prospectively recruited group ever of people with benign adrenal tumors. The results are published in Annals of Internal Medicine.

Adrenal masses, including NFAT and steroid overproducing masses, are detected in approximately 5% of cross-sectional imaging studies and MACS, formerly known as subclinical Cushing syndrome, is the most common hormonal abnormality in benign adrenal tumors. MACS has been reported to be associated with type 2 diabetes and hypertension, but little is known about the precise extent of the impact of MACS on the risk of cardiometabolic disease.

Researchers at the University of Birmingham, Birmingham, UK, studied data from the European Network for the Study of Adrenal Tumors (ENSAT) to determine the cardiometabolic disease burden and steroid excretion in 1,305 people with benign adrenal tumors with or without MACS. The data showed that many more women than men had MACS and that the prevalence of hypertension and diabetes was higher in patients with MACS. Diabetes in these patients more often required insulin therapy to achieve adequate glycemic control. People with MACS carried an increased cardiometabolic load similar to that seen in Cushing’s syndrome, although they did not have the typical features of clinically evident excess cortisol. Based on these results, patients diagnosed with adrenal tumors should have a cardiovascular risk assessment at the time of diagnosis, with particular attention to blood pressure and glucose metabolism.

Media contacts: For an embargoed PDF, please contact Angela Collom at [email protected] To speak with the corresponding author, Wiebke Arlt, MD, DSc, please contact Emma McKinney at [email protected]

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2. Risk-adjusted performance measures may not be an accurate measure of health plan performance.

Summary: https://www.acpjournals.org/doi/10.7326/M21-0881

Editorial: https://www.acpjournals.org/doi/10.7326/M21-4665

The URL is put online when the embargo is lifted

There may be significant residual confusion in the risk adjustment models used to assess the performance of health plans due to differences in patient characteristics between plans. This means that they may not be able to accurately or fairly identify the differences between regimes and should caution policy makers against assuming that the risk adjustment is sufficient to isolate the actual differences in. plan performance. These results are published in Annals of Internal Medicine.

Almost 70% of the Medicaid-eligible population is enrolled in a Medicaid managed care plan. Managed care plans are private health care plans that receive potential monthly capitation payments per registrant and are then responsible for managing and paying for registrant health care. Capitation payments to plans are “risk-adjusted”, which means they differ to reflect differences in the health care needs of patient populations. However, our results suggest that an inadequate adjustment for patient risk penalizes plans (and providers) with patients at higher unobservable risk, prompts plans and providers to engage in risk screening strategies. that are unnecessary and can affect the quality of care, and leads to public reporting. initiatives aimed at potentially misinforming patients.

Researchers at the Yale School of Public Health analyzed data from Louisiana Medicaid to assess the extent to which risk-adjusted health plan performance metrics reflect differences in performance between plans versus differences in characteristics of the plans. patients (residual confusion). The authors reviewed data from 2013 and 2014, when Louisiana Medicaid transitioned to Medicaid managed care. The scans focused on 137,933 eligible residents in the first region to switch to Medicaid-managed care. Of these, 94,972 did not select a shot and were randomly assigned to one of the 5 shots, creating a natural experience. The remaining 42,961 chose from among the same 5 regimes. The authors compared the risk-adjusted performance of each of the 5 plans between the patients who selected a plan and the “baseline” estimates of plan performance based on the patients who were randomly assigned. The authors found that risk-adjusted measures of plan performance based on registrants who chose plans differed significantly from estimates based on randomly assigned registrants, with residual confusion only slightly reduced by adjusting the plan. risk. The authors suggest that the findings should serve as a warning to policymakers who assume that the current risk adjustment is sufficient to measure the performance of schemes (or providers), and the study examines several implications of the findings for how payers and providers assess performance and deploy risk. adjustment of public insurance programs.

Media contacts: For an embargoed PDF, please contact Angela Collom at [email protected] To speak with the corresponding author, Jacob Wallace, PhD, please contact Michael Greenwood at [email protected]

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3. NIH workshop participants find that health and prevention research on populations of Asian, Hawaiian and Pacific Islander descent is urgently needed to eliminate disparities and promote health equity.

Summary: https://www.acpjournals.org/doi/10.7326/M21-3729

The URL is put online when the embargo is lifted

Researchers who have been summoned by the National Heart, Lung, and Blood Institute (NHLBI) and 8 other National Institutes of Health (NIH) institutes say that populations of Asian Americans (AsA), Native Hawaiians and Islanders Pacific (NHPI) should be included in the search. studies aimed at eliminating health disparities, achieving health equity and identifying untapped scientific potential. A summary of the findings of their multidisciplinary workshop, “Identifying Research Opportunities for Asian American, Native Hawaiian, and Pacific Islander Health”, is published in Annals of Internal Medicine.

In 2020, AsA and NHPI made up 7.7% of the total US population, but only made up 2% of the nearly 245,000 participants in the 14 largest cohorts supported by the NHLBI. A review of NIH-funded clinical research found that studies focusing on AsA and NHPI only accounted for 0.17% of the total NIH budget between 1992 and 2018.

To bridge these gaps, the NHLBI / NIH workshop covered 5 areas: 1) socio-cultural, environmental, psychological and lifestyle dimensions; 2) metabolic disorders; 3) cardiovascular and pulmonary diseases; 4) cancer; and 5) cognitive function and healthy aging. Researchers found very limited data for target populations on epidemiology, risk factors, and outcome for most conditions, and most of the existing data is not disaggregated by subgroup. Experts say these findings are particularly important given the enormous heterogeneity among the 40 AsA and NHPI ethnic subgroups with respect to indigeneity, nativity or ancestry, culture, immigration patterns, l acculturation, level of education, income, language and English proficiency all influence health, access to health care and outcomes. To minimize disparities and improve equity, more funding is needed to improve research support and infrastructure for health research in AsA and NHPI populations. And to improve inclusion and inform prevention and intervention efforts, researchers should seek collaborations with community partners, invest in infrastructure support for cohort studies, improve existing data sources to enable disaggregation. data and incorporate new technology for objective measurement.

Media contacts: For an embargoed PDF, please contact Angela Collom at [email protected] To speak with the corresponding author, Ann W. Hsing, PhD, MPH, please contact Julie Greicius at [email protected]

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