Lenalidomide is an antiangiogenic drug associated with hypothyroidism. We describe a case-series of lenalidomide use in hematological cancers and the prevalence of thyroid abnormalities. We reviewed medical records of patients treated with lenalidomide at a single center form 2005 to 2010 and extracted demographic, clinical, and laboratory data. Of 170 patients with confirmed lenalidomide use (age 64.9 ± 15 years), 148 were treated for multiple myeloma and 6% had thyroid abnormalities attributable only to lenalidomide. In patients with a previous diagnosis of thyroid dysfunction, the addition of lenalidomide therapy was associated with a higher incidence of subsequent TFTF abnormality (17%) as compared to patients with no previous diagnosis of thyroid dysfunction (6%) (P=0.0001). Many patients (44%) with pre-existing disease and a change in thyroid function before or while on lenalidomide had no further follow-up of their thyroid abnormalities, Of 20 patients who did not undergo any thyroid finction testing either before starting or while on lenalidomide for a median of 9.4 months ( ± 6.5), 35% developed new symptoms compatible with hypothyroidism, including worsened fating, constipation or cold intolerance. Symptoms of thyroid dysfunction overlap with side effects of lenalidomide. Thyroid hormone levele are not regularly evaluated in patients on lenalidomide. While on this treatment, thyroid abnormalities can occur in patients with no previous diagnoses and in patients with pre-existing abnormalities. Because symptoms of thyroid dysfunction could be alleviated by appropriate treatment, thyroid function should be evaluated during the course of lenalidomide to improve patients quality of life. Am. J. Hematol. 86:467-470, 2011. V
Background: Hybrid closed-loop (HCL) insulin pump therapy (Medtronic 670G) is an emerging technology that is growing in use worldwide. Initial clinical trials demonstrated the effectiveness of HCL in reducing hypoglycemia and improving glucose control; however, these subjects were intensely monitored and supervised. There has been concern regarding the ability of patients to remain in auto mode. We aimed to assess HCL when used in a typical outpatient endocrine clinic. Methods: We initially analyzed data from 80 individuals with type 1 diabetes managed in an endocrine clinic by a single certified diabetes educator (CDE). We then included our other providers and had 230 subjects by the end of the study. Patients were either transitioned from traditional insulin pump or multiple daily insulin injection therapy (MDI) to HCL. Patients initiated to HCL pump therapy from July 2017 through February 2020 were studied. Endpoints of change in time in hypoglycemic/hyperglycemic range and time in target range were analyzed. The primary outcome was a change in percent time in the target range during manual mode compared with auto mode. Results: There was an 18.2% increase in average time in target range when comparing manual mode to auto mode (59.3% vs 70.1%, P < .0001). Average time in hyperglycemic range was significantly reduced by 26.7% (39.0% vs 28.6%, P < .0001) but without increasing average time in hypoglycemic range (1.7% vs 1.3%, P = 0.95). Conclusions: HCL was effective in reducing hyperglycemia and increasing time in the target range but did not increase hypoglycemia. These data suggest HCL will improve the metrics of glucose control.
Diabetic patients who underwent LVAD implantation had a higher risk of death compared with nondiabetic patients. Adverse event rates did not differ between the two groups. Finally, the degree of glycemic control in diabetic patients before LVAD was not found to influence mortality.
This article reviews the current diabetes technology landscape and how recent advancements are being used to help overcome barriers in the management of diabetes. The authors offer case examples of how digital tools and platforms can facilitate diabetes care via telehealth and remote patient monitoring for individuals in special populations. They also provide tips to ensure success in implementing diabetes technology to provide the best possible care for people with diabetes in outpatient settings.
Background Multidomain lifestyle interventions may slow aging as captured by deficit accumulation frailty indices; however, it is unknown whether benefits extend beyond intervention delivery. Methods We developed a deficit accumulation frailty index (FI-E) to span the ten years that the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial delivered interventions (a multidomain lifestyle intervention focused on caloric restriction, increased physical activity, and diet compared to a control condition) and to extend across an additional eight years post-delivery. The study cohort included 5,145 individuals, aged 45-76 years at enrollment, who had type 2 diabetes and either obesity or overweight. Results Overall, FI-E scores were relatively lower among lifestyle participants throughout follow-up, averaging 0.0130 [95% CI: 0.0104, 0.0156] (p<0.001) less across the 18 years. During years 1-8, the mean relative difference between control and lifestyle participants’ FI-E scores was 0.0139 [0.0115, 0.0163], approximately 10% of the baseline level. During years 9-18, this average difference was 0.0107 [0.0066, 0.0148]. Benefits were comparable for individuals grouped by baseline age and body mass index and sex but were not evident for those entering the trial with a history of cardiovascular disease. Conclusions Multidomain lifestyle intervention may slow biological aging long-term, as captured by a deficit accumulation frailty index.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.