A paucity of data exists regarding sex differences in age‐related obesity and insulin resistance, particularly in the preclinical murine model. The purpose of this study was to determine the effects of age and sex on insulin action and body composition in C57BL/6J mice. Aged (AG, 18 months old) male C57BL/6J mice, glucose tolerance was diminished compared to young (YG, 6 months old) male mice (Area Under Curve: 95,103 ± 6818 vs. 64,005 ± 2031, P = 0.002). However, there was no age‐related decline in glucose or insulin tolerance in females. Body composition analysis revealed that AG males had significantly greater body mass (42.2 ± 1.9 vs. 30.0 ± 0.4 g, P < 0.0001), fat mass (18.7 ± 2.0 vs. 3.3 ± 0.4 g, P < 0.0001), body fat (43.0 ± 3.0 vs. 11.0 ± 1.5%, P < 0.0001) than YG males. In AG females, body mass (32.8 ± 1.6 vs. 26.3 ± 0.9 g, P = 0.02) was higher, but fat mass (13.3 ± 2.0 vs. 9.5 ± 1.3 g, P = 0.24) and body fat (37.8 ± 4.8 vs. 35.5 ± 3.8%, P = 0.67) were similar when compared to YG females. AG males had significantly higher body mass (42.2 ± 1.9 vs. 32.8 ± 1.6 g, P = 0.001) and fat mass (18.7 ± 2.0 vs. 13.3 ± 2.0 g, P = 0.04) compared to AG females; however, body fat (43.0 ± 3.0 vs. 37.8 ± 4.8%, P = 0.28) was similar. Six weeks of treatment with MitoQ, a mitochondrial‐targeted antioxidant, did not reverse age‐related obesity in male mice. Surprisingly, obesity and insulin resistance appear to be reversed in the oldest of the old male mice (28 vs. 20 months). Our findings indicate that female mice, unlike males, are protected from age‐related obesity and insulin resistance.
Importance: Racial disparities in COVID-19 outcomes have been amplified during this pandemic and reports on outcomes in African-American (AA) populations, known to have higher rates of cardiovascular (CV) comorbidities, remain limited. Objective: To examine prevalence of comorbidities, rates of hospitalization and survival, and incidence of CV manifestations of COVID-19 in a predominantly AA population in south metropolitan Chicago. Design, Setting, Participants: This was an observational cohort study of COVID-19 patients encountered from March 16 to April 16, 2020 at the University of Chicago. Deidentified data were obtained from an institutional data warehouse. Group comparisons and logistic regression modeling based on baseline demographics, clinical characteristics, laboratory and diagnostic testing was performed. Exposures: COVID-19 was diagnosed by nasopharyngeal swab testing and clinical management was at the discretion of treating physicians. Main Outcomes and Measures: Primary outcomes were hospitalization and in-hospital mortality, and secondary outcomes included incident CV manifestations of COVID-19 in the context of overall cardiology service utilization. Results: During the 30 day study period, 1008 patients tested positive for COVID-19 and 689 had available encounter data. Of these, 596 (87%) were AA and 356 (52%) were hospitalized, of which 319 (90%) were AA. Age > 60 years, tobacco use, BMI >40 kg/m2, diabetes mellitus (DM), insulin use, hypertension, chronic kidney disease, coronary artery disease (CAD), and atrial fibrillation (AF) were more common in hospitalized patients. Age > 60 years, tobacco use, CAD, and AF were associated with greater risk of in-hospital mortality along with several elevated initial laboratory markers including troponin, NT-proBNP, blood urea nitrogen, and ferritin. Despite this, cardiac manifestations of COVID-19 were uncommon, coincident with a 69% decrease in cardiology service utilization. For hospitalized patients, median length of stay was 6.2 days (3.4-11.9 days) and mortality was 13%. AA patients were more commonly hospitalized, but without increased mortality. Conclusions and Relevance: In this AA-predominant experience from south metropolitan Chicago, CV comorbidities and chronic diseases were highly prevalent and associated with increased hospitalization and mortality. Insulin-requiring DM and CKD emerged as novel predictors for hospitalization. Despite the highest rate of comorbidities reported to date, CV manifestations of COVID-19 and mortality were relatively low. The unexpectedly low rate of mortality merits further study.
Introduction: Patients with coronavirus disease 2019 (COVID-19) can develop rapidly progressive respiratory failure. Ventilation strategies during the COVID-19 pandemic seek to minimize patient mortality. In this study we examine associations between the availability of emergency department (ED)-initiated high-flow nasal cannula (HFNC) for patients presenting with COVID-19 respiratory distress and outcomes, including rates of endotracheal intubation (ETT), mortality, and hospital length of stay. Methods: We performed a retrospective, non-concurrent cohort study of patients with COVID-19 respiratory distress presenting to the ED who required HFNC or ETT in the ED or within 24 hours following ED departure. Comparisons were made between patients presenting before and after the introduction of an ED-HFNC protocol. Results: Use of HFNC was associated with a reduced rate of ETT in the ED (46.4% vs 26.3%, P <0.001) and decreased the cumulative proportion of patients who required ETT within 24 hours of ED departure (85.7% vs 32.6%, P <0.001) or during their entire hospitalization (89.3% vs 48.4%, P <0.001). Using HFNC was also associated with a trend toward increased survival to hospital discharge; however, this was not statistically significant (50.0% vs 68.4%, P = 0.115). There was no impact on intensive care unit or hospital length of stay. Demographics, comorbidities, and illness severity were similar in both cohorts. Conclusions: The institution of an ED-HFNC protocol for patients with COVID-19 respiratory distress was associated with reductions in the rate of ETT. Early initiation of HFNC is a promising strategy for avoiding ETT and improving outcomes in patients with COVID-19
BACKGROUND: Functional capacity assessment plays a core role in the preoperative evaluation. The Duke Activity Status Index (DASI) and the 6-minute walk test (6MWT) are 2 methods that have demonstrated the ability to evaluate functional capacity and predict perioperative outcomes. Smartphones offer a novel method to facilitate functional capacity assessment as they can easily administer a survey and accelerometers can track patient activity during a 6MWT. We developed a smartphone application to administer a 6MWT and DASI survey and performed a pilot study to evaluate the accuracy of a smartphone-based functional capacity tool in our Anesthesia and Perioperative Medicine Clinic. METHODS: Using the Apple ResearchKit software platform, we developed an application that administers a DASI survey and 6MWT on an iOS smartphone. The DASI was presented to the patient 1 question on the screen at a time and the application calculated the DASI score and estimated peak oxygen uptake (Vo 2). The 6MWT used the CMPedometer class from Apple’s core motion facility to retrieve accelerometer data collected from the device’s motion coprocessor to estimate steps walked. Smartphone estimated steps were compared to a research-grade pedometer using the intraclass correlation coefficient (ICC). Distance walked was directly measured during the 6MWT and we performed a multivariable linear regression with biometric variables to create a distance estimation algorithm to estimate distance walked from the number of steps recorded by the application. RESULTS: Seventy-eight patients were enrolled in the study and completed the protocol. Steps measured by the smartphone application as compared to the pedometer demonstrated moderate agreement with an ICC (95% CI) of 0.87 (0.79–0.92; P = .0001). The variables in the distance estimation algorithm included (β coefficient [slope], 95% CI) steps walked (0.43, 0.29–0.57; P < .001), stride length (0.38, 0.22–0.53; P < .001), age in years (−1.90, −3.06 to −0.75; P = .002), and body mass index (−2.59, −5.13 to −0.06; P = .045). The overall model fit was R 2 = 0.72, which indicates a moderate level of goodness of fit and explains 72% of the variation of distance walked during a 6MWT. CONCLUSIONS: Our pilot study demonstrated that a smartphone-based functional capacity assessment is feasible using the DASI and 6MWT. The DASI was easily completed by patients and the application clearly presented the results of the DASI to providers. Our application measured steps walked during a 6MWT moderately well in a preoperative patient population; however, future studies are needed to improve the smartphone application’s step-counting accuracy and distance estimation algorithm.
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.