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Objective: Early time-restricted feeding (eTRF) is an intermittent fasting strategy restricting caloric intake to the first 6-8 hours of the day. While previous studies have shown that eTRF improves glycemia, it is unclear if the effect is due to associated weight loss or metabolic benefits of the feeding strategy itself. In this study, we evaluated the weight-independent effects of eTRF on glycemia using multiple CGM-based time in range (TIR) metrics. Methods: We conducted a randomized 7-day isocaloric crossover supervised feeding study comparing eTRF (80% of calories consumed between 8am-1pm) to a usual feeding pattern (UFP, 50% of calories consumed after 4pm) among participants with prediabetes and BMI > 28 kg/m2 in a metabolic ward. Participants were randomized 1:1 to eTRF or UFP for days 1-7, then crossed over to the other arm on days 8-14. Food intake was tailored to meet weight stable caloric needs. Participants also wore blinded Abbott Freestyle Libre CGMs throughout the study period. We evaluated time spent below 70 mg/dL (TBR<70), in 70-140 mg/dL (TIR70-140), and in 140-180 mg/dL (TIR140-180) glucose range per arm. Further, we compared TIR140-180 between arms stratified by time of day: Daytime and Overnight (6am-12am and 12am-6am CGM readings, respectively) using linear mixed effect regression adjusting for type and order of intervention. Results: We analyzed data from 10 participants (age 58 (10) years, 50% female, 80% Black, BMI: 37.3 (5.4) kg/m2, HbA1c: 5.8 (0.1)%). Weight change over the study period was not significant (p=0.08). Compared to UFP, eTRF was associated with a decrease in TIR140-180 overall (3.3%, p=0.01) and during Daytime (4.3%, p=0.02) but not Overnight (0.4%, p=0.73). We observed no significant differences in TBR<70 (p=0.28) and TIR70-140 (p=0.88) between arms. Conclusion: eTRF may improve glucose control in adults with prediabetes and high BMI by reducing daytime excursions into the elevated 140-180 mg/dL range. Disclosure S. Barua: None. J. Bruno: None. S. Nasserifar: None. S. M. Vanegas: None. C. Popp: None. J. M. Walker: None. J. O. Aleman: Advisory Panel; Intellihealth, Consultant; Novo Nordisk, Employee; Veterans Administration, Research Support; NIH - National Institutes of Health, Veterans Administration. Funding Shapiro-Silverberg Foundation; The Rockefeller University; Doris Duke Charitable Foundation; American Heart Association (17-SFRN33490004); National Institutes of Health (K08DK117064); National Heart, Lung, and Blood Institute (5T32HL098129-12)
Purpose: To determine the relationship between obesity and thirty-days readmission, mortality, morbidity, and health care resource utilization in patients who underwent cardiopulmonary resuscitation (CPR) during their hospitalization in the in the United States. Method: A retrospective study was conducted using the AHRQ-HCUP NRD for the year 2014. Adults (≥ 18 years) with a primary diagnosis of CPR (1), along with a secondary diagnosis of obesity were identified using ICD-9 codes as described in the literature (2). The primary outcome was the rate of all-cause readmission within 30 days of discharge. Secondary outcomes were reasons for readmission, readmission mortality rate, morbidity, and resource use. Propensity score (PS) using the 1:1 nearest neighbor matching without replacement was utilized to adjust for confounders (3). Results: 113,394 hospital admissions among adults with a primary and secondary diagnosis of CPR were identified, of which 14.8% were obese. 1:1 PS matching was performed based on demographic and clinical characteristics. The 30-day rate of readmission among obese and non-obese with CPR were 4.94% and 2.82% (p <0.001). The most common readmission for both groups was unspecified sepsis (17.3%). During the index admission for CPR, the length of stay (LOS) among obese and non-obese patients were similar (10.3 vs 9.4 days, p=0.16). However, the total cost for the obese patients was statistically different ($33,232 vs $33,692, p <0.001). Most importantly, obese patients’ in-hospital mortality rate during their index admission was significant higher (58.7% vs 6.72%, p <0.001). Amongst those readmitted, obese patients similarly had a significantly longer LOS than their non-obese counterparts (8.1 vs 4.5 days, p <0.001) and their total cost was more expensive ($19,027 vs $10,572, p <0.001). But, obese patients’ in-hospital mortality rate during their readmission was not significant different (0.34 % vs 0.08%, p =0.09). Obesity (HR 1.77, p <0.02) was an independent predictor associated with higher risks of readmission. Conclusion: In this study, obese patients admitted with CPR have a higher 30 days of readmission rate, total hospital cost, and in-hospital mortality (p <0.02) than non-obese patients.
PURPOSE: To determine the relationship between tobacco smokers and the rate of hospital readmission within 30 days, mortality, morbidity, and health care resource utilization in patients admitted to the hospital in the United States with diabetic ketoacidosis (DKA). METHOD: A retrospective study was conducted using the AHRQ-HCUP National Inpatient Sample for the year 2014. Adults (≥ 18 years) with a principal diagnosis of DKA and a secondary diagnosis of tobacco dependence or active smokers were identified using ICD-9 codes as described in the literature (1). The primary outcome was in-hospital mortality. Secondary outcomes include readmission rate, length of hospital stay (LOS), total hospitalization costs. Propensity score (PS) using the next neighbor method without replacement with 1:1 matching was utilized to adjust for confounders (2). Independent risk factors for readmission were identified using multivariate logistic regression model (3). RESULTS: In total, 186,824 hospital admissions with a primary diagnosis of DKA were identified, of which 32.44% (47,382) had TD. In-hospital morality among the smoking cohort (0.39%, SD 0.03) was lower than the non-smoking cohort (0.32%, SD 0.04) during the first hospitalization. Similar effects were observed after propensity match - 0.33% (SD 0.18) vs 0.27% (SD 0.03). The mortality rate during next hospitalization was also lower in the smoking cohort (0.72%, SD 0.03) in comparison to their counterpart (1.16%, SD 0.01). Smokers had a higher readmission rate of 17.6% (SD 0.57) than non-smokers (9.6%, SD 0.25). The length of stay among smokers and non-smokers were similar after propensity match - 3.12 days (SD 0.03) vs 3.06 days (SD 0.09), p=0.42, respectively. Total hospital cost was also similar between the two groups, $6,898 (SD $82) vs $7,100 (SD $203), p=0.32, respectively. Based on multivariate logistic regression, female and high Charlson comorbidity index were associated with higher 30-day readmission rate; whereas private insurance and high household income were associated with reduced readmission rate. CONCLUSION: Smoking has been associated with improved survival in patients with DKA (4). Previous studies have shown that glucose concentration were significantly lower at fasting and 120 min in current smokers than non-smokers. However, the effects of cigarette smoking on glucose metabolism and insulin resistance are still disputed.
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