bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical characteristics and outcomes of patients admitted with acute heart failure: insights from a single-center heart failure registry in South India
Authors: Shukkoor Aashiq Ahamed , George Nimmy Elizabeth , Radhakrishnan Shanmugasundaram , Velusamy Sivakumar , Gopalan Rajendiran , Kaliappan Tamilarasu , Anandan Premkrishna , Palanimuthu Ramasamy , Balasubramaniam Vidhyakar , Doraiswamy Vinoth , Ponnusamy Arun Kaushik 
Published: May 2021

Abstract
Background
The epidemiology of HF in India is largely unexplored. Current resources are based on a few hospital-based and a community-based registry from North India. Thus, we present the data from a single hospital-based registry in South India. Patients admitted with acute heart failure over a period of 1 year were enrolled in the registry and were characterized based on their ejection fraction (EF) measured by echocardiogram. The clinical profile of the patients was assessed, including their in-hospital outcomes. One-way ANOVA and univariate analysis were performed for comparison between three EF-based groups and for the assessment of in-hospital outcomes.

Results
A total of 449 patients were enrolled in the registry, of which 296, 90, and 63 patients were categorized as, HFrEF, HFmrEF, and HFpEF, respectively. The prevalence of HFrEF was higher (65.99%). The mean age (SD) of the study cohort was 59.9±13.3. The majority of the patients presented with acute denovo HF (67%) and were more likely to be males (65.9%). The majority of patients presented with warm and wet clinical phenotype (86.4%). In hospital mortality was higher in HFmrEF (3.3%).

Conclusion
Patients with HFrEF had high adherence to guideline-directed medical therapy (GDMT). HFrEF patients were also likely to have longer hospital stay along with a worsening of renal function. The in-hospital mortality was comparable between the EF-based groups. Additionally, the association of clinical phenotypes with outcome highlighted that patients in warm and wet phenotype had a longer length of hospital stay, whereas the mortality and worsening renal function rates were found to be significantly higher in the cold and wet group.
Improvement of Grey System Model using Particle Swarm Optimization
Authors: Twumasi Elvis , Frimpong Emmanuel Asuming , Kwegyir Daniel , Folitse Denis 
Published: May 2021

AbstractAn improvement of the traditional grey system model, GM(1,1), to enhance forecast accuracy, has been realized using the particle swarm optimization (PSO) algorithm. Unlike the GM(1,1) which uses a fixed adjacent neighbor weight for all data sets, the proposed PSO-improved model, PSO-GM(1,1), determines an optimal adjacent neighbor weight, based on the presented data set. This optimal adjacent neighbor weight so determined is the principal factor that enhances forecast accuracy. The performance of the proposed model was evaluated using generated monotonic increasing and decreasing data sets as well as measured energy consumption data for a laptop computer, desktop computer, printer, and photocopier. The performance of PSO-GM(1,1) was compared with that of GM(1,1), and two other models in literature that sought to improve the performance of GM(1,1). The PSO-GM(1,1) outperformed the traditional model and the two other models. For the monotonic increasing data, the mean absolute percentage error (MAPE) for the proposed model was 0.007% as against a MAPE value of 20.383% for the GM(1,1). For the monotonic decreasing data, the PSO-GM(1,1) again outperformed GM(1,1), yielding a MAPE of 0.057% compared to a value of 13.407% for the traditional model. For the measured laptop computer energy data, the obtained MAPE for the PSO-GM(1,1) was 0.675% while the values for the two models were 4.052% and 2.991%. For the measured desktop computer energy data, the obtained MAPE for the PSO-GM(1,1) was 0.0018% while the values for the two models were 0.0018% and 1.163%. For the data associated with the printer, the MAPEs were 8.414% for the PSO-GM(1,1), 20.957% for the first model and 9.080% for the second model. For the measured photocopier energy data, the obtained MAPE for the PSO-GM(1,1) was 0.901% while the values for the two models were 3.799% and 0.943%. Thus, the proposed PSO-GM(1,1) greatly improves forecast accuracy and is recommended for adoption, for forecasting.
Assessing Treatment Effects with Pharmacometric Models: A New Method that Addresses Problems with Standard Assessments
Authors: Chasseloup Estelle , Tessier Adrien , Karlsson Mats O. 
Published: May 2021

AbstractLongitudinal pharmacometric models offer many advantages in the analysis of clinical trial data, but potentially inflated type I error and biased drug effect estimates, as a consequence of model misspecifications and multiple testing, are main drawbacks. In this work, we used real data to compare these aspects for a standard approach (STD) and a new one using mixture models, called individual model averaging (IMA). Placebo arm data sets were obtained from three clinical studies assessing ADAS-Cog scores, Likert pain scores, and seizure frequency. By randomly (1:1) assigning patients in the above data sets to “treatment” or “placebo,” we created data sets where any significant drug effect was known to be a false positive. Repeating the process of random assignment and analysis for significant drug effect many times (N = 1000) for each of the 40 to 66 placebo-drug model combinations, statistics of the type I error and drug effect bias were obtained. Across all models and the three data types, the type I error was (5th, 25th, 50th, 75th, 95th percentiles) 4.1, 11.4, 40.6, 100.0, 100.0 for STD, and 1.6, 3.5, 4.3, 5.0, 6.0 for IMA. IMA showed no bias in the drug effect estimates, whereas in STD bias was frequently present. In conclusion, STD is associated with inflated type I error and risk of biased drug effect estimates. IMA demonstrated controlled type I error and no bias.
Developmental Changes in Food Perception and Preference
Authors: Serrano-Gonzalez Monica , Lim Seung-Lark , Sullivan Nicolette , Kim Robert , Herting Megan M , Espinoza Juan , Koppin Christina , Javier Joyce R , Luo Shan , Kim Mimi S 
Published: May 2021

Abstract
Food choices are a key determinant of dietary intake, with involved brain regions such as the mesolimbic and prefrontal cortex maturing at a differential rate from childhood to young adulthood. However, developmental changes in healthy and unhealthy food perception and preference remain poorly understood. We aimed to understand this gap by investigating whether perceptions and preferences for food vary as a function of age, and how specific food attributes (i.e., taste and health) impact these age-related changes. We hypothesized that there would be an inverted U-shaped relationship between age and preference for high-calorie foods. As well, we expected that both dietary self-control and the decision weight of the health attribute would increase with age. One hundred thirty-nine participants aged 8–23 years (79 males, 60 females) participated in this study. They completed computerized rating tasks to assess taste, health, and liking (or preference) of high-calorie and low-calorie foods, followed by 100 binary food choices based on each participant’s individual ratings for taste and health. Among the 100 pairs, 75 were deemed challenge trials, where one food had a higher taste rating but a lower health rating than the other food item. Dietary self-control was considered successful when the healthier food cue in the challenge trial was chosen, and self-control success ratio (SCSR) was computed as the proportion of self-control success trials over the total number of choices. Results showed that high-calorie foods were rated as more tasty (r = 0.32, p &lt; 0.001) and less healthy (r = -0.22, p &lt; 0.01) with increasing age. As well, older participants wanted to eat high-calorie foods more than the younger participants (r = 0.29, p = 0.001). Furthermore, older age was associated with an increased decision weight of taste attribute on food preferences (r = 0.26, p = 0.002), suggesting that the taste attribute may contribute to the age-related increases in preference for high-calorie foods. Although participants rated low-calorie foods as less tasty (r = -0.17, p = 0.04) and less healthy (r= -0.31, p &lt; 0.001) with increasing age, there was no significant association between age and preference for low-calorie foods. Participants made faster food choices with increasing age (r= -0.31, p &lt; 0.001), which was driven by failed self-control choices (r = -0.23, p = 0.006). There was no significant association between age and SCSR (p = 0.5). Our results are consistent with other studies that demonstrate age-related increases in consumption of calorie-dense foods in youth, and suggest that age may be more relevant to preference for high-calorie than low-calorie foods. Future studies are merited to investigate the neurobiology underlying these developmental changes in food perceptions and preferences.
Engagement in a Multi-Feature Digital Health Lifestyle Change Program as a Predictor of Weight Loss
Authors: Dzubur Eldin , James Roberta , Shah Bimal , Kompala Tejaswi 
Published: May 2021

Abstract
Background: Modern digital health interventions targeting weight loss employ multiple evidence-based strategies, including nutrition tracking, coaching, and activity monitoring, providing users with choice as they set and achieve their own goals. Still, limited research exists on the partial effects of each component of such interventions, and whether participants choose to use all of the features of a program. The objective of this study was to test the individual components of a fully-featured digital health lifestyle intervention as predictors of weight loss in a single statistical model.
Methods: Participants in the study (N=25,273) were enrolled in the Livongo for Weight Loss program as part of their employee wellness benefit across 57 states/territories of the US from April, 2019 to January, 2021. Participants received a cellular-connected scale to use daily in the program; they were asked to track their eating via the app and physical activity via smartphones or wearables. Additionally, participants could engage with coaches voluntarily or by receiving feedback from coaches on their recorded food logs. A mixed-effects generalized linear model was used to test the effects of scale usage, physical activity, human telephonic coaching, and food logs without and without coaching feedback on the percent weight loss the following month. Predictors were disaggregated into between- and within-subject components to understand the impact of each component relative to one’s own mean. The month in the program and whether or not that month occurred during the COVID-19 pandemic were entered as time-varying covariates. Baseline age, gender, and BMI were entered as time-invariant covariates.
Results: Participants were 45% male and had average age of 54.3 years old (SD =11.4), with an average BMI of 33.10 kg/m2 (SD: 6.2). On average, participants were enrolled in the program for 10.4 months (SD: 5.1). Each additional use of the scale above one’s own average was associated with an overall 7.4% weight loss (z=21.06,p&lt;0.001). Similarly, each additional minute of moderate-vigorous physical activity (MVPA) above one’s own average was associated with an overall 2.4% weight loss (z=3.14, p&lt;0.01). Lastly, coaching and food logging with coaching feedback at a frequency above one’s own average were associated with approximately a 6% weight loss throughout the program (z=3.08 and 2.35, respectively; p&lt;0.05 for both).
Conclusion: We found that frequency of use of a scale in a weight loss intervention was most predictive of weight loss, followed by human coaching interaction and physical activity. However, food logging without feedback did not significantly impact weight loss among participants. Additional work is needed to understand drivers associated with increased utilization of beneficial program features, including optimizing the use of coaching, which offers great benefit, but may be costly to scale.
Insulin Resistance Moderates the Association Between BMI and Metabolic Syndrome Severity in Women 4–10 Years After Pregnancy, Independent of Gestational Diabetes Status
Authors: Callahan Makenzie , Martin Samantha , Bahorski Jessica , Pavela Gregory , Garvey W Timothy , Chandler-Laney Paula C 
Published: May 2021

Abstract
Objective: Obesity and gestational diabetes mellitus (GDM) increase the risk for metabolic syndrome (MetS). Insulin resistance (IR) is associated with obesity, contributes to risk for GDM, and persists after pregnancy even when glucose tolerance returns. Further, IR may enhance the risk of MetS associated with obesity and GDM. The purpose of this study was to test the hypothesis that IR moderates the relationship between BMI and MetS severity 4–10 years after pregnancy, independent of prior GDM, such that the positive association between BMI and MetS severity is stronger among women with greater IR. Methods: This hypothesis was tested in a secondary analysis of data collected from women enrolled in a study of the intergenerational transmission of obesity, 4–10 years after the index pregnancy. Recruitment in the parent study was stratified to include women with normal weight without GDM (NW), overweight or obesity without GDM (OwOB), and women with GDM during the index pregnancy. Standard clinical procedures were used to measure height, weight, waist circumference and blood pressure, and a fasting blood draw was obtained with which to measure glucose, insulin, triglycerides, and HDL-cholesterol. MetS was evaluated as a continuous outcome, reflecting severity, using the method of Gurka and DeBoer.1 IR was calculated with the homeostatic model assessment (HOMA-IR) and modeled as a continuous variable. An OLS regression model predicting MetS as a function of HOMA-IR, BMI, and their interaction, along with key covariates was used to test whether HOMA-IR moderates the relationship between BMI and MetS severity, independent of GDM. Results: The association between BMI and MetS severity was significantly modified by HOMA-IR (b=0.008, p&lt;0.001), independent of GDM status during pregnancy, such that the positive association between BMI and MetS severity was stronger among individuals with higher HOMA-IR. For example, among women with HOMA-IR values 1-standard deviation below the mean, the estimated association between BMI and MetS severity was (b=0.0394, p&lt;0.001); however, among women with a HOMA-IR value 1-standard deviation above the mean, the association between BMI and MetS severity was (b=0.0745, p&lt;0.001). Conclusion: IR after pregnancy was a significant moderator of the association between BMI and MetS severity. Future studies should explore whether interventions to improve IR can reduce MetS severity independent of BMI and prior GDM.
References: 1.Gurka MJ, Lilly CL, Oliver MN, DeBoer MD. An examination of sex and racial/ethnic differences in the metabolic syndrome among adults: a confirmatory factor analysis and a resulting continuous severity score. Metabolism. 2014;63(2):218–225.
L-Leucine Supplementation for Preserving Lean Mass During Low Calorie Diet in Sarcopenic Obese Women: A Pilot Study
Authors: Camajani Elisabetta , Persichetti Agnese , Contini Savina , Lubrano Carla , Caprio Massimiliano , Gnessi Lucio , Basciani Sabrina 
Published: May 2021

Abstract
Background: In sarcopenic obese subjects it is essential to reduce body weight and to preserve lean mass, in order to avoid a worsening of muscle function (1). Several studies have shown that leucine supplementation can be useful to improve skeletal muscle mass in sarcopenic patients (2). Aim: Evaluate the effectiveness of a short-term low calorie diet (LCD) combined with combined supplementation with whey protein, leucine and vitamin D on weight loss, lean mass and muscle strength in sarcopenic, obese, hyperinsulinemic and menopause women. Materials and methods: 16 female with mean age: 58.1 years (range: 47–69 years), BMI 37.6 Kg/m2 (range: 31,7 - 44,1 Kg/m2), HOMA-index ≥ 2.5, were assigned to an LCD regimen (1000 kcal/day) with supplementation of 18 g protein, 4 g leucine and 5 mcg vitamin D for 45 days. Anthropometric indexes, blood and urine chemistry, body composition by DEXA, muscle strength by handgrip test and Short Physical Performance Battery (SPPB) were assessed at baseline and at the end of the treatment. Results: A significant reduction of BMI (35,7 vs 37,6 Kg/m2), waist circumference (102,4 vs 107 cm), HOMA index (2,3 vs 4,8) and fasting insulin (10,4 vs 17,4 μIU/ml) was observed in all patients. Women preserved total lean body mass (57 vs 55 %) and improved significantly muscle strength, as measured by handgrip (22,2 vs 18,6 Kg) and SPPB (8,9 vs 7,5). Conclusion: We conclude that LCD with adequate protein intake and a supplementation with whey protein, leucine and vitamin D should be promoted to maintain muscle mass and improve muscle strength in menopause women with sarcopenic obesity. References: 1. Batsis JA, Villareal DT. Sarcopenic obesity in older adults: aetiology, epidemiology and treatment strategies. Nat Rev Endocrinol. 2018 Sep;14(9):513–5372. Bauer JM, Verlaan S, Bautmans I, Brandt K, Donini LM, Maggio M, McMurdo ME, Mets T, Seal C, Wijers SL, Ceda GP, De Vito G, Donders G, Drey M, Greig C, Holmbäck U, Narici M, McPhee J, Poggiogalle E, Power D, Scafoglieri A, Schultz R, Sieber CC, Cederholm T. Effects of a vitamin D and leucine-enriched whey protein nutritional supplement on measures of sarcopenia in older adults, the PROVIDE study: a randomized, double-blind, placebo-controlled trial. J Am Med Dir Assoc. 2015 Sep 1;16(9)
Metabolic and Endocrine Comorbidities in Hidradenitis Suppurativa: A Nationwide Study
Authors: Edigin Ehizogie , Eseaton Precious O , Shaka Hafeez , Asemota Iriagbonse , Akuna Emmanuel , Ojemolon Pius , Velazquez Genaro , Asotibe Jennifer Chiagoziem , Williams Dimeji 
Published: May 2021

Abstract
Introduction: Hidradenitis suppurativa (HS) or acne inversa is a chronic, inflammatory, recurrent, debilitating skin disease. There have been studies linking HS to metabolic syndrome [1]. However, there is a scarcity of studies on metabolic and endocrine co-morbidities of hospitalized HS patients. This study aims to compare the prevalence of metabolic and endocrine co-morbidities in hospitalized HS patients to hospitalized non-HS patients.
Methods: Data were abstracted from the National Inpatient Sample (NIS) 2016 and 2017 Database. NIS is the largest inpatient hospitalization database in the United States. The NIS was searched for hospitalizations for adult patients aged 18 years or above with a principal or secondary diagnosis of HS and those without any diagnosis of HS. Chi-square test was used to compare the prevalence of common metabolic and endocrine comorbidities between HS and non-HS hospitalized patients. Co-morbidities were obtained from secondary diagnoses. We used ICD-10 codes to obtain HS hospitalizations and co-morbidities. STATA, version 16 was used for analysis.
Results: There were over 71 million discharges in the combined 2016 and 2017 NIS database. Out of which, 40,275 hospitalizations had a diagnosis of HS. HS hospitalizations had higher prevalence of type 2 diabetes (33.1% vs 24.5%, p&lt;0.0001), type 1 diabetes mellitus (1.9% vs 0.9%, p&lt;0.0001), obesity (35.8% vs 14.3%, p&lt;0.0001), lower prevalence of dyslipidemia (21.3% vs 31.8%, p&lt;0.0001), hypothyroidism (6.3% vs 12.0%, p&lt;0.0001) and similar prevalence of hyperthyroidism (0.4% vs 0.5%, p=0.2373) compared to non-HS hospitalizations
Conclusion: Hospitalized HS patients have a higher prevalence of type 1 & 2 diabetes mellitus and obesity compared to hospitalized non-HS patients. An interdisciplinary approach involving the endocrinologist, dermatologist, and hospitalist may be needed to optimally manage these co-morbidities in hospitalized HS patients.
References 1. Ergun T. Hidradenitis suppurativa and the metabolic syndrome. Clin Dermatol. 2018;36(1):41–47. doi:10.1016/j.clindermatol.2017.09.007
Morbid Obesity Is Associated With Worse Outcomes and Increased Inpatient Mortality in Patients With Alcohol Induced Acute Pancreatitis
Authors: Shaka Hafeez , Rashad Essam , Achebe Ikechukwu , Asotibe Jennifer Chiagoziem , Palomera Emmanuel , Pudasaini Garima , Warraich Muhammad-Sheharyar 
Published: May 2021

Abstract
Introduction: The prevalence of obesity in the United States is rising. Obesity is a known comorbidity with various health impacts. Alcohol is a common etiology for acute pancreatitis. Obesity is known to be associated with liver dysfunction. It is unclear to what extent the degree of obesity affects patients with alcohol induced acute pancreatitis (AAP), as nationally representative data are lacking. This study aimed to ascertain the impact of morbid obesity on outcomes of patients with alcohol induced pancreatitis.
Methods: Data was obtained from the Nationwide Inpatient Sample database for 2016 and 2017. Hospital discharges of patients 18 years and over with a principal diagnosis of AAP were included. This cohort was divided based on presence of comorbid obesity into nonobese patients, mild-moderately obese patients (MMO) (BMI: 30.0 - 39.9) and morbidly obese patients (MO) (BMI &gt;/=40.0). Primary outcome was inpatient mortality. Secondary outcomes included length of hospital stay (LOS), total hospital charges (THC), discharge diagnoses of hypocalcemia, sepsis, acute renal failure (AKI) and acute respiratory failure (ARF). Multivariate regression analysis was used to adjust for patients’ sociodemographic factors, Charlson comorbidity index as well as hospital characteristics as confounders.
Results: A total of 143650 hospitalizations were principally for AAP, with 5.5% and 2.7% of these patients classified as having MMO and MO, respectively.
In MO patients, there was increased odds of mortality (aOR=2.99, 95% CI: 1.509 - 5.917, p=0.002) when compared with patients who were nonobese. There was no difference in mortality in patients with MMO (aOR 0.88 95% CI: 0.383 - 2.026, p=0.765) when compared with the nonobese group. MO patients had increased mean LOS of 1.1 days (95% CI: 0.7 - 1.6, p&lt;0.001) as well as THC of $14481 (95% CI: 7894 - 21068, p&lt;0.001), increased odds of hypocalcemia (aOR=1.77, 95% CI: 1.302 - 2.392, p&lt;0.001), sepsis (aOR=1.84, 95% CI: 1.183 - 2.873, p=0.007), AKI (aOR=1.55, 95% CI: 1.257 - 1.912, p&lt;0.001).
Conclusion: Morbid obesity has a negative impact on outcomes of patients with AAP. Efforts should be channeled towards promoting alcohol cessation in at-risk patients as a preventative measure, as well as closer monitoring of hospitalized patients with morbid obesity to mitigated these adverse events.