2339-PUB: Effect of IDegLira on HbA1c and Weight: Data from the Association of British Clinical Diabetologists (ABCD) IDegLira Audit

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 2339-PUB
Author(s):  
SEAN NORONHA ◽  
ALISTAIR N. LUMB ◽  
ALEX BICKERTON ◽  
SING YEE SIM ◽  
IAN W. GALLEN ◽  
...  
Keyword(s):  
BMJ ◽  
2020 ◽  
pp. m4561
Author(s):  
R A Lewis

AbstractObjectiveTo estimate the daily dietary energy intake for me to maintain a constant body weight. How hard can it be?DesignVery introspective study.SettingAt home. In lockdown. (Except every Tuesday afternoon and Saturday morning, when I went for a run.)ParticipantsMe. n=1.Main outcome measuresMy weight, measured each day.ResultsSleeping, I shed about a kilogram each night (1.07 (SD 0.25) kg). Running 5 km, I shed about half a kilogram (0.57 (SD 0.15) kg). My daily equilibrium energy intake is about 10 000 kJ (10 286 (SD 201) kJ). Every kJ above (or below) 10 000 kJ adds (or subtracts) about 40 mg (35.4 (SD 3.2) mg).ConclusionsBody weight data show persistent variability, even when the screws of control are tightened and tightened.


2021 ◽  
pp. 155982762110066
Author(s):  
Keith Brazendale ◽  
Jeanette Garcia ◽  
Ethan T. Hunt ◽  
Michael Blankenship ◽  
Daniel Eisenstein ◽  
...  

Purpose. Preventive measures to curtail the spread of the Coronavirus Disease 2019 (COVID-19)—such as home quarantine, closure of schools/programs—are necessary, yet the impact of these restrictions on children’s weight status is unknown. The purpose of this case report was to investigate changes in children’s body mass index (BMI) and zBMI during COVID-19 quarantine. Methods. Children had their heights and weights recorded early March 2020 (pre-COVID-19) and 5 months later (early August 2020). Paired sample t tests examined changes in BMI and zBMI from baseline to follow-up. Results. Twenty-nine children (62% female; mean age 9.3 years; 27.5% with overweight or obesity) provided height and weight data at both time points. There was a significant difference in pre-COVID-19 BMI (mean [M] = 20.1, standard deviation [SD] = 6.0) and follow-up BMI (M = 20.7, SD = 6.4); t(57) = −3.8, P < .001, and pre-COVID-19 zBMI (M = 0.8, SD = 0.9) and follow-up zBMI (M = 0.9, SD = 0.9); t(57) = -3.1, P = .003. Five of the 29 children moved from normal weight to overweight (n = 4) or obese (n = 1) during 5 months of quarantine. Conclusions. Preliminary evidence shows most children increased their BMI and zBMI values from pre-COVID-19 assessment to the follow-up assessment, 5 months later. These initial findings identify potential incidental negative health consequences of children as a result of COVID-19 preventative measures such as home quarantine.


1998 ◽  
pp. 359-370
Author(s):  
Shouji Toma ◽  
Takumi Suzuku ◽  
Yasuhiro Kuroda

1999 ◽  
Vol 47 (1) ◽  
pp. 123-128 ◽  
Author(s):  
T. Varga ◽  
I. Hlubik ◽  
L. Várnagy ◽  
P. Budai ◽  
E. Molnár

The purpose of this work was to determine the individual and combined effects of insecticide Sumithion 50 EC (50% fenitrothion) and herbicide Fusilade S (12.5% fluazifop-P-butyl) on the development of pheasant embryos. Eggs were treated by injection of various concentrations of pesticides into the air space on day 12 of incubation. Pathological examination of embryos was carried out on day 23 of the hatching period. Mortality rate, body weight data and morphological alterations were evaluated after the macroscopic examination. The skeletal staining method was used to detect deformities. The two pesticides used in combination moderated the toxic/teratogenic effects of individual treatment.


1999 ◽  
Vol 22 (2) ◽  
pp. 187-196 ◽  
Author(s):  
Sônia Mara Carrijo ◽  
Francisco A. Moura Duarte

Weight data from birth to 18 months of age of Nelore and Chianina, both meat-producing cattle breeds, were analyzed. Data were corrected for significant effects of environment and utilized to estimate genetic parameters through the non-linear von Bertalanffy model. Average values found for growth parameters in Nelore were: mature weight (A), 312.87 kg; integration constant (B), 0.49; maturity rate (k), 0.13; age at inflection point (T(I)), 3.29 months; weight at inflection point (P(I)), 92.70 kg, and maturity interval (1/k), 8.04 months. For the Chianina animals, the values were 751.38 kg, 0.59, 0.10, 6.64 months, 222.63 kg, and 10.98 months, respectively. Nelore animals exhibited higher maturity rate, smaller maturity intervals, reaching mature weights younger than Chianina animals, although lighter than these at maturity. Heritability estimates presented low values, mainly for mature weight (0.093 and 0.212), age at inflection point (0.062 and 0.202), weight at inflection point (0.093 and 0.212) and maturity interval (0.057 and 0.309) (for Nelore and Chianina, respectively). The parameters mature weight and weight at inflection point presented positive genetic correlations with weights at different ages and with similar trends, increasing as age increased, in both breeds. Considering the development period analyzed, from birth to 18 months of age, the parameter maturity rate and the weights at different ages showed genetic correlations which increased until the weight at 150 and 205 days in Nelore and Chianina, respectively, and decreased from these ages on, and the genetic correlations among the parameter maturity interval and the weights at different ages were negative. They decreased until the weights at 150 and 205 days, respectively, in Nelore and Chianina, and increased from these ages on.


2021 ◽  
Vol 888 (1) ◽  
pp. 012009
Author(s):  
F Mustofa ◽  
A P Z N L Sari ◽  
A Agus ◽  
H Sasongko ◽  
E Suryanto ◽  
...  

Abstract The production of local chickens in Indonesia is determined by the availability of high-quality local chicken stocks. However, information on local chicken performance is limited, therefore, this study aims to determine the live weight performance of three local Indonesian chicken namely Merawang, Murung Panggang, and KUB in the starter phase. The study was conducted at chicken farm located in Semanu Gunung Kidul, Yogyakarta. Meanwhile, the live weight data were collected at the starter phase (0, 2, and 4 weeks. The samples consisted of 196 Merawang, 157 Murung Panggang, and 416 KUB chickens reared in a battery cage in a closed house under similar conditions. Furthermore, the live weight performance data were analyzed using analysis of variance (ANOVA). As a result, the Merawang chicken had the highest live weight (P<0.05) at the day-old chick (DOC) age. At the same age, no significant difference was detected between the KUB and Murung Panggang chicken (P>0.05). However, the live weight of Murung Panggang was significantly higher at 2 and 4 weeks compared to others (P< 0.05). Therefore, it was concluded that there are variations in the live weight of the three local chickens during the starter phase.


2019 ◽  
Author(s):  
Ho-Ling Hwang ◽  
Hyeonsup Lim ◽  
Shih-Miao Chin ◽  
Ross Wang ◽  
Brennan Wilson

2012 ◽  
Vol 167 (3) ◽  
pp. 453 ◽  
Author(s):  
Leo Niskanen ◽  
Lawrence A Leiter ◽  
Edward Franek ◽  
Jianping Weng ◽  
Taner Damci ◽  
...  

The journal and the authors apologise for errors in Table 2 of this article that was published in the August issue (vol 167, pp 287–294). The n values were incorrectly published. The correct values are presented below and the table is published in full below.Table 2Observed mean changes from baseline HbA1c, FPG and body weight. Data are observed as mean (s.d.) for all randomised subjects (full analysis set).nBaselineaWeek 16bChange from baselineHbA1c (%) IDegAsp618.5 (1.2)6.7 (1.0)−1.8 (1.1)c AF598.5 (0.9)6.6 (0.6)−1.9 (1.1)c BIAsp 30628.6 (1.0)6.7 (0.7)−1.8 (0.9)cFPG (mmol/l) IDegAsp6111.5 (2.6)6.4 (2.2)−5.1 (2.9) AF5911.8 (2.9)6.5 (1.9)−5.3 (3.0) BIAsp 306211.7 (3.1)7.5 (2.1)−4.3 (3.0)Body Weight (kg) IDegAsp6187.5 (16.3)88.6 (16.9)1.1 (2.8) AF5984.9 (14.3)85.6 (14.9)0.7 (2.5) BIAsp 306291.8 (13.5)93.2 (13.1)1.4 (3.2)aValues at randomisation.bLast observation carried forward.c% points.


1969 ◽  
Vol 26 (10) ◽  
pp. 2643-2650 ◽  
Author(s):  
Norman R. Glass

The rationale for employing a nonlinear iterative least-squares technique for fitting the well-known power function to oxygen consumption–body weight data is set forth. Twenty-six sets of routine or standard metabolism data from six authors were used to demonstrate the relative merits of two methods of calculating parameter values for the power function. The conclusion was reached that if accuracy in predicting oxygen consumption over a wide range of values of body weight is desired, an iterative curve fitting method may be superior to the much used technique of performing a linear regression on logarithmically transformed data.


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