Detection of Respiratory Viruses in the 2009 Winter Season in Rome: 2009 Influenza a (H1N1) Complications in Children and Concomitant Type 1 Diabetes Onset

2011 ◽  
Vol 24 (3) ◽  
pp. 651-659 ◽  
Author(s):  
R. Nenna ◽  
P. Papoff ◽  
C. Moretti ◽  
A. Pierangeli ◽  
G. Sabatino ◽  
...  
2012 ◽  
Vol 25 (2) ◽  
pp. 547-549 ◽  
Author(s):  
B. Piccini ◽  
S. Toni ◽  
L. Lenzi ◽  
M. Guasti ◽  
F. Barm ◽  
...  

Epidemiology ◽  
2018 ◽  
Vol 29 (1) ◽  
pp. e6-e8 ◽  
Author(s):  
Paz L. D. Ruiz ◽  
Lars C. Stene ◽  
Hanne L. Gulseth ◽  
German Tapia ◽  
Lill Trogstad ◽  
...  

2019 ◽  
Author(s):  
Fujian Qin ◽  
Yanfeng Zhang ◽  
Kaiying Li ◽  
Huashan Gao ◽  
Qian Zhao ◽  
...  

2018 ◽  
Vol 3 (2) ◽  
pp. 1-2
Author(s):  
Bishnu Prasad Upadhyay

Influenza virus type A and B are responsible for seasonal epidemics as well as pandemics in human. Influenza A viruses are further divided into two major groups namely, low pathogenic seasonal influenza (A/H1N1, A/H1N1 pdm09, A/H3N2) and highly pathogenic influenza virus (H5N1, H5N6, H7N9) on the basis of two surface antigens: hemagglutinin (HA) and neuraminidase (NA). Mutations, including substitutions, deletions, and insertions, are one of the most important mechanisms for producing new variant of influenza viruses. During the last 30 years; more than 50 viral threat has been evolved in South-East Asian countriesof them influenza is one of the major emerging and re-emerging infectious diseases of global concern. Similar to tropical and sub-tropical countries of Southeast Asia; circulation of A/H1N1 pdm09, A/H3N2 and influenza B has been circulating throughout the year with the peak during July-November in Nepal. However; the rate of infection transmission reach peak during the post-rain and winter season of Nepal.


2004 ◽  
Vol 27 (8) ◽  
pp. 728-732 ◽  
Author(s):  
K. Vondra ◽  
J. Vrbíková ◽  
I. Šterzl ◽  
R. Bílek ◽  
M. Vondrova ◽  
...  

Author(s):  
Fouzeyah OTHMAN ◽  
Dr. Fawzia Mandani ◽  
Dr. Zaidan Al-Mazidi ◽  
Dr. Khalid Al-Kandari

2019 ◽  
Vol 104 (11) ◽  
pp. 5195-5204 ◽  
Author(s):  
Emma H Dahlström ◽  
Niina Sandholm ◽  
Carol M Forsblom ◽  
Lena M Thorn ◽  
Fanny J Jansson ◽  
...  

Abstract Context The relationship between body mass index (BMI) and mortality may differ between patients with type 1 diabetes and the general population; it is not known which clinical characteristics modify the relationship. Objective Our aim was to assess the relationship between BMI and mortality and the interaction with clinically meaningful factors. Design, Setting, and Participants This prospective study included 5836 individuals with type 1 diabetes from the FinnDiane study. Main Outcome Measure and Methods We retrieved death data for all participants on 31 December 2015. We estimated the effect of BMI on the risk of mortality using a Cox proportional hazards model with BMI as a restricted cubic spline as well as effect modification by adding interaction terms to the spline. Results During a median of 13.7 years, 876 individuals died. The relationship between baseline BMI and all-cause mortality was reverse J-shaped. When analyses were restricted to those with normal albumin excretion rate, the relationship was U-shaped. The nadir BMI (BMI with the lowest mortality) was in the normal weight region (24.3 to 24.8 kg/m2); however, among individuals with diabetic nephropathy, the nadir BMI was in the overweight region (25.9 to 26.1 kg/m2). Diabetic nephropathy, diabetes-onset age, and sex modified the relationship between BMI and mortality (Pinteraction < 0.05). Conclusions Normal weight is optimal for individuals with type 1 diabetes to delay mortality, whereas underweight might be an indication of underlying complications. Maintaining normal weight may translate into reduced risk of mortality in type 1 diabetes, particularly for individuals of male sex, later diabetes-onset age, and normal albumin excretion rate.


Bone ◽  
2019 ◽  
Vol 123 ◽  
pp. 260-264 ◽  
Author(s):  
Viral N. Shah ◽  
Prakriti Joshee ◽  
Rachel Sippl ◽  
Laura Pyle ◽  
Tim Vigers ◽  
...  

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