scholarly journals Trends in Method of Diagnosis of Type 2 Diabetes Mellitus: Results from SHIELD

2009 ◽  
Vol 2009 ◽  
pp. 1-6 ◽  
Author(s):  
Helena W. Rodbard ◽  
Andrew J. Green ◽  
Kathleen M. Fox ◽  
Susan Grandy

Aims. This study assessed whether recent screening recommendations have led to increased diagnosis of type 2 diabetes mellitus (T2DM) through routine screening.Methods. Respondents to the 2006 US SHIELD survey reported whether a physician told them they had T2DM, age at diagnosis, specialty of the physician who made the diagnosis, and whether the diagnosis was made after having symptoms, during routine screening, or when being treated for another health problem.Results. Of 3 022 T2DM respondents, 36% of respondents reported that T2DM diagnosis was made during routine screening alone, 20% after having symptoms alone, and 6% when being treated for another health problem alone. The proportion of T2DM respondents reporting a diagnosis based only on screening increased approximately 42% over a 15+-year time span (absolute increase from 31% to 44%) (P<.001), whereas symptom-based diagnosis did not change significantly (P=.10). T2DM was diagnosed primarily by family physicians (88.3%).Conclusion. These findings highlight the importance of regular screening for diabetes and the vital role of primary care physicians in recognizing individuals with T2DM.

Author(s):  
Nermien Abd El Rahman Ibraheim ◽  
Fatema El Zahraa Sayed Bukhary ◽  
Yehia Zakareia Mahmoud ◽  
Mahmoud Ragab Mohamed ◽  
Salama Rabei Abdel-Rahim

2018 ◽  
Vol 15 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Sayantan Nath ◽  
Sambuddha Das ◽  
Aditi Bhowmik ◽  
Sankar Kumar Ghosh ◽  
Yashmin Choudhury

Background:Studies pertaining to association of GSTM1 and GSTT1 null genotypes with risk of T2DM and its complications were often inconclusive, thus spurring the present study.Methods:Meta-analysis of 25 studies for evaluating the role of GSTM1/GSTT1 null polymorphisms in determining the risk for T2DM and 17 studies for evaluating the role of GSTM1/GSTT1 null polymorphisms in development of T2DM related complications were conducted.Results:Our study revealed an association between GSTM1 and GSTT1 null polymorphism with T2DM (GSTM1; OR=1.37;95% CI =1.10-1.70 and GSTT1; OR=1.29;95% CI =1.04-1.61) with an amplified risk of 2.02 fold for combined GSTM1-GSTT1 null genotypes. Furthermore, the GSTT1 null (OR=1.56;95%CI=1.38-1.77) and combined GSTM1-GSTT1 null genotypes (OR=1.91;95%CI=1.25- 2.94) increased the risk for development of T2DM related complications, but not the GSTM1 null genotype. Stratified analyses based on ethnicity revealed GSTM1 and GSTT1 null genotypes increase the risk for T2DM in both Caucasians and Asians, with Asians showing much higher risk of T2DM complications than Caucasians for the same. </P><P> Discussion: GSTM1, GSTT1 and combined GSTM1-GSTT1 null polymorphism may be associated with increased risk for T2DM; while GSTT1 and combined GSTM1-GSTT1 null polymorphism may increase the risk of subsequent development of T2DM complications with Asian population carrying an amplified risk for the polymorphism.Conclusion:Thus GSTM1 and GSTT1 null genotypes increases the risk for Type 2 diabetes mellitus alone, in combination or with regards to ethnicity.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hua Zha ◽  
Fengping Liu ◽  
Zongxin Ling ◽  
Kevin Chang ◽  
Jiezuan Yang ◽  
...  

AbstractType 2 diabetes mellitus (T2DM) influences the human health and can cause significant illnesses. The genitourinary microbiome profiles in the T2DM patients remain poorly understood. In the current study, a series of bioinformatic and statistical analyses were carried out to determine the multiple bacteria associated with the more dysbiotic genitourinary microbiomes (i.e., those with lower dysbiosis ratio) in T2DM patients, which were sequenced by Illumina-based 16S rRNA gene amplicon sequencing. All the genitourinary microbiomes from 70 patients with T2DM were clustered into three clusters of microbiome profiles, i.e., Cluster_1_T2DM, Cluster_2_T2DM and Cluster_3_T2DM, with Cluster_3_T2DM at the most dysbiotic genitourinary microbial status. The three clustered T2DM microbiomes were determined with different levels of alpha diversity indices, and driven by distinct urinalysis variables. OTU12_Clostridiales and OTU28_Oscillospira were likely to drive the T2DM microbiomes to more dysbiotic status, while OTU34_Finegoldia could play a vital role in maintaining the least dysbiotic T2DM microbiome (i.e., Cluster_1_T2DM). The functional metabolites K08300_ribonuclease E, K01223_6-phospho-beta-glucosidase and K00029_malate dehydrogenase (oxaloacetate-decarboxylating) (NADP+) were most associated with Cluster_1_T2DM, Cluster_2_T2DM and Cluster_3_T2DM, respectively. The characteristics and multiple bacteria associated with the more dysbiotic genitourinary microbiomes in T2DM patients may help with the better diagnosis and management of genitourinary dysbiosis in T2DM patients.


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