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Objective:To analyze the distribution characteristics of special types of diabetes in China, in order to provide a theoretical basis for the diagnosis and treatment of special types of diabetes.Methods:Pubmed, CNKI, and WanFang Data were searched for the case reports and clinical studies of special types of diabetes in China from 2011 to 2021. After independent literature screening by 2 researchers according to the inclusion and exclusion criteria, diseases and the number of corresponding cases included were extracted for statistics. The etiological composition and disease characteristics of three subtypes of special type diabetes were analyzed.Results:A total of 613 articles(7 377 patients)were included and roughly divided into eight subtypes of special type diabetes according to etiological classification for disease composition analysis. The results by ratio in descending order were as follows: mono-genetic gene defects in islet β-cell function, pancreatogenic diabetes, diabetes induced by drugs or chemicals, endocrine disease, mono-genetic gene defects in insulin action, other genetic syndromes associated with diabetes, infection, and uncommon immune-mediated diabetes. The disease composition of the three subtypes of special types of diabetes that we focused on were mono-genetic gene defects in islet β-cell function(50.21%), pancreatogenic diabetes(35.65%), and mono-genetic gene defects in insulin action(1.56%). The composition analysis of the special types of diabetes in each subtype showed that neonatal diabetes mellitus(NDM, n=1 749, 23.71%)and maturity onset diabetes in young(MODY, n=1 554, 21.07%)accounted for the largest proportions. According to the composition analysis of each subtype of MODY patients, the top three subtypes were MODY2(50.89%), MODY3(16.03%), and MODYX(8.91%). In addition, taking MODY as an example, patients with de novo mutations(DNMs)and(or)new mutation sites were summarized and analyzed. The results revealed 31 MODY patients with DNMs(1.99%) and 339 MODY patients with new mutation sites(21.81%). Conclusions:According to the literature analysis, NDM and MODY represent the largest proportion of patients with special type diabetes in China. MODY2 patients make up the largest proportion of MODY patients. In addition, diabetic patients carrying DNMs and(or)new mutation sites should be taken seriously.
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Objective To establish and verify the fluctuation of reference intervals for biochestry parameters in routine physical exami-nation. Methods The results of biochemistry parameters,i.e., total protein (TP), albumin (Alb), total bilirubin (T-Bil), alanine aminotransferase (ALT), glucose (Glu), urea (Urea), creatinine (Cr), uric acid (UA), triacylglycerol (TG) and total cholesterol ( TC) from 2 089 healthy subjects in routine physical examination during consecutive 2014, 2015 and 2016 were randomly collected, in which all the results were within the reference range. The ratio (λ1) of the results of 2015 to those of 2014, and ratio (λ2) of the re-sults of 2016 to those of 2015 were calculated. λ1was analyzed statistically to establish the fluctuation of reference interval (CIλ). CIλ was verified by λ2.The personalized reference interval (CIp) was established by multiplying each result of 2015 and the upper and low-er limits of CIλ. The CIpwas verified by the results of 2016. The ratios of CIpto the upper and lower limits of conventional reference in-terval were calculated. Results The values of CIλwere as follows: TP: 0.91 to 1.08, Alb: 0.91 to 1.08, T-Bil: 0.58 to 1.74, ALT:0.49 to 1.99, Glu: 0.84 to 1.20, Urea: 0.67 to 1.50, Cr: 0.82 to 1.22, UA: 0.77 to 1.32, TG: 0.51 to 1.98 and TC: 0.80 to 1.26. Compared with conventional reference interval, the ratio of the upper and lower limits of CIp was lessened. Conclusion The personal-ized reference interval (CIp) which may increase the sensitivity of conventional reference intervals was established and verified.
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Objective To establish and verify the personalized reference interval of blood cells.Methods The results of blood cells from 2 089 health subjects in 2014,2015 and 2016 were collected.The ratio of the later results to the previous results was defined as the fluctuation (λ).The ratio (λ1) of the results of 2015 to the results of 2014 was calculated and λ1 was analyzed statistically to establish the fluctuation reference interval (CIλ).The ratio (λ2) of the results of 2016 to the results of 2015 was calculated.λ2 was used to verify λ2.The personalized reference interval (CIp) was established by multiplying each result of 2015 and CIλ.CIp was verified by results of 2016.The ratio of the upper and lower limits of CIp was calculated.The ratio of the upper and lower limits of the reference interval (WS/T 405) was calculated.Results The values of CIλ were as follows:WBC (0.66 to 1.53),L(0.67 to 1.51),M (0.50 to 2.00),N(0.56 to 1.78),E(0.4 to 2.51),PLT(0.76 to 1.32),RBC(0.92 to 1.12),Hb(0.92 to 1.11),Hct(0.91 to 1.12),MCV(0.95 to 1.07),MCH(0.95 to 1.05)and MCHC(0.94 to 1.06).The validation tests of CIλ and CIp showed that both CIλ and CIp were suitable for this laboratory.Compared with the reference interval of professional criteria,the ratio of the upper and lower limits of the CIp was smaller than that of traditional criteria.Conclusion CIp for this laboratory was established and verified.Compared with traditional criteria,CIp should be more personalized and highly sensitive.