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  • Li, WeiSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)

Non-lab and semi-lab algorithms for screening undiagnosed diabetes : A cross-sectional study

  • Artikel/kapitelEngelska2018

Förlag, utgivningsår, omfång ...

  • ELSEVIER SCIENCE BV,2018
  • electronicrdacarrier

Nummerbeteckningar

  • LIBRIS-ID:oai:DiVA.org:uu-363628
  • https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-363628URI
  • https://doi.org/10.1016/j.ebiom.2018.08.009DOI

Kompletterande språkuppgifter

  • Språk:engelska
  • Sammanfattning på:engelska

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Klassifikation

  • Ämneskategori:ref swepub-contenttype
  • Ämneskategori:art swepub-publicationtype

Anmärkningar

  • Background: The terrifying undiagnosed rate and high prevalence of diabetes have become a public emergency. A high efficiency and cost-effective early recognition method is urgently needed. We aimed to generate innovative, user-friendly nomograms that can be applied for diabetes screening in different ethnic groups in China using the non-lab or noninvasive semi-lab data. Methods: This multicenter, multi-ethnic, population-based, cross-sectional study was conducted in eight sites in China by enrolling subjects aged 20-70. Sociodemographic and anthropometric characteristics were collected. Blood and urine samples were obtained 2 h following a standard 75 g glucose solution. In the final analysis, 10,794 participants were included and randomized into model development (n - 8096) and model validation (n = 2698) group with a ratio of 3:1. Nomograms were developed by the stepwise binary logistic regression. The nomograms were validated internally by a bootstrap sampling method in the model development set and externally in the model validation set. The area under the receiver operating characteristic curve (AUC) was used to assess the screening performance of the nomograms. Decision curve analysis was applied to calculate the net benefit of the screening model. Results: The overall prevalence of undiagnosed diabetes was 9.8% (1059/10794) according to ADA criteria. The non-lab model revealed that gender, age, body mass index, waist circumference, hypertension, ethnicities, vegetable daily consumption and family history of diabetes were independent risk factors for diabetes. By adding 2 h post meal glycosuria qualitative to the non-lab model, the semi-lab model showed an improved Akaike information criterion (AIC: 4506 to 3580). The AUC of the semi-lab model was statistically larger than the non-lab model (0.868 vs 0.763, P < 0.001). The optimal cutoff probability in semi-lab and non-lab nomograms were 0.088 and 0.098, respectively. The sensitivity and specificity were 76.3% and 81.6%, respectively in semi-lab nomogram, and 72.1% and 673% in non-lab nomogram at the optimal cut off point. The decision curve analysis also revealed a bigger decrease of avoidable OGTT test (52 per 100 subjects) in the semi-lab model compared to the non-lab model (36 per 100 subjects) and the existed New Chinese Diabetes Risk Score (NCDRS, 35 per 100 subjects). Conclusion: The non-lab and semi-lab nomograms appear to be reliable tools for diabetes screening, especially in developing countries. However, the semi-lab model outperformed the non-lab model and NCDRS prediction systems and might be worth being adopted as decision support in diabetes screening in China.

Ämnesord och genrebeteckningar

Biuppslag (personer, institutioner, konferenser, titlar ...)

  • Xie, BoSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Qiu, ShanhuSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Huang, XinSoutheast Univ, Sch Publ Hlth, Nanjing, Jiangsu, Peoples R China (författare)
  • Chen, JuanSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Wang, XinlingPeoples Hosp Xinjiang Uyghur Autonomous Reg, Dept Endocrinol, Urumqi, Peoples R China (författare)
  • Li, HongKunming Med Univ, Affiliated Hosp 1, Dept Endocrinol, Kunming, Yunnan, Peoples R China (författare)
  • Chen, QingyunGuangxi Med Univ, Affiliated Hosp 1, Dept Endocrinol, Nanning, Peoples R China (författare)
  • Wang, QingJilin Univ, China Japan Union Hosp, Dept Endocrinol, Changchun, Jilin, Peoples R China (författare)
  • Tu, PingThird Hosp Nanchang, Dept Endocrinol, Nanchang, Jiangxi, Peoples R China (författare)
  • Zhang, LihuiHebei Med Univ, Hosp 2, Dept Endocrinol, Shijiazhuang, Hebei, Peoples R China (författare)
  • Yan, SunjieFujian Med Univ, Affiliated Hosp 1, Diabet Res Inst, Dept Endocrinol, Fuzhou, Fujian, Peoples R China (författare)
  • Li, KailiXinjiang Uygur Autonomous Reg Hosp Tradit Chinese, Dept Endocrinol, Urumqi, Peoples R China (författare)
  • Maimaitiming, JimilanmuPeoples Hosp Xinjiang Uyghur Autonomous Reg, Dept Endocrinol, Urumqi, Peoples R China (författare)
  • Nian, XinKunming Med Univ, Affiliated Hosp 1, Dept Endocrinol, Kunming, Yunnan, Peoples R China (författare)
  • Liang, MinGuangxi Med Univ, Affiliated Hosp 1, Dept Endocrinol, Nanning, Peoples R China (författare)
  • Wen, YanJilin Univ, China Japan Union Hosp, Dept Endocrinol, Changchun, Jilin, Peoples R China (författare)
  • Liu, Jiang (författare)
  • Wang, MianHebei Med Univ, Hosp 2, Dept Endocrinol, Shijiazhuang, Hebei, Peoples R China (författare)
  • Zhang, YongzeFujian Med Univ, Affiliated Hosp 1, Diabet Res Inst, Dept Endocrinol, Fuzhou, Fujian, Peoples R China (författare)
  • Ma, LiXinjiang Uygur Autonomous Reg Hosp Tradit Chinese, Dept Endocrinol, Urumqi, Peoples R China (författare)
  • Wu, HangSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Wang, XuyiSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Wang, XiaohangSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Liu, JingbaoSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Cai, MinSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Wang, ZhiyaoSuzhou MetroHlth Med Technol Co LTD, Suzhou, Peoples R China (författare)
  • Guo, LinSuzhou MetroHlth Med Technol Co LTD, Suzhou, Peoples R China (författare)
  • Chen, FangqunSuzhou MetroHlth Med Technol Co LTD, Suzhou, Peoples R China (författare)
  • Wang, BeiSoutheast Univ, Sch Publ Hlth, Nanjing, Jiangsu, Peoples R China (författare)
  • Sandberg, MonicaUppsala universitet,Institutionen för medicinsk cellbiologi(Swepub:uu)mosan330 (författare)
  • Carlsson, Per-OlaUppsala universitet,Institutionen för medicinsk cellbiologi(Swepub:uu)perocarl (författare)
  • Sun, ZilinSoutheast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R China (författare)
  • Southeast Univ, Sch Med, Inst Diabet, Dept Endocrinol,Zhongda Hosp, Nanjing, Jiangsu, Peoples R ChinaSoutheast Univ, Sch Publ Hlth, Nanjing, Jiangsu, Peoples R China (creator_code:org_t)

Sammanhörande titlar

  • Ingår i:EBioMedicine: ELSEVIER SCIENCE BV35, s. 307-3162352-3964

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