For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
24
views
37
references
 Top references
cited by
1
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
2 collections
    0
    shares
      53
      similar
       All similar

          The flagship journal of the Society for Endocrinology. Learn more

      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Development and validation of a risk score model for prediction of lower extremity arterial disease in Chinese with type 2 diabetes aged over 50 years

      research-article

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Lower extremity arterial disease (LEAD) is highly prevalent in people with diabetes in China, but half of cases are underdiagnosed due to diversities of clinical presentations and complexities of diagnosis approaches. The purpose of this study was to develop a risk score model for LEAD to facilitate early screening among type 2 diabetes (T2DM) patients.

          Methods

          A total of 8313 participants with T2DM from the China DIA-LEAD study, a multicenter, cross-sectional epidemiological study, were selected as the training dataset to develop a risk score model for LEAD by logistic regression. The area under receiver operating characteristic curve (AUC) and bootstrapping were utilized for internal validation. A dataset of 287 participants consecutively enrolled from a teaching hospital between July 2017 and November 2017 was used as external validation for the risk score model.

          Results

          A total of 931 (11.2%) participants were diagnosed as LEAD in the training dataset. Factors including age, current smoking, duration of diabetes, blood pressure control, low density lipoprotein cholesterol, estimated glomerular filtration rate, and coexistence of cardio and/or cerebrovascular disease correlated with LEAD in logistic regression analysis and resulted in a weighed risk score model of 0–13. A score of ≥5 was found to be the optimal cut-off for discriminating moderate–high risk participants with AUC of 0.786 (95% CI: 0.778–0.795). The bootstrapping validation showed that the AUC was 0.784. Similar performance of the risk score model was observed in the validation dataset with AUC of 0.731 (95% CI: 0.651–0.811). The prevalence of LEAD was 3.4, 12.1, and 27.6% in the low risk (total score 0–4), moderate risk (total score 5–8), and high risk (total score 9–13) groups of LEAD in the training dataset, respectively, which were 4.3, 19.6, and 30.2% in the validation dataset.

          Conclusion

          The weighed risk score model for LEAD could reliably discriminate the presence of LEAD in Chinese with T2DM aged over 50 years, which may be helpful for a precise risk assessment and early diagnosis of LEAD.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: found
          • Article: not found

          A new equation to estimate glomerular filtration rate.

          Andrew Levey, Lesley Stevens, Christopher H Schmid … (2009)
          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
          Article 0 comments Cited 6100 times – based on 0 reviews     Review now
            • Record: found
            • Abstract: found
            • Article: not found

            General cardiovascular risk profile for use in primary care: the Framingham Heart Study.

            Ralph B. D’Agostino, Ramachandran S Vasan, Michael J Pencina … (2008)
            Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
            Article 0 comments Cited 2509 times – based on 0 reviews     Review now
              • Record: found
              • Abstract: found
              • Article: not found

              Comparison of global estimates of prevalence and risk factors for peripheral artery disease in 2000 and 2010: a systematic review and analysis.

              F. Fowkes, Diana Rudan, Igor Rudan … (2013)
              Lower extremity peripheral artery disease is the third leading cause of atherosclerotic cardiovascular morbidity, following coronary artery disease and stroke. This study provides the first comparison of the prevalence of peripheral artery disease between high-income countries (HIC) and low-income or middle-income countries (LMIC), establishes the primary risk factors for peripheral artery disease in these settings, and estimates the number of people living with peripheral artery disease regionally and globally. We did a systematic review of the literature on the prevalence of peripheral artery disease in which we searched for community-based studies since 1997 that defined peripheral artery disease as an ankle brachial index (ABI) lower than or equal to 0·90. We used epidemiological modelling to define age-specific and sex-specific prevalence rates in HIC and in LMIC and combined them with UN population numbers for 2000 and 2010 to estimate the global prevalence of peripheral artery disease. Within a subset of studies, we did meta-analyses of odds ratios (ORs) associated with 15 putative risk factors for peripheral artery disease to estimate their effect size in HIC and LMIC. We then used the risk factors to predict peripheral artery disease numbers in eight WHO regions (three HIC and five LMIC). 34 studies satisfied the inclusion criteria, 22 from HIC and 12 from LMIC, including 112,027 participants, of which 9347 had peripheral artery disease. Sex-specific prevalence rates increased with age and were broadly similar in HIC and LMIC and in men and women. The prevalence in HIC at age 45-49 years was 5·28% (95% CI 3·38-8·17%) in women and 5·41% (3·41-8·49%) in men, and at age 85-89 years, it was 18·38% (11·16-28·76%) in women and 18·83% (12·03-28·25%) in men. Prevalence in men was lower in LMIC than in HIC (2·89% [2·04-4·07%] at 45-49 years and 14·94% [9·58-22·56%] at 85-89 years). In LMIC, rates were higher in women than in men, especially at younger ages (6·31% [4·86-8·15%] of women aged 45-49 years). Smoking was an important risk factor in both HIC and LMIC, with meta-OR for current smoking of 2·72 (95% CI 2·39-3·09) in HIC and 1·42 (1·25-1·62) in LMIC, followed by diabetes (1·88 [1·66-2·14] vs 1·47 [1·29-1·68]), hypertension (1·55 [1·42-1·71] vs 1·36 [1·24-1·50]), and hypercholesterolaemia (1·19 [1·07-1·33] vs 1·14 [1·03-1·25]). Globally, 202 million people were living with peripheral artery disease in 2010, 69·7% of them in LMIC, including 54·8 million in southeast Asia and 45·9 million in the western Pacific Region. During the preceding decade the number of individuals with peripheral artery disease increased by 28·7% in LMIC and 13·1% in HIC. In the 21st century, peripheral artery disease has become a global problem. Governments, non-governmental organisations, and the private sector in LMIC need to address the social and economic consequences, and assess the best strategies for optimum treatment and prevention of this disease. Peripheral Arterial Disease Research Coalition (Europe). Copyright © 2013 Elsevier Ltd. All rights reserved.
              Article 0 comments Cited 593 times – based on 0 reviews     Review now
                All references

                Author and article information

                Journal
                Journal ID (nlm-ta): Endocr Connect
                Journal ID (iso-abbrev): Endocr Connect
                Journal ID (hwp): EC
                Title: Endocrine Connections
                Publisher: Bioscientifica Ltd (Bristol )
                ISSN (Electronic): 2049-3614
                Publication date (Electronic): 20 August 2021
                Publication date Collection: 01 September 2021
                Volume: 10
                Issue: 9
                Pages: 1212-1220
                Affiliations
                [1 ]Department of Endocrinology, Peking University International Hospital , Beijing, China
                [2 ]Diabetes Center , Characteristic Medical Center of Strategic Support Force, Beijing, China
                [3 ]Department of Endocrinology and Metabolism , West China Hospital, Sichuan University, Chengdu, China
                [4 ]Department of Endocrinology and Metabolism , Peking University People’s Hospital, Beijing, China
                Author notes
                Correspondence should be addressed to X Ran or L Ji: ranxingwu@ 123456163.com or jilinong@ 123456pkuih.edu.cn
                Article
                Publisher ID: EC-21-0152
                DOI: 10.1530/EC-21-0152
                PMC ID: 8494415
                PubMed ID: 34424851
                SO-VID: bda95300-6b77-4559-9c5a-e07ea58eb036
                Copyright © © The authors
                License:

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                Date received : 12 August 2021
                Date accepted : 20 August 2021
                Categories
                Subject: Research

                Keywords: type 2 diabetes,lower extremity arterial disease,risk score model
                Data availability:
                Keywords: type 2 diabetes, lower extremity arterial disease, risk score model

                Comments

                Comment on this article

                Related Documents Log
                scite_

                Similar content53

                See all similar

                Cited by1

                See all cited by

                Most referenced authors1,166

                See all reference authors