Cardiovascular risk prediction model for Omanis with type 2 diabetes

Alrawahi, Abdul Hakeem; Lee, Patricia; Al-Anqoudi, Zahir M.; Alrabaani, Muna; Almahrouqi, Faisal; Al-Busaidi, Ahmed

doi:10.1016/j.dsx.2017.09.012

Cited by 6 publications

(28 citation statements)

References 17 publications

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“…Separate models by D'Agostino et al (Framingham Stroke Risk Score),37 Yang et al (Hong Kong Diabetes Registry for Stroke),38 Kiadaliri et al ,22 Stevens et al (UKPDS 66),24 Hippisley-Cox et al (QRISK2),39 Elley et al (New Zealand Diabetes Cohort Study)40 and Alrawahi et al 41 were each validated in one external or separate cohort with sample sizes ranging from 178 to 1 81 399 patients. For the studies that reported discrimination, C-statistics ranged from 0.67 to 0.79.…”

Section: Resultsmentioning

confidence: 99%

Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics

et al. 2019

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ObjectiveStroke is a major cause of disability and death worldwide. People with diabetes are at a twofold to fivefold increased risk for stroke compared with people without diabetes. This study systematically reviews the literature on available stroke prediction models specifically developed or validated in patients with diabetes and assesses their predictive performance through meta-analysis.DesignSystematic review and meta-analysis.Data sourcesA detailed search was performed in MEDLINE, PubMed and EMBASE (from inception to 22 April 2019) to identify studies describing stroke prediction models.Eligibility criteriaAll studies that developed stroke prediction models in populations with diabetes were included.Data extraction and synthesisTwo reviewers independently identified eligible articles and extracted data. Random effects meta-analysis was used to obtain a pooled C-statistic.ResultsOur search retrieved 26 202 relevant papers and finally yielded 38 stroke prediction models, of which 34 were specifically developed for patients with diabetes and 4 were developed in general populations but validated in patients with diabetes. Among the models developed in those with diabetes, 9 reported their outcome as stroke, 23 reported their outcome as composite cardiovascular disease (CVD) where stroke was a component of the outcome and 2 did not report stroke initially as their outcome but later were validated for stroke as the outcome in other studies. C-statistics varied from 0.60 to 0.92 with a median C-statistic of 0.71 (for stroke as the outcome) and 0.70 (for stroke as part of a composite CVD outcome). Seventeen models were externally validated in diabetes populations with a pooled C-statistic of 0.68.ConclusionsOverall, the performance of these diabetes-specific stroke prediction models was not satisfactory. Research is needed to identify and incorporate new risk factors into the model to improve models’ predictive ability and further external validation of the existing models in diverse population to improve generalisability.

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Section: Resultsmentioning

confidence: 99%

Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics

et al. 2019

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“…Although a previous study had developed a CVD risk assessment tool for Omani nationals, their study cohort consisted exclusively of patients with type 2 diabetes and the follow-up period was relatively shorter at 5 years. 33 Therefore, this nomogram is the first 10-year CVD risk assessment tool that has been empirically developed and validated using long-term follow-up data from an Arab population. However, this study has several limitations.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, a relatively large patient cohort representing approximately 1% of the adult UAE national population in Al-Ain city and high-quality data were used for model development and validation. Although a previous study had developed a CVD risk assessment tool for Omani nationals, their study cohort consisted exclusively of patients with type 2 diabetes and the follow-up period was relatively shorter at 5 years 33. Therefore, this nomogram is the first 10-year CVD risk assessment tool that has been empirically developed and validated using long-term follow-up data from an Arab population.…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a novel 10-year cardiovascular risk prediction nomogram for the United Arab Emirates national population

Al-Shamsi

2022

BMJ Open

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ObjectivesAtherosclerotic cardiovascular disease (ASCVD) is the leading cause of morbidity and mortality among United Arab Emirates (UAE) nationals. Recent studies have shown that current tools are poor in predicting the risk of incident ASCVD in Emiratis. To improve ASCVD risk prediction in this high-risk population, this study sought to develop and validate a novel and practical 10-year ASCVD risk nomogram using risk factors known to be significant in UAE nationals.DesignA 10-year retrospective cohort study.SettingOutpatient clinics at a large public tertiary care hospital in Al-Ain, UAE.ParticipantsEmiratis aged ≥18 years without prior cardiovascular disease (CVD) who had presented to Tawam Hospital’s clinics between 1 April 2008 and 31 December 2008, were included. Patients’ data were collected retrospectively until 31 January 2020.ExposureCox proportional hazards models were developed to estimate the 10-year ASCVD risk.Primary outcome measureModel discrimination and calibration were assessed using the Harrell C-statistic and the Greenwood-Nam-D’Agostino (GND) χ2test, respectively. Receiver operating characteristic curve analysis was used to determine the optimal cut-off point of the nomogram for elevated ASCVD risk.ResultsThe study included 1245 patients, of whom 117 developed ASCVD within 10 years. The ASCVD risk nomogram comprised age, sex, family history of CVD, hypertension treatment, systolic blood pressure, total cholesterol, glycosylated haemoglobin A1c and estimated glomerular filtration rate. The Harrell C-statistic was 0.826 and the GND χ2was 2.83 (p=0.830), which indicated good discrimination and calibration of the nomogram model, respectively. The optimal cut-off point was determined to be 10% (sensitivity=79%; specificity=77%). The nomogram can be freely accessed as an online calculator at (https://ascvdriskuae.shinyapps.io/ASCVDrisk/).ConclusionsThe developed nomogram provides an accurate prognostic tool for 10-year ASCVD risk prediction in UAE nationals. These findings may help guide future research on CVD prevention in this high-risk population.

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“…These scoring models were selected because they have already been used in cohort studies with robust samples 8,9,[11][12][13][14] , including patients with DM.…”

Section: Cardiovascular Risk Scoring Modelsmentioning

confidence: 99%

Comparison of cardiovascular risk calculators in patients with diabetes

Ribeiro

Amorim

Cardoso

et al. 2021

Rev. Assoc. Med. Bras.

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OBJECTIVE: Cardiovascular risk stratification is an important clinical practice to estimate the severity of cardiovascular disease in patients with type 2 diabetes. This study aimed to compare the stratification of global cardiovascular risk with the specific risk stratification for patients with type 2 diabetes, seen at specialized outpatient clinics, and to evaluate possible differences in diagnoses and treatments.METHODS: A total of 122 patients with type 2 diabetes treated at two specialized outpatient clinics, from 2017 to 2019, were studied.The cardiovascular risk stratification calculators, global risk score, Cardiovascular Risk Stratification Calculator, and United Kingdom Prospective Diabetes Study-Risk Engine, were used to calculate the risk of death from cardiovascular disease. The agreement between these calculators was analyzed using the kappa index. The indications for the use of statins and acetylsalicylic acid for the group studied were evaluated according to the Brazilian Diabetes Society Guideline.RESULTS: There was a low degree of agreement among the three risk calculators. The global risk score calculator showed insignificant agreement with the Cardiovascular Risk Stratification Calculator (kappa=0.0816; p=0.0671). There was no agreement between the global risk score calculator and United Kingdom Prospective Diabetes Study-Risk Engine (kappa=-0.099), or between the Cardiovascular Risk Stratification Calculator and United Kingdom Prospective Diabetes Study-Risk Engine (kappa=-0.0095). CONCLUSION:The substantial disagreements among the cardiovascular risk calculators may lead to different diagnoses and may consequently influence therapeutic strategies. The findings herein highlight the need for specific validated cardiovascular risk calculators for patients with DM2 that can reliably estimate risk in these individuals.

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Cardiovascular risk prediction model for Omanis with type 2 diabetes

Cited by 6 publications

References 17 publications

Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics

Predicting the risk of stroke among patients with type 2 diabetes: a systematic review and meta-analysis of C-statistics

Development and validation of a novel 10-year cardiovascular risk prediction nomogram for the United Arab Emirates national population

Comparison of cardiovascular risk calculators in patients with diabetes

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