The Performance of a Risk Score in Predicting Undiagnosed Hyperglycemia

Park, P.J.; Griffin, Simon J.; Sargeant, Lincoln A.; Wareham, Nick

doi:10.2337/diacare.25.6.984

Cited by 85 publications

(76 citation statements)

References 31 publications

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“…In cross-sectional studies conducted in the USA and Europe, prediction models based on clinical information and lifestyle-related factors have appeared to be useful for identifying undiagnosed diabetes cases and high HbA 1c levels in screening populations [7,8,38,39]. For example, the Cambridge model has been applied successfully to identify individuals with high HbA 1c levels [9,10]. In addition, a recent cohort study showed that the Cambridge model was useful for identifying individuals with a higher [3], PROCAM [30], San Antonia [13] and Framingham models [5], were developed to predict incident diabetes in different populations.…”

Section: Discussionmentioning

confidence: 99%

“…The standard-error estimates and the confidence intervals were obtained based on 1,000 bootstrap samples. Finally, we compared the performance of the proposed prediction model with that of various prediction models derived from other populations, including Cambridge [8][9][10], Prospective Cardiovascular Münster (PROCAM) [30], San Antonia [13,14] and Framingham [5]. AUC was used to compare the discriminatory capabilities of these models and our simple points model.…”

Section: Measurement Of Biochemical Markersmentioning

confidence: 99%

“…The prediction models for the risk of diabetes can help to guide screening and interventions and to predict diabetes occurrence [3][4][5]. Routinely available and easily collected clinical and lifestyle-related information has been found to be effective for identifying diabetes cases [6][7][8][9][10][11][12]. In addition, a prediction model has been developed in Mexican Americans [13] and further tested in Japanese Americans [14].…”

Section: Introductionmentioning

confidence: 99%

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A prediction model for type 2 diabetes risk among Chinese people

et al. 2008

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Aims/hypothesis A range of prediction rules for the onset of type 2 diabetes have been proposed. However, most studies have been conducted in white groups and it is not clear whether these models apply to Asian populations. The purpose of this study was to construct a simple points model for predicting incident diabetes among Chinese people.Methods We estimated the 10 year risk of diabetes in a cohort study of middle-aged and elderly participants who were free from diabetes at baseline. Cox regression coefficients were used to construct the simple points model and the discriminatory ability of the resulting prediction rule was determined using AUC and net reclassification improvement and integrated discrimination improvement statistics. Fivefold random splitting was used to test the internal validity and obtain bootstrap estimates of the AUC. Results Of the 2,960 participants without diabetes at the baseline examination, 548 developed type 2 diabetes during a median 10 year follow-up period. Age (four points), elevated fasting glucose (11 points), body mass index (eight points), triacylglycerol (five points), white blood cell count (four points) and a higher HDL-cholesterol (negative four points) were found to strongly predict diabetes incidence in a multivariate model. The estimated AUC for the model was 0.702 (95% CI 0.676-0.727). This model performed better than existing prediction models developed in other populations, including the Prospective Cardiovascular Münster, Cambridge, San Antonia and Framingham models for diabetes risk. Conclusions/interpretation We have constructed a model for predicting the 10 year incidence of diabetes in Chinese people that could be useful for identifying individuals at high risk of diabetes in the Chinese population.

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Section: Discussionmentioning

confidence: 99%

Section: Measurement Of Biochemical Markersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A prediction model for type 2 diabetes risk among Chinese people

et al. 2008

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“…Age constitutes a factor of independent predictive value for chronic illnesses, and is also used as a parameter to classify a person's risk for the development of nondiagnosed hyperglycemia (21) .…”

Section: Discussionmentioning

confidence: 99%

Occupation and risk factors for type 2 diabetes: a study with health workers

Almeida

Zanetti

Almeida

et al. 2011

Rev. Latino-Am. Enfermagem

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We aimed to analyze the interrelationships between occupation and prevalence of risk factors for type 2 diabetes in workers at a hospital in Fortaleza-CE. Cross-sectional study with 299 subjects and form-based, covering socio-demographic concerns and risk factors for Type 2 Diabetes. Results showed that 40.5% of the sample were nursing workers, 63.9% were women, 68.6% were under 35 years of age, 49.5% had an education level equivalent to high school and 51.9% had no marriage or stable union. Comparison among the prevalence of risk factors in different occupations was significant (p<0.05) for the following factors:abdominal obesity, waist-hip ratio increased, sedentary lifestyle and HDL-cholesterol <35 mg/dl, and the nursing workers showed higher prevalence levels for these three factors.Hence, within the study context, nursing workers are at an increased risk for developing diabetes in comparison with other health professionals. Ocupación y factores de riesgo para diabetes tipo 2: un estudio en trabajadores de enfermeríaSe tuvo por objetivo analizar las interrelaciones entre ocupación y prevalencia de factores de riesgo para Diabetes Tipo 2. Participaron 299 sujetos trabajadores de un hospital público de Fortaleza, estado de Ceará. Para la recolección de datos se utilizó un formulario, contemplando variables sociodemográficas y relativas a los factores de riesgo para Diabetes Tipo 2. Se verificó que 40,5% eran trabajadores de enfermería, 63,9% mujeres, 68,6% tenían menos de 35 años, 49,5% tenían escolaridad equivalente a la enseñanza media y el 51,9% no poseía vínculo matrimonial o de unión estable. La comparación de la prevalencia de los factores de riesgo en las diferentes ocupaciones fue significativa (p<0,05) para los siguientes factores: obesidad abdominal, relación cintura/cadera aumentada, sedentarismo, tabaquismo y HDL colesterol < 35 mg/dl, siendo que los trabajadores de enfermería presentaron mayor prevalencia para 3 de esos factores. Se concluye que los trabajadores de enfermería presentaron mayor riesgo para desarrollar diabetes mellitus que los demás profesionales de salud.

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“…Hal ini sesuai dengan teori yang mengatakan bahwa mereka dengan usia lebih dari 45 tahun adalah kelompok usia yang berisiko menderita DM.8 Lebih lanjut dikatakan bahwa DM merupakan penyakit yang terjadi akibat penurunan fungsi organ tubuh (degeneratif) terutama gangguan organ pangkreas dalam menghasilkan hormon insulin, sehingga DM akan meningkat kasusnya sejalan dengan pertambahan usia. 9 Hasil penelitian ini sejalan dengan penelitian sebelumnya di Jakarta 10 dan di Padang 11 , menunjukkan bahwa kelompok umur 50-60 tahun (di atas 45 tahun) adalah kelompok yang terbanyak menderita DM dibanding kelompok umur di bawahnya. Angka kasus DM akan meningkat sesuai dengan pertambahan usia.…”

Section: Pendahuluanunclassified

Mengenali Faktor-Faktor Risiko Pasien Diabetes Melitus

Sentosa

2016

Intisari Sains Medis

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Results: There was association between several risk factors and incidence of DM, include; age [odds ratio (OR) = 6, 45; p= 0,000, PAR= 0, 84], family history of DM (OR= 3, 75; p = 0,001, PAR= 0, 73), knowledge about DM (OR= 0, 13; p = 0,000, PAR= -6, 7/as a protective factor). However, there was evidence of a no association between type of personality and incidence of DM (OR= 50.4; p = 0,479, PAR= 0, 98) and also dietary habits (OR= 1, 06; p = 0,896, PAR= 0 06) Conclusion: These findings suggest a complex interaction among age factor, family history of diabetes, knowledge about DM, dietary habits and type of personality with the incidence of DM in Regional Hospital of Karangasem Bali Province. Keywords: risk factors, diabetes mellitus, type of personality PENDAHULUAN Diabetes Melitus (DM) pada saat ini merupakan salah satu masalah kesehatan yang berdampak pada produktivitas dan menurunkan mutu sumber daya manusia. Penderita DM di seluruh dunia pada tahun 2025 berkisar 333 juta orang (5,4%). Berdasarkan catatan organisasi kesehatan dunia tahun 1998, Indonesia menduduki peringkat keenam dengan jumlah penderita diabetes terbanyak setelah India, Cina, Rusia, Jepang, dan Brasil.1 Penderita DM di Indonesia semakin meningkat. Hal ini dapat diketahui bahwa pada tahun 1995 terdapat lebih kurang 5 juta penderita DM di Indonesia dengan peningkatan sekitar 230 ribu penderita setiap tahun, sehingga pada tahun 2025 penderita diabetes di Indonesia diperkirakan akan mencapai 12 juta orang. Peningkatan terjadi akibat bertambahnya populasi penduduk usia lanjut dan perubahan gaya hidup, mulai dari pola makan/jenis makanan yang dikonsumsi sampai berkurangnya kegiatan jasmani. Hal ini terjadi terutama pada kelompok usia dewasa ke atas pada seluruh status sosial-ekonomi. 2 Selain itu, peningkatan jumlah kasus DM terjadi karena kurangnya tenaga kesehatan, peralatan pemantauan

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The Performance of a Risk Score in Predicting Undiagnosed Hyperglycemia

Cited by 85 publications

References 31 publications

A prediction model for type 2 diabetes risk among Chinese people

A prediction model for type 2 diabetes risk among Chinese people

Occupation and risk factors for type 2 diabetes: a study with health workers

Mengenali Faktor-Faktor Risiko Pasien Diabetes Melitus

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