Lack of association of glycated haemoglobin with blood pressure and subclinical atherosclerosis in black South Africans: a five-year prospective study

Objectives: Hypertension and diabetes are common in rapidly urbanising sub-Saharan African communities. However, lack of longitudinal data in these regions prevents adequate analysis of the link between measures of glycaemia and cardiovascular disease. Therefore, we examined the relationships of fasting glucose and glycated haemoglobin (HbA1c) with brachial and central blood pressure (BP), and measures of vascular structure and function after five years in black South Africans.Setting and subjects: Nine hundred and twenty-eight participants were included as part of the Prospective Urban Rural Epidemiological (PURE) study in the North West Province.Outcome measures: Fasting glucose, HbA1c and brachial BP at two time points were determined. Central BP, augmentation index (AI) and carotid intima-media thickness (CIMT) were taken at follow-up.Results: Fasting glucose [4.78 (3.50, 6.30) vs. 5 mmol/l (3.96, 6.42)]; HbA1c [5.6 (4.9, 6.3) vs. 5.9% (5.2, 6.9) and (37 vs. 41 mmol/mol)]; and BP (134/88.1 vs. 138/89.5 mmHg) increased significantly over five years (p-value < 0.05). However, an association was absent between BP, AI or CIMT and either baseline or the five-year change in glucose or HbA,sub>1c. Multivariate analyses confirmed that neither glucose or HbA1c predicted changes in BP, CIMT or AI, but factors that did associate significantly were age, male gender, rural location, abdominal obesity, alcohol intake, total cholesterol to high-density lipoprotein ratio, C-reactive protein and antihypertensive medication (R2, ranging from 0.24-0.36).Conclusion: Although both BP and measures of glycaemia increased significantly over five years in black South Africans, glucose was not independently associated with BP or measures of large artery structure or function. We suggest that fasting glucose and HbA1c below the threshold of diagnosing diabetes should not be used in isolation to predict cardiovascular risk in African individuals.Keywords: fasting glucose, glycated haemoglobin, ethnicity, atherosclerosis, longitudina

Homeostatic model assessment of insulin resistance as a predictor of metabolic syndrome: Consequences of obesity in children and adolescents

AbstractBackgroundObesity and/or insulin resistance have gained increasing attention as the core manifestations of metabolic syndrome.ObjectiveTo evaluate insulin resistance according to homeostasis model assessment of insulin resistance index HOMA-IR in obese children and adolescents with or without metabolic syndrome at risk of type 2 diabetes mellitus.Design and subjects60 obese children and adolescents were recruited, metabolic syndrome was diagnosed according to the modified WHO criteria adapted for children and adolescents. Insulin resistance was calculated using the HOMA-IR.ResultsMetabolic syndrome (MS) was found in 42 subjects (70%), using modified WHO guidelines for diagnosing MS. On comparing MS-related parameters between the groups with (MS+) and without metabolic syndrome (MS−), median body mass index, waist circumference, waist/height ratio, and blood pressure, total cholesterol and triglyceride were significantly higher in the MS+group. Basal insulin level as well as HOMA-IR was also significantly different between MS+ and MS-groups. The presence of insulin resistance according to HOMA-IR was identified in 53% of obese children and adolescents. This HOMA-IR age and sex limit was exceeded by 70% children in the MS+group, but only by 43% children in the MS-group (p<0.001). HOMA-IR was positively correlated with the majority of anthropometric and biochemical parameters. The correlation was strongest with body mass index, waist circumference and diastolic blood pressure.ConclusionsHOMA-IR might be a reliable surrogate measure of insulin resistance and a strong predictor of type 2 diabetes in obese adolescents allowing the development of preventive measures and treatment when needed

Gestational Diabetes Mellitus in Ghana: Validity of Screening Tests, Prevalence, Maternal Risk Factors and Pregnancy Outcomes

Background: Gestational diabetes is increasing globally. Studies from Sub-Saharan Africa have investigated the risk factors but reported prevalence is often based on one diagnostic test while short-term outcomes have scarcely been explored. In primary settings, gestational diabetes is tested after screen-positive glycosuria and/or presence of clinical risk factors. There is suspicion of missing cases due to likelihood of active hyperglycemia without detectable glycosuria and the wide profile of risk facts associated with gestational diabetes. Despite recent updates of diagnostic guidelines with lowered diagnostic cut-off in most cases, opinions are divided on the screening methods diagnostic cut-offs to apply, and whether to do selective screening followed by diagnostic testing of screen-positive cases vis-à-vis universal testing of all pregnant women. Objective: This study was conducted to address three overarching objectives: (1) validate the diagnostic validity of screening tests for gestational diabetes and estimate the proportion of cases that could be missed if selective screening is applied; (2) estimate the prevalence of gestational diabetes and assess the risk factors; and (3) assess the pregnancy outcomes including the extent of attainment of euglycemia at 12 weeks postpartum. Materials and methods: This study employed blind-comparison-to-the-gold-standard and case-control designs embedded in a prospective cohort study. Singleton non-diabetic singleton pregnant women (n=807) were recruited in the first trimester from five state-owned hospitals serving rural and peri-urban communities in Ghana. They were all screened for gestational diabetes from 13-20 weeks using dipstick glycosuria, random glucose and clinical risk factor assessment. Between 20-34 weeks, 491 pregnant women were tested for gestational diabetes using glycated hemoglobin, fasting glucose, 1-hour and the ‘gold standard’ 2-hour oral glucose tolerance test following the universal ‘one-step’ approach. Dietary and obstetric history were assessed retrospectively while physiologic measurements were repeated throughout pregnancy. Case definition was fasting ≥5.6 mmol/L and/or 2-hour postprandial glucose ≥8.5 mmol/L. Short-term outcomes of 403 and 100 women were traced at delivery and 12 weeks postpartum respectively. Validity of test instruments were estimated using standard disease measures. Adjusted odds ratio for gestational diabetes and relative risk for adverse birth outcomes were estimated by logistic regressions. Results: Fasting plasma glucose had the highest diagnostic validity among all the screening and diagnostic tests evaluated. Fasting glucose cut-off ≥5.1 mmol/L threshold had the highest clinically relevant sensitivity and specificity but the ≥5.6 mmol/L threshold had higher disease prediction. Selective screening using glycosuria, random glucose and risk factors missed 97.4%, 87.2% and 45.7% of cases respectively. Using the area under the curve to determine the diagnostic accuracy and test performance, fasting and 1-hour postprandial glucose tests were found to be very good, random glucose was poor whereas glycated hemoglobin was not diagnostically useful. Depending on the diagnostic test and cut-off used, 5-27% of participants were diagnosed with gestational diabetes. Overall 15.9% met the case definition; prevalence per 2-hour postprandial glucose ≥8.5 mmol/L was 9.0% and per fasting glucose ≥5.6 mmol/L was 10.8%; 3.9% were positive in both tests. Adjusted risk factors for gestational diabetes included high glycemic intake, obesity, previous Cesarean section and antenatal care in a primary facility. In terms of outcomes, a unit rise in blood glucose significantly increased maternal blood loss and fetal birthweight. Associated adverse birth outcomes were perineal tear and birth asphyxia. At 12 weeks postpartum, 30% of the diagnosed women did not achieve euglycemia. Conclusions and recommendations: Findings show rising gestational diabetes in the general population. Selective screening using glycosuria, random glucose and clinical risk factors are unnecessary due to their low diagnostic validity. Fasting glucose monitoring need to be integrated into all gestational diabetes detection protocols. Cut-off ≥5.1 mmol/L could be applicable for screening at the population level but to make therapeutic decision, cut-off ≥5.6 mmol/L is recommended where 2-hour oral glucose tolerance test is unavailable. Primary facilities need strengthening to test and refer cases. Diet and adiposity are key risk factors that necessitate lifestyle modifications with focus on nutrition education and weight control. Fetuses exposed to hyperglycemia uterine environment require quality obstetric care as birth asphyxia which is a key outcome is likely to compromise their survival. Follow-up on women diagnosed with gestational diabetes is crucial to avert transition into active diabetes. Cut-off values that would balance risks and benefits of adverse pregnancy and long-term outcomes is needed for the Ghanaian population. Physiologic interactions between fasting and oral glucose tolerance tests need further research. ZUSAMMENFASSUNG Hintergrund: Gestationsdiabetes steigt weltweit an. Studien aus Subsahara-Afrika untersuchen die Risikofaktoren; es gibt aber wenig Studien zur Prävalenz und diese basieren oft nur auf einem einzigen diagnostischen Test. Es gibt auch kaum Studien zur Nachverfolgung post partum. In primären Gesundheitseinrichtungen in Ghana beruht die Diagnose Gestationsdiabetes auf einem positiven Glykosurie-Test oder dem Vorhandensein klinischer Risikofaktoren. Vermutlich werden aber viele Fälle übersehen, bei denen eine aktive Hyperglykämie ohne feststellbare Glykosurie besteht. Trotz kürzlich angepasster internationaler Richtlinien für das Screening und die Diagnostik, mit in den meisten Fällen gesenkten Grenzwerten, sind die Meinungen bezüglich der Screening-Möglichkeiten nach wie vor gespalten zwischen einem universellen Screening aller schwangeren Frauen und einem selektiven Screening nach Risikobelastung. Darüber hinaus gibt es unterschiedliche Vorschläge für diagnostische Tests und deren Grenzwerte. Zielsetzung: Diese Studie wurde durchgeführt, um die folgenden drei Ziele zu erreichen: (1) die Validität von Tests zum Screening und zur Diagnose von Gestationsdiabetes in Ghana zu ermitteln, sowie den Anteil von Fällen einzuschätzen, die bei selektivem Screening übersehen werden; (2) (2) die Prävalenz von Gestationsdiabetes in Ghana zu ermitteln, sowie Risikofaktoren zu identifizieren und (3) (3) die kindlichen und mütterlichen Schwangerschaftsergebnisse, einschließlich der mütterlichen glykämischen Situation 12 Wochen postpartum zu untersuchen. Material und Methoden: Die vorliegende Studie ist eine Kohortenstudie mit eingebetteter Fall-Kontroll-Studie die Schwangere während der Schwangerschaft und bis zu 12 Wochen post partum einschließt. Nicht-diabetische Frauen mit einer Einlings-Schwangerschaft (n=807) wurden in ihrem ersten Trimester in fünf staatlichen Krankenhäusern, welche ländliche und halb-städtische Gemeinden in Ghana versorgen, rekrutiert. Sie wurden alle zwischen der 13. und 20. Schwangerschaftswoche auf Gestationsdiabetes untersucht, und zwar mittels Tests auf Glucosurie und Blutzucker. Ebenso wurde ein klinisches Risikoassessment gemacht. Zwischen der 20. und 34. Schwangerschaftswoche, wurden 491 schwangere Frauen nach dem „single-step“ Verfahren untersucht. Dabei wurden glykosyliertes Hämoglobin, Nüchtern-Blutzucker, oraler Glukosebelastungstest 1-Stunden-Wert und als „Goldstandard“ der 2-Stunden-Wert erhoben. Ernährungs- und geburtshilfliche Anamnesen wurden retrospektiv erhoben und bewertet. Die Falldefinition für Gestationsdiabetes lautete: Nüchtern-Blutzucker ≥ 5,6 mmol/L und/ oder 2-Stunden Wert nach oralem Glukosebelastungstest ≥ 8,5 mmol/L. Von 403 Frauen wurden die Geburtsergebnisse erfasst; 100 Frauen aus dieser Gruppe wurden zusätzlich nach 12 Wochen postpartum untersucht. Die adjustierten Odds Ratios für Gestationsdiabetes und für weitere Schwangerschaftskomplikationen wurden mittels logistischen Regression ermittelt. Ergebnisse: Nüchtern-Blutzucker im Plasma hatte die höchste diagnostische Validität von allen getesteten Screening- und Diagnostik-Tests. Nüchtern-Blutzucker-Grenzwerte von ≥5,1 mmol/L hatte die höchste klinisch relevante Spezifität, aber der Schwellenwert ≥5,6 mmol/L hatte einen höheren Krankheitsvorhersagewert. Selektive Screenings, welche mit Testen von Glykosurie, spontanen Blutzuckermessungen und Risikoprofilen durchgeführt wurden, verfehlten 97,4%, 87,2% beziehungsweise 45,7% der Fälle. Benutzt man die „area under the curve“, um die diagnostische Genauigkeit und die Leistung eines Tests zu bestimmen, ergaben der Nüchtern-Blutzucker und der 1-Stunde-Wert des Glukosebelastungstests die besten Ergebnisse. Spontane Blutzuckermessungen hingegen schnitten schlecht ab, während das glykolisierte Hämoglobin diagnostisch nicht brauchbar war. Abhängig davon, welcher diagnostische Test und welcher Grenzwert verwendet wurde, ergaben sich Prävalenzen von 5-27%. Unter Verwendung des eingangs genannten Goldstandards für diese Studie (Nüchtern-Blutzucker ≥ 5,6 mmol/L und/ oder 2-Stunden Wert nach oralem Glukosebelastungstest ≥ 8,5 mmol/L) ergab sich eine Prävalenz für Gestationsdiabetes von 15,9%: Die Prävalenz für den 2-Stundenwert des Glukosebelastungstests von ≥8,5 mmol/L war 9,0% und für den Nüchtern-Blutzucker ≥5,6 mmol/L war 10,8%; bei 3,9 % waren beide Tests positive. Die Risikofaktoren für Gestationsdiabetes beinhalteten großen Zuckerkonsum, Adipositas und vorhergehenden Sectio caesarea. Ein Anstieg der Glukose im Blut um eine Einheit hatte einen signifikanten Anstieg des mütterlichen Blutverlusts sowie des Geburtsgewichts des Neugeborenen zur Folge. Assoziierte ungünstige Geburtenergebnisse beinhalteten perineale Geburtsverletzungen und kindliche Asphyxie. Zwölf Wochen post partum hatten 30% der Frauen mit Gestationsdiabetes noch keine Euglykämie erreicht. Schlussfolgerung und Empfehlungen: Die Ergebnisse zeigen, dass die Prävalenz des Gestationsdiabetes in der Ghana zunimmt. Selektive Screening-Verfahren wie Glykosurie und spontane Blutzuckermessung sind wenig valide und unnötig. Die Nüchtern-Blutzucker-Überwachung sollte jedoch routinemäßig in die Schwangerenvorsorge integriert werden. Die Nüchtern-Blutzucker-Obergrenze von ≥5,1 mmol/L sollte in Ghana für Screenings der aller Schwangeren benutzt werden, um jedoch therapeutische Entscheidungen zu treffen, soll ein diagnostischer Grenzwert von ≥5,6 mmol/L gelten, falls kein oraler Glukosetoleranztest durchführbar ist. Primäre Gesundheitseinrichtungen sollten beim Screening und in der Überweisung von Gestationsdiabetes-Fällen unterstützt werden. Diabetogene Ernährung und Adipositas sind Hauptrisiken, welche eine Änderung des Lebensstils benötigen. Der Fokus der Beratung sollte in der Ernährung und der Gewichtskontrolle liegen. Feten welche intrauterinen Hyperglykämien ausgesetzt waren, brauchen eine spezialisierte Geburtshilfe, da Geburts-Asphyxien eine häufige Folge von Gestationsdiabetes sind und diese das Sterberisiko erhöhen. Es ist wichtig, Frauen mit Gestationsdiabetes nachzubetreuen, um zu verhindern bzw. zu erkennen, ob ein Gestationsdiabetes in einen manifesten Diabetes mellitus übergeht. Die spezifische klinische Wertigkeit von erhöhtem Nüchternblutzucker und pathologischem oralem Glukosetoleranztest im Kontext der Situation in Ghana sollte weiter untersucht werden

New Measure of Insulin Sensitivity Predicts Cardiovascular Disease Better than HOMA Estimated Insulin Resistance

10.1371/journal.pone.0074410PLoS ONE89-POLN

Framework to predict the metabolic syndrome without doing a blood test: based on machine learning for a clinical decision support system

Metabolic Syndrome (MetS) is a cluster of risk factors that increase the likelihood of heart disease and diabetes mellitus, and researchers have recently linked it to worse outcomes for the novel Covid-19 disease. It is crucial to get diagnosed with time to take preventive measures, especially for patients in locations without proper laboratories and medical consultations. This work presents a new model to diagnose metabolic syndrome using machine learning and non-biochemical variables that healthcare professionals can obtain from initial consultations. For evaluating and comparing the model, this work also proposes a new methodology for performing research on data mining called RAMAD. The methodology standardizes the novel model’s comparison with similar classification models, using their reported variables and previously obtained data from a study in Colombia, using the holdout and random subsampling validation methods to get performance evaluation indicators between the models. The resulting ANN model used three hidden layers and only Hip Circumference, dichotomous Waist Circumference, and dichotomous blood pressure variables. It gave an Area under Receiver Operating Characteristic curves (AROC) of 87.75% by the International Diabetes Federation (IDF) and 85.12% by Harmonized Diagnosis or Joint Interim Statement (HMS) diagnosis criteria, higher than previous models. Thanks to the new methodology, diagnosis models can be thoroughly documented for appropriate future comparisons, thus benefiting the studied diseases’ diagnosis. Medical personnel needs to know the factors involved in the syndrome to start a treatment. So, this work also presents the segmentation of metabolic syndrome in types related to each biochemical variable. It uses the RAMAD methodology together with several machine learning techniques to design a framework to predict MetS and their several types, without using a blood test and only anthropometric and clinical information. The results showed an excellent system for predicting six MetS types that combine several factors mentioned above that have an AROC with a range of 71% to 96%, and an AROC 82.86%. This thesis finishes with the proposal of using a SCRUM Thinking framework for creating mobile health applications to implement the new models and serve as decision tools for healthcare professionals. The standard and fundamental characteristics were analyzed, finding the quality attributes verified in the framework’s early stages. Keywords — Metabolic Syndrome, Segmentation, Quine–McCluskey, Random Subsampling validation, RAMAD, Machine learning, Framework, International Diabetes Federation (IDF), Harmonized Diagnosis or Joint Interim Statement (HMS).DoctoradoDoctor en Ingeniería de Sistemas y Computació

Association between noninvasive fibrosis markers and cardio-vascular organ damage among adults with hepatic steatosis

Evidence suggests that advanced fibrosis, as determined by the noninvasive NAFLD fibrosis score (NFS), is a predictor of cardiovascular mortality in individuals with ultrasonography-diagnosed NAFLD. Whether the severity of histology (i.e., fibrosis stage) is associated with more pronounced cardiovascular organ damage is unsettled. In this study, we analyzed the clinical utility of NFS in assessing increased carotid intima-media thickness (cIMT), and left ventricular mass index (LVMI). In this cross-sectional study NFS, cIMT and LVMI were assessed in 400 individuals with ultrasonography-diagnosed steatosis. As compared with individuals at low probability of liver fibrosis, individuals both at high and at intermediate probability of fibrosis showed an unfavorable cardio-metabolic risk profile having significantly higher values of waist circumference, insulin resistance, high sensitivity C-reactive protein (hsCRP), fibrinogen, cIMT, and LVMI, and lower insulin-like growth factor-1 (IGF-1) levels. The differences in cIMT and LVMI remained significant after adjustment for smoking and metabolic syndrome. In a logistic regression model adjusted for age, gender, smoking, and diagnosis of metabolic syndrome, individuals at high probability of fibrosis had a 3.9-fold increased risk of vascular atherosclerosis, defined as cIMT.0.9 mm, (OR 3.95, 95% CI 1.12–13.87) as compared with individuals at low probability of fibrosis. Individuals at high probability of fibrosis had a 3.5-fold increased risk of left ventricular hypertrophy (LVH) (OR 3.55, 95% CI 1.22–10.34) as compared with individuals at low probability of fibrosis. In conclusion, advanced fibrosis, determined by noninvasive fibrosis markers, is associated with cardiovascular organ damage independent of other known factors

Prediction model for high glycated hemoglobin concentration among ethnic Chinese in Taiwan

<p>Abstract</p> <p>Background</p> <p>This study aimed to construct a prediction model to identify subjects with high glycated hemoglobin (HbA1c) levels by incorporating anthropometric, lifestyle, clinical, and biochemical information in a large cross-sectional ethnic Chinese population in Taiwan from a health checkup center.</p> <p>Methods</p> <p>The prediction model was derived from multivariate logistic regression, and we evaluated the performance of the model in identifying the cases with high HbA1c levels (> = 7.0%). In total 17,773 participants (age > = 30 years) were recruited and 323 participants (1.8%) had high HbA1c levels. The study population was divided randomly into two parts, with 80% as the derivation data and 20% as the validation data.</p> <p>Results</p> <p>The point-based clinical model, including age (maximal 8 points), sex (1 point), family history (3 points), body mass index (2 points), waist circumference (4 points), and systolic blood pressure (3 points) reached an area under the receiver operating characteristic curve (AUC) of 0.723 (95% confidence interval, 0.677- 0.769) in the validation data. Adding biochemical measures such as triglycerides and HDL cholesterol improved the prediction power (AUC, 0.770 [0.723 - 0.817], <it>P </it>= < 0.001 compared with the clinical model). A cutoff point of 7 had a sensitivity of 0.76 to 0.96 and a specificity of 0.39 to 0.63 for the prediction model.</p> <p>Conclusions</p> <p>A prediction model was constructed for the prevalent risk of high HbA1c, which could be useful in identifying high risk subjects for diabetes among ethnic Chinese in Taiwan.</p

Proteomic signatures for identification of impaired glucose tolerance

The implementation of recommendations for type 2 diabetes (T2D) screening and diagnosis focuses on the measurement of glycated hemoglobin (HbA1c) and fasting glucose. This approach leaves a large number of individuals with isolated impaired glucose tolerance (iIGT), who are only detectable through oral glucose tolerance tests (OGTTs), at risk of diabetes and its severe complications. We applied machine learning to the proteomic profiles of a single fasted sample from 11,546 participants of the Fenland study to test discrimination of iIGT defined using the gold-standard OGTTs. We observed significantly improved discriminative performance by adding only three proteins (RTN4R, CBPM and GHR) to the best clinical model (AUROC = 0.80 (95% confidence interval: 0.79–0.86), P = 0.004), which we validated in an external cohort. Increased plasma levels of these candidate proteins were associated with an increased risk for future T2D in an independent cohort and were also increased in individuals genetically susceptible to impaired glucose homeostasis and T2D. Assessment of a limited number of proteins can identify individuals likely to be missed by current diagnostic strategies and at high risk of T2D and its complications

Accuracy and utility of fasting and stimulated glucose for diagnosis of diabetes in Sub-Saharan Africa

The oral glucose tolerance test (OGTT) is regarded as the gold standard for diagnosing diabetes and impaired glucose tolerance, and it is widely used in epidemiological studies to estimate the prevalence of diabetes, prediabetes and gestational diabetes mellitus in different populations, including those in sub-Saharan Africa. However, there is a lot of debate on the usefulness of this test, especially in low-resource settings. This thesis aims to determine the accuracy and utility of OGTT in sub-Saharan Africa through four different studies done in Uganda and Malawi. OGTT results in sub-Saharan Africa are influenced by challenges in sample handling before the analysis. In Chapter 2, we show that in the absence of the recommended sodium fluoride (NaF) sample collecting tubes for glucose measurement, the readily available EDTA tubes can be used provided that the samples are kept in a cooler box with ice and are centrifuged or analysed within six hours. The accuracy of OGTT based prevalence studies in regions with high food insecurity is unknown. In Chapter 3, we conducted a randomised cross over study in rural Uganda to explore factors that impact fasting and post-load glucose results. We demonstrated that the OGTT is affected by alteration of a single evening meal before the test. The two-hour glucose results are significantly higher after a low-carbohydrate evening meal compared to after a normal carbohydrate evening meal, even if the total daily carbohydrate intake was the recommended amount. The prevalence of abnormal glucose tolerance doubled after a restricted evening meal. 4 This finding raises questions on the utility of OGTT in populations with high levels of food insecurity. In Chapter 4, we followed up participants with prediabetes classified by impaired fasting glucose levels in urban and rural Malawi. By a period of 4 years, we found that the progression to diabetes in Malawi is high, with 30% of participants progressing to diabetes in the study period. The incident rate of diabetes was 63 per 1000 person-years. We also found that the waist circumference and the baseline glucose levels were the strongest predictors of progression. A simple chart with probabilities of progression based on these risk factors could be used to identify those at risk of developing diabetes in this population. In Chapter 5, we analysed the relationship between birth weight and adverse pregnancy outcomes with maternal fasting plasma glucose and stimulated glucose in Uganda. We found that the contribution of maternal glucose to birthweight is much lower in this population than what has been reported in other populations. Fasting plasma glucose was just as good at predicting large for gestational age babies than either one or two-hour glucose results. An overview of the major findings of each chapter, their implications, and potential future research are discussed in Chapter 6