Dominic Bright

Bio: Dominic Bright is an academic researcher from Swansea University. The author has contributed to research in topics: Blood glucose monitoring & Proinsulin. The author has an hindex of 2, co-authored 6 publications receiving 1993 citations.

Performance evaluation of a self‐administered home oral glucose tolerance test kit in a controlled clinical research setting

Abstract: Aim To evaluate the performance of the current, pre-production version of a novel home oral glucose tolerance test (Home OGTT) device when administered by trained research nurses, compared with a reference laboratory glucose analyser and a second laboratory analyser, incorporating a sample processing delay to simulate normal practice. Methods One hundred women (aged 19-48 years), with and without known glucose intolerance were recruited. Following an overnight fast, participants attended for a 75-g OGTT. A fasting capillary sample was applied to the Home OGTT device with a corresponding venous sample collected and measured immediately on the reference YSI 2300 stat plus analyser, and following a 1-h delay on the Randox Daytona Plus analyser. The sampling process was repeated 2 h after the oral glucose load. Results Some 97% of tested devices gave complete data for analysis. Good agreement was observed between the reference glucose analyser and the Home OGTT device, with the Home OGTT device displaying a small negative bias (-0.18 mmol/l, -1.75 to 1.39 mmol/mol; -1.0%, -26.4% to 24.5%; absolute and relative mean, 95% limits of agreement). When classified as normal glucose tolerant or glucose intolerant, the Home OGTT device showed 100% and 90% sensitivity, and 99% and 99% specificity using fasting plasma glucose and 2-h glucose respectively. Similar sensitivity (100% and 100%) and specificity (96% and 99%) for fasting plasma glucose and 2-h glucose were observed using the secondary analyser. Conclusions The novel Home OGTT device was reliable and easy to use and showed excellent agreement with two separate laboratory analysers. The Home OGTT offers potential as an effective alternative for clinic-based OGTT testing.

Accuracy Evaluation of a Blood Glucose Monitoring System According to EN ISO 15197:2015.

Abstract: The accuracy of the blood glucose readings provided by the GLUCOCARD SM blood glucose meter (A. Menarini Diagnostics, Florence, Italy) was assessed according to the guidelines (EN ISO 15197:2015, paragraph 6.3) introduced to establish acceptable performance for blood glucose monitoring systems. This is a new blood glucose meter recently introduced into the European market, offering advanced features like Bluetooth Low Energy on board, allowing patients to have glucose values automatically sent to a smartphone. The study was performed within the Joint Clinical Research Facility, Swansea University in compliance with Good Clinical Practice (GCP) and approved by the relevant ethics committee. Subjects (N = 100; male and female) who met the inclusion criteria had a fingerstick capillary blood sample taken in appropriate anticoagulant. This sample was used for measurement of the blood glucose level in the meter (3 lots of strips in duplicate), and a laboratory reference method analyzer, YSI 2300. Plasma glucose was analyzed in duplicate using a YSI 2300 Stat Plus (Yellow Springs Instruments, Fleet, UK) and blood glucose determined on 6 different meters using 3 lots of test strips, which were all provided by the manufacturer. For YSI measurement, blood samples were collected into capillary collection tubes (Lithium Heparin Microvette, Sarstedt, Leicester, UK) and centrifuged prior to plasma glucose measurement. In addition, hematocrit was measured using a HemoControl analyzer (EKF, Cardiff, UK). Daily control measures were carried out on all meters and instruments. Other than in the modified samples, all blood sampling and analysis were performed within a 5-minute time frame. To meet the extreme glucose concentration criterion, samples aimed to be <80 mg/dL (4.44 mmol/L) were incubated to allow glucose to hydrolyze (glycolysis). Similarly, to obtain samples >300 mg/dL (16.65 mmol/L) a supplement of glucose was added. A maximum of 22 blood samples were modified in this way in accordance with EN ISO 15197:2015. Modified samples had pO 2 concentrations equivalent to capillary blood prior to assay. Good agreement and linearity were observed between the blood glucose results from the 3 different lots and the YSI reference results (Fig 1). Combined data from the 3 lots showed 99% of readings from the blood glucose meter met each of the individual criteria. At glucose concentration <100 mg/dL, 168/174 (95% [lot 1], 97% [lot 2], 98% [lot 3]) results fell within ±15 mg/dL of the YSI values. At glucose concentrations ≥100 mg/dL, 423/426 (100% [lot 1], 99% [lot 2], 99% [lot 3]) results fell within ±15% specified by EN ISO 15197:2015. The overall combined results demonstrated conformance (591/600 [99%] within ±15 mg/dL and within ±15%). As shown in Figure 1B, a total of 99.8% values fell within zone A of the consensus error grid, defined as “clinically accurate measurement,” and the remaining 0.2% fell in zone B demonstrating compliance with criterion B specified by EN ISO 15197:2015. These results demonstrate good agreement between the test blood glucose meter and the reference laboratory method, 695340 DSTXXX10.1177/1932296817695340Journal of Diabetes Science and TechnologyBright et al letter2017

Comparative Accuracy Evaluation of a Blood Glucose Meter With Novel Hematocrit Correction Technology, With Three Currently Used Commercially Available Blood Glucose Monitoring Systems.

Abstract: Hematocrit is known to influence glucose values obtained on some blood glucose meters, with bias observed especially at low and high hematocrit levels. We evaluated the performance of a meter with hematocrit correction technology alongside 3 other commercially available meters. Capillary blood samples from 100 subjects were analyzed in duplicate and compared to the plasma values obtained by reference laboratory analyzer. Bias, error grid, and sensitivity to hematocrit analyses were performed for each meter. Average percentage bias was similar for all meters, however the evaluated meter performed best with respect to error grid analysis, with 100% of values falling within the "no effect on clinical action" and "no risk" categories and did not display any hematocrit associated bias.

Proinsulin in the identification and risk stratification of gestational diabetes mellitus: study protocol for a prospective, longitudinal cohort study

Abstract: Introduction Gestational diabetes mellitus (GDM) is a common metabolic disorder occurring in up to 10% of pregnancies in the western world. Most women with GDM are asymptomatic; therefore, it is important to screen, diagnose and manage the condition as it is associated with an increased risk of maternal and perinatal complications. Diagnosis of GDM is made in the late second trimester or early third trimester because accurate diagnosis or risk stratification in the first trimester is still lacking. An increase in serum proinsulin may be seen earlier in pregnancy and before a change in glycaemic control can be identified. This study will aim to establish if fasting proinsulin concentrations at 16–18 weeks gestation will help to identify or risk stratify high-risk pregnant women with GDM. Methods and analysis This is a prospective, longitudinal cohort study. Two oral glucose tolerance tests will be carried out at 16–18 and 24–28 weeks gestation in 200 pregnant women with at least one risk factor for GDM (body mass index>30 kg/m2, previous macrosomic baby (>4.5 kg), previous gestational diabetes, first degree relative with type 2 diabetes mellitus) recruited from antenatal clinics. Blood samples will be taken fasting and at 30 min, 1 and 2 hours following the 75 g glucose load. In addition, a fasting blood sample will be taken 6-weeks post delivery. All samples will be analysed for glucose, insulin, C peptide and proinsulin. Recruitment began in November 2017. Optimal cut-off points for proinsulin to diagnose gestational diabetes according to National Institute for Health and Care Excellence (2015) criteria will be established by the receiver operating characteristic plot and sensitivity and specificity will be calculated to assess the diagnostic accuracy of proinsulin at 16–18 weeks gestation. Ethics and dissemination This study received ethical approval from the Wales Research Ethics Committee (Panel 6) (Ref. 17/WA/0194). Data will be presented at international conferences and published in peer-reviewed journals. Trial registration number ISRCTN16416602; Pre-results.

Standards of Medical Care in Diabetes

Abstract: XI. STRATEGIES FOR IMPROVING DIABETES CARE D iabetes is a chronic illness that requires continuing medical care and patient self-management education to prevent acute complications and to reduce the risk of long-term complications. Diabetes care is complex and requires that many issues, beyond glycemic control, be addressed. A large body of evidence exists that supports a range of interventions to improve diabetes outcomes. These standards of care are intended to provide clinicians, patients, researchers, payors, and other interested individuals with the components of diabetes care, treatment goals, and tools to evaluate the quality of care. While individual preferences, comorbidities, and other patient factors may require modification of goals, targets that are desirable for most patients with diabetes are provided. These standards are not intended to preclude more extensive evaluation and management of the patient by other specialists as needed. For more detailed information, refer to Bode (Ed.): Medical Management of Type 1 Diabetes (1), Burant (Ed): Medical Management of Type 2 Diabetes (2), and Klingensmith (Ed): Intensive Diabetes Management (3). The recommendations included are diagnostic and therapeutic actions that are known or believed to favorably affect health outcomes of patients with diabetes. A grading system (Table 1), developed by the American Diabetes Association (ADA) and modeled after existing methods, was utilized to clarify and codify the evidence that forms the basis for the recommendations. The level of evidence that supports each recommendation is listed after each recommendation using the letters A, B, C, or E.

Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ITU admission.

Abstract: Anecdotal evidence suggests that Coronavirus disease 2019 (COVID-19), caused by the coronavirus SARS-CoV-2, exhibits differences in morbidity and mortality between sexes. Here, we present a meta-analysis of 3,111,714 reported global cases to demonstrate that, whilst there is no difference in the proportion of males and females with confirmed COVID-19, male patients have almost three times the odds of requiring intensive treatment unit (ITU) admission (OR = 2.84; 95% CI = 2.06, 3.92) and higher odds of death (OR = 1.39; 95% CI = 1.31, 1.47) compared to females. With few exceptions, the sex bias observed in COVID-19 is a worldwide phenomenon. An appreciation of how sex is influencing COVID-19 outcomes will have important implications for clinical management and mitigation strategies for this disease. Anecdotal reports suggest potential severity and outcome differences between sexes following infection by SARS-CoV-2. Here, the authors perform meta-analyses of more than 3 million cases collected from global public data to demonstrate that male patients with COVID-19 are 3 times more likely to require intensive care, and have ~40% higher death rate.

Diabetes mellitus is associated with increased mortality and severity of disease in COVID-19 pneumonia - A systematic review, meta-analysis, and meta-regression.

Abstract: BACKGROUND AND AIMS: Diabetes Mellitus (DM) is chronic conditions with devastating multi-systemic complication and may be associated with severe form of Coronavirus Disease 2019 (COVID-19). We conducted a systematic review and meta-analysis in order to investigate the association between DM and poor outcome in patients with COVID-19 pneumonia. METHODS: Systematic literature search was performed from several electronic databases on subjects that assess DM and outcome in COVID-19 pneumonia. The outcome of interest was composite poor outcome, including mortality, severe COVID-19, acute respiratory distress syndrome (ARDS), need for intensive care unit (ICU) care, and disease progression. RESULTS: There were a total of 6452 patients from 30 studies. Meta-analysis showed that DM was associated with composite poor outcome (RR 2.38 [1.88, 3.03], p < 0.001; I2: 62%) and its subgroup which comprised of mortality (RR 2.12 [1.44, 3.11], p < 0.001; I2: 72%), severe COVID-19 (RR 2.45 [1.79, 3.35], p < 0.001; I2: 45%), ARDS (RR 4.64 [1.86, 11.58], p = 0.001; I2: 9%), and disease progression (RR 3.31 [1.08, 10.14], p = 0.04; I2: 0%). Meta-regression showed that the association with composite poor outcome was influenced by age (p = 0.003) and hypertension (p < 0.001). Subgroup analysis showed that the association was weaker in studies with median age ≥55 years-old (RR 1.92) compared to <55 years-old (RR 3.48), and in prevalence of hypertension ≥25% (RR 1.93) compared to <25% (RR 3.06). Subgroup analysis on median age <55 years-old and prevalence of hypertension <25% showed strong association (RR 3.33) CONCLUSION: DM was associated with mortality, severe COVID-19, ARDS, and disease progression in patients with COVID-19.

Is diabetes mellitus associated with mortality and severity of COVID-19? A meta-analysis.

Abstract: Background Many studies on COVID-19 have reported diabetes to be associated with severe disease and mortality, however, the data is conflicting. The objectives of this meta-analysis were to explore the relationship between diabetes and COVID-19 mortality and severity, and to determine the prevalence of diabetes in patients with COVID-19. Methods We searched the PubMed for case-control studies in English, published between Jan 1 and Apr 22, 2020, that had data on diabetes in patients with COVID-19. The frequency of diabetes was compared between patients with and without the composite endpoint of mortality or severity. Random effects model was used with odds ratio as the effect size. We also determined the pooled prevalence of diabetes in patients with COVID-19. Heterogeneity and publication bias were taken care by meta-regression, sub-group analyses, and trim and fill methods. Results We included 33 studies (16,003 patients) and found diabetes to be significantly associated with mortality of COVID-19 with a pooled odds ratio of 1.90 (95% CI: 1.37–2.64; p Conclusions Diabetes in patients with COVID-19 is associated with a two-fold increase in mortality as well as severity of COVID-19, as compared to non-diabetics. Further studies on the pathogenic mechanisms and therapeutic implications need to be done.