Evaluation of venous plasma glucose measured by point-of-care testing (Accu-Chek Inform II) and a hospital laboratory hexokinase method (Cobas c701) in oral glucose tolerance testing during pregnancy – a challenge in diagnostic accuracy

Landberg, Eva; Nevander, Sofia; Hadi, M. Azam; Blomberg, Marie; Norling, Anna; Ekman, Bertil; Lilliecreutz, Caroline

doi:10.1080/00365513.2021.1980224

Cited by 6 publications

(3 citation statements)

References 24 publications

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“…In total 230 pregnant women were included. The age and gestation were 34 (30-37) years and 28 (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35) weeks respectively. Our hospital serves a large ethnically diverse catchment area.…”

Section: Resultsmentioning

confidence: 99%

Clinical utility of point of care glucose in the assessment of gestational diabetes: Prospective cohort study.

Al-Hasani

Ranasinghe

Rogers

et al. 2022

Preprint

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Objective: To assess the clinical utility of point of care (POC) capillary blood glucose (CBG) in the assessment of gestational diabetes (GDM) during oral glucose tolerance test (OGTT). Design: Prospective cohort study. Setting: Antenatal clinics at King’s Collage Hospital. Population: Women screening for GDM between March and June 2020. Methods: CBG was measured using POC-StatStrip® (Nova) and venous plasma glucose (VPG) was measured by Roche (Cobas 8000 c702) analyser. GDM was diagnosed based on NICE-2015 criteria. The two methods were compared statistically using Analyse-It (v 5.40.2) Main outcome measures: Diagnostic sensitivity, specificity, positive and negative predictive values (PPV and NPV) for POC-StatStrip® compared to reference laboratory method. Results: 230 women were included. The number and the percentage of women with glucose concentration above the GDM thresholds using POC-StatStrip® vs. Lab-VPG measurement was 15 (6.5%) vs. 8 (3.4%) at fasting and 105 (45%.6) vs. 72 (31.1%) at 2-hour respectively. Sensitivity and specificity for POC-StatStrip® were 88% and 97% at fasting and 97% and 79% at 2-hour respectively. However, the specificity and the NPV for POC-StatStrip® concentrations ≤5.0 mmol/L at fasting or <7.5mmol/L at 2-hour were 100% and the sensitivity and the PPV for concentration >9.5mmol/L at 2-hour was 100 %. Conclusion: In our cohort POC-CBG measurement cannot entirely replace laboratory method in OGTT, however, it can be used to rule out/rule in GDM when the glucose concentrations are ≤5.0mmol/L at fasting or <7.5/>9.5mmol/L at 2-hour. Funding: not applicable. Key Words: Gestational Diabetes Mellitus (GDM), point of care (POC).

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Section: Resultsmentioning

confidence: 99%

Clinical utility of point of care glucose in the assessment of gestational diabetes: Prospective cohort study.

Al-Hasani

Ranasinghe

Rogers

et al. 2022

Preprint

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show abstract

“…Thus, such important procedural factors influencing the GDM prevalence are not necessarily similar between regions. It is well known that many components can influence the results of an OGTT and that the diagnosis of GDM relies on several pre-analytical, analytical and post-analytical factors with potential resulting bias in glucose measurements, which potentially contribute to differences in the final glucose value and subsequently the prevalence of GDM [ 13 , 14 ].…”

Section: Discussionmentioning

confidence: 99%

Regional divergence and time trends in the prevalence of gestational diabetes mellitus: a national Danish cohort study

et al. 2022

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Aims To evaluate the prevalence and time trends of gestational diabetes mellitus (GDM) across the five regions of Denmark with uniform national guidelines for screening and diagnosing GDM. Methods This register-based national cohort study included 287,684 births from 2013 to 2017. Trends in GDM prevalence over time and differences between the five regions were evaluated. Crude and adjusted odd ratios (ORs) for GDM were calculated including potential confounding clinical risk factors as age, BMI, educational level, marital status, parity, country of origin and assisted reproduction. Results From 2013 to 2017, GDM prevalence in Denmark increased by 7% per year (OR 1.07, 95% CI 1.06–1.09, P < 0.001). GDM prevalence varied considerably between regions and ranged from 3.0 to 5.9% in 2017, corresponding to a maximal regional difference of 97%. In crude analyses, the risk of GDM in 2017 was significantly different in four of five regions compared to the remaining regions (OR ranging from 0.60 to 1.55), and these differences persisted after adjusting for confounding clinical risk factors (adjusted OR: 0.59–1.45). Conclusion The prevalence of GDM increased over time in all Danish regions with substantial regional divergence. Up to a 97%, difference in GDM prevalence was observed between Danish regions, which was not explained by available clinical risk factors. This occurred despite national guidelines and raises the question of whether regional variations in screening efficacy, diagnostic procedures or inequality in clinical health care access may explain the observed differences.

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“…Several methods could be used to conduct diabetes screening. They are fasting plasma glucose (FPG) [19][20][21][22][23][24], hemoglobin A1C (HbA1C) [25][26][27][28], capillary fasting blood glucose (CBG) [16,[29][30][31], venous plasma glucose (VPG) [32][33][34], and oral glucose tolerance test (OGTT) [22,23,35] which checks the 2-h plasma glucose (2hPG). Among these available diabetes screening or diagnostic tests, FPG, HbA1c, and OGTT are the most recommended and useful for population-based screening [36].…”

Section: Literature Reviewmentioning

confidence: 99%

A Comprehensive Analysis of Chinese, Japanese, Korean, US-PIMA Indian, and Trinidadian Screening Scores for Diabetes Risk Assessment and Prediction

et al. 2022

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Risk assessment and developing predictive models for diabetes prevention is considered an important task. Therefore, we proposed to analyze and provide a comprehensive analysis of the performance of diabetes screening scores for risk assessment and prediction in five populations: the Chinese, Japanese, Korean, US-PIMA Indian, and Trinidadian populations, utilizing statistical and machine learning (ML) methods. Additionally, due to the present COVID-19 epidemic, it is necessary to investigate how diabetes and COVID-19 are related to one another. Thus, by using a sample of the Korean population, the interrelationship between diabetes and COVID-19 was further investigated. The results revealed that by using a statistical method, the optimal cut points among Chinese, Japanese, Korean, US-PIMA Indian, and Trinidadian populations were 6.205 mmol/L (FPG), 5.523 mmol/L (FPG), and 5.375% (HbA1c), 150.50–106.50 mg/dL (FBS), 123.50 mg/dL (2hPG), and 107.50 mg/dL (FBG), respectively, with AUC scores of 0.97, 0.80, 0.78, 0.85, 0.79, and 0.905. The results also confirmed that diabetes has a significant relationship with COVID-19 in the Korean population (p-value 0.001), with an adjusted OR of 1.21. Finally, the overall best ML models were performed by Naïve Bayes with AUC scores of 0.736, 0.75, and 0.83 in the Japanese, Korean, and Trinidadian populations, respectively.

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Evaluation of venous plasma glucose measured by point-of-care testing (Accu-Chek Inform II) and a hospital laboratory hexokinase method (Cobas c701) in oral glucose tolerance testing during pregnancy – a challenge in diagnostic accuracy

Cited by 6 publications

References 24 publications

Clinical utility of point of care glucose in the assessment of gestational diabetes: Prospective cohort study.

Clinical utility of point of care glucose in the assessment of gestational diabetes: Prospective cohort study.

Regional divergence and time trends in the prevalence of gestational diabetes mellitus: a national Danish cohort study

A Comprehensive Analysis of Chinese, Japanese, Korean, US-PIMA Indian, and Trinidadian Screening Scores for Diabetes Risk Assessment and Prediction

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