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  1. A hybrid Transformer-LSTM model apply to glucose prediction
    Bian Q, As'arry A, Cong X, Rezali KABM, Raja Ahmad RMKB
    PLoS One, 2024;19(9):e0310084.
    PMID: 39259758 DOI: 10.1371/journal.pone.0310084
    The global prevalence of diabetes is escalating, with estimates indicating that over 536.6 million individuals were afflicted by 2021, accounting for approximately 10.5% of the world's population. Effective management of diabetes, particularly monitoring and prediction of blood glucose levels, remains a significant challenge due to the severe health risks associated with inaccuracies, such as hypoglycemia and hyperglycemia. This study addresses this critical issue by employing a hybrid Transformer-LSTM (Long Short-Term Memory) model designed to enhance the accuracy of future glucose level predictions based on data from Continuous Glucose Monitoring (CGM) systems. This innovative approach aims to reduce the risk of diabetic complications and improve patient outcomes. We utilized a dataset which contain more than 32000 data points comprising CGM data from eight patients collected by Suzhou Municipal Hospital in Jiangsu Province, China. This dataset includes historical glucose readings and equipment calibration values, making it highly suitable for developing predictive models due to its richness and real-time applicability. Our findings demonstrate that the hybrid Transformer-LSTM model significantly outperforms the standard LSTM model, achieving Mean Square Error (MSE) values of 1.18, 1.70, and 2.00 at forecasting intervals of 15, 30, and 45 minutes, respectively. This research underscores the potential of advanced machine learning techniques in the proactive management of diabetes, a critical step toward mitigating its impact.
    Matched MeSH terms: Blood Glucose Self-Monitoring/instrumentation
  2. Effect of ambient temperature on analytical and clinical performance of a blood glucose monitoring system: Omnitest Sensor glucose meter
    Nawawi H, Sazali BS, Kamaruzaman BH, Yazid TN, Jemain AA, Ismail F, et al.
    Ann. Clin. Biochem., 2001 Nov;38(Pt 6):676-83.
    PMID: 11732650
    The effect of ambient temperature on the analytical and clinical performance of a glucose meter was examined. A total of 114 venous whole blood samples were analysed for glucose by a reference method, and by a glucose meter at 21-22 degrees C, room temperatures, 26-27 degrees C and 33-34 degrees C. Glucose meter readings at each temperature were compared with the reference values and evaluated by analysis of variance, Spearman's correlation, the percentage of glucose meter readings within +/- 10% of the reference value and error grid analysis. Analysis of covariance was used to determine the effect of temperature on glucose meter readings. There were no significant differences in the glucose meter readings and in accuracy of the meter readings between different temperatures. Temperature was not a significant independent determinant of the glucose meter readings. For each glucose concentration, the precision of the meter and clinical performance were comparable between the different temperatures. In conclusion, ambient temperature does not affect the accuracy, precision and clinical performance of the Omnitest Sensor.
    Matched MeSH terms: Blood Glucose Self-Monitoring/instrumentation*
  3. Continuous glucose monitoring results in lower HbA1c in Malaysian women with insulin-treated gestational diabetes: a randomized controlled trial
    Paramasivam SS, Chinna K, Singh AKK, Ratnasingam J, Ibrahim L, Lim LL, et al.
    Diabet Med, 2018 08;35(8):1118-1129.
    PMID: 29663517 DOI: 10.1111/dme.13649
    AIMS: To determine if therapeutic, retrospective continuous glucose monitoring (CGM) improves HbA1c with less hypoglycaemia in women with insulin-treated gestational diabetes mellitus (GDM).

    METHODS: This prospective, randomized controlled, open-label trial evaluated 50 women with insulin-treated GDM randomized to either retrospective CGM (6-day sensor) at 28, 32 and 36 weeks' gestation (Group 1, CGM, n = 25) or usual antenatal care without CGM (Group 2, control, n = 25). All women performed seven-point capillary blood glucose (CBG) profiles at least 3 days per week and recorded hypoglycaemic events (symptomatic and asymptomatic CBG

    Matched MeSH terms: Blood Glucose Self-Monitoring/instrumentation
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