Clarke Error Grid Analysis for Performance Evaluation of Glucometers in a Tertiary Care Referral Hospital

High-precision prediction of blood glucose concentration utilizing Fourier transform Raman spectroscopy and an ensemble machine learning algorithm

Raman spectroscopy has gained popularity in analyzing blood glucose levels due to its non-invasive identification and minimal interference from water. However, the challenge lies in how to accurately predict blood glucose concentrations in human blood using Raman spectroscopy. This paper researches a novel integrated machine learning algorithm called Bagging-ABC-ELM. The optimal input weights and biases of extreme learning machine (ELM) model are obtained by artificial bee colony (ABC) algorithm. The bagging algorithm is used to obtain a better the stability of the model and higher performance than ELM algorithm. The results show that the mean value of coefficient of determination is 0.9928, and root mean square error is 0.1928. Compared to other regression models, the Bagging-ABC-ELM model exhibited superior prediction accuracy, robustness, and generalization capability. The Bagging-ABC-ELM model presents a promising alternative for analyzing blood glucose levels in clinical and research settings.

Insight into continuous glucose monitoring: from medical basics to commercialized devices

According to the latest statistics, more than 537 million people around the world struggle with diabetes and its adverse consequences. As well as acute risks of hypo- or hyper- glycemia, long-term vascular complications may occur, including coronary heart disease or stroke, as well as diabetic nephropathy leading to end-stage disease, neuropathy or retinopathy. Therefore, there is an urgent need to improve diabetes management to reduce the risk of complications but also to improve patient's quality life. The impact of continuous glucose monitoring (CGM) is well recognized, in this regard. The current review aims at introducing the basic principles of glucose sensing, including electrochemical and optical detection, summarizing CGM technology, its requirements, advantages, and disadvantages. The role of CGM systems in the clinical diagnostics/personal testing, difficulties in their utilization, and recommendations are also discussed. In the end, challenges and prospects in future CGM systems are discussed and non-invasive, wearable glucose biosensors are introduced. Though the scope of this review is CGMs and provides information about medical issues and analytical principles, consideration of broader use will be critical in future if the right systems are to be selected for effective diabetes management.

An In-Ear PPG-Based Blood Glucose Monitor: A Proof-of-Concept Study

Monitoring diabetes saves lives. To this end, we introduce a novel, unobtrusive, and readily deployable in-ear device for the continuous and non-invasive measurement of blood glucose levels (BGLs). The device is equipped with a low-cost commercially available pulse oximeter whose infrared wavelength (880 nm) is used for the acquisition of photoplethysmography (PPG). For rigor, we considered a full range of diabetic conditions (non-diabetic, pre-diabetic, type I diabetic, and type II diabetic). Recordings spanned nine different days, starting in the morning while fasting, up to a minimum of a two-hour period after eating a carbohydrate-rich breakfast. The BGLs from PPG were estimated using a suite of regression-based machine learning models, which were trained on characteristic features of PPG cycles pertaining to high and low BGLs. The analysis shows that, as desired, an average of 82% of the BGLs estimated from PPG lie in region A of the Clarke error grid (CEG) plot, with 100% of the estimated BGLs in the clinically acceptable CEG regions A and B. These results demonstrate the potential of the ear canal as a site for non-invasive blood glucose monitoring.

A qualitative assessment of facility readiness and barriers to the facility-based management of childhood severe acute malnutrition in the public healthcare settings in Bangladesh

OBJECTIVE

To assess facility readiness and identify barriers to the facility-based management of childhood severe acute malnutrition (SAM) in public healthcare settings.

DESIGN

Qualitative methods were applied to assess readiness and identify different perspectives on barriers to the facility-based management of children with SAM. Data collection was done using in-depth interviews, key informant interviews, exit interviews and pre-tested observation tools.

SETTINGS

Two tertiary care and four district hospitals in Rangpur and Sylhet Divisions of Bangladesh.

PARTICIPANTS

Healthcare professionals and caregivers of children with SAM.

RESULTS

Anthropometric tools, glucometer, medicines, F-75, F-100 and national guidelines for facility-based management of childhood SAM were found unavailable in some of the hospitals. Sitting and sleeping arrangements for the caregivers were absent in all of the chosen facilities. We identified a combination of health system and contextual barriers that inhibited the facility-based management of SAM. The health system barriers include inadequate manpower, rapid turnover of staff, increased workload, lack of training and lack of adherence to management protocol. The major facility barriers were insufficient space and unavailability of required equipment, medicines and foods for hospitalised children with SAM. The reluctance of caregivers to complete the treatment regimen, their insufficient knowledge regarding proper feeding, increased number of attendants and poverty of parents were the principal contextual barriers.

CONCLUSIONS

The study findings provide insights on barriers that are curbing the facility-based management of SAM and emphasise policy efforts to develop feasible interventions to reduce the barriers and ensure the preparedness of the facilities for effective service delivery.

Evaluation of a Point-of-Care Test for Bilirubin in Malawi

OBJECTIVES

BiliSpec is a low-cost spectrophotometric reader and disposable paper-based strip to quantify total serum bilirubin from several blood drops. This study was a prospective evaluation of BiliSpec in 2 neonatal wards in Malawi compared with a reference standard bilirubinometer over a large range of bilirubin and hematocrit levels.

METHODS

The accuracy of BiliSpec and a transcutaneous bilirubinometer were compared with the reference standard of spectrophotometry for 475 blood samples collected from 375 subjects across a range of total serum bilirubin concentrations from 0.0 to 33.7 mg/dL. The development of error grids to assess the clinical effects of measurement differences is reported.

RESULTS

BiliSpec was found to have a mean bias of -0.48 mg/dL and 95% limits of agreement of -5.09 mg/dL to +4.12 mg/dL. Results show 90.7% of BiliSpec measurements would have resulted in the same clinical decision as the reference standard, whereas 55.0% of transcutaneous bilirubin measurements would have resulted in the same clinical decision as the reference standard.

CONCLUSIONS

This evaluation supports use of BiliSpec to provide accurate, low-cost, point-of-care bilirubin measurements in low-resource hospitals. Future work is needed to evaluate BiliSpec among a larger number of users.