Atrial fibrillation (AF) is the most common arrhythmia and has a major impact on morbidity and mortality; however, detection of asymptomatic AF is challenging. This study sims to evaluate the ...sensitivity and specificity of non-invasive AF detection by a medical wearable. In this observational trial, patients with AF admitted to a hospital carried the wearable and an ECG Holter (control) in parallel over a period of 24 h, while not in a physically restricted condition. The wearable with a tight-fit upper armband employs a photoplethysmography technology to determine pulse rates and inter-beat intervals. Different algorithms (including a deep neural network) were applied to five-minute periods photoplethysmography datasets for the detection of AF. A total of 2306 h of parallel recording time could be obtained in 102 patients; 1781 h (77.2%) were automatically interpretable by an algorithm. Sensitivity to detect AF was 95.2% and specificity 92.5% (area under the receiver operating characteristics curve (AUC) 0.97). Usage of deep neural network improved the sensitivity of AF detection by 0.8% (96.0%) and specificity by 6.5% (99.0%) (AUC 0.98). Detection of AF by means of a wearable is feasible in hospitalized but physically active patients. Employing a deep neural network enables reliable and continuous monitoring of AF.
OBJECTIVE
Reliability of continuous glucose monitoring (CGM) sensors is key in several applications. In this work we demonstrate that real-time algorithms can render CGM sensors smarter by reducing ...their uncertainty and inaccuracy and improving their ability to alert for hypo- and hyperglycemic events.
RESEARCH DESIGN AND METHODS
The smart CGM (sCGM) sensor concept consists of a commercial CGM sensor whose output enters three software modules, able to work in real time, for denoising, enhancement, and prediction. These three software modules were recently presented in the CGM literature, and here we apply them to the Dexcom SEVEN Plus continuous glucose monitor. We assessed the performance of the sCGM on data collected in two trials, each containing 12 patients with type 1 diabetes.
RESULTS
The denoising module improves the smoothness of the CGM time series by an average of ∼57%, the enhancement module reduces the mean absolute relative difference from 15.1 to 10.3%, increases by 12.6% the pairs of values falling in the A-zone of the Clarke error grid, and finally, the prediction module forecasts hypo- and hyperglycemic events an average of 14 min ahead of time.
CONCLUSIONS
We have introduced and implemented the sCGM sensor concept. Analysis of data from 24 patients demonstrates that incorporation of suitable real-time signal processing algorithms for denoising, enhancement, and prediction can significantly improve the performance of CGM applications. This can be of great clinical impact for hypo- and hyperglycemic alert generation as well in artificial pancreas devices.
Self-monitoring of blood glucose using capillary glucose testing (C) has a number of shortcomings compared to continuous glucose monitoring (CGM). We aimed to compare these two methods and used blood ...glucose measurements in venous blood (IV) as a reference. Postprandial blood glucose levels were measured after 50 g oral glucose load and after the consumption of a portion of different foods containing 50 g of carbohydrates. We also evaluated the associations between postprandial glucose responses and the clinical characteristics of the participants at the beginning of the study.
12 healthy volunteers (age: 36 ± 17 years, BMI: 24.9 ± 3.5 kg/m²) ate white bread (WB) and whole grain (WG) bread and drank a 50 g glucose drink as reference. Postprandial glucose responses were evaluated by CGM, IV and C blood glucose measurements. Incremental area under the curve (AUC
) of postprandial blood glucose was calculated for 1 h (AUC
) and 2 h (AUC
).
After the consumption of white bread and whole grain bread, the AUC
did not differ between CGM and IV or C. AUC
of CGM showed no difference compared to C. Correlation analyses revealed a positive association of age with glucose AUC
(
= 0.768;
= 0.004) and WG AUC
(
= 0.758;
= 0.004); fasting blood glucose correlated with WG AUC
(
= 0.838;
< 0.001).
Despite considerable inter-individual variability of postprandial glycemic responses, CGM evaluated postprandial glycemic excursions which had comparable results compared to standard blood glucose measurements under real-life conditions. Associations of AUC
and AUC
postprandial glucose response with age or fasting blood glucose could be shown.
It remains to be seen as to what share of the market FGM will achieve if the manufacturer can supply any amount desired.Will a significant portion of the glucose monitoring market then be taken over ...by FGM? The availability of FGM as anew option for glucose monitoring can basically be evaluated positively and it does indeed clearly show the benefit of“more information” on the glucose trend. The relatively low price for glucose monitoring using FGM and the unusual market introduction (not first via the National Association of Statutory Health Insurance Funds, as was the case with CGM) have given increased attention to the use of more glucose information. It will likely take a certain amount of time before other providers are able to bring different FGM systems to the market.The option of coupling a CGM system with an insulin pump offers the perspective of an automated insulin application,that is, a closed-loop system. Such systems are currently being tested under everyday conditions, although it is not possible to predict when they will actually reach the market.There are, however, such couplings where algorithms are responsible for shutting off insulin delivery when the glucose concentration reaches a defined level or if it will be reached in the foreseeable future. This significantly helps prevent hypoglycemia. These options are only available with CGM. The aim of this commentary is to present the differences between CGM and FGM, including the advantages and disadvantages of both approaches. We see significant benefits in both options based on the different positioning of the approaches and the different user groups.
Biosimilar Insulin and Costs Heinemann, Lutz
Journal of diabetes science and technology,
03/2016, Letnik:
10, Številka:
2
Journal Article
Recenzirano
The costs for insulin treatment are high, and the steady increase in the number of patients with diabetes on insulin presents a true challenge to health care systems. Therefore, all measures to lower ...these costs are welcomed by patients, physicians, and health care providers. The market introduction of biosimilar insulins presents an option to lower treatment costs as biosimilars are usually offered at a lower price than the originator product. However, the assumption that a drastic reduction in insulin prices will take place, as was observed with many generic drugs, is most probably not realistic. As the first biosimilar insulin has now been approved in the EU, this commentary discusses a number of aspects that are relevant when it comes to the potential cost reduction we will see with the use of biosimilar insulins.
Home and work situations can expose diabetes medical devices to a number of environmental factors that may influence their function and safety. In accordance with regulatory requirements, ...manufacturing companies take great care in the construction and design of their products so that environmental factors encountered on a daily basis have as little influence as possible. However, more intense environmental conditions, such as undergoing magnetic resonance imaging (MRI), require patients to remove personal electronic medical devices beforehand. During product development, manufacturers thoroughly investigate how various environmental factors may impact a new medical device. Corresponding operational documents and manufacturer guarantees accompany each device. Similarly, manufacturers investigate any adverse interactions that may occur during communications between medical devices, such as those required with another product, smartphone, or another personal medical device, such as a pacemaker. Questions that arise from patients or medical professionals about a medical device’s safety or quality, particularly because of environmental factors, are made to the manufacturer. Manufacturers then often refer to the operating instructions, even though these contain information, such as electromagnetic compatibility, that are difficult to understand for people lacking special technical or physical knowledge. This review highlights the effects of various physical and technical influences on medical devices used in diabetes therapy.
An insulin infusion set (IIS) is a key component of insulin pumps. In daily practice issues with the IIS appear to be as relevant for a successful insulin therapy as the pumps themselves. The insulin ...is applied to the subcutaneous tissue via a Teflon(®) (Dupont, Wilmington, DE) or steel cannula. There are intensive discussions about the impact the choice of material for insulin application has on insulin pharmacokinetics. In this review, this factor and others that are known to have an impact on the successful usage of IIS are discussed.
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