Early identification of cardiac autonomic neuropathy using complexity analysis in children with type 1 diabetes

The Potential of Current Noninvasive Wearable Technology for the Monitoring of Physiological Signals in the Management of Type 1 Diabetes: Literature Survey

Background

Monitoring glucose and other parameters in persons with type 1 diabetes (T1D) can enhance acute glycemic management and the diagnosis of long-term complications of the disease. For most persons living with T1D, the determination of insulin delivery is based on a single measured parameter—glucose. To date, wearable sensors exist that enable the seamless, noninvasive, and low-cost monitoring of multiple physiological parameters.

Objective

The objective of this literature survey is to explore whether some of the physiological parameters that can be monitored with noninvasive, wearable sensors may be used to enhance T1D management.

Methods

A list of physiological parameters, which can be monitored by using wearable sensors available in 2020, was compiled by a thorough review of the devices available in the market. A literature survey was performed using search terms related to T1D combined with the identified physiological parameters. The selected publications were restricted to human studies, which had at least their abstracts available. The PubMed and Scopus databases were interrogated. In total, 77 articles were retained and analyzed based on the following two axes: the reported relations between these parameters and T1D, which were found by comparing persons with T1D and healthy control participants, and the potential areas for T1D enhancement via the further analysis of the found relationships in studies working within T1D cohorts.

Results

On the basis of our search methodology, 626 articles were returned, and after applying our exclusion criteria, 77 (12.3%) articles were retained. Physiological parameters with potential for monitoring by using noninvasive wearable devices in persons with T1D included those related to cardiac autonomic function, cardiorespiratory control balance and fitness, sudomotor function, and skin temperature. Cardiac autonomic function measures, particularly the indices of heart rate and heart rate variability, have been shown to be valuable in diagnosing and monitoring cardiac autonomic neuropathy and, potentially, predicting and detecting hypoglycemia. All identified physiological parameters were shown to be associated with some aspects of diabetes complications, such as retinopathy, neuropathy, and nephropathy, as well as macrovascular disease, with capacity for early risk prediction. However, although they can be monitored by available wearable sensors, most studies have yet to adopt them, as opposed to using more conventional devices.

Conclusions

Wearable sensors have the potential to augment T1D sensing with additional, informative biomarkers, which can be monitored noninvasively, seamlessly, and continuously. However, significant challenges associated with measurement accuracy, removal of noise and motion artifacts, and smart decision-making exist. Consequently, research should focus on harvesting the information hidden in the complex data generated by wearable sensors and on developing models and smart decision strategies to optimize the incorporation of these novel inputs into T1D interventions.

Large fibre, small fibre and autonomic neuropathy in adolescents with type 1 diabetes: A systematic review

AIMS

To estimate the prevalence of neuropathy in adolescents with type 1 diabetes.

METHODS

Systematic collection of published studies exploring the prevalence of large fibre neuropathy (LFN), small fibre neuropathy (SFN), and autonomic neuropathy in adolescents with type 1 diabetes. Following prospective registration (Prospero CRD42020206093), PubMed, EMBASE, and Cochrane Library were searched for studies from 2000 to 2020. PICO framework was used in the selection process (Population: adolescents aged 10-19 years with type 1 diabetes; Intervention: diagnostic methods for neuropathy; Comparison: reference data; Outcome: data on prevalence or comparison). Data were extracted concerning study quality based on available data and established methods for determining and diagnosing various neuropathy types.

RESULTS

From 2,017 initial citations, 27 studies (7589 participants) fulfilled eligibility criteria. The study population (47% males) had a diabetes duration between 4.0 and 10.6 years, and HbA1c level between 7.3 and 10.8%, 56-95 mmol/mol. The prevalence of LFN, based on nerve conduction studies, was 10-57%. Based on other tests for neuropathy, the prevalence of LFN and SFN was 12-62%, and that of cardiac autonomic neuropathy was 12-75%.

CONCLUSION

The described prevalence of neuropathy in adolescents with type 1 diabetes varied, which can be methodological due to different screening methods and classifications of neuropathy.