Insulin Pump Therapy

Faradji, Raquel N.; Viadero, María Elena Sainz de la Maza

doi:10.1007/978-3-030-11815-0_36

Cited by 1 publication

(1 citation statement)

References 24 publications

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“…Personal continuous subcutaneous insulin infusion pumps (CSII) 1-4 deliver insulin into the subcutaneous tissue through an intradermal catheter, allowing a more physiological delivery of insulin than multiple daily injections. 4 The efficacy of CSII pumps can be further enhanced by integrating them with a continuous glucose monitor (CGM) sensor.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Anomaly Detection Algorithms to Alert Patients Using Sensor Augmented Pump of Infusion Site Failures

Meneghetti

Dassau

Doyle

et al. 2021

J Diabetes Sci Technol

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Background: Personal insulin pumps have shown to be effective in improving the quality of therapy for people with type 1 diabetes (T1D). However, the safety of this technology is limited by the possible infusion site failures, which are linked with hyperglycemia and ketoacidosis. Thanks to the large availability of collected data provided by modern therapeutic technologies, machine learning algorithms have the potential to provide new way to identify failures early and avert adverse events. Methods: A clinical dataset ( N = 20) is used to evaluate a novel method for detecting real-time infusion site failures using unsupervised anomaly detection algorithms, previously proposed and developed on in-silico data. An adapted feature engineering procedure is introduced to make the method able to operate in the absence of a closed-loop (CL) system and meal announcements. Results: In the optimal configuration, we obtained a performance of 0.75 Sensitivity (15 out of 20 total failures detected) and 0.08 FP/day, outperforming previously proposed literature algorithms. The algorithm was able to anticipate the replacement of the malfunctioning infusion sets by ~2 h on average. Conclusions: On the considered dataset, the proposed algorithm showed the potential to improve the safety of patients treated with sensor-augmented pump systems.

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