Publications by authors named "Monica Pittarello"

Chronic wounds are a syndrome that affects around 4% of the world population due to several pathologies. The COV-19 pandemic has enforced the need of developing new techniques and technologies that can help clinicians to monitor the affected patients easily and reliably. In this prospective observational study a new device, the Wound Viewer, that works through a memristor-based Discrete-Time Cellular Neural Network (DT-CNN) has been developed and tested through a clinical trial of 150 patients.

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Objective: Blue light (410-430nm) has been suggested to be effective in the healing process of hard-to-heal wounds. The aim of this study was to test this hypothesis.

Method: This single-centre observational study assessed the efficacy of photobiomodulation with blue light (120 seconds at a distance of 4cm from the wound bed once a week for four weeks) in activating healing in patients with hard-to-heal skin lesions (mean duration 23.

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Objective: Immediately following a two-year prospective case series in which the wounds of 60 patients with hard-to-heal ulcers were treated with a hypochlorous acid oxidising solution (AOS) in addition to standard of care (SoC) for 70 days (T0-T70), a subset of 31 patients (51.7%) whose wounds had not fully healed by T70 opted to continue with treatment for a further 22 weeks (days T70-T224, a total treatment time of 32 weeks (224 days). The objective was to provide long-term evidence on the clinical performance and safety of AOS when used in association with the usual SoC in patients with stalled, hard-to-heal ulcers of various aetiologies.

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Objective: This prospective case series aims to evaluate the clinical impact of a hypochlorous acid oxidising solution (AOS) in association with usual standard of care (SoC) on wound bed preparation (WBP) in patients with hard-to-heal ulcers of various aetiologies. The AOS (Nexodyn, APR Applied Pharma Research S.A.

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Objective: To report the clinical validation of an innovative, artificial intelligence (AI)-powered, portable and non-invasive medical device called Wound Viewer. The AI medical device uses dedicated sensors and AI algorithms to remotely collect objective and precise clinical data, including three-dimensional (3D) wound measurements, tissue composition and wound classification through the internationally recognised Wound Bed Preparation (WBP) protocol; this data can then be shared through a secure General Data Protection Regulation (GDPR)- and Health Insurance Portability and Accountability Act (HIPAA)-compliant data transfer system. This trial aims to test the reliability and precision of the AI medical device and its ability to aid health professionals in clinically evaluating wounds as efficiently remotely as at the bedside.

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