Blue light photobiomodulation for reactivation of healing in wounds not responding to standard therapy.

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 23.9 months) of the lower limb that had not responded to four weeks of standard treatment. RESULTS: A total of 59 patients were assessed. Wounds were divided into groups according to aetiology: hard-to-heal venous wound (30.5%); hard-to-heal arterial and mixed wounds (16.9%); hard-to-heal inflammatory wound (22.0%); other hard-to-heal wounds (13.6%); and acute wound (16.9%). The mean reduction in wound area at the end of the four-week treatment period with blue light compared with baseline was 51.38% (p<0.001) across all wounds. Among subgroups, the best performance was obtained for hard-to-heal venous wounds, achieving a 63.36% (p<0.001) mean reduction in wound size, and acute wounds, achieving a mean reduction of 82.76% (p<0.001). The greatest mean change in wound bed score was seen at the end of the four-week treatment period with blue light, with an increase in the mean score from 8.6 at baseline to 12.8 at week four (77.2%; p<0.001). There was a clear decrease in pain during blue light treatment, achieving a reduction in the average numeric rating scale (NRS) from 4.3 at baseline to 1.8 at week 4 (53.23%; p <0.001). At week 4, the highest proportion of complete healing was seen in acute (100.0%) and venous wounds (83.3%). CONCLUSION: Based on these results, photobiomodulation with blue light appears to reactivate the healing process in acute and hard-to-heal wounds that do not respond to standard treatment. Photobiomodulation with blue light treatment is easy to perform and safe, with no reported adverse events or side-effects.

Wound bed preparation with hypochlorous acid oxidising solution and standard of care: a prospective case series.

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., Switzerland) comprises three main features: highly pure and stabilised hypochlorous acid, acidic pH and high reduction-oxidation potential. METHOD: Between February 2015 and February 2017, patients who met the inclusion criteria were treated with AOS and usual SoC. Data collection ran for 70 days: T0-T70. A baseline assessment was undertaken at T0; parameters assessed at fortnightly visits included: WBP score, area and depth of ulcer, duration, pain, Bates-Jensen score and infection status. RESULTS: A total of 60 patients took part in the study. By T70, 68.3% of wounds had healed or improved and a significant wound size reduction of 21% was observed (p<0.001), despite a mean wound duration of 20.6 months. All wounds were free of local infection and cellulitis; 10% were colonised. WBP scores improved, while Bates-Jensen and pain scores fell significantly over time. CONCLUSION: This evaluation suggests that AOS might represent a valuable therapeutic addition for an optimal WBP in the routine management of hard-to-heal ulcers of different aetiologies. DECLARATION OF INTEREST: ER worked as a consultant for APR Applied Pharma Research S.A. The authors have no other conflicts of interest.

Hard-to-heal ulcers treated with hypochlorous acid oxidising solution and standard of care: a 32-week follow-up.

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. METHOD: As per the main study, wounds were formally assessed by the study lead at 28 days (±14 days, depending on patient attendance). Parameters assessed at fortnightly visits included area, depth and duration of ulcer; pain; wound bed preparation (WBP) score; and infection status. Wounds were managed in accordance with the SoC protocol. RESULTS: By T224, 35.5% (n=11) of wounds healed completely and 83.9% showed some types of improvement. All wounds were free of infection and colonisation, the WBP score improved (100% A1-A2 at T196), and pain scores fell. Use of AOS in combination with several types of dressing (SoC) for such a long period confirmed a good safety profile. CONCLUSION: This follow-up evaluation, coupled with the primary study, suggests that AOS might represent a valuable therapeutic addition for the management of hard-to-heal ulcers for long periods of treatment. DECLARATION OF INTEREST: ER worked as a consultant for APR Applied Pharma Research S.A. The authors have no other conflicts of interest.

AI technology for remote clinical assessment and monitoring.

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. METHOD: This non-randomised comparative clinical trial was conducted in the Clinica San Luca (Turin, Italy). Patients were divided into three groups: (i) patients with venous and arterial ulcers in the lower limbs; (ii) patients with diabetes and presenting with diabetic foot syndrome; and (iii) patients with pressure ulcers. Each wound was evaluated for area, depth, volume and WBP wound classification. Each patient was examined once and the results, analysed by the AI medical device, were compared against data obtained following visual evaluation by the physician and research team. The area and depth were compared with a Kruskal-Wallis one-way analysis of variations in the obtained distribution (expected p-value>0.1 for both tests). The WBP classification and tissue segmentation were analysed by directly comparing the classification obtained by the AI medical device against that of the testing physician. RESULTS: A total of 150 patients took part in the trial. The results demonstrated that the AI medical device's AI algorithm could acquire objective clinical parameters in a completely automated manner. The AI medical device reached 97% accuracy against the WBP classification and tissue segmentation analysis compared with that performed in person by the physician. Moreover, data regarding the measurements of the wounds, as analysed through the Kruskal-Wallis technique, showed that the data distribution proved comparable with the other methods of measurement previously clinically validated in the literature (p=0.9). CONCLUSION: These findings indicate that remote wound assessment undertaken by physicians is as effective through the AI medical device as bedside examination, and that the device was able to assess wounds and provide a precise WBP wound classification. Furthermore, there was no need for manual data entry, thereby reducing the risk of human error while preserving high-quality clinical diagnostic data.