Skin and soft tissue infections (SSTIs) represent a wide range of clinical conditions characterized by a considerable variety of clinical presentations and severity. Their aetiology can also vary, with numerous possible causative pathogens. While other authors previously published analyses on several types of SSTI and on restricted types of patients, we conducted a large nationwide surveillance programme on behalf of the Italian Society of Infectious and Tropical Diseases to assess the clinical and microbiological characteristics of the whole SSTI spectrum, from mild to severe life-threatening infections, in both inpatients and outpatients. Twenty-five Infectious Diseases (ID) Centres throughout Italy collected prospectively data concerning both the clinical and microbiological diagnosis of patients affected by SSTIs via an electronic case report form. All the cases included in our database, independently from their severity, have been managed by ID specialists joining the study while SSTIs from other wards/clinics have been excluded from this analysis. Here, we report the preliminary results of our study, referring to a 12-month period (October 2016-September 2017). During this period, the study population included 254 adult patients and a total of 291 SSTI diagnoses were posed, with 36 patients presenting more than one SSTIs. The type of infection diagnosed, the aetiological micro-organisms involved and some notes on their antimicrobial susceptibilities were collected and are reported herein. The enrichment of our registry is ongoing, but these preliminary results suggest that further analysis could soon provide useful information to better understand the national epidemiologic data and the current clinical management of SSTIs in Italy.
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http://dx.doi.org/10.1080/1120009X.2018.1536320 | DOI Listing |
J Med Case Rep
January 2025
Department of Clinical Medicine, Jining Medical University, Jining, China.
Background: Superficial acral fibromyxoma is a noncancerous, benign tumor of soft tissue with an unidentified origin. Occurrences of abnormalities on the palm are less frequently documented.
Case Report Presentation: A 47-year-old East Asian woman presented with a palm tumor on her left knuckle that had been present for 4 months.
J Colloid Interface Sci
January 2025
School of Chemistry and Chemical Engineering, Shandong University, Jinan 250100, China. Electronic address:
Soft ionic conductors are promising candidates for epidermal electrodes, flexible sensors, ionic skins, and other soft iontronic devices. However, their inadequate ionic conductivity and mechanical properties (such as toughness and adhesiveness) are still the main constraints for their wide applications in wearable bioelectronics. Herein, an all-biocompatible composite gel with a double-network (DN) strategy is proposed.
View Article and Find Full Text PDFACS Appl Mater Interfaces
January 2025
College of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an 710054, China.
Soft and stretchable strain sensors are crucial for applications in human-machine interfaces, flexible robotics, and electronic skin. Among these, capacitive strain sensors are widely used and studied; however, they face challenges due to material and structural constraints, such as low baseline capacitance and susceptibility to external interference, which result in low signal-to-noise ratios and poor stability. To address these issues, we propose a U-shaped electrode flexible strain sensor based on liquid metal elastomer (LME).
View Article and Find Full Text PDFCancers (Basel)
January 2025
Unit of Dermatology, Department of Medicine, University of Padova, 35122 Padua, Italy.
Diagnostics (Basel)
January 2025
College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia.
Early and accurate diagnosis of skin cancer improves survival rates; however, dermatologists often struggle with lesion detection due to similar pigmentation. Deep learning and transfer learning models have shown promise in diagnosing skin cancers through image processing. Integrating attention mechanisms (AMs) with deep learning has further enhanced the accuracy of medical image classification.
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