Preventing the acute skin side effects in patients treated with radiotherapy for breast cancer: the use of corneometry in order to evaluate the protective effect of moisturizing creams

BACKGROUND AND PURPOSE: The purpose of this study was to add, to the objective evaluation, an instrumental assessment of the skin damage induced by radiation therapy. MATERIALS AND METHODS: A group of 100 patients affected by breast cancer was recruited in the study over one year. Patients were divided into five groups of 20 patients. For each group it was prescribed a different topical treatment. The following products were used: Betaglucan, sodium hyaluronate (Neoviderm®), Vitis vinifera A. s-I-M.t-O.dij (Ixoderm®), Alga Atlantica plus Ethylbisiminomethylguaicolo and Manganese Cloruro (Radioskin1®) and Metal Esculetina plus Ginko Biloba and Aloe vera (Radioskin 2®); Natural triglycerides-fitosterols (Xderit®); Selectiose plus thermal water of Avene (Trixera+®). All hydrating creams were applied twice a day starting 15 days before and one month after treatment with radiations. Before and during treatment patients underwent weekly skin assessments and corneometry to evaluate the symptoms related to skin toxicity and state of hydration. Evaluation of acute cutaneous toxicity was defined according to the RTOG scale. RESULTS: All patients completed radiotherapy; 72% of patients presented a G1 cutaneous toxicity, 18% developed a G2 cutaneous toxicity, 10% developed a G3 toxicity, no one presented G4 toxicity. The corneometry study confirmed the protective role of effective creams used in radiation therapy of breast cancer and showed its usefulness to identify radiation-induced dermatitis in a very early stage. CONCLUSIONS: The preventive use of topic products reduces the incidence of skin side effects in patients treated with radiotherapy for breast cancer. An instrumental evaluation of skin hydration can help the radiation oncologist to use strategies that prevent the onset of toxicity of high degree. All moisturizing creams used in this study were equally valid in the treatment of skin damage induced by radiotherapy

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

Data preprocessing impact on machine learning algorithm performance

The popularity of artificial intelligence applications is on the rise, and they are producing better outcomes in numerous fields of research. However, the effectiveness of these applications relies heavily on the quantity and quality of data used. While the volume of data available has increased significantly in recent years, this does not always lead to better results, as the information content of the data is also important. This study aims to evaluate a new data preprocessing technique called semi-pivoted QR (SPQR) approximation for machine learning. This technique is designed for approximating sparse matrices and acts as a feature selection algorithm. To the best of our knowledge, it has not been previously applied to data preprocessing in machine learning algorithms. The study aims to evaluate the impact of SPQR on the performance of an unsupervised clustering algorithm and compare its results to those obtained using principal component analysis (PCA) as the preprocessing algorithm. The evaluation is conducted on various publicly available datasets. The findings suggest that the SPQR algorithm can produce outcomes comparable to those achieved using PCA without altering the original dataset

An ontology-based approach to human telepresence

Abstract-Detecting human presence automatically is a challenging task since several environmental parameters may affect the quality and the continuity of detection. Although many techniques have been developed so far in the literature to solve this problem, they generally rely on well-defined operational context. Hence, they are sensitive to uncontrolled variables and unpredicted events. In this work an ontology-based approach to human telepresence detection is presented. Contrarily to classic sensor-driven techniques, a top-down methodology is applied. Starting from a formal description of the problem ontology, a set of high-response rate and low-response rate sensors is employed in a computational model. As a consequence of this model, a multi-sensor equipped device has been experimentally setup to conduct measurements on real scenarios. Experiments have been devised to estimate the robustness of the detection. In particular, some preliminary evaluations related to using a minimal set of chemical sensors are reported

Semantic Analysis and Understanding of Human Behavior in Video Streaming

XII, 108 p.online resource