Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects

[EN] Quality of life (QoL) indicators are now being adopted as clinical outcomes in clinical trials on cancer treatments. Technology-free daily monitoring of patients is complicated, time-consuming and expensive due to the need for vast amounts of resources and personnel. The alternative method of using the patients¿ own phones could reduce the burden of continuous monitoring of cancer patients in clinical trials. This paper proposes monitoring the patients¿ QoL by gathering data from their own phones. We considered that the continuous multiparametric acquisition of movement, location, phone calls, conversations and data use could be employed to simultaneously monitor their physical, psychological, social and environmental aspects. An open access phone app was developed (Human Dynamics Reporting Service (HDRS)) to implement this approach. We here propose a novel mapping between the standardized QoL items for these patients, the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) and define HDRS monitoring indicators. A pilot study with university volunteers verified the plausibility of detecting human activity indicators directly related to QoL.Funding for this study was provided by the authors' various departments, and partially by the CrowdHealth Project (Collective Wisdom Driving Public Health Policies (727560)) and the MTS4up project (DPI2016-80054-R).Asensio Cuesta, S.; Sánchez-García, Á.; Conejero, JA.; Sáez Silvestre, C.; Rivero-Rodriguez, A.; Garcia-Gomez, JM. (2019). Smartphone sensors for monitoring cancer-related Quality of Life: App design, EORTC QLQ-C30 mapping and feasibility study in healthy subjects. 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Skin and Soft Tissue Infections (Patera Foot) in Immigrants, Spain

An unusual skin and soft tissue infection of the lower limbs has been observed in immigrants from sub-Saharan Africa who cross the Atlantic Ocean crowded on small fishing boats (pateras). Response to conventional treatment is usually poor. Extreme extrinsic factors (including new pathogens) may contribute to the etiology of the infection and its pathogenesis

Childhood asthma outcomes during the COVID-19 pandemic: Findings from the PeARL multinational cohort

Background The interplay between COVID-19 pandemic and asthma in children is still unclear. We evaluated the impact of COVID-19 pandemic on childhood asthma outcomes.Methods The PeARL multinational cohort included 1,054 children with asthma and 505 non-asthmatic children aged between 4 and 18 years from 25 pediatric departments, from 15 countries globally. We compared the frequency of acute respiratory and febrile presentations during the first wave of the COVID-19 pandemic between groups and with data available from the previous year. In children with asthma, we also compared current and historical disease control.Results During the pandemic, children with asthma experienced fewer upper respiratory tract infections, episodes of pyrexia, emergency visits, hospital admissions, asthma attacks, and hospitalizations due to asthma, in comparison with the preceding year. Sixty-six percent of asthmatic children had improved asthma control while in 33% the improvement exceeded the minimal clinically important difference. Pre-bronchodilatation FEV1 and peak expiratory flow rate were improved during the pandemic. When compared to non-asthmatic controls, children with asthma were not at increased risk of LRTIs, episodes of pyrexia, emergency visits, or hospitalizations during the pandemic. However, an increased risk of URTIs emerged.Conclusion Childhood asthma outcomes, including control, were improved during the first wave of the COVID-19 pandemic, probably because of reduced exposure to asthma triggers and increased treatment adherence. The decreased frequency of acute episodes does not support the notion that childhood asthma may be a risk factor for COVID-19. Furthermore, the potential for improving childhood asthma outcomes through environmental control becomes apparent.</p

Development and validation of a sexual relations satisfaction scale in patients with breast cancer - "SEXSAT-Q".

Because the currently available questionnaires to evaluate sexual changes on breast cancer women only address the sexual sphere with a few questions our purpose was to develop a questionnaire that assesses changes in sexual dysfunction and satisfaction in women treated for breast cancer. A sample was selected of women aged between 18 and 65 who had had surgery for breast cancer, completed neoadjuvant/adjuvant chemotherapy treatment and could be receiving adjuvant hormonal treatment, with an active sex life at least 3 months before starting treatment. Metastatic disease was excluded. A questionnaire structured in 4 dimensions was developed. The MOS SF-12 and QLQ-BR23 questionnaires were also provided. The following metric properties were evaluated: item analysis; internal consistency; temporal stability; construct validity; concurrent, convergent and divergent validity; and feasibility. Three samples were recruited: a pilot sample of 20; a reduction sample of 152; and a validation sample of 148. The presence of 6 dimensions was confirmed: 1) Loss of sex drive; 2) worsening of body image; 3) psychological coping; 4) discomfort during intercourse; 5) satisfaction with sexual relations; and 6) satisfaction with breast reconstruction. Good goodness-of-fit statistics were obtained (χ2/df = 1.5, GFI = 0.9, AGFI = 0.84, CFI = 0.959, RMSEA = 0.062). Reliability was good (α = 0.855), as was test-retest stability (r = 0.838). The correlation with the convergent questionnaires proved to be higher than that obtained with generic measurements. We were able to develop a short questionnaire (17 items) capable of measuring sexual satisfaction in women with breast cancer with good metric properties

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts