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Studies reported that patients were mostly satisfied with TB care services, and those that were dissatisfied were substantially more likely to be lost to follow-up. The high satisfaction rates could have been due to lack of education on good quality patient care or fear of losing access to health care. A standardized patient centered tool could be designed to help assess user experience and patient satisfaction to allow comparisons among health systems and countries. © 2020 The Author(s).Vascular bypass graft infection with Mycobacterium bovis following Bacillus Calmette-Guérin (BCG) immunotherapy for bladder cancer is an incredibly rare complication. We present the case of an 85-year-old man with a history of femorofemoral bypass who developed this complication over a year after BCG treatment. He was successfully treated with explantation of the polytetrafluoroethylene (PTFE) graft, redo bypass with vein graft, and antituberculous medical therapy. © 2020 The Author(s).Wearable devices, like smartwatches, are increasingly used for tracking physical activity, community mobility, and monitoring symptoms. Data generated from smartwatches (PGHD_SW) is a form of patient-generated health data, which can benefit providers by supplying frequent temporal information about patients. The goal of this study was to understand providers' perceptions towards PGHD_SW adoption and its integration with electronic medical records. In-depth, semi-structured qualitative interviews were conducted with 12 providers from internal medicine, family medicine, geriatric medicine, nursing, surgery, rehabilitation, and anesthesiology. Diffusion of Innovations was used as a framework to develop questions and guide data analysis. The constant comparative method was utilized to formulate salient themes from the interviews. Four main themes emerged (1) PGHD_SW is perceived as a relative advantage; (2) data are viewed as compatible with current practices; (3) barriers to overcome to effectively use PGHD_SW; (4) assessments from viewing sample data. Overall, PGHD_SW was valued because it enabled access to information about patients that were traditionally unattainable. It also can initiate discussions between patients and providers. Providers consider PGHD_SW important, but data preferences varied by specialty. The successful adoption of PGHD_SW will depend on tailoring data, frequencies of reports, and visualization preferences to correspond with the demands of providers. © The Author(s) 2020.Social interaction deficits are evident in many psychiatric conditions and specifically in autism spectrum disorder (ASD), but hard to assess objectively. We present a digital tool to automatically quantify biomarkers of social interaction deficits the simulated interaction task (SIT), which entails a standardized 7-min simulated dialog via video and the automated analysis of facial expressions, gaze behavior, and voice characteristics. In a study with 37 adults with ASD without intellectual disability and 43 healthy controls, we show the potential of the tool as a diagnostic instrument and for better description of ASD-associated social phenotypes. Using machine-learning tools, we detected individuals with ASD with an accuracy of 73%, sensitivity of 67%, and specificity of 79%, based on their facial expressions and vocal characteristics alone. Especially reduced social smiling and facial mimicry as well as a higher voice fundamental frequency and harmony-to-noise-ratio were characteristic for individuals with ASD. The time-effective and cost-effective computer-based analysis outperformed a majority vote and performed equal to clinical expert ratings. © The Author(s) 2020.Storing very large amounts of data and delivering them to researchers in an efficient, verifiable, and compliant manner, is one of the major challenges faced by health care providers and researchers in the life sciences. The electronic health record (EHR) at a hospital or clinic currently functions as a silo, and although EHRs contain rich and abundant information that could be used to understand, improve, and learn from care as part learning health system access to these data is difficult, and the technical, legal, ethical, and social barriers are significant. If we create a microservice ecosystem where data can be accessed through APIs, these challenges become easier to overcome a service-driven design decouples data from clients. This decoupling provides flexibility different users can write in their preferred language and use different clients depending on their needs. APIs can be written for iOS apps, web apps, or an R library, and this flexibility highlights the potential ecosystem-building power of APIs. In this article, we use two case studies to illustrate what it means to participate in and contribute to interconnected ecosystems that powers APIs in a healthcare systems. © The Author(s) 2020.Artificial intelligence (AI) algorithms continue to rival human performance on a variety of clinical tasks, while their actual impact on human diagnosticians, when incorporated into clinical workflows, remains relatively unexplored. In this study, we developed a deep learning-based assistant to help pathologists differentiate between two subtypes of primary liver cancer, hepatocellular carcinoma and cholangiocarcinoma, on hematoxylin and eosin-stained whole-slide images (WSI), and evaluated its effect on the diagnostic performance of 11 pathologists with varying levels of expertise. Our model achieved accuracies of 0.885 on a validation set of 26 WSI, and 0.842 on an independent test set of 80 WSI. Although use of the assistant did not change the mean accuracy of the 11 pathologists (p = 0.184, OR = 1.281), it significantly improved the accuracy (p = 0.045, OR = 1.499) of a subset of nine pathologists who fell within well-defined experience levels (GI subspecialists, non-GI subspecialists, and trainees). In the assisted state, model accuracy significantly impacted the diagnostic decisions of all 11 pathologists. As expected, when the model's prediction was correct, assistance significantly improved accuracy (p = 0.000, OR = 4.289), whereas when the model's prediction was incorrect, assistance significantly decreased accuracy (p = 0.000, OR = 0.253), with both effects holding across all pathologist experience levels and case difficulty levels. Our results highlight the challenges of translating AI models into the clinical setting, and emphasize the importance of taking into account potential unintended negative consequences of model assistance when designing and testing medical AI-assistance tools. © The Author(s) 2020.Introduction Pre-exposure prophylaxis (PrEP) is provided free of costs to at-risk populations in Kenya, including men who have sex with men (MSM), but anal intercourse is not an eligibility criterion. We set out to determine PrEP eligibility, uptake and predictors of PrEP uptake among MSM enrolled in an HIV-1 vaccine feasibility cohort in coastal Kenya. EGFR inhibitors cancer Methods We compared the number of MSM identified as eligible for PrEP from June-December 2017 by Kenyan Ministry of Health (MoH) criteria, which do not include reported anal intercourse, to those identified as eligible by a published MSM cohort-derived HIV-1 risk score (CDHRS). We determined PrEP uptake and assessed factors associated with uptake at first offer among eligible MSM followed up monthly for HIV-1 testing, risk assessment, and risk reduction counselling. Results Out of 167 MSM assessed for PrEP eligibility, 118 (70.7%) were identified by both MoH and CDHRS eligibility criteria. However, the CDHRS identified 33 (19.8%) more cohort MSM for PrEP eligibility than the MoH criteria, of whom the majority (24 or 72.7%) reported receptive anal intercourse (RAI). Of the 162 MSM eligible for PrEP, 113 (69.7%) accepted PrEP at first offer. Acceptance of PrEP was higher for men reporting RAI (adjusted prevalence ratio [aPR], 1.4; 95% confidence interval [CI], 1.0-1.9), having paid for sex (aPR, 1.3; 95% CI, 1.1-1.6) and group sex (aPR, 1.4; 95% CI, 1.1-1.8), after adjustment for sociodemographic factors. Conclusions Assessing PrEP eligibility using a CDHRS identified 20% more at-risk MSM for PrEP initiation than when Kenyan MoH criteria were used. Approximately 70% of eligible men accepted PrEP at first offer, suggesting that PrEP is acceptable among at-risk MSM. MSM reporting RAI, group sex, or paying for sex were more likely to accept PrEP, reinforcing the importance of an informed discussion of HIV-1 risk during PrEP counselling. Copyright © 2019 Wahome E et al.The DBCG89D trial randomized high-risk early breast cancer patients to adjuvant CMF (cyclophosphamide, methotrexate and fluorouracil) or CEF (cyclophosphamide, epirubicin and fluorouracil). Prosigna assays were performed by researchers with no access to clinical data. Time to distant recurrence (DR) was the primary endpoint, time to recurrence (TR) and overall survival (OS) secondary. Among the 980 Danish patients enrolled, Prosigna results were obtained in 686. Continuous ROR score was associated with DR for CMF (adjusted hazard ratio (HR) 1.20, 95% CI 1.09-1.33), and for CEF (HR 1.04, 95% CI 0.92-1.18), P interaction = 0.06. DR was significantly longer in CEF compared to CMF treated patients with Her2-enriched tumors (HR 0.58, 95% CI 0.38-0.86), but not in patients with luminal tumors. Heterogeneity of treatment effect was significant for TR and OS. In this prospective-retrospective analysis, patients with Her2-enriched breast cancer derived substantial benefit from anthracycline chemotherapy whereas anthracyclines are not an essential component of chemotherapy for patients with luminal subtypes. The benefit of CEF vs. CMF correlated with increasing ROR Score. © The Author(s) 2020.Human cytomegalovirus (HCMV) components are often found in tumors, but the precise relationship between HCMV and cancer remains a matter of debate. Pro-tumor functions of HCMV were described in several studies, but an association between HCMV seropositivity and reduced cancer risk was also evidenced, presumably relying on recognition and killing of cancer cells by HCMV-induced lymphocytes. This study aimed at deciphering whether CMV influences cancer development in an immune-independent manner. Using immunodeficient mice, we showed that systemic infection with murine CMV (MCMV) inhibited the growth of murine carcinomas. Surprisingly, MCMV, but not HCMV, also reduced human colon carcinoma development in vivo. In vitro, both viruses infected human cancer cells. Expression of human interferon-β (IFN-β) and nuclear domain (ND10) were induced in MCMV-infected, but not in HCMV-infected human colon cancer cells. These results suggest a decreased capacity of MCMV to counteract intrinsic defenses in the human cellular host. Finally, immunodeficient mice receiving peri-tumoral MCMV therapy showed a reduction of human colon cancer cell growth, albeit no clinical sign of systemic virus dissemination was evidenced. Our study, which describes a selective advantage of MCMV over HCMV to control human colon cancer, could pave the way for the development of CMV-based therapies against cancer. © 2020 The Author(s).
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