Moddicom: a Complete and Easily Accessible Library for Prognostic Evaluations Relying on Image Features

Decision Support Systems (DSSs) are increasingly exploited in the area of prognostic evaluations. For predicting the effect of therapies on patients, the trend is now to use image features, i.e. information that can be automatically computed by considering images resulting by analysis. The DSSs application as predictive tools is particularly suitable for cancer treatment, given the peculiarities of the disease –which is highly localised and lead to significant social costs– and the large number of images that are available for each patient. At the state of the art, there exists tools that allow to handle image features for prognostic evaluations, but they are not designed for medical experts. They require either a strong engineering or computer science background since they do not integrate all the required functions, such as image retrieval and storage. In this paper we fill this gap by proposing Moddicom, a user-friendly complete library specifically designed to be exploited by physicians. A preliminary experimental analysis, performed by a medical expert that used the tool, demonstrates the efficiency and the effectiveness of Moddicom

Higher risk of tuberculosis reactivation when anti-TNF is combined with immunosuppressive agents. A systematic review of randomized controlled trials

Objective. Treatment with tumour necrosis factor antagonists (anti-TNF) has been recognized as a risk factor for tuberculosis (TB) reactivation. Our aim was to evaluate risk of TB reactivation in rheumatologic and non-rheumatologic diseases treated with the same anti-TNF agents with and without concomitant therapies. Methods. We searched for randomized controlled trials (RCTs) evaluating infliximab, adalimumab, and certolizumab in both rheumatologic and non-rheumatologic diseases until 2012. Results were calculated as pooled rates and/or pooled odd ratios (OR). Results. Overall, 40 RCTs with a total of 14,683 patients (anti-TNF: 10,010; placebo: 4673) were included. TB reactivation was 0.26% (26/10,010) in the anti-TNF group and 0% (0/4673) in the control group, corresponding to an OR of 24.8 (95% CI 2.4-133). TB risk was higher when anti-TNF agents were combined with methotrexate or azathioprine as compared with either controls (24/4241 versus 0/4673; OR 54; 95% CI 5.3-88) or anti-TNF monotherapy (24/4241 versus 2/5769; OR 13.3; 95% CI 3.7-100). When anti-TNF was used as monotherapy, TB risk tended to be higher than placebo (2/5769 versus 0/4673; OR 4; 95% CI 0.2-15.7). Conclusions. TB risk with anti-TNF agents appeared to be increased when these agents were used in combination with methotrexate or azathioprine as compared with monotherapy regimen. TB risk seemed to be higher than placebo, even when monotherapy is prescribed

Development and validation of a machine learning-based predictive model to improve the prediction of inguinal status of anal cancer patients: A preliminary report

Introduction: The role of prophylactic inguinal irradiation (PII) in the treatment of anal cancer patients is controversial. We developped an innovative algorithm based on the Machine Learning (ML) allowing the tailoring of the prescription of PII. Results: Once verified on the independent testing set, J48 showed the better performances, with specificity, sensitivity, and accuracy rates in predicting relapsing patients of 86.4%, 50.0% and 83.1% respectively (vs 36.5%, 90.4% and 80.25%, respectively, for LR). Methods: We classified 194 anal cancer patients with Logistic Regression (LR) and other 3 ML techniques based on decision trees (J48, Random Tree and Random Forest), using a large set of clinical and therapeutic variables. We tested obtained ML algorithms on an independent testing set of 65 anal cancer patients. TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis) methodology was used for the development, the Quality Assurance and the description of the experimental procedures. Conclusion: In an internationally approved quality assurance framework, ML seems promising in predicting the outcome of patients that would benefit or not of the PII. Once confirmed in larger and/or multi-centric databases, ML could support the physician in tailoring the treatment and in deciding if deliver or not the PII

Process Mining Dashboard in Operating Rooms: Analysis of Staff Expectations with Analytic Hierarchy Process

[EN] The widespread adoption of real-time location systems is boosting the development of software applications to track persons and assets in hospitals. Among the vast amount of applications, real-time location systems in operating rooms have the advantage of grounding advanced data analysis techniques to improve surgical processes, such as process mining. However, such applications still find entrance barriers in the clinical context. In this paper, we aim to evaluate the preferred features of a process mining-based dashboard deployed in the operating rooms of a hospital equipped with a real-time location system. The dashboard allows to discover and enhance flows of patients based on the location data of patients undergoing an intervention. Analytic hierarchy process was applied to quantify the prioritization of the dashboard features (filtering data, enhancement, node selection, statistics, etc.), distinguishing the priorities that each of the different roles in the operating room service assigned to each feature. The staff in the operating rooms (n = 10) was classified into three groups: Technical, clinical, and managerial staff according to their responsibilities. Results showed different weights for the features in the process mining dashboard for each group, suggesting that a flexible process mining dashboard is needed to boost its potential in the management of clinical interventions in operating rooms. This paper is an extension of a communication presented in the Process-Oriented Data Science for Health Workshop in the Business Process Management Conference 2018.This project received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No 812386.Martinez-Millana, A.; Lizondo, A.; Gatta, R.; Vera, S.; Traver Salcedo, V.; Fernández Llatas, C. (2019). Process Mining Dashboard in Operating Rooms: Analysis of Staff Expectations with Analytic Hierarchy Process. International Journal of Environmental research and Public Health. 16(2):1-14. https://doi.org/10.3390/ijerph16020199S114162Agnoletti, V., Buccioli, M., Padovani, E., Corso, R. M., Perger, P., Piraccini, E., … Gambale, G. (2013). Operating room data management: improving efficiency and safety in a surgical block. BMC Surgery, 13(1). doi:10.1186/1471-2482-13-7Marques, I., Captivo, M. E., & Vaz Pato, M. (2011). An integer programming approach to elective surgery scheduling. 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(2011). doi:10.1145/1978942Anual Report 2014http://chguv.san.gva.es/documents/10184/81032/Informe_anual2014.pdf/713c6559-0e29-4838-967c-93380c24eff9Ratwani, R. M., Fairbanks, R. J., Hettinger, A. Z., & Benda, N. C. (2015). Electronic health record usability: analysis of the user-centered design processes of eleven electronic health record vendors. Journal of the American Medical Informatics Association, 22(6), 1179-1182. doi:10.1093/jamia/ocv050Van der Aalst, W. M. P., Reijers, H. A., Weijters, A. J. M. M., van Dongen, B. F., Alves de Medeiros, A. K., Song, M., & Verbeek, H. M. W. (2007). Business process mining: An industrial application. Information Systems, 32(5), 713-732. doi:10.1016/j.is.2006.05.00

Crohn's Disease Imaging: A Review

Crohn's disease is a chronic granulomatous inflammatory disease of the gastrointestinal tract, which can involve almost any segment from the mouth to the anus. Typically, Crohn's lesions attain segmental and asynchronous distribution with varying levels of seriousness, although the sites most frequently involved are the terminal ileum and the proximal colon. A single gold standard for the diagnosis of CD is not available and the diagnosis of CD is confirmed by clinical evaluation and a combination of endoscopic, histological, radiological, and/or biochemical investigations. In recent years, many studies have been performed to investigate the diagnostic potential of less invasive and more patient-friendly imaging modalities in the evaluation of Crohn's disease including conventional enteroclysis, ultrasonography, color-power Doppler, contrast-enhanced ultrasonography, multidetector CT enteroclysis, MRI enteroclysis, and 99mTc-HMPAO-labeled leukocyte scintigraphy. The potential diagnostic role of each imaging modality has to be considered in different clinical degrees of the disease, because there is no single imaging technique that allows a correct diagnosis and may be performed with similar results in every institution. The aim of this paper is to point out the advantages and limitations of the various imaging techniques in patients with suspected or proven Crohn's disease

Targeting Food Allergy with Probiotics.

The dramatic increase in food allergy prevalence and severity globally is demanding effective strategies. Food allergy derives from a defect in immune tolerance mechanisms. Immune tolerance is modulated by gut microbiota composition and function, and gut microbiota dysbiosis has been associated with the development of food allergy. Selected probiotic strains could act on immune tolerance mechanisms. The mechanisms are multiple and still not completely defined. Increasing evidence is providing useful information on the choice of optimal bacterial species/strains, dosage, and timing for intervention. The increased knowledge on the crucial role played by gut microbiota-derived metabolites, such as butyrate, is also opening the way to a postbiotic approach in the stimulation of immune tolerance

Sequence-specific transcription factor NF-Y displays histone-like DNA binding and H2B-like ubiquitination

SummaryThe sequence-specific transcription factor NF-Y binds the CCAAT box, one of the sequence elements most frequently found in eukaryotic promoters. NF-Y is composed of the NF-YA and NF-YB/NF-YC subunits, the latter two hosting histone-fold domains (HFDs). The crystal structure of NF-Y bound to a 25 bp CCAAT oligonucleotide shows that the HFD dimer binds to the DNA sugar-phosphate backbone, mimicking the nucleosome H2A/H2B-DNA assembly. NF-YA both binds to NF-YB/NF-YC and inserts an α helix deeply into the DNA minor groove, providing sequence-specific contacts to the CCAAT box. Structural considerations and mutational data indicate that NF-YB ubiquitination at Lys138 precedes and is equivalent to H2B Lys120 monoubiquitination, important in transcriptional activation. Thus, NF-Y is a sequence-specific transcription factor with nucleosome-like properties of nonspecific DNA binding and helps establish permissive chromatin modifications at CCAAT promoters. Our findings suggest that other HFD-containing proteins may function in similar ways

A Process Mining Approach to Statistical Analysis: Application to a Real-World Advanced Melanoma Dataset

AbstractThanks to its ability to offer a time-oriented perspective on the clinical events that define the patient's path of care, Process Mining (PM) is assuming an emerging role in clinical data analytics. PM's ability to exploit time-series data and to build processes without any a priori knowledge suggests interesting synergies with the most common statistical analyses in healthcare, in particular survival analysis. In this work we demonstrate contributions of our process-oriented approach in analyzing a real-world retrospective dataset of patients treated for advanced melanoma at the Lausanne University Hospital. Addressing the clinical questions raised by our oncologists, we integrated PM in almost all the steps of a common statistical analysis. We show: (1) how PM can be leveraged to improve the quality of the data (data cleaning/pre-processing), (2) how PM can provide efficient data visualizations that support and/or suggest clinical hypotheses, also allowing to check the consistency between real and expected processes (descriptive statistics), and (3) how PM can assist in querying or re-expressing the data in terms of pre-defined reference workflows for testing survival differences among sub-cohorts (statistical inference). We exploit a rich set of PM tools for querying the event logs, inspecting the processes using statistical hypothesis testing, and performing conformance checking analyses to identify patterns in patient clinical paths and study the effects of different treatment sequences in our cohort