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This paper shows the experimental and numerical analysis developed on a brick masonry wall of 3x2.5x0.2 m to understand the changes on its dynamic behaviour with different stiffness situations: (i) original, (ii) loaded with different load levels, (iii) damaged by horizontal in plane loads, (iv) retrofitted with Textile Reinforced Mortars (TRM) and (v) retrofitted and damaged by horizontal in plane loads. This analysis has been developed at the Civil Engineering Lab at the University of Alicante. On this masonry wall a matrix of 8 seismic accelerometers have been installed to evaluate, in plane and out of plane, changes in the main frequencies, modal damping ratios and modal shapes. By the use of Operational Modal Analysis techniques the results shows that the changes on the stiffness have important influence on the main frequencies and in the modal damping ratios. Very low influence have been detected on the modal shapes due to the low level of external vibrations generated during the tests. Due to the low level of vibrations inside the lab,the classical application of ambient vibrations for OMA has been not possible and an external white noise force has been introduced on the top the wall by the use of a shaker to generate a general level of vibrations on the specimen.

The use of predictive models is becoming widespread. However, these models should be developed appropriately (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modeling Studies [CHARMS] and Prediction model Risk Of Bias ASsessment Tool [PROBAST] statements). Concerning mortality/recurrence in oropharyngeal cancer, we are not aware of any systematic reviews of the predictive models. We carried out a systematic review of the MEDLINE/EMBASE databases of those predictive models. In these models, we analyzed the 11 domains of the CHARMS statement and the risk of bias and applicability, using the PROBAST tool. Six papers were finally included in the systematic review and all of them presented high risk of bias and several limitations in the statistical analysis. The applicability was satisfactory in five out of six studies. None of the models could be considered ready for use in clinical practice.

Introduction Predictive models must meet clinical/methodological standards to be used in clinical practice. However, no critique of those models relating to mortality/recurrence in tongue cancer has been done bearing in mind the accepted standards. Methods We conducted a systematic review evaluating the methodology and clinical applicability of predictive models for mortality/recurrence in tongue cancer published in MEDLINE and Scopus. For each model, we analysed (domains of CHARMS, Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) the following: source of data, participants, outcome to be predicted, candidate predictors, sample size, missing data, model development, model performance, model evaluation, results and interpretation and discussion. Results We found two papers that included eight prediction models, neither of which adhered to the CHARMS recommendations. Conclusion Given the quality of tongue cancer models, new studies following current consensus are needed to develop predictive tools applicable in clinical practice.

OBJECTIVES: Though predictive models have been constructed to determine the risk of recurrence in differentiated thyroid carcinoma, various aspects of these models are inadequate. Therefore, we aimed to construct, internally validate and implement on a mobile application a scoring system to determine this risk within 10 years. DESIGN: A retrospective cohort study in 1984-2016. SETTING: A Spanish region. PARTICIPANTS: We enrolled 200 patients with differentiated thyroid carcinoma without distant metastasis at diagnosis. MAIN OUTCOME MEASURES: Time-to-recurrence. A risk table was constructed based on the sum of points to estimate the likelihood of recurrence. The model was internally validated and implemented as a mobile application for Android. RESULTS: Predictive factors were follicular histology, T, N and multifocality. This risk table had a C-statistic of 0.723. The calibration was satisfactory. CONCLUSIONS: This study provides an instrument able to predict rapidly and very simply which patients with differentiated thyroid carcinoma have a greater risk of recurrence.

Background Differentiated thyroid carcinoma (DTC) is associated with an increased mortality. Few studies have constructed predictive models of all-cause mortality with a high discriminating power for patients with this disease that would enable us to determine which patients are more likely to die. Objective To construct a predictive model of all-cause mortality at 5, 10, 15 and 20 years for patients diagnosed with and treated surgically for DTC for use as a mobile application. Design We undertook a retrospective cohort study using data from 1984 to 2013. Setting All patients diagnosed with and treated surgically for DTC at a general university hospital covering a population of around 200,000 inhabitants in Spain. Participants The study involved 201 patients diagnosed with and treated surgically for DTC (174, papillary; 27, follicular). Exposures Age, gender, town, family history, type of surgery, type of cancer, histological subtype, micro-carcinoma, multicentricity, TNM staging system, diagnostic stage, permanent post-operative complications, local and regional tumor persistence, distant metastasis, and radioiodine therapy. Main outcome measure All-cause mortality. Methods A Cox multivariate regression model was constructed to determine which variables at diagnosis were associated with mortality. Using the model a risk table was constructed based on the sum of all points to estimate the likelihood of death. This was then incorporated into a mobile application. Results The mean follow-up was 8.8 +/- 6.7 years. All-cause mortality was 12.9%(95% confidence interval [CI]: 8.3- 17.6%). Predictive variables: older age, local tumor persistence and distant metastasis. The area under the ROC curve was 0.81 (95% CI: 0.72- 0.91, p< 0.001). Conclusion This study provides a practical clinical tool giving a simple and rapid indication (via a mobile application) of which patients with DTC are at risk of dying in 5, 10, 15 or 20 years. Nonetheless, caution should be exercised until validation studies have corroborated our results.