Analysis of Early Postoperative Morbidity Among Patients with Rectal Cancer Treated with and without Neoadjuvant Chemoradiotherapy

Background: The impact of neoadjuvant treatment and their subsequent early complications in the treatment of rectal cancer has not been adequately assessed. The aim of this prospective study was to evaluate early postoperative morbidity and mortality among patients with rectal cancer treated with adjuvant radiotherapy and chemotherapy followed by surgery, compared with patients treated with surgery alone. We also identified independent risk factors associated with early major complications. Methods: Between 1995 and 2004, 273 consecutive patients underwent treatment for rectal cancer. A total of 170 patients (group A) received preoperative radiotherapy with a total of 45–50.4 Gy (180 cGy per day) and 5-fluorouracil-based chemotherapy, followed by surgery; 103 patients (group B) were treated with surgery alone. Dependent variables related to patients, treatment, radiotherapy, and tumor were analyzed. Results: Both groups were similar with regard to age, sex, body mass index, American Society of Anesthesiologists (ASA) score, and tumor location but not for ileostomy (27% in group A vs. 6.8% in group B). The number of complications was similar in both groups (43.1% in group A vs. 44.6% in group B). No differences in wound infection (8.2% vs. 7.8%), intraabdominal abscess (4.7% vs. 4.9%), anastomotic dehiscence (4.2% vs. 3.8%), postoperative hemorrhage (3.5% vs. 3.9%), urinary complications (6.5% vs. 4.9%), paralytic ileus (8.9% vs. 9.7%), or general complications (7.1% vs. 9.6%) were found. The global mortality in the first 30 days after surgery was .7%. An ASA score of III–IV and surgery duration longer than 3 hours were identified as independent prognostic factors for early complications. Conclusions: Preoperative chemoradiation in patients with rectal cancer treated with surgery is not associated with a higher incidence of early postoperative complications. The patient~s preoperative clinical condition and lengthy surgery time are prognostic factors for early complications

Analysis of POSSUM score and postoperative morbidity in patients with rectal cancer undergoing surgery

The Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) and later modifications (P-POSSUM y CR-POSSUM) have been used to predict morbidity and mortality rates among patients with rectal cancer undergoing surgery. These calculations need some adjustment, however. The aim of this study was to assess the applicability of POSSUM to a group of patients with rectal cancer undergoing surgery, analysing surgical morbidity by means of several variables. METHODS: between January 1995 and December 2004, 273 consecutive patients underwent surgery for rectal cancer. Information was gathered about the patients, tumour and therapy. To assess the prediction capacity of POSSUM, subgroups for analysis were created according to variables related to operative morbidity and mortality. RESULTS: The global morbidity rate was 23.6% (31.2% predicted by POSSUM). The mortality rate was 0.7% (6.64, 1.95 and 2.08 predicted by POSSUM, P-POSSUM and CR-POSSUM respectively). POSSUM predictions may be more accurate for patients younger than 51 years, older than 70 years, with low anaesthetic risk (ASA I/II), DUKES stage C and D, surgery duration of less than 180 minutes and for those receiving neoadjuvant therapy. CONCLUSION: POSSUM is a good instrument to make results between different institutions and publication comparable. We found prediction errors for some variables related to morbidity. Modifications of surgical variables and specifications for neoadjuvant therapy as well as physiological variables including life style may improve future prediction of surgical risk. More research is needed to identify further potential risk factors for surgical complications

Trabajando con alienígenas: gestión de emociones como clave del éxito

La globalización y la revolución digital han generado numerosos beneficios, pero también han provocado cambios radicales en el entorno laboral. Para en- frentarse a ellos con éxito ya no es suficiente el conocimiento, sino que es pre- ciso saber interactuar con todos los actores: jefes, compañeros y empleados. TRABAJANDO CON ALIENÍGENAS presenta técnicas y herramientas concretas para desarrollar las habilidades personales, tanto en la gestión como en las re- laciones cotidianas, que se precisan en el trabajo en equipo. Este libro expone numerosos casos reales que nos enseñan a actuar y dar res- puestas útiles a las interacciones laborales y al trato con ‘alienígenas’. Cómo hacerte valorar en el trabajo Navegar en modelos tóxicos de autoridad Aprender a negociar a tu favorSin financiaciónNo data (2016)UE

Manual práctico de inteligencia artificial en entornos sanitarios

Sin financiaciónNo data 2020UE

Impact of the first interprofessional education undergraduate program in Spain

In 2015, the Universidad Europea de Madrid started the first interprofessional education program in Spain. Nursing students undergo different interprofessional education activities in all 4 academic years, covering various aspects of the following 3 competencies: interprofessional communication, role clarification (definition, interaction and defense), and authority models and decision making. In second year, they integrate these activities with students from psychology, pharmacy and medicine. We assessed the self-perception of second year nursing students with an adapted and validated IPEC questionnaire, in four different transversal moments of the academic year 2015-16. Differences in mean values were analyzed with the Kruskal-Wallis test and post-hoc Mann-Whitney tests with Bonferroni corrections in case of statistical significance. Results showed that this IPE program improves the self-perception second year students have about their competence in interprofessional communication, especially in the dimensions of oral expression, active listening, communication tools and interprofessional conflict resolution.Sin financiación1.772 JCR (2018) Q3, 46/82 Health Policy & Services, 61/98 Health Care Sciences & Services0.864 SJR (2018) Q2, 712/2844 Medicine (miscellaneous)No data IDR 2018UE

Comparison of machine learning algorithms for clinical event prediction (risk of coronary heart disease)

The aim of this study is to compare the utility of several supervised machine learning (ML) algorithms for predicting clinical events in terms of their internal validity and accuracy. The results, which were obtained using two statistical software platforms, were also compared. The data used in this research come from the open database of the Framingham Heart Study, which originated in 1948 in Framingham, Massachusetts as a prospective study of risk factors for cardiovascular disease. Through data mining processes, three data models were elaborated and a comparative methodological study between the different ML algorithms – decision tree, random forest, support vector machines, neural networks, and logistic regression – was carried out. The global selection criterium for choosing the right set of hyperparameters and the type of data manipulation was the area under a curve (AUC). The software tools used to analyze the data were R-Studio® and RapidMiner®. The Framingham study open database contains 4240 observations. The algorithm that yielded the greatest AUC when analyzing the data in R-Studio was neural network applied to a model that excluded all observations in which there was at least one missing value (AUC = 0.71); when analyzing the data in RapidMiner and applying the same model, the best algorithm was support vector machines (AUC = 0.75). ML algorithms can reinforce the diagnostic and prognostic capacity of traditional regression techniques. Differences between the applicability of those algorithms and the results obtained with them were a function of the software platforms used in the data analysis.2019/UEM113.526 JCR (2019) Q2, 32/109 Computer Science, Interdisciplinary Applications, 7/27 Medical Informatics1.140 SJR (2019) Q1, 115/1377 Computer Science Applications, 10/141 Health InformaticsNo data IDR 2019UE

Clínica Integrada-ME162-201901

Curso de especialidad de la carrera de medicina de carácter teórico- práctico del ciclo 7 en el que los estudiantes al establecer una buena relación con el paciente y/o familiar realizan la anamnesis que es una entrevista dirigida al problema de salud que presenta el paciente realizan el examen físico e integran conocimientos que servirán para establecer el diagnostico por síndromes o problemas y el plan de trabajo.El curso de Clínica integrada busca desarrollar las competencias generales de Comunicación escrita y Comunicación oral(nivel 2) y las competencias específicas de práctica clínica-diagnóstico (nivel 2) y profesionalismo-sentido ético y legal y responsabilidad profesional(nivel 2).La elaboración de una historia clínica orientada por problemas permitirá al estudiante plantear un adecuado plan de trabajo y terapéutico para su paciente