A comparative study of case-based learning with conventional teaching in undergraduate training of pharmacology

Background: Pharmacology as a specialty deals with drugs, therapies, and their application to clinical medicine. The traditional teaching approach has been through didactic lectures in medical colleges. Case-based learning (CBL) as a teaching-learning method is an inquiry-guided, conceptual, and application-based novel approach in medical education. Aims and Objectives: This study aims to evaluate the effectiveness of CBL compared to conventional method among medical graduates and evaluate the perception of students regarding CBL in pharmacology. Materials and Methods: After taking ethics committee approval (IEC/ASR APPROVAL/017/2019) and obtaining informed consent from 60 students randomly divided into two equal groups: Group 1 (CBL) and Group 2 (Conventional). Case scenarios in Type 2 diabetes mellitus and bronchial asthma, test questionnaires, and feedback forms on the perception of students for CBL were developed and validated by experts. Group 1 had CBL sessions while Group 2 had didactic lectures and was evaluated immediately after sessions and 4 weeks later. Student perceptions regarding CBL were collected and analyzed. Results: In our study, Group 1 (CBL) had significantly higher scores (P < 0.001) as compared to Group 2 in knowledge-based questions as well as application-based questions. About 90% of the students had a positive perception of CBL and insisted on its implementation in the curriculum. Conclusions: CBL is more effective than conventional teaching in certain topics of pharmacology. Retention of subject and concepts was better as compared to the conventional group.

O processo de produção científica e as dificuldades para utilização de resultados de pesquisas pelos profissionais de saúde / The health research process and obstacles to the use of research findings by health professionals / El proceso de producción científica y las dificultades para utilización de resultados de investigaciones por parte de los profesionales de salud

O estudou pretendeu conhecer os obstáculos existentes no processo de produção científica em saúde, dando ênfase à incorporação desses resultados na prática dos trabalhadores da Atenção Primária à Saúde (APS). trata-se de pesquisa qualitativa realizada em uma coordenadoria da cidade de Fortaleza, Ceará, e em um serviço de atenção primária. Foram realizados levantamento de projetos de pesquisa e entrevistas com profissionais da coordenadoria e do serviço no período de 2015 a 2016. A análise fundamentou-se na Análise de Conteúdo e os resultados revelaram que empecilhos relacionados à academia e aos serviços de saúde como questões burocráticas para entrada em campo, bem como as dificuldades do serviço em acolher o pesquisador, dificultam a utilização dos resultados das pesquisas. Para uma articulação entre saber e fazer, é necessário o empenho de pesquisadores e dos sujeitos envolvidos na prática, sejam profissionais de saúde ou gestores.(AU)

This study explored the current obstacles to the health research process, with emphasis on the application of results to the everyday practices of PrimaryHhealthcare workers. A qualitative study was conducted in a coordinating office in and primary care facility in Fortaleza, Ceará. A search of research projects and interviews with health professionals were conducted during the period 2015 to 2016. The results of the content analysis reveal obstacles to the use of research findings related to academia and health services, including bureaucratic problems linked to field work and difficulties experienced by health services in receiving researchers. Ensuring articulation between knowing and doing requires effort and commitment from both researchers and health professionals and administrators.(AU)

El objetivo del estudio fue conocer los obstáculos existentes en el proceso de producción científica en salud, enfatizando la incorporación de esos resultados en la práctica de los trabajadores de la Atención Primaria de la Salud (APS). Es una investigación cualitativa realizada en una coordinación de la ciudad de Fortaleza, Ceará, y en un servicio de atención primaria, se realizaron levantamientos de proyectos de investigación y entrevistas con profesionales de la coordinación y del servicio en el periodo de 2015 a 2016. El análisis tuvo como fundamento el Análisis de Contenido, cuyos resultados revelaron que obstáculos relacionados al sector académico y a los servicios de salud tales como cuestiones burocráticas para entrada en el campo, así como las dificultades del servicio para acoger al investigador dificultan la utilización de los resultados de las investigaciones. Para una articulación entre saber y hacer, es necesario el empeño de investigadores y de los sujetos envueltos en la práctica, sean ellos profesionales de salud o gestores.(AU)

Contrast-Enhanced CT with Knowledge-Based Iterative Model Reconstruction for the Evaluation of Parotid Gland Tumors: A Feasibility Study

OBJECTIVE: The purpose of this study was to determine the diagnostic utility of low-dose CT with knowledge-based iterative model reconstruction (IMR) for the evaluation of parotid gland tumors. MATERIALS AND METHODS: This prospective study included 42 consecutive patients who had undergone low-dose contrast-enhanced CT for the evaluation of suspected parotid gland tumors. Prior or subsequent non-low-dose CT scans within 12 months were available in 10 of the participants. Background noise (BN), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were compared between non-low-dose CT images and images generated using filtered back projection (FBP), hybrid iterative reconstruction (iDose⁴; Philips Healthcare), and knowledge-based IMR. Subjective image quality was rated by two radiologists using five-point grading scales to assess the overall image quality, delineation of lesion contour, image sharpness, and noise. RESULTS: With the IMR algorithm, background noise (IMR, 4.24 ± 3.77; iDose⁴, 8.77 ± 3.85; FBP, 11.73 ± 4.06; p = 0.037 [IMR vs. iDose⁴] and p < 0.001 [IMR vs. FBP]) was significantly lower and SNR (IMR, 23.93 ± 7.49; iDose⁴, 10.20 ± 3.29; FBP, 7.33 ± 2.03; p = 0.011 [IMR vs. iDose⁴] and p < 0.001 [IMR vs. FBP]) was significantly higher compared with the other two algorithms. The CNR was also significantly higher with the IMR compared with the FBP (25.76 ± 11.88 vs. 9.02 ± 3.18, p < 0.001). There was no significant difference in BN, SNR, and CNR between low-dose CT with the IMR algorithm and non-low-dose CT. Subjective image analysis revealed that IMR-generated low-dose CT images showed significantly better overall image quality and delineation of lesion contour with lesser noise, compared with those generated using FBP by both reviewers 1 and 2 (4 vs. 3; 4 vs. 3; and 3–4 vs. 2; p < 0.05 for all pairs), although there was no significant difference in subjective image quality scores between IMR-generated low-dose CT and non-low-dose CT images. CONCLUSION: Iterative model reconstruction-generated low-dose CT is an alternative to standard non-low-dose CT without significantly affecting image quality for the evaluation of parotid gland tumors.

Knowledge-based semi-automated optimization of intensity-modulated radiotherapy plans using a volume modulated arc therapy-configured model / 中华放射肿瘤学杂志

Objective To evaluate the feasibility and dosimetric features of a volume modulated arc therapy (VMAT)-configured model in knowledge-based optimization of fixed-field dynamic intensitymodulated radiotherapy (IMRT) plans based on the Varian RapidPlan system.Methods ① A dose-volume histogram prediction model was trained with 81 qualified preoperative VMAT plans for rectal cancer and then statistically verified.② For clinically approved 10 IMRT plans with the same dose prescription,the above model was used to automatically generate new optimization parameters and dynamic muhileaf collimator (MLC) sequences with field geometry and beam energy unchanged.③ In order to rule out the disparities between different versions,a single algorithm was used to calculate the absolute doses of the original and new plans.④ Statistical analyses were performed on dosimetric parameters after comparable target dose coverage was achieved in the two plans by appropriate normalization.Results On the basis of similar target dose homogeneity and coverage,RapidPlan significantly reduced the doses to the urinary bladder (D50％ by 9.01 Gy,P =0.000;Dmean by 8.08 Gy,P =0.005) and the femoral head (D50％ by 4.20 Gy,P =0.000;Dmean by 3.84 Gy,P=0.005) but significantly elevated the mean total number of monitor units (1211±99 vs.771±79,P=0.000) and the number of fields with multiple MLC carriage groups.The knowledge-based semi-automated optimization caused a significantly larger number of high-dose hotspots but a similar D2％ (52.54 vs.52.71 Gy,P=0.239).Conclusions The VMAT model can be used for the knowledge-based semi-automated optimization of IMRT plans to enhance the efficiency and OAR protection.However,the resulting high-dose hotspots need further manual intervention.

Dosimetric evaluation of RapidPlan model on different Radiotherapy devices / 中华放射肿瘤学杂志

Objective To evaluate the dosimetric differences of one RapidPlan Model on different Radiotherapy devices.Methods A RapidPlan Model was built based on 30 reoptimization IMRT plans of cervical cancer patients on typeA LA.Dosimetric differences of automatic optimized IMRT plans using this model on 4 different type LAs,named respectivelyA,B,C andD,were compared with 12 test cervical cancer cases.These four LAs were well commissioned in the treatment planning system (TPS).Student t test was applied for statistical analysis on dosimetric differences.Results Dosimetric differences between A vs.B,C and D were observed on Dmean,HI,CI of PTV50 and PTV45,as well as on V50,V40,V30 of rectum and bladder.Significant dosimetric differences were observed between A and D (P<0.05).Conclusions Automatic planning with RapidPlan model may result in dosimetric differences on different Radiotherapy devices.These differences should be aware of with caution in its clinical application.

Aplicaciones médicas como ayuda al diagnóstico en la medicina. Experiencia SOFTEL-MINSAP / Medical application for support of diagnosis in medicine. SOFTEL-MINSAP experience

La Inteligencia Artificial (IA) en una primera aproximación, se puede definir como la rama de la computación que estudia la automatización del comportamiento inteligente. La investigación en este campo ha llevado al desarrollo de herramientas computacionales específicas, entre las cuales se cuentan una gran diversidad de formalismos de representación de conocimientos y de algoritmos que los aplican, además de los lenguajes, estructuras de datos y técnicas de programación utilizados para su implementación. Este mecanismo es el que intentan imitar los programas de inteligencia artificial llamados sistemas expertos o sistemas basados en el conocimiento. La Empresa SOFTEL, perteneciente al Ministerio de la Informática y las Comunicaciones (MIC), desde sus inicios desarrolló la informática médica, y dentro de ésta la rama de Inteligencia Artificial en aplicaciones como INFOTOXI, encargado de controlar y diagnosticar intoxicación por productos tóxicos en centros dedicados a este tema; GERISOFT, para la Atención Primaria de Salud del adulto mayor y el SEAA, Sistema de Ayuda Diagnóstica en la Asistencia Primaria. Para desarrollar estos sistemas se apoyaron en el conocimiento de médicos especialistas del Ministerio de Salud Pública (MINSAP) en calidad de expertos. Dichos sistemas fueron instalados en diferentes unidades del sistema de salud(AU)

Artificial Intelligence (AI) in a first approximation can be defined as the branch of computer science that studies the automation of intelligent behavior. This research has led to the development of specific computational tools, which include a wide range of knowledge representation formalisms and related algorithms, in addition to the language of data structures and programming techniques used for its implementation. This mechanism is attempting to imitate the programs of artificial intelligence known as expert systems or knowledge-based systems. Softel Company, owned by the Ministry of Informatics and Communications (MIC), from its inception has developed medical informatics within this branch of artificial intelligence in applications such as INFOTOXI, in charge of monitoring and diagnosing poisoning by toxic products in centers devoted to this theme; GER-ISOFT, for Primary Health Care for the elderly and SAAS System Diagnostic Support in Primary Care. The development of these systems was supported in the knowledge of specialist doctors from the Ministry of Public Health of Cuba (MINSAP), in quality of experts in their respective subjects. These systems are deployed in different units of the health system(AU)

Modelo de sistema basado en conocimiento para apoyo en la investigación y p'roceso clínico de la diabetes / Knowledge-based system model to support diabetes research and clinical process

Due to the great amount of information generated and supported by the explosive evolution of computer science systems since the end of the last century, the expansion and transference of scientific knowledge has caused a rapid transformation of scientific discoveries in products and applications that have positive effects in the life quality of societies. Today, a great amount of data in medicine is obtained by the application of biotechnological methods that constantly evolve. Thus, scientific research related to diabetes keeps improving. In this context, productivity and competitiveness must be sustained on knowledge which facilitates and encourages organizational innovation capacity. For this reason, knowledge based systems emerge as a useful tool to help organizations solve difficult assignments or improve their processes. In this work, derivate from known diabetes group of symptoms and interactions that diabetes research maintains with the biotechnological processes, the authors carried out a brief analysis of the knowledge involved as well as the role that knowledge-based systems have played, and keep playing in support of them. Additionally, with the systemic perspective obtained by the authors regarding aspects like knowledge, practices and resources needed in clinical and laboratory practices, they propose a systemic model that can support diabetes research and clinical process.

Debido a la gran cantidad de información generada y apoyada por la evolución explosiva de sistemas de la ciencia computacional, desde finales del siglo pasado, la expansión y transferencia de conocimiento científico ha provocado una rápida transformación de los descubrimientos científicos en productos y aplicaciones que afectan positivamente la calidad de vida de las sociedades. Actualmente, una gran cantidad de datos en medicina se obtiene por la aplicación de métodos biotecnológicos que constantemente evolucionan. De igual manera, la investigación científica sobre diabetes mantiene una mejora constante. En este contexto, tanto la productividad como la competitividad se deben apoyar con conocimiento que facilite y promueva la capacidad de innovación organizacional. Por esta razón, los sistemas basados en conocimiento emergen como una herramienta útil para coadyuvar con las organizaciones en la solución de situaciones difíciles o en la mejora de sus procesos. En este trabajo, derivado del conocido grupo de síntomas y de las interacciones que la investigación en diabetes mantiene con los procesos biotecnológicos, los autores realizan un breve análisis del conocimiento implicado y del rol que los sistemas basados en el conocimiento han desempeñado, -y continúan desempeñando, en apoyo a tales procesos. Adicionalmente, con la perspectiva sistémica obtenida por los autores respecto al conocimiento y recursos necesarios en prácticas clínicas y de laboratorio, proponen un modelo sistémico capaz de apoyar la investigación y el proceso clínico de la diabetes.

Development of Rule-based Expert System for Interpretative Report with Health Screening Tests / 영남의대학술지

BACKGROUND: Interpretative reporting is an important aspect of laboratory medicine. The large menu of laboratory tests available today makes it increasingly difficult for the non-specialist to order and interpret all laboratory tests. The aim of this study was to determine the usefulness of an expert system to interpret laboratory tests and help physicians order the appropriate tests. MATERIALS AND METHODS: In order to interpret laboratory tests, a rules-based expert system was developed. In this module, if-then rules were used to interpret the given test result patterns (e.g. urinalysis, anemia, hepatitis B virus, hypercholesterolemia, glucose, syphilis, and tumor markers) and select matching text elements. The system was used to evaluate 535 subjects who visited a health-check program. RESULTS: The overall abnormal rate was 50.5% in the expert system; 34% for cholesterol, 9.9% for urinalysis, 8.0% for anemia, 7.7% for thyroid function tests, 4.5% for tumor marker study, 4.7% for hepatitis virus antigen, 4.3% for serum glucose, and 1.1% for syphilis. CONCLUSION: These results indicate that the application of the expert system for the interpretation of laboratory tests may provide a useful method for the interpretation of reports. However more rules are needed for the application to in-patients.