Una mirada a las series de casos y sus unidades de análisis

Las series de casos constituyen un tipo particular de estudio de uso muy frecuente en la investigación clínica. En este artículo se pretende resaltar la utilidad y plena vigencia de estos estudios como propuestas de proyectos de terminación de la especialidad, así como abordar sus particularidades más importantes en la delimitación de sus unidades de análisis. Cuando son bien realizadas, estas investigaciones constituyen una excelente fuente de actualización del conocimiento médico y una magnífica oportunidad para que los investigadores jóvenes se entrenen en el campo de la investigación científica.

Case series are a particular type of study that is very frequently used in clinical research. This article intends to highlight the usefulness and full validity of these studies as proposals for completion projects of the specialty, as well as to address their most important particularities in the delimitation of their analysis units. When they are well carried out, these researches constitute an excellent source of updating medical knowledge and a magnificent opportunity for young researchers to train in the scientific research field.

Assessment of the dissimilarities of totally 186 countries and regions according to COVID-19 indicators at the end of March 2020.

Background: This study is aimed at evaluating the relationship between the number of days elapsed since a country's first case(s) of coronavirus disease 2019 (COVID-19), the total number of tests conducted, and outbreak indicators such as the total numbers of cases, deaths, and patients who recovered. The study compares COVID-19 indicators among countries and clusters them according to similarities in the indicators. Methods: Descriptive statistics of the indicators were computed and the results were presented in figures and tables. A fuzzy c-means clustering algorithm was used to cluster/group the countries according to the similarities in the total numbers of patients who recovered, deaths, and active cases. Results: The highest numbers of COVID-19 cases were found in Gibraltar, Spain, Switzerland, Liechtenstein and Italy were also of that order with about 1500 cases per million population. Spain and Italy had the highest total number of deaths, which were about 140 and 165 per million population, respectively. In Japan, where exposure to the causative virus was longer than in most other countries, the total number of deaths per million population was less than 0.5. According to cluster analysis, the total numbers of deaths, patients who recovered, and active cases were higher in Western countries, especially in central and southern European countries, which had the highest numbers when compared with other countries. Conclusion: There may be various reasons for the differences between the clusters obtained by fuzzy c-means clustering. These include quarantine measures, climatic conditions, economic levels, health policies, and the duration of the fight against the outbreak.

Big data analytics and COVID-19: investigating the relationship between government policies and cases in Poland, Turkey and South Korea.

We used big data analytics for exploring the relationship between government response policies, human mobility trends and numbers of coronavirus disease 2019 (COVID-19) cases comparatively in Poland, Turkey and South Korea. We collected daily mobility data of retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential areas. For quantifying the actions taken by governments and making a fairness comparison between these countries, we used stringency index values measured with the 'Oxford COVID-19 government response tracker'. For the Turkey case, we also developed a model by implementing the multilayer perceptron algorithm for predicting numbers of cases based on the mobility data. We finally created scenarios based on the descriptive statistics of the mobility data of these countries and generated predictions on the numbers of cases by using the developed model. Based on the descriptive analysis, we pointed out that while Poland and Turkey had relatively closer values and distributions on the study variables, South Korea had more stable data compared to Poland and Turkey. We mainly showed that while the stringency index of the current day was associated with mobility data of the same day, the current day's mobility was associated with the numbers of cases 1 month later. By obtaining 89.3% prediction accuracy, we also concluded that the use of mobility data and implementation of big data analytics technique may enable decision-making in managing uncertain environments created by outbreak situations. We finally proposed implications for policymakers for deciding on the targeted levels of mobility to maintain numbers of cases in a manageable range based on the results of created scenarios.

A close look at 2019 novel coronavirus (COVID 19) infections in Turkey using time series analysis & efficiency analysis.

2019 novel coronavirus (COVID 19) infections detected as the first official records of the disease in Wuhan, China, affected almost all countries worldwide, including Turkey. Due to the number of infected cases, Turkey is one of the most affected countries in the world. Thus, an examination of the pandemic data of Turkey is a critical issue to understand the shape of the spread of the virus and its effects. In this study, we have a close look at the data of Turkey in terms of the variables commonly used during the pandemic to set an example for possible future pandemics. Both time series modeling and popular efficiency measurement methods are used to evaluate the data and enrich the results. It is believed that the results and discussions are useful and can contribute to the language of numbers for pandemic researchers working on the elimination of possible future pandemics.

Determinants of patient satisfaction and their willingness to return after primary total hip replacement: a cross-sectional study.

BACKGROUND: Surveys of patient satisfaction and their willingness to return can be used for the optimization of processes, improving their quality, and increasing the satisfaction and loyalty in customers. This study looked at the factors significantly associated with patient satisfaction after primary total hip replacement (THR), and which affect the patients' willingness to return to the same hospital for future treatment, even when unrelated to their THR. METHODS: Data for the study was collected by written survey from 810 patients of 43 hospitals following their THR. Satisfaction and willingness to return were measured using a validated, multidimensional questionnaire, primarily based on six-point scales, which were then evaluated together with routine hospital data, according to bivariate and multivariate analyses. RESULTS: The bivariate analysis showed a strong correlation between satisfaction or willingness to return and the health condition before hospitalization as well as the perceived length of stay. In contrast, the patient's gender and the number of inpatient cases in a hospital with THR had no influence. The binary logistic regression analyses identified three predictors associated with overall satisfaction and seven predictors associated with willingness to return. The strongest factor for both dependent variables was the perceived length of stay, and the weakest factor for satisfaction was the treatment outcome. CONCLUSIONS: Overall, with all of the medical and service-related issues considered, high levels of satisfaction were reached. Despite the high satisfaction scores, probable causes for declining the willingness to return were identified. The results provide incentives for hospitals and medical professionals to attain a high satisfaction levels in their THR patients.

Adult onset Still disease: A rare condition. Clinical experience with 17 cases / Una patología poco frecuente: la enfermedad de Still del adulto. Experiencia clínica con 17 casos

OBJECTIVE: To present current clinical experience and the clinical outcomes in the management of patients with adult Still disease. MATERIALS AND METHODS: A retrospective study of a case series was conducted on of 17 cases diagnosed with adult Still disease during a period between 2009 and 2014 in 2 tertiary hospitals in Santiago de Cali. RESULTS: Of the 17 cases diagnosed and treated, it was found that 50% of patients had an elevated ferritin five times its normal value, being useful in the diagnosis. Less than 50% of cases were under 40 years, and about 50% of the population required combined treatment, with two patients requiringbiological therapy to control their symptoms. Yamaguchi criteria were used for diagnostic correlation. CONCLUSIONS: Adult Still's disease is a rare disease that requires a high index of suspicion, but it must be a disease to rule out, and it always requires management generally combined with schemes to improve the quality of life of patients.

OBJETIVO: Dar a conocer la experiencia clínica en el mundo real y los resultados clínicos del manejo de los pacientes con enfermedad de Still del adulto. MATERIALES Y MÉTODOS: Se realiza un estudio retrospectivo de serie de casos, de 17 casos con diagnóstico de enfermedad de Still del adulto, en 2 clínicas de nivel 3 de Santiago de Cali, Colombia, en el periodo comprendido entre 2009 y 2014. RESULTADOS: De los 17 casos diagnosticados y tratados se encontró que en el 50% de los pacientes había una elevación de ferritina de 5 veces su valor normal, siendo útil en el diagnóstico, menos del 50% de los casos fueron en menores de 40 anos, alrededor del 50% de la población requirió tratamiento combinado y 2 pacientes requirieron terapia biológica para el control de sus síntomas. Se usaron los criterios de Yamaguchi para la correlación diagnóstica. CONCLUSIONES: de descarte y, generalmente, siempre requiere manejo con esquemas combinados para mejorar la calidad de vida del paciente.