Recruitment characteristics and non-adherence associated factors of fibromyalgia patients in a randomized clinical trial : a retrospective survival analysis

Introduction: Fibromyalgia is a complex pain condition that affects mostly women. Given the disease's lack of understanding, patients report poor adherence to medication and mistrust of medical services. This study aims to describe the recruitment characteristics and non-adherence associated factors of fibromyalgia patients to an RCT. Methods: We performed a retrospective longitudinal analysis with data from our ongoing RCT. We investigated characteristics of subjects recruited, consented, and randomized. Adherence was studied using survival analysis techniques, and its associated factors were identified using Cox proportional hazards regression model. Results: 524 subjects were contacted, 269 were eligible, 61 consented and 40 subjects were randomized. Thirtyeight percent were non-adherent to the protocol with a median of visits of five. The recruitment survey reported that 90% would likely participate in RCTs, 52% had previous participation, and 19% were aware of RCTs by their physicians. Some barriers were investigator-related (staff's friendliness and receiving the results of their trial participation) and center-related (privacy-confidentiality issues and the institution's reputation), without difference between adherent and non-adherent participants. We report significant factors for non-adherence as VAS anxiety score of 5 or more (5.3 HR, p = 0.01), Body Mass Index (BMI) (0.91 HR, p = 0.041) and Quality of Life (QoL) – Personal development subdomain (0.89 HR, p = 0.046). Conclusion: Recruitment and adherence of fibromyalgia patients is a challenge; however, they seem eager to participate in RCTs. We recommend creating a comfortable, friendly and trusting environment to increase the recruitment rate. Higher anxiety, lower BMI and lower quality of life were associated with a higher attrition rate

Evaluación de mutaciones en el gen PIK3CA en tumor y plasma de pacientes peruanas con cáncer de mama mediante PCR digital Lima 2016-2017: análisis de sensibilidad y nivel de concordancia

Objetivo: Determinar la sensibilidad de la PCR digital para detectar mutaciones en el gen PIK3CA en tumor y su nivel de concordancia en el plasma de pacientes peruanas con cáncer de mama. Metodología: Estudio observacional, analítico, transversal, en el que se recolectaron 59 muestras de tumor y 43 de plasma preoperatorio de pacientes con cáncer de mama. Los tumores fueron analizados por secuenciación Sanger y PCR digital para tres mutaciones comunes de PIK3CA (E545K, H1047R y H1047L), mientras que el plasma fue analizado solo por PCR digital para las dos primeras mutaciones. Resultados: La secuenciación de los tumores identificó en total siete pacientes (11.8%) con mutaciones en el gen PIK3CA, de las cuales tres corresponden a la mutación H1047R y cuatro a E545K. La PCR digital identificó las mismas, pero detectó 37 pacientes adicionales con por lo menos una mutación, 33 de E545K, diez de H1047R y dos de H1047L. La comparación entre PCR digital y secuenciación presentó una sensibilidad de 100% con una especificidad de 73.53%. Las 43 muestras de plasma preoperatoria fueron analizadas por PCR digital. Se encontraron dos casos mutados, los cuales fueron confirmados por el análisis de tumor. La concordancia de la PCR digital entre tumor y plasma fue débil (k=0.074). Conclusiones: La PCR digital presenta una alta sensibilidad en detectar mutaciones PIK3CA en tumor respecto a la secuenciación Sanger y una concordancia débil entre tumor y plasma, según el presente estudio

COVID-19 pandemic and Farr's law: A global comparison and prediction of outbreak acceleration and deceleration rates.

The COVID-19 outbreak has forced most of the global population to lock-down and has put in check the health services all over the world. Current predictive models are complex, region-dependent, and might not be generalized to other countries. However, a 150-year old epidemics law promulgated by William Farr might be useful as a simple arithmetical model (percent increase [R1] and acceleration [R2] of new cases and deaths) to provide a first sight of the epidemic behavior and to detect regions with high predicted dynamics. Thus, this study tested Farr's Law assumptions by modeling COVID-19 data of new cases and deaths. COVID-19 data until April 10, 2020, was extracted from available countries, including income, urban index, and population characteristics. Farr's law first (R1) and second ratio (R2) were calculated. We constructed epidemic curves and predictive models for the available countries and performed ecological correlation analysis between R1 and R2 with demographic data. We extracted data from 210 countries, and it was possible to estimate the ratios of 170 of them. Around 42·94% of the countries were in an initial acceleration phase, while 23·5% already crossed the peak. We predicted a reduction close to zero with wide confidence intervals for 56 countries until June 10 (high-income countries from Asia and Oceania, with strict political actions). There was a significant association between high R1 of deaths and high urban index. Farr's law seems to be a useful model to give an overview of COVID-19 pandemic dynamics. The countries with high dynamics are from Africa and Latin America. Thus, this is a call to urgently prioritize actions in those countries to intensify surveillance, to re-allocate resources, and to build healthcare capacities based on multi-nation collaboration to limit onward transmission and to reduce the future impact on these regions in an eventual second wave

Características de los factores de riesgo cardiovascular en una población urbana y rural de la selva peruana, julio - 2014

Objetivo: Determinar las características del lugar de residencia y los factores de riesgo cardiovascular en una población de la selva peruana en julio 2014.Materiales y métodos: Estudio descriptivo transversal realizado en individuos entre 30 y 74 años sin diagnóstico ni tratamiento de enfermedad cardiovascular en una población urbana y una rural del distrito de Yantaló. La muestra se obtuvo a partir del programa Power Analysis and Sample Size Software (PASS) y estuvo conformada por 268 personas (152 habitantes urbanos y 116 rurales). Los factores estudiados fueron hipertensión arterial (HTA), diabetes mellitus (DM), índice de masa corporal (IMC), índice cintura-cadera (ICC) y tabaquismo.Resultados: La población urbana presentó un mayor porcentaje de HTA (18,4%), mientras que los otros factores de riesgo no presentaron diferencias significativas.Conclusiones: El único factor de riesgo que mostró asociación significativa con el lugar de residencia fue la HTA. En contraste, los otros factores de riesgo del estudio no presentaron diferencias entre ambas poblaciones, lo que demostraría que el distrito de Yantaló se encuentra inmerso en un proceso de transición epidemiológica debido a la urbanización