Impact of the COVID-19 Pandemic on a Cancer Fast-Track Programme

Introduction: The COVID-19 pandemic has disrupted many aspects of clinical practice in oncology, particularly regarding early cancer diagnosis, sparking public health concerns that possible delays could increase the proportion of patients diagnosed at advanced stages. In 2009, a cancer fast-track program (CFP) was implemented at the Clinico-Malvarrosa Health Department in Valencia, Spain with the aim of shortening waiting times between suspected cancer symptoms, diagnosis and therapy initiation. Objectives: The study aimed to explore the effects of the COVID-19 pandemic on our cancer diagnosis fast-track program. Methods: The program workflow (patients included and time periods) was analysed from the beginning of the state of alarm on March 16th, 2020 until March 15th, 2021. Data was compared with data from the same period of time from the year before (2019). Results: During the pandemic year, 975 suspected cancer cases were submitted to the CFP. The number of submissions only decreased during times of highest COVID-19 incidence and stricter lockdown, and overall, referrals were slightly higher than in the previous 2 years. Cancer diagnosis was confirmed in 197 (24.1%) cases, among which 33% were urological, 23% breast, 16% gastrointestinal and 9% lung cancer. The median time from referral to specialist appointment was 13 days and diagnosis was reached at a median of 18 days. In confirmed cancer cases, treatment was started at around 30 days from time of diagnosis. In total, 61% of cancer disease was detected at early stage, 20% at locally advanced stage, and 19% at advanced stage, displaying time frames and case proportions similar to pre-pandemic years. Conclusions: Our program has been able to maintain normal flow and efficacy despite the challenges of the current pandemic, and has proven a reliable tool to help primary care physicians referring suspected cancer patients.S

Development and validation of a population-based prediction scale for osteoporotic fracture in the region of Valencia, Spain: the ESOSVAL-R study

<p>Abstract</p> <p>Background</p> <p>Today, while there are effective drugs that reduce the risk of osteoporotic fracture, yet there are no broadly accepted criteria that can be used to estimate risks and decide who should receive treatment. One of the actual priorities of clinical research is to develop a set of simple and readily-available clinical data that can be used in routine clinical practice to identify patients at high risk of bone fracture, and to establish thresholds for therapeutic interventions. Such a tool would have high impact on healthcare policies. The main objective of the ESOSVAL-R is to develop a risk prediction scale of osteoporotic fracture in adult population using data from the Region of Valencia, Spain.</p> <p>Methods/Design</p> <p><it>Study design</it>: An observational, longitudinal, prospective cohort study, undertaken in the Region of Valencia, with an initial follow-up period of five years; <it>Subjects</it>: 14,500 men and women over the age of 50, residing in the Region and receiving healthcare from centers where the ABUCASIS electronic clinical records system is implanted; <it>Sources of data</it>: The ABUCASIS electronic clinical record system, complemented with hospital morbidity registers, hospital Accidents & Emergency records and the Regional Ministry of Health's mortality register; <it>Measurement of results</it>: Incident osteoporotic fracture (in the hip and/or major osteoporotic fracture) during the study's follow-up period. Independent variables include clinical data and complementary examinations; <it>Analysis</it>: 1) Descriptive analysis of the cohorts' baseline data; 2) Upon completion of the follow-up period, analysis of the strength of association between the risk factors and the incidence of osteoporotic fracture using Cox's proportional hazards model; 3) Development and validation of a model to predict risk of osteoporotic fracture; the validated model will serve to develop a simplified scale that can be used during routine clinical visits.</p> <p>Discussion</p> <p>The ESOSVAL-R study will establish a prediction scale for osteoporotic fracture in Spanish adult population. This scale not only will constitute a useful prognostic tool, but also it will allow identifying intervention thresholds to support treatment decision-making in the Valencia setting, based mainly on the information registered in the electronic clinical records.</p

Estatinas: eficacia, seguridad e indicaciones

Las estatinas han demostrado que son útiles en la prevención de la enfermedad cardiovascular: infarto de miocardio, ictus, mortalidad cardiovascular y total. Los beneficios del tratamiento se manifiestan sobre todo en pacientes que han padecido una enfermedad cardiovascular o con un riesgo cardiovascular alto. La dosis mínimas eficaces de las estatinas en la prevención de la enfermedad cardiovascular son: atorvastatina 10 mg/día, simvastatina 20-40 mg/día, lovastatina 20-40 mg/día y pravastatina 40 mg/día. Estas dosis consiguen un 20% de reducción del cLDL (colesterol de las lipoproteínas de baja densidad) en los ensayos clínicos. La hepatotoxicidad y miotoxicidad son los efectos secundarios más importantes de las estatinas. La elevación de las transaminasas y la aparición de síntomas musculares son la forma de detectarlos. Las estatinas están indicadas para el tratamiento de la enfermedad cardiovascular o en un paciente con riesgo cardiovascular alto cuando el cLDL sea superior a 115 mg/dl

Searching for the optimal drought index and timescale combination to detect drought: a case study from the lower Jinsha River basin, China

Drought indices based on precipitation are commonly used to identify and characterize droughts. Due to the general complexity of droughts, the comparison of index-identified events with droughts at different levels of the complete system, including soil humidity or river discharges, relies typically on model simulations of the latter, entailing potentially significant uncertainties. The present study explores the potential of using precipitation-based indices to reproduce observed droughts in the lower part of the Jinsha River basin (JRB), proposing an innovative approach for a catchment-wide drought detection and characterization. Two indicators, namely the Overall Drought Extension (ODE) and the Overall Drought Indicator (ODI), have been defined. These indicators aim at identifying and characterizing drought events on the basin scale, using results from four meteorological drought indices (standardized precipitation index, SPI; rainfall anomaly index, RAI; percent of normal precipitation, PN; deciles, DEC) calculated at different locations of the basin and for different timescales. Collected historical information on drought events is used to contrast results obtained with the indicators. This method has been successfully applied to the lower Jinsha River basin in China, a region prone to frequent and severe droughts. Historical drought events that occurred from 1960 to 2014 have been compiled and cataloged from different sources, in a challenging process. The analysis of the indicators shows a good agreement with the recorded historical drought events on the basin scale. It has been found that the timescale that best reproduces observed events across all the indices is the 6-month timescale