Background: Leptospirosis is a worldwide zoonotic infection, and its management needs to be refined. This study aims to discern which antibiotic would be the best option to treat leptospirosis disease and analyze the efficacy of chemoprophylaxis regimens to prevent this illness. Methods: systematic review and meta-analysis on the efficacy of antibiotic treatment and chemoprophylaxis of leptospirosis in humans. Results: Ten clinical trials compared an antibiotic treatment with placebo or other antibiotic treatments in leptospirosis (the most recent one was published in 2007). The meta-analysis shows no effect of penicillin treatment on mortality compared to placebo (OR 1.65; 95% CI 0.76–3.57; p = 0.21). There are no differences between penicillin and cephalosporins or doxycycline. Penicillin does not reduce the time of defervescence (MD-0.16; 95% CI (−1.4) –1.08; p = 0.80) nor hospital stay (MD 0.15; 95% CI (−0.75)–1.06; p = 0.74). Besides, the data did not demonstrate any effectiveness of the use of penicillin in terms of the incidence of oliguria/anuria, the need for dialysis treatment, time to creatinine normalization, incidence of jaundice, or the liver function normalization time. Eight trials have assessed prophylactic treatment against leptospirosis with different strategies. A weekly dose of 200 mg of doxycycline does not show benefit versus placebo regarding the number of new cases of symptomatic leptospirosis (OR 0.20; 95% CI 0.02–1.87; p = 0.16). A single dose of doxycycline at exposure to flood water could have a beneficial effect (OR 0.23; 95% CI 0.07–0.77; p = 0.02). None of the other chemoprophylaxis regimens tested have shown a statistically significant effect on the number of new symptomatic cases. Conclusion: There is no evidence that antibiotics are a better treatment than placebo regarding mortality, shortening of fever, liver and kidney function, or reduction in the hospital stay. On the other hand, neither doxycycline nor penicillin, nor azithromycin have shown statistically significant differences in preventing symptomatic infection. Well-designed clinical trials, including other antibiotics such as quinolones or aminoglycosides, are urgently needed to improve our understanding of the treatment for this infection, which continues to be a neglected disease.

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Background: COVID-19 has a wide range of symptoms reported, which may vary from very mild cases (even asymptomatic) to deadly infections. Identifying high mortality risk individuals infected with the SARS-CoV-2 virus through a prediction instrument that uses simple clinical and analytical parameters at admission can help clinicians to focus on treatment efforts in this group of patients. Methods: Data was obtained retrospectively from the electronic medical record of all COVID-19 patients hospitalized in the Albacete University Hospital Complex until July 2020. Patients were split into two: a generating and a validating cohort. Clinical, demographical, and laboratory variables were included. A multivariate logistic regression model was used to select variables associated with in-hospital mortality in the generating cohort. A numerical and subsequently a categorical score according to mortality was constructed (A.-mortality from 0 to 5%; B.-from 5 to 15%; C.-from 15 to 30%; D.-from 30 to 50%; E.-greater than 50%). These scores were validated with the validation cohort. Results: Variables independently related to mortality during hospitalization were age, diabetes mellitus, confusion, SaFiO2, heart rate, and LDH at admission. The numerical score defined ranges from 0 to 13 points. Scores included are: age ≥ 71 years (3 points), diabetes mellitus (1 point), confusion (2 points), onco-hematologic disease (1 point), SaFiO2 ≤ 419 (3 points), heart rate ≥ 100 bpm (1point), and LDH ≥ 390 IU/L (2 points). The area under the curve (AUC) for the numerical and categorical scores from the generating cohort were 0.8625 and 0.848, respectively. In the validating cohort, AUCs were 0.8505 for the numerical score and 0.8313 for the categorical score. A c c e p t e d M a n u s c r i p t Conclusions:. Data analysis found a correlation between clinical admission parameters and inhospital mortality for COVID-19 patients. This correlation is used to develop a model to assist physicians in the emergency department in the COVID-19 treatment decision-making process.

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El estudio realiza un análisis bibliométrico del European Journal of Psychology Applied to Legal Context entre 2009-2018, situado en el percentil 96 en su categoría. Se construyó una base de datos que permite analizar autores, instituciones, países, género, temáticas e impacto en las bases de datos de la Web of Science. Los resultados permiten observar el incremento de la colaboración internacional, y la existencia de un grupo reducido de autores muy productivos, en grupos de colaboración próximos al equipo editorial y a la Sociedad Española de Psicología Jurídica y Forense, de la que la revista es órgano de expresión. Encuentra un eje vertebrador institucional que incluye un pequeño grupo de universidades españolas, y que vincula universidades y centros extranjeros, sobre todo mejicanos y de la Europa del Norte. Hay una elevada presencia de mujeres, productivas, con buen posicionamiento en el orden de firma e impacto diferencial en la comunidad científica, aunque no en el Consejo Editorial. Son temas destacados la evaluación, la credibilidad y el testimonio. El 95% de sus artículos han sido citados, y sólo siete explican una cuarta parte del total de citas recibidas. La revista está bien posicionada en el ámbito de las aplicaciones de la Psicología al contexto legal.