Informing the medical education reform in Tajikistan : evidence on the learning environment at two nursing colleges

The Tajik medical education system is undergoing a complex reform to enhance the transition of the healthcare system from its soviet legacy of emphasizing secondary level care/specialisation to become more family medicine and primary health care oriented. The current study presents the first empirical evaluation of the educational environment for nursing students in Tajikistan using the Dundee Ready Educational Environment Measure (DREEM). The study results contribute to the benchmarking efforts of monitoring and positively steering the educational environment over time.; The study was based on a cross-sectional survey involving 630 nursing students at two nursing colleges in Tajikistan. Students' perception of the learning environment was measured using the DREEM. Internal consistency was examined using Cronbach's alpha. General scores were calculated and measured against international benchmarks. Data was further interpreted by comparing DREEM scores between students of different sex, at different colleges and different study years using T tests.; Cronbach's alpha ranged from 0.30 to 0.75 with an overall alpha of 0.89. General DREEM scores were slightly above average compared to similar studies with nursing students in other countries. In particular, results showed that students' academic self-perception and teachers' technical competences were generally favourably rated. Teachers' pedagogical skills were critically perceived by the study participants and teaching was generally viewed as too teacher-centred with an over-emphasis on factual learning.; Statistical results indicated acceptable levels of reliability of the DREEM tool when applied to the Tajik nursing educational context. Students rated the learning environment as generally satisfactory with average scores similar or slightly higher than comparable scores from similar studies involving nursing students. However, the on-going educational reform could have placed more emphasis on developing faculty pedagogical skills in nursing schools. Teaching approaches would benefit from being more competency based rather than so heavily focused on factual knowledge

A highly virulent variant of HIV-1 circulating in the Netherlands

We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log10 increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence

The value of open-source clinical science in pandemic response: lessons from ISARIC

International audienc

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use