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UnknownPrevalence and influencing factors of self-medication during the COVID-19 pandemic in the Arab region: a multinational cross-sectional study.

Background

The novel coronavirus pandemic (COVID-19) has begun with a wave of misinformation and fear of infection. This may have led people to self-medicate inappropriately. The World Health Organization describes self-medication (SM) as utilizing medicines to relieve symptoms or health con...
S-EPMC9880368 | biostudies-literature
UnknownThe overexpression of DNA repair genes in invasive ductal and lobular breast carcinomas: Insights on individual variations and precision medicine.
In the era of precision medicine, analyzing the transcriptomic profile of patients is essential to tailor the appropriate therapy. In this study, we explored transcriptional differences between two invasive breast cancer subtypes; infiltrating ductal carcinoma (IDC) and lobular carcinoma (LC) using ...
S-EPMC7932549 | biostudies-literature
UnknownImplementation of Recommendations on the Use of Corticosteroids in Severe COVID-19.

Importance

Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines.

Objectives

To compare variations over time and across World Health Organization (WHO) geographic regions of co...
S-EPMC10751594 | biostudies-literature
UnknownCharacteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19.

Background

We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients.

Method...

S-EPMC10114094 | biostudies-literature
UnknownThe value of open-source clinical science in pandemic response: lessons from ISARIC.
Not available
S-EPMC8489876 | biostudies-literature
UnknownISARIC-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 h...
S-EPMC9339000 | biostudies-literature
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