Publications by authors named "J el Baghdadi"

Importance: Sepsis, a leading cause of death in the hospital, is a heterogeneous syndrome without a defined or specific set of symptoms.

Objectives: We conducted a survey of clinicians in practice to understand which clinical findings they tend to associate with sepsis.

Design, Setting, And Participants: A survey was distributed to physicians and advanced practice providers across a multihospital health system during April 2022 and May 2022 querying likelihood of suspecting sepsis and initiating sepsis care in response to various normal and abnormal clinical findings.

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The goal of our study was to explore the association of the polymorphisms in the JAK/STAT pathway among Moroccan COVID-19 patients, using a case-control approach. Next-generation sequencing was employed to investigate the IFNAR1, IFNAR2, JAK1, TYK2, STAT2, and IRF9 genes within the JAK/STAT pathway. We also performed an in silico study to examine the rare variants in this pathway.

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The RAS genes are importantly implicated in oncogenesis and are frequently mutated in childhood acute lymphoblastic leukemia. This study is the first to our knowledge, to determine the mutational status of NRAS and KRAS genes in Moroccan pediatric acute lymphoblastic leukemia (ALL). Polymerase chain reaction and Sanger sequencing were performed for 45 ALL samples to explore the coding exons.

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Background: infection (CDI) may be misdiagnosed if testing is performed in the absence of signs or symptoms of disease. This study sought to support appropriate testing by estimating the impact of signs, symptoms, and healthcare exposures on pre-test likelihood of CDI.

Methods: A panel of fifteen experts in infectious diseases participated in a modified UCLA/RAND Delphi study to estimate likelihood of CDI.

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Background: COVID-19 changed the epidemiology of community-acquired respiratory viruses. We explored patterns of respiratory viral testing to understand which tests are most clinically useful in the postpandemic era.

Methods: We conducted a retrospective observational study of discharge data from PINC-AI (formerly Premier), a large administrative database.

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