Publications by authors named "Baiceanu D"

Introduction: Despite advances in diagnostic technologies for tuberculosis (TB), global control of this disease requires improved technologies for active case finding in selected vulnerable populations. The integration of artificial intelligence (AI) into imaging modalities has been anticipated to assume a pivotal position in conjunction with traditional bacteriological diagnostic approaches, especially in the active diagnosis of vulnerable groups.

Methods: The study was conducted as a prospective investigation spanning from November 2019 to October 2023, in Romania's national TB screening project.

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Background: Tuberculosis (TB) remains a global health challenge, with 1.3 million deaths in 2022. Ten countries in the European Union (EU) and European Economic Area (EEA) accounted for 88.

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Background: Neuropathic adverse events occur frequently in linezolid-containing regimens, some of which remain irreversible after drug discontinuation.

Objective: We aimed to identify and validate a host RNA-based biomarker that can predict linezolid-associated neuropathy before multidrug-resistant/rifampicin-resistant tuberculosis (MDR/RR-TB) treatment initiation and to identify genes and pathways that are associated with linezolid-associated neuropathy.

Methods: Adult patients initiating MDR/RR-TB treatment including linezolid were prospectively enrolled in 3 independent cohorts in Germany.

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Background: Tuberculosis (TB), and especially its drug resistant forms, is responsible for not only significant mortality, but also considerable morbidity, still under-quantified. This study used four Patient-Reported Outcome Measures (PROMS) to assess the status of persons affected by drug-susceptible and drug-resistant TB during their TB treatment or after treatment completion, in Romania, the highest TB burden country in the EU.

Methods: People affected by TB in two different regions in Romania were included during and after treatment, following a cross-sectional design.

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Introduction: Tuberculosis (TB) remains a global health challenge, requiring enhanced active case finding (ACF) through screening strategies. This study assesses the effectiveness of such an approach in locating TB cases among vulnerable groups, such as homeless persons, injecting drug users, those detained in prison, and people living in rural areas.

Methods: The study focuses on socio-economic characteristics and TB detection rates across Romanian counties using modern techniques including computer-aided detection of lesions on chest X-ray and GeneXpert tests.

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The study proposes a dynamic spatio-temporal profile of the distribution of tuberculosis incidence and air pollution in Romania, where this infectious disease induces more than 8,000 new cases annually. The descriptive analysis for the years 2012-2021 assumes an identification of the structuring patterns of mycobacterium tuberculosis risk in the Romanian population, according to gender and age, exploiting spatial modeling techniques of time series data. Through spatial autocorrelation, the degree of similarity between the analyzed territorial systems was highlighted and the relationships that are built between the analysis units in spatial proximity were investigated.

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Therapeutic drug monitoring (TDM) could improve TB treatment outcomes by avoiding drug toxicity or underdosing. In this study, we describe the patient burden in three TB centres in Romania and Ukraine with a TDM indication, as per the current guidelines, in order to estimate the feasibility of implementing TDM. A retrospective multi-centre study was conducted at the Iasi Lung Hospital (Iasi, Romania), Bucharest Marius Nasta Institute (Bucharest, Romania) and Chernivtsi TB Centre (Chernivtsi, Ukraine) in adult hospitalised TB patients.

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Article Synopsis
  • International cancer registries, like AACR Project GENIE, provide access to genomic and clinical data from over 130,000 cancer patients, but analyzing this combined data can be tricky.
  • The cBioPortal for Cancer Genomics has improved its features to help visualize and analyze longitudinal clinical and genomic data, allowing users to see how treatment impacts patient outcomes over time.
  • These enhancements enable researchers and clinicians to explore complex datasets, fostering discoveries on how specific genomic changes affect cancer prognosis and treatment effectiveness.
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