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  <title>DSpace Collection:</title>
  <link rel="alternate" href="https://repositorio.ufu.br/handle/123456789/41072" />
  <subtitle />
  <id>https://repositorio.ufu.br/handle/123456789/41072</id>
  <updated>2026-04-11T10:00:51Z</updated>
  <dc:date>2026-04-11T10:00:51Z</dc:date>
  <entry>
    <title>Avaliação dos protocolos de morte encefálica</title>
    <link rel="alternate" href="https://repositorio.ufu.br/handle/123456789/48496" />
    <author>
      <name />
    </author>
    <id>https://repositorio.ufu.br/handle/123456789/48496</id>
    <updated>2026-03-06T06:22:17Z</updated>
    <published>2025-10-27T00:00:00Z</published>
    <summary type="text">Title: Avaliação dos protocolos de morte encefálica
Abstract: The inherent complexity and urgency of diagnosing Brain Death (BD) constitute a persistent challenge in Intensive Care Units (ICU), representing a critical factor for the success of the National Transplant Policy (PNT). BD, defined as the irreversible cessation of all brain functions, is the legal premise of death authorizing organ removal, in accordance with Law No. 9,434/97 and CFM Resolution No. 2,173/17. The ethical and logistical imperative demands absolute celerity and safety, given that delay compromises organ viability. Furthermore, initiating the BD diagnostic protocol entails a fatal prognosis, culminating either in BD confirmation or Cardiac Arrest (PCR).&#xD;
With the objective of optimizing the diagnosis and the rational use of ancillary tests, such as the Electroencephalogram (EEG), this thesis sought to establish a robust predictive score capable of differentiating progression to BD from Death by Cardiac Arrest (PCR) in neurocritical patients. &#xD;
The study was conducted as a retrospective cohort analysis, approved by the Ethics Committee (CEP) of the Universidade Federal de Uberlândia (UFU), utilizing an Analytical Sample of N=66 patients and applying Binary Logistic Regression to identify independent predictive factors.&#xD;
The statistical model confirmed that the outcome is primarily determined by the initial neurovascular severity. Two clinical factors were identified as the most robust predictors for the outcome of Brain Death: the initial Glasgow Coma Scale (GCS) score and the Use of Vasoactive Drugs (DVA). The initial GCS score proved to be the strongest independent predictor (OR = 1.70; p=0.002), indicating that the BD outcome is intrinsically linked to catastrophic initial neurological injury. Complementarily, the use of DVA was a strong predictor of BD (OR = 0.04; p=0.031), as the need for pressure support (observed in approximately 95% of BD cases) is a robust marker of neurogenic shock and brainstem failure, reducing the chance of death by PCR by 96%.&#xD;
Univariate analyses corroborated that Traumatic Brain Injury (TBI) etiology was significantly more prevalent in the BD Group (approximately 44% vs. 0% in the PCR Group; p=0.022), reinforcing the epidemiological profile of high-impact acute lesions. Furthermore, the extremely low rate of Cardiac Arrest in the BD Group (approximately 1.7%; p&lt;0.001) attested to the high quality of intensive clinical management, maintaining organ viability until the legal declaration of death. Regarding ancillary testing, Quantitative EEG (QEEG) analysis in selected cases demonstrated that progression to BD is marked by a profound electrophysiological disorganization, featuring an inversion in power patterns and extreme, dysregulated variability of electrical activity. This reinforces the potential of EEG, due to its non-invasive and cost-effective nature, as an ideal tool within the reality of the public health system (SUS).&#xD;
The main practical contribution of this thesis resides in the proposition of the Predictive Triage Model (GCS + DVA). This model allows for the quicker and more focused activation of the BD protocol and complementary examinations, particularly concentrating on EEG use. This optimization directly contributes to maintaining organ viability. &#xD;
In summary, the work demonstrates that the integration of methodological rigor from data science with clinical physiology establishes powerful tools to refine the diagnosis of Brain Death, ensuring the excellence and efficiency demanded by the ethical and legal imperative</summary>
    <dc:date>2025-10-27T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Cálculo de blindagem em medicina nuclear no Brasil: diretrizes, metodologia e avaliação do impacto do uso de fatores não usuais na espessura final</title>
    <link rel="alternate" href="https://repositorio.ufu.br/handle/123456789/48396" />
    <author>
      <name />
    </author>
    <id>https://repositorio.ufu.br/handle/123456789/48396</id>
    <updated>2026-02-26T06:26:11Z</updated>
    <published>2026-02-10T00:00:00Z</published>
    <summary type="text">Title: Cálculo de blindagem em medicina nuclear no Brasil: diretrizes, metodologia e avaliação do impacto do uso de fatores não usuais na espessura final
Abstract: Radiation shielding calculation reports are a legal requirement and a fundamental prerequisite for obtaining authorization for the construction and operation of nuclear medicine services in Brazil. Despite their regulatory and technical relevance, the national and international literature presents fragmented approaches, with gaps in the methodological organization of shielding calculations. This thesis is characterized as applied regulatory research, aiming to consolidate and structure an integrated methodology for radiation shielding calculations in nuclear medicine services, adapted to the Brazilian regulatory and operational context. The work is based on a critical compilation of the specialized literature, the analysis of consolidated references, and the practical application of the proposed methodology to representative scenarios, encompassing diagnostic and therapeutic environments, multiple dose contributions, and hybrid systems. Non-standard factors, often treated in a simplified manner in conventional methods, are discussed and evaluated, including the definition of the critical group, the customization of occupancy factors, the integrated consideration of multiple dose contributions, and the integration between different diagnostic modalities. It is demonstrated that decisions usually regarded as secondary may lead to significant variations in the final shielding thickness, affecting both radiological optimization and the technical and economic feasibility of projects, while maintaining compliance with dose limits established by regulations. The main contribution of this work lies in the compilation, organization, and critical systematization of concepts, parameters, and formulations already consolidated in the literature, reinterpreted in light of current national legislation and accumulated practical experience. By explicitly addressing underexplored factors and discussing their implications for shielding calculations, this thesis broadens the scope of traditional approaches and provides support for more realistic, context-aware designs aligned with the actual operating conditions of nuclear medicine services, while also serving as a technical reference for professionals in the field and for regulatory assessment.</summary>
    <dc:date>2026-02-10T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Plataforma computacional para análise de sinais EEG baseada em python aplicada a indivíduos em coma e estimulação musical de indivíduos normais</title>
    <link rel="alternate" href="https://repositorio.ufu.br/handle/123456789/48244" />
    <author>
      <name />
    </author>
    <id>https://repositorio.ufu.br/handle/123456789/48244</id>
    <updated>2026-02-23T13:23:44Z</updated>
    <published>2025-12-11T00:00:00Z</published>
    <summary type="text">Title: Plataforma computacional para análise de sinais EEG baseada em python aplicada a indivíduos em coma e estimulação musical de indivíduos normais
Abstract: The electroencephalogram (EEG) allows the non-invasive recording of brain electrical dynamics from the scalp, being crucial for investigating cerebral processes. However, the complexity of the signals and the need to broaden access to analyses motivated the migration of a processing software originally developed on a computational platform to Python, an openSource programming language.&#xD;
During the transcription, functional improvements were incorporated, including customized preprocessing routines, criteria for discarding noisy channels, selection of quantifiers, adjustable parameters, and the development of a graphical interface that facilitated adoption and training for researchers with different levels of experience. &#xD;
Although the computational platform version presented superior performance in the preprocessing and processing stages, being about 60 times faster, and generated processed data files five times smaller, the Python version guaranteed functional equivalence in the calculated quantifiers, with negligible relative error (on the order of 10^(-12)), except for the coherence quantifier, which has a slightly different algorithm. Statistical routines were developed to evaluate the effects of musical stimulation, in which the percentage of power contribution (PCP) quantifier, especially in the delta and alpha bands, proved to be more informative than the median frequency.&#xD;
Artificial intelligence techniques were applied to classify signals in clinical and musical tasks. In the coma prognosis database, a macro F1 Score of 90% was obtained; for coma etiology classification, 63% accuracy was achieved, increasing to 70% after removing exams in the "others" category; and in musical stimulus classification, 67% accuracy was reached.&#xD;
This work contributes to the dissemination of open and reproducible tools in neurophysiological signal analysis and paves the way for future improvements and research in the field.</summary>
    <dc:date>2025-12-11T00:00:00Z</dc:date>
  </entry>
  <entry>
    <title>Estudo dosimétrico em profissionais de diferentes IMC durante o exame de tomografia computadorizada utilizando simulação de Monte Carlo</title>
    <link rel="alternate" href="https://repositorio.ufu.br/handle/123456789/48158" />
    <author>
      <name />
    </author>
    <id>https://repositorio.ufu.br/handle/123456789/48158</id>
    <updated>2026-02-05T06:25:19Z</updated>
    <published>2025-11-18T00:00:00Z</published>
    <summary type="text">Title: Estudo dosimétrico em profissionais de diferentes IMC durante o exame de tomografia computadorizada utilizando simulação de Monte Carlo
Abstract: Generally, when performing a CT scan, only the patient is exposed to ionizing radiation.&#xD;
However, there are special cases where healthcare professionals (doctors/nurses/radiologists)&#xD;
need to stay in the CT room during the exam. The reasons are monitoring and restraining&#xD;
pediatric patients, special care in multiple trauma patients, performing manual ventilation,&#xD;
among others. The presence of the staff at the exam room, during the exam, leads to the&#xD;
exposure to ionizing radiation. Occupational exposure to radiation can cause biological&#xD;
effects such as dermatitis, skin cancer, leukemia, cataracts, and brain tumors in the&#xD;
professional. In the literature there are few studies about occupational exposure for CT&#xD;
professionals, and there are no studies that use computational tools to evaluate occupational&#xD;
exposure of professionals who accompany the patient during conventional CT examination.&#xD;
Therefore, this work aims to determine and evaluate the doses received by professionals&#xD;
when they are exposed to ionizing radiation during the follow-up of the patients during CT&#xD;
examinations. The dose values will be obtained through Monte Carlo simulation of adult&#xD;
virtual anthropomorphic phantoms representing patients and professionals during different&#xD;
CT scans. With the results of this work, it is intended to determine which positions are the&#xD;
safest, to assist in the awareness and training of professionals regarding radiological&#xD;
protection during CT examinations.</summary>
    <dc:date>2025-11-18T00:00:00Z</dc:date>
  </entry>
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