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Record W7120553350

Dispneia em foco: insights na avaliação

2023· dissertation· en· W7120553350 on OpenAlexfundno aff
Letícia Fernandes Belo

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2023
Typedissertation
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchFonds de Recherche du Québec - SantéPfizer CanadaAstraZeneca CanadaReseau canadien de recherche respiratoireUniversidade Norte do ParanáMcGill University Health CentreMcGill UniversityGlaxoSmithKlineUniversidade Estadual de LondrinaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorAstraZenecaPfizer
KeywordsCOPDQuality of life (healthcare)LimitingDiseaseExertionSensationActivities of daily livingPulmonary disease
DOInot available

Abstract

fetched live from OpenAlex

Dyspnea is a limiting symptom in several populations, and one of the main symptoms reported by individuals with chronic obstructive pulmonary disease (COPD). The progression of dyspnea correlates with disease progression. In early stages of COPD, the complaint of dyspnea is more common during exertion, while in severe stages the subjects report a limitant sensation sometimes even at rest. In addition, dyspnea leads to impaired quality of life and hindered performance in activities of daily living. Concomitantly, a reduction in the level of physical activity in daily life increases the risk of death. In recent years there has been growing interest in the study of all facets of this symptom. However, there are still several gaps in the literature to be addressed, especially with regard to the physiological mechanisms that trigger dyspnea during exertion and its evaluation methods. Objectives: This thesis has the aim of contributing to the scientific evidence related to the dyspnea assessment specifically by: 1) comparing the clinical and physiological variables of individuals with and without COPD who stop exercising due to dyspnea versus others symptoms; and 2) making available a multidimensional tool for dyspnea assessment for Portuguese-speaking individuals with COPD. Methodology: Two original studies were developed: (1) The first study discriminated the proportion of individuals with and without COPD according to their reason to stop the exercise. Furthermore, the physiological responses at the peak of the exercise were verified and compared between groups, as well as their pulmonary function and clinical data; (2) In the second study, the translation, validation and reproducibility of the Portuguese version of the Multidimensional Dyspnea Profile (MDP) were proposed. Results: Study (1) demonstrated that, independently of COPD diagnosis, individuals who stop exercising due to dyspnea present changes such as hyperinflation and restriction of lung volumes, even with preserved exercise capacity, compared to individuals who stop for another reason. Study (2) showed that the Portuguese version of the MDP is a valid and reproducible tool for assessing this symptom in individuals with COPD. Conclusions: The two scientific articles contained in this thesis add novel information to the available literature on dyspnea in individuals with COPD. Rregardless of lung function, age and BMI, individuals who stop exercise due to dyspnea have greater lung restrictions than individuals who stop exercise for other reasons. Moreover, dyspnea can now be confidently assessed multidimensionally in Brazilian individuals with COPD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.101
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.101
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.004
Science and technology studies0.0020.003
Scholarly communication0.0100.008
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0140.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.288
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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