Esquistossomose e o Coração - Em Nome das Doenças Tropicais Negligenciadas e Outras Doenças Infecciosas que Afetam o Coração (Projeto NET-Heart)
Bibliographic record
Abstract
BACKGROUND: Schistosomiasis is a Neglected Tropical Disease which may lead to cardiovascular (CV) complications. However, the CV involvement in schistosomiasis has yet to be fully elucidated due to the limited number of cases and lack of reliable evidence, as schistosomiasis typically occurs in locations without adequate infrastructure for robust data collection. OBJECTIVE: This systematic review aims to assess cardiovascular implications of schistosomiasis, including in the diagnosis and treatment, and propose an algorithm for screening of CV manifestations. METHODS: A systematic review was performed in the MEDLINE/PubMed and LILACS databases of articles on the CV involvement in schistosomiasis. RESULTS: Thirty-three records were considered for this review: six review articles, one systematic review, one clinical trial, 14 observational studies, seven case reports, and four cases series. CV involvement includes a wide spectrum of clinical conditions, such as myocardial ischemia, ventricular dysfunction, myocarditis, pulmonary arterial hypertension, and pericarditis. CONCLUSIONS: Cardiac complications of schistosomiasis may cause long-term disability and death. Clinical monitoring, physical examination, early electrocardiogram, and echocardiogram should be considered as key measures to detect CV involvement. Due to the lack of effective treatment of complications, sanitation and education in endemic areas are necessary for the elimination of this global health problem.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".