Circulating <i>Trypanosoma cruzi</i> load and major cardiovascular outcomes in patients with chronic Chagas cardiomyopathy: a prospective cohort study
Bibliographic record
Abstract
OBJECTIVES: To analyse the effect of parasite load assessed by quantitative reverse transcription PCR (RT-qPCR) in serum on the prognosis of patients with chronic Chagas cardiomyopathy (CCM) after a 2-year follow-up. METHODS: Prospective cohort study conducted between 2015 and 2017. One hundred patients with CCM were included. Basal parasitaemia levels of Trypanosoma cruzi (T. cruzi) were measured using a quantitative polymerase chain reaction (qPCR) test. The primary composite outcome (CO) was all-cause mortality, cardiac transplantation and implantation of a left ventricular assist device. Secondary outcomes were the baseline levels of serum biomarkers and echocardiographic variables. RESULTS: After a 2 years of follow-up, the primary CO rate was 16%. A positive qPCR was not associated with a higher risk of the CO. However, when parasitaemia was evaluated by comparing tertiles (tertile 1: undetectable parasitaemia, tertile 2: low parasitaemia and tertile 3: high parasitaemia), a higher risk of the CO (HR 3.66; 95% CI 1.11-12.21) was evidenced in tertile 2. Moreover, patients in tertile 2 had significantly higher levels of high-sensitivity troponin T and cystatin C and more frequently exhibited an ejection fraction <50%. CONCLUSION: Low parasitaemia was associated with severity markers of myocardial injury and a higher risk of the composite outcome when compared with undetectable parasitaemia. This finding could be hypothetically explained by a more vigorous immune response in patients with low parasitaemia that could decrease T. cruzi load more efficiently, but be associated with increased myocardial damage. Additional studies with a larger number of patients and cytokine measurement are required to support this hypothesis.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".