Avaliação da acurácia da ressonância magnética cardiovascular como método diagnóstico precoce na rejeição do enxerto nos receptores de transplante cardíaco
Bibliographic record
Abstract
Introduction: Cardiac function is a progressive disease affecting millions of people. with 10% health of patients with an advanced quality health diagnosis Heart transplantation is indicated for patients with cardiac function in functional classes NY or IV of the NY Heart Association classification (New York Heart Association). one one year. After performing a heart transplant, one of the biggest challenges in patient management is the early detection of changes in the transplant. Cardiac rejection can cause severe and irreversible myocardial damage before clinical manifestations. To date, there is no monitoring of unauthorized exams for rejection of rejection. The literature considers an endomyocardial biopsy (EMB) the gold standard for the detection of rejection. Magnetic resonance imaging (MRI) is an invasive imaging modality not able to detect areas of fibrosis, edema and correction of alterations in the power to alter the screening power for heart transplantation. Thus, it starts from the idea that CMR, as it is able to assess all myocardial functionality, may offer an advantage when the gold standard assessment is lower. Objective: To evaluate the accuracy of CMR as a non-invasive diagnostic method for the early detection of acute transplant disease in heart transplant patients. Methods: Heart transplant patients who met the inclusion criteria were defined by CMR, analysis of the presence of myocardial fibrosis and quantification of myocardial edema, using the CVI-42 software (Circle Cardiovascular Imaging, Calgary, Canada). For image acquisition after GFR assessment, patients received 0.2 mmol/kg of non-ionic gadolinium-based contrast agent (gadodiamide 0.5mmol/ml) by intravenous puncture. Results: 26 heart transplant recipients were included in a Brazilian heart transplant referral hospital, from June 2019 to February 2022. Patients underwent BEM as a screening for graft rejection; the interval for performing the procedure was defined through the institution's protocol according to the Working Group of the International Society for Heart and Lung Transplantation system and according to clinical criteria assessed by the cardiologist. Patients were divided into two groups: without evidence of rejection (0R/n=13), and with rejection (>=2R n=13). Subsequently, the patients underwent CMR examination within a period of up to 120 hours, without any change in immunosuppressive therapy. Patients under 18 years of age, who had uncontrolled arrhythmias, glomerular filtration rate <30ml/min, or who had absolute contraindications for CMR were excluded. Patients with 1R rejection were also excluded from the study. Analyzes were blindly evaluated by two radiologists. The delayed enhancement (LGE) methodology was detected in (84.6%) of the patients with BEM>=2R and in (38.5%) of the patients without rejection (p=0.016). It can be stated that the fibrosis regression models defined by the quantitative analysis of the LGE was significant (p=0.022). Conclusion: It is concluded that the subjective and quantitative analyzes of the LGE can be promising in the screening of patients with suspected rejection, as stratification tools and possible reduction in the need for EMB.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".