A review of the presentation and outcome of left ventricular thrombus in coronavirus disease 2019 infection.
Bibliographic record
Abstract
BACKGROUND: Cardiovascular complications of the coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2), have been documented both in the acute phase and in convalescence. One such complication is the formation of the left ventricular (LV) thrombus. There is a lack of clarity regarding the incidence, risk factors, and management of this complication. AIM: The aim of the study is to identify the clinical presentation, risk factors and outcome of COVID-19 patients with left ventricular thrombus (LVT). METHODS: A literature search was conducted to identify all case reports of COVID-19 with LVT in PubMed/Medline, Embase, Web of Science, and Google Scholar. RESULTS: Among the 65 patients identified, 60 had LVT, either at admission, or during the acute phase of the illness. Six patients with mild symptoms during the acute phase of viral illness had only the COVID-19 antibody test positivity at the time LV thrombus was detected. Few of the patients (23.1%) had no comorbidities. The mean age of the patients was 52.8 years, and the youngest patient was 4 years old. This suggests that LVT formation can occur in young COVID-19 patients with no co-morbid conditions. Most of the patients (69.2%) had more than one site of thrombosis. A mortality rate of 23.1% was observed in our review, and ST-elevation myocardial infarction (STEMI) was diagnosed in 33.3% of those who died. CONCLUSIONS: A high degree of suspicion for LVT must be maintained in patients with known cardiac disease and those with new-onset arterial or venous thromboembolism, and such patients may benefit from a screening echocardiography at admission. RELEVANCE FOR PATIENTS: The patients with preexisting cardiovascular disease must take added precautions to prevent acquiring COVID-19 infection as there is a higher risk of developing LV thrombus. In patients who develop LVT in COVID-19, mortality rate is higher.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".