COVID-19 infection in children with cancer in Armenia: report for the whole pandemic period
Bibliographic record
Abstract
Background and aims. Immunocompromised pediatric patients with cancer are more susceptible to experiencing severe COVID-19 infection compared to other children. In a global registry study of childhood cancer with COVID-19, involving 1500 patients, severe of critical infections were detected in 20 % of the cases. The mortality rate of 4 % excelled that of the general pediatric population. Data about the development of COVID-19 complications in children with cancer remains limited and varies across different countries. This study aims to describe the incidence and characteristics of COVID-19 infection in children with cancer in Armenia. Methods. A prospective analysis was conducted on PCR-confirmed cases of COVID-19 infection in children with cancer aged 0–18 years from 2020 to 2022 at the Pediatric Cancer and Blood Disorders Center of Armenia, Yeolyan Hematology Center, the only pediatric hematology/ oncology institution in our country. Results. Between June 2020 and March 2022, we studied 201 children with cancer in Armenia, of whom 35 cases of COVID-19 infection were confirmed. The median age was 8.4, and the male/female ratio was 1.3. Among the COVID-19-positive patients, 15 had acute lymphoblastic leukemia, 5 had lymphomas, 4 patients had neuroblastoma, and 2 each had medulloblastoma, rhabdomyosarcoma and Ewing sarcoma. There were single cases of osteosarcoma, acute myeloid leukemia and malignant triton tumor. Twenty patients (57 %) were asymptomatic, and the rest presented with fever, sore throat, and cough. Among the patients with hematological malignancies, four developed pneumonia, and two of them experienced cancer progression subsequently. Additionally, four patients had pancytopenia/thrombocytopenia, likely due to the infection with the Omicron in the last three months of the mentioned period. Overall, the incidence of COVID-19 complications was 11 %, and mortality was zero. Conclusion. This is the first nationwide report on COVID-19 in children with cancer in Armenia. The findings indicate lower rates of severe infection and mortality among compared to global estimates. Further studies are emerging to explore these differences.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".