Evidence map›Paper›PMID 35431663›Full record

ArticlePathology oncology research : POR2022

Clinical Course of COVID-19 Disease in Children Treated With Neoplastic Diseases in Hungary.

Judit Müller, Dóra Szűcs-Farkas, István Szegedi, Monika Csóka, Miklós Garami, Lilla Györgyi Tiszlavicz, Péter Hauser, Gergely Kriván, Krisztina Csanádi, Gábor Ottóffy and 3 more

Abstract read
In one paragraph

Article in Pathology oncology research : POR, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Judit MüllerSecond Department of Pediatrics, Semmelweis University, Budapest, Hungary.
Dóra Szűcs-FarkasDepartment of Pediatrics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
István SzegediDepartment of Pediatrics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Monika CsókaSecond Department of Pediatrics, Semmelweis University, Budapest, Hungary.
Miklós GaramiSecond Department of Pediatrics, Semmelweis University, Budapest, Hungary.
Lilla Györgyi TiszlaviczDepartment of Pediatrics, University of Szeged, Szeged, Hungary.
Péter HauserHaematology/Oncology and Pediatric Bone Marrow Transplantation Unit, Child Health Centre, Borsod-Abauj-Zemplen County Hospital, Miskolc, Hungary.
Gergely KrivánPediatric Bone Marrow Transplantation Department, South-Pest Centrum Hospital, Budapest, Hungary.
Krisztina CsanádiHemato-Oncology Unit, Heim Pal Children's Hospital, Budapest, Hungary.
Gábor OttóffyDepartment of Pediatrics, University of Pecs, Pecs, Hungary.
Béla NagyDepartment of Laboratory Medicine, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Csongor KissDepartment of Pediatrics, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Gábor KovácsSecond Department of Pediatrics, Semmelweis University, Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We report on children with cancer in Hungary suffering from COVID-19, surveying a 13-months-long period of time. We performed a retrospective clinical trial studying the medical documentation of children treated in seven centers of the Hungarian Pediatric Oncology-Hematology Group. About 10% of children admitted to tertiary hemato-oncological centers for anti-neoplastic treatment or diagnosis for

Indexed as

COVID-19NeoplasmsAdolescentChildHumansHungaryRetrospective StudiesSARS-CoV-2Systemic Inflammatory Response Syndromechemotherapy delayCOVID-19pediatric malignancySARS-CoV-2SARS-CoV-2S antibodies

Identifiers

PMID35431663
PMCPMC9008132

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.