DAVID, Jan, Veronika STARA, Ondrej HRADSKY, Jana TUČKOVÁ, Kateřina SLABÁ, Petr JABANDŽIEV, Lumir SASEK, Michal HUML, Iveta ZIDKOVA, Jan PAVLICEK, Alzbeta PALATOVA, Eva KLASKOVA, Karina BANSZKA, Eva TERIFAJOVA, Radim VYHNANEK, Marketa BLOOMFIELD, Sarka FINGERHUTOVA, Pavla DOLEZALOVA, Lucie PROCHAZKOVA, Gabriela CHRAMOSTOVA, Filip FENCL and Jan LEBL. Nationwide observational study of paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS) in the Czech Republic. European journal of pediatrics. New York: Springer, 2022, vol. 181, No 10, p. 3663-3672. ISSN 0340-6199. Available from: https://dx.doi.org/10.1007/s00431-022-04593-7.
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Basic information
Original name Nationwide observational study of paediatric inflammatory multisystem syndrome temporally associated with SARS-CoV-2 (PIMS-TS) in the Czech Republic
Authors DAVID, Jan (203 Czech Republic, guarantor), Veronika STARA (203 Czech Republic), Ondrej HRADSKY (203 Czech Republic), Jana TUČKOVÁ (203 Czech Republic, belonging to the institution), Kateřina SLABÁ (203 Czech Republic, belonging to the institution), Petr JABANDŽIEV (203 Czech Republic, belonging to the institution), Lumir SASEK (203 Czech Republic), Michal HUML (203 Czech Republic), Iveta ZIDKOVA (203 Czech Republic), Jan PAVLICEK (203 Czech Republic), Alzbeta PALATOVA (203 Czech Republic), Eva KLASKOVA (203 Czech Republic), Karina BANSZKA (203 Czech Republic), Eva TERIFAJOVA (203 Czech Republic), Radim VYHNANEK (203 Czech Republic), Marketa BLOOMFIELD (203 Czech Republic), Sarka FINGERHUTOVA (203 Czech Republic), Pavla DOLEZALOVA (203 Czech Republic), Lucie PROCHAZKOVA (203 Czech Republic), Gabriela CHRAMOSTOVA (203 Czech Republic), Filip FENCL (203 Czech Republic) and Jan LEBL (56 Belgium).
Edition European journal of pediatrics, New York, Springer, 2022, 0340-6199.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 30209 Paediatrics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 3.600
RIV identification code RIV/00216224:14110/22:00128211
Organization unit Faculty of Medicine
Doi http://dx.doi.org/10.1007/s00431-022-04593-7
UT WoS 000842757300001
Keywords in English MIS-C; COVID-19; Incidence; Predictors; Severe outcome; Myocardial dysfunction
Tags 14110317, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Tereza Miškechová, učo 341652. Changed: 2/2/2023 14:41.
Abstract
The worldwide outbreak of the novel 2019 coronavirus disease (COVID-19) has led to recognition of a new immunopathological condition: paediatric inflammatory multisystem syndrome (PIMS-TS). The Czech Republic (CZ) suffered from one of the highest incidences of individuals who tested positive during pandemic waves. The aim of this study was to analyse epidemiological, clinical, and laboratory characteristics of all cases of paediatric inflammatory multisystem syndrome (PIMS-TS) in the Czech Republic (CZ) and their predictors of severe course. We performed a retrospective-prospective nationwide observational study based on patients hospitalised with PIMS-TS in CZ between 1 November 2020 and 31 May 2021. The anonymised data of patients were abstracted from medical record review. Using the inclusion criteria according to World Health Organization definition, 207 patients with PIMS-TS were enrolled in this study. The incidence of PIMS-TS out of all SARS-CoV-2-positive children was 0.9:1,000. The estimated delay between the occurrence of PIMS-TS and the COVID-19 pandemic wave was 3 weeks. The significant initial predictors of myocardial dysfunction included mainly cardiovascular signs (hypotension, oedema, oliguria/anuria, and prolonged capillary refill). During follow-up, most patients (98.8%) had normal cardiac function, with no residual findings. No fatal cases were reported. Conclusions: A 3-week interval in combination with incidence of COVID-19 could help increase pre-test probability of PIMS-TS during pandemic waves in the suspected cases. Although the parameters of the models do not allow one to completely divide patients into high and low risk groups, knowing the most important predictors surely could help clinical management.
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