Multivariate linear mixture models for the prediction of
febrile seizure risk and recurrence: a prospective case-control
study

J 2023

Multivariate linear mixture models for the prediction of febrile seizure risk and recurrence: a prospective case-control study

PAPEŽ, Jan, Rene LABOUNEK, Petr JABANDŽIEV, Katarína ČESKÁ, Kateřina SLABÁ et. al.

Basic information

Original name

Multivariate linear mixture models for the prediction of febrile seizure risk and recurrence: a prospective case-control study

Authors

PAPEŽ, Jan (203 Czech Republic, belonging to the institution), Rene LABOUNEK, Petr JABANDŽIEV (203 Czech Republic, belonging to the institution), Katarína ČESKÁ (703 Slovakia, belonging to the institution), Kateřina SLABÁ (203 Czech Republic, belonging to the institution), Hana OŠLEJŠKOVÁ (203 Czech Republic, belonging to the institution), Štefánia AULICKÁ (703 Slovakia, belonging to the institution) and Igor NESTRASIL (guarantor)

Edition

Nature Scientific Reports, BERLIN, NATURE PORTFOLIO, 2023, 2045-2322

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

30210 Clinical neurology

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 4.600 in 2022

RIV identification code

RIV/00216224:14110/23:00134687

Organization unit

Faculty of Medicine

DOI

http://dx.doi.org/10.1038/s41598-023-43599-5

UT WoS

001086926800024

Keywords in English

Multivariate linear mixture models; febrile seizure

Abstract

V originále

Our goal was to identify highly accurate empirical models for the prediction of the risk of febrile seizure (FS) and FS recurrence. In a prospective, three-arm, case-control study, we enrolled 162 children (age 25.8 +/- 17.1 months old, 71 females). Participants formed one case group (patients with FS) and two control groups (febrile patients without seizures and healthy controls). The impact of blood iron status, peak body temperature, and participants' demographics on FS risk and recurrence was investigated with univariate and multivariate statistics. Serum iron concentration, iron saturation, and unsaturated iron-binding capacity differed between the three investigated groups (pFWE < 0.05). These serum analytes were key variables in the design of novel multivariate linear mixture models. The models classified FS risk with higher accuracy than univariate approaches. The designed bi-linear classifier achieved a sensitivity/specificity of 82%/89% and was closest to the gold-standard classifier. A multivariate model assessing FS recurrence provided a difference (p(FWE) < 0.05) with a separating sensitivity/specificity of 72%/69%. Iron deficiency, height percentile, and age were significant FS risk factors. In addition, height percentile and hemoglobin concentration were linked to FS recurrence. Novel multivariate models utilizing blood iron status and demographic variables predicted FS risk and recurrence among infants and young children with fever.

Links

NU21-04-00305, research and development project

Name: Analýza transkriptomu a metylace DNA u pacientů s fokální kortikální dysplázií

Investor: Ministry of Health of the CR, Transcriptomics and DNA methylation analysis in patients with focal cortical dysplasia, Subprogram 1 - standard

Citovat

PAPEŽ, Jan, Rene LABOUNEK, Petr JABANDŽIEV, Katarína ČESKÁ, Kateřina SLABÁ, Hana OŠLEJŠKOVÁ, Štefánia AULICKÁ and Igor NESTRASIL. Multivariate linear mixture models for the prediction of febrile seizure risk and recurrence: a prospective case-control study. Nature Scientific Reports. BERLIN: NATURE PORTFOLIO, 2023, vol. 13, No 1, p. 1-12. ISSN 2045-2322. Available from: https://dx.doi.org/10.1038/s41598-023-43599-5.

@article{2355297,
   author = {Papež, Jan and Labounek, Rene and Jabandžiev, Petr and Česká, Katarína and Slabá, Kateřina and Ošlejšková, Hana and Aulická, Štefánia and Nestrasil, Igor},
   article_location = {BERLIN},
   article_number = {1},
   doi = {http://dx.doi.org/10.1038/s41598-023-43599-5},
   keywords = {Multivariate linear mixture models; febrile seizure},
   language = {eng},
   issn = {2045-2322},
   journal = {Nature Scientific Reports},
   title = {Multivariate linear mixture models for the prediction of febrile seizure risk and recurrence: a prospective case-control study},
   url = {https://www.nature.com/articles/s41598-023-43599-5},
   volume = {13},
   year = {2023}
}

TY  - JOUR
ID  - 2355297
AU  - Papež, Jan - Labounek, Rene - Jabandžiev, Petr - Česká, Katarína - Slabá, Kateřina - Ošlejšková, Hana - Aulická, Štefánia - Nestrasil, Igor
PY  - 2023
TI  - Multivariate linear mixture models for the prediction of febrile seizure risk and recurrence: a prospective case-control study
JF  - Nature Scientific Reports
VL  - 13
IS  - 1
SP  - 1-12
EP  - 1-12
PB  - NATURE PORTFOLIO
SN  - 20452322
KW  - Multivariate linear mixture models
KW  - febrile seizure
UR  - https://www.nature.com/articles/s41598-023-43599-5
N2  - Our goal was to identify highly accurate empirical models for the prediction of the risk of febrile seizure (FS) and FS recurrence. In a prospective, three-arm, case-control study, we enrolled 162 children (age 25.8 +/- 17.1 months old, 71 females). Participants formed one case group (patients with FS) and two control groups (febrile patients without seizures and healthy controls). The impact of blood iron status, peak body temperature, and participants' demographics on FS risk and recurrence was investigated with univariate and multivariate statistics. Serum iron concentration, iron saturation, and unsaturated iron-binding capacity differed between the three investigated groups (pFWE < 0.05). These serum analytes were key variables in the design of novel multivariate linear mixture models. The models classified FS risk with higher accuracy than univariate approaches. The designed bi-linear classifier achieved a sensitivity/specificity of 82%/89% and was closest to the gold-standard classifier. A multivariate model assessing FS recurrence provided a difference (p(FWE) < 0.05) with a separating sensitivity/specificity of 72%/69%. Iron deficiency, height percentile, and age were significant FS risk factors. In addition, height percentile and hemoglobin concentration were linked to FS recurrence. Novel multivariate models utilizing blood iron status and demographic variables predicted FS risk and recurrence among infants and young children with fever.
ER  -

PAPEŽ, Jan, Rene LABOUNEK, Petr JABANDŽIEV, Katarína ČESKÁ, Kateřina SLABÁ, Hana OŠLEJŠKOVÁ, Štefánia AULICKÁ and Igor NESTRASIL. Multivariate linear mixture models for the prediction of febrile seizure risk and recurrence: a prospective case-control study. \textit{Nature Scientific Reports}. BERLIN: NATURE PORTFOLIO, 2023, vol.~13, No~1, p.~1-12. ISSN~2045-2322. Available from: https://dx.doi.org/10.1038/s41598-023-43599-5.

Detailed Information on Publication Record