Evidence map›Paper›PMID 37970115›Full record

ArticleReumatologia2023

Approach to prediction and receiver operating characteristic analysis of a regression model for assessing the severity of the course Lyme borreliosis in children.

Svetlana Oleksiivna Nykytyuk, Andriy Stepanovych Sverstiuk, Serhiy Ivanovich Klymnyuk, Dmytro Stepanovych Pyvovarchuk, Yuri Bogdanovich Palaniza

Open access · diamondAbstract read
In one paragraph

Article in Reumatologia, 2023. 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
0.6field-weighted citation impact, top 35% of its field
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, 2 citations in OpenAlex.

  1. Article
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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

5 authors at 2 institutions in 1 country.

Svetlana Oleksiivna NykytyukDepartment of Children's Diseases and Pediatric Surgery, I Horbachevsky Ternopil National Medical University, Ukraine.ORCID https://orcid.org/0000-0003-3146-9664
Andriy Stepanovych SverstiukDepartment of Children's Diseases and Pediatric Surgery, I Horbachevsky Ternopil National Medical University, Ukraine.ORCID https://orcid.org/0000-0001-8644-0776
Serhiy Ivanovich KlymnyukDepartment of Children's Diseases and Pediatric Surgery, I Horbachevsky Ternopil National Medical University, Ukraine.ORCID https://orcid.org/0000-0002-1308-3250
Dmytro Stepanovych PyvovarchukDepartment of Children's Diseases and Pediatric Surgery, I Horbachevsky Ternopil National Medical University, Ukraine.
Yuri Bogdanovich PalanizaTernopil Ivan Puluj National Technical University, Ukraine.ORCID https://orcid.org/0000-0002-8710-953X
I.Horbachevsky Ternopil National Medical University · UATernopil Ivan Pului National Technical University · UA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Lyme borreliosis (LB) is a multisystemic zoonotic disease transmitted by the bite of infected tick vectors.The aim of the study is to develop a mathematical model for predicting the risk of severity of Lyme disease by the risk factor of the disseminated form of LB in children who have had a tick attack. To test the effectiveness of the formula for predicting the development of the disseminated stage of LB, we built a receiver operating characteristic (ROC) curve and determined the specificity and sensitivity of our model. The results of the examination of 122 patients with the confirmed local and disseminated stages of LB were taken as a basis. Material and methods: To build a prognostic model for prediction of the risk of the developing of the stage in LB predicting the risk of severity of course in Lyme borreliosis (PRSCLB), 122 children (aged 13 ±3 years) with LB were examined using multivariate regression analysis, including 52 boys and 70 girls. Groups of patients: 79 children with erythema migrans, 16 with Lyme arthritis, and 27 with nervous system involvement by LB. The quality of the prognostic model was checked by the Nagelkerke R Square (Nagelkerke R2) and the acceptability of this model was assessed using ROC analysis. Results: The method of multivariate regression analysis for predicting severe course and organ and system damage in LB in children, taking into account the factors and variants of the disease itself, makes it possible to develop a mathematical model for predicting the relative response factors (RRF) of severe forms of Lyme disease and will improve the effectiveness of treatment. This will create all the prerequisites for high-quality preventive measures and reduce the relative response factors rate.The initial data for predicting the severity of LB were 28 factors. According to the results of regression analysis, 24 factors were included in the model for predicting the severity of LB. Conclusions: The results of the study showed that the multifactorial model predicts the severity and organ and system damage in LB in children with an accuracy of 95%. The ROC curve, which was built on the basis of the results, has an area under the curve of 0.94, which indicates the high efficiency of the model.

Indexed as

childrenLyme borreliosisLyme diseasereceiver operating characteristic analysisregression model

Identifiers

PMID37970115
PMCPMC10634403
OpenAlexW4388089492

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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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.