Evidence map›Paper›PMID 40190303›Full record

ArticleArchives of medical science : AMS2025

LC risk score - development and evaluation of a scale for assessing the risk of developing long COVID.

Mateusz Babicki, Mateusz Lejawa, Tadeusz Osadnik, Joanna Kapusta, Maciej Banach, Piotr Jankowski, Agnieszka Mastalerz-Migas, Żaneta Kałuzińska-Kołat, Damian Kołat, Michal Chudzik

Abstract read
In one paragraph

Article in Archives of medical science : AMS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Long COVID-19: A Concept Analysis.Infectious disease reports · 2025
    Article
  3. 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

10 authors.

Mateusz BabickiDepartment of Family Medicine, Wroclaw Medical University, Wroclaw, Poland.
Mateusz LejawaDepartment of Pharmacology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, Poland.
Tadeusz OsadnikDepartment of Pharmacology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia in Katowice, Poland.
Joanna KapustaDepartment of Internal Diseases, Rehabilitation, and Physical Medicine, Medical University of Lodz, Lodz, Poland.
Maciej BanachDepartment of Preventive Cardiology and Lipidology, Medical University of Lodz, Lodz, Poland.
Piotr JankowskiDepartment of Internal Medicine and Geriatric Cardiology, Medical Centre for Postgraduate Education, Warsaw, Poland.
Agnieszka Mastalerz-MigasDepartment of Family Medicine, Wroclaw Medical University, Wroclaw, Poland.
Żaneta Kałuzińska-KołatDepartment of Biomedicine and Experimental Surgery, Medical University of Lodz, Lodz, Poland.
Damian KołatDepartment of Biomedicine and Experimental Surgery, Medical University of Lodz, Lodz, Poland.
Michal ChudzikDepartment of Internal Medicine and Geriatric Cardiology, Medical Centre for Postgraduate Education, Warsaw, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The aim of the study was to create a valuable practical tool for evaluating the risk of developing long COVID. Material and methods: 1150 patients from the Polish STOP-COVID registry (PoLoCOV study) were used to develop the risk score. The patients were ill between 03/2020 and 04/2022. To develop a clinically useful scoring model, the LC risk score was generated using the machine learning-based framework AutoScore. Patient data were first randomised into a training (70% of output) and a test (30% of output) cohort. Due to the relatively small study group, cross-validation was used. Model predictive ability was evaluated based on the ROC curve and the AUC value. The result of the risk score for a given patient was the total value of points assigned to selected variables. Results: To create the LC risk score, eight variables were ultimately selected due to their significance and clinical value. Female gender significantly contributed to higher final outcome values, with age range 40-49, body mass index < 18.5 kg/m Conclusions: The LC risk score may be a practical and undemanding utility that employs basic sociodemographic data, vaccination status, and symptoms during COVID-19 to assess the risk of long COVID.

Indexed as

AutoScorelong COVIDpost-COVIDrisk scorerisk stratification

Identifiers

PMID40190303
PMCPMC11969552

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.