Evidence map›Paper›PMID 38871785›Full record

ArticleScientific reports2024

Development and validation of an interpretable model for predicting sepsis mortality across care settings.

Young Seok Lee, Seungbong Han, Ye Eun Lee, Jaehwa Cho, Young Kyun Choi, Sun-Young Yoon, Dong Kyu Oh, Su Yeon Lee, Mi Hyeon Park, Chae-Man Lim and 2 more

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2024. 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
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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

12 authors.

Young Seok Lee *Division of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul, Republic of Korea.
Seungbong Han *Department of Biostatistics, Korea University College of Medicine, Seoul, Republic of Korea.
Ye Eun LeeDepartment of Biostatistics, Korea University College of Medicine, Seoul, Republic of Korea.
Jaehwa ChoDivision of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
Young Kyun ChoiDivision of Infectious Disease and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Chungnam National University Sejong Hospital, Sejong, Republic of Korea.
Sun-Young YoonDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Chungnam National University Sejong Hospital, Sejong, Republic of Korea.
Dong Kyu OhDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Su Yeon LeeDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Mi Hyeon ParkDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Chae-Man LimDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Jae Young MoonDivision of Pulmonary, Allergy, and Critical Care Medicine, Department of Internal Medicine, Chungnam National University College of Medicine, Chungnam National University Sejong Hospital, Sejong, Republic of Korea. diffable@hanmail.net.
Korean Sepsis Alliance (KSA) Investigators

Funding

Korea Disease Control and Prevention Agency 2019E280500Korea Disease Control and Prevention Agency 2020E280700Korea Disease Control and Prevention Agency 2021-10-026National Research Foundation of Korea 2022R1F1A1063027
6 · The paper itself

Abstract

There are numerous prognostic predictive models for evaluating mortality risk, but current scoring models might not fully cater to sepsis patients' needs. This study developed and validated a new model for sepsis patients that is suitable for any care setting and accurately forecasts 28-day mortality. The derivation dataset, gathered from 20 hospitals between September 2019 and December 2021, contrasted with the validation dataset, collected from 15 hospitals from January 2022 to December 2022. In this study, 7436 patients were classified as members of the derivation dataset, and 2284 patients were classified as members of the validation dataset. The point system model emerged as the optimal model among the tested predictive models for foreseeing sepsis mortality. For community-acquired sepsis, the model's performance was satisfactory (derivation dataset AUC: 0.779, 95% CI 0.765-0.792; validation dataset AUC: 0.787, 95% CI 0.765-0.810). Similarly, for hospital-acquired sepsis, it performed well (derivation dataset AUC: 0.768, 95% CI 0.748-0.788; validation dataset AUC: 0.729, 95% CI 0.687-0.770). The calculator, accessible at https://avonlea76.shinyapps.io/shiny_app_up/ , is user-friendly and compatible. The new predictive model of sepsis mortality is user-friendly and satisfactorily forecasts 28-day mortality. Its versatility lies in its applicability to all patients, encompassing both community-acquired and hospital-acquired sepsis.

Indexed as

SepsisAgedAged, 80 and overArea Under CurveCommunity-Acquired InfectionsFemaleHospital MortalityHumansMaleMiddle AgedPrognosisRisk AssessmentROC CurveModelingMortalityPoint systemPrognosisSepsis

Identifiers

PMID38871785
PMCPMC11176384

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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.