Evidence map›Paper›PMID 41150592›Full record

ArticleToxics2025

An In-Hospital Mortality Prediction Model for Acute Pesticide Poisoning in the Emergency Department.

Yoonseo Jeon, Da-Eun Kim, Inyong Jeong, Se-Jin Ahn, Nam-Jun Cho, Hyo-Wook Gil, Hwamin Lee

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Toxics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Yoonseo JeonCollege of Medicine, Korea University, Seoul 02841, Republic of Korea.ORCID 0009-0008-6955-1894
Da-Eun KimCollege of Medicine, Korea University, Seoul 02841, Republic of Korea.
Inyong JeongDepartment of Biomedical Informatics, Korea University College of Medicine, Seoul 02841, Republic of Korea.
Se-Jin AhnDepartment of Biomedical Informatics, Korea University College of Medicine, Seoul 02841, Republic of Korea.ORCID 0009-0003-5379-3673
Nam-Jun ChoDepartment of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan 31151, Republic of Korea.
Hyo-Wook GilDepartment of Internal Medicine, Soonchunhyang University Cheonan Hospital, Cheonan 31151, Republic of Korea.ORCID 0000-0003-2550-2739
Hwamin LeeDepartment of Biomedical Informatics, Korea University College of Medicine, Seoul 02841, Republic of Korea.ORCID 0000-0002-6482-3511

Funding

Institute of Information & Coummunications Technology Planning & Evaluation IITP-2025-RS-2022-00156439Korea Institute for Advancement of Technology P0023675
6 · The paper itself

Abstract

Pesticide poisoning remains a significant public health issue, characterized by high morbidity and mortality, particularly among patients presenting to the emergency department. This study aimed to develop a 14-day in-hospital mortality prediction model for patients with acute pesticide poisoning using early clinical and laboratory data. This retrospective cohort study included 1056 patients who visited Soonchunhyang University Cheonan Hospital between January 2015 and December 2020. The cohort was randomly divided into train (

Indexed as

acute pesticide poisoningemergency departmentin-hospital mortalitylogistic regressionmachine learning

Identifiers

PMID41150592
PMCPMC12567830

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.