Evidence map›Paper›PMID 42170443›Full record

ArticleAmerican journal of translational research2026

Construction and validation of a prognostic nomogram for predicting in-hospital mortality of patients with acute chlorfenapyr poisoning.

Yuan Xie, Yanxing Lan, Zongming Xu, Yaowu Chen, Guoyun Shi, Fenshuang Zheng

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Article in American journal of translational research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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6 authors.

Yuan XieDepartment of Emergency Medicine, The Affiliated Hospital of Yunnan University Kunming, Yunnan, China.
Yanxing LanDepartment of Emergency Medicine, The Affiliated Hospital of Yunnan University Kunming, Yunnan, China.
Zongming XuDepartment of Emergency Medicine, Yunnan Provincial Emergency Medical Center Kunming, Yunnan, China.
Yaowu ChenDepartment of Emergency Medicine, People's Hospital of Lijiang Lijiang, Yunnan, China.
Guoyun ShiDepartment of Emergency Medicine, People's Hospital of Lijiang Lijiang, Yunnan, China.
Fenshuang ZhengDepartment of Emergency Medicine, The Affiliated Hospital of Yunnan University Kunming, Yunnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo identify key risk factors for in-hospital mortality in patients with acute chlorfenapyr poisoning and to develop a clinically applicable nomogram to predict in-hospital mortality in this population.

methodsThis retrospective study analyzed 130 patients, who were assigned to training (n=91) and validation (n=39) cohorts. The training cohort included 53 survivors and 38 non-survivors, with 30-day mortality as the endpoint. Univariate analysis was used to identify factors associated with mortality. Candidate variables were screened using LASSO regression, followed by multivariate logistic regression to identify independent risk factors. A nomogram was constructed based on these predictive factors, and its discriminative power, calibration, and clinical applicability were evaluated. The performance of the nomogram was validated in an external validation cohort.

resultsThe mortality rate was 41.8% in the training cohort and 38.5% in the validation cohort. Among the nine candidate variables screened by LASSO regression, multivariate analysis identified four independent predictors: ATP-cytochrome C utilization (OR 78.57, 95% CI 1.81-3412), procalcitonin (OR 65.76, 95% CI 1.04-4175), administered dose (OR 1.08, 95% CI 1.02-1.14), and alanine aminotransferase (ALT) (OR 1.09, 95% CI 1.02-1.17). The predictive model demonstrated excellent discriminative power, with a C-index of 0.988 in the training group and 0.849 in the validation group. The calibration was good (P=0.771 and P=0.942), and decision curve analysis confirmed its significant clinical applicability.

conclusionWe developed and validated a practical nomogram that accurately predicts the risk of in-hospital mortality in patients with acute chlorfenapyr poisoning, which may aid in early risk stratification and clinical decision-making.

Indexed as

Acute chlorfenapyr poisoningnomogramprediction modelrisk factors

Identifiers

PMID42170443
PMCPMC13186761

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