Evidence map›Paper›PMID 37828549›Full record

ArticleEuropean journal of medical research2023

A dynamic online nomogram for predicting death in hospital after aneurysmal subarachnoid hemorrhage.

Tian Li, Dongzhou Zhuang, Yong Xiao, Xiaoxuan Chen, Yuan Zhong, Xurong Ou, Hui Peng, Shousen Wang, Weiqiang Chen, Jiangtao Sheng

Open access · goldAbstract read
In one paragraph

Article in European journal of medical research, 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
0.4field-weighted citation impact, top 34% 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

10 authors at 5 institutions in 1 country.

Tian Li *Department of Microbiology and Immunology, Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, Shantou University Medical College, 22 Xinling Road, Shantou, 515000, Guangdong, China.
Dongzhou Zhuang *Department of Neurosurgery, Fuzong Clinical Medical College of Fujian Medical University, 900 Hospital, Fuzhou, 350025, China.
Yong Xiao *Department of Neurosurgery, First Affiliated Hospital, Shantou University Medical College, 57 Changping Road, Shantou, 515000, Guangdong, China.
Xiaoxuan ChenDepartment of Microbiology and Immunology, Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, Shantou University Medical College, 22 Xinling Road, Shantou, 515000, Guangdong, China.
Yuan ZhongDepartment of Neurosurgery, First Affiliated Hospital, Shantou University Medical College, 57 Changping Road, Shantou, 515000, Guangdong, China.
Xurong OuDepartment of Neurosurgery, First Affiliated Hospital, Shantou University Medical College, 57 Changping Road, Shantou, 515000, Guangdong, China.
Hui PengDepartment of Neurosurgery, Affiliated Jieyang People's Hospital of Sun Yat-sen University, 107 Tianfu Road, Jieyang, 522000, China.
Shousen WangDepartment of Neurosurgery, Fuzong Clinical Medical College of Fujian Medical University, 900 Hospital, Fuzhou, 350025, China. wshsen@126.com.
Weiqiang ChenDepartment of Neurosurgery, First Affiliated Hospital, Shantou University Medical College, 57 Changping Road, Shantou, 515000, Guangdong, China. wqchen@stu.edu.cn.
Jiangtao ShengDepartment of Microbiology and Immunology, Guangdong Provincial Key Laboratory of Infectious Disease and Molecular Immunopathology, Shantou University Medical College, 22 Xinling Road, Shantou, 515000, Guangdong, China. jtsheng@stu.edu.cn.
First Affiliated Hospital of Shantou University Medical College · CNFujian Medical University · CNShantou University · CNShantou University Medical College · CNSun Yat-sen University · CN

Funding

China Postdoctoral Science Foundation 2018M633091Fujian Provincial Science and Technology Innovation Joint Fund 2019Y9045Natural Science Foundation of Guangdong Province 2019A1515010649
6 · The paper itself

Abstract

backgroundThis study aimed to validate the efficacy the multiplication of neutrophils and monocytes (MNM) and a novel dynamic nomogram for predicting in-hospital death in patients with aneurysmal subarachnoid hemorrhage (aSAH).

methodsRetrospective study was done on 986 patients with endovascular coiling for aSAH. Independent risk factors associated with in-hospital death were identified using both univariate and multivariate logistic regression analysis. In the development cohort, a dynamic nomogram of in-hospital deaths was introduced and made available online as a straightforward calculator. To predict the in-hospital death from the external validation cohort by nomogram, calibration analysis, decision curve analysis, and receiver operating characteristic analysis were carried out.

results72/687 patients (10.5%) in the development cohort and 31/299 patients (10.4%) in the validation cohort died. MNM was linked to in-hospital death in univariate and multivariate regression studies. In the development cohort, a unique nomogram demonstrated a high prediction ability for in-hospital death. According to the calibration curves, the nomogram has a reliable degree of consistency and calibration. With threshold probabilities between 10% and 90%, the nomogram's net benefit was superior to the basic model. The MNM and nomogram also exhibited good predictive values for in-hospital death in the validation cohort.

conclusionsMNM is a novel predictor of in-hospital mortality in patients with aSAH. For aSAH patients, a dynamic nomogram is a useful technique for predicting in-hospital death.

Indexed as

NomogramsSubarachnoid HemorrhageHospital MortalityHospitalsHumansRetrospective StudiesAneurysmal subarachnoid hemorrhageInflammationMultiplication of neutrophil and monocyte countsNomogramOutcome

Identifiers

PMID37828549
PMCPMC10571411
OpenAlexW4387579861

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LicenceCC BY
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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.