Evidence map›Paper›PMID 35280284›Full record

ArticleFrontiers in neurology2022

A Nomogram That Includes Neutrophils and High-Density Lipoprotein Cholesterol Can Predict the Prognosis of Acute Ischaemic Stroke.

Nan Wang, Hongbing Liu, Mengke Tian, Jing Liang, Wenxian Sun, Luyang Zhang, Lulu Pei, Kai Liu, Shilei Sun, Jun Wu and 4 more

Abstract read
In one paragraph

Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

14 authors.

Nan WangDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Hongbing LiuDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Mengke TianDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jing LiangDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Wenxian SunDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Luyang ZhangDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Lulu PeiDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Kai LiuDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Shilei SunDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Jun WuDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yuan GaoDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yuming XuDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Yilong WangDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Bo SongDepartment of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lipids are implicated in inflammatory responses affecting acute ischaemic stroke prognosis. Therefore, we aimed to develop a predictive model that considers neutrophils and high-density lipoprotein cholesterol to predict its prognosis. This prospective study enrolled patients with acute ischaemic stroke within 24 h of onset between January 2015 and December 2017. The main outcome was a modified Rankin Scale score ≥3 at the 90th day of follow-up. Patients were divided into training and testing sets. The training set was divided into four states according to the median of neutrophils and high-density lipoprotein cholesterol levels in all patients. Through binary logistic regression analysis, the relationship between factors and prognosis was determined. A nomogram based on the results was developed; its predictive value was evaluated through internal and external validations. Altogether, 1,090 patients were enrolled with 872 (80%) and 218 (20%) in the training and testing sets, respectively. In the training set, the major outcomes occurred in 24 (10.4%), 24 (11.6%), 37 (17.2%), and 49 (22.3%) in states 1-4, respectively (

Indexed as

high-density lipoprotein cholesterolneutrophilnomogramprognosisstroke

Identifiers

PMID35280284
PMCPMC8914087

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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.