Evidence mapPaperPMID 35799673Full record

Trial reportComputational and mathematical methods in medicine2022

Prediction Model between Serum Vitamin D and Neurological Deficit in Cerebral Infarction Patients Based on Machine Learning.

Hailiu Zhang, Guotao Yang, Aiqin Dong

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Computational and mathematical methods in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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

3 authors.

Hailiu ZhangDepartment of Neurology, Cangzhou Central Hospital, Cangzhou 061000, China.ORCID https://orcid.org/0000-0002-6418-7666
Guotao YangDepartment of Neurology, Cangzhou Central Hospital, Cangzhou 061000, China.ORCID https://orcid.org/0000-0002-1286-3159
Aiqin DongDepartment of Neurology, Cangzhou Central Hospital, Cangzhou 061000, China.ORCID https://orcid.org/0000-0002-3382-5768

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Vitamin D is associated with neurological deficits in patients with cerebral infarction. This study uses machine learning to evaluate the prediction model's efficacy of the correlation between vitamin D and neurological deficit in patients with cerebral infarction. Methods: A total of 200 patients with cerebral infarction admitted to the Department of Neurology of our hospital from July 2018 to June 2019 were selected. The patients were randomly divided into a training set ( Results: In the training set, the area under the curve (AUC) of the logistic regression model and XGBoost algorithm model was 0.727 (95% CI: 0.601~0.854) and 0.818 (95% CI: 0.734~0.934), respectively. While in the test set, the AUC of the logistic regression model and XGBoost algorithm model was 0.761 (95% CI: 0.640~0.882) and 0.786 (95% CI: 0.670~0.902), respectively. Conclusion: The prediction model of the correlation between vitamin D and neurological deficit in patients with cerebral infarction based on machine learning has a good prediction efficiency.

Indexed as

Machine LearningVitamin DArea Under CurveCerebral InfarctionHumansLogistic ModelsRetrospective StudiesVitamin D

Identifiers

PMID35799673
PMCPMC9256304

What Socratic holds

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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 Socratic graph.