Evidence map›Paper›PMID 35937067›Full record

ArticleFrontiers in neurology2022

Establishment and validation of a prediction model for self-absorption probability of chronic subdural hematoma.

Ye Tian, Dong Wang, Xinjie Zhang, Huijie Wei, Yingsheng Wei, Shuo An, Chuang Gao, Jinhao Huang, Jian Sun, Rongcai Jiang and 1 more

Open access · goldAbstract 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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 28% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

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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

11 authors at 1 institution in 1 country.

Ye TianDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Dong WangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Xinjie ZhangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Huijie WeiDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Yingsheng WeiDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Shuo AnDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Chuang GaoDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Jinhao HuangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Jian SunDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Rongcai JiangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Jianning ZhangDepartment of Neurosurgery, Tianjin Medical University General Hospital, Tianjin, China.
Tianjin Medical University General Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chronic subdural hematoma (CSDH) is common in elderly people with a clear or occult traumatic brain injury history. Surgery is a traditional method to remove the hematomas, but it carries a significant risk of recurrence and poor outcomes. Non-surgical treatment has been recently considered effective and safe for some patients with CSDH. However, it is a challenge to speculate which part of patients could obtain benefits from non-surgical treatment. Objective: To establish and validate a new prediction model of self-absorption probability with chronic subdural hematoma. Method: The prediction model was established based on the data from a randomized clinical trial, which enrolled 196 patients with CSDH from February 2014 to November 2015. The following subjects were extracted: demographic characteristics, medical history, hematoma characters in imaging at admission, and clinical assessments. The outcome was self-absorption at the 8th week after admission. A least absolute shrinkage and selection operator (LASSO) regression model was implemented for data dimensionality reduction and feature selection. Multivariable logistic regression was adopted to establish the model, while the experimental results were presented by nomogram. Discrimination, calibration, and clinical usefulness were used to evaluate the performance of the nomogram. A total of 60 consecutive patients were involved in the external validation, which enrolled in a proof-of-concept clinical trial from July 2014 to December 2018. Results: Diabetes mellitus history, hematoma volume at admission, presence of basal ganglia suppression, presence of septate hematoma, and usage of atorvastatin were the strongest predictors of self-absorption. The model had good discrimination [area under the curve (AUC), 0.713 (95% Conclusions: This prediction model can be used to obtain self-absorption probability in patients with CSDH, assisting in guiding the choice of therapy, whether they undergo non-surgical treatment or surgery.

Indexed as

chronic subdural hematomanomogramnon-surgical treatmentprediction modelself-absorption

Identifiers

PMID35937067
PMCPMC9355276
OpenAlexW4286560731

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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.