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Electroencephalography Network Indices as Biomarkers of Upper Limb Impairment in Chronic Stroke

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Liver function test indices-based prediction model for post-stroke depression: a multicenter, retrospective study.

Jun Gong^1,2, Yalian Zhang^3,4, Xiaogang Zhong^5,6

¹Department of Information Center, University-town Hospital of Chongqing Medical University, Chongqing, China.

BMC Medical Informatics and Decision Making

|July 19, 2023

Summary

This summary is machine-generated.

This study identified six liver function test indices associated with post-stroke depression (PSD). A Gradient Boosting Decision Tree (GBDT) model effectively predicts PSD risk, offering a valuable tool for early detection and intervention.

Keywords:

Liver function test Post-stroke depression Prediction model Predictors Relationship

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Area of Science:

Neuroscience
Medical Informatics
Hepatology

Background:

Post-stroke depression (PSD) is a common and severe neuropsychiatric complication following stroke.
Current prediction tools for PSD are lacking, and the link between liver function and PSD is not well understood.

Purpose of the Study:

To investigate the association between liver function test indices and PSD.
To develop and validate a predictive model for PSD using machine learning algorithms.

Main Methods:

Data from 464 PSD patients and 1621 stroke patients were collected from seven medical institutions.
Six liver function test indices (AST, ALT, TBA, TBil, TP, ALB/GLB) were identified as predictors.
Gradient Boosting Decision Tree (GBDT) was employed to build the prediction model, evaluated using AUC, F1 score, sensitivity, and specificity.

Main Results:

Six liver function test indices were significantly associated with PSD.
The GBDT model demonstrated superior predictive performance with an AUC of 0.761 and F1 score of 0.498.
The logistic regression model achieved an AUC of 0.697 in the test set.

Conclusions:

The GBDT-based prediction model shows promising accuracy for identifying patients at risk of PSD.
This tool can be deployed via mobile or computer for clinical use in healthcare settings.
The identified liver function markers provide new insights into the pathophysiology of PSD.