# Hidden risk patterns among acute ischemic stroke patients identified by latent class analysis

## TL;DR

This study identifies two distinct risk patterns in acute ischemic stroke patients using statistical analysis, showing one group has worse outcomes.

## Contribution

The study introduces a novel use of latent class analysis to identify subgroups of AIS patients with distinct risk patterns and outcomes.

## Key findings

- Two subgroups of AIS patients were identified based on lymphocyte and neutrophil levels.
- Patients in the 'Elderly with low lymphocytes' group had significantly worse functional outcomes.
- CRP levels were low in both groups, but lymphocyte levels differed significantly.

## Abstract

Few studies focus on the comprehensive influence of multiple risk factors on the follow-up outcomes of acute ischemic stroke (AIS) patients. To fill this gap, this study aims to identify different subgroups with specific clinical characteristics and risk patterns among patients with AIS and to provide individualized treatment plans accordingly.

We obtained clinical follow-up data from 448 AIS patients within 72 h of admission. Subgroup patients were characterized by latent class analysis (LCA) using 5 risk factors of AIS. Cox proportional hazard regression analysis was used to explore the relationship between classified risk factor patterns and functional outcomes of patients with AIS at 3 months.

We obtained two risk factor patterns as “Elderly with low lymphocytes,” and “Participants with low neutrophils and high lymphocytes.” Class 1 (n = 214, 47.8%) had lower lymphocytes levels and was mainly elderly. Patients in Class 2 (N = 234, 53.2%) had higher lymphocytes levels and lower neutrophils levels than those in Class 1. In addition, CRP levels were mostly low in both Classes 1 and 2. There was a significant difference in poor functional outcomes between the two patterns after adjusting various confounders (p < 0.001). Compared with patients in Class 2, patients in Class 1 had a higher risk of adverse functional outcomes (adjusted Hazard Ratio, 3.21; 95% confidence interval: 2.07–4.98; p < 0.001).

In our study, LCA was used to identify a 2-Class LCA model that was shown distinct clinical features and laboratory measurements among AIS patients. Our findings are beneficial for health management and therapy.