# Predicting stroke-associated infection in acute ischemic stroke patients treated by thrombolysis

## TL;DR

This study identifies risk factors for stroke-associated infections and creates a tool to predict them in stroke patients treated with thrombolysis.

## Contribution

A predictive nomogram for early identification of stroke-associated infection in thrombolysis-treated stroke patients.

## Key findings

- 20.1% of patients developed stroke-associated infection, with pulmonary infections being most common.
- Five independent risk factors were identified, including higher modified Rankin Scale and male sex.
- The predictive nomogram achieved an area under the curve of 0.80 in training and 0.72 in validation cohorts.

## Abstract

Acute ischemic stroke (AIS) remains one of the major contributors to mortality and disability worldwide. Stroke-associated infection (SAI) is one of the most frequent complications following AIS and has a substantial impact on clinical outcomes, being closely linked to unfavorable prognosis. This study aimed to provide a comprehensive description of SAI, identify independent risk factors, and develop a predictive nomogram for its early identification.

This study included 836 AIS patients of the Dalian Single-center Study on Intravenous Thrombolysis for Ischaemic Stroke (DATIS) cohort who received recombinant tissue-plasminogen activator-induced thrombolysis at Central Hospital of Dalian University of Technology between January 2018 and November 2021. Patients were divided into a training cohort (n = 586, 70%) and a validation cohort (n = 250, 30%). Composition and economic features of SAI was explored. Independent risk factors were identified using univariate, multivariate, and multimodal logistic regression analyses. A predictive nomogram was then developed based on these independent risk factors. Model performance was assessed with receiver operating characteristic curves, and calibration curves.

Among the 836 enrolled patients, 168 (20.1%) developed SAI. Composition of 168 patients with SAI were: 99 pulmonary infections (58.93%), 44 upper respiratory tract infections (26.19%), 15 urinary tract infection (8.93%), 2 gastrointestinal tract infections (1.19%), 1 periodontal infection (0.60%), 1 conjunctival infection (0.60%), and 1 erysipela (0.60%). In addition, 5 patients (2.98%) had multi-site infections (4 pulmonary plus urinary tract infection, 1 pulmonary plus gastrointestinal tract infection). Compared with non-infected patients, the SAI group experienced a significantly longer median hospitalization duration [9 days, IQR (7, 10) vs. 8 days, IQR (7, 9), p < 0.001] and incurred higher median inpatient medical costs [28114.04 RMB, IQR (23230.12, 33379.85) vs. 22292.84 RMB, IQR (19203.53, 25999.63), p < 0.001]. Five variables—higher modified Rankin Scale at admission, male sex, prolonged prothrombin time, elevated blood urea nitrogen and lower thyroid-stimulating hormone—were independent risk factors for SAI. The nomogram constructed based on above predictors achieved an area under the curve of 0.80 in the training cohort and 0.72 in the validation cohort. Calibration curves supported the model’s performance.

This prospective cohort study comprehensively described composition and economic features, identified risk factors and developed predictive nomogram for SAI in AIS patients receiving intravenous rt-PA. Early identification of high-risk patients may facilitate targeted interventions, potentially reducing infection-related complications and improving clinical outcomes.