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Murine Oropharyngeal Aspiration Model of Ventilator-associated and Hospital-acquired Bacterial Pneumonia
Published on: June 28, 2018
Risk factors for post-stroke aspiration pneumonia in long-term hospitalized patients: a retrospective study
Mengxia Shen1, Zheke Fang1, Di Sun1
1Rehabilitation Department, Tongde Hospital of Zhejiang Province, Hangzhou, China.
Background:
Aspiration pneumonia (AP) is highly common among stroke patients and significantly impacts their prognosis. This study aimed to explore the risk factors for AP in long-term hospitalized stroke patients.
Methods:
We conducted a retrospective analysis of long-term hospitalized stroke patients at the Tongde Hospital of Zhejiang Province. The patients were divided into two groups based on whether (or not) they developed AP during hospitalization. The clinical features and blood test indicators of the two groups were compared. Binary logistic regression was employed to identify the risk factors for post-stroke AP.
Results:
A total of 120 sub-acute or chronic stroke patients were included from August 1, 2021 to March 1, 2025, of whom, 64 experienced AP during hospitalization. The binary logistic regression analysis identified independent risk factors for AP, including water swallow test grades 3-5 [odds ratio (OR) =5.105, 95% confidence interval (CI): 1.260-20.676, P=0.02], requirement of a wheelchair (OR =5.133, 95% CI: 1.232-21.387, P=0.03, compared to those able to walk or stand), being bedridden (OR =6.829, 95% CI: 1.472-31.671, P=0.01, compared to those able to walk or stand), albumin ≤35 g/L (OR =3.362, 95% CI: 1.030-10.977, P=0.045), and C-reactive protein (CRP) (OR =1.123, 95% CI: 1.008-1.250, P=0.035). Significant statistical differences in serum albumin levels were observed between the AP and non-AP group at various hospitalization time points, including admission, 1 month, 2 months, and 3 months, all P<0.001.
Conclusions:
Our research findings identified dysphagia, an inability to walk or stand, low serum albumin level, and a high CRP level as key factors in predicting the occurrence of post-stroke AP. Our prediction model can be used for early life-style clinical interventions or to inform therapeutic decisions for high-risk patients.
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