Related Experiment Video
Updated: Apr 24, 2026

Following in Real Time the Impact of Pneumococcal Virulence Factors in an Acute Mouse Pneumonia Model Using Bioluminescent Bacteria
Published on: February 23, 2014
[Pathogen Profile and Risk Factors for Hospital-Acquired Infection in Stroke Patients]
Ting Xu1, Bingqing Han1, Hanyu Zhang1
1( 100070)Department of Laboratory Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China.
Objective:
To investigate the risk factors for hospital-acquired infection in patients with stroke and to analyze the distribution of pathogens and characteristics of infection sites.
Methods:
A retrospective cohort study was conducted, enrolling 393 patients with stroke hospitalized at Beijing Tiantan Hospital, Capital Medical University, from January 2024 to July 2025. Among them, 184 patients were assigned to the infection group and 209 to the non-infection group. Multivariable logistic regression analysis was used to identify risk factors for hospital-acquired infection, and a nomogram prediction model was constructed.
Results:
Multivariable logistic regression analysis identified cerebral infarction (odds ratio = 25.09, 95% confidence interval: 5.38-117.10), no history of alcohol consumption (odds ratio = 4.47, 95% confidence interval: 1.51-13.18), no history of cerebrovascular disease (odds ratio = 5.04, 95% confidence interval: 1.35-18.76), elevated neutrophil count (odds ratio = 1.29, 95% confidence interval: 1.08-1.55), and elevated C-reactive protein (odds ratio = 1.03, 95% confidence interval: 1.01-1.06) as independent risk factors for hospital-acquired infection in patients with stroke. Absence of nasogastric tube feeding (odds ratio = 0.09, 95% confidence interval: 0.03-0.31), no indwelling urinary catheterization (odds ratio = 0.21, 95% confidence interval: 0.06-0.77), and absence of postoperative coma (odds ratio = 0.07, 95% confidence interval: 0.01-0.36) were identified as protective factors. The nomogram model achieved an area under the curve of 0.96 (95% confidence interval: 0.94-0.98) in the training set and 0.94 (95% confidence interval: 0.90-0.99) in the validation set, with good calibration. Gram-negative bacteria were the predominant pathogens (70.2%), and the respiratory tract was the most common infection site (92.9%). Endotracheal intubation and impaired consciousness were identified as common risk factors for both pulmonary and Gram-negative bacterial infections.
Conclusion:
This study identified independent risk factors for hospital-acquired infection in patients with stroke, developed a nomogram model with good predictive performance, and preliminarily characterized the risk profiles associated with different infection types and sites. These findings provide a reference for early identification of high-risk patients and the formulation of targeted prevention and control strategies.
More Related Videos
12:21A Mouse Model for the Transition of Streptococcus pneumoniae from Colonizer to Pathogen upon Viral Co-Infection Recapitulates Age-Exacerbated Illness
Published on: September 28, 2022
06:28Modeling Stroke in Mice - Middle Cerebral Artery Occlusion with the Filament Model
Published on: January 6, 2011
Related Concept Videos
Factors Affecting the Risk of Infection
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
Healthcare Associated Infections II: Preventive Measures
The best practices for preventing healthcare-associated infections include hand hygiene, patient risk...
Healthcare Associated Infections I: Iatrogenic, Exogenic and Endogenic
HAIs significantly increase the cost of health care. Extended stays in healthcare institutions, increased disability, increased costs of medications, including specialized antibiotics, and prolonged recovery times add to the patient's expenses and the healthcare institution and funding bodies.
Pneumonia I: Introduction
Risk Factors
Various factors influence the likelihood of developing pneumonia. Age plays a crucial role, with infants, children under two, and individuals over 65 at increased risk due to their...
Pneumonia I: Introduction
Endocarditis I: Introduction