Adam J Friedant1, Brittany M Gouse1, Amelia K Boehme2, James E Siegler3, Karen C Albright4, Dominique J Monlezun1, Alexander J George1, Timothy Mark Beasley5, Sheryl Martin-Schild6. 1. Stroke Program, Department of Neurology, Tulane University Hospital, New Orleans, LA. 2. Gertrude H. Sergievsky Center, Department of Neurology, Columbia University, New York, NY; Department of Neurology, School of Medicine, University of Alabama at Birmingham, Birmingham, AL. 3. Stroke Program, Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA. 4. Department of Epidemiology, School of Public Health; Health Services and Outcomes Research Center for Outcome and Effectiveness Research and Education (COERE), Division of Preventive Medicine; Center of Excellence in Comparative Effectiveness Research for Eliminating Disparities (CERED) Minority Health & Health Disparities Research Center (MHRC). 5. Section on Statistical Genetics, Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, AL. 6. Stroke Program, Department of Neurology, Tulane University Hospital, New Orleans, LA. Electronic address: smartin2@tulane.edu.
Abstract
BACKGROUND: Hospital-acquired infections (HAIs) are a major cause of morbidity and mortality in acute ischemic stroke patients. Although prior scoring systems have been developed to predict pneumonia in ischemic stroke patients, these scores were not designed to predict other infections. We sought to develop a simple scoring system for any HAI. METHODS: Patients admitted to our stroke center (July 2008-June 2012) were retrospectively assessed. Patients were excluded if they had an in-hospital stroke, unknown time from symptom onset, or delay from symptom onset to hospital arrival greater than 48 hours. Infections were diagnosed via clinical, laboratory, and imaging modalities using standard definitions. A scoring system was created to predict infections based on baseline patient characteristics. RESULTS: Of 568 patients, 84 (14.8%) developed an infection during their stays. Patients who developed infection were older (73 versus 64, P < .0001), more frequently diabetic (43.9% versus 29.1%, P = .0077), and had more severe strokes on admission (National Institutes of Health Stroke Scale [NIHSS] score 12 versus 5, P < .0001). Ranging from 0 to 7, the overall infection score consists of age 70 years or more (1 point), history of diabetes (1 point), and NIHSS score (0-4 conferred 0 points, 5-15 conferred 3 points, >15 conferred 5 points). Patients with an infection score of 4 or more were at 5 times greater odds of developing an infection (odds ratio, 5.67; 95% confidence interval, 3.28-9.81; P < .0001). CONCLUSION: In our sample, clinical, laboratory, and imaging information available at admission identified patients at risk for infections during their acute hospitalizations. If validated in other populations, this score could assist providers in predicting infections after ischemic stroke.
BACKGROUND: Hospital-acquired infections (HAIs) are a major cause of morbidity and mortality in acute ischemic strokepatients. Although prior scoring systems have been developed to predict pneumonia in ischemic strokepatients, these scores were not designed to predict other infections. We sought to develop a simple scoring system for any HAI. METHODS:Patients admitted to our stroke center (July 2008-June 2012) were retrospectively assessed. Patients were excluded if they had an in-hospital stroke, unknown time from symptom onset, or delay from symptom onset to hospital arrival greater than 48 hours. Infections were diagnosed via clinical, laboratory, and imaging modalities using standard definitions. A scoring system was created to predict infections based on baseline patient characteristics. RESULTS: Of 568 patients, 84 (14.8%) developed an infection during their stays. Patients who developed infection were older (73 versus 64, P < .0001), more frequently diabetic (43.9% versus 29.1%, P = .0077), and had more severe strokes on admission (National Institutes of Health Stroke Scale [NIHSS] score 12 versus 5, P < .0001). Ranging from 0 to 7, the overall infection score consists of age 70 years or more (1 point), history of diabetes (1 point), and NIHSS score (0-4 conferred 0 points, 5-15 conferred 3 points, >15 conferred 5 points). Patients with an infection score of 4 or more were at 5 times greater odds of developing an infection (odds ratio, 5.67; 95% confidence interval, 3.28-9.81; P < .0001). CONCLUSION: In our sample, clinical, laboratory, and imaging information available at admission identified patients at risk for infections during their acute hospitalizations. If validated in other populations, this score could assist providers in predicting infections after ischemic stroke.
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