ACDD4 s core: A s imple t ool for a ssessing r isk of p neumonia after s troke

Abstract Background Pneumonia is a serious but a preventable stroke complication. Prediction scales for post-stroke pneumonia have been proposed with an intent to improve surveillance and prevention but they remain under-utilized in clinical practice. Most existing scales were developed using both ventilated and non-ventilated patients which may affect their accuracy. We derived and validated a novel, pragmatic scale to predict hospital-acquired pneumonia (HAP) after stroke employing only a non-ventilated stroke cohort. Methods All consecutive patients admitted with acute stroke to a large hospital in Boston, Massachusetts, were identified using International Classification of Diseases, 9th revision (ICD-9) codes for acute ischemic strokes, intracerebral hemorrhages and confirmed by chart review. The following exclusion criteria were used: stroke occurring after hospitalization, pneumonia on admission, intubation, presence of brain or lung neoplasms, admission < 48 hours duration. HAP was defined using discharge ICD-9 codes. The association of relevant covariates with HAP was analyzed using multivariable stepwise logistic regression analysis to develop a scoring system and validated using bootstrapping. Results A total of 1644 patients met study criteria; 144 (8.8 %) developed HAP. An 8-point pneumonia prediction scale (ACDD4 ) was derived using significant covariates (age ≥ 75 = 1; congestive heart failure = 1; dysarthria = 1; dysphagia = 4). The risk of pneumonia varied between 2% and 33.9% with scores of 0 to 7, respectively. The c-statistic of the final model was 0.82 and bootstrap validation c-statistic was 0.81. Conclusion ACDD4 scale is a promising tool for predicting HAP in non-ventilated stroke patients that can be easily computed at the patient's bedside. Subject term: cerebrovascular disease/stroke