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Objectives: Fever frequently occurs in stroke patients and worsens their prognosis. However, only few studies have assessed the determinants of fever in acute stroke, and no study has specifically addressed the possible prediction of the development of fever., Materials and Methods: This investigation included 536 patients with acute stroke and a body temperature <=37°C during the first 24 h of stay. Ninety-two of them (17.2%) subsequently developed fever (defined as a temperature >=37.5°C starting after 24 h). Among the clinical variables available during the first 24 h from admission, those predictive of the subsequent appearance of fever were searched for. One hundred further patients had a temperature >37°C during the first 24 h., Results: In univariate analysis, many variables were predictive of the subsequent development of fever, but in multivariate analysis, only the following four predictors remained significant (odds ratio [95% confidence interval], P value): nasogastric tube (4.0 [2.2-7.4], <0.0001), atrial fibrillation (2.3 [1.4-3.8], 0.001), total anterior circulation syndrome (2.0 [1.2-3.5], 0.01), and urinary catheter (1.9 [1.1-3.3], 0.01). Among the 52 (9.7%) patients with three or four predictors, 31 (59.6%) subsequently developed fever. In addition, the factors independently associated with a temperature >37°C during the first 24 h were as follows: National Institutes of Health Stroke Scale (P < 0.0001), hemorrhagic stroke (P = 0.0008), atrial fibrillation (P = 0.002), and total parenteral nutrition (P = 0.03)., Conclusions: In patients with acute stroke, four clinical variables were found to be independently associated with the risk of developing fever and, of them, nasogastric tube was the strongest and most significant one., (© 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objectives: According to most existing models, a computer is usually needed for predicting stroke outcome. Our purpose was to construct a simple and reliable prognostic scale not requiring the use of a calculating machine., Materials and Methods: The scale [the Bologna Outcome Algorithm for Stroke (BOAS)] was obtained in 221 patients with ischemic stroke not undergoing thrombolysis and was then validated in a test group of 100 different patients. Outcome was assessed at 9 months as the number of dependent or dead patients (modified Rankin scale - mRS > 2)., Results: By a preliminary systematic univariate analysis, 25 of 415 baseline variables were found to be associated with a mRS > 2 independently of stroke severity and age. Subsequent multivariable analyses led to a final model based on five dichotomous risk factors (RF): National Institutes of Health Stroke Scale score ≥10, age ≥78, need of urinary catheter, oxygen administration, and persistence of upper limb paralysis at discharge from stroke unit. The patients with two or more RF (53%) had a mRS > 2 in 91% of cases and were dead in 42% of cases. With 0-1 RF, the two percentages were 24% and 2%, respectively (overall accuracy of prediction 83.9%, area under ROC curve [AUC] 0.891). In the test group, the accuracy was 79.0% and the AUC was 0.839., Conclusions: The need of urinary catheter, oxygen administration, and persistence of upper limb paralysis, together with stroke severity and advanced age, allow a simple and accurate prediction of dependency or death after ischemic stroke., (© 2011 John Wiley & Sons A/S.)