It Is Difficult to Make Predictions, Especially About the Future

See related article, p 3308 Physicists, politicians, poets, and punters understand the pitfalls of predicting the future. Similarly, predicting outcomes after stroke rehabilitation can be difficult when based on clinical impression, and several approaches to combining key variables in predictive models have been developed.1–3 In this issue, Scrutinio et al4 introduce a predictive model of functional outcome after stroke based on retrospective data from several hundred patients who were treated at the Maugeri rehabilitation centers between 2002 and 2015. Their primary binary logistic model predicts the probability of a patient having mild disability at discharge from inpatient rehabilitation, defined as a score of ≥61 on the motor component of the functional independence scale (M-FIM; maximum score 91). A second model predicts the probability of a patient requiring no more than supervision in activities of daily living at discharge. Both models use expected predictors such as age, sex, and FIM scores on admission to rehabilitation and perform well with areas under the curve around 0.80. The authors have taken a further step by creating an online tool that allows them to calculate the probability that each of their patients will achieve …