Accurate Prediction of Persistent Upper Extremity Impairment in Patients With Ischemic Stroke.
Adam de Havenon, Laura Heitsch, Abimbola Sunmonu and 7 others
PMID 34813742WHAT IT FOUND
A simple bedside score using age and standard stroke severity items predicts persistent arm impairment at 90 days.
Scores calculated from discharge assessments were more accurate than those from 24 hours, offering a practical tool to identify patients likely to need long-term rehabilitation.
Key findings
01The PUPPI index, using a cutpoint of ≥3, predicted persistent arm impairment with an AUC of 0.78 when calculated from 24-hour data and 0.81 when calculated from discharge data.
02Prediction accuracy was significantly better when using NIHSS scores collected at discharge or day 4–10 compared to 24 hours.
03The index components are age ≥55 years, worse arm score of 4, worse leg score ≥3, facial palsy score of 3, and total NIHSS score ≥10.
STILL TO COME
How it was doneWhat they foundWhat it means for PTsWhat it means for OTs
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What it does not show
The study lacked an external validation dataset, relying on internal derivation and validation splits. Data came from clinical trials, which may not reflect the general stroke population due to selection bias. Information on discharge destination and specific rehabilitation resources was not available, so the impact of these factors on outcomes could not be assessed. The index predicts the presence of persistent impairment (moderate-to-severe) rather than the specific gradations of motor function recovery.
Declared interests
Funding was provided by the National Institute of Neurological Disorders and Stroke (NINDS) and other U.S. Government and Non-U.S. Government sources. The authors used deidentified, publicly available datasets from previous trials.
The easy way to misread this
Do not assume this index predicts full motor recovery or specific functional outcomes. It only predicts the presence of moderate-to-severe impairment at 90 days, and its accuracy depends heavily on using discharge rather than 24-hour assessment data.