JOURNAL ARTICLE

Prediction of motor recovery after stroke: being pragmatic or innovative?

Charlotte Rosso, Jean-Charles Lamy
Current Opinion in Neurology 2020, 33 (4): 482-487
32657889

PURPOSE OF REVIEW: This review considers both pragmatic and cutting-edge approaches for predicting motor stroke recovery over the period 2017-2019. It focuses on the predictive value of clinical scores and biomarkers including Transcranial Magnetic Stimulation (TMS) and MRI as well as more innovative alternatives.

RECENT FINDINGS: Clinical scores combined with corticospinal tract (CST) integrity as assessed by both TMS-induced motor-evoked potential (MEP) and MRI predict motor recovery with an accuracy of about 75%. Therefore, research on novel biomarkers is still needed to improve the accuracy of these models.

SUMMARY: Up to date, there is no consensus about which predictive models should be used in clinical routine. Decision trees, such as the PREP2 algorithm are probably the easiest approach to operationalize the translation of predictive models from bench to bedside. However, external validation is still needed to implement current models.

Full Text Links

We have located links that may give you full text access.

Discussion

You are not logged in. Sign Up or Log In to join the discussion.

Related Papers

Remove bar
Read by QxMD icon Read
32657889
×

Save your favorite articles in one place with a free QxMD account.

×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"