@article{iaaskwabtgafwhrrckcb2022,
 author = {Ziegler, W.},
 title = {The prevalence of apraxia of speech in chronic aphasia after stroke: A bayesian hierarchical analysis, Cortex},
 abstract = {Apraxia of speech is a motor speech disorder that occurs after lesions to the left cerebral hemisphere, most often concomitant with aphasia. It requires specific approaches in the study of its physiological and neuroanatomical basis and special expertise in clinical care. Knowing its prevalence in patients with aphasia after stroke is therefore relevant for planning specific resources in clinical research and in health care provision. Systematic studies of the frequency of this condition are lacking. We examined the frequency of apraxia of speech in a representative sample of 156 patients with chronic post-stroke aphasia. Three experts classified the patients’ speech by best-practice auditory-perceptual methods. Bayesian hierarchical models were fitted to obtain probability distributions for prevalence estimates. A prior distribution was calculated in two steps, including Bayesian models for published frequency data (step 1) and prevalence estimates from experienced clinicians (step 2). Separate models were fitted for different severity ranges. Overall, a prevalence rate of .44 [.30, .58] was obtained. When only moderate and severe cases were taken into account, the rate was .35 [.23, .49]. After a further restriction to only severe impairment, prevalence dropped to .22 [.12, .34]. Patients identified with apraxia of speech had suffered more severe strokes according to clinical criteria and had more severe aphasias. The presence of apraxia of speech was predicted by the articulation/prosody and syntax rating scales of the Aachen Aphasia Test. Lower prevalence estimates published earlier are probably biased by low sensitivity of assessment instruments for mild speech impairment.},
 keywords = {Apraxia of speech; Chronic aphasia; Prevalence; Stroke},
 tags = {""},
 year = {2022},
 pages = {15-29},
 volume = {151},
 journal = {Cortex},
 doi = {https://doi.org/10.1016/j.cortex.2022.02.012. (https://www.sciencedirect.com/science/article/pii/S0010945222000661)},
 isbn = {0010-9452},
}