| Literature DB >> 32907594 |
Klaudia Grechuta1, Belén Rubio Ballester1, Rosa Espín Munné2, Teresa Usabiaga Bernal2, Begoña Molina Hervás2, Bettina Mohr3, Friedemann Pulvermüller4,5,6, Rosa Maria San Segundo2, Paul F M J Verschure7,8.
Abstract
BACKGROUND: Impaired naming is a ubiquitous symptom in all types of aphasia, which often adversely impacts independence, quality of life, and recovery of affected individuals. Previous research has demonstrated that naming can be facilitated by phonological and semantic cueing strategies that are largely incorporated into the treatment of anomic disturbances. Beneficial effects of cueing, whereby naming becomes faster and more accurate, are often attributed to the priming mechanisms occurring within the distributed language network.Entities:
Keywords: Aphasia; Lexical access; Multisensory cueing; Neurorehabilitation; Stroke; Word-finding
Mesh:
Year: 2020 PMID: 32907594 PMCID: PMC7487671 DOI: 10.1186/s12984-020-00751-w
Source DB: PubMed Journal: J Neuroeng Rehabil ISSN: 1743-0003 Impact factor: 4.262
Sociodemographic patient characteristics
| ID | Age | Sex | Etiology | Chronicity (m) | Severity |
|---|---|---|---|---|---|
| 9 | 58 | M | Ischemia | 6 | Severe |
| 10 | 39 | F | Ischemia | 83 | Severe |
| 11 | 64 | M | Ischemia | 46 | Severe |
| 12 | 63 | F | Hemorrhage | 72 | severe |
| 13 | 62 | M | Ischemia | 106 | Severe |
| 14 | 56 | F | Ischemia | 144 | Severe |
| 15 | 43 | F | Hemorrhage | 72 | Severe |
| 16 | 55 | F | Ischemia | 6 | Moderate |
| 17 | 75 | M | Ischemia | 144 | Moderate |
| 18 | 61 | M | Ischemia | 20 | Moderate |
| 57.6 (9.9) | 69.9 (48.7) |
Fig. 1a Illustration of the Interaction Time (IT) measure, possible moves, and speech- acts. b Example of the materials. Left: stimuli undergoing SAC, right: stimuli undergoing SVC. c Fit for each participant’s averaged IT over the therapy interval for all the stimuli undergoing Silent Visuomotor (SVC, violet) and Semantic Auditory (SAC, red) cueing. Upper panels: Lines represent linear regression models for individual participants including cued and non-cued trials. Lower panels: Median ITs of all the participants including all stimuli for each therapy session
Outcome measures at weeks 2, 4, 6, 8, and 16 (followup). Bold values indicate significant differences (p < .05). P-values for within-group analysis were obtained with Wilcoxon signedrank test
| Within-group analysis | ||
|---|---|---|
| W2 | δ(W2-BL) | |
| 86.93(10.26)-88.60 | 7.8(6.85)-10.73 | |
| [79.19-94.67] | [2.63-12.97] | |
| W4 | δ(W4−BL) | |
| 90.01(9.81)-94.09 | 10.88(7.03)-12.54 | |
| [82.61-97.41] | [5.57-16.19] | |
| W6 | δ(W6−BL) | |
| 92.47(10.63)-97.37 | 13.34(7.33)-13.19 | |
| [84.45-100.49] | [7.81-18.87] | |
| W8 | δ(TW8−BL) | |
| 95.06(8.31)-98.44 | 15.93(7.56)-13.68 | |
| [88.79-101.33] | [10.22-21.64] | |
| W16 | δ(W16−BL) | |
| 94.78(8.79)-98.77 | 15.65(7.02)-14.42 | |
| [88.15-101.41] | [10.35-20.95] | |
Fig. 2a Evolution of median ITs for cued on non-cued stimuli over the therapy sessions. Lines represent nonlinear regression models for cued and non-cued visuomotor (violet) and auditory (red) cues. b Quantification of differences in ITs for SVC and SAC between cued and non-cued stimuli in the early (first 15) and late (last 15) therapy sessions