Determinants of aphasia recovery: exploratory decision tree analysis
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Lahiri, Durjoy
[1
,2
]
Dubey, Souvik
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IPGMER, Bangur Inst Neurosci, Kolkata, India
SSKM Hosp Kolkata, Kolkata, IndiaIPGMER, Bangur Inst Neurosci, Kolkata, India
Dubey, Souvik
[1
,2
]
Ardila, Alfredo
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IM Sechenov First Moscow State Med Univ, Inst Linguist & Intercultural Commun, Moscow, Russia
Albizu Univ, Psychol Doctoral Program, Miami, FL 33172 USAIPGMER, Bangur Inst Neurosci, Kolkata, India
Ardila, Alfredo
[3
,4
]
Sanyal, Debasish
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KPC Med Coll & Hosp, Dept Psychiat, Kolkata, IndiaIPGMER, Bangur Inst Neurosci, Kolkata, India
Sanyal, Debasish
[5
]
Ray, Biman Kanti
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IPGMER, Bangur Inst Neurosci, Kolkata, India
SSKM Hosp Kolkata, Kolkata, IndiaIPGMER, Bangur Inst Neurosci, Kolkata, India
Ray, Biman Kanti
[1
,2
]
机构:
[1] IPGMER, Bangur Inst Neurosci, Kolkata, India
[2] SSKM Hosp Kolkata, Kolkata, India
[3] IM Sechenov First Moscow State Med Univ, Inst Linguist & Intercultural Commun, Moscow, Russia
[4] Albizu Univ, Psychol Doctoral Program, Miami, FL 33172 USA
[5] KPC Med Coll & Hosp, Dept Psychiat, Kolkata, India
One hundred and sixty-three aphasia patients underwent initial language examination during the first week following stroke and 90-100 days post-stroke. Demographic factors (age, gender, and number of years of formal education), lesion-related factors (type of stroke, lesion volume, cortical versus sub-cortical location, and site of lesion), as well as initial severity and type of aphasia were taken as independent variables while aphasia recovery (in terms of no change versus change to a milder type or complete recovery) was the dependent variable. Chi square automatic interaction detection (CHAID) was performed to assess predictor importance and formulate a predictive model for aphasia recovery. Initial severity of aphasia followed by initial aphasia symptomatology was found to be the most important factor determining aphasia recovery. Age and gender had some importance. Lesion-related factors did not reach statistical significance as independent determinant of aphasia recovery. The predictive value of the model was 66.87%