Analysis on risk factors for post-stroke emotional incontinence

Xiao-chun ZHANG, Xing-yun YUAN, Yu-rong ZHANG, Le ZHANG, Xiao-li LIU, Juan-li ZHANG, Guo-gang LUO

Abstract


Objective To investigate the occurrence rate and related risk factors for post-stroke emotional incontinence (PSEI).  Methods The clinical data [sex, age, body mass index (BMI), education, marital status, medical history (hypertension, heart disease, diabetes, hyperlipemia, smoking and drinking) and family history of stroke] of 162 stroke patients were recorded. Serum homocysteine (Hcy) level was examined. Head CT and/or MRI were used to indicate stroke subtype, site of lesion and number of lesion. Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-Ⅴ) Chinese version and Hamilton Depression Rating Scale-17 Items (HAMD-17) were used to evaluate the degree of depression. House diagnostic standard was used to diagnose PSEI. Univariate and multivariate backward Logistic regression analysis was used to screen related risk factor for PSEI. Spearman rank correlation analysis was used to discuss the correlation between PSEI and post-stroke depression (PSD).  Results Among 162 stroke patients, 12 cases were diagnosed as PSEI (7.41% ). The ratio of age < 60 years in PSEI group was significantly higher than non-PSEI group (P = 0.045). The ratio of smoking in PSEI group was significantly lower than non-PSEI group (P = 0.036). Univariate and multivariate backward Logistic regression analysis showed age < 60 years was independent risk factor for PSEI (OR = 4.000, 95%CI: 1.149-13.924; P = 0.029). Ten cases were combined with PSD in 12 PSEI patients, and the co-morbidity rate of PSEI and PSD was83.33%. Spearman rank correlation analysis showed PSEI was positively related to PSD (rs = 0.305, P = 0.000).  Conclusions PSEI is common affective disorder in stroke patients, which easily happens in patients under 60 years of age.

 

DOI: 10.3969/j.issn.1672-6731.2017.12.010


Keywords


Stroke; Affective disorders; Depression; Risk factors; Regression analysis

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