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Journal of Southern Medical University ; (12): 130-136, 2022.
Article in Chinese | WPRIM | ID: wpr-936294


OBJECTIVE@#To explore the risk factors for recurrence in first-episode ischemic stroke survivors and establish a model for predicting stroke recurrence using a nomogram.@*METHODS@#We collected the data from a total of 821 first-episode ischemic stroke survivors admitted in the Department of Neurology, West China Hospital, Sichuan University from January, 2010 to December, 2018. R software was used for random sampling of the patients, and 70% of the patients were included in the training set to establish the prediction model and 30% were included in the validation set. Cox proportional risk regression model was used to analyze the factors affecting stroke recurrence, and R software rms package was used to construct the histogram and establish the visual prediction model. C-index and calibration curve were used to evaluate the performance of the model for predicting stroke occurrence.@*RESULTS@#Among the 821 survivors, the recurrence rate was 16.81% at 3 years and 19.98% at 5 years. Multivariate analysis of the training set by Cox regression model showed that an age over 65 years (HR= 2.596, P=0.024), an age of 45-64 years (HR=2.510, P=0.006), a mRS score beyond 3 (HR=2.284, P=0.004) and a history of coronary heart disease (HR=1.353, P=0.034) were all risk factors for stroke recurrence. The C-indexes of the nomogram for the 3-and 5-year relapse prediction model were 0.640 and 0.671, respectively.@*CONCLUSION@#Age, mRS score and peripheral vascular disease are the factors affecting stroke recurrence in first-episode ischemic stroke survivors, and the nomogram has a high discrimination and predictive power for predicting ischemic stroke recurrence.

Aged , Humans , Middle Aged , Ischemic Stroke , Nomograms , Prognosis , Proportional Hazards Models , Retrospective Studies , Risk Factors , Stroke
Chinese Journal of Preventive Medicine ; (12): 158-162, 2011.
Article in Chinese | WPRIM | ID: wpr-349864


<p><b>OBJECTIVE</b>To understand the mental intervention service system responsiveness.</p><p><b>METHODS</b>A stratified, multi-stage random cluster sampling method was used, and a total of 211 residents in the central earthquake area were face to face interviewed by using the evaluating questionnaire of mental intervention service system responsiveness (including confidentiality, autonomy, prompt attention and so on, in sum of eight indicators). Analytic hierarchy process method was used to determine the weight of each index, carrying out a single index evaluation and fuzzy comprehensive evaluation on the mental intervention service system responsiveness, and using Spearman rank correlation and Binary logistic regression model to analyze the relationship of total satisfaction of mental intervention with each index.</p><p><b>RESULTS</b>The dignity and confidentiality indicators were higher weight and rating. Prompt attention and the autonomy indicators were higher weight but lower rating, while surroundings and choice of providers indicators were lower weight and rating. It was also found that communication and social support network indicators were lower weight but higher rating. The overall assessment of mental intervention service system responsiveness ranged between "good" and "very good". All rank correlation coefficients of the indicators and the total satisfaction of mental interventions were significant (r(s) = 0.186 - 0.362, P < 0.05), except for confidentiality. The logistic regression analysis showed that the main factors of the individual variables influencing the total satisfaction were dignity (adjusted OR = 3.047, P < 0.001), surroundings (adjusted OR = 1.619, P = 0.019), and social support network (adjusted OR = 1.527, P = 0.005).</p><p><b>CONCLUSION</b>The overall assessment of mental intervention service system responsiveness was high. Mental interventions should be taken positive and effective measures to improve the prompt attention, autonomy, the choice of providers and service environment.</p>

Adolescent , Adult , Aged , Female , Humans , Male , Middle Aged , Young Adult , China , Disasters , Earthquakes , Mental Health Services , Outcome Assessment, Health Care , Patient Satisfaction , Quality Control , Surveys and Questionnaires