ANALISIS FAKTOR RISIKO KEJADIAN TRANSIENT ISCHEMIC ATTACK (TIA) MENGGUNAKAN REGRESI LOGISTIK GANDA (Studi di RSUD Dr. Soetomo Surabaya)
Multivariate logistic regression was a logistic regression model used to analyze the relationship between dependent variable and independent variables, but dependent variable was dichotomy. This analysis was applied to case of TIA. TIA was a warning that stroke would occur in people who had TIA. Thi...
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| Format: | Theses and Dissertations NonPeerReviewed |
| Language: | Indonesian Indonesian |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://repository.unair.ac.id/39807/1/6%20abstract.pdf http://repository.unair.ac.id/39807/2/FKM.125-16%20Fad%20a.pdf http://repository.unair.ac.id/39807/ http://lib.unair.ac.id |
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| Institution: | Universitas Airlangga |
| Language: | Indonesian Indonesian |
| Summary: | Multivariate logistic regression was a logistic regression model used to analyze the relationship between dependent variable and independent variables, but dependent variable was dichotomy. This analysis was applied to case of TIA. TIA was a warning that stroke would occur in people who had TIA. This study was carried out to determine risk factors that affect case of TIA in Dr. Soetomo Regional Public Hospital Surabaya in 2012-2015 and the best multivariate logistic regression model.
Measurement in research subjects was conducted in the medical record. These measurement did not involved direct contact so the subjects were not disturbed during the research proces (observational research). Subjects were 90 inpatients, such as 30 patients of TIA and 90 patients of non TIA (case-control design). Measurement was conducted to obtain information of variables examined. Independent variables were sex, age, hypertension, dyslipidemia, diabetes mellitus, and obesity.
Result of simultaneous test showed that at least one variable that affected TIA (p = 0,000). Partial test showed that hypertension (p = 0,015; OR = 4,327), dyslipidemia (p = 0,000; OR = 10,455), and diabetes mellitus (p = 0,032; OR = 3,942) affected TIA (p < 0,05). This independent variables have contributed as much as 49% to TIA with prediction accuracy was 80%. Model obtained was fit (p > 0,05) and the best model was f(z) = 1/[1+e2,531-1,465(hipertensi)-2,347(dislipidemia)-1,372(diabetes)].
Multivariate logistic regression can be used to analyze risk factors of TIA in Dr. Soetomo Regional Public Hospital Surabaya in 2012-2015 with high prediction accuracy. Dyslipidemia was the highest risk of TIA so that needed Communication, Information, and Education of TIA for TIA prevention in patients who had dyslipidemia and stroke prevention in patients who had a history of TIA. |
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