Analisis Regresi Logistik Biner pada Kejadian Transient Ischemic Attack (Tia) di RSUD Dr. Soetomo Surabaya

Adelia Rahma Fadhilah, Hari Basuki Notobroto

= http://dx.doi.org/10.20473/jbk.v5i2.2016.157-165
Abstract views = 84 times | views = 77 times

Abstract


Analysis of the infl uence of risk factors aims to describe the unidirectional relationship between risk factors to an
incident or a spesifi c disease, one of which is binary logistic regression. This analysis is applied to case of TIA
because TIA is a warning that stroke will occur. This study was carried out to determine risk factors that aff ect case
of TIA in Dr. Soetomo Regional Public Hospital Surabaya in 2012-2015 and the best binary logistic regression
model. This study was an observational and case control study. Subjects were 90 inpatients at nerve division.
Data were collected by observing the patient’s card status to get information of variables examined. Independent
variables were hypertension, dyslipidemia, and diabetes mellitus. Result of simultaneous test showed that at
least one variable that aff ected 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) aff ected TIA (p < 0.05).
This independent variables have contributed as much as 49% to TIA with prediction accuracy was 67%. Model
obtained was fi t (p > 0.05). Binary 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. Patients with dyslipidemia have
the highest risk of TIA. Hypertension or diabetes mellitus was also signifi cant risk factor of TIA.

Keywords


binary logistic regression, TIA, risk factors

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References


Agresti, A. 1990. Categorical Data Analysis. New

York: John Wiley and Sons, Inc.

Anderson, D. et al. 2012. Health Care Guideline:

Diagnosis and Initial Treatment of Ischemic

Stroke. 10th ed. Bloomington: Institute for

Clinical Systems Improvement.

Chest Heart and Stroke Scotland. 2014.

Understanding Transient Ischemic Attack

(T.I.A.) and Minor Stroke. Scotland: Offi ce of

the Scottish Charity Regulator.

Ellis, H., Ahmed, T., dan Khanna, P. 2011. Life

After Stroke and Transient Ischemic Attack.

Abergavenny, Gerimed: 413–416.

Fitrianty, A., Delbra, Wardhani, N.W.S., dan

Soehono, L.A. 2013. Ketepatan Klasifi kasi

dengan Analisis Regresi Logistik dan

Multivariate Regression Splines (MARS)

pada Data dengan Peubah Respons Biner.

Malang: Jurusan Matematika Fakultas MIPA.

Universitas Brawijaya.

Haloho, O., Sembiring, P., dan Manurung, A.

Penerapan Analisis Regresi Logistik

pada Pemakaian Alat Kontrasepsi Wanita.

Jurnal Universitas Sumatera Utara, 1(1):

pp. 51–61.

Hayati, E., 2002. Analisis Regresi Logistik

untuk Mengetahui Faktor-Faktor yang

Mempengaruhi Frekuensi Kedatangan

Pelanggan di Pusat Perbelanjaan “X”.

Lamongan: Fakultas Ekonomi. Universitas

Islam Lamongan.

Heart and Stroke Foundation. 2016. Understanding

Transient Ischemic Attack (TIA). Canada.

CAT17810323.

Hosmer, D.W. dan Lemeshow, S. 2000. Applied

Logistic Regression, John Wiley and Sons,

New York.

Howard, G. et al. 1994. A Prospective Reevaluation

of Transient Ischemic Attacks As a Risk

Factor for Death and Fatal or Nonfatal

Cardiovascular Events, Stroke, 25: 342–345.

Tersedia di: < http://stroke.ahajourmas.org/

content/25/2/342> [diakses tanggal 12 Mei

.

Indra, R. 2009. Faktor-faktor yang Memengaruhi

Risiko Penyebab Penderita Kanker Payudara

dengan Menggunakan Pendekatan Regresi

Logistik. Surabaya: Jurusan Statistika

Fakultas MIPA. Institut Teknologi Sepuluh

November.

Junaidi, I. 2011. Stroke Waspadai Ancamannya.

Yogyakarta: Penerbit Andi.

Kim, J.S., and Dailey, R.J. 2008. Biostatistic

for Oral Healthcare. USA: Blackwell

Munksgaard.

Kuntoro. 2009. Dasar Filosofis Metodologi

Penelitian. Surabaya: Pustaka Melati.

Kurniasari, L., Sumarminingsih, E., dan Solimun.

Permodelan Regresi Logistik dan Regresi

Probit pada Peubah Respon Multinomial.

Malang: Jurusan Matematika Fakultas MIPA.

Universitas Brawijaya.

Pendlebury, S.T., Giles, M.F., dan Rothwell,

P.M., Cambridge University Press. 2008.

Epidemiology, Risk Factors, Pathophysiology

and Causes of Transient Ischemic Attacks and

Stroke. 978-0-521-73512-4.

Purwoto, A. 2007. Panduan Laboratorium

Statistik Inferensial. Jakarta: Grasindo

Ringleb, P.A. et al., 2011. Chapter 9: Ischaemic

Stroke and Transient Ischaemic Attack.

European Handbook of Neurological

Management, 1(2): 101–158.

Sari, V.N., Sumarminingsih, E., dan Bernadetha,

M. 2010. Pemilihan Model Regresi Logistik

Multinomial dan Ordinal Terbaik berdasarkan

R2 MC. Fadden. Malang: Jurusan Matematika

Fakultas MIPA. Universitas Brawijaya.

Siket, M.S., Ediow, J. 2013. Transient Ischemic

Attack: An Evidence-Based Update.

Emergency Medicine Practice, 15(1).

Simmons, B.B., Cirignano, B., dan Gadegbeku,

A.B. 2012. Transient Ischemic Attack: Part I.

Diagnosis and Evaluation. American Family

Physician, 86(6): 521–526.

Simmons, B.B., Cirignano, B., dan Gadegbeku,

A.B. 2012. Transient Ischemic Attack: Part

II. Risk Factor Modifi cation and Treatment.

American Family Physician, 86(6): 527–532.

Sinaga, M., Sengkey, L., Angliadi, E. 2014.

Gambaran Fungsi Kognitif pada Pasien Stroke

Non Hemoragik Menggunakan Mini-Mental

State Examination (MMSE). e-Clinic, 2(2).

Sirimarco, G. et al. 2011. Atherogenic

Dyslipidemia in Patients With Transient

Ischemic Attack. Stroke, 42: 2131–2137.

Tersedia di: <http://stroke. ahajourmas.

o r g / c o n t e n t / s u p p l / 2 0 1 1 / 0 7 / 0 7 /

STROKEAHA.110.609727.DCO.html>

[diakses tanggal 24 Mei 2016].

Sorganvi, V., Kulkarni, M.S., Udgiri, R., Kadeli,

D., Atharga, S. 2014. Risk Factors For

Ischemic Stroke–A Case Control Study.

International Journal of Advanced Biological

Research, 4(1): 9–12.

Sudoyo, A.W. dkk. 2009. Buku Ajar Ilmu Penyakit

Dalam. Edisi V, Jilid III. Jakarta: Pusat

Penerbitan Ilmu Penyakit Dalam.

Susilo, E., Islamiyati, A., AF., Muh. Saleh. 2014.

Model Regresi Logistik Biner dengan Metode

Penalized Maximum Likelihood.

Usman, H., Akbar, R.P.S. 2006. Pengantar

Statistika. Edisi 2. Jakarta: PT. Bumi Aksara.

Utomo, S. 2009. Model Regresi Logistik untuk

Menunjukkan Pengaruh Pendapatan per

Kapita, Tingkat Pendidikan, dan Status

Pekerjaan terhadap Status Gizi Masyarakat

Kota Surakarta. Skripsi. Universitas Sebelas

Maret.

Widhiarso, W. 2010. Berkenalan dengan Metode-

Metode Analisis Regresi melalui SPSS.

Yogyakarta: Fakultas Psikologi UGM.

Widiarta, I.B.P., Wardana, I.G.N. 2011. Analisis

Pemilihan Moda dengan Regresi Logistik

pada Rencana Koridor Trayek Trans Sarbagita.

Jurnal Ilmiah Teknik Sipil, 15(2).


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