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Utility of an algorithm predicting nasal continuous positive airway pressure sophia e schiza., bouloukaki izolde, tzanakis nikos, ekonomidou foteini, n.m. siafakas sleep disorders unit, dept. of thoracic medicine, medical school, university of crete, heraklion, greece.
ABSTINENCE RATES AND PREDICTORS OF OUTCOME OF
Izolde Bouloukaki, Despoina Moraitaki, Kostantinos Karagiannis, Nikolaos Siafakas,
Dept of Thoracic Medicine, University Of Crete, Heraklion, Crete, Greece
•Smoking cessation effectively decreases the incidence
•Two years after quit day, 285 (38%) were ex
of a number of major diseases, such as cardiovascular
smokers, while 476 (62%) were current smokers.
diseases and lung cancer, even at a relatively old age.
•Of the non-smokers 26% received nicotine
• However, even though about 70% of smokers would like
replacement therapy, 57% bupropion and 11% both
•Thus, a better understanding of the factors
•Subjects receiving bupropion exhibited higher
contributing to smoking cessation is needed in order to
abstinence rate than nicotine replacement therapy
identify smokers who might need more intensive
•The duration of treatment has been shown to
affect the quit rate in a statistical significant way
The aim of the study was to evaluate
factors associated with smoking cessation, in patients
•Highly educated persons had higher success rates
referred to our smoking cessation clinic.
•The quitting rate, was significantly associated with
the compliance, as expressed by visit numbers
•1288 smokers mean age 44 yrs., visited and started
therapy in the Outpatient Clinic for Smoking Cessation.
Table 2. Comparison between smokers and non
• They followed for a total period of 2 years October
smokers two years after t
after the quit day.
•Each smoker was interviewed to register
sociodemographic data, smoking behaviour, age started
smoking and nicotine dependence using the Fagerstrom
•All individuals participate in the same behavioural
therapy program and, according to the degree of
dependence (Fagerstrom test), received nicotine
Age started smoking
•A random sample of 761 (465 males and 295 females)
out of the 1288 interviewed by telephone about their
current and former smoking habits as well as about their
Nicotine patch plus
Table 1: Patient Characteristics
Identification of parameters that predict
•match smokers with a treatment that is more likely
•identify smokers who might need more intensive
1. Grandes G, Cortada JM, Arantza A and Laka JP. Predictors of long-term outcome of a smoking cessation programme in primary care.
2. Boury ML, Buurma H and Egberts CG. Determinants for successful smoking cessation with bupropion in daily practice. Pharm World Sci
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