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Follow-up loss in smoking cessation consultation: can we predict and prevent it?
BACKGROUND: Cigarette smoking has a considerable health and economic burden in modern society, with increased risk of morbidity and mortality. Therefore, smoking cessation policies and medical treatments are essential. However, cessation rates are low and the abandonment of the consultation is commo...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107513/ https://www.ncbi.nlm.nih.gov/pubmed/34012582 http://dx.doi.org/10.21037/jtd-20-1832 |
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author | Cabrita, Bruno Miguel Oliveira Galego, Maria-Antónia Fernandes, Ana-Luísa Dias, Sara Correia, Sílvia Simão, Paula Ferreira, Jorge Amado, Joana |
author_facet | Cabrita, Bruno Miguel Oliveira Galego, Maria-Antónia Fernandes, Ana-Luísa Dias, Sara Correia, Sílvia Simão, Paula Ferreira, Jorge Amado, Joana |
author_sort | Cabrita, Bruno Miguel Oliveira |
collection | PubMed |
description | BACKGROUND: Cigarette smoking has a considerable health and economic burden in modern society, with increased risk of morbidity and mortality. Therefore, smoking cessation policies and medical treatments are essential. However, cessation rates are low and the abandonment of the consultation is common. The identification of characteristics that may predict adherence will help defining the best treatment strategy. This study aimed to identify predictors of follow-up loss in smoking cessation consultation. METHODS: We made a retrospective observational study, including a cohort of patients who started smoking cessation consultation (April-December 2018). Clinical data from consultations was collected and analyzed with IBM SPSS Statistics (SPSS, RRID:SCR_002865). RESULTS: A total of 175 patients was selected (41.1% female), with a mean age of 53±12 years. Eighty-five patients (48.6%) were discharged for abandonment. They had a median pack-year unit 38±36 (P=0.011), Fagerström and Richmond scores of 5±2 and 7±2, respectively. There was an association between women (P<0.001), younger age (P<0.001), depression/anxiety (P=0.023), lower smoking load (P=0.019), starting the treatment in the first appointment (P=0.004) and the abandonment of the consultation. In binary logistic regression, younger age (less than 50 years) (OR =4.39; 95% CI: 1.99–9.70), starting the treatment in the first appointment (OR =3.04; 95% CI: 1.44–6.42) and depression/anxiety (OR =2.30; 95% CI: 1.08–4.88) remained independent predictors of loss in follow-up. CONCLUSIONS: Women, younger age, depression/anxiety, lower smoking load and starting treatment in the first appointment are predictors of follow-up loss, so, these patients may benefit from more frequent evaluations and intensive cognitive approach. This study also raises awareness about the adequate timing to start pharmacological support for smoking cessation. |
format | Online Article Text |
id | pubmed-8107513 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-81075132021-05-18 Follow-up loss in smoking cessation consultation: can we predict and prevent it? Cabrita, Bruno Miguel Oliveira Galego, Maria-Antónia Fernandes, Ana-Luísa Dias, Sara Correia, Sílvia Simão, Paula Ferreira, Jorge Amado, Joana J Thorac Dis Original Article BACKGROUND: Cigarette smoking has a considerable health and economic burden in modern society, with increased risk of morbidity and mortality. Therefore, smoking cessation policies and medical treatments are essential. However, cessation rates are low and the abandonment of the consultation is common. The identification of characteristics that may predict adherence will help defining the best treatment strategy. This study aimed to identify predictors of follow-up loss in smoking cessation consultation. METHODS: We made a retrospective observational study, including a cohort of patients who started smoking cessation consultation (April-December 2018). Clinical data from consultations was collected and analyzed with IBM SPSS Statistics (SPSS, RRID:SCR_002865). RESULTS: A total of 175 patients was selected (41.1% female), with a mean age of 53±12 years. Eighty-five patients (48.6%) were discharged for abandonment. They had a median pack-year unit 38±36 (P=0.011), Fagerström and Richmond scores of 5±2 and 7±2, respectively. There was an association between women (P<0.001), younger age (P<0.001), depression/anxiety (P=0.023), lower smoking load (P=0.019), starting the treatment in the first appointment (P=0.004) and the abandonment of the consultation. In binary logistic regression, younger age (less than 50 years) (OR =4.39; 95% CI: 1.99–9.70), starting the treatment in the first appointment (OR =3.04; 95% CI: 1.44–6.42) and depression/anxiety (OR =2.30; 95% CI: 1.08–4.88) remained independent predictors of loss in follow-up. CONCLUSIONS: Women, younger age, depression/anxiety, lower smoking load and starting treatment in the first appointment are predictors of follow-up loss, so, these patients may benefit from more frequent evaluations and intensive cognitive approach. This study also raises awareness about the adequate timing to start pharmacological support for smoking cessation. AME Publishing Company 2021-04 /pmc/articles/PMC8107513/ /pubmed/34012582 http://dx.doi.org/10.21037/jtd-20-1832 Text en 2021 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Cabrita, Bruno Miguel Oliveira Galego, Maria-Antónia Fernandes, Ana-Luísa Dias, Sara Correia, Sílvia Simão, Paula Ferreira, Jorge Amado, Joana Follow-up loss in smoking cessation consultation: can we predict and prevent it? |
title | Follow-up loss in smoking cessation consultation: can we predict and prevent it? |
title_full | Follow-up loss in smoking cessation consultation: can we predict and prevent it? |
title_fullStr | Follow-up loss in smoking cessation consultation: can we predict and prevent it? |
title_full_unstemmed | Follow-up loss in smoking cessation consultation: can we predict and prevent it? |
title_short | Follow-up loss in smoking cessation consultation: can we predict and prevent it? |
title_sort | follow-up loss in smoking cessation consultation: can we predict and prevent it? |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8107513/ https://www.ncbi.nlm.nih.gov/pubmed/34012582 http://dx.doi.org/10.21037/jtd-20-1832 |
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