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Demystifying Smoker's Paradox: A Propensity Score–Weighted Analysis in Patients Hospitalized With Acute Heart Failure

journal contribution
submitted on 2024-03-05, 11:06 and posted on 2024-03-05, 11:08 authored by Suhail A. Doi, Nazmul Islam, Kadhim Sulaiman, Alawi A. Alsheikh‐Ali, Rajvir Singh, Awad Al‐Qahtani, Nidal Asaad, Khalid F. AlHabib, Ibrahim Al‐Zakwani, Mohammed Al‐Jarallah, Wael AlMahmeed, Bassam Bulbanat, Nooshin Bazargani, Haitham Amin, Ahmed Al‐Motarreb, Husam AlFaleh, Prashanth Panduranga, Abdulla Shehab, Jassim Al Suwaidi, Amar M. Salam

Background

Smoker's paradox has been observed with several vascular disorders, yet there are limited data in patients with acute heart failure ( HF ). We examined the effects of smoking in patients with acute HF using data from a large multicenter registry. The objective was to determine if the design and analytic approach could explain the smoker's paradox in acute HF mortality.

Methods and Results

The data were sourced from the acute HF registry (Gulf CARE [Gulf Acute Heart Failure Registry]), a multicenter registry that recruited patients over 10 months admitted with a diagnosis of acute HF from 47 hospitals in 7 Middle Eastern countries. The association between smoking and mortality (in hospital) was examined using covariate adjustment, making use of mortality risk factors. A parallel analysis was performed using covariate balancing through propensity scores. Of 5005 patients hospitalized with acute HF , 1103 (22%) were current smokers. The in‐hospital mortality rates were significantly lower in current smoker's before (odds ratio, 0.71; 95% CI , 0.52–0.96) and more so after (odds ratio, 0.47; 95% CI , 0.31–0.70) covariate adjustment. With the propensity score–derived covariate balance, the smoking effect became much less certain (odds ratio, 0.63; 95% CI, 0.36–1.11).

Conclusions

The current study illustrates the fact that the smoker's paradox is likely to be a result of residual confounding as covariate adjustment may not resolve this if there are many competing prognostic confounders. In this situation, propensity score methods for covariate balancing seem preferable.

Clinical Trial Registration

URL : https://www.clinicaltrials.gov/ . Unique identifier: NCT 01467973.

Other Information

Published in: Journal of the American Heart Association
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1161/jaha.119.013056

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

Wolters Kluwer

Publication Year

  • 2019

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Qatar University
  • Qatar University Health - QU
  • College of Medicine - QU HEALTH
  • Hamad Medical Corporation
  • Weill Cornell Medical College in Qatar (-2015)

Methodology

The data were sourced from the acute HF registry (Gulf CARE [Gulf Acute Heart Failure Registry]), a multicenter registry that recruited patients over 10 months admitted with a diagnosis of acute HF from 47 hospitals in 7 Middle Eastern countries. The association between smoking and mortality (in hospital) was examined using covariate adjustment, making use of mortality risk factors. A parallel analysis was performed using covariate balancing through propensity scores. Of 5005 patients hospitalized with acute HF , 1103 (22%) were current smokers. The in‐hospital mortality rates were significantly lower in current smoker's before (odds ratio, 0.71; 95% CI , 0.52–0.96) and more so after (odds ratio, 0.47; 95% CI , 0.31–0.70) covariate adjustment. With the propensity score–derived covariate balance, the smoking effect became much less certain (odds ratio, 0.63; 95% CI, 0.36–1.11).

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