Dataset Information

Assessing recent smoking status by measuring exhaled carbon monoxide levels.

ABSTRACT:

Background

Cigarette smoke causes both acute and chronic changes of the immune system. Excluding recent smoking is therefore important in clinical studies with chronic inflammation as primary focus. In this context, it is common to ask the study subjects to refrain from smoking within a certain time frame prior to sampling. The duration of the smoking cessation is typically from midnight the evening before, i.e. 8 hours from sampling. As it has been shown that a proportion of current smokers underestimates or denies smoking, objective assessment of recent smoking status is of great importance. Our aim was to extend the use of exhaled carbon monoxide (CO(breath)), a well-established method for separating smokers from non-smokers, to assessment of recent smoking status.

Methods and findings

The time course of CO(breath) decline was investigated by hourly measurements during one day on non-symptomatic smokers and non-smokers (6+7), as well as by measurements on three separate occasions on non-smokers (n?=?29), smokers with normal lung function (n?=?38) and smokers with chronic obstructive pulmonary disease (n?=?19) participating in a clinical study. We used regression analysis to model the decay, and receiver operator characteristics analysis for evaluation of model performance. The decline was described as a mono-exponential decay (r(2)?=?0.7) with a half-life of 4.5 hours. CO decline rate depends on initial CO levels, and by necessity a generic cut-off is therefore crude as initial CO(breath) varies a lot between individuals. However, a cut-off level of 12 ppm could classify recent smokers from smokers having refrained from smoking during the past 8 hours with a specificity of 94% and a sensitivity of 90%.

Conclusions

We hereby describe a method for classifying recent smokers from smokers having refrained from smoking for >8 hours that is easy to implement in a clinical setting.

SUBMITTER: Sandberg A

PROVIDER: S-EPMC3241681 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Publications

Assessing recent smoking status by measuring exhaled carbon monoxide levels.

Sandberg AnnSofi A Sköld C Magnus CM Grunewald Johan J Eklund Anders A Wheelock Åsa M ÅM

PloS one 20111216 12

<h4>Background</h4>Cigarette smoke causes both acute and chronic changes of the immune system. Excluding recent smoking is therefore important in clinical studies with chronic inflammation as primary focus. In this context, it is common to ask the study subjects to refrain from smoking within a certain time frame prior to sampling. The duration of the smoking cessation is typically from midnight the evening before, i.e. 8 hours from sampling. As it has been shown that a proportion of current smo ...[more]

PMID: 22194931

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Project description:ImportanceCigarette smoking is a risk factor for many perioperative complications, including surgical site infection (SSI). The duration of abstinence from smoking required to reduce this risk is unknown.ObjectivesTo evaluate if abstinence from smoking on the day of surgery is associated with a decreased frequency of SSI in patients who smoke cigarettes and to confirm that smoking is significantly independently associated with SSI when adjustment is made for potentially relevant covariates, such as body mass index.Design, setting, and participantsIn this observational, nested, matched case-control study, 2 analyses were performed at an academic referral center in the upper Midwest. Cases included all patients undergoing elective surgical procedures at Mayo Clinic, Rochester, Minnesota, between January 1, 2009, and July 31, 2014 (inclusive) who subsequently developed an SSI. Controls for both analyses were matched on age, sex, and type of surgery.ExposuresSmoking status and preoperative exhaled carbon monoxide level, assessed by nurses in the preoperative holding area. Patients were classified as smoking on the day of surgery if they self-reported smoking or if their preoperative exhaled carbon monoxide level was 10 ppm or higher.Main outcomes and measuresSurgical site infection after a surgical procedure at Mayo Clinic, Rochester, as identified by routine clinical surveillance using National Healthcare Safety Network criteria.ResultsOf the 6919 patients in the first analysis, 3282 (47%) were men and 3637 (53%) were women; median age (interquartile range) for control and SSI cases was 60 (48-70). Of the 392 patients in the second analysis, 182 (46%) were men and 210 (54%) were women; median age (interquartile range) for controls was 53 (45-49) and for SSI cases was 51 (45-60). During the study period, approximately 2% of surgical patients developed SSI annually. Available for the first analysis (evaluating the influence of current smoking status) were 2452 SSI cases matched to 4467 controls. The odds ratio for smoking and SSI was 1.51 (95% CI, 1.20-1.90; P < .001), which remained statistically significant after adjusting for covariates. In the second analysis (evaluating the influence of smoking on the day of surgery), there were 137 SSI cases matched to 255 controls. The odds ratio for smoking on the day of surgery and SSI was 1.96 (95% CI, 1.23-3.13; P < .001), which remained statistically significant after adjusting for covariates. Preoperative exhaled carbon monoxide level was not associated with the frequency of SSI, suggesting that the association between smoking on the day of surgery and SSI was not related to preoperative exhaled carbon monoxide levels.Conclusions and relevanceCurrent smoking is associated with the development of SSI, and smoking on the day of surgery is independently associated with the development of SSI. These data cannot distinguish whether abstinence per se reduces risk or whether it is associated with other factors that may be causative.

Dataset Information

Assessing recent smoking status by measuring exhaled carbon monoxide levels.

Background

Methods and findings

Conclusions

Publications

Assessing recent smoking status by measuring exhaled carbon monoxide levels.

Similar Datasets

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