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BMJ Open
Tobacco stained fingers: a clue for smoking related disease
or harmful alcohol use? A case-control study.
Journal:
BMJ Open
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Manuscript ID:
Article Type:
Date Submitted by the Author:
Complete List of Authors:
bmjopen-2013-003304
Research
27-May-2013
Secondary Subject Heading:
Addiction, Respiratory medicine, Cardiovascular medicine, Diagnostics
INTERNAL MEDICINE, Cardiology < INTERNAL MEDICINE, Thoracic
medicine < INTERNAL MEDICINE, Adult oncology < ONCOLOGY,
PREVENTIVE MEDICINE, Substance misuse < PSYCHIATRY
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Keywords:
Smoking and tobacco
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<b>Primary Subject
Heading</b>:
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John, Gregor; Geneva University Hospitals (HUG), Internal Medicine
Pasche, Séphora; Geneva University Hospitals (HUG), Department of
Community Medicine, Primary Care and Emergency Medicine
Rothen, Nicole; Bern University hospital, Internal Medicine
Charmoy, Alexia; Lausanne University Hospital (CHUV), Anaesthesiology
Delhumeau-Cartier, Cecile; Geneva University Hospitals (HUG), Infectious
disease
Genne, Daniel; HNE La ChauxdeFonds, Internal Medicine
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For peer review only - http://bmjopen.bmj.com/site/about/guidelines.xhtml
Page 1 of 24
BMJ Open
TOBACCO STAINED FINGERS: A CLUE FOR SMOKING RELATED
DISEASE OR HARMFUL ALCOHOL USE? A CASE-CONTROL
STUDY.
Authors: During the study, except Cécile Delhumeau-Cartier*, all authors were working in
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the Department of Internal Medicine, Hôpitaux Neuchâtelois, La Chaux-de-Fonds,
Switzerland.
Gregor John, MD (correspondence to and requests for reprints); Department of Internal
medicine, Geneva University Hospitals (HUG), Gabrielle-Perret-Gentil 4, CH-1205 Geneva,
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Switzerland, Phone number: 0041 79 553 43 08, [email protected] (may be
published).
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Sephora Pasche, MD; Department of Community Medicine, Primary Care and Emergency
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Medicine, Geneva University Hospitals (HUG), Geneva, Switzerland; [email protected]
Nicole Rothen, MD; -Department of Internal Medicine, Bern University hospital, Bern,
Switzerland; [email protected]
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Alexia Charmoy, MD; Department of Anaesthesiology, Lausanne University Hospital
(CHUV), Lausanne, Switzerland, [email protected]
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Cécile Delhumeau-Cartier*, PhD, statistician; Department of Internal Medicine, Geneva
University Hospitals (HUG), Geneva, Switzerland; [email protected]
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Daniel Genne, Professor; Department of Internal Medicine, Hôpitaux Neuchâtelois, La
Chaux-de-Fonds, Switzerland; [email protected]
Key words (MeSh) : Smoking; Alcohol Drinking; Physical examination; Pulmonary Disease,
Chronic Obstructive; cardiovascular disease.
Word count: Abstract: 253, Article: 2405
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ABSTRACT
Objective: Tobacco stain on fingers is frequent. However, there is scarce description of this
clinical sign. We aimed to explore tobacco stain on fingers as a marker of tobacco related
disease, or of harmful alcohol use, independent of cumulative tobacco exposure.
Design: Case-control study
Setting: A Swiss community hospital of 180 beds.
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Participants: 49 adults presenting tobacco-tars staining on fingers were matched to 49
control smokers by age, gender, height, and pack-year.
Outcome measures: Documented smoking related carcinoma, ischemic heart disease,
peripheral arterial disease, stroke, and chronic obstructive pulmonary disease (COPD) also
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determined by lung function, were compared between groups. Association between harmful
alcohol use, mental disorders, or unemployment, and tar-staining was adjusted for smoking
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behaviour through conditional logistic regression.
Results: Overall cigarette related disease was high in the case group (84%), and
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symptomatic peripheral arterial disease was more frequent compared to controls (OR 3.5,
CI95% 1.1-14.6). Smoking-related carcinoma (OR 1.5, CI95% 0.5-5.1), ischemic heart
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disease (OR 0.8, CI95% 0.4-2.3), stroke (OR 0.5, CI95% 0.1-3.5), and COPD (OR 2.2,
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CI95% 0.7-8.1) were not statistically different to control smokers. Harmful alcohol use was
strongly associated with stains and this association persists after adjustment for smoking
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unfiltered cigarettes, smoking more than one pack of cigarette in a day, and age at smoking
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onset (adjusted OR 4.6, CI95% 1.2-17.2). Mental disorders and unemployment were not
statistically significant.
Conclusions: Tobacco-tar stained fingers seem to identify high-risk smokers due to the
tobacco exposure, rather than a specific increased susceptibility. Harmful alcohol use should
be explored among these patients.
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ARTICLE SUMMARY
Article focus
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Identification of smokers at high risk of smoking related disease could impact their
management.
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A deeper puff could result in higher tar deposition on skin and greater inhalation of
tobacco, putting the lung and distant organs at increased health hazard
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Apart from cigarette characteristics, behavioural and environmental factors may be
important in stain development.
Key messages
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Tobacco-tar stained fingers give clue for a tobacco related conditions four times out
of five.
However, tobacco-tar stained fingers seem to identify high-risk smokers due to the
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tobacco exposure, rather than a specific increased susceptibility
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The study suggests a link between this tar-stained fingers and addictive behaviour or
concomitant high alcohol consumption that should be taken into account in smoking
cessation and prevention programs.
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Strengths and limitations of this study
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This case-control study explores an easily identifiable and frequent clinical sign
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among smokers and appreciates the additional risk for health due to tar deposition
(influenced by puffing or cigarettes characteristics) not included in the usual measure
of tobacco exposure (PY).
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Diagnoses were obtained from medical records or from patients self-reporting, subject
to recall bias. Problematic alcohol consumption was not measured with established
instruments (e.g. AUDIT). The sample size was small.
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INTRODUCTION
"The yellow finger stain is an emblem of deeper degradation and enslavement than the ball
and chain."
Henry Ford, The Case Against the Little White Slaver (Detroit: 1914)
Tobacco use is the leading cause of preventable death around the world. The 2011 World
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Health Organization report on the global tobacco epidemic predicted that if current trends
persist, more than eight million people worldwide will die from tobacco related disease each
year by 2030.[1] Although cigarette smoking is by far the most common risk factor for chronic
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obstructive pulmonary disease (COPD), is strongly associated with cardiovascular disease,
and is responsible for 30% of all cancer deaths, additional factors are involved in determining
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each individual’s susceptibility to tobacco related disease.[2-3] Identifying smokers at higher
risk of developing disease could improve their management and screening programs.[4]
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Smoking has been linked to many skin conditions for more than 150 years and evidence
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exist that skin involvement might be a conspicuous marker of other tobacco related
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disease.[5] For example, smoking related wrinkles have been associated with a decrease in
lung function independent of tobacco exposure.[6] The “yellow rounded digit” and “Harlequin
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nail” signs are two other simple clinical signs which aid the diagnosis of health conditions.[7-
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8] The former, characterised by fingers that are both tobacco-stained and clubbed, raises
suspicion of lung carcinoma. The latter is seen after acute cessation of cigarette
consumption resulting in a bi-colour nail (the distal end is cigarette stained contrasting the
newly growing proximal part) and is a reliable marker of concurrent disease. We
hypothesised that tar deposition itself (figure 1) could be a marker of tobacco related disease
independent of cumulative tobacco exposure. A deeper puff could result in higher tar
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deposition on skin and greater inhalation of tobacco, putting the lung and distant organs at
increased health hazard.
Tobacco-stains on fingers are commonly seen among smokers but there is scarce
description of this phenomenon. Apart from cigarette characteristics, behavioural and
environmental factors may be important in stain development. Epidemiologic studies
worldwide show higher rate of smoking among people suffering from mental or substance
use disorders.[9-10] Yellow stained fingers often observed in psychiatric units and among
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young drug users (autopsy series) supports a possible association between those conditions
and tar deposition.[11-12]
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We conducted the present study to determine whether tar deposit is an independent marker
of tobacco related disease and to identify factors associated with stain development, such as
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alcohol consumption, psychiatric conditions, unemployment, and smoking habits.
METHODS
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Study design and population
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We performed a case-control study between March 2006 and January 2010 in a 180-bed
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community hospital in La Chaux-de-Fonds, Switzerland. Eligible patients were adult current
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smokers admitted to the departments of internal medicine or surgery, or the intensive care
unit, irrespective of diagnosis or cause of admission. We excluded patients unable to provide
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informed consent, those post thoracic surgery or suffering from an ear–nose–throat (ENT)
conditions which could prevent lung function testing, patients receiving palliative care, and
pregnant women. Cases were defined by presence of tobacco stains on their fingers, and
were reported to the study group by the medical team or identified by the group through
frequent screening. They were included consecutively to avoid selection bias. Controls were
selected randomly from the same population, to fulfil the matching criteria. All participants
provided written informed consent. Institutional Review Board approved the study.
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Measures and outcomes of interest
Four physicians dedicated to the study collected all information. The main investigator
checked data accuracy using the study information and medical charts. A single thirty-minute
standard interview was performed for each participant to obtain a medical history, a physical
exam, and to perform pulmonary function tests. Investigations were performed at least one
month after an exacerbation of a chronic pulmonary condition, pneumonia, or acute heart
failure. Forced expiratory volume in one second (FEV1) and the forced vital capacity (FVC)
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were assessed using Microloop spirometer (Micro Medical Limited, England).
Tobacco-related disease
A history of tobacco-related disease – ischemic stroke (haemorrhagic or cardio-embolic
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events excluded), coronary heart disease (CHD), peripheral arterial disease (PAD), tobacco-
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related carcinoma (lung, urinary tract, or ENT), and COPD- was obtained from the patient’s
interview and from past and current medical records, classified according to the International
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Statistical Classification of Diseases, tenth revision (ICD-10).[13] COPD was also assessed
on lung function, when FEV1/FVC was less than 70%.[14] We defined coronary heart disease
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(CHD) as a history of angina pectoris, myocardial infarction, coronary arterial bypass graft,
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arterial angioplasty, or known vessel obstruction of 50% or more. Leg pain associated with
ankle brachial ratio index less than 0.9 or a procedure for arterial insufficiency defined a
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peripheral arterial disease (PAD). We recorded coughing, sputum production, and the degree
of dyspnea according to the New York Heart Association classification (NYHA).[15]
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Factors for stains development:
We documented any mental disorders diagnosed according to DSM-IV criteria and
antidepressant, benzodiazepine, neuroleptic, or mood stabilizer use.[16] We considered
harmful alcohol use when high alcohol intake –more than fourteen standard drinks per week
for women and more than twenty-one standard drinks per week for men (140g and 210g of
alcohol respectively)- was associated with documented withdrawal, medical consequences
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(neurologic, cardiac, hepatic, or pancreatic), or erythrocyte macrocytosis (mean corpuscular
volume greater than 98 fl) not otherwise explained.[17]
Occupations were classified according to the six-class version of the National Statistics
Socio-Economic Classification.[18] Previous occupation was considered for retired
individuals. Smoking habits reviewed were: age at onset, number of packets smoked per
day, unfiltered, or low tar cigarettes, and attempts at smoking cessation.
Patients were questioned on the number of years the stains have been present, their
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tendency to extend, their impact on everyday life, and attempts to make them disappear. We
recorded the number and location of stains for each patient as well as the surface area in
centimetres squared of stain located on finger skin only. The intensity of all stains was
graded using a standardised visual scale from one to five depending on the colour (pale
yellow to intense brown).
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Statistical analysis
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We paired one control for every case, and matched them individually by age, gender, height,
and pack-years smoked (PY). Pairs were matched closely with up to ten percent difference
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for each continuous variable. We then compared the predicted value of FEV1 (according to
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height, age, and gender) of each pair to ensure a difference of <10%.[19] The PY was
calculated as the number of packs smoked in a day multiplied by the number of years spent
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smoking. When the consumption was irregular from day to day we used the mean of the
extremes as an estimate of the number of packs smoked daily. If the consumption was
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higher or lower for more than a year’s duration, the total cumulative PY was calculated as the
sum of the different PYs throughout life.
We calculated that 50 participants in each group would allow us to detect a threefold
increase of tobacco related disease in the cases group (odds ratio), using McNemar test with
a two-sided alpha of 5% and a power of 80%, if at least 30% of pairs are discordant. To
compare groups, we used McNemar test for binary variables and paired Wilcoxon test for
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continuous variables. Among the case group, we used Spearman rank correlation to test for
an association between measured FEV1 and stain characteristics.
Conditional logistic regression was used to assess the association between cigarette staining
and mental health condition, psychotropic medications, harmful alcohol use, occupational
categories, and smoking behaviours. We built a parsimonious multivariate model, guided by
the analyst, entering each potential variable one by one, starting with those strongly
associated and clinically relevant, and keeping only statistically significant and mutually
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adjusted variables in the final model. With about 50 events (cases) and a requested number
of 10-15 events per variable we expected a maximum of 4-5 variables in the final model.[20]
We performed post hoc sub-analyses excluding pairs in which controls notified finger/nail
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stains in the past. Since those analyses showed similar results, only results of the initial
analyses are shown.
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Analyses were performed on cases and controls with complete documented information.
Data analyses were perform by using STATA 10.1 (StataCorp LP, Texas, USA). This study
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received no external funding source and volunteers received no financial reward.
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RESULTS
Participants:
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Between March 2006 and December 2007, 4520 patients were admitted to the hospital, of
which 1127 were current smokers (25%). Among those current smokers, 63 (6%) presented
one or more tar staining on the hand. Nine refused to participate and five could not be
matched, resulting into 49 cases. The corresponding 49 controls were included between
February 2007 and January 2010. All participants were Caucasians (Table 1).
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For one participant stain characteristics were impossible to determine due to a peripheral
cyanosis at the time of examination. The 48 other cases possessed a total of 153 stains;
64% on nail and 36% on finger skin (Table 2). Among the controls, eleven (22%) reported
the presence of at least one stain on fingers within their lifetime but not at the time of the
study.
Tobacco related disease, and lung function test:
Although there was a slight increase in vascular disease, COPD, and smoking related cancer
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in the case group, the difference was not statistically significant (Table 3). Peripheral arterial
disease was more prevalent among the case group with 14/49 (29%) complaining of
claudication and 12/49 (24%) having undergone revascularization procedure compared to
5/49 (10%; p=0.049) and 2/49 (4%; p=0.006) respectively in the control group.
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Lung function tests were not available for three controls. Measured FEV1 was not statistically
different between groups. Thirteen cases (26%) and 11/46 (24%) controls had less than
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50% of expected FEV1. Stain number (r: 0.13, p=0.39), mean size (r: 0.24, p=0.25), and
median colour intensity (r: 0.22, p=0.13) had no influence on measured FEV1 among cases.
Factors associated with tar staining:
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Smoking more than one pack of cigarettes per day, smoking unfiltered cigarettes, having
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more cigarette breaks, harmful alcohol use, or being on psychotropic medication were all
associated with higher risk of tar staining in univariate analyses (Table 4). Use of low tar
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content cigarettes was less frequent among tobacco stain participants.
In a multivariate analysis, four factors remained significantly associated with stain: smoking
more than one pack per day, smoking unfiltered cigarettes, age at onset, and harmful alcohol
use. Adding more variables produced artificially high OR due to insufficient events-pervariable. These four factors accounted for 41% of variance (pseudo-R2) in the presence of
stains.
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DISCUSSION
Our case-control study explores an easily identifiable and frequent clinical sign among
smokers. A tar stained finger gives clue for a tobacco related conditions four times out of five.
Furthermore, this clinical sign is linked to harmful alcohol use. As far as we know this is the
first description of this particular category of smokers.
The design of the study appreciates the additional risk for health due to tar deposition
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(influenced by puffing or cigarettes characteristics) not included in the usual measure of
tobacco exposure (PY). Yet the high incidence of COPD, overall cardiovascular disease, and
tobacco-related carcinomas are not independently related to tar deposition. PAD, found in
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excess among finger stained individuals, might be due to an alpha error, related to the
sample size. Besides, similar lung function between case and control groups and the
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absence of relationship between FEV1 and stain characteristics among cases are consistent
with a lack of association between yellow fingers and obstructive lung disease. Thus yellow
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staining is rather a proxy of the consequences of tobacco: its presence in itself seems to
identify high-risk smokers due to the tobacco exposure, rather than a specific increased
susceptibility.
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Four variables mutually adjusted – smoking more than one pack of cigarette in a day or
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unfiltered cigarettes, age at smoking onset, and harmful alcohol use – could explain a
substantial part of stain development, even in individuals matched for characteristics that are
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probably linked to stains (pack-year, age, and gender). Our results suggest that staining is
influenced by the characteristics of cigarettes smoked and smoker’s behaviour. Indeed,
finger stained smokers seem to present a more severe addictive behaviour (high proportion
of harmful alcohol use, early age at smoking onset, high number of cigarettes smoked per
day, and few cigarette breaks). An industry-funded study concluded that psychological and
personality constructs were positively associated with depth of inhalation.[21] Apart from
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puffing characteristics, smoking the entirety of cigarettes, seen among addict individuals,
might also contribute to tar staining. Previous studies have shown that the proportion of
alcohol disorders increases with cigarette consumption, and that daily tobacco use increases
with the level of alcohol consumption.[22-23] Our study is the first to demonstrate an
association between harmful alcohol use and tar staining independent of the extent of
tobacco consumption. Alcohol consumption in itself could influence smoking behaviour,
which in turn impacts on tar deposition. Nil and colleagues reported increased puff volume
following consumption of 0.7 g/kg of ethanol.[24] This addictive behaviour and concomitant
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high alcohol consumption must be taken into account in tobacco cessation programs.
The study has several limitations. First, many diagnoses were obtained from medical records
or from patients self-reporting. Thus the study was dependent of the quality and
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completeness of medical charts and subject to recall bias. This assessment might also cover
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a specific fraction of mental disorders (those who seek professional help). Second, tobacco
dependence or problematic alcohol consumption were not measured with established
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instruments (e.g. AUDIT). “Harmful alcohol use” is not a standard definition and includes
MCV which has a low specificity. Furthermore, the observers were not blinded to the
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allocation (case vs. control) of the patients, which could influence clinical interview. However,
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the results are plausible, and future studies should used standard tools to confirm them.
Third, a lack of statistical power might have underestimated the effect of yellow fingers on
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study outcomes. Moreover, 22% of controls reported transient tar discoloration in the past,
which might have blurred the effect. However, tar deposition appears to be constant over
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time in the case group, and a transient finger staining could be a clinically insignificant event.
Finally, our observations are limited to the inpatient hospital setting and may have to be
confirmed in finger-stained patients seen outside this context.
In a world of growing technology and complicated diagnosis procedure, our work highlights
the importance of clinical assessment of smokers; an important message to transmit in
medical education. This costless and easy obtainable information should stress tobacco-
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related disease screening and reinforce smoking counselling. Harmful alcohol use should be
explored among these patients.
ACKNOWLEDGEMENTS
We gratefully acknowledge Sebastian Carballo, Fraser Easton and Andrew Stewardson for
their correction of the English manuscript.
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COMPETING INTERESTS
All authors declare: no support from any organisation for the submitted work; no financial
relationships with any organisations that might have an interest in the submitted work in the
previous three years, no other relationships or activities that could appear to have influenced
the submitted work.
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FUNDING
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This research received no specific grant from any funding agency in the public, commercial
or not-for-profit sectors
CONTRIBUTORSHIP
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We confirm that all authors have participated in conception and design, or analysis and
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interpretation of data, drafting the article or revising it critically for important intellectual
content:
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Drs John and Genné had full access to all the data in the study and take responsibility for the
integrity of the data and the accuracy of the data analysis. Study concept and design: John
and Genné. Acquisition of data: Pasche, Rothen, Charmoy, John. Analysis and interpretation
of data: Delhumeau-Cartier, John.Drafting of the manuscript: John. Critical revision of the
manuscript for important intellectual content: Delhumeau-Cartier, Pasche, Rothen, Charmoy
and Genné. Statistical analysis: Delhumeau-Cartier, John. Study supervision: Genné.
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DATA SHARING
The full dataset can be obtain by request to the corresponding author
REFERENCES:
1. World Health Organziation. Report on the global tobacco epidemic.
http://www.who.int/tobacco/global_report/2011/qanda/en/index.html, 2011. Date last
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update: september 2011. Last access date: november 2012.
2. Ezzati M, Lopez AD. Regional, disease specific patterns of smoking-attributable mortality
in 2000. Tob Control 2004;13(4):388-95.
3. Office of the Surgeon General. How tobacco smoke causes disease the biology and
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behavioral basis for smoking-attributable disease : a report of the Surgeon General. Dept.
of Health and Human Services, Public Health Service, 2010.
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http://www.surgeongeneral.gov/library/reports/tobaccosmoke/full_report.pdf.Last access
date: november 2012.
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4. Aberle DR, Adams AM, Berg CD, et al. Reduced lung-cancer mortality with low-dose
computed tomographic screening. N Engl J Med 2011;365:395-409.
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5. Solly S. Clinical lectures on paralysis. The Lancet 1856;63:669-71.
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6. Lange P, Schnohr P. The relationship between facial wrinkling and airflow obstruction. Int
J Dermatol 1994;33:123-6.
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7. Levine H. The yellow rounded digit: sign of the times. N Engl J Med 1968;279:660-1.
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8. Verghese A, Krish G, Howe D, Stonecipher M. The harlequin nail. A marker for smoking
cessation. Chest 1990;97:236-8.
9. Lawrence D, Mitrou F, Zubrick SR. Smoking and mental illness: results from population
surveys in Australia and the United States. BMC Public Health 2009;9:285.
10. Kalman D, Morissette SB, George TP. Co-morbidity of smoking in patients with
psychiatric and substance use disorders. Am J Addict 2005;14:106-23.
11. Thakurdas H. Smoking and Psychiatrc Patient. Br Med J 1963;388.
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12. Hafezi M, Bohnert M, Weinmann W, Pollak S. Prevalence of nicotine consumption in drug
deaths. Forensic Sci Int 2001;119(3):284-9.
13. World Health Organisation. International statistical classification of diseases and related
health problems. Instruction Manual v. 2: Tenth Revision. Geneva, Switzerland: World
Health Organisation 2004.
14. Global Initiative for Chronic Obstructive Lung Disease (GOLD), Global Strategy for the
Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease. ,
(2006). http://www.who.int/respiratory/copd/GOLD_WR_06.pdf. Last access date:
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november 2012.
15. The Criteria Committee of the New York Heart Association. Nomenclature and Criteria for
Dagnosis of Diseases of the Heart and Great Vessels. 9 ed. Boston, MA: Little, Brown,
1994.
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16. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders.
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4 ed. Washington, DC: American Psychiatric Association, 1994.
17. World Health Organziation. Lexicon of alcohol and drug terms published by the World
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Health Organization. http://www.who.int/substance_abuse/terminology/who_lexicon/en/.
Last access date: november 2012.
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18. The National Statistics Socio-economic Classification (NS-SEC rebased on the
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SOC2010), 2010. http://www.ons.gov.uk/ons/guide-method/classifications/currentstandard-classifications/soc2010/soc2010-volume-3-ns-sec--rebased-on-soc2010--usermanual/index.html. Last access date: november 2012.
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19. Hankinson JL, Odencrantz JR, Fedan KB. Spirometric reference values from a sample of
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the general U.S. population. Am J Respir Crit Care Med 1999;159:179-87.
20. Courvoisier DS, Combescure C, Agoritsas T, Gayet-Ageron A, Perneger TV.
Performance of logistic regression modeling: beyond the number of events per variable,
the role of data structure. J Clin Epidemiol 2011;64:993-1000.
21. Wood D, Wilkes E. Project Wheat - Part 1 Cluster Profiles of U.K. Male Smokers and
Their General Smoking Habits. Report No. Rd.1229-R., 1960.
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http://tobaccodocuments.org/product_design/1208809.html. Last access date: november
2012.
22. Friedman GD, Tekawa I, Klatsky AL, Sidney S, Armstrong MA. Alcohol drinking and
cigarette smoking: an exploration of the association in middle-aged men and women.
Drug Alcohol Depend 1991;27:283-90.
23. Dawson DA. Drinking as a risk factor for sustained smoking. Drug Alcohol Depend
2000;59:235-49.
24. Nil R, Buzzi R, Battig K. Effects of single doses of alcohol and caffeine on cigarette
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smoke puffing behavior. Pharmacol Biochem Behav 1984;20:583-90.
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Table 1 Baseline characteristics of the yellow-stained finger cases and their controls smokers. Values
are numbers (percentage) unless stated otherwise.
Variables
Cases (n=49)
Controls (n=49)
P value*
Matching
.65 †
59 (50 - 69)
62 (50 - 69)
Median (IQR) age (years)
Male
32 (65)
32 (65)
.99
.84 †
170 (165 - 175)
170 (165 - 177)
Median (IQR) height (centimetres)
‡
Median (IQR) pack years’ smoked
50 (40 - 61)
46 (38- 58)
.20 †
§
.60 †
3.2 (2.4 - 3.7)
3.3 (2.4 - 3.8)
Median (IQR) predicted FEV1 (litres)
||
Diagnosis category on admission
.48
15 (31)
11 (22)
Cardiovascular
Neurologic
7 (14)
6 (12)
.99
.79
6 (12)
8 (16)
Oncology
Infectious disease
5 (10)
5 (10)
.99
.99
5 (10)
6 (12)
Traumatology
Others
12 (24)
12 (24)
.99
*
McNemar and exact test unless stated otherwise
†
Paired Wilcoxon sign-rank test
‡
Number of packs smoked in a day multiplied by the number of years spent smoking or sum of the
different PYs throughout life if the consumption was higher or lower for more than a year’s duration
§
Predicted FEV1 calculated according to the third National Health and Nutrition Examination Survey
formula18
||
Category of main diagnosis claimed on the exit chart
FEV1: maximal forced expiratory volume in one second; PY: pack year unit; 95%CI: 95% confidence
interval; IQR: interquartile range 25-75%
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Table 2 Stains characteristics in cases. Value are numbers of cases
(percentage) unless stated otherwise
Stains characteristics
Cases N(%)*
Time of stain appearance (years)
15 (31)
1-4
5-9
2 (4)
31 (65)
≥10
Suffering due to the stain
3 (6)
23 (48)
Physical/chemical attempt to remove the stain
Variation over time (stain size or intensity)
18 (37)
3 (2-4)
Median (IQR) stains per cases
Median (IQR) nails stained
2 (1-2)
1 (0-3)
Median (IQR) stains on skin
Median (IQR) number of fingers discoloured per cases
3 (2-3)
25 (52)
First finger
45 (94)
Second finger
37 (77)
Third finger
1 (2)
Fourth finger
0 (0)
Fifth finger
1.9 (1.2-3.1)
Median (IQR) total skin area stained per cases (square
centimetre)
* Stain location, size, and colour intensity were impossible to determine for one
patient due to peripheral cyanosis at the time of examination. In another three
cases, the precise size of stains present on skin (five stains) was not
measured because of scant demarcation of the stain.
IQR: interquartile range 25-75%
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Table 3 Tobacco-related diseases and respiratory complaints. Values are numbers (percentage)
unless stated otherwise
Cases
Controls
N pairs OR(CI 95%)
p value*
Any tobacco-related disease †
41 (84)
39 (80)
49
1.3 (0.4-4.1)
.80
.83
0.9 (0.4-2.3)
49
26 (53)
25 (51)
Vascular disease
Coronary arterial disease ‡
17 (35)
19 (39)
49
0.8 (0.3-2.1)
.67
.69
0.5 (0.1-3.5)
49
6 (12)
4 (8)
Strokes/TIA§
Peripheral arterial disease ||
15 (31)
5 (10)
49
3.5 (1.1-14.6)
.03
.13
2.2 (0.7-8.1)
47
24 (49)
31 (63)
COPD
FEV1/FVC<70%
25 (51)
17 (37)
46
1.1 (0.4-3.5)
.11
.59
1.3 (0.4-4.7)
49
20 (41)
22 (45)
Clinical diagnosis ¶
**
Smoking-related Cancer
10 (20)
7 (14)
49
1.5 (0.5-5.1)
.61
Respiratory complaints
Coughing
32 (65)
25 (51)
49
2.2 (0.8-6.9)
.11
.28
1.8 (0.5-6.8)
49
15 (31)
19 (39)
Sputum production
††
‡‡
Median (IQR) grade dyspnoea
1 (1-2)
1 (0-2)
49
.14
§§
.004
4.5 (1.5-18.3)
49
10 (20)
24 (49)
Abnormal lung auscultation
Median (IQR) FEV1 (litre)
1.9 (1.3-2.5) 1.9 (1.4-2.6)
46
.49 ‡‡
*
McNemar exact test
†
At least one vascular disease, BPCO, or smoking-related carcinoma
‡
Self reporting angina pectoris, heart infarction, coronary arterial bypass graft, percutaneous
angioplasty or more than 50% vessel obstruction on coronary catheterization
§
Stroke or a transient neurologic symptoms except traumatic, haemorrhagic, or cardio embolic event
||
Self reporting symptomatic arterial claudication, ankle brachial ratio less than 0.9, or chirurgical or
radiological procedure for arterial insufficiency
¶
Self reporting or documented in the medical record
**
Carcinoma of lung, urinary tract, or head and neck
††
According to the New York Heart Association functional capacity classification
‡‡
§§
Wheezing or crackles
N pairs: number of pairs used in the analysis; OR: Odds ratio; FEV1: maximal forced expiratory
volume in one second; FVC: forced vital capacity; TIA: transient ischemic attack; COPD: chronic
obstructive pulmonary disease; CI95: 95% confidence interval; IQR: (interquartile range 25-75%)
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Table 4 Smoking behaviour, mental health, harmful alcohol use, and occupation categories in univariated and multivariated conditional regression model.
Values are numbers (percentage) unless stated otherwise
Univariated
Multivariated
Cases
Controls
OR (CI 95%)
p value
aOR (CI 95%)
p value
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Smoking habits
Median (IQR) age at beginning (years)
17 (15-20)
18 (15-20)
1.5 (1.0-2.4) *
.06
2.1 (1.1-4.0) *
.02
†
†
Median (IQR) number pack per day
1 (1-1.8)
1 (1-1.5)
3.9 (1.2-12.7)
.02
8.5 (1.9-38.4)
.006
Nb of brand median (IQR)
2 (1-3)
2 (2-3)
0.9 (0.7-1.2)
.39
Breaks median (IQR)
1 (0-2)
2 (1-3)
0.7 (0.5-1)
.04
Nb patients smoking unfiltered cigarettes
20 (41)
9 (18)
3.2 (1.2-8.7)
.02
4.2 (1.1-16.0)
.03
Nb patients smoking low tar cigarettes
7 (14)
17 (35)
0.3 (0.1-0.9)
.03
Mental health and harmful alcohol use
Harmful alcohol use §
25 (51)
10 (20)
3.5 (1.4-8.7)
.007
4.6 (1.2-17.2)
.02
Others psychiatric condition ||
22 (45)
14 (29)
1.7 (0.8-3.7)
.18
¶
On psychotropic medication
33 (67)
20 (41)
2.4 (1.1-5.3)
.02
Occupation
Unemployment
17 (35)
12 (24)
1.7 (0.7-4.3)
.26
*
For every two years younger than 22 years old
†
For every ten cigarettes more than 20
‡
For every ten years
§
More than fourteen drinks per week for women, more than twenty-one drinks per week for men associated with alcohol withdrawal, or documented
complications
||
According to the medical chart and DSMIV criteria
¶
Antidepressant, anxiolytic, neuroleptic, opioid, and antiepileptic (used as mood stabilizer) drug
OR (CI95%): Odds ratio (95% confidence interval); aOR: adjusted Odds ratio; IQR: (interquartile range 25-75%)
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Tar staining seen in a 70 years old men smoker (80PY).
626x534mm (72 x 72 DPI)
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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of case-control studies
Section/Topic
Title and abstract
Item
#
1
Recommendation
Reported on
page #
(a) Indicate the study’s design with a commonly used term in the title or the abstract
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(b) Provide in the abstract an informative and balanced summary of what was done and what was found
Introduction
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2
Background/rationale
2
Explain the scientific background and rationale for the investigation being reported
4,5
Objectives
3
State specific objectives, including any prespecified hypotheses
5
Study design
4
Present key elements of study design early in the paper
Setting
5
Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection
5-7
Participants
6
(a) Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for
5
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Methods
the choice of cases and controls
Variables
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5
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(b) For matched studies, give matching criteria and the number of controls per case
7
Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if
6,7
applicable
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Data sources/
measurement
8*
For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability
of assessment methods if there is more than one group
Bias
9
Describe any efforts to address potential sources of bias
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6
Study size
10
Explain how the study size was arrived at
Quantitative variables
11
Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why
7,8
7
Statistical methods
12
(a) Describe all statistical methods, including those used to control for confounding
7,8
(b) Describe any methods used to examine subgroups and interactions
8
(c) Explain how missing data were addressed
8
(d) If applicable, explain how matching of cases and controls was addressed
7
(e) Describe any sensitivity analyses
8
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Results
Participants
13*
(a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed
8
eligible, included in the study, completing follow-up, and analysed
Descriptive data
14*
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(b) Give reasons for non-participation at each stage
8
(c) Consider use of a flow diagram
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(a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential
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8, 15-18
confounders
(b) Indicate number of participants with missing data for each variable of interest
17
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Outcome data
15*
Report numbers in each exposure category, or summary measures of exposure
15-18
Main results
16
(a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence
interval). Make clear which confounders were adjusted for and why they were included
8-9, 15-18
(b) Report category boundaries when continuous variables were categorized
8-9, 15-18
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period
-
Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses
7
Other analyses
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Discussion
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Key results
18
Summarise key results with reference to study objectives
Limitations
19
Discuss limitations of the study, taking into account sources of potential bias or imprecision.
Discuss both direction and magnitude of any potential bias
11
Interpretation
20
Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar
11
studies, and other relevant evidence
Generalisability
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Discuss the generalisability (external validity) of the study results
22
Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the
present article is based
Other information
Funding
10
11
12
*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.
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Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE
checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.
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Tobacco stained fingers: a clue for smoking related disease
or harmful alcohol use? A case-control study.
Journal:
BMJ Open
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Manuscript ID:
Article Type:
Date Submitted by the Author:
Complete List of Authors:
bmjopen-2013-003304.R1
Research
28-Jul-2013
Secondary Subject Heading:
Addiction, Respiratory medicine, Cardiovascular medicine, Diagnostics
INTERNAL MEDICINE, Cardiology < INTERNAL MEDICINE, Thoracic
medicine < INTERNAL MEDICINE, Adult oncology < ONCOLOGY,
PREVENTIVE MEDICINE, Substance misuse < PSYCHIATRY
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Keywords:
Smoking and tobacco
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<b>Primary Subject
Heading</b>:
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John, Gregor; Geneva University Hospitals (HUG), Internal Medicine
Pasche, Séphora; Geneva University Hospitals (HUG), Department of
Community Medicine, Primary Care and Emergency Medicine
Rothen, Nicole; Bern University hospital, Internal Medicine
Charmoy, Alexia; Lausanne University Hospital (CHUV), Anaesthesiology
Delhumeau-Cartier, Cecile; Geneva University Hospitals (HUG), Infectious
disease
Genne, Daniel; HNE La ChauxdeFonds, Internal Medicine
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STUDY.
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Switzerland.
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ABSTRACT
disease independent of cumulative tobacco exposure, and find behavioural and
environmental characteristics associated with those stains.
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CI95% 1.1-14.6). Smoking-related carcinoma, ischemic heart disease, stroke, and COPD
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were not statistically different to control smokers. Harmful alcohol use was strongly
associated with stains and this association persists after adjustment for smoking unfiltered
on
cigarettes, smoking more than one pack of cigarette in a day, and age at smoking onset
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(adjusted OR 4.6, CI95% 1.2-17.2). Mental disorders and unemployment were not
Conclusions: Patients with tobacco-tar stained fingers frequently have cigarette related
disease, however statistically not more than control smokers matched for YP, except for
symptomatic peripheral arterial disease. This study suggests a link between stained fingers
and addictive behaviour or concomitant high alcohol consumption.
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ARTICLE SUMMARY
Article focus
•
management.
•
•
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Key messages
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Tobacco related diseases (defined as smoking related carcinoma, ischemic heart
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disease, peripheral arterial disease, stroke, or chronic obstructive pulmonary disease)
are frequent (84%) among patients with tobacco-tar stained fingers.
•
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concomitant high alcohol consumption.
•
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instruments (e.g. AUDIT). The sample size was small. This study included only
hospital population.
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INTRODUCTION
and chain."
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suspicion of lung carcinoma. The latter is seen after an acute illness that causes cessation of
cigarette consumption resulting in a bi-colour nail (the distal end is cigarette stained
contrasting the newly growing proximal part). We hypothesised that tar deposition itself
(figure 1) could be a marker of tobacco related disease independent of cumulative tobacco
exposure. A deeper puff could result in higher tar deposition on skin and greater inhalation of
tobacco, putting the lung and distant organs at increased health hazard.
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METHODS
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events excluded), coronary heart disease (CHD), peripheral arterial disease (PAD), tobaccorelated carcinoma (lung, urinary tract, or ENT), and COPD- was obtained from the patient’s
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We documented any mental disorders diagnosed according to Diagnostic and Statistical
Manual of Mental Disorders (DSM-IV) criteria and antidepressant, benzodiazepine,
neuroleptic, or mood stabilizer use.[16] We considered harmful alcohol use when high
alcohol intake –more than fourteen standard drinks per week for women and more than
twenty-one standard drinks per week for men (140g and 210g of alcohol respectively)- was
associated with documented withdrawal, medical consequences (neurologic, cardiac,
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hepatic, or pancreatic), or erythrocyte macrocytosis (mean corpuscular volume greater than
98 fl) not otherwise explained.[17]
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analyses are shown.
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RESULTS
Participants:
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study.
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stains.
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DISCUSSION
smokers. Tobacco related diseases (defined as smoking related carcinoma, ischemic heart
disease, peripheral arterial disease, stroke, and chronic obstructive pulmonary disease) are
frequent (84%) among patients with tobacco-tar stained fingers. Furthermore, this clinical
sign is linked to harmful alcohol use. As far as we know this is the first description of this
particular category of smokers.
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The design of the study appreciates the additional risk for health due to tar deposition not
included in the usual measure of tobacco exposure (PY). Stain may result from local pigment
ee
deposition secondary to high tar concentration in the skin-cigarette interface (influenced by
puffing or cigarettes characteristics), but higher concentration of nicotine (and other
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substances) smoked could affect stain removal by impaired skin repair. [21] Similarly,
nicotine has been shown to reduce blood flow in fingers and increase systemic blood
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pressure, a mechanism that could rationally explain the association of impaired stain removal
and peripheral arterial disease. [22, 23]
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Yet the high incidence of COPD, overall cardiovascular disease, and tobacco-related
carcinomas are not independently related to tar deposition. Besides, similar lung function
on
between case and control groups and the absence of relationship between FEV1 and stain
characteristics among cases are consistent with a lack of association between yellow fingers
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and obstructive lung disease. We believe that yellow staining identifies high-risk smokers due
to the tobacco exposure (PY), rather than a specific increased susceptibility (e.g. puffing
characteristics). Lack of an association with investigated tobacco related illnesses other than
symptomatic peripheral arterial disease, could however arise from insufficient power of the
study.
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following consumption of 0.7 g/kg of ethanol.[27] We believe that this addictive behaviour
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and concomitant high alcohol consumption could impact tobacco cessation programs,
although it has not been tested yet.
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Third, power size calculation was made for 50 pairs and only 49 could be found, because of
the restrictive matching criteria. Moreover, 22% of controls reported transient tar
discoloration in the past, which might have blurred the effect. However, tar deposition
appears to be constant over time in the case group, and a transient finger staining could be a
clinically insignificant event. Finally, our observations are limited to the inpatient hospital
setting and may have to be confirmed in finger-stained patients seen outside this context.
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medical education. This costless and easy obtainable information should stress tobaccorelated disease screening and reinforce smoking counselling. Harmful alcohol use should be
ACKNOWLEDGEMENTS
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COMPETING INTERESTS
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the submitted work.
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FUNDING
REFERENCES:
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http://www.who.int/tobacco/global_report/2011/qanda/en/index.html, 2011.
in 2000. Tob Control 2004;13(4):388-95.
3. United States. Public Health Service. Office of the Surgeon General. How tobacco smoke
causes disease the biology and behavioral basis for smoking-attributable disease : a
report of the Surgeon General. Rockville, MD
[Washington, D.C.]: U.S. Dept. of Health and Human Services, Public Health Service
For sale by the Supt. of Docs., U.S. G.P.O., 2010:1 online resource (xv, 706 p.).
4. Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, et al. Reduced
lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med
2011;365(5):395-409.
5. Solly S. Clinical lectures on paralysis. The Lancet 1856;63(1738):669-71.
J Dermatol 1994;33(2):123-6.
7. Levine H. The yellow rounded digit: sign of the times. N Engl J Med 1968;279(12):660-1.
cessation. Chest 1990;97(1):236-8.
psychiatric and substance use disorders. Am J Addict 2005;14(2):106-23.
12. Hafezi M, Bohnert M, Weinmann W, Pollak S. Prevalence of nicotine consumption in
drug deaths. Forensic Sci Int 2001;119(3):284-9.
health problems. 10 ed. Geneva, 2007.
2009.
15. The Criteria Committee of the New York Heart Association. Nomenclature and Criteria
for Dagnosis of Diseases of the Heart and Great Vessels. 9 ed. Boston, Mass, 1994.
16. American Psychiatric Association. Diagnostic and Statistical Manual of Mental
Disorders. 4 ed. Washington, DC: American Psychiatric Association, 1994.
Health Organization.
http://www.who.int/substance_abuse/terminology/who_lexicon/en/, 2005.
SOC2010), 2010.
the general U.S. population. Am J Respir Crit Care Med 1999;159(1):179-87.
20. Courvoisier DS, Combescure C, Agoritsas T, Gayet-Ageron A, Perneger TV. Performance
of logistic regression modeling: beyond the number of events per variable, the role of
data structure. J Clin Epidemiol 2011;64(9):993-1000.
21. Sorensen LT, Toft B, Rygaard J, Ladelund S, Teisner B, Gottrup F. Smoking attenuates
wound inflammation and proliferation while smoking cessation restores inflammation
but not proliferation. Wound Repair Regen 2010;18(2):186-92.
22. Reus WF, Robson MC, Zachary L, Heggers JP. Acute effects of tobacco smoking on
blood flow in the cutaneous micro-circulation. Br J Plast Surg 1984;37(2):213-5.
23. Rojanapongpun P, Drance SM. The effects of nicotine on the blood flow of the
ophthalmic artery and the finger circulation. Graefes Arch Clin Exp Ophthalmol
1993;231(7):371-4.
w
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Drug Alcohol Depend 1991;27(3):283-90.
2000;59(3):235-49.
smoke puffing behavior. Pharmacol Biochem Behav 1984;20(4):583-90.
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Variables
Cases (n=49)
Controls (n=49)
P value*
Matching
.65 †
59 (50 - 69)
62 (50 - 69)
Male
32 (65)
32 (65)
.99
.84 †
170 (165 - 175)
170 (165 - 177)
‡
50 (40 - 61)
46 (38- 58)
.20 †
§
.60 †
3.2 (2.4 - 3.7)
3.3 (2.4 - 3.8)
||
.48
15 (31)
11 (22)
Cardiovascular
Neurologic
7 (14)
6 (12)
.99
.79
6 (12)
8 (16)
Oncology
Infectious disease
5 (10)
5 (10)
.99
.99
5 (10)
6 (12)
Traumatology
Others
12 (24)
12 (24)
.99
*
†
‡
§
formula18
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Cases N(%)*
15 (31)
1-4
5-9
2 (4)
31 (65)
≥10
3 (6)
23 (48)
18 (37)
3 (2-4)
2 (1-3)
1 (0-2)
3 (2-4)
25 (52)
First finger
45 (94)
Second finger
37 (77)
Third finger
1 (2)
Fourth finger
0 (0)
Fifth finger
1.9 (1.0-3.1)
centimetre)
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Cases
Controls
N pairs OR(CI 95%)
p value*
41 (84)
39 (80)
49
1.3 (0.4-4.1)
.80
.83
0.9 (0.4-2.3)
49
26 (53)
25 (51)
Vascular disease
17 (35)
19 (39)
49
0.8 (0.3-2.1)
.67
.69
0.5 (0.1-3.5)
49
6 (12)
4 (8)
Strokes/TIA§
15 (31)
5 (10)
49
3.5 (1.1-14.6)
.03
.13
2.2 (0.7-8.1)
47
24 (49)
30 (64)
COPD
FEV1/FVC<70%
24 (52)
17 (37)
46
2.2 (0.8-6.9)
.11
.59
1.3 (0.4-4.7)
49
20 (41)
22 (45)
**
10 (20)
7 (14)
49
1.5 (0.5-5.1)
.61
Coughing
32 (65)
25 (51)
49
2.2 (0.8-6.9)
.11
.28
1.8 (0.5-6.8)
49
15 (31)
19 (39)
Sputum production
††
‡‡
1 (1-2)
1 (0-2)
49
.14
§§
.004
4.5 (1.5-18.3)
49
10 (20)
24 (49)
1.9 (1.3-2.5) 1.8 (1.4-2.6)
46
.49 ‡‡
*
McNemar exact test
†
‡
§
||
¶
**
††
‡‡
§§
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Univariated
Multivariated
Cases
Controls
OR (CI 95%)
p value
aOR (CI 95%)
p value
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Smoking habits
17 (15-20)
18 (15-20)
1.5 (1.0-2.4) *
.06
2.1 (1.1-4.0) *
.02
†
†
1 (1-1.8)
1 (1-1.5)
3.9 (1.2-12.7)
.02
8.5 (1.9-38.4)
.006
2 (1-3)
2 (2-3)
0.9 (0.7-1.2)
.39
Breaks median (IQR)
1 (0-2)
2 (1-3)
0.7 (0.5-1)
.03
20 (41)
9 (18)
3.2 (1.2-8.7)
.02
4.2 (1.1-16.0)
.04
7 (14)
17 (35)
0.3 (0.1-0.9)
.03
25 (51)
10 (20)
3.5 (1.4-8.7)
.007
4.6 (1.2-17.2)
.02
22 (45)
14 (29)
1.7 (0.8-3.7)
.18
¶
33 (67)
20 (41)
2.4 (1.1-5.3)
.02
Occupation
Unemployment
17 (35)
12 (24)
1.7 (0.7-4.3)
.26
*
†
‡
For every ten years
§
complications
||
¶
Antidepressant, anxiolytic, neuroleptic, and antiepileptic (used as mood stabilizer) drug
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STUDY.
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Switzerland.
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published).
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ABSTRACT
disease independent of cumulative tobacco exposure, and find behavioural and
environmental characteristics associated with those stains.
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CI95% 1.1-14.6). Smoking-related carcinoma, ischemic heart disease, stroke, and COPD
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were not statistically different to control smokers. Harmful alcohol use was strongly
associated with stains and this association persists after adjustment for smoking unfiltered
on
cigarettes, smoking more than one pack of cigarette in a day, and age at smoking onset
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(adjusted OR 4.6, CI95% 1.2-17.2). Mental disorders and unemployment were not
Conclusions: Patients with tobacco-tar stained fingers frequently have cigarette related
disease, however statistically not more than control smokers matched for YP, except for
symptomatic peripheral arterial disease. This study suggests a link between stained fingers
and addictive behaviour or concomitant high alcohol consumption.
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ARTICLE SUMMARY
Article focus
•
management.
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•
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Key messages
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Tobacco related diseases (defined as smoking related carcinoma, ischemic heart
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disease, peripheral arterial disease, stroke, or chronic obstructive pulmonary disease)
are frequent (84%) among patients with tobacco-tar stained fingers.
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concomitant high alcohol consumption.
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instruments (e.g. AUDIT). The sample size was small. This study included only
hospital population.
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INTRODUCTION
and chain."
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suspicion of lung carcinoma. The latter is seen after an acute illness that causes cessation of
cigarette consumption resulting in a bi-colour nail (the distal end is cigarette stained
contrasting the newly growing proximal part). We hypothesised that tar deposition itself
(figure 1) could be a marker of tobacco related disease independent of cumulative tobacco
exposure. A deeper puff could result in higher tar deposition on skin and greater inhalation of
tobacco, putting the lung and distant organs at increased health hazard.
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METHODS
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events excluded), coronary heart disease (CHD), peripheral arterial disease (PAD), tobaccorelated carcinoma (lung, urinary tract, or ENT), and COPD- was obtained from the patient’s
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We documented any mental disorders diagnosed according to Diagnostic and Statistical
Manual of Mental Disorders (DSM-IV) criteria and antidepressant, benzodiazepine,
neuroleptic, or mood stabilizer use.[16] We considered harmful alcohol use when high
alcohol intake –more than fourteen standard drinks per week for women and more than
twenty-one standard drinks per week for men (140g and 210g of alcohol respectively)- was
associated with documented withdrawal, medical consequences (neurologic, cardiac,
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hepatic, or pancreatic), or erythrocyte macrocytosis (mean corpuscular volume greater than
98 fl) not otherwise explained.[17]
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analyses are shown.
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RESULTS
Participants:
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study.
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stains.
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DISCUSSION
smokers. Tobacco related diseases (defined as smoking related carcinoma, ischemic heart
disease, peripheral arterial disease, stroke, and chronic obstructive pulmonary disease) are
frequent (84%) among patients with tobacco-tar stained fingers. Furthermore, this clinical
sign is linked to harmful alcohol use. As far as we know this is the first description of this
particular category of smokers.
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The design of the study appreciates the additional risk for health due to tar deposition not
included in the usual measure of tobacco exposure (PY). Stain may result from local pigment
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deposition secondary to high tar concentration in the skin-cigarette interface (influenced by
puffing or cigarettes characteristics), but higher concentration of nicotine (and other
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substances) smoked could affect stain removal by impaired skin repair. [21] Similarly,
nicotine has been shown to reduce blood flow in fingers and increase systemic blood
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pressure, a mechanism that could rationally explain the association of impaired stain removal
and peripheral arterial disease. [22, 23]
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Yet the high incidence of COPD, overall cardiovascular disease, and tobacco-related
carcinomas are not independently related to tar deposition. Besides, similar lung function
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between case and control groups and the absence of relationship between FEV1 and stain
characteristics among cases are consistent with a lack of association between yellow fingers
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and obstructive lung disease. We believe that yellow staining identifies high-risk smokers due
to the tobacco exposure (PY), rather than a specific increased susceptibility (e.g. puffing
characteristics). Lack of an association with investigated tobacco related illnesses other than
symptomatic peripheral arterial disease, could however arise from insufficient power of the
study.
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following consumption of 0.7 g/kg of ethanol.[27] We believe that this addictive behaviour
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and concomitant high alcohol consumption could impact tobacco cessation programs,
although it has not been tested yet.
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Third, power size calculation was made for 50 pairs and only 49 could be found, because of
the restrictive matching criteria. Moreover, 22% of controls reported transient tar
discoloration in the past, which might have blurred the effect. However, tar deposition
appears to be constant over time in the case group, and a transient finger staining could be a
clinically insignificant event. Finally, our observations are limited to the inpatient hospital
setting and may have to be confirmed in finger-stained patients seen outside this context.
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medical education. This costless and easy obtainable information should stress tobaccorelated disease screening and reinforce smoking counselling. Harmful alcohol use should be
ACKNOWLEDGEMENTS
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COMPETING INTERESTS
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the submitted work.
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FUNDING
REFERENCES:
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http://www.who.int/tobacco/global_report/2011/qanda/en/index.html, 2011.
in 2000. Tob Control 2004;13(4):388-95.
3. United States. Public Health Service. Office of the Surgeon General. How tobacco smoke
causes disease the biology and behavioral basis for smoking-attributable disease : a
report of the Surgeon General. Rockville, MD
[Washington, D.C.]: U.S. Dept. of Health and Human Services, Public Health Service
For sale by the Supt. of Docs., U.S. G.P.O., 2010:1 online resource (xv, 706 p.).
4. Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, et al. Reduced
lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med
2011;365(5):395-409.
5. Solly S. Clinical lectures on paralysis. The Lancet 1856;63(1738):669-71.
J Dermatol 1994;33(2):123-6.
7. Levine H. The yellow rounded digit: sign of the times. N Engl J Med 1968;279(12):660-1.
cessation. Chest 1990;97(1):236-8.
psychiatric and substance use disorders. Am J Addict 2005;14(2):106-23.
12. Hafezi M, Bohnert M, Weinmann W, Pollak S. Prevalence of nicotine consumption in
drug deaths. Forensic Sci Int 2001;119(3):284-9.
health problems. 10 ed. Geneva, 2007.
2009.
15. The Criteria Committee of the New York Heart Association. Nomenclature and Criteria
for Dagnosis of Diseases of the Heart and Great Vessels. 9 ed. Boston, Mass, 1994.
16. American Psychiatric Association. Diagnostic and Statistical Manual of Mental
Disorders. 4 ed. Washington, DC: American Psychiatric Association, 1994.
Health Organization.
http://www.who.int/substance_abuse/terminology/who_lexicon/en/, 2005.
SOC2010), 2010.
the general U.S. population. Am J Respir Crit Care Med 1999;159(1):179-87.
20. Courvoisier DS, Combescure C, Agoritsas T, Gayet-Ageron A, Perneger TV. Performance
of logistic regression modeling: beyond the number of events per variable, the role of
data structure. J Clin Epidemiol 2011;64(9):993-1000.
21. Sorensen LT, Toft B, Rygaard J, Ladelund S, Teisner B, Gottrup F. Smoking attenuates
wound inflammation and proliferation while smoking cessation restores inflammation
but not proliferation. Wound Repair Regen 2010;18(2):186-92.
22. Reus WF, Robson MC, Zachary L, Heggers JP. Acute effects of tobacco smoking on
blood flow in the cutaneous micro-circulation. Br J Plast Surg 1984;37(2):213-5.
23. Rojanapongpun P, Drance SM. The effects of nicotine on the blood flow of the
ophthalmic artery and the finger circulation. Graefes Arch Clin Exp Ophthalmol
1993;231(7):371-4.
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Drug Alcohol Depend 1991;27(3):283-90.
2000;59(3):235-49.
smoke puffing behavior. Pharmacol Biochem Behav 1984;20(4):583-90.
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Variables
Cases (n=49)
Controls (n=49)
P value*
Matching
.65 †
59 (50 - 69)
62 (50 - 69)
Male
32 (65)
32 (65)
.99
.84 †
170 (165 - 175)
170 (165 - 177)
‡
50 (40 - 61)
46 (38- 58)
.20 †
§
.60 †
3.2 (2.4 - 3.7)
3.3 (2.4 - 3.8)
||
.48
15 (31)
11 (22)
Cardiovascular
Neurologic
7 (14)
6 (12)
.99
.79
6 (12)
8 (16)
Oncology
Infectious disease
5 (10)
5 (10)
.99
.99
5 (10)
6 (12)
Traumatology
Others
12 (24)
12 (24)
.99
*
†
‡
§
formula18
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Cases N(%)*
15 (31)
1-4
5-9
2 (4)
31 (65)
≥10
3 (6)
23 (48)
18 (37)
3 (2-4)
2 (1-3)
1 (0-2)
3 (2-4)
25 (52)
First finger
45 (94)
Second finger
37 (77)
Third finger
1 (2)
Fourth finger
0 (0)
Fifth finger
1.9 (1.0-3.1)
centimetre)
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Cases
Controls
N pairs OR(CI 95%)
p value*
41 (84)
39 (80)
49
1.3 (0.4-4.1)
.80
.83
0.9 (0.4-2.3)
49
26 (53)
25 (51)
Vascular disease
17 (35)
19 (39)
49
0.8 (0.3-2.1)
.67
.69
0.5 (0.1-3.5)
49
6 (12)
4 (8)
Strokes/TIA§
15 (31)
5 (10)
49
3.5 (1.1-14.6)
.03
.13
2.2 (0.7-8.1)
47
24 (49)
30 (64)
COPD
FEV1/FVC<70%
24 (52)
17 (37)
46
2.2 (0.8-6.9)
.11
.59
1.3 (0.4-4.7)
49
20 (41)
22 (45)
**
10 (20)
7 (14)
49
1.5 (0.5-5.1)
.61
Coughing
32 (65)
25 (51)
49
2.2 (0.8-6.9)
.11
.28
1.8 (0.5-6.8)
49
15 (31)
19 (39)
Sputum production
††
‡‡
1 (1-2)
1 (0-2)
49
.14
§§
.004
4.5 (1.5-18.3)
49
10 (20)
24 (49)
1.9 (1.3-2.5) 1.8 (1.4-2.6)
46
.49 ‡‡
*
McNemar exact test
†
‡
§
||
¶
**
††
‡‡
§§
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Univariated
Multivariated
Cases
Controls
OR (CI 95%)
p value
aOR (CI 95%)
p value
Fo
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Smoking habits
17 (15-20)
18 (15-20)
1.5 (1.0-2.4) *
.06
2.1 (1.1-4.0) *
.02
†
†
1 (1-1.8)
1 (1-1.5)
3.9 (1.2-12.7)
.02
8.5 (1.9-38.4)
.006
2 (1-3)
2 (2-3)
0.9 (0.7-1.2)
.39
Breaks median (IQR)
1 (0-2)
2 (1-3)
0.7 (0.5-1)
.03
20 (41)
9 (18)
3.2 (1.2-8.7)
.02
4.2 (1.1-16.0)
.04
7 (14)
17 (35)
0.3 (0.1-0.9)
.03
25 (51)
10 (20)
3.5 (1.4-8.7)
.007
4.6 (1.2-17.2)
.02
22 (45)
14 (29)
1.7 (0.8-3.7)
.18
¶
33 (67)
20 (41)
2.4 (1.1-5.3)
.02
Occupation
Unemployment
17 (35)
12 (24)
1.7 (0.7-4.3)
.26
*
†
‡
For every ten years
§
complications
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¶
Antidepressant, anxiolytic, neuroleptic, and antiepileptic (used as mood stabilizer) drug
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Tar staining seen in a 70 years old men smoker (80PY).
626x534mm (72 x 72 DPI)
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STROBE 2007 (v4) Statement—Checklist of items that should be included in reports of case-control studies
Section/Topic
Title and abstract
Item
#
1
Recommendation
Reported on
page #
(a) Indicate the study’s design with a commonly used term in the title or the abstract
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(b) Provide in the abstract an informative and balanced summary of what was done and what was found
Introduction
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Background/rationale
2
Explain the scientific background and rationale for the investigation being reported
4,5
Objectives
3
State specific objectives, including any prespecified hypotheses
5
Study design
4
Present key elements of study design early in the paper
Setting
5
Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection
5-7
Participants
6
(a) Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for
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Methods
the choice of cases and controls
Variables
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5
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(b) For matched studies, give matching criteria and the number of controls per case
7
Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if
6,7
applicable
on
Data sources/
measurement
8*
For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability
of assessment methods if there is more than one group
Bias
9
Describe any efforts to address potential sources of bias
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6
Study size
10
Explain how the study size was arrived at
Quantitative variables
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Explain how quantitative variables were handled in the analyses. If applicable, describe which groupings were chosen and why
7,8
7
Statistical methods
12
(a) Describe all statistical methods, including those used to control for confounding
7,8
(b) Describe any methods used to examine subgroups and interactions
8
(c) Explain how missing data were addressed
8
(d) If applicable, explain how matching of cases and controls was addressed
7
(e) Describe any sensitivity analyses
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Page 41 of 42
Results
Participants
13*
(a) Report numbers of individuals at each stage of study—eg numbers potentially eligible, examined for eligibility, confirmed
8
eligible, included in the study, completing follow-up, and analysed
Descriptive data
14*
Fo
(b) Give reasons for non-participation at each stage
8
(c) Consider use of a flow diagram
-
rp
(a) Give characteristics of study participants (eg demographic, clinical, social) and information on exposures and potential
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BMJ Open
8, 15-18
confounders
(b) Indicate number of participants with missing data for each variable of interest
17
ee
Outcome data
15*
Report numbers in each exposure category, or summary measures of exposure
15-18
Main results
16
(a) Give unadjusted estimates and, if applicable, confounder-adjusted estimates and their precision (eg, 95% confidence
interval). Make clear which confounders were adjusted for and why they were included
8-9, 15-18
(b) Report category boundaries when continuous variables were categorized
8-9, 15-18
(c) If relevant, consider translating estimates of relative risk into absolute risk for a meaningful time period
-
Report other analyses done—eg analyses of subgroups and interactions, and sensitivity analyses
7
Other analyses
17
rr
ev
Discussion
iew
Key results
18
Summarise key results with reference to study objectives
Limitations
19
Discuss limitations of the study, taking into account sources of potential bias or imprecision.
Discuss both direction and magnitude of any potential bias
11
Interpretation
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Give a cautious overall interpretation of results considering objectives, limitations, multiplicity of analyses, results from similar
11
studies, and other relevant evidence
Generalisability
on
ly
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Discuss the generalisability (external validity) of the study results
22
Give the source of funding and the role of the funders for the present study and, if applicable, for the original study on which the
present article is based
Other information
Funding
10
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*Give information separately for cases and controls in case-control studies and, if applicable, for exposed and unexposed groups in cohort and cross-sectional studies.
2
BMJ Open
Note: An Explanation and Elaboration article discusses each checklist item and gives methodological background and published examples of transparent reporting. The STROBE
checklist is best used in conjunction with this article (freely available on the Web sites of PLoS Medicine at http://www.plosmedicine.org/, Annals of Internal Medicine at
http://www.annals.org/, and Epidemiology at http://www.epidem.com/). Information on the STROBE Initiative is available at www.strobe-statement.org.
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rp
ee
rr
ev
iew
on
ly
3
Tobacco-stained fingers: a clue for
smoking-related disease or harmful alcohol
use? A case−control study
Gregor John, Sephora Pasche, Nicole Rothen, Alexia Charmoy, Cécile
Delhumeau-Cartier and Daniel Genné
BMJ Open 2013 3:
doi: 10.1136/bmjopen-2013-003304
Updated information and services can be found at:
http://bmjopen.bmj.com/content/3/11/e003304
These include:
References
This article cites 18 articles, 2 of which you can access for free at:
http://bmjopen.bmj.com/content/3/11/e003304#BIBL
Open Access
This is an Open Access article distributed in accordance with the Creative
Commons Attribution Non Commercial (CC BY-NC 3.0) license, which
permits others to distribute, remix, adapt, build upon this work
non-commercially, and license their derivative works on different terms,
provided the original work is properly cited and the use is non-commercial.
See: http://creativecommons.org/licenses/by-nc/3.0/
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