Instantaneous Carboxyhemoglobin Level Change Due to Smoking and Analysis of Baseline SpCO in Smokers

Instantaneous Carboxyhemoglobin Level Change Due to Smoking and Analysis of Baseline SpCO in Smokers | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Instantaneous Carboxyhemoglobin Level Change Due to Smoking and Analysis of Baseline SpCO in Smokers Salih Kocaoğlu, Tufan Alatlı This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5880374/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The aim of this study was to investigate baseline carboxyhemoglobin saturation (SpCO) values in smokers and to show the relationship between SpCO and age, years smoking, cigarettes per day, and nicotine dependence. We also analyzed the changes in carboxyhemoglobin in the body during active smoking. Methods This prospective cohort study involved 136 outdoor smokers and 60 controls who had never smoked. SpCO, heart rate (HR), and oxyhemoglobin saturation (SpO2) values were recorded with a CO-oximeter device before, during, and two minutes after smoking. Changes during active smoking were analyzed, and all parameters were compared between smoking and non-smoking groups. Age, BMI, years smoking, cigarettes per day, and Fagerström nicotine dependence (FTND) level were correlated with baseline SpCO. Results The mean age of smokers was 32.3 years (70.6% male; 22.79% with comorbidities), while the mean age of non-smokers was 36.7 years (38.3% male). The SpCO and HR were significantly higher during (p = 0.006, p < 0.001) and after (p = 0.015, p < 0.001) smoking than the pre-cigarette levels. There was a significant difference between smokers (3.07) and non-smokers (1.77) in terms of baseline SpCO (p < 0.001). Correlation analysis showed that age, years smoking, and nicotine dependence were positively correlated with baseline SpCO. In the ROC analysis, the AUC value for SpCO was 0.705 and the optimal cut-off value was 1.50. In addition, 83% of smokers had a baseline SpCO value below 5%. Conclusion In this study, the baseline SpCO values of smokers were found to be approximately 200% higher than those of non-smokers. In addition, SpCO and HR increased during active smoking. However, 83% of smokers had a baseline SpCO below 5%, suggesting that the intoxication level of 9% in smokers should be reconsidered. Cigarette smoking Carbon monoxide Poisoning Carboxyhemoglobin SpCO Figures Figure 1 Figure 2 Figure 3 Introduction Carbon monoxide (CO)—a colorless, odorless, and tasteless gas—is released as a result of incomplete combustion of hydrocarbons and poses a serious danger that is invisible to the naked eye. CO binds to hemoglobin 240 times more than oxygen, causing tissue hypoxia ( 1 ). It is thought that there are around 30,000 − 50,000 emergency room admissions each year due to CO poisoning ( 2 ). This number is expected to be much higher in undeveloped countries. Patients present to the emergency department with nonspecific symptoms such as nausea, headache, dyspnea, weakness, palpitations, and dizziness. Therefore, CO poisoning cases are likely to be missed, especially in crowded emergency departments. Since CO is also an environmental toxin, its diagnosis is also important for other individuals who may be affected by the CO present in the environment. Diagnosis of CO poisoning used to be routinely performed by emergency clinicians with invasive blood tests. However, the development of the multiwave pulse CO-oximeter has provided a non-invasive, easy, and rapid method. The working principle of these devices is based on the transmission of different wavelengths of light during blood flow, which measures carboxyhemoglobin saturation (SpCO) (3 − 5). Comparison of SpCO obtained from CO-oximetry with carboxyhemoglobin obtained from blood sampling has been done in previous studies and its accuracy has been confirmed ( 6 , 7 ). The noninvasive and easily applicable nature of the device enables easy screening in emergency departments and has been shown to detect unexpected CO exposures ( 8 ). However, baseline CO levels remain insufficiently investigated. While levels above 2 − 3% are considered to signify CO intoxication in non-smokers, the cut-off value for smokers is currently unclear owing to the variability of baseline SpCO levels due to smoking. Some studies show that the baseline SpCO level in smokers is below 9%. However, current guidelines published by the Centers for Disease Control and Prevention still recommend a SpCO level of 9% as the threshold value (8 − 10). In this study, we investigated baseline SpCO levels in smokers using a CO-oximetry device. We also recorded dynamic SpCO levels during and after active smoking and examined the relationship of smoking-related carboxyhemoglobin kinetics with time. Methods Study design and setting Following the approval from the Clinical Research Ethics Committee (Decision Date: 03.11.2021, Decision Number: 2021/247), this prospective cohort study was conducted between January 2023 and January 2024 on volunteer subjects who were active smokers. The research team, who were waiting in the open smoking area around our hospital, identified and approached people who were about to smoke and briefly informed them about the study. Volunteers underwent measurements just before, during, and two minutes after smoking. Smokers under 18 years of age, indoor smokers, people who refused to participate in the study, and people who did not want to wait after smoking were excluded from the study. Data collection and processing Masimo Rad 57 CO-oximeter (Masimo Inc., Irvine, CA) with fingertip sensor was used for the measurements. In all subjects, a single device was placed on the index finger for the duration of the assessment. This model has been used in many previous studies. SpCO, SpO2, and heart rate (HR) were measured before smoking, during (halfway through) smoking, and two minutes after smoking. Age, gender, years smoking, cigarettes per day, body mass index (BMI), and comorbidities were also collected. The subjects were also administered the Fagerström nicotine dependence (FTND) test. The 60 subjects who never smoked and were approached outdoors served as the control group and their SpCO, SpO2, and HR were recorded as described above. Outcomes Baseline SpCO, HR, and SpO2 values of smokers and non-smokers were compared, while for smokers comparisons were also made across the SpCO, HR, and SpO2 values obtained before, during, and two minutes after smoking. The relationship between baseline SpCO values and age, BMI, years smoking, cigarettes per day, and FTND scores was also investigated. Statistical analysis Normality of the numeric data was tested with the Shapiro − Wilk test, and the Mann − Whitney U test was used to compare non-normal variables between two independent groups. To compare numerical variables between two dependent groups, differences between the pairs were calculated, and paired samples t-test and Wilcoxon test was performed for normal and non-normal pair differences, respectively. Pearson chi-squared and Fisher’s exact chi-squared tests were conducted to compare categorical variables between independent groups. Mean ± standard deviation and median (Q1 − Q3) values were given as the descriptive statistics for numerical data. Categorical data were presented as frequencies (n) and percentages. Pearson and Spearman correlation coefficients were calculated to evaluate the relationship between baseline SpCO, HR, and SpO2, and other numerical variables, including age, BMI, years smoking, cigarettes per day, and total FTND score. To determine the effect of smoking status (smoker or non-smoker) as a risk factor for the baseline SpCO > 5%, logistic regression analysis was performed, adjusting for gender and age. Receiver operating characteristics (ROC) curve analysis was performed and area under the ROC curve (AUC) was estimated to examine the performance of SpCO, HR, and SpO2 in discriminating between smokers and non-smokers and to identify a significant cut-off value (p < 0.05 was accepted as statistically significant). Statistical analyses were performed using the IBM SPSS Statistics 29.0.0 software. Results Of the 165 smokers that initially agreed to participate in the study, 29 were excluded for various reasons (e.g., not waiting for the post-cigarette SpCO measurement, not smoking the entire cigarette, immediately switching to the second cigarette). As a result, the data pertaining to 136 (69.39%) smokers and 60 (30.61%) non-smoker volunteers (controls) were retained for analysis. Demographic data, including age, sex, and smoking habits, are given in Table 1. While the mean age of smokers was 32.35 ± 11.66 years, the mean age of non-smokers was 36.75 ± 14.80 years, and this difference was statistically significant (p = 0.027). There were 96 (70.6%) males and 40 (29.4%) females among smokers, and 23 (38.3%) males and 37 (61.7%) females among non-smokers (p < 0.001). For the smokers, the mean number of years smoking and the mean number of cigarettes per day were 13.13 ± 10.97 years and 18.93 ± 10.32, respectively (Table 1). Table 1 Demographic characteristics and smoking habits of smokers and non-smokers Variable Smokers (n = 136) Non-smokers (n = 60) p-value Male * 96 (70.59) 23 (38.33) < 0.001 Age [years] # 32.35 ± 11.66 36.75 ± 14.80 0.027 Years smoking # 13.13 ± 10.97 0 - Cigarettes per day # 18.93 ± 10.32 0 - Data given with the * n (%) or # mean ± standard deviation. SpCO, HR, and SpO2 measurements were obtained pre-cigarette, during smoking, and two minutes after smoking (post-cigarette) from all smokers (n = 136 for all sessions). The SpCO levels and the HR were significantly higher during the cigarette-smoking session (p = 0.006 and p < 0.001) and post-cigarette session (p = 0.015 and p < 0.001) than in the pre-cigarette session (Table 2). We also measured SpCO, HR, and SpO2 for the non-smokers. There was a significant difference between smokers and non-smokers in terms of baseline SpCO (p < 0.001), HR (p = 0.002), and SpO2 (p = 0.004). These measurements were significantly higher in smokers than in non-smokers (Table 3). Table 2 SpCO, HR and SpO2 levels of smokers in pre-cigarette, during cigarette and post-cigarette Variables Pre-cigarette (I) During cigarette (II) Post-cigarette (III) p-value I-II I-III SpCO 3.07 ± 2.02 3.60 ± 2.37 3.43 ± 2.15 0.006 0.015 HR 87.26 ± 14.87 92.57 ± 15.19 90.35 ± 13.96 < 0.001 < 0.001 SpO2 98.42 ± 1.26 98.46 ± 1.35 98.36 ± 1.37 0.595 0.506 Data given with the mean ± standard. Table 3 Comparison of baseline SpCO, HR and SpO2 levels between smokers and non-smokers Variables Smokers (n = 136) Non-smokers (n = 60) p-value SpCO 3.07 ± 2.02 1.77 ± 1.32 < 0.001 HR 87.26 ± 14.87 80.83 ± 14.58 0.002 SpO2 98.42 ± 1.26 97.62 ± 1.86 0.004 Data given with the mean ± standard. Mean total score on the FTND test was 4.19 ± 2.92 for the smokers. There were 47 (34.56%) smokers with very low, 28 (20.59%) with low, 16 (11.76%) with moderate, 25 (18.38) with high, and 20 (14.71%) with very high nicotine dependence (Table 4). Table 4 Descriptive statistics for the Fagerström nicotine dependence test FTND test Descriptive statistics Total score * 4.19 ± 2.92 Very low dependence 47 (34.56) Categories # Low dependence 28 (20.59) Moderate dependence 16 (11.76) High dependence 25 (18.38) Very high dependence 20 (14.71) Data presented with * mean ± standard, or # n (%). Mean BMI of the smokers was 25.44 ± 3.83 kg/m 2 and 31 (22.79%) individuals in this group had at least one comorbidity. Correlation analyses indicated a positive relationship between baseline SpCO and age (r = 0.242, p = 0.005), years smoking (r = 0.260, p = 0.002), and total FTND score (r = 0.173, p = 0.044), indicating that older age, longer smoking duration, and greater nicotine dependency were associated with higher baseline SpCO levels for the smokers. Correlations between baseline SpCO and BMI (r = 0.119, p = 0.166) and baseline SpCO and number of cigarettes smoked daily (r = 0.073, p = 0.400) were not significant. There was a negative correlation between HR and age (r=-0.329, p < 0.001), and between HR and years smoking (r=-0.335, p < 0.001), indicating that older age and longer smoking duration were associated with lower baseline HR for the smokers (Table 5). No statistically significant difference was found between smokers with and without comorbidities in terms of baseline SpCO (p = 0.448), HR (p = 0.072), and SpO2 (p = 0.972) levels. (Table 6). Table 6 Comparison of baseline SpCO, HR and SpO2 levels between those with and without comorbidities Variables Without comorbidity (n = 105) With comorbidity (n = 31) p-value SpCO 3.00 (2.00–4.00) 3.00 (1.00–11.00) 0.448 HR 88.50 ± 15.10 83.03 ± 13.44 0.072 SpO2 99.00 (98.00–99.00) 99.00 (98.00–99.00) 0.972 Data presented with mean ± standard deviation or median (Q1-Q3) We also performed ROC curve analysis to assess the effectiveness of SpCO, HR, and SpO2 (measured at baseline for smokers) in discriminating between smokers and non-smokers. The AUC for SpCO was 0.705, which was statistically significant, and the optimal cut-off value was 1.50. The AUC values for HR and SpO2 were also statistically significant but lower (Table 7, Fig. 3). Table 7 ROC curve analysis results for the SpCO, HR and SpO2 Variables AUC p-value cut-off value Sensitivity Specificity SpCO 0.705 < 0.001 1.50 0.809 0.467 HR 0.637 0.002 79.50 0.721 0.533 SpO2 0.627 0.004 98.50 0.522 0.700 AUC: Area under the ROC curve We found that 113 (83.09%) of the smokers had SpCO ≤ 5%, and 134 (98.53%) had SpCO ≤ 9%. There was a significant difference between smokers and non-smokers in terms of proportions with SpCO ≤ 5%, but not for SpCO ≤ 9% (Table 8). Table 8 Comparison of smokers and non-smokers in terms of baseline SpCO groups Baseline SpCO Controls Smokers p-value ≤ 5% 57 (95.00) 113 (83.09) 0.023 > 5% 3 (5.00) 23 (16.91) ≤ 9% 60 (100.00) 134 (98.53) 1.000 > 9% 0 (0.00) 2 (1.47) We performed binary logistic regression analysis to predict baseline SpCO category (≤ 5% / >5%) by taking an indicator of smoking as an independent variable and adjusting for age and gender (Omnibus test for the model: p = 0.043, Hosmer − Lemeshow test: p = 0.672). According to the obtained findings, smokers were 4.596 times more likely to have baseline SpCO levels above 5% than non-smokers (OR = 4.596, p = 0.023). Gender (p = 0.846) and age (p = 0.133) did not emerge as significant predictors of baseline SpCO (Table 9). Table 9 Results of the logistic regression analysis for predicting baseline SpCO groups Variables p-value OR 95% CI for OR Lower Upper Smoking status (RC: Non-smokers) 0.023 4.596 1.237 17.071 Gender (RC: Female) 0.846 1.095 0.441 2.717 Age 0.133 1.024 0.993 1.057 RC: Reference category, OR: Odds ratio, CI: Confidence interval Dependent variable: CO groups (category (≤ 5% /> 5%) Independent variable: Smoking status (smoker/non-smoker), gender (male/female) and age (years). p-value for the model: p = 0.043 for the Omnibus test, p = 0.672 for the Hosmer & Lemeshow test Discussion We believe that this prospective cohort study conducted on healthy volunteer subjects provides important information on the effect of smoking on carboxyhemoglobin levels. The study provides information about the baseline SpCO values of smokers, while also offering insight into the carboxyhemoglobin changes that occur in the human body during smoking. CO enters the human body through respiration. The amount of CO absorbed is directly related to the CO concentration in the inhaled air, the amount of ventilation per minute, and the duration of exposure. Inhaled CO binds to iron molecules in hemoglobin, myoglobin, and cytochrome C ( 11 ). CO toxicity can present in a variety of forms, ranging from mild symptoms to coma. The illness severity is related to the degree of CO exposure and comorbidities ( 12 ). It should be kept in mind that delayed neurologic sequelae may occur in addition to acute effects. Cigarette smoke is also an important source of CO as it contains about 3.5% CO ( 13 ). In the present study, SpCO and HR values were found to be significantly higher during smoking and two minutes after smoking than before smoking, suggesting that carboxyhemoglobin levels in the blood increase during and after smoking. The increase in HR may be explained by the activation of the sympathetic system due to stress in metabolism and tissue hypoxia. Similarly, in a study conducted on 85 smokers, Schimmel et al. showed that SpCO levels increased during and after smoking ( 14 ). Some older studies with a limited number of subjects have also presented results supporting those obtained in the present study ( 15 , 16 ). Baseline SpCO and HR values of smokers were significantly higher than those of non-smokers (smokers: SpCO = 3.07, nonsmokers: SpCO = 1.77, p < 0.001). In the ROC analysis, the AUC value for SpCO was 0.705, while the optimal cut-off value was 1.5. This was expected, given that smoking causes a chronic increase in the metabolic carboxyhemoglobin levels, leading to an increase in baseline SpCO. Over time, it causes tachycardia due to changes in vascular and pulmonary structures, which explains the difference in HR. However, it should be noted that, although the 9% limit of CO intoxication for smokers is typically cited in the literature, 98.5% of smokers in this study had a baseline SpCO below 9% and 83.1% had a baseline SpCO below 5%. These findings suggest that the 9% intoxication threshold for smokers should be re-examined and additional studies are needed. It is suggested that with SpCO values in the 5 − 9% range should be examined in the clinic more carefully to assess their presenting symptoms and level of CO intoxication. Schimmel et al. also raised this issue and reported similar findings ( 14 ). Correlation analysis showed that older age, longer smoking duration, and greater nicotine dependence were associated with higher baseline SpCO levels for smokers. However, BMI and number of cigarettes smoked per day were not significantly associated with their baseline SpCO values. Schimmel et al. showed that there was no significant correlation between pre-cigarette SpCO and age, years smoking, number of cigarettes smoked per day, or number of cigarettes smoked on the day of measurement. However, recent smoking was closely associated with baseline SpCO ( 14 ). On the other hand, Roth et al. showed that the number of cigarettes smoked per day was an independent predictor of baseline SpCO ( 7 ). In this study, cardiopulmonary diseases such as hypertension, diabetes, asthma, COPD, coronary artery disease, and heart failure were present in 22.7% of smokers. However, there was no statistically significant difference in baseline SpCO, HR, and SpO2 between smokers with and without comorbidities. Several authors cautioned that SpCO may be elevated in asthma and COPD, but the link between specific conditions and increased carboxyhemoglobin levels is insufficiently investigated ( 17 , 18 ). Limitations As our study participants were recruited via convenience sampling, although the aim was to assess the typical smoking population, our subjects appeared to be healthier and younger. Moreover, the information on smoking habits was self-reported and may be inaccurate. Obviously, obtaining carboxyhemoglobin values via blood gas analysis would provide more reliable results, but since this is an invasive procedure, CO-oximetry was preferred. Longer observation of post-smoking SpCO values would provide more accurate information about the kinetics of smoking-induced carboxyhemoglobin, but the subjects’ unwillingness to wait after smoking led us to limit this period to two minutes. We believe that additional multicenter studies with larger samples are needed to more accurately determine baseline SpCO in smokers. Conclusion The ability to use CO-oximetry as a screening tool for suspected CO poisoning in a larger population is certainly an advantage over blood gas analysis. However, the results obtained in this study suggest that the threshold value for smokers should be reconsidered, because 83.1% of smokers had a baseline SpCO below 5%. In smokers, baseline SpCO was associated with age, years of smoking, and FTND level. In addition, SpCO values considerably increased during active smoking, and the baseline SpCO values of smokers were approximately 200% higher than those of non-smokers. Declarations Acknowledgements We would like to thank Prof. Dr. Deniz Sığırlı from Bursa Uludağ University for her help in the statistical analysis of our article. Ethical approval Ethics Committee approval was obtained from the Ethics Committee of the Faculty of Medicine, Balikesir University (Date: 03.11.2021; Issue: 2021/247). Competing interest The authors declared no competing interest. Funding This research has not received any specific support from any funding. Author information Authors and Affiliations ¹Balikesir University, Faculty of Medicine, Dept. of Emergency Medicine, Balikesir, Turkey Authors’ contributions SK: Data collection, conceived and designed the study, paper write-up. TA: Statistic analyses, discussion and proofreading. Corresponding author Correspondence to Salih Kocaoğlu. Clinical trial number Not applicable. Consent for publication Not applicable. References Megas IF, Beier JP, Grieb G. The History of Carbon Monoxide Intoxication. Medicina (Kaunas). 2021 Apr 21;57(5):400. doi: 10.3390/medicina57050400. Chenoweth JA, Albertson TE, Greer MR. Carbon Monoxide Poisoning. Crit Care Clin. 2021 Jul;37(3):657-672. doi: 10.1016/j.ccc.2021.03.010. Nikkanen H, Skolnik A. Diagnosis and management of carbon monoxide poisoning in the emergency department. Emerg Med Pract. 2011 Feb;13(2):1-14; quiz 14. PMID: 22164402. Bledsoe BE, Nowicki K, Creel JH Jr, Carrison D, Severance HW. 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Lung. 2015 Apr;193(2):183-7. doi: 10.1007/s00408-015-9686-x. Epub 2015 Feb 14. Yasuda H, Yamaya M, Nakayama K, Ebihara S, Sasaki T, Okinaga S, Inoue D, Asada M, Nemoto M, Sasaki H. Increased arterial carboxyhemoglobin concentrations in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2005 Jun 1;171(11):1246-51. doi: 10.1164/rccm.200407-914OC. Epub 2005 Mar 11. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5880374","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":407712682,"identity":"ab1d5f79-27ed-4b28-9976-e3991066a283","order_by":0,"name":"Salih Kocaoğlu","email":"data:image/png;base64,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","orcid":"","institution":"Balıkesir University","correspondingAuthor":true,"prefix":"","firstName":"Salih","middleName":"","lastName":"Kocaoğlu","suffix":""},{"id":407712683,"identity":"60744b4d-ed6d-48c6-a9a9-7478fcd5ff1b","order_by":1,"name":"Tufan Alatlı","email":"","orcid":"","institution":"Balıkesir University","correspondingAuthor":false,"prefix":"","firstName":"Tufan","middleName":"","lastName":"Alatlı","suffix":""}],"badges":[],"createdAt":"2025-01-22 11:26:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5880374/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5880374/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74995958,"identity":"10239307-9c20-4634-94ca-ad66a79cd231","added_by":"auto","created_at":"2025-01-29 08:41:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":58041,"visible":true,"origin":"","legend":"\u003cp\u003eBox-plots for SpCO, HR and SpO2 for smokers and non-smokers\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5880374/v1/fe53b20dd9ee8f365eacf961.png"},{"id":74995959,"identity":"c1da0684-b290-4a0e-8747-9b8ec0c1a010","added_by":"auto","created_at":"2025-01-29 08:41:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":40915,"visible":true,"origin":"","legend":"\u003cp\u003eBox-plots for pre-cigarette, during cigarette, post-cigarette A) SpCO, B) HR and C) SpO2 levels for smokers\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5880374/v1/9206ca58bb0a7b251cb5e442.png"},{"id":74995960,"identity":"a797ab3a-a58b-4c22-b28d-97be997237bd","added_by":"auto","created_at":"2025-01-29 08:41:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48752,"visible":true,"origin":"","legend":"\u003cp\u003eROC curves for the SpCO, HR and SpO2 in discriminating between smokers and non-smokers\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-5880374/v1/8d672b67eb12a3e2e17778a8.png"},{"id":75070687,"identity":"07c4655c-4c58-4dfb-980f-af38934b1908","added_by":"auto","created_at":"2025-01-30 06:53:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":852713,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5880374/v1/ddaa2f9e-4bcb-43aa-80e3-a0784194efe9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Instantaneous Carboxyhemoglobin Level Change Due to Smoking and Analysis of Baseline SpCO in Smokers","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCarbon monoxide (CO)\u0026mdash;a colorless, odorless, and tasteless gas\u0026mdash;is released as a result of incomplete combustion of hydrocarbons and poses a serious danger that is invisible to the naked eye. CO binds to hemoglobin 240 times more than oxygen, causing tissue hypoxia (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is thought that there are around 30,000\u0026thinsp;\u0026minus;\u0026thinsp;50,000 emergency room admissions each year due to CO poisoning (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). This number is expected to be much higher in undeveloped countries. Patients present to the emergency department with nonspecific symptoms such as nausea, headache, dyspnea, weakness, palpitations, and dizziness. Therefore, CO poisoning cases are likely to be missed, especially in crowded emergency departments. Since CO is also an environmental toxin, its diagnosis is also important for other individuals who may be affected by the CO present in the environment.\u003c/p\u003e \u003cp\u003eDiagnosis of CO poisoning used to be routinely performed by emergency clinicians with invasive blood tests. However, the development of the multiwave pulse CO-oximeter has provided a non-invasive, easy, and rapid method. The working principle of these devices is based on the transmission of different wavelengths of light during blood flow, which measures carboxyhemoglobin saturation (SpCO) (3\u0026thinsp;\u0026minus;\u0026thinsp;5). Comparison of SpCO obtained from CO-oximetry with carboxyhemoglobin obtained from blood sampling has been done in previous studies and its accuracy has been confirmed (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The noninvasive and easily applicable nature of the device enables easy screening in emergency departments and has been shown to detect unexpected CO exposures (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, baseline CO levels remain insufficiently investigated. While levels above 2\u0026thinsp;\u0026minus;\u0026thinsp;3% are considered to signify CO intoxication in non-smokers, the cut-off value for smokers is currently unclear owing to the variability of baseline SpCO levels due to smoking. Some studies show that the baseline SpCO level in smokers is below 9%. However, current guidelines published by the Centers for Disease Control and Prevention still recommend a SpCO level of 9% as the threshold value (8\u0026thinsp;\u0026minus;\u0026thinsp;10).\u003c/p\u003e \u003cp\u003eIn this study, we investigated baseline SpCO levels in smokers using a CO-oximetry device. We also recorded dynamic SpCO levels during and after active smoking and examined the relationship of smoking-related carboxyhemoglobin kinetics with time.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eFollowing the approval from the Clinical Research Ethics Committee (Decision Date: 03.11.2021, Decision Number: 2021/247), this prospective cohort study was conducted between January 2023 and January 2024 on volunteer subjects who were active smokers. The research team, who were waiting in the open smoking area around our hospital, identified and approached people who were about to smoke and briefly informed them about the study. Volunteers underwent measurements just before, during, and two minutes after smoking. Smokers under 18 years of age, indoor smokers, people who refused to participate in the study, and people who did not want to wait after smoking were excluded from the study.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection and processing\u003c/h3\u003e\n\u003cp\u003eMasimo Rad 57 CO-oximeter (Masimo Inc., Irvine, CA) with fingertip sensor was used for the measurements. In all subjects, a single device was placed on the index finger for the duration of the assessment. This model has been used in many previous studies. SpCO, SpO2, and heart rate (HR) were measured before smoking, during (halfway through) smoking, and two minutes after smoking. Age, gender, years smoking, cigarettes per day, body mass index (BMI), and comorbidities were also collected. The subjects were also administered the Fagerstr\u0026ouml;m nicotine dependence (FTND) test. The 60 subjects who never smoked and were approached outdoors served as the control group and their SpCO, SpO2, and HR were recorded as described above.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eBaseline SpCO, HR, and SpO2 values of smokers and non-smokers were compared, while for smokers comparisons were also made across the SpCO, HR, and SpO2 values obtained before, during, and two minutes after smoking. The relationship between baseline SpCO values and age, BMI, years smoking, cigarettes per day, and FTND scores was also investigated.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eNormality of the numeric data was tested with the Shapiro\u0026thinsp;\u0026minus;\u0026thinsp;Wilk test, and the Mann\u0026thinsp;\u0026minus;\u0026thinsp;Whitney U test was used to compare non-normal variables between two independent groups. To compare numerical variables between two dependent groups, differences between the pairs were calculated, and paired samples t-test and Wilcoxon test was performed for normal and non-normal pair differences, respectively. Pearson chi-squared and Fisher\u0026rsquo;s exact chi-squared tests were conducted to compare categorical variables between independent groups. Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation and median (Q1\u0026thinsp;\u0026minus;\u0026thinsp;Q3) values were given as the descriptive statistics for numerical data. Categorical data were presented as frequencies (n) and percentages. Pearson and Spearman correlation coefficients were calculated to evaluate the relationship between baseline SpCO, HR, and SpO2, and other numerical variables, including age, BMI, years smoking, cigarettes per day, and total FTND score. To determine the effect of smoking status (smoker or non-smoker) as a risk factor for the baseline SpCO\u0026thinsp;\u0026gt;\u0026thinsp;5%, logistic regression analysis was performed, adjusting for gender and age. Receiver operating characteristics (ROC) curve analysis was performed and area under the ROC curve (AUC) was estimated to examine the performance of SpCO, HR, and SpO2 in discriminating between smokers and non-smokers and to identify a significant cut-off value (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was accepted as statistically significant). Statistical analyses were performed using the IBM SPSS Statistics 29.0.0 software.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 165 smokers that initially agreed to participate in the study, 29 were excluded for various reasons (e.g., not waiting for the post-cigarette SpCO measurement, not smoking the entire cigarette, immediately switching to the second cigarette). As a result, the data pertaining to 136 (69.39%) smokers and 60 (30.61%) non-smoker volunteers (controls) were retained for analysis. Demographic data, including age, sex, and smoking habits, are given in Table\u0026nbsp;1. While the mean age of smokers was 32.35 ± 11.66 years, the mean age of non-smokers was 36.75 ± 14.80 years, and this difference was statistically significant (p = 0.027). There were 96 (70.6%) males and 40 (29.4%) females among smokers, and 23 (38.3%) males and 37 (61.7%) females among non-smokers (p \u0026lt; 0.001). For the smokers, the mean number of years smoking and the mean number of cigarettes per day were 13.13 ± 10.97 years and 18.93 ± 10.32, respectively (Table\u0026nbsp;1).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDemographic characteristics and smoking habits of smokers and non-smokers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSmokers\u003c/p\u003e\n \u003cp\u003e(n = 136)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-smokers\u003c/p\u003e\n \u003cp\u003e(n = 60)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96 (70.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (38.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge [years]\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32.35 ± 11.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.75 ± 14.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYears smoking\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.13 ± 10.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCigarettes per day\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18.93 ± 10.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData given with the \u003csup\u003e*\u003c/sup\u003en (%) or \u003csup\u003e#\u003c/sup\u003emean ± standard deviation.\u003c/p\u003e\n\u003cp\u003eSpCO, HR, and SpO2 measurements were obtained pre-cigarette, during smoking, and two minutes after smoking (post-cigarette) from all smokers (n = 136 for all sessions). The SpCO levels and the HR were significantly higher during the cigarette-smoking session (p = 0.006 and p \u0026lt; 0.001) and post-cigarette session (p = 0.015 and p \u0026lt; 0.001) than in the pre-cigarette session (Table\u0026nbsp;2). We also measured SpCO, HR, and SpO2 for the non-smokers. There was a significant difference between smokers and non-smokers in terms of baseline SpCO (p \u0026lt; 0.001), HR (p = 0.002), and SpO2 (p = 0.004). These measurements were significantly higher in smokers than in non-smokers (Table\u0026nbsp;3).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSpCO, HR and SpO2 levels of smokers in pre-cigarette, during cigarette and post-cigarette\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePre-cigarette\u003c/p\u003e\n \u003cp\u003e(I)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDuring cigarette\u003c/p\u003e\n \u003cp\u003e(II)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePost-cigarette\u003c/p\u003e\n \u003cp\u003e(III)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eI-II\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eI-III\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.07 ± 2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.60 ± 2.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.43 ± 2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87.26 ± 14.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92.57 ± 15.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90.35 ± 13.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpO2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.42 ± 1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.46 ± 1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.36 ± 1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData given with the mean ± standard.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison of baseline SpCO, HR and SpO2 levels between smokers and non-smokers\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSmokers\u003c/p\u003e\n \u003cp\u003e(n = 136)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon-smokers\u003c/p\u003e\n \u003cp\u003e(n = 60)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.07 ± 2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.77 ± 1.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87.26 ± 14.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80.83 ± 14.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpO2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98.42 ± 1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e97.62 ± 1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData given with the mean ± standard.\u003c/p\u003e\n\u003cp\u003eMean total score on the FTND test was 4.19 ± 2.92 for the smokers. There were 47 (34.56%) smokers with very low, 28 (20.59%) with low, 16 (11.76%) with moderate, 25 (18.38) with high, and 20 (14.71%) with very high nicotine dependence (Table\u0026nbsp;4).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eDescriptive statistics for the Fagerström nicotine dependence test\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFTND test\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDescriptive statistics\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal score\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.19 ± 2.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery low dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47 (34.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eCategories\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28 (20.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16 (11.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25 (18.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVery high dependence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20 (14.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData presented with \u003csup\u003e*\u003c/sup\u003emean ± standard, or \u003csup\u003e#\u003c/sup\u003en (%).\u003c/p\u003e\n\u003cp\u003eMean BMI of the smokers was 25.44 ± 3.83 kg/m\u003csup\u003e2\u003c/sup\u003e and 31 (22.79%) individuals in this group had at least one comorbidity. Correlation analyses indicated a positive relationship between baseline SpCO and age (r = 0.242, p = 0.005), years smoking (r = 0.260, p = 0.002), and total FTND score (r = 0.173, p = 0.044), indicating that older age, longer smoking duration, and greater nicotine dependency were associated with higher baseline SpCO levels for the smokers. Correlations between baseline SpCO and BMI (r = 0.119, p = 0.166) and baseline SpCO and number of cigarettes smoked daily (r = 0.073, p = 0.400) were not significant. There was a negative correlation between HR and age (r=-0.329, p \u0026lt; 0.001), and between HR and years smoking (r=-0.335, p \u0026lt; 0.001), indicating that older age and longer smoking duration were associated with lower baseline HR for the smokers (Table\u0026nbsp;5).\u003c/p\u003e\n\u003cdiv\u003e\n \u003cdiv align=\"left\"\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1738139563.png\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cp\u003eNo statistically significant difference was found between smokers with and without comorbidities in terms of baseline SpCO (p = 0.448), HR (p = 0.072), and SpO2 (p = 0.972) levels. (Table\u0026nbsp;6).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison of baseline SpCO, HR and SpO2 levels between those with and without comorbidities\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWithout comorbidity\u003c/p\u003e\n \u003cp\u003e(n = 105)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWith comorbidity\u003c/p\u003e\n \u003cp\u003e(n = 31)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.00 (2.00–4.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.00 (1.00–11.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88.50 ± 15.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83.03 ± 13.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpO2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.00 (98.00–99.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99.00 (98.00–99.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.972\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eData presented with mean ± standard deviation or median (Q1-Q3)\u003c/p\u003e\n\u003cp\u003eWe also performed ROC curve analysis to assess the effectiveness of SpCO, HR, and SpO2 (measured at baseline for smokers) in discriminating between smokers and non-smokers. The AUC for SpCO was 0.705, which was statistically significant, and the optimal cut-off value was 1.50. The AUC values for HR and SpO2 were also statistically significant but lower (Table\u0026nbsp;7, Fig.\u0026nbsp;3).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 7\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eROC curve analysis results for the SpCO, HR and SpO2\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ecut-off value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.467\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e79.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.533\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpO2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAUC: Area under the ROC curve\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eWe found that 113 (83.09%) of the smokers had SpCO ≤ 5%, and 134 (98.53%) had SpCO ≤ 9%. There was a significant difference between smokers and non-smokers in terms of proportions with SpCO ≤ 5%, but not for SpCO ≤ 9% (Table\u0026nbsp;8).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 8\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eComparison of smokers and non-smokers in terms of baseline SpCO groups\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBaseline SpCO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControls\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSmokers\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e≤ 5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (95.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e113 (83.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; 5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (16.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e≤ 9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e134 (98.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; 9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eWe performed binary logistic regression analysis to predict baseline SpCO category (≤ 5% / \u0026gt;5%) by taking an indicator of smoking as an independent variable and adjusting for age and gender (Omnibus test for the model: p = 0.043, Hosmer − Lemeshow test: p = 0.672). According to the obtained findings, smokers were 4.596 times more likely to have baseline SpCO levels above 5% than non-smokers (OR = 4.596, p = 0.023). Gender (p = 0.846) and age (p = 0.133) did not emerge as significant predictors of baseline SpCO (Table\u0026nbsp;9).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 9\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eResults of the logistic regression analysis for predicting baseline SpCO groups\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003ep-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e95% CI for OR\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoking status (RC: Non-smokers)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e4.596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.237\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (RC: Female)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.717\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.057\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eRC: Reference category, OR: Odds ratio, CI: Confidence interval\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eDependent variable: CO groups (category (≤ 5% /\u0026gt; 5%)\u003c/p\u003e\n\u003cp\u003eIndependent variable: Smoking status (smoker/non-smoker), gender (male/female) and age (years).\u003c/p\u003e\n\u003cp\u003ep-value for the model: p = 0.043 for the Omnibus test, p = 0.672 for the Hosmer \u0026amp; Lemeshow test\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe believe that this prospective cohort study conducted on healthy volunteer subjects provides important information on the effect of smoking on carboxyhemoglobin levels. The study provides information about the baseline SpCO values of smokers, while also offering insight into the carboxyhemoglobin changes that occur in the human body during smoking.\u003c/p\u003e \u003cp\u003eCO enters the human body through respiration. The amount of CO absorbed is directly related to the CO concentration in the inhaled air, the amount of ventilation per minute, and the duration of exposure. Inhaled CO binds to iron molecules in hemoglobin, myoglobin, and cytochrome C (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). CO toxicity can present in a variety of forms, ranging from mild symptoms to coma. The illness severity is related to the degree of CO exposure and comorbidities (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). It should be kept in mind that delayed neurologic sequelae may occur in addition to acute effects. Cigarette smoke is also an important source of CO as it contains about 3.5% CO (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, SpCO and HR values were found to be significantly higher during smoking and two minutes after smoking than before smoking, suggesting that carboxyhemoglobin levels in the blood increase during and after smoking. The increase in HR may be explained by the activation of the sympathetic system due to stress in metabolism and tissue hypoxia. Similarly, in a study conducted on 85 smokers, Schimmel et al. showed that SpCO levels increased during and after smoking (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Some older studies with a limited number of subjects have also presented results supporting those obtained in the present study (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBaseline SpCO and HR values of smokers were significantly higher than those of non-smokers (smokers: SpCO\u0026thinsp;=\u0026thinsp;3.07, nonsmokers: SpCO\u0026thinsp;=\u0026thinsp;1.77, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the ROC analysis, the AUC value for SpCO was 0.705, while the optimal cut-off value was 1.5. This was expected, given that smoking causes a chronic increase in the metabolic carboxyhemoglobin levels, leading to an increase in baseline SpCO. Over time, it causes tachycardia due to changes in vascular and pulmonary structures, which explains the difference in HR. However, it should be noted that, although the 9% limit of CO intoxication for smokers is typically cited in the literature, 98.5% of smokers in this study had a baseline SpCO below 9% and 83.1% had a baseline SpCO below 5%. These findings suggest that the 9% intoxication threshold for smokers should be re-examined and additional studies are needed. It is suggested that with SpCO values in the 5\u0026thinsp;\u0026minus;\u0026thinsp;9% range should be examined in the clinic more carefully to assess their presenting symptoms and level of CO intoxication. Schimmel et al. also raised this issue and reported similar findings (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCorrelation analysis showed that older age, longer smoking duration, and greater nicotine dependence were associated with higher baseline SpCO levels for smokers. However, BMI and number of cigarettes smoked per day were not significantly associated with their baseline SpCO values. Schimmel et al. showed that there was no significant correlation between pre-cigarette SpCO and age, years smoking, number of cigarettes smoked per day, or number of cigarettes smoked on the day of measurement. However, recent smoking was closely associated with baseline SpCO (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). On the other hand, Roth et al. showed that the number of cigarettes smoked per day was an independent predictor of baseline SpCO (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this study, cardiopulmonary diseases such as hypertension, diabetes, asthma, COPD, coronary artery disease, and heart failure were present in 22.7% of smokers. However, there was no statistically significant difference in baseline SpCO, HR, and SpO2 between smokers with and without comorbidities. Several authors cautioned that SpCO may be elevated in asthma and COPD, but the link between specific conditions and increased carboxyhemoglobin levels is insufficiently investigated (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eAs our study participants were recruited via convenience sampling, although the aim was to assess the typical smoking population, our subjects appeared to be healthier and younger. Moreover, the information on smoking habits was self-reported and may be inaccurate. Obviously, obtaining carboxyhemoglobin values via blood gas analysis would provide more reliable results, but since this is an invasive procedure, CO-oximetry was preferred. Longer observation of post-smoking SpCO values would provide more accurate information about the kinetics of smoking-induced carboxyhemoglobin, but the subjects\u0026rsquo; unwillingness to wait after smoking led us to limit this period to two minutes. We believe that additional multicenter studies with larger samples are needed to more accurately determine baseline SpCO in smokers.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe ability to use CO-oximetry as a screening tool for suspected CO poisoning in a larger population is certainly an advantage over blood gas analysis. However, the results obtained in this study suggest that the threshold value for smokers should be reconsidered, because 83.1% of smokers had a baseline SpCO below 5%. In smokers, baseline SpCO was associated with age, years of smoking, and FTND level. In addition, SpCO values considerably increased during active smoking, and the baseline SpCO values of smokers were approximately 200% higher than those of non-smokers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Prof. Dr. Deniz Sığırlı from Bursa Uludağ University for her help in the statistical analysis of our article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics Committee approval was obtained from the Ethics Committee of the Faculty of Medicine, Balikesir University (Date: 03.11.2021; Issue: 2021/247).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declared no competing interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research has not received any specific support from any funding.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026sup1;Balikesir University, Faculty of Medicine, Dept. of Emergency Medicine, Balikesir, Turkey\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSK: Data collection, conceived and designed the study, paper write-up.\u003c/p\u003e\n\u003cp\u003eTA: Statistic analyses, discussion and proofreading.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Salih Kocaoğlu.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMegas IF, Beier JP, Grieb G. The History of Carbon Monoxide Intoxication. Medicina (Kaunas). 2021 Apr 21;57(5):400. doi: 10.3390/medicina57050400. \u003c/li\u003e\n\u003cli\u003eChenoweth JA, Albertson TE, Greer MR. Carbon Monoxide Poisoning. Crit Care Clin. 2021 Jul;37(3):657-672. doi: 10.1016/j.ccc.2021.03.010.\u003c/li\u003e\n\u003cli\u003eNikkanen H, Skolnik A. Diagnosis and management of carbon monoxide poisoning in the emergency department. Emerg Med Pract. 2011 Feb;13(2):1-14; quiz 14. PMID: 22164402.\u003c/li\u003e\n\u003cli\u003eBledsoe BE, Nowicki K, Creel JH Jr, Carrison D, Severance HW. Use of pulse co-oximetry as a screening and monitoring tool in mass carbon monoxide poisoning. Prehosp Emerg Care. 2010 Jan-Mar;14(1):131-3. doi: 10.3109/10903120903349853. \u003c/li\u003e\n\u003cli\u003eRoth D, Hubmann N, Havel C, Herkner H, Schreiber W, Laggner A. Victim of carbon monoxide poisoning identified by carbon monoxide oximetry. J Emerg Med. 2011 Jun;40(6):640-2. doi: 10.1016/j.jemermed.2009.05.017.\u003c/li\u003e\n\u003cli\u003eBarker SJ, Curry J, Redford D, Morgan S. Measurement of carboxyhemoglobin and methemoglobin by pulse oximetry: a human volunteer study. Anesthesiology. 2006 Nov;105(5):892-7. doi: 10.1097/00000542-200611000-00008. Erratum in: Anesthesiology. 2007 Nov;107(5):863.\u003c/li\u003e\n\u003cli\u003eRoth D, Herkner H, Schreiber W, Hubmann N, Gamper G, Laggner AN, Havel C. Accuracy of noninvasive multiwave pulse oximetry compared with carboxyhemoglobin from blood gas analysis in unselected emergency department patients. Ann Emerg Med. 2011 Jul;58(1):74-9. doi: 10.1016/j.annemergmed.2010.12.024. \u003c/li\u003e\n\u003cli\u003eSuner S, Partridge R, Sucov A, Valente J, Chee K, Hughes A, Jay G. Non-invasive pulse CO-oximetry screening in the emergency department identifies occult carbon monoxide toxicity. J Emerg Med. 2008 May;34(4):441-50. doi: 10.1016/j.jemermed.2007.12.004. \u003c/li\u003e\n\u003cli\u003eCenters for Disease Control and Prevention. Clinical guidance for carbon monoxide (CO) poisoning after a disasters 2014. Available at: http://emergency.cdc.gov/disasters/ co_guidance.asp.\u003c/li\u003e\n\u003cli\u003eNeilsen BK, Aloi J, Sharma A. Acute Carbon Monoxide Poisoning Secondary to Cigarette Smoking in a 40-Year-Old Man: A Case Report. Am J Addict. 2019 Sep;28(5):413-415. doi: 10.1111/ajad.12939. Epub 2019 Jul 26.\u003c/li\u003e\n\u003cli\u003eForbes WHSF, Roughton FJW. The rate of carbon monoxide uptake by normal men. Am J Physiol 1945;143:594\u0026ndash;608. \u003c/li\u003e\n\u003cli\u003eAubard Y, Magne I. Carbon monoxide poisoning in pregnancy. BJOG. 2000 Jul;107(7):833-8. doi: 10.1111/j.1471-0528.2000.tb11078.x.\u003c/li\u003e\n\u003cli\u003eGajdos P, Conso F, Korach JM, Chevret S, Raphael JC, Pasteyer J, Elkharrat D, Lanata E, Geronimi JL, Chastang C. 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Lung. 2015 Apr;193(2):183-7. doi: 10.1007/s00408-015-9686-x. Epub 2015 Feb 14. \u003c/li\u003e\n\u003cli\u003eYasuda H, Yamaya M, Nakayama K, Ebihara S, Sasaki T, Okinaga S, Inoue D, Asada M, Nemoto M, Sasaki H. Increased arterial carboxyhemoglobin concentrations in chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2005 Jun 1;171(11):1246-51. doi: 10.1164/rccm.200407-914OC. Epub 2005 Mar 11.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cigarette smoking, Carbon monoxide, Poisoning, Carboxyhemoglobin, SpCO","lastPublishedDoi":"10.21203/rs.3.rs-5880374/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5880374/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe aim of this study was to investigate baseline carboxyhemoglobin saturation (SpCO) values in smokers and to show the relationship between SpCO and age, years smoking, cigarettes per day, and nicotine dependence. We also analyzed the changes in carboxyhemoglobin in the body during active smoking.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis prospective cohort study involved 136 outdoor smokers and 60 controls who had never smoked. SpCO, heart rate (HR), and oxyhemoglobin saturation (SpO2) values were recorded with a CO-oximeter device before, during, and two minutes after smoking. Changes during active smoking were analyzed, and all parameters were compared between smoking and non-smoking groups. Age, BMI, years smoking, cigarettes per day, and Fagerstr\u0026ouml;m nicotine dependence (FTND) level were correlated with baseline SpCO.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe mean age of smokers was 32.3 years (70.6% male; 22.79% with comorbidities), while the mean age of non-smokers was 36.7 years (38.3% male). The SpCO and HR were significantly higher during (p\u0026thinsp;=\u0026thinsp;0.006, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and after (p\u0026thinsp;=\u0026thinsp;0.015, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) smoking than the pre-cigarette levels. There was a significant difference between smokers (3.07) and non-smokers (1.77) in terms of baseline SpCO (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Correlation analysis showed that age, years smoking, and nicotine dependence were positively correlated with baseline SpCO. In the ROC analysis, the AUC value for SpCO was 0.705 and the optimal cut-off value was 1.50. In addition, 83% of smokers had a baseline SpCO value below 5%.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn this study, the baseline SpCO values of smokers were found to be approximately 200% higher than those of non-smokers. In addition, SpCO and HR increased during active smoking. However, 83% of smokers had a baseline SpCO below 5%, suggesting that the intoxication level of 9% in smokers should be reconsidered.\u003c/p\u003e","manuscriptTitle":"Instantaneous Carboxyhemoglobin Level Change Due to Smoking and Analysis of Baseline SpCO in Smokers","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-29 08:41:02","doi":"10.21203/rs.3.rs-5880374/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"25d3aeca-fa96-47f3-ab8c-12bd27ebead1","owner":[],"postedDate":"January 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-28T09:38:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-29 08:41:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5880374","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5880374","identity":"rs-5880374","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}