Low Respiratory Quotient Correlates with High Mortality in Patients Undergoing Mechanical Ventilation

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Cassiere, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2391735/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Apr, 2024 Read the published version in The American Journal of Emergency Medicine → Version 1 posted You are reading this latest preprint version Abstract Background Oxygen consumption (VO 2 ), carbon dioxide generation (VCO 2 ), and respiratory quotient (RQ), which is the ratio of VO 2 to VCO 2 , are critical indicators of human metabolism. To seek a link between the patient’s metabolism and pathophysiology of critical illness, we investigated the correlation of these values with mortality in critical care patients. Methods This was a prospective, observational study conducted at a suburban, quaternary care teaching hospital. Age 18 years or older healthy volunteers and patients who underwent mechanical ventilation were enrolled. A high-fidelity automation device, which accuracy is equivalent to the gold standard Douglas Bag technique, was used to measure VO 2 , VCO 2 , and RQ at a wide range of fraction of inspired oxygen (F I O 2 ). Results We included a total of 21 subjects including 8 post-cardiothoracic surgery patients, 7 intensive care patients, 3 patients from the emergency room, and 3 healthy volunteers. This study included 10 critical care patients, whose metabolic measurements were performed in the ER and ICU, and 6 died. VO 2 , VCO 2 , and RQ of survivors were 282 +/- 95 mL/min, 202 +/- 81 mL/min, and 0.70 +/- 0.10, and those of non-survivors were 240 +/- 87 mL/min, 140 +/- 66 mL/min, and 0.57 +/- 0.08 ( p = 0.34, p = 0.10, and p < 0.01), respectively. The difference of RQ was statistically significant ( p < 0.01) and it remained significant when the subjects with F I O 2 <0.5 were excluded ( p < 0.05). Conclusions Low RQ correlated with high mortality, which may potentially indicate a decompensation of the oxygen metabolism in critically ill patients. Indirect Calorimetry Oxygen Consumption Carbon Dioxide Generation Respiratory Quotient Douglas Bag Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Oxygen consumption (VO 2 ) and carbon dioxide generation (VCO 2 ) are important measures of the human metabolism ( 1 , 2 ) and respiratory quotient (RQ), which is the ratio of VCO 2 to VO 2 , can indicate an alteration of the metabolism ( 3 ). These measurements are widely used in patients with a variety of conditions, including post-surgery ( 1 ), shock ( 4 ), pulmonary and cardiac diseases ( 5 ), and critical care patients who undergo mechanical ventilation ( 2 , 6 , 7 ). Exciting data from our laboratory has demonstrated that our current understanding of aerobic respiration cannot explain the oxygen consumption measured in rats resuscitated from prolonged cardiac arrest ( 8 , 9 ), however few studies have focused on these critical measurements in critically ill patients. Indirect calorimetry is a non-invasive method, in which VO 2 and VCO 2 are calculated from concentrations of oxygen and carbon dioxide of inhalation and exhalation ( 10 – 12 ). Since it is non-invasive, indirect calorimetry has been widely used by clinicians ( 13 , 14 ) and translational researchers ( 15 – 18 ). However, owing to a lack of gold standard and unreliability of measurements particularly at high concentrations of inspired oxygen, there have been few studies on critically ill patients, who often require high-level oxygen as it is mandated in life-supporting situations ( 6 , 7 , 19 ). One of the reference standards is the Douglas Bag (DB) collection technique that has been routinely used for a long time ( 19 , 20 ). The central focus of this method is the accuracy of gas concentrations ( 12 , 18 ). The DB technique uses collection bags that equilibrate gas concentrations while gases are inside the bags. The DB technique exerts reliable numbers especially when measuring a gas concentration that dynamically changes. The gas concentrations of exhalation change during a breath; therefore, the DB method allows for reliable measurements when the accuracy of VO 2 , VCO 2 , and RQ is in need ( 19 ). We developed an automation system that enables repeat measurements of VO 2 , VCO 2 , and RQ, which accuracy is equivalent to those measured by the DB method. Using this system, we sought the values of VO 2 , VCO 2 , and RQ in critically ill patients who underwent mechanical ventilation. Based on our findings from a lethal cardiac arrest model in rats, we hypothesized that critically ill patients might have altered metabolism that could be identified as an imbalance between VCO 2 and VO 2 , leading to a decrease in RQ. To the best of our knowledge, this is the first study that applied repeat measurements of VO 2 , VCO 2 , RQ by using the highly accurate and equivalent method of the DB technique and we demonstrate the results of metabolic measurements in patients undergoing mechanical ventilation. Materials And Methods Study Design This was a prospective observational study. Age 18 years or older healthy volunteers and patients who underwent mechanical ventilation were enrolled. The study protocol was approved by the Institutional Review Board. Written informed consent for participation was obtained from volunteers, patients, or next of kin prior to the procedures. If a patient did not hold a capacity for consent or did not have a legally authorized representative or next of kin, the patient was enrolled with waived consent. We excluded patients whose PEEP setting was higher than 10 cm H 2 O. Our algorithm enabled measurements of VO 2 , VCO 2 , and RQ at a variety range of fraction of inspired oxygen (F I O 2 ) ( 21 ) and therefore, no upper limit was made on an F I O 2 setting. Primary endpoint of this study was to observe a change in RQ between survivors and non-survivors. The RQ indicates a balance between oxygen and carbon dioxide metabolism, therefore RQ was the primary measurement in this study and VO 2 and VCO 2 were the secondary. The subjects were divided into two groups according to the survival outcomes and the values of metabolic measurements including RQ, VO 2 , and VCO 2 were compared between the groups. Douglas Bag collection Ten minutes were given to all patients/volunteers for acclimating to the apparatus before starting a measurement. A commercially available gas analyzer (GF-210R Multi-Gas Module, Nihon Kohden Corporation, Irvine, CA, USA) was used to measure concentrations of oxygen and carbon dioxide. The gases were sampled from a mechanical ventilator (AVEA® ventilator, CareFusion, San Diego, CA, USA). Healthy volunteers breathed by the mechanical ventilator through a face sealed mask or a mouse peace plus nose clip. The healthy volunteers were given enough time to synchronize their breaths with mechanical ventilation. The inhalation and exhalation gases were separately collected into two bags (4 liters, polyvinylidene fluoride gas collection bag, Cole-Parmer, Vernon Hills, IL and 50 liters, polyvinyl chloride gas collection bag, Harvard Apparatus, Holliston, MA, respectively). A 4-L bag was used for the collection of the inhalation gas with an adaptor placed 4 inches from a Y piece connector of the mechanical ventilation circuit. We collected the exhalation gas by connecting the 50-L bag to the exhaust port, meaning that we collected the whole exhalation gas over a period of experiment. The valves of the collection bags for inhalation and exhalation were opened simultaneously and the gases were collected for approximately 5–7 minutes until the bags were 80% filled. The temperature, humidity, and atmospheric pressure were recorded during the gas collection. To reduce the humidity level of the gas, we placed both bags in a freezer and lowered the gas temperature <-20 °C. The humidity became under detectable level when the gases went into the gas analyzer. The gas humidity was measured by a hygrometer (Ebro TFH620 Compact Thermohygrometer, Cole-Parmer, Vernon Hills, IL) attached to the gas analyzer. Ventilation settings of the patients/volunteers including a minute ventilation volume of exhalation, inhalation to exhalation (I:E) ratio, leak rate, and bias flow, were recorded simultaneously with the gas collection. Automation system The DB collection method is the gold standard; however, it allows for a point measurement. Due to the increment need for continuous and repeat measurements, we developed an automation system with the same methodological principle of the aforementioned DB technique. The same gas analyzer was used to measure the concentrations of oxygen and carbon dioxide. The measurement was performed at bedside, which enabled a real-time and continuous collection of data. The sampling adaptor was inserted inside the ventilator circuit to collect the inhalation gas. The connector was placed 4 inches from a Y piece connector attached to the patient’s endotracheal tube/volunteer’s face mask. The inhalation gas was collected at a flow rate of 200 mL/min, which was regulated by the gas analyzer. A dehumidification device (DHU-1000 Dehumidification Unit, Nihon Kohden Corporation, Tokyo, Japan) was set in conjunction with the gas analyzer: the dehumidification unit was intended for use in dehumidifying a sample gas. This unit included switching valves to select inhalation or exhalation. A 100-mL mixing chamber was attached to the exhaust port. This chamber was engineered to obtain the concentration of whole-gas from a partial sampling. Our system was first validated, and the accuracy was confirmed equivalent to the DB technique ( 22 ). Calculations and Analysis F I O 2 , F E O 2 (fraction of expired oxygen), F I CO 2 (fraction of inspired carbon dioxide), F E CO 2 (fraction of expired carbon dioxide), in-circuit humidity and temperature in the dehumidification device, and ambient pressure and temperature around the mechanical ventilator circuit were measured. A minute ventilation volume of exhalation (V E ), I:E ratio, and bias flow were recorded from the mechanical ventilator. For the automation system, F E O 2 and F E CO 2 were calculated from the gas concentrations measured at the ventilator exhaust port. The gas concentrations of inhalation and exhalation were measured alternately, and the duty cycle was 15 minutes. The inhalation gas was measured for the first 6 minutes of the duty cycle and the exhalation was for the second 9 minutes. The initial 4 minutes of each phase were discarded. If there was a significant change in F I O 2 within a duty cycle, the value was excluded from our analysis. The time series of F I O 2 was calculated from the values of pre- and post-F I O 2 . The following equations are used in this study: $$R=\frac{VI}{VE}$$ 1 $$VO2=VI\times FIO2-VE\times FEO2$$ 2 $$VCO2=VE\times FEO2-VI\times FIO2$$ 3 where V I is a minute ventilation volume of inhalation and V E is that of exhalation. F I CO 2 is zero since the inhalation gas does not contain CO 2 . The VO 2 , VCO 2 , and RQ are then transformed as follows: $$VO2=\left(R\times FIO2-FEO2\right)\times VE$$ 4 $$VCO2=FECO2\times VE$$ 5 $$RQ=\frac{VCO2}{VO2}$$ 6 R is generally derived from the Haldane transformation with the assumption that nitrogen is neither produced nor retained by the body, and that no gases are present other than O 2 , CO 2 , and nitrogen ( 23 ). Because the denominator includes F I O 2 and it goes to zero as F I O 2 increases to 1.0, R increases to infinite number when F I O 2 is 1.0. Therefore, the Haldane transformation limits F I O 2 generally up to 0.6. This is a significant limitation in critical care medicine, in which patients normally require high F I O 2 . Therefore, we developed a method for measuring R and sought the number of R by using our rodent model ( 21 ). Our results suggested that R was not 1.0 and so V I was not equal to V E . While our result was in line with the concept of the Haldane transformation suggesting V I ≠V E , the data from our report supported that R might be a constant in lieu of a dependent variable affected by F I O 2 . Our results from the rodent model showed that R was 1.0081+/-0.0017 at an F I O 2 of 0.3 and 1.0092+/-0.0029 at an F I O 2 of 1.0. We sought a value of human R calculated from the values obtained from previous reports ( 23 , 24 ) and determined it as 1.0097 in this study. Statistical Analysis We reported data as mean and standard deviation (SD) and descriptive statistics were used. The values were reported as standard temperature and pressure and dry (STPD). Unpaired t-test was used for comparison between two groups. There were no missing values in this study. We planned to enroll 20 patients in this explanatory phage of the study. According to the values of RQ from our rodent model ( 8 ), n = 4 for each outcome group would provide the statistical significancy with a power of 0.8 and α < 0.05. However, owing to the uncertainty of RQ values and SD range in human samples, the sample number was anyway set at n = 20 in this study. As high F I O 2 lowers RQ ( 21 ), there is a possibility that high F I O 2 may bias the results. Therefore, the sensitivity analysis of this study was the secondary analysis including only patients, whose F I O 2 was 0.5 and greater. Prism for Mac version 9 (GraphPad Software, San Diego, CA) and SPSS version 27 (IBM, Armonk, NY) were used for statistical analysis, and P values less than 0.05 was considered statistically significant. Results One data was excluded due to a technical error (damaged equipment) and data from 21 subjects were included in the analysis (Fig. 1 ). Table 1 shows baseline characteristics. Out of 21 subjects, 8 were patients post cardiothoracic surgery, 7 were patients in the intensive care units (ICU), 3 were those in the emergency room (ER), and 3 were healthy volunteers. Sequential organ failure assessment (SOFA) score, blood lactate level (mmol/L), and P/F ratio (arterial partial oxygen pressure to F I O 2 ) were obtained at ICU admission, if applicable. None of the post-cardiothoracic surgery patients had major adverse events. This study included 10 critical care patients, whose metabolic measurements were performed in the ER or ICU, and 6 died. Out of the 10 critical care patients, 4 had cardiac arrest before the enrollment. We first validated the device measurements. The values of VO 2 , VCO 2 , and RQ measured by the automation device were compared with those by the DB technique. The mean differences of VO 2 , VCO 2 , and RQ between the methods were 1.5+/-6.6: 3%, 2.3+/-5.1: 5%, 0.008+/-0.030: 4%, respectively. The inter-rater reliability of these two methods on VO 2 , VCO 2 , RQ were calculated as 0.999, 0.993, and 0.993, respectively. Collectively, these data support that VO 2 , VCO 2 , and RQ are interchangeable between the two methods. Table 1 Characteristics of Study Subjects and Fraction of Inspired Oxygen at Measurement Subject Test Subject Type Site Age Gender Diagnosis SOFA Lactate P/F ratio Discharge Outcome Method F I O 2 1 1 Patient CTICU 75 Male CAD 2 2.5 305 Alive DB 0.50 2 1 Patient CTICU 70 Male CAD 3 1.9 251 Alive DB 0.50 3 1 Patient CTICU 61 Male CAD, MR, TR 3 2.1 357 Alive DB 0.50 4 1 Patient CTICU 37 Male Endocarditis 2 4.2 261 Alive DB 0.50 5 1 Volunteer Lab 32 Male N/A N/A N/A N/A N/A DB 0.21 2 Volunteer Lab DB 0.90 6 1 Patient ER 56 Female CA, DKA 8 2.5 49 Death DB 0.90 7 1 Volunteer Lab 44 Male N/A N/A N/A N/A N/A DB 0.21 2 Volunteer Lab DB 0.90 8 1 Volunteer Lab 40 Male N/A N/A N/A N/A N/A DB 0.21 2 Volunteer Lab DB 0.90 9 1 Patient ER 79 Male CA, Septic Shock, NSTEMI 4 6.7 269 Alive DB 0.90 10 1 Patient SICU 73 Male CA, SAH, Seizure, Hypoxic Respiratory Failure 5 1.6 208 Death DB 0.90 11 1 Patient CCU 87 Male CA, TIA, Multiorgan Dysfunction 7 5.3 405 Death DB 0.90 12 1 Patient CTICU 52 Male CAD 3 2 233 Alive Device 1.00 13 1 Patient CTICU 63 Male CAD 3 1.7 155 Alive Device 1.00 14 1 Patient CTICU 72 Male Aortic Aneurysm, Aortic Valve Stenosis 5 1.7 207 Alive Device 1.00 15 1 Patient CTICU 62 Male CAD 7 1.9 296 Alive Device 1.00 16 1 Patient ER 85 Female Aspiration Pneumonia, Respiratory Arrest 6 7.1 277 Death Device 1.00 17 1 Patient MICU 76 Male Multiple Myeloma, Renal Failure 9 1.4 392 Death Device 0.60 18 1 Patient MICU 62 Male Cirrhosis, Pulmonary Fibrosis, Respiratory Failure 12 2.9 68 Death Device 1.00 19 1 Patient MICU 92 Male Pneumonia, Vocal Cord Paralysis, Respiratory Failure 4 1.1 260 Alive Device 1.00 20 1 Patient MICU 70 Female Airway Compromise, Aspiration Pneumonia 0 1 403 Alive Device 0.30 21 1 Patient MICU 71 Female COPD exacerbation, Hypercapnia 0 5.7 633 Alive Device 0.25 Sequential Organ Failure Assessment (SOFA) score, blood lactate level (mmol/L), and arterial partial oxygen pressure / F I O 2 (P/F) ratio were calculated from the values at ICU admission. CTICU stands for cardiothoracic intensive care unit; ER, emergency room; SICU, surgical intensive care unit; CCU, coronary care unit; MICU, medical intensive care unit; CAD, coronary artery disease; MR, mitral valve regurgitation; TR, tricuspid valve, regurgitation; CA, cardiac arrest; DKA, diabetic ketoacidosis; NSTEMI, non-ST elevation myocardial infarction; TIA, transient ischemic attack; COPD, chronic obstructive pulmonary disease; N/A, not applicable; DB, Douglas Bag. Low RQ can Indicate Severity of Patients Out of 18 patients who were participated in this study, 6 died. High SOFA score at ICU admission was associated with worse outcome ( p < 0.01), while there were no statistical differences in initial blood lactate levels or P/F ratio. We obtained 24 metabolic measurements from total 21 subjects, who had a variety of back grounds (healthy volunteers to patients with critical illnesses, Fig. 2 ). Including data from the healthy volunteers, VO 2 , VCO 2 , and RQ of survivors were 282+/-95 mL/min, 202+/-81 mL/min, and 0.70+/-0.10, and those of non-survivors were 240+/-87 mL/min, 140+/-66 mL/min, and 0.57+/-0.08, respectively ( p = 0.34, p = 0.10, and p < 0.01, Fig. 3 ). Among the metabolic measurements, only RQ had a statistically significant difference between the survivors and non-survivors. The difference in RQ remained statistically significant after excluding data from healthy volunteers. As high F I O 2 lowers RQ, there was a potential bias by high F I O 2 . Therefore, we excluded the values from patients with F I O 2 <0.5 and we performed subgroup analysis including only patients with F I O 2 ≥0.5. In this subgroup analysis, VO 2 , VCO 2 , and RQ of survivors were 254+/-59 mL/min, 169+/-57 mL/min, and 0.66+/-0.08, and those of non-survivors were 240+/-87 mL/min, 140+/-66 mL/min, and 0.57+/-0.08, respectively ( p = 0.71, p = 0.36, and p < 0.05, Fig. 4 ). The non-survivors had significantly lower RQ than the survivors. As we used equations ( 4 ) and ( 6 ), R greater than 1.0 contributes to increasing VO 2 and lowering RQ. Therefore, in order to reduce a bias, we sought VO 2 , VCO 2 , and RQ that were calculated with R = 1.0, even though V I ≠V E (R≠1). We analyzed 24 metabolic measurements obtained from total 21 subjects and VO 2 , VCO 2 , and RQ of survivors were 238+/-86 mL/min, 202+/-81 mL/min, and 0.84+/-0.06, and those of non-survivors were 179+/-80 mL/min, 140+/-66 mL/min, and 0.78+/-0.03, respectively. The non-survivors had significantly lower RQ than the survivors ( p < 0.05). Discussion We developed an automation device for measuring accurate F I O 2 , F E O 2 , and F E CO 2 in human subjects undergoing mechanical ventilation. These gas concentrations are critical elements to collecting accurate numbers of VO 2 , VCO 2 , and RQ. The accuracy of our system was validated, and it was equivalent to the gold standard method, the DB collection technique ( 22 ). In addition, our automation system allows for repeat measurements as opposed to the DB technique that limits the number of collections due to its complexity in the methodology. By using both automation device and DB technique, we were able to collect 24 metabolic data from total 21 human subjects including healthy volunteers, and post-surgical and critical care patients The volume ratio of inhalation to exhalation defined as R in this study was essential to comparing the values of VO 2 and RQ among patients with different F I O 2 levels. There is a significant technical difficulty of measuring the small differences between V I and V E . Therefore, V I is commonly calculated from the Haldane transformation, which unfortunately limits F I O 2 generally up to 0.6, and this limitation makes it impossible to compare VO 2 and RQ between low and high F I O 2 . Assuming V I equals V E and ignoring this small difference eliminate the concern. However, failure to account for this small difference can erroneously decrease VO 2 by 17% ( 12 ), if V I is actually not equal to V E , and the error even more propagates as F I O 2 is higher. The adequacy of the Haldane transformation ( 23 ) supports that V I is not equal to V E (V I ≠V E and R≠1). Values of the current study are affected by R. Therefore, we also analyzed our data by using R = 1 (V I =V E ), even though this assumption is not in line with the consensus. In this study, we were able to draw the robust conclusion from results using both scenario calculations (V I ≠V E and V I =V E ). The important finding of this study was that low RQ correlated with patient’s mortality. As it is described above, if the small difference between V I and V E is not properly taken into account, the uncertainty of VO 2 and RQ hinders a comparison between those from subjects with different F I O 2 levels. Because our previous data indicates that R is not affected by F I O 2 , we can reasonably use a constant number (1.0097) to both normal and high F I O 2 . However, R > 1.0 impacts the calculation of VO 2 and decreases RQ. Therefore, we performed the secondary analysis that included only patients with F I O 2 ≥0.5 and the results were still statistically significant in this subgroup analysis. Our data have become compelling, and we are confident of the conclusion. Oxygen molecules are substrates for biological and enzymatic reactions and so the oxygen utilization is theoretically O 2 concentration dependent. We observed that high F I O 2 increased VO 2 without a concomitant increase of VCO 2 resulting in decreased RQ ( 21 ). In addition, the finding was more remarkable in critical illness such as post-cardiac arrest ( 8 ). Notably, Uber et al. reported that post-cardiac arrest patients had low RQs and a large percentage of patients (> 70%) showed the number of RQ below physiologic norms (< 0.7) ( 25 ). The mechanisms of this phenotype have not yet been cleared, but our rodent data ( 9 ) could support an idea of hyperoxia-induced production of mitochondrial reactive oxygen species. The other factor that can contribute to gas exchange is cutaneous respiration. It accounts for 2% of the lung respiration in humans ( 26 ). In a condition that the skin has higher oxygen than atmosphere, the oxygen is diffused from the skin to the atmosphere. Because the concentration gradient of carbon dioxide is not affected by a change in F I O 2 , the diffusion mechanism can contribute to increased VO 2 but not VCO 2 when high F I O 2 is used. In this mode, the mechanism is oxygen diffusion rather than consumption. Further mechanistic studies will warrant deeper understanding of oxygen metabolism in critically ill patients. This study is subject to several limitations. The number of samples, first and foremost, is limited in this study owing to the nature of explanatory design. A methodological complexity of the DB technique results in a lack of gold standard that hinders a development of science in human oxygen metabolism. We have high hope that our automation device becomes a breakthrough and leads to more and more numbers of both phenotypic and mechanistic studies on oxygen metabolism in humans. Conclusions We developed an automation system that enables repeat measurements of VO 2 , VCO 2 , and RQ. Low RQ correlated with high mortality, which may potentially indicate decompensated oxygen metabolism in critically ill patients. Declarations ACKNOWLEDGEMENTS None AUTHORS’ CONTRIBUTIONS K. Shinozaki has full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis; K. Shinozaki, K. Saeki, JWL, LBB designed the conception of the study; K. Shinozaki, PJY, QZ, DMR, JJ, and YO performed acquisition of data and K. Shinozaki analyzed data; all authors made interpretations of data; all authors added intellectual content of revisions to the paper and gave full approval of the version to be published. Saeki belongs to Nihon Kohden Innovation Center, INC and Goto to Nihon Kohden Corporation as employee. This does not invade the authors’ adherence to all the Journal's policies. Shinozaki and Becker own intellectual property of metabolic measurement in critically ill patients. Shinozaki has grant/research supported by Nihon Kohden Corp. Becker has grant/research supported by Philips Healthcare, the National Institutes of Health, Nihon Kohden Corp., BeneChill Inc., Zoll Medical Corp, Medtronic Foundation, and patents in the areas of hypothermia induction and perfusion therapies. The other authors have no disclosures. ETHICAL APPROVAL The study protocol was approved by the Institutional Review Board. Written informed consent for participation for study and publication of data was obtained from volunteers, patients, or next of kin prior to the procedures. If a patient did not hold a capacity for consent or did not have a legally authorized representative or next of kin, the patient was enrolled with waived consent. FUNDING This research was supported by the research grant of Nihon Kohden Corporation. AVAILABILITY OF DATA AND MATERIALS K. Shinozaki is the corresponding author and has full access to all data in the study. 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Saeki belongs to Nihon Kohden Innovation Center, INC and Goto to Nihon Kohden Corporation as employee. This does not invade the authors’ adherence to all the Journal's policies. Shinozaki and Becker own intellectual property of metabolic measurement in critically ill patients. Shinozaki has grant/research supported by Nihon Kohden Corp. Becker has grant/research supported by Philips Healthcare, the National Institutes of Health, Nihon Kohden Corp., BeneChill Inc., Zoll Medical Corp, Medtronic Foundation, and patents in the areas of hypothermia induction and perfusion therapies. The other authors have no disclosures. 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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-2391735","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":163761788,"identity":"87f8d151-ca50-4fa5-bc8e-a57c75ebc092","order_by":0,"name":"Koichiro Shinozaki","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/0lEQVRIiWNgGAWjYDACCcYGBoYKBgN+VFGCWs4wGEg2ICvGrwWIGdsYDAwOEGE+GMjPbm578HFerbHBAfaHDxh32NQxSDcfYLDcgVuLwZ2D7YYztx03kzzAY2zAeCZNgkHmWAKD5Bk8WiQS26R5tx2z4TvAwyb9t+2wBINEjgGDZBseh80AaZlzzIbhAPszCca2/0At+R/wamG4AdLSUGMmcIDBDKjlAMgWBrxaDIBaJGccO2As2QzyS1uyZJtEmsEBfH6Rn5H+TOJDTZ1hP3s7MMTa7Pj5JZIfPpbEE2JQcJiBgRnKZANxYRGLB9Shchk/EtYyCkbBKBgFIwcAAO8QSjYgfytPAAAAAElFTkSuQmCC","orcid":"","institution":"Zucker School of Medicine at Hofstra/Northwell","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Koichiro","middleName":"","lastName":"Shinozaki","suffix":""},{"id":163761790,"identity":"e8fcdc5e-9d87-42d3-860a-2703f9124ff1","order_by":1,"name":"Pey-Jen Yu","email":"","orcid":"","institution":"North Shore University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pey-Jen","middleName":"","lastName":"Yu","suffix":""},{"id":163761792,"identity":"f7786a1d-f785-4d16-8a58-ae03a05fd179","order_by":2,"name":"Qiuping Zhou","email":"","orcid":"","institution":"Long Island Jewish Medical Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Qiuping","middleName":"","lastName":"Zhou","suffix":""},{"id":163761794,"identity":"5729b565-b991-44d3-9743-42d48e87eeae","order_by":3,"name":"Hugh A. Cassiere","email":"","orcid":"","institution":"North Shore University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hugh","middleName":"A.","lastName":"Cassiere","suffix":""},{"id":163761795,"identity":"7bda6970-4c4c-4344-a44f-b1610204c818","order_by":4,"name":"Stanley John","email":"","orcid":"","institution":"North Shore University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Stanley","middleName":"","lastName":"John","suffix":""},{"id":163761796,"identity":"3ff1b5fd-5212-4b97-be80-cf5dcede0040","order_by":5,"name":"Daniel M. Rolston","email":"","orcid":"","institution":"North Shore University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"M.","lastName":"Rolston","suffix":""},{"id":163761797,"identity":"36a7fd12-ed48-465a-8c4d-85f33d4a922f","order_by":6,"name":"Nidhi Garg","email":"","orcid":"","institution":"South Shore University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Nidhi","middleName":"","lastName":"Garg","suffix":""},{"id":163761798,"identity":"09756077-e5a7-43f5-b3dd-8b63c2a0b131","order_by":7,"name":"Timmy Li","email":"","orcid":"","institution":"Zucker School of Medicine at Hofstra/Northwell","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Timmy","middleName":"","lastName":"Li","suffix":""},{"id":163761799,"identity":"434a5082-7661-4c8a-85e2-2cc8cb67917c","order_by":8,"name":"Jennifer Johnson","email":"","orcid":"","institution":"North Shore University Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jennifer","middleName":"","lastName":"Johnson","suffix":""},{"id":163761800,"identity":"2f53535c-7a0e-4f94-b346-2030e54046cb","order_by":9,"name":"Kota Saeki","email":"","orcid":"","institution":"Nihon Kohden Innovation Center","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kota","middleName":"","lastName":"Saeki","suffix":""},{"id":163761801,"identity":"04ffd9bf-d8c3-4414-b737-3dec90f06f88","order_by":10,"name":"Taiki Goto","email":"","orcid":"","institution":"Nihon Kohden Corporation","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Taiki","middleName":"","lastName":"Goto","suffix":""},{"id":163761803,"identity":"022aa0c9-2f57-4e0b-b476-d273fd7fee7b","order_by":11,"name":"Yu Okuma","email":"","orcid":"","institution":"Feinstein Institutes for Medical Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Okuma","suffix":""},{"id":163761805,"identity":"428d6691-1cf5-435e-a3f7-b1f7316b0107","order_by":12,"name":"Santiago J. Miyara","email":"","orcid":"","institution":"Feinstein Institutes for Medical Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Santiago","middleName":"J.","lastName":"Miyara","suffix":""},{"id":163761807,"identity":"1f7c5959-c36b-4658-b0ef-69d8d9e8b32d","order_by":13,"name":"Kei Hayashida","email":"","orcid":"","institution":"Feinstein Institutes for Medical Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Kei","middleName":"","lastName":"Hayashida","suffix":""},{"id":163761809,"identity":"1d836ffd-f52d-416d-b280-17cfd448e3e6","order_by":14,"name":"Tomoaki Aoki","email":"","orcid":"","institution":"Feinstein Institutes for Medical Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tomoaki","middleName":"","lastName":"Aoki","suffix":""},{"id":163761811,"identity":"a1531805-572d-45d2-b81f-abb481d6beb8","order_by":15,"name":"Vanessa Wong","email":"","orcid":"","institution":"Feinstein Institutes for Medical Research","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Vanessa","middleName":"","lastName":"Wong","suffix":""},{"id":163761812,"identity":"445846a3-c006-49c6-ba27-c18e3042bee4","order_by":16,"name":"Ernesto P. Molmenti","email":"","orcid":"","institution":"Zucker School of Medicine at Hofstra/Northwell","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ernesto","middleName":"P.","lastName":"Molmenti","suffix":""},{"id":163761813,"identity":"073b767b-ad25-468f-820c-eeba07b28a84","order_by":17,"name":"Joshua Lampe","email":"","orcid":"","institution":"ZOLL Medical","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Lampe","suffix":""},{"id":163761814,"identity":"a329573e-7192-46d4-9773-256bc7e9470d","order_by":18,"name":"Lance Becker","email":"","orcid":"","institution":"Zucker School of Medicine at Hofstra/Northwell","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lance","middleName":"","lastName":"Becker","suffix":""}],"badges":[],"createdAt":"2022-12-19 02:44:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2391735/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2391735/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1016/j.ajem.2024.01.003","type":"published","date":"2024-04-01T04:56:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":31110143,"identity":"b64ecc13-2356-460e-9f0d-263deca0b135","added_by":"auto","created_at":"2023-01-04 17:51:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":29994,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow Diagram of the Study Progress.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"F1.png","url":"https://assets-eu.researchsquare.com/files/rs-2391735/v1/cd978ffbfc618404a275134b.png"},{"id":31110145,"identity":"82e2fc02-360b-4f68-8fe3-0ae5c033d1ed","added_by":"auto","created_at":"2023-01-04 17:51:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, VCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, and RQ in Study Subjects. \u003c/strong\u003eA VO\u003csub\u003e2\u003c/sub\u003e at standard temperature and pressure and dry (STPD). B VCO\u003csub\u003e2\u003c/sub\u003e at STPD. C RQ. N = 3 in healthy volunteers, n = 8 in post-surgical, n = 4 in post-cardiac arrest, and n = 6 in ICU patients. Numbers are expressed as mean +/- SD.\u003c/p\u003e","description":"","filename":"F2.png","url":"https://assets-eu.researchsquare.com/files/rs-2391735/v1/975bd17663efc7b8c79a78a4.png"},{"id":31110655,"identity":"eba2fd27-2504-4bd8-8f6b-d573f1cb9e10","added_by":"auto","created_at":"2023-01-04 17:59:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38294,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, VCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, and RQ in Survivors and Non-survivors.\u003c/strong\u003e A VO\u003csub\u003e2\u003c/sub\u003e at STPD. B VCO\u003csub\u003e2\u003c/sub\u003e at STPD. C RQ. Survivors (n = 15) included healthy volunteers and non-survivors (n = 6) were ICU patients. Numbers are expressed as mean +/- SD. * indicates P \u0026lt; 0.05;\u0026nbsp; **, P \u0026lt; 0.01; ns, no significancy.\u003c/p\u003e","description":"","filename":"F3.png","url":"https://assets-eu.researchsquare.com/files/rs-2391735/v1/a937227f60f282b154cba197.png"},{"id":31110144,"identity":"4d8adfce-62ee-4d80-893a-8e76e68c8aa3","added_by":"auto","created_at":"2023-01-04 17:51:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":42827,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, VCO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e, and RQ at F\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003eI\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003eO\u003c/strong\u003e\u003csub\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sub\u003e\u003cstrong\u003e ³ 0.5 in Survivors and Non-survivors. \u003c/strong\u003eThree healthy volunteers and 3 patients, whose F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e was lower than 0.5, were excluded from the analysis. A VO\u003csub\u003e2\u003c/sub\u003e at STPD. B VCO\u003csub\u003e2\u003c/sub\u003e at STPD. C RQ. Numbers are expressed as mean +/- SD. * indicates P \u0026lt; 0.05;\u0026nbsp; **, P \u0026lt; 0.01; ns, no significancy.\u003c/p\u003e","description":"","filename":"F4.png","url":"https://assets-eu.researchsquare.com/files/rs-2391735/v1/394a22266040889714269f2a.png"},{"id":53051147,"identity":"687e4f45-5c73-4cb5-9831-a782020dbe60","added_by":"auto","created_at":"2024-03-20 04:56:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":610210,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2391735/v1/ab2642c6-caf8-43bc-9377-b06674b7b6a6.pdf"}],"financialInterests":"Competing interest reported. Saeki belongs to Nihon Kohden Innovation Center, INC and Goto to Nihon Kohden Corporation as employee. This does not invade the authors’ adherence to all the Journal's policies. Shinozaki and Becker own intellectual property of metabolic measurement in critically ill patients. Shinozaki has grant/research supported by Nihon Kohden Corp. Becker has grant/research supported by Philips Healthcare, the National Institutes of Health, Nihon Kohden Corp., BeneChill Inc., Zoll Medical Corp, Medtronic Foundation, and patents in the areas of hypothermia induction and perfusion therapies. The other authors have no disclosures.","formattedTitle":"Low Respiratory Quotient Correlates with High Mortality in Patients Undergoing Mechanical Ventilation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eOxygen consumption (VO\u003csub\u003e2\u003c/sub\u003e) and carbon dioxide generation (VCO\u003csub\u003e2\u003c/sub\u003e) are important measures of the human metabolism (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) and respiratory quotient (RQ), which is the ratio of VCO\u003csub\u003e2\u003c/sub\u003e to VO\u003csub\u003e2\u003c/sub\u003e, can indicate an alteration of the metabolism (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). These measurements are widely used in patients with a variety of conditions, including post-surgery (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), shock (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e), pulmonary and cardiac diseases (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), and critical care patients who undergo mechanical ventilation (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Exciting data from our laboratory has demonstrated that our current understanding of aerobic respiration cannot explain the oxygen consumption measured in rats resuscitated from prolonged cardiac arrest (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e), however few studies have focused on these critical measurements in critically ill patients.\u003c/p\u003e \u003cp\u003eIndirect calorimetry is a non-invasive method, in which VO\u003csub\u003e2\u003c/sub\u003e and VCO\u003csub\u003e2\u003c/sub\u003e are calculated from concentrations of oxygen and carbon dioxide of inhalation and exhalation (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Since it is non-invasive, indirect calorimetry has been widely used by clinicians (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) and translational researchers (\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, owing to a lack of gold standard and unreliability of measurements particularly at high concentrations of inspired oxygen, there have been few studies on critically ill patients, who often require high-level oxygen as it is mandated in life-supporting situations (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). One of the reference standards is the Douglas Bag (DB) collection technique that has been routinely used for a long time (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The central focus of this method is the accuracy of gas concentrations (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The DB technique uses collection bags that equilibrate gas concentrations while gases are inside the bags. The DB technique exerts reliable numbers especially when measuring a gas concentration that dynamically changes. The gas concentrations of exhalation change during a breath; therefore, the DB method allows for reliable measurements when the accuracy of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ is in need (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe developed an automation system that enables repeat measurements of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ, which accuracy is equivalent to those measured by the DB method. Using this system, we sought the values of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ in critically ill patients who underwent mechanical ventilation. Based on our findings from a lethal cardiac arrest model in rats, we hypothesized that critically ill patients might have altered metabolism that could be identified as an imbalance between VCO\u003csub\u003e2\u003c/sub\u003e and VO\u003csub\u003e2\u003c/sub\u003e, leading to a decrease in RQ. To the best of our knowledge, this is the first study that applied repeat measurements of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, RQ by using the highly accurate and equivalent method of the DB technique and we demonstrate the results of metabolic measurements in patients undergoing mechanical ventilation.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis was a prospective observational study. Age 18 years or older healthy volunteers and patients who underwent mechanical ventilation were enrolled. The study protocol was approved by the Institutional Review Board. Written informed consent for participation was obtained from volunteers, patients, or next of kin prior to the procedures. If a patient did not hold a capacity for consent or did not have a legally authorized representative or next of kin, the patient was enrolled with waived consent. We excluded patients whose PEEP setting was higher than 10 cm H\u003csub\u003e2\u003c/sub\u003eO. Our algorithm enabled measurements of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ at a variety range of fraction of inspired oxygen (F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and therefore, no upper limit was made on an F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e setting.\u003c/p\u003e \u003cp\u003ePrimary endpoint of this study was to observe a change in RQ between survivors and non-survivors. The RQ indicates a balance between oxygen and carbon dioxide metabolism, therefore RQ was the primary measurement in this study and VO\u003csub\u003e2\u003c/sub\u003e and VCO\u003csub\u003e2\u003c/sub\u003e were the secondary. The subjects were divided into two groups according to the survival outcomes and the values of metabolic measurements including RQ, VO\u003csub\u003e2\u003c/sub\u003e, and VCO\u003csub\u003e2\u003c/sub\u003e were compared between the groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDouglas Bag collection\u003c/h2\u003e \u003cp\u003eTen minutes were given to all patients/volunteers for acclimating to the apparatus before starting a measurement. A commercially available gas analyzer (GF-210R Multi-Gas Module, Nihon Kohden Corporation, Irvine, CA, USA) was used to measure concentrations of oxygen and carbon dioxide. The gases were sampled from a mechanical ventilator (AVEA\u0026reg; ventilator, CareFusion, San Diego, CA, USA). Healthy volunteers breathed by the mechanical ventilator through a face sealed mask or a mouse peace plus nose clip. The healthy volunteers were given enough time to synchronize their breaths with mechanical ventilation. The inhalation and exhalation gases were separately collected into two bags (4 liters, polyvinylidene fluoride gas collection bag, Cole-Parmer, Vernon Hills, IL and 50 liters, polyvinyl chloride gas collection bag, Harvard Apparatus, Holliston, MA, respectively). A 4-L bag was used for the collection of the inhalation gas with an adaptor placed 4 inches from a Y piece connector of the mechanical ventilation circuit. We collected the exhalation gas by connecting the 50-L bag to the exhaust port, meaning that we collected the whole exhalation gas over a period of experiment. The valves of the collection bags for inhalation and exhalation were opened simultaneously and the gases were collected for approximately 5\u0026ndash;7 minutes until the bags were 80% filled. The temperature, humidity, and atmospheric pressure were recorded during the gas collection. To reduce the humidity level of the gas, we placed both bags in a freezer and lowered the gas temperature \u0026lt;-20 \u0026deg;C. The humidity became under detectable level when the gases went into the gas analyzer. The gas humidity was measured by a hygrometer (Ebro TFH620 Compact Thermohygrometer, Cole-Parmer, Vernon Hills, IL) attached to the gas analyzer. Ventilation settings of the patients/volunteers including a minute ventilation volume of exhalation, inhalation to exhalation (I:E) ratio, leak rate, and bias flow, were recorded simultaneously with the gas collection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eAutomation system\u003c/h2\u003e \u003cp\u003eThe DB collection method is the gold standard; however, it allows for a point measurement. Due to the increment need for continuous and repeat measurements, we developed an automation system with the same methodological principle of the aforementioned DB technique. The same gas analyzer was used to measure the concentrations of oxygen and carbon dioxide. The measurement was performed at bedside, which enabled a real-time and continuous collection of data. The sampling adaptor was inserted inside the ventilator circuit to collect the inhalation gas. The connector was placed 4 inches from a Y piece connector attached to the patient\u0026rsquo;s endotracheal tube/volunteer\u0026rsquo;s face mask. The inhalation gas was collected at a flow rate of 200 mL/min, which was regulated by the gas analyzer. A dehumidification device (DHU-1000 Dehumidification Unit, Nihon Kohden Corporation, Tokyo, Japan) was set in conjunction with the gas analyzer: the dehumidification unit was intended for use in dehumidifying a sample gas. This unit included switching valves to select inhalation or exhalation. A 100-mL mixing chamber was attached to the exhaust port. This chamber was engineered to obtain the concentration of whole-gas from a partial sampling. Our system was first validated, and the accuracy was confirmed equivalent to the DB technique (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCalculations and Analysis\u003c/h2\u003e \u003cp\u003eF\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, F\u003csub\u003eE\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (fraction of expired oxygen), F\u003csub\u003eI\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e (fraction of inspired carbon dioxide), F\u003csub\u003eE\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e (fraction of expired carbon dioxide), in-circuit humidity and temperature in the dehumidification device, and ambient pressure and temperature around the mechanical ventilator circuit were measured. A minute ventilation volume of exhalation (V\u003csub\u003eE\u003c/sub\u003e), I:E ratio, and bias flow were recorded from the mechanical ventilator. For the automation system, F\u003csub\u003eE\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and F\u003csub\u003eE\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e were calculated from the gas concentrations measured at the ventilator exhaust port. The gas concentrations of inhalation and exhalation were measured alternately, and the duty cycle was 15 minutes. The inhalation gas was measured for the first 6 minutes of the duty cycle and the exhalation was for the second 9 minutes. The initial 4 minutes of each phase were discarded. If there was a significant change in F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e within a duty cycle, the value was excluded from our analysis. The time series of F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e was calculated from the values of pre- and post-F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. The following equations are used in this study:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$R=\\frac{VI}{VE}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$VO2=VI\\times FIO2-VE\\times FEO2$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ3\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ3\" name=\"EquationSource\"\u003e\n$$VCO2=VE\\times FEO2-VI\\times FIO2$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e3\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere V\u003csub\u003eI\u003c/sub\u003e is a minute ventilation volume of inhalation and V\u003csub\u003eE\u003c/sub\u003e is that of exhalation. F\u003csub\u003eI\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e is zero since the inhalation gas does not contain CO\u003csub\u003e2\u003c/sub\u003e. The VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ are then transformed as follows:\u003cdiv id=\"Equ4\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ4\" name=\"EquationSource\"\u003e\n$$VO2=\\left(R\\times FIO2-FEO2\\right)\\times VE$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e4\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ5\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ5\" name=\"EquationSource\"\u003e\n$$VCO2=FECO2\\times VE$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e5\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Equ6\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ6\" name=\"EquationSource\"\u003e\n$$RQ=\\frac{VCO2}{VO2}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e6\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eR is generally derived from the Haldane transformation with the assumption that nitrogen is neither produced nor retained by the body, and that no gases are present other than O\u003csub\u003e2\u003c/sub\u003e, CO\u003csub\u003e2\u003c/sub\u003e, and nitrogen (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Because the denominator includes F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e and it goes to zero as F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e increases to 1.0, R increases to infinite number when F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e is 1.0. Therefore, the Haldane transformation limits F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e generally up to 0.6. This is a significant limitation in critical care medicine, in which patients normally require high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. Therefore, we developed a method for measuring R and sought the number of R by using our rodent model (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Our results suggested that R was not 1.0 and so V\u003csub\u003eI\u003c/sub\u003e was not equal to V\u003csub\u003eE\u003c/sub\u003e. While our result was in line with the concept of the Haldane transformation suggesting V\u003csub\u003eI\u003c/sub\u003e\u0026ne;V\u003csub\u003eE\u003c/sub\u003e, the data from our report supported that R might be a constant in lieu of a dependent variable affected by F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. Our results from the rodent model showed that R was 1.0081+/-0.0017 at an F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e of 0.3 and 1.0092+/-0.0029 at an F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e of 1.0. We sought a value of human R calculated from the values obtained from previous reports (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) and determined it as 1.0097 in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eWe reported data as mean and standard deviation (SD) and descriptive statistics were used. The values were reported as standard temperature and pressure and dry (STPD). Unpaired t-test was used for comparison between two groups. There were no missing values in this study. We planned to enroll 20 patients in this explanatory phage of the study. According to the values of RQ from our rodent model (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), n\u0026thinsp;=\u0026thinsp;4 for each outcome group would provide the statistical significancy with a power of 0.8 and α\u0026thinsp;\u0026lt;\u0026thinsp;0.05. However, owing to the uncertainty of RQ values and SD range in human samples, the sample number was anyway set at n\u0026thinsp;=\u0026thinsp;20 in this study. As high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e lowers RQ (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), there is a possibility that high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e may bias the results. Therefore, the sensitivity analysis of this study was the secondary analysis including only patients, whose F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e was 0.5 and greater. Prism for Mac version 9 (GraphPad Software, San Diego, CA) and SPSS version 27 (IBM, Armonk, NY) were used for statistical analysis, and P values less than 0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOne data was excluded due to a technical error (damaged equipment) and data from 21 subjects were included in the analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows baseline characteristics. Out of 21 subjects, 8 were patients post cardiothoracic surgery, 7 were patients in the intensive care units (ICU), 3 were those in the emergency room (ER), and 3 were healthy volunteers. Sequential organ failure assessment (SOFA) score, blood lactate level (mmol/L), and P/F ratio (arterial partial oxygen pressure to F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) were obtained at ICU admission, if applicable. None of the post-cardiothoracic surgery patients had major adverse events. This study included 10 critical care patients, whose metabolic measurements were performed in the ER or ICU, and 6 died. Out of the 10 critical care patients, 4 had cardiac arrest before the enrollment. We first validated the device measurements. The values of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ measured by the automation device were compared with those by the DB technique. The mean differences of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ between the methods were 1.5+/-6.6: 3%, 2.3+/-5.1: 5%, 0.008+/-0.030: 4%, respectively. The inter-rater reliability of these two methods on VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, RQ were calculated as 0.999, 0.993, and 0.993, respectively. Collectively, these data support that VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ are interchangeable between the two methods.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of Study Subjects and Fraction of Inspired Oxygen at Measurement\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubject\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSubject Type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSite\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eLactate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eP/F ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDischarge Outcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eF\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCAD, MR, TR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEndocarditis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolunteer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolunteer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCA, DKA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolunteer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolunteer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolunteer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVolunteer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCA, Septic Shock, NSTEMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCA, SAH, Seizure, Hypoxic Respiratory Failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCA, TIA, Multiorgan Dysfunction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e405\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e155\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAortic Aneurysm, Aortic Valve Stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCTICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAspiration Pneumonia, Respiratory Arrest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMultiple Myeloma, Renal Failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCirrhosis, Pulmonary Fibrosis, Respiratory Failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDeath\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePneumonia, Vocal Cord Paralysis, Respiratory Failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAirway Compromise, Aspiration Pneumonia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCOPD exacerbation, Hypercapnia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e633\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eAlive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eDevice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003eSequential Organ Failure Assessment (SOFA) score, blood lactate level (mmol/L), and arterial partial oxygen pressure / F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (P/F) ratio were calculated from the values at ICU admission.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"13\"\u003eCTICU stands for cardiothoracic intensive care unit; ER, emergency room; SICU, surgical intensive care unit; CCU, coronary care unit; MICU, medical intensive care unit; CAD, coronary artery disease; MR, mitral valve regurgitation; TR, tricuspid valve, regurgitation; CA, cardiac arrest; DKA, diabetic ketoacidosis; NSTEMI, non-ST elevation myocardial infarction; TIA, transient ischemic attack; COPD, chronic obstructive pulmonary disease; N/A, not applicable; DB, Douglas Bag.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eLow RQ can Indicate Severity of Patients\u003c/h2\u003e \u003cp\u003eOut of 18 patients who were participated in this study, 6 died. High SOFA score at ICU admission was associated with worse outcome (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), while there were no statistical differences in initial blood lactate levels or P/F ratio. We obtained 24 metabolic measurements from total 21 subjects, who had a variety of back grounds (healthy volunteers to patients with critical illnesses, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Including data from the healthy volunteers, VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ of survivors were 282+/-95 mL/min, 202+/-81 mL/min, and 0.70+/-0.10, and those of non-survivors were 240+/-87 mL/min, 140+/-66 mL/min, and 0.57+/-0.08, respectively (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.34, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among the metabolic measurements, only RQ had a statistically significant difference between the survivors and non-survivors. The difference in RQ remained statistically significant after excluding data from healthy volunteers.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e lowers RQ, there was a potential bias by high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. Therefore, we excluded the values from patients with F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u0026lt;0.5 and we performed subgroup analysis including only patients with F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u0026ge;0.5. In this subgroup analysis, VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ of survivors were 254+/-59 mL/min, 169+/-57 mL/min, and 0.66+/-0.08, and those of non-survivors were 240+/-87 mL/min, 140+/-66 mL/min, and 0.57+/-0.08, respectively (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.71, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.36, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The non-survivors had significantly lower RQ than the survivors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs we used equations (\u003cspan refid=\"Equ4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) and (\u003cspan refid=\"Equ6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), R greater than 1.0 contributes to increasing VO\u003csub\u003e2\u003c/sub\u003e and lowering RQ. Therefore, in order to reduce a bias, we sought VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ that were calculated with R\u0026thinsp;=\u0026thinsp;1.0, even though V\u003csub\u003eI\u003c/sub\u003e\u0026ne;V\u003csub\u003eE\u003c/sub\u003e (R\u0026ne;1). We analyzed 24 metabolic measurements obtained from total 21 subjects and VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ of survivors were 238+/-86 mL/min, 202+/-81 mL/min, and 0.84+/-0.06, and those of non-survivors were 179+/-80 mL/min, 140+/-66 mL/min, and 0.78+/-0.03, respectively. The non-survivors had significantly lower RQ than the survivors (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe developed an automation device for measuring accurate F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, F\u003csub\u003eE\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, and F\u003csub\u003eE\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e in human subjects undergoing mechanical ventilation. These gas concentrations are critical elements to collecting accurate numbers of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ. The accuracy of our system was validated, and it was equivalent to the gold standard method, the DB collection technique (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). In addition, our automation system allows for repeat measurements as opposed to the DB technique that limits the number of collections due to its complexity in the methodology. By using both automation device and DB technique, we were able to collect 24 metabolic data from total 21 human subjects including healthy volunteers, and post-surgical and critical care patients\u003c/p\u003e \u003cp\u003eThe volume ratio of inhalation to exhalation defined as R in this study was essential to comparing the values of VO\u003csub\u003e2\u003c/sub\u003e and RQ among patients with different F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e levels. There is a significant technical difficulty of measuring the small differences between V\u003csub\u003eI\u003c/sub\u003e and V\u003csub\u003eE\u003c/sub\u003e. Therefore, V\u003csub\u003eI\u003c/sub\u003e is commonly calculated from the Haldane transformation, which unfortunately limits F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e generally up to 0.6, and this limitation makes it impossible to compare VO\u003csub\u003e2\u003c/sub\u003e and RQ between low and high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. Assuming V\u003csub\u003eI\u003c/sub\u003e equals V\u003csub\u003eE\u003c/sub\u003e and ignoring this small difference eliminate the concern. However, failure to account for this small difference can erroneously decrease VO\u003csub\u003e2\u003c/sub\u003e by 17% (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), if V\u003csub\u003eI\u003c/sub\u003e is actually not equal to V\u003csub\u003eE\u003c/sub\u003e, and the error even more propagates as F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e is higher. The adequacy of the Haldane transformation (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) supports that V\u003csub\u003eI\u003c/sub\u003e is not equal to V\u003csub\u003eE\u003c/sub\u003e (V\u003csub\u003eI\u003c/sub\u003e\u0026ne;V\u003csub\u003eE\u003c/sub\u003e and R\u0026ne;1). Values of the current study are affected by R. Therefore, we also analyzed our data by using R\u0026thinsp;=\u0026thinsp;1 (V\u003csub\u003eI\u003c/sub\u003e=V\u003csub\u003eE\u003c/sub\u003e), even though this assumption is not in line with the consensus. In this study, we were able to draw the robust conclusion from results using both scenario calculations (V\u003csub\u003eI\u003c/sub\u003e\u0026ne;V\u003csub\u003eE\u003c/sub\u003e and V\u003csub\u003eI\u003c/sub\u003e=V\u003csub\u003eE\u003c/sub\u003e).\u003c/p\u003e \u003cp\u003eThe important finding of this study was that low RQ correlated with patient\u0026rsquo;s mortality. As it is described above, if the small difference between V\u003csub\u003eI\u003c/sub\u003e and V\u003csub\u003eE\u003c/sub\u003e is not properly taken into account, the uncertainty of VO\u003csub\u003e2\u003c/sub\u003e and RQ hinders a comparison between those from subjects with different F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e levels. Because our previous data indicates that R is not affected by F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, we can reasonably use a constant number (1.0097) to both normal and high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. However, R\u0026thinsp;\u0026gt;\u0026thinsp;1.0 impacts the calculation of VO\u003csub\u003e2\u003c/sub\u003e and decreases RQ. Therefore, we performed the secondary analysis that included only patients with F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u0026ge;0.5 and the results were still statistically significant in this subgroup analysis. Our data have become compelling, and we are confident of the conclusion.\u003c/p\u003e \u003cp\u003eOxygen molecules are substrates for biological and enzymatic reactions and so the oxygen utilization is theoretically O\u003csub\u003e2\u003c/sub\u003e concentration dependent. We observed that high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e increased VO\u003csub\u003e2\u003c/sub\u003e without a concomitant increase of VCO\u003csub\u003e2\u003c/sub\u003e resulting in decreased RQ (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). In addition, the finding was more remarkable in critical illness such as post-cardiac arrest (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Notably, Uber et al. reported that post-cardiac arrest patients had low RQs and a large percentage of patients (\u0026gt;\u0026thinsp;70%) showed the number of RQ below physiologic norms (\u0026lt;\u0026thinsp;0.7) (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The mechanisms of this phenotype have not yet been cleared, but our rodent data (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) could support an idea of hyperoxia-induced production of mitochondrial reactive oxygen species. The other factor that can contribute to gas exchange is cutaneous respiration. It accounts for 2% of the lung respiration in humans (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). In a condition that the skin has higher oxygen than atmosphere, the oxygen is diffused from the skin to the atmosphere. Because the concentration gradient of carbon dioxide is not affected by a change in F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, the diffusion mechanism can contribute to increased VO\u003csub\u003e2\u003c/sub\u003e but not VCO\u003csub\u003e2\u003c/sub\u003e when high F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e is used. In this mode, the mechanism is oxygen diffusion rather than consumption. Further mechanistic studies will warrant deeper understanding of oxygen metabolism in critically ill patients.\u003c/p\u003e \u003cp\u003eThis study is subject to several limitations. The number of samples, first and foremost, is limited in this study owing to the nature of explanatory design. A methodological complexity of the DB technique results in a lack of gold standard that hinders a development of science in human oxygen metabolism. We have high hope that our automation device becomes a breakthrough and leads to more and more numbers of both phenotypic and mechanistic studies on oxygen metabolism in humans.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe developed an automation system that enables repeat measurements of VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ. Low RQ correlated with high mortality, which may potentially indicate decompensated oxygen metabolism in critically ill patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eACKNOWLEDGEMENTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAUTHORS\u0026rsquo; CONTRIBUTIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK. Shinozaki has full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis; K. Shinozaki, K. Saeki, JWL, LBB designed the conception of the study; K. Shinozaki, PJY, QZ, DMR, JJ, and YO performed acquisition of data and K. Shinozaki analyzed data; all authors made interpretations of data; all authors added intellectual content of revisions to the paper and gave full approval of the version to be published.\u003c/p\u003e\n\u003cp\u003eSaeki belongs to Nihon Kohden Innovation Center, INC and Goto to Nihon Kohden Corporation as employee. This does not invade the authors\u0026rsquo; adherence to all the Journal\u0026apos;s policies. Shinozaki and Becker own intellectual property of metabolic measurement in critically ill patients. Shinozaki has grant/research supported by Nihon Kohden Corp. Becker has grant/research supported by Philips Healthcare, the National Institutes of Health, Nihon Kohden Corp., BeneChill Inc., Zoll Medical Corp, Medtronic Foundation, and patents in the areas of hypothermia induction and perfusion therapies. The other authors have no disclosures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICAL APPROVAL\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Institutional Review Board. Written informed consent for participation for study and publication of data was obtained from volunteers, patients, or next of kin prior to the procedures. If a patient did not hold a capacity for consent or did not have a legally authorized representative or next of kin, the patient was enrolled with waived consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFUNDING\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the research grant of Nihon Kohden Corporation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAVAILABILITY OF DATA AND MATERIALS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eK. Shinozaki is the corresponding author and has full access to all data in the study. The data will be made available upon reasonable requests and communication with the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGump FE, Kinney JM, Price JB Jr: Energy metabolism in surgical patients: oxygen consumption and blood flow. J Surg Res 10: 613\u0026ndash;627, 1970.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManthous CA, Hall JB, Olson D, et al: Effect of cooling on oxygen consumption in febrile critically ill patients. Am J Respir Crit Care Med 151: 10\u0026ndash;14, 1995.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcClave SA, Lowen CC, Kleber MJ, et al: Clinical use of the respiratory quotient obtained from indirect calorimetry. JPEN J Parenter Enteral Nutr 27: 21\u0026ndash;26, 2003.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiegel JH, Fabian M, Smith JA, et al: Oxygen debt criteria quantify the effectiveness of early partial resuscitation after hypovolemic hemorrhagic shock. J Trauma 54: 862\u0026ndash;880; discussion 880, 2003.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuazzi M, Adams V, Conraads V, et al: EACPR/AHA Scientific Statement. Clinical recommendations for cardiopulmonary exercise testing data assessment in specific patient populations. Circulation 126: 2261\u0026ndash;2274, 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSundstrom M, Tjader I, Rooyackers O, et al: Indirect calorimetry in mechanically ventilated patients. A systematic comparison of three instruments. Clin Nutr 32: 118\u0026ndash;121, 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGraf S, Karsegard VL, Viatte V, et al: Evaluation of three indirect calorimetry devices in mechanically ventilated patients: which device compares best with the Deltatrac II((R))? A prospective observational study. Clin Nutr 34: 60\u0026ndash;65, 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShinozaki K, Becker LB, Saeki K, et al: Dissociated Oxygen Consumption and Carbon Dioxide Production in the Post-Cardiac Arrest Rat: A Novel Metabolic Phenotype. J Am Heart Assoc 7: e007721, 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkuma Y, Becker LB, Hayashida K, et al: Effects of Post-Resuscitation Normoxic Therapy on Oxygen-Sensitive Oxidative Stress in a Rat Model of Cardiac Arrest. J Am Heart Assoc 10: e018773, 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatarese LE: Indirect calorimetry: technical aspects. J Am Diet Assoc 97: S154-160, 1997.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eda Rocha EE, Alves VG, da Fonseca RB: Indirect calorimetry: methodology, instruments and clinical application. Curr Opin Clin Nutr Metab Care 9: 247\u0026ndash;256, 2006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBranson RD, Johannigman JA: The measurement of energy expenditure. Nutr Clin Pract 19: 622\u0026ndash;636, 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoussi S, Vallee F, Roquet F, et al: Measurement of Oxygen Consumption Variations in Critically Ill Burns Patients: Are the Fick Method and Indirect Calorimetry Interchangeable? Shock 48: 532\u0026ndash;538, 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHensel M, Kox WJ: Increased intrapulmonary oxygen consumption in mechanically ventilated patients with pneumonia. Am J Respir Crit Care Med 160: 137\u0026ndash;143, 1999.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMusch TI, Bruno A, Bradford GE, et al: Measurements of metabolic rate in rats: a comparison of techniques. J Appl Physiol (1985) 65: 964\u0026ndash;970, 1988.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Klinken JB, van den Berg SA, van Dijk KW: Practical aspects of estimating energy components in rodents. Front Physiol 4: 94, 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYo K, Yu YM, Zhao G, et al: Brown adipose tissue and its modulation by a mitochondria-targeted peptide in rat burn injury-induced hypermetabolism. Am J Physiol Endocrinol Metab 304: E331-341, 2013.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEven PC, Nadkarni NA: Indirect calorimetry in laboratory mice and rats: principles, practical considerations, interpretation and perspectives. Am J Physiol Regul Integr Comp Physiol 303: R459-476, 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlack C, Grocott MP, Singer M: Metabolic monitoring in the intensive care unit: a comparison of the Medgraphics Ultima, Deltatrac II, and Douglas bag collection methods. Br J Anaesth 114: 261\u0026ndash;268, 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSHEPHARD RJ: A critical examination of the Douglas bag technique. J Physiol 127: 515\u0026ndash;524, 1955.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShinozaki K, Okuma Y, Saeki K, et al: A method for measuring the molecular ratio of inhalation to exhalation and effect of inspired oxygen levels on oxygen consumption. Sci Rep 11: 12815, 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShinozaki K, Yu PJ, Zhou Q, et al: An Automation System Equivalent to The Douglas Bag Technique Enables Continuous and Repeat Metabolic Measurements in Patients Undergoing Mechanical Ventilation. Clin Ther [accepted], 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWilmore JH, Costill DL: Adequacy of the Haldane transformation in the computation of exercise VO2 in man. J Appl Physiol 35: 85\u0026ndash;89, 1973.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHerron JM, Saltzman HA, Hills BA, et al: Differences between inspired and expired minute volumes of nitrogen in man. J Appl Physiol 35: 546\u0026ndash;551, 1973.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUber A, Grossestreuer AV, Ross CE, et al: Preliminary observations in systemic oxygen consumption during targeted temperature management after cardiac arrest. Resuscitation 127: 89\u0026ndash;94, 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eErnstene AC, Volk MC: CUTANEOUS RESPIRATION IN MAN: IV. The Rate of Carbon Dioxide Elimination and Oxygen Absorption in Normal Subjects. J Clin Invest 11: 363\u0026ndash;376, 1932.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"Indirect Calorimetry, Oxygen Consumption, Carbon Dioxide Generation, Respiratory Quotient, Douglas Bag","lastPublishedDoi":"10.21203/rs.3.rs-2391735/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2391735/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eOxygen consumption (VO\u003csub\u003e2\u003c/sub\u003e), carbon dioxide generation (VCO\u003csub\u003e2\u003c/sub\u003e), and respiratory quotient (RQ), which is the ratio of VO\u003csub\u003e2\u003c/sub\u003e to VCO\u003csub\u003e2\u003c/sub\u003e, are critical indicators of human metabolism. To seek a link between the patient\u0026rsquo;s metabolism and pathophysiology of critical illness, we investigated the correlation of these values with mortality in critical care patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was a prospective, observational study conducted at a suburban, quaternary care teaching hospital. Age 18 years or older healthy volunteers and patients who underwent mechanical ventilation were enrolled. A high-fidelity automation device, which accuracy is equivalent to the gold standard Douglas Bag technique, was used to measure VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ at a wide range of fraction of inspired oxygen (F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe included a total of 21 subjects including 8 post-cardiothoracic surgery patients, 7 intensive care patients, 3 patients from the emergency room, and 3 healthy volunteers. This study included 10 critical care patients, whose metabolic measurements were performed in the ER and ICU, and 6 died. VO\u003csub\u003e2\u003c/sub\u003e, VCO\u003csub\u003e2\u003c/sub\u003e, and RQ of survivors were 282 +/- 95 mL/min, 202 +/- 81 mL/min, and 0.70 +/- 0.10, and those of non-survivors were 240 +/- 87 mL/min, 140 +/- 66 mL/min, and 0.57 +/- 0.08 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.34, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), respectively. The difference of RQ was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and it remained significant when the subjects with F\u003csub\u003eI\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u0026lt;0.5 were excluded (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eLow RQ correlated with high mortality, which may potentially indicate a decompensation of the oxygen metabolism in critically ill patients.\u003c/p\u003e","manuscriptTitle":"Low Respiratory Quotient Correlates with High Mortality in Patients Undergoing Mechanical Ventilation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-04 17:51:13","doi":"10.21203/rs.3.rs-2391735/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":"c3a40949-d585-4ce3-bcca-b499df38fdce","owner":[],"postedDate":"January 4th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-20T04:56:08+00:00","versionOfRecord":{"articleIdentity":"rs-2391735","link":"https://doi.org/10.1016/j.ajem.2024.01.003","journal":{"identity":"the-american-journal-of-emergency-medicine","isVorOnly":true,"title":"The American Journal of Emergency Medicine"},"publishedOn":"2024-04-01 04:56:08","publishedOnDateReadable":"April 1st, 2024"},"versionCreatedAt":"2023-01-04 17:51:13","video":"","vorDoi":"10.1016/j.ajem.2024.01.003","vorDoiUrl":"https://doi.org/10.1016/j.ajem.2024.01.003","workflowStages":[]},"version":"v1","identity":"rs-2391735","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2391735","identity":"rs-2391735","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}