Open Access

Erratum: Concordance and limits between transcutaneous and arterial carbon dioxide pressure in emergency department patients with acute respiratory failure: a single-center, prospective, and observational study

  • Xavier Bobbia1,
  • Pierre-Géraud Claret1Email author,
  • Ludovic Palmier1,
  • Michaël Robert1,
  • Romain Genre Granpierre1,
  • Claire Roger1,
  • Justin Yan2,
  • Patrick Ray3,
  • Mustapha Sebbane1,
  • Laurent Muller1 and
  • Jean-Emmanuel de La Coussaye1
Contributed equally
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine201523:77

https://doi.org/10.1186/s13049-015-0154-7

Received: 7 September 2015

Accepted: 7 September 2015

Published: 6 October 2015

The original article was published in Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine 2015 23:40

Abstract

After publication of this article (Scand J Trauma Resusc Emerg Med 23:40, 2015), it came to light that an earlier version had been published in error. This erratum contains the correct version of the article, which incorporates revisions made in response to reviewer comments. Additionally, one of the authors was inadvertently omitted from the author list. This author, Justin Yan, has been included in the corrected author list above.

Background

Transcutaneous CO2 (PtCO2) is a continuous and non-invasive measure recommended by scientific societies in the management of respiratory distress. The objective of this study was to evaluate the correlation between PtCO2 and arterial partial pressure of CO2 (PaCO2) by arterial blood gas analysis in emergency patients with dyspnoea, and to determine the factors that interfere with this correlation.

Methods

From January to June 2014, all adult patients admitted to the RR with dyspnoea during business hours were included in the study if arterial blood gas measurements were indicated. A sensor measuring the PtCO2 was attached to the ear lobe of the patient before the gas analysis. Anamnesis, clinical and laboratory parameters were identified.

Results

Ninety patients with dyspnoea were included (104 pairs of measurements). The median (IQR) age was 79 years (69 – 85). The correlation between PtCO2 and PaCO2 was R2 =.83 (p<.001) but became lower for values of PaCO2 above 60 mm Hg. The mean bias (± SD) between the two methods of measurement (Bland-Altman analysis) was −1.4 mm Hg (± 7.7) with limits of agreement from −16.4 to 13.7 mm Hg. In univariate analysis, PaO2 interfered with this correlation. After multivariate analysis, temperature (OR = 3.01; 95 % CIs [1.16, 7.80]) and PaO2 (OR = 1.22; 95 % CIs [1.02, 1.47]) significantly interfered with this correlation.

Conclusions

There is a significant correlation between PaCO2 and PtCO2 values for patients admitted to the emergency department for acute respiratory failure. One limiting factor to routine use of PtCO2 measurements in the emergency department is the presence of hyperthermia.

Keywords

Emergency service Blood gas monitoring Transcutaneous Carbon dioxide Partial pressure

Background

This is a corrected version of the previously published article [1]. Arterial blood gas monitoring is crucial for management of patients with respiratory failure [2]. The gold standard technique involves an arterial puncture which is invasive, time-consuming, and only gives results at one point in time [3, 4]. Moreover, the delay in waiting for the results of blood gas analysis does not allow for real-time adaptation of oxygen therapy or mechanical ventilation. Oxygen saturation by pulse oximetry (SpO2) is widely used as a surrogate of arterial oxygen saturation (SaO2) [5]. Similarly, end tidal CO2 (EtCO2) allows for an indirect, but reliable and continuous assessment of arterial pCO2 for mechanically ventilated patients. However, for non-ventilated patients, assessment of EtCO2 is more complex, less accurate, and often impossible. For these patients, the recently recommended [6, 7] transcutaneous monitoring of carbon dioxide (PtCO2) could represent an alternative for immediate and continuous assessment of pCO2. Numerous studies of both children [8, 9] and adults [1012] have found a good correlation between PaCO2 and PtCO2. Yet in the specific setting of the emergency department (ED) resuscitation room (RR), PtCO2 has been poorly studied. The main objective of this study was to investigate the relationship between measures of PtCO2 and PaCO2 for patients admitted to the ED RR. The secondary objective was to determine the variables that may disrupt the link between PtCO2 and PaCO2.

Methods

Setting

We conducted this single-center prospective observational study from January to June 2014 in the ED of Nîmes University Hospital, France. This study was reviewed and approved by our Institutional Review Board (number: 13/06–02) and was declared to and approved by the national commission for data processing and civil liberties. All patients provided written informed consent. This study is in compliance with the Helsinki Declaration.

Study population

All adult patients admitted to the RR with dyspnoea during business hours (from 9:00 to 17:00, weekend excluded) were included in the study if arterial blood gas measurements were indicated. In our ED, patients are admitted to the RR if they are level 1 or level 2 according to the Canadian Triage and Acuity Scale (CTAS). Thus, patients with dyspnoea are admitted to the RR if they suffered from severe respiratory distress, asthma, or important dyspnoea. Definition of CTAS level 1 and level 2 for dyspnoea are specified in Appendix 1. Exclusion criteria were incorrect installation of the sensor, signal abnormality on the monitor, and backup error on the memory of the device.

Measurement

The PtCO2 measurement was performed by a Stow-Severinghaus sensor (tc Sensor 92 by Radiometer™, Copenhagen, Denmark). The sensor heats skin to a temperature of 44 °C resulting in a dilatation of the capillary bed that allows for diffusion of gases (CO2 and O2) [13]. On the sensor, carbon dioxide reacts with water to form carbonic acid which dissociates into H + and HCO\(_{3}^{-}\), thereby changing pH values. These pH changes are translated into PtCO2 value through the Henderson-Hasselbalch formula [14]. Medical and paramedical staff were trained in the operation and maintenance of the PtCO2 TOSCA monitor (Radiometer™, Copenhagen, Denmark) before the study commenced. For included patients, the PtCO2 sensor was attached to the ear lobe of the patient allowing for continuous measurement of PtCO2. After stabilization of the monitor to obtain a good signal, arterial blood gases and PtCO2 measurements were performed simultaneously. The medical team was blinded to the value of PtCO2 measured.

Outcomes

The primary outcome was concordance between the simultaneous PaCO2 and PtCO2 values. The sample size calculation was based on the anticipated variation in the differences between the measurements and the required precision. Using a previous study [15] for an estimate of the variation between the differences, a sample size of 50 patients gave a precision of ± 0.19 kPa as the limits of agreement. The secondary outcome was to determine the factors that interfere with this correlation. PtCO2 values were automatically saved every ten seconds by the monitor. Medical patient data were collected and entered into an electronic database after initial collection on paper case report forms (CRF). Blood pressure, heart rate, respiratory rate, blood oxygen saturation, Glasgow coma scale, temperature, time to completion of arterial blood gases, catecholamine use, and non-invasive ventilation or tracheal intubation were recorded by the attending physician. Characteristics of patients such as ED arrival modalities, hospital length of stay, and biological data were collected on the CRF.

Statistical analysis

Patient characteristics were described using qualitative (frequencies and percentages) or quantitative variables (means and standard deviations or median with interquartile ranges - depending on type of distribution) where appropriate. The concordance between PtCO2 and PaCO2 was evaluated by linear regression (correlation coefficients) and Bland-Altman analysis, which determined bias, precision, and agreement of PtCO2 and PaCO2, taking the automated analysis in the laboratory as the reference standard. The Pearson correlation coefficient was used to demonstrate the presence or absence of a relationship between PtCO2 and PaCO2. Relationships between measurement differences (|PaCO2- PtCO2 |) and patient characteristics were investigated by regression analysis. Variables related to the difference between PtCO2 and PaCO2 in the univariate analysis (defined by p<.1, forward selection) were further analyzed in a multivariate model (analysis of covariance). We included PaCO2 in this model but did not included pH or PtCO2 to avoid a collinear bias. Overall model fit was assessed using the Hosmer-Lemeshow test. All statistical tests were two sided. A p-value less than.05 was considered significant for all analyses.

Analyses were performed with the use of R 3.0.2 (R Core Team 2013, R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria). The authors had full access to and take full responsibility for the integrity of the data.

Results

Between January 2014 and June 2014, 102 patients were screened for eligibility. Ninety patients were included and analyzed with 104 PtCO2 values (Fig. 1). Table 1 shows the patient characteristics corresponding to the 104 measurements. After linear regression analysis of 104 couples of measurements, we found a significant correlation between PaCO2 and PtCO2 with R2 =.83 (p<.001) (Fig. 2). The linear regression equation between the two variables was PaCO2 = (0.81 × PtCO2) +10.86. The Bland-Altman analysis is shown in Fig. 3. The mean bias was −1.4 mm Hg (± 7.7) and the limits of agreement (bias ± 1.96 SD) between the two techniques were −16.4 mm Hg and 13.7 mm Hg. The Pearson’s correlation coefficient was.94 (95 % CIs [0.87, 0.94]; p<.001). For the group with PaC02 < 60 mm Hg, R2 =.70 (p<.001) and the mean bias was −3.5 mm Hg (± 5.0). For the group with PaC02 > 60 mm Hg, R2 =.57 (p<.001) and the mean bias was 4.1 mm Hg (± 10.2).
Fig. 1

Flow diagram

Fig. 2

Linear regression between transcutaneous PtcCO2 and PaCO2. Regression line is the continuous line, the dotted lines show the 95 % confidence interval

Fig. 3

Bland-Altman representation of comparison analysis between PaCO2 and PtcCO2 vs means of paired measurements

Table 1

Patients’ characteristics

Male sex, no. (%)

51 (57)

Age, mean (± SD) - year

76 (15)

Past medical history, no. (%)

Acute pulmonary edema

27 (29)

Chronic obstructive pulmonary disease

27 (29)

Ischemic heart disease

21 (23)

Home oxygen

16 (17)

Clinical data at admission, median (IQR)

Heart rate - beats/min.

94 (80–110)

Systolic blood pressure - mm Hg

122 (106–144)

Diastolic blood pressure - mm Hg

69 (60–78)

Respiratory rate - breaths/min.

24 (19–28)

Glasgow coma scale

15 (14–15)

Temperature - °C

37.0 (36.2–37.6)

Laboratory values, median (IQR)

PaCO2 - mm Hg

46.2 (37.6–66.8)

PtCO2 - mm Hg

47.2 (42.1–60.0)

PaO2 - mm Hg

73.5 (63.0–89.0)

pH

7.37 (7.30–7.43)

HCO3 - mEq/L

26.0 (22.8–29.7)

Base excess - mmol/L

1.9 (-1.9–5.8)

Lactate - mmol/L

1.3 (0.7–2.2)

Hemoglobin - g/dL

12.3 (10.9–13.8)

White blood cells - G/L

12.4 (7.9–15.5)

C-reactive protein

41 (8–122)

Glycemia - g/L

1.4 (1.2–1.7)

Brain natriuretic peptide - ng/L

1704 (579–6200)

Diagnosis, no. (%)

Heart failure

25 (27)

COPD

14 (15)

Pneumonia

42 (46)

Pulmonary embolism

5 (5)

Outcome, no. (%)

Noninvasive ventilation required

41 (45)

Intubation required

4 (4)

Admitted to hospital

61 (66)

Admitted to ICU

19 (21)

Discharged from ED

10 (11)

Death at the ED

2 (2)

Inpatient mortality

9 (10)

In the univariate analysis, the only factor associated with a difference between PaCO2 and PtCO2 was PaO2 (Table 2). In multivariate analysis with three explanatory variables (PaCO2, PaO2, temperature), we found the temperature and the PaO2 to be significantly associated with a large difference between PaCO2 and PtCO2 (Table 2). The higher the temperature of the patient, the greater the difference between PaCO2 and PtCO2 (Fig. 4). We developed this model on a data set of 93 measurements (11 observations were exluded due to missingness). This model had a non-significant Hosmer-Lemeshow chi-square goodness-of-fit statistic.
Fig. 4

Linear regression between temperature and difference between PaCO2 and PtCO2 (|PaCO2-PtCO 2|). Regression line is the continuous line, the dotted lines show the 95 % confidence interval

Table 2

Relationships between measurement differences (|PaCO2-PtCO2 |) and patient characteristics using univariate and multivariate analysis (ANCOVA)

 

Univariate analysis

Multivariate analysis

Variable

OR [95 % CIs]

P-value

OR [95 % CIs]

P-value

Sex

1.61 [0.18, 14.25]

.66

  

Past medical history

Acute pulmonary

0.29 [0.03, 2.96]

.29

  

edema

    

COPD

0.60 [0.06, 6.18]

.67

  

Ischemic heart

0.75 [0.06, 8.91]

.82

  

disease

    

Home oxygen

1.01 [0.06, 16.77]

.99

  

Heart rate

0.98 [0.94, 1.03]

.40

  

Systolic blood

1.01 [0.97, 1.05]

.60

  

pressure

    

Diastolic blood

0.97 [0.91, 1.03]

.33

  

pressure

    

Respiratory rate

1.01 [0.88, 1.18]

.85

  

Temperature

2.45 [0.93, 6.49]

.07

3.01 [1.16, 7.80]

.03

PaCO2

1.05 [1.00, 1.12]

.06

1.06 [1.00, 1.12]

.05

PtCO2

1.06 [1.00, 1.13]

.06

  

PaO2

1.21 [1.01, 1.45]

.04

1.22 [1.02, 1.47]

.03

HCO3

0.96 [0.80, 1.15]

.64

  

Base excess

0.96 [0.82, 1.12]

.60

  

Lactate

1.44 [0.43, 4.79]

.54

  

Hemoglobin

1.20 [0.74, 1.95]

.45

  

White blood cells

0.91 [0.74, 1.12]

.38

  

C-reactive protein

1.00 [0.99, 1.01]

.72

  

Glycemia

4.70 [0.62, 35.58]

.13

  

Brain natriuretic

1.00 [1.00, 1.00]

.82

  

vpeptide

    

Discussion

To our knowledge, our study is the largest cohort of PtCO2 measurements conducted in the ED. The mean bias was −1.4 mm Hg (± 7.7) and the limits of agreement (bias ± 1.96 SD) between the two techniques were −16.4 mm Hg and 13.7 mm Hg. There was a significant correlation between PaCO2 and PtCO2 (R2 =.83; p<.001). Because most of our patients were non-intubated, our results highlight the feasibility and the potential benefit of measuring PtCO2 since EtCO2 cannot easily be monitored in non-intubated patients. The correlation coefficient in our study was comparable to what was shown in a previous intensive care study (R2 =.86; p<.01) [10]. However, other studies have found a stronger correlation (R2 coefficient, ranged between.91 and.99 [1618]). We assume this difference is not a consequence of the use of various devices since most of the studies were completed with a Radiometer™device. This difference can be explained by the selection of our patients, as only those in the RR with acute respiratory failure were included. Indeed, the high and extreme PaCO2 values were reported as possibly interfering with the correlation between PtCO2 and PaCO2 [10, 1921]. In a study by Delerme et al. [11], patients had a lower PaCO2 than in our study (39 mm Hg vs. 46, respectively). Secondly, this difference may result from the use of the device by many physicians. Calibration, sensor placement and latency to reach the plateau value of PtCO2 may differ from one physician to another. Because some operators used the monitor less frequently, this may have led to poorer reproducibility. However, it also reflects our center’s daily practice and this issue may occur with any change of device. Thirdly, we did not correct the arterial blood gases according to the patient’s temperature and this may explain a portion of the increased difference. Finally, our population was more likely to have significant dyspnoea and therefore agitation or diaphoresis leading to movement of the sensor may have led to inaccurate measurements. Indeed, in the Gancel et al. study [12] where the difference was lower, the exclusion criteria were very rigorous. Authors did not study patients with status epilepticus, confusion or agitation. According to the authors, these criteria may have led to the exclusion of some patients with severe hypercapnia.

Our study found that PtCO2 values were generally greater than PaCO2 values. Indeed, our linear regression equation is PaCO2 = (0.81 × PtCO2) + 10.86. This overestimation is in accordance with available literature [10, 22, 23] and may have implications for patients requiring non-invasive ventilation and with no arterial blood gas reference. Thus, the recommendations highlight the need to conduct an arterial blood gas analysis to support the correlation between PaCO2 and PtCO2 values [6]. This issue is important given that the Bland-Altman analysis reveals a poorer correlation for PtCO2 values above 60 mm Hg. The value of the mean bias reported in our study corresponds to those found in the literature (−1.4 to 4.6 mm Hg) [16, 24, 25]. The decrease of the correlation for high PaCO2 values has been previously reported. The accuracy of PtCO2 seems to be better for patients with PaCO2 values below 56 mm Hg [26]. One explanation for this poor correlation is that the clinical manifestations of hypercapnia (excessive sweating and vasodilatation) leads to a lower diffusion of carbon dioxide [26]. In our study, after multivariate analysis, temperature was associated with a poor correlation between PaCO2 and PtCO2 (OR = 3.01; 95 % CIs [1.16, 7.80]; p=.03). The issue that the temperature can influence the correlation has been raised by Rodriguez et al. [27]. Our linear regression analysis revealed that the higher the body temperature, the greater the difference between PaCO2 and PtCO2 values. This poor correlation can be explained by the fact that asthe patient’s temperature increased, the difference between the patient and the temperature sensor (44 °C) decreased, resulting in small changes in local perfusion and production of CO2. This hypothesis follows directly from the operating principle of the sensor [6]. It could also be hypothesized that a high body temperature promotes sweating and vasodilatation making the sensor’s measurement more inaccurate. Finally, a low blood pressure could also be a cause of a poor correlation between PaCO2 and PtCO2 [28]. Unfortunately, this hypothesis cannot be confirmed by our data because few patients had shock criteria. Similarly, the assumption that the pH may explain a poor correlation [21] cannot not be confirmed in our study with the multivariate analysis.

Limitations

Although several studies have found a poor correlation between PaCO2 and PtCO2 in patients with shock who are treated with catecholamines [10], we did not analyze this particular relationship. Indeed, we included few patients with hemodynamic instability requiring the administration of intravenous fluids or vasopressor support. It is therefore difficult to assess the impact of decreased circulation on the correlation between PaCO2 and PtCO2. Several studies have shown that the correlation is not affected by catecholamines but by dermal vasoconstriction secondary to a state of shock [23, 27].

Secondly, body mass index (BMI) was not measured in our study. Several studies reported conflicting conclusions regarding the influence of skin thickness, indirectly estimated by BMI, on the CO2 diffusion to the skin and therefore on the PaCO2 values [10, 23, 25, 26]. However, there is no correlation between BMI and the skin on the earlobe, where the sensor was fixed [29].

Finally, one subject that remains to be explored is the intra-individual correlation. Most of the patients had only one arterial blood gas measurement during their management in the RR, which was inadequate for obtaining intra-individual correlations between different PtCO2 and PaCO2 values. This analysis would be important to predict PaCO2 values from continuous measurement of PtCO2, especially for patients requiring several hours of monitoring [27, 30].

Conclusions

There is a significant correlation between PaCO2 and PtCO2 values for patients admitted to the ED for acute respiratory failure. This correlation is particularly accurate for values below 60 mm Hg. One limiting factor to routine use of PtCO2 measurements in the ED is the presence of hyperthermia.

Key messages

  • There is a significant correlation between PaCO2 and PtCO2 values for patients admitted to the emergency department for acute respiratory failure.

  • This correlation is comparable to that which has been shown in intensive care.

  • One limiting factor to the use of PtCO2 measurements in the ED is the presence of hyperthermia.

Appendix 1: Definition of Canadian triage and acuity scale (CTAS) level 1 and level 2 for dyspnoea

Patients with dyspnoea and CTAS Level 1:

Severe respiratory distress: serious intracranial events, pneumothorax, near death asthma (unable to speak, cyanosis, lethargic/confused, tachycardia/bradycardia, arterial oxygen saturation below 90 %), chronic obstructive pulmonary disease exacerbations, cardiac heart failure, anaphylaxis and severe metabolic disturbances (renal failure, diabetic keto-acidosis).

Patients with dyspnoea and CTAS Level 2:

Asthma: severe asthma defined with a combination of objectives measures and clinical factors which relate to the severity of symptoms, vital signs and history of previous severe episodes. If the forced expiratory volume in 1 second or peak expiratory flow rate are below 40 % predicted or previous best, the patient is considered severe.

Dyspnea: this is subjective and may correlate poorly with lung function or deficits in oxygen uptake and delivery. Depending on the age, previous history and physical assessment one may not be able to distinguish between asthma chronic obstructive pulmonary disease, cardiac heart failure, pulmonary embolism, pneumothorax, pneumonia, croup, epiglottitis, anaphylaxis or a combination of problems.

Notes

Abbreviations

ANCOVA: 

Analysis of covariance

BMI: 

Body mass index

CI: 

Confidence interval

CTAS: 

Canadian triage and acuity scale

COPD: 

Chronic obstructive pulmonary disease

CRF: 

Case report form

ED: 

Emergency department

EtCO2

End tidal CO2

ICU: 

Intensive care unit

IQR: 

Interquartile range

OR: 

Odds ratio

RR: 

Resuscitation room

PaCO2

Partial pressure of carbon dioxide in the blood

PtCO2

Transcutaneous partial pressure of carbon dioxide in the blood

PaO2

Partial pressure of dioxygen in the blood

SaO2

Arterial oxygen saturation

SpO2

Oxygen saturation by pulse oxymetry

Declarations

Acknowledgements

The authors acknowledge all the emergency physicians at Nîmes University Hospital who recruited the patients, the residents who helped in this process, and other members of our research team for their help.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors’ Affiliations

(1)
Pôle Anesthésie Réanimation Douleur Urgences, Nîmes University Hospital
(2)
Division of Emergency Medicine, Department of Medicine, London Health Sciences Centre and The Schulich School of Medicine and Dentistry, The University of Western Ontario
(3)
Emergency Department, Hôpital Tenon, Assistance Publique - Hôpitaux de Paris

References

  1. Bobbia X, Claret PG, Palmier L, Robert M, Grandpierre RG, Roger C, et al.Concordance and limits between transcutaneous and arterial carbon dioxide pressure in emergency department patients with acute respiratory failure: a single-center prospective observational study. Scand J Trauma Resusc Emerg Med. 2015; 23:40.PubMed CentralView ArticlePubMedGoogle Scholar
  2. Rady MY. Bench-to-bedside review: Resuscitation in the emergency department. Crit Care. 2005 Apr; 9(2):170–6.PubMed CentralView ArticlePubMedGoogle Scholar
  3. Burri E, Potocki M, Drexler B, Schuetz P, Mebazaa A, Ahlfeld U, et al.Value of arterial blood gas analysis in patients with acute dyspnea: an observational study. Crit Care. 2011; 15(3):R145.PubMed CentralView ArticlePubMedGoogle Scholar
  4. Bobbia X, Grandpierre RG, Claret PG, Moreau A, Pommet S, Bonnec JM, et al.Ultrasound guidance for radial arterial puncture: a randomized controlled trial. Am J Emerg Med. 2013 May; 31(5):810–5.View ArticlePubMedGoogle Scholar
  5. Silversides JA, Ferguson ND. Clinical review: Acute respiratory distress syndrome - clinical ventilator management and adjunct therapy. Crit Care. 2013; 17(2):225.PubMed CentralView ArticlePubMedGoogle Scholar
  6. Restrepo RD, Hirst KR, Wittnebel L, Wettstein R. AARC clinical practice guideline: transcutaneous monitoring of carbon dioxide and oxygen: 2012. Respir Care. 2012 Nov; 57(11):1955–62.View ArticlePubMedGoogle Scholar
  7. Brochard L, Martin GS, Blanch L, Pelosi P, Belda FJ, Jubran A, et al.Clinical review: Respiratory monitoring in the ICU - a consensus of 16. Crit Care. 2012; 16(2):219.PubMed CentralView ArticlePubMedGoogle Scholar
  8. Monaco F, Nickerson BG, McQuitty JC. Continuous transcutaneous oxygen and carbon dioxide monitoring in the pediatric ICU. Crit Care Med. 1982 Nov; 10(11):765–6.View ArticlePubMedGoogle Scholar
  9. O’Connor TA, Grueber R. Transcutaneous measurement of carbon dioxide tension during long-distance transport of neonates receiving mechanical ventilation. Perinatol. 1998; 18(3):189–92.Google Scholar
  10. Bendjelid K, Schütz N, Stotz M, Gerard I, Suter PM, Romand JA. Transcutaneous PCO2 monitoring in critically ill adults: clinical evaluation of a new sensor. Crit Care Med. 2005 Oct; 33(10):2203–6.View ArticlePubMedGoogle Scholar
  11. Delerme S, Montout V, Goulet H, Arhan A, Le Saché F, Devilliers C, et al.Concordance between transcutaneous and arterial measurements of carbon dioxide in an ED. Am J Emerg Med. 2012 Nov; 30(9):1872–6.View ArticlePubMedGoogle Scholar
  12. Gancel PE, Roupie E, Guittet L, Laplume S, Terzi N. Accuracy of a transcutaneous carbon dioxide pressure monitoring device in emergency room patients with acute respiratory failure. Intensive Care Med. 2011 Feb; 37(2):348–51.View ArticlePubMedGoogle Scholar
  13. Severinghaus JW, Astrup P, Murray JF. Blood gas analysis and critical care medicine. Am J Respir Crit Care Med. 1998 Apr; 157(4 Pt 2):S114–22.View ArticlePubMedGoogle Scholar
  14. Kellum JA. Determinants of blood pH in health and disease. Crit Care. 2000; 4(1):6–14.PubMed CentralView ArticlePubMedGoogle Scholar
  15. Heuss LT, Chhajed PN, Schnieper P, Hirt T, Beglinger C. Combined pulse oximetry/cutaneous carbon dioxide tension monitoring during colonoscopies: pilot study with a smart ear clip. Digestion. 2004; 70(3):152–8.View ArticlePubMedGoogle Scholar
  16. Storre JH, Steurer B, Kabitz HJ, Dreher M, Windisch W. Transcutaneous PCO2 monitoring during initiation of noninvasive ventilation. Chest. 2007 Dec; 132(6):1810–6.View ArticlePubMedGoogle Scholar
  17. McVicar J, Eager R. Validation study of a transcutaneous carbon dioxide monitor in patients in the emergency department. Emerg Med J. 2009 May; 26(5):344–6.View ArticlePubMedGoogle Scholar
  18. Cox M, Kemp R, Anwar S, Athey V, Aung T, Moloney ED. Non-invasive monitoring of CO2 levels in patients using NIV for AECOPD. Thorax. 2006 Apr; 61(4):363–4.PubMed CentralView ArticlePubMedGoogle Scholar
  19. McLellan PA, Goldstein RS, Ramcharan V, Rebuck AS. Transcutaneous carbon dioxide monitoring. Am Rev Respir Dis. 1981 Aug; 124(2):199–201.PubMedGoogle Scholar
  20. Tobias JD. Transcutaneous carbon dioxide monitoring in infants and children. Paediatr Anaesth. 2009 May; 19(5):434–44.View ArticlePubMedGoogle Scholar
  21. Versmold HT, Linderkamp O, Holzmann M, Strohhacker I, Riegel K. Transcutaneous monitoring of PO2 in newborn infants: where are the limits? Influence of blood pressure, blood volume, blood flow, viscosity, and acid base state. Birth Defects Orig Artic Ser. 1979; 15(4):285–94.PubMedGoogle Scholar
  22. Rosner V, Hannhart B, Chabot F, Polu JM. Validity of transcutaneous oxygen/carbon dioxide pressure measurement in the monitoring of mechanical ventilation in stable chronic respiratory failure. Eur Respir J. 1999 May; 13(5):1044–7.View ArticlePubMedGoogle Scholar
  23. Janssens JP, Howarth-Frey C, Chevrolet JC, Abajo B, Rochat T. Transcutaneous PCO2 to monitor noninvasive mechanical ventilation in adults: assessment of a new transcutaneous PCO2 device. Chest. 1998 Mar; 113(3):768–73.View ArticlePubMedGoogle Scholar
  24. Lang CJ. Apnea testing guided by continuous transcutaneous monitoring of partial pressure of carbon dioxide. Crit Care Med. 1998 May; 26(5):868–72.View ArticlePubMedGoogle Scholar
  25. Maniscalco M, Zedda A, Faraone S, Carratù P, Sofia M. Evaluation of a transcutaneous carbon dioxide monitor in severe obesity. Intensive Care Med. 2008 Jul; 34(7):1340–4.View ArticlePubMedGoogle Scholar
  26. Cuvelier A, Grigoriu B, Molano LC, Muir JF. Limitations of transcutaneous carbon dioxide measurements for assessing long-term mechanical ventilation. Chest. 2005 May; 127(5):1744–8.View ArticlePubMedGoogle Scholar
  27. Rodriguez P, Lellouche F, Aboab J, Buisson CB, Brochard L. Transcutaneous arterial carbon dioxide pressure monitoring in critically ill adult patients. Intensive Care Med. 2006 Feb; 32(2):309–12.View ArticlePubMedGoogle Scholar
  28. Belenkiy S, Ivey KM, Batchinsky AI, Langer T, Necsoiu C, Baker W, et al.Noninvasive carbon dioxide monitoring in a porcine model of acute lung injury due to smoke inhalation and burns. Shock. 2013 Jun; 39(6):495–500.View ArticlePubMedGoogle Scholar
  29. Edston E. The earlobe crease, coronary artery disease, and sudden cardiac death: an autopsy study of 520 individuals. Am J Forensic Med Pathol. 2006 Jun; 27(2):129–33.View ArticlePubMedGoogle Scholar
  30. Randerath WJ, Stieglitz S, Galetke W, Anduleit N, Treml M, Schäfer T. Evaluation of a system for transcutaneous long-term capnometry. Respiration. 2010; 80(2):139–45.View ArticlePubMedGoogle Scholar

Copyright

© Bobbia et al. 2015