Deadspace ventilation: a waste of breath!

Sinha, Pratik; Flower, Oliver; Soni, Neil

doi:10.1007/s00134-011-2194-4

Cited by 59 publications

(34 citation statements)

References 67 publications

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“…An arterial blood gas was obtained at the time of expired gas analysis. Measured dead-space fraction was calculated using the Enghoff modification to the Bohr equation (26):

\frac{V_{D}}{V_{T}} = \frac{false(P a C O_{2} - P_{E} C O_{2} false)}{P a C O_{2}}

where PaCO 2 and P E CO 2 represent partial pressure of CO 2 in arterial blood and expired gas, respectively. All measurements were made prior to study interventions.…”

Section: Methodsmentioning

confidence: 99%

Estimating Dead-Space Fraction for Secondary Analyses of Acute Respiratory Distress Syndrome Clinical Trials

Beitler

Thompson

Matthay

et al. 2015

Critical Care Medicine

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Objective Pulmonary dead-space fraction is one of few lung-specific independent predictors of mortality from acute respiratory distress syndrome (ARDS). However, it is not measured routinely in clinical trials and thus altogether ignored in secondary analyses that shape future research directions and clinical practice. This study sought to validate an estimate of dead-space fraction for use in secondary analyses of clinical trials. Design Analysis of patient-level data pooled from ARDS clinical trials. Four approaches to estimate dead-space fraction were evaluated: three required estimating metabolic rate; one estimated dead-space fraction directly. Setting U.S. academic teaching hospitals. Patients Data from 210 patients across three clinical trials were used to compare performance of estimating equations with measured dead-space fraction. A second cohort of 3,135 patients from six clinical trials without measured dead-space fraction was used to confirm whether estimates independently predicted mortality. Interventions None. Measurements and Main Results Dead-space fraction estimated using the unadjusted Harris-Benedict equation for energy expenditure was unbiased (mean ± SD Harris-Benedict 0.59 ± 0.13; measured 0.60 ± 0.12). This estimate predicted measured dead-space fraction to within ± 0.10 in 70% of patients and ± 0.20 in 95% of patients. Measured dead-space fraction independently predicted mortality (OR 1.36 per 0.05 increase in dead-space fraction, 95% CI 1.10–1.68; p < .01). The Harris-Benedict estimate closely approximated this association with mortality in the same cohort (OR 1.55, 95% CI 1.21–1.98; p < .01) and remained independently predictive of death in the larger ARDSNet cohort. Other estimates predicted measured dead-space fraction or its association with mortality less well. Conclusions Dead-space fraction should be measured in future ARDS clinical trials to facilitate incorporation into secondary analyses. For analyses where dead-space fraction was not measured, the Harris-Benedict estimate can be used to estimate dead-space fraction and adjust for its association with mortality.

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“…An arterial blood gas was obtained at the time of expired gas analysis. Measured dead-space fraction was calculated using the Enghoff modification to the Bohr equation (26):

\frac{V_{D}}{V_{T}} = \frac{false(P a C O_{2} - P_{E} C O_{2} false)}{P a C O_{2}}

where PaCO 2 and P E CO 2 represent partial pressure of CO 2 in arterial blood and expired gas, respectively. All measurements were made prior to study interventions.…”

Section: Methodsmentioning

confidence: 99%

Estimating Dead-Space Fraction for Secondary Analyses of Acute Respiratory Distress Syndrome Clinical Trials

Beitler

Thompson

Matthay

et al. 2015

Critical Care Medicine

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“…The last decade has seen many advancements in care for patients with the Acute Respiratory Distress Syndrome (ARDS) including improvements in ventilator management,[1, 2] noninvasive mechanical ventilation strategies,[3–5] sepsis management,[6] and intensive care unit system changes. [7, 8] More patients with ARDS are now surviving to hospital discharge, a phenomenon that has been reported in both observational studies and randomized trials.…”

Section: Introductionmentioning

confidence: 99%

One-year mortality and predictors of death among hospital survivors of acute respiratory distress syndrome

et al. 2014

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Purpose Advances in supportive care and ventilator management for the acute respiratory distress syndrome (ARDS) have resulted in declines in short-term mortality, but risks of death after survival to hospital discharge have not been well described. Our objective was to quantify the difference between short-term and long-term mortality in ARDS and to identify risk factors for death and causes of death at one year among hospital survivors. Methods This multi-intensive care unit, prospective cohort included patients with ARDS enrolled between January 2006 and February 2010. We determined the clinical characteristics associated with in-hospital and 1-year mortality among hospital survivors and utilized death certificate data to identify causes of death. Results Of 646 patients hospitalized with ARDS, mortality at one year was substantially higher (41%, 95% CI 37–45%) than in-hospital mortality (24%, 95% CI 21–27%), P<0.0001. Among 493 patients who survived to hospital discharge, the 110 (22%) who died in the subsequent year were older (P < 0.001) and more likely to have been discharged to a nursing home, other hospital or hospice compared to patients alive at one year (P < 0.001). Important predictors of death among hospital survivors were comorbidities present at the time of ARDS, and not living at home prior to admission. ARDS-related measures of severity of illness did not emerge as independent predictors of mortality in hospital survivors. Conclusions Despite improvements in short-term ARDS outcomes, one-year mortality is high, in large part due to the large burden of comorbidities, which are prevalent in patients with ARDS.

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“…Several studies have demonstrated the value of V D /V T in critically ill patients in both prognostication and disease progression in conditions such as acute respiratory distress syndrome (ARDS) [1-4]. Yet due to the complexity or equipment costs associated with its calculation, V D /V T is seldom measured in daily intensive care unit (ICU) practice [5,6]. The partial pressure of oxygen in arterial blood/fractional concentration of inspired oxygen (PaO 2 /FiO 2 ) is a simple ratio that describes the adequacy of oxygenation and is widely used in daily practice despite being a poor predictor of outcome [7].…”

Section: Introductionmentioning

confidence: 99%

Analysis of ventilatory ratio as a novel method to monitor ventilatory adequacy at the bedside

et al. 2013

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IntroductionDue to complexities in its measurement, adequacy of ventilation is seldom used to categorize disease severity and guide ventilatory strategies. Ventilatory ratio (VR) is a novel index to monitor ventilatory adequacy at the bedside. textVRMathClass-rel=(trueV˙EmeasuredMathClass-bin×PaCO20.3emthinspacemeasured)MathClass-bin/(trueV˙EpredictedMathClass-bin×PaCO20.3emthinspaceideal). trueV˙Epredicted is 100 mL.Kg-1.min-1 and PaCO20.3emthinspaceideal is 5 kPa. Physiological analysis shows that VR is influenced by dead space (VD/VT) and CO2 production (trueV˙CO2). Two studies were conducted to explore the physiological properties of VR and assess its use in clinical practice.MethodsBoth studies were conducted in adult mechanically ventilated ICU patients. In Study 1, volumetric capnography was used to estimate daily VD/VT and measure trueV˙CO2 in 48 patients. Simultaneously, ventilatory ratio was calculated using arterial blood gas measurements alongside respiratory and ventilatory variables. This data was used to explore the physiological properties of VR. In Study 2, 224 ventilated patients had daily VR and other respiratory variables, baseline characteristics, and outcome recorded. The database was used to examine the prognostic value of VR.ResultsStudy 1 showed that there was significant positive correlation between VR and VD/VT (modified r = 0.71) and trueV˙CO2 (r = 0.14). The correlation between VR and VD/VT was stronger in mandatory ventilation compared to spontaneous ventilation. Linear regression analysis showed that VD/VT had a greater influence on VR than trueV˙CO2 (standardized regression coefficient 1/1-VD/VT: 0.78, trueV˙CO2: 0.44). Study 2 showed that VR was significantly higher in non-survivors compared to survivors (1.55 vs. 1.32; P < 0.01). Univariate logistic regression showed that higher VR was associated with mortality (OR 2.3, P < 0.01), this remained the case after adjusting for confounding variables (OR 2.34, P = 0.04).ConclusionsVR is an easy to calculate bedside index of ventilatory adequacy and appears to yield clinically useful information.

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Deadspace ventilation: a waste of breath!

Cited by 59 publications

References 67 publications

Estimating Dead-Space Fraction for Secondary Analyses of Acute Respiratory Distress Syndrome Clinical Trials

Estimating Dead-Space Fraction for Secondary Analyses of Acute Respiratory Distress Syndrome Clinical Trials

One-year mortality and predictors of death among hospital survivors of acute respiratory distress syndrome

Analysis of ventilatory ratio as a novel method to monitor ventilatory adequacy at the bedside

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