Criteria abstracted from The Users' Guide to Medical Literature, from the Health Information Research Unit and Clinical Epidemiology and Biostatistics, McMaster University

Highlighted lines and questions below provide links to the pertinent description of criteria in The EBM User's Guide, now available at the Canadian Centres for Health Evidence

Article Reviewed:

Please visit the new Evidence Based Journal Club Reviews

Pulmonary dead-space fraction as a risk factor for death in the acute respiratory distress syndrome.

Nuckton TJ, Alonso JA, Kallet RH, Daniel BM, Pittet JF, Eisner MD, Matthay MA.

N Engl J Med. 2002;346(17):1281-6. [abstract; full-text for subscribers]

Reviewed by Sujatha Kannan MD, Kathleen Meert MD, Critical Care Department, Children's Hospital of Michigan, Detroit

Review posted November 3, 2002

I. What is being studied?

Study objective:

To evaluate the association between pulmonary dead space fraction early in the course of illness and risk of death from acute respiratory distress syndrome.

Study design

This was a prospective evaluation of 179 patients greater than 18 years of age, on positive pressure ventilation who met the American-European consensus definition of ARDS. These patients were admitted to a tertiary care intensive care unit over a period of 27 months.

II. Are the results of the study valid?

Note: These questions follow from Randolph AG et al. Understanding articles describing clinical prediction tools. Crit Care Med 1998;26:1603-1612. [abstract]

1. Was a representative group of patients completely followed up? Was follow-up sufficiently long and complete?

All patients were followed until they were breathing without assistance or until time of death before discharge from the hospital.

The follow up was complete and adequate to evaluate the outcome of mortality from ARDS. The sample included patients with different clinical disorders like sepsis, aspiration, pneumonia and trauma that were associated with the ARDS. This was representative of the larger population that they were trying to sample from and to which the results will be applied.

2. Were all potential predictors included?

Variables were chosen on the basis of prior studies of outcomes in ARDS and their potential clinical and physiological significance. Predictors of severity of illness and mortality included the simplified acute physiology score II (SAPS II); respiratory data (e.g., PaO2:FiO2 ratio, Tidal volume, Dead space fraction, respiratory compliance, minute ventilation) demographic data (e.g., age), therapeutic interventions (e.g., vasopressors, low tidal volume ventilation), clinical disorders, and underlying medical illness during the admission period.

3. Did the investigators test the independent contribution of each predictor variable?

Yes. The variables that were independently associated with death were identified using univariate logistic regression first. Variables with significant association (P value < 0.05) and those with potential clinical importance were introduced into a forward, stepwise, logistic-regression model to determine the odds ratios for the variables that were independently associated with an increased risk for death.

4. Were outcome variables clearly and objectively defined?

Yes. The outcome variable was death before discharge from the hospital.

III. What are the results?

1. What is(are) the prediction tool(s)?

Dead space fraction, SAPS II score and Quasistatic respiratory compliance were found to be independently associated with an increased risk of death. As shown in the following table, for every increase of 0.05 in the dead space fraction, the odds of death increased by 45%. For every 1-point increase in SAPS II score and every 1 ml/cm water decrease in compliance the odds of death increased by 6%.

Variable	Odds Ratio (95% CI)	P Value
Dead space fraction (per increase of 0.05)	1.45 (1.15-1.83)	0.002
SAPS II (per 1-point increase)	1.06 (1.03-1.08)	<0.001
Quasistatic respiratory compliance (per decrease of 1 ml/cm of water)	1.06 (1.01-1.10)	0.01

According to this data, the dead space fraction appears to be a more important predictor of mortality with an odds ratio of 1.45. This may falsely appear to be so, because the odds ratio of 1.45 is for every 5% increase in the dead space fraction whereas the odds ratios for SAPS II and respiratory compliance are calculated for every point increase and for every 1ml/cm water decrease respectively. Nonetheless, all three variables appear to be significant independent risk factors for death in ARDS.

It is unclear why variables like PaO2: FiO2 ratio that was so strongly associated with death in the bivariate model (table 2) did not prove to be independent predictors in the full logistic regression model.

2. How well does the model categorize patients into different levels of risk?

The dead space fraction was divided into quintiles. The observed mortality according to the quintile of the dead space fraction was similar to the mortality predicted by logistic regression. The Hosmer-Lemeshow test was performed and indicated that the fit of the model was good (p = 0.44).

3. How confident are you in the estimates of risk?

Based on the data, the dead space fraction is a reliable predictor of increased risk of death as denoted by the 95% CI (1.15-1.83). In other words, for each 5% increase in dead space, the odds of death are increased between 15% to 85%.

IV. Will the results help me in caring for my patients?

1. Does the tool maintain its prediction power in a new sample of patients?

It cannot be determined from this study whether this tool will maintain its prediction power in a new sample of patients. The model was not tested beyond the subset of patients described in this study. In the present subset of patients the model worked well. One of the predictor variables identified (SAPS II) has been shown in a prior study to be independently predictive of death in ARDS. Other known outcome predictors like PaO2: FiO2 ratio did not prove to be independent predictors in this model.

2. Are your patients similar to those patients used in deriving and validating the tool(s)?

This study was done on adult patients and did not include any pediatric subjects. However, the clinical disorders associated with the ARDS are similar to those that occur in pediatric patients. These results cannot be directly applied to pediatric patients since other variables like age; cirrhosis and non-pulmonary multi-organ dysfunction (which are more common in adults) are known to be associated with increased risk of death in ARDS.

3. Does the tool improve your clinical decisions?

With modern metabolic monitoring equipment, measurement of the dead space fraction can easily be done at the bedside and this appears to provide prognostic information early in the course of illness. This tool will probably not change any clinical decisions in pediatric patients at this time. However, in a research setting this tool may be very valuable to identify patients at high risk of mortality who may benefit from experimental therapy. It is unknown from this study how changes in dead space fraction during the course of therapy influence the outcome.

4. Are the results useful for reassuring or counseling patients?

Until the model is tested in pediatric patients and the relationship between changes in dead space fraction over time and the outcome is determined, we will not be able to use this tool for reassuring or counseling patients.

 

Comments

Back to the EB Journal Club Index