Affiliations: Medical University of Plovdiv, Plovdiv, Bulgaria,
A. Galateo Lung Disease Hospital, Leece, Italy
Correspondence to: Stefan Kostianev, MD, DMSc, Department of Pathophysiology, Medical University of Plovdiv, 15A Vassil Aprilov Blvd, 4002 Plovdiv, Bulgaria; e-mail: email@example.com
Toraldo and colleagues (December 2005)1 are to be congratulated on their endeavor to identify daytime variables that are predictive of nocturnal desaturation in COPD patients, a field in which many attempts have failed. However, we think that some points are worth addressing.
First, despite the plethora of data presented by Toraldo et al,1 it does not greatly contribute to the evidence base of numerous previous articles that the probability for nonapneic desaturation is proportional to the severity of blood gas disturbances and lung function impairment.
Second, we think that an analysis of the possible usefulness of the oxyhemoglobin dissociation curve2(ODC) as a predictive tool for nonapneic desaturation in COPD patients could have been included in the discussion. A physiologic decrease of Pao2 during sleep in healthy subjects does not result in significant desaturation because of the plateau in this section of the lung. The decrease of Pao2 in COPD patients frequently combined with an increase in Paco2 and a decrease in pH, as well as with some specific changes in the biochemistry of hemoglobin (ie, an increase in 2,3-diphosphoglycerate and Po2 corresponding to 50% saturation of hemoglobin) causes a rightward shift of ODC and a displacement of the desaturation point to the steeper slope of the ODC.3 All of those conditions are prerequisites for significant nocturnal desaturation. We believe that the so-called capacitance coefficients that are a measure of the slope of different parts of the ODC,3 and their “desaturation capacity” may be a promising avenue for the more accurate prediction of the nocturnal desaturation in COPD patients.
Having in mind the major clinical implications of significant nocturnal desaturation, we believe that the authors should comment on these issues.
The authors hereby declare that they have no conflicts of interest to disclose.
The authors have reported to the ACCP that no significant conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.
We thank Dr. Kostianev et al for contribution of their knowledge in the field addressed by our article (December 2005).1We agree that independent predictors of nighttime desaturation in COPD patients useful for clinical applications are still being discussed. Some tests have been proposed: (1) low daytime Pao2 values2; (2) reduced sensitivity of respiratory centers to chemical stimuli3; (3) serious alteration of pulmonary function test results; (4) a clinical frame of “blue bloaters”; (5) desaturation after physical effort; (6) measurement of carbon dioxide ventilatory response; and (7) awake daytime arterial oxygen saturation (Sao2) values.
Our study used for the first time a cluster analysis in such a prediction. The cluster analysis involves grouping similar objects into distinct, mutually exclusive subsets referred to as clusters. The elements within a cluster have a high degree of “natural association” among themselves, while the clusters are “relatively distinct” from one another. A cluster analysis method, therefore, can be simply defined as a procedure to classify data already used in clinical medicine for patients or patient data classification.
Our data showed that i-cluster analysis was able to detect populations among both “desatutator” and “nondesaturator” COPD patients; desatutator patients were identified not by the percentage of total recording time (TRT) spent in bed with arterial oxygen saturation (Sao2) < 90% alone, but rather by a pattern of percentage of TRT spent in bed with Sao2 < 90% and mean pulmonary artery pressure and Paco2 values, the two latter also being predictors of nocturnal desaturation severity. Moreover, cluster analysis was able to identify subgroups of both desatutator and nondesaturator patients with varying degrees of illness.
Kostianev et al4identified new biochemical parameters to evaluate oxygen transport using the dissociation curve of human hemoglobin. Siggaard-Andersen and Siggaard-Anderson5 proposed a computer program for calculating and displaying pH and blood gas data that can be used to predict the oxygen status or acid-base status. Both methods are not simply to be used in clinical medicine for classification of patients. Our contribution is a further clinical/practical approach to clarify such a field opening to further studies on the sleep lung ventilation and oxygen saturation, the chemical control of respiratory function and on response to hypoxic and hypercapnic awake stimuli.
Become a CHEST member and receive a FREE subscription as a benefit of membership.
Individuals can purchase this article on ScienceDirect.
Individuals can purchase a subscription to the journal.
Individuals can purchase a subscription to the journal or buy individual articles.
Learn more about membership or Purchase a Full Subscription.
Institutional access is now available through ScienceDirect and can be purchased at myelsevier.com.
Some tools below are only available to our subscribers or users with an online account.
Download citation file:
Web of Science® Times Cited:
Customize your page view by dragging & repositioning the boxes below.
Enter your username and email address. We'll send you a reminder to the email address on record.
Athens and Shibboleth are access management services that provide single sign-on to protected resources. They replace the multiple user names and passwords necessary to access subscription-based content with a single user name and password that can be entered once per session. It operates independently of a user's location or IP address. If your institution uses Athens or Shibboleth authentication, please contact your site administrator to receive your user name and password.