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(Chest. 2005;128:1201-1208.)
© 2005 American College of Chest Physicians

Prognostic Value of the Hematocrit in Patients With Severe COPD Receiving Long-term Oxygen Therapy*

Arnaud Chambellan, MD; Edmond Chailleux, MD and Thomas Similowski, MD, PhD{dagger}

* From the Service de Pneumologie (Dr. Chailleux) and Laboratoire des Explorations Fonctionnelles (Dr. Chambellan), CHU de Nantes, Nantes; and the Service de Pneumologie (Dr. Similowski), Groupe Hospitalier Pitié-Salpêtriere, Assistance Publique-Hôpitaux de Paris, Paris, France. {dagger} Fédération Antadir, 66 Bd St-Michel, 75006 Paris, France.

Correspondence to: Edmond Chailleux, MD, Service de Pneumologie, CHU de Nantes, Boulevard Jacques Monod, 44093 Nantes Cedex 1, France; e-mail: edmond.chailleux{at}chu-nantes.fr


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: Although traditionally associated with polycythemia, COPD has a systemic inflammatory component that could interfere with erythropoiesis. This study describes the distribution and prognostic value of the hematocrit in patients with severe COPD receiving long-term oxygen therapy (LTOT).

Methods: A total of 2,524 patients with COPD, FEV1/vital capacity (VC) < 70%, FEV1 < 80% of predicted, and PaO2 < 7.3 kPa in whom a hematocrit was available at entry was identified between 1980 and 1999 in the French Association Nationale pour le Traitement à Domicile de l’Insuffisance Respiratoire chronic respiratory insufficiency and home-care database (male/female ratio, 5/1; mean ± SD age, 68 ± 10 years for men, and 70 ± 10 years for women). Correlations between hematocrit, demographic data, and pulmonary function data were examined. A multivariate Cox proportional hazard regression was performed to identify prognostic factors.

Results: Mean hematocrit was 45.9 ± 7.0% in men and 43.9 ± 6.0% in women (< 39% in 12.6% of men, and < 36% in 8.2% of women) according to the World Health Organization definition of anemia. Hematocrit was negatively correlated with age (r = – 0.245) and FEV1/VC (r = – 0.068) and was positively correlated with PaCO2 (r = 0.161) and body mass index (r = 0.127). Multivariate analysis found hematocrit to be an independent predictor of survival, hospital admission rate, and cumulative duration of hospitalization. The 3-year survival was 24% (95% confidence interval, 16 to 33%) when the hematocrit was < 35%, and 70% (63 to 76%) when the hematocrit was ≥ 55%.

Conclusions: A low hematocrit is not uncommon in LTOT/COPD patients. Hematocrit is negatively associated with mortality and morbidity. Whether the association is causative or not and whether or not corrective measures are warranted remain to be determined.

Key Words: anemia • COPD • erythropoietin • hematocrit • long-term oxygen therapy • survival


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
COPD is, according to a widely disseminated definition,1 "a disease state characterized by airflow limitation that is not fully reversible," where "the airflow limitation is usually both progressive and associated with an abnormal inflammatory response of the lungs to noxious particles or gases" (the main source of which is tobacco smoke). Besides spirometric abnormalities, bronchopulmonary lesions lead to ventilation-perfusion imbalance and the ensuing gas exchange abnormalities. FEV1 and hypoxemia are strong prognostic markers,23 and long-term oxygen therapy (LTOT) has been shown to improve survival.45 The deleterious effects of hypoxemia proceed from the effects of tissue hypoxia on cell metabolism and organ function. Among these effects, the stimulation of erythropoietin production can lead to a compensatory erythrocytosis that is traditionally viewed as a typical of COPD.

COPD also has a systemic inflammatory dimension. Patients with COPD often exhibit raised levels of proinflammatory cytokines, eg, interleukin (IL)-1, IL-6, tumor necrosis factor (TNF)-{alpha}, chemokines (IL-8, monocyte chemotactic protein-A), and C-reactive protein. The expression of neutrophil adhesion molecules is increased, and there are changes in neutrophil functions, and many other perturbations.67 In some COPD patients, this could contribute to an increased energy expenditure, promoting muscle wasting, nutritional imbalance, and weight loss. Weight loss in patients with COPD has been correlated with serum TNF-{alpha} levels8 and has a negative prognostic value.9 COPD-related inflammation could also impair erythropoiesis, as do other chronic inflammatory processes. Hemoglobin levels in COPD patients would then reflect the balance between the stimulation of erythropoiesis by hypoxia and its depression by inflammation.

Inadequate hemoglobin levels could aggravate tissue hypoxia and carry a negative prognostic impact. Hints as to the plausibility of this scenario exist in the literature. Blood cell transfusion in anemic COPD patients reduces minute ventilation and the work of breathing,10 suggesting that correcting low hemoglobin levels could alleviate dyspnea and improve exercise capacity. In a small set of anemic ventilator-dependent COPD patients, raising hemoglobin levels to > 12 g/dL seemed to improve patients enough to make ventilator weaning possible.11 A reduced hematocrit was found to be an independent predictor of poor outcomes in COPD patients following elective open abdominal aortic aneurysm resection.12 In the COPD population from which Celli et al13 derived the prognostic value of a multidimensional index combining four variables (body mass index [BMI], airflow obstruction, dyspnea, and exercise capacity [BODE] index), the patients who died had a significantly lower hematocrit (mean ± SD, 39 ± 5%) than those who survived (42 ± 5%).

The present study was conducted to look for a putative association between hematocrit and prognosis in severe COPD patients receiving LTOT. The data were extracted, over a period of 20 years, from a large national database in France maintained by the Association Nationale pour le Traitement à Domicile de l’Insuffisance Respiratoire (ANTADIR). This database has already been used, for example, to describe the main prognostic factors in various types of chronic respiratory insufficiency,14 or to relate BMI15 to outcome in this population.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Organization of the ANTADIR Observatory
The ANTADIR is a French national nonprofit associative network of 23 regional associations founded in 1981 to ensure health-care support and technical follow-up to disabled patients requiring domiciliary oxygen support, mechanical ventilation, or continuous positive airway pressure. Since its foundation, ANTADIR has maintained a comprehensive demographic database or "observatory,"14 providing a unique national register allowing epidemiologic surveys in large cohorts of patients with various types of chronic respiratory diseases. Individual patient records derive from the single document filled in by prescribing physicians for the reimbursement of costs by the French social security system. Available information includes demographic data (age, sex, height, and weight) and clinical data (diagnosis, room air arterial blood gases and hematocrit, pulmonary function tests, and smoking status). Prescriptions, hospitalizations, treatment withdrawals, and deaths are registered by the regional associations using common software and compiled together by ANTADIR, which manages the national database and produces an annual report.

Patients
Among the patients registered in the database, 11,366 had a clinical diagnosis of COPD with a FEV1/vital capacity (VC) ratio < 70% and a FEV1 < 80% of predicted. Room air PaO2 was < 7.3 kPa in 6,111 cases. The initial hematocrit was available in 2,524 of these patients (2,097 men and 427 women), who constitute the study cohort (Table 1 ). In this population, women were older than men and were more likely to be nonsmokers than ex-smokers or current smokers. Although they had been prescribed oxygen, 10.2% of the patients were reported as current smokers (men, 9.9%; women, 11.3%).


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  		Table 1.. Demographic and Functional Characteristics of the Patients by Sex*

 
Hematocrit
Hematocrit values considered for analysis were those recorded with the arterial blood gases retained to prescribe LTOT. Six hematocrit categories (21 to 34%, 35 to 39%, 40 to 44%, 45 to 49%, 50 to 54% and ≥ 55%) were defined for the purpose of statistical calculations.

Anthropometric Data and Pulmonary Function Tests
The BMI was calculated as the ratio of weight to height squared from the data available in the initial patients records. Spirometric values obtained in body temperature and pressure, saturated, conditions were expressed as percentages of predicted values.16

Outcomes
The annual death rate, annual hospital admission rate, and annual number of days spent in the hospital were computed from the follow-up records.

Statistical Analysis
In the 2,524 studied patients, the associations between hematocrit and age, BMI, and pulmonary function tests were studied by linear correlation and represented graphically for each hematocrit category. The population survival was calculated from the onset of LTOT by the actuarial and Kaplan-Meier methods with a closing date of January 1, 2001. The study of prognostic factors was performed using the log-rank test and Cox semiparametric models as previously described.1415 The influence of hematocrit, age, sex, BMI, arterial blood gases, and pulmonary function tests on the annual rate of hospital admissions and on the number of days spent in the hospital were studied by univariate regression followed by a multivariate stepwise regression. These patients were also compared to the 3,587 patients with a FEV1/VC ratio < 70%, a FEV1 < 80% of predicted, and a room air PaO2 < 7.3 kPa but in whom a hematocrit was not available.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Hematocrit
Anemia can be defined by a hematocrit < 39% in men and < 36% in women.17 According to this definition, the prevalence of anemia in the cohort studied was 12.6% in men and 8.2% in women (but 18.5% of the women had a hematocrit < 39%). The prevalence of a hematocrit value ≥ 55% was 8.4% (men, 8.9%; women, 5.9%). Hematocrit was significantly higher in men than in women (t = 5.6, p < 0.001), and was negatively correlated with age (r = –0.245, p < 0.001) and positively correlated with PaCO2 (r = 0.161, p < 0.001) and BMI (r = 0.127, p < 0.001), but there was no significant correlation between hematocrit and PaO2 (r = –0.033, p = 0.095). A weak negative correlation existed between hematocrit and FEV1/VC (r = –0.084, p < 0.001), and between hematocrit and FEV1 percentage of predicted (r = –0.054, p = 0.006) [Fig 1 ]. Current smokers had significantly higher hematocrit values than ex-smokers or nonsmokers (Table 2 ).



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  		Figure 1.. Links between hematocrit, age, BMI, and respiratory function. The values shown are the mean age, BMI, and spirometric and arterial blood gas values for each interval of hematocrit (SEM). pred = predicted.

 

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  		Table 2.. Hematocrit by Sex and Smoking Habits*

 
Survival
At the time of analysis, 1,842 patients had died, 266 were alive, and 416 were unavailable for follow-up by the ANTADIR system (two thirds of those were known to have stopped oxygen for motives such as alleged poor tolerance or a personal wish; one third was known to have entered a long-term care facility). The mean duration of follow-up was 10 years. The overall median survival was 3.0 years. Survival was increased when the hematocrit was high and reached the longest duration in polycythemic patients (p < 0.001, log-rank test) [Fig 2 ]. The 3-year survival rate was 24% (95% confidence interval [CI], 16 to 33%) in patients with a hematocrit < 35%; 36% (95% CI, 31 to 42%) in patients with a hematocrit between 35% and 39%; 47% (95% CI, 43 to 51%) in patients with a hematocrit between 40% and 44%; 51% (95% CI, 47 to 55%) in patients with a hematocrit between 45% and 49%; 59% (95% CI, 54 to 64%) in patients with a hematocrit between 50% and 54%; and 70% (95% CI, 63 to 76%) in patients with a hematocrit ≥ 55%.



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  		Figure 2.. Ten-year survival analysis of the influence of hematocrit calculated by the actuarial method. The initial numbers in each group were 120 (< 35 years old), 323 (35 to 39 years old), 675 (40 to 44 years old), 739 (45 to 49 years old), 456 (50 to 54 years old), and 211 (≥ 55 years old); log-rank, 171; degree of freedom = 5 (p < 0.001).

 
Multivariate analysis ranked age, hematocrit, BMI, PaO2, sex, and FEV1 percentage of predicted as prognostic factors, in descending order (Table 3 ). The prognostic influence of the hematocrit was significant in both men and women. The interactions between correlated variables (hematocrit and BMI, hematocrit and FEV1, hematocrit and PaO2) were not significant predictors of survival.


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  		Table 3.. Multivariate Study of Prognostic Factors by Cox Model*

 
Admission Rate and Hospital Length of Stay
For the 1,799 patients with a follow-up of at least 1 year, the annual hospitalization rate was 1.17 ± 1.21 (median, 0.86) and the average number of days in the hospital was 25.1 ± 35.1 (median, 13.3). Univariate analysis showed that hematocrit was negatively correlated with the rate (r = –0.091, p = 0.001) and duration (r = –0.095, p < 0.001) of hospitalizations (Fig 3 ). This correlation, although weak, was the second strongest found in the data set after the correlation with between BMI and hospitalizations.



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  		Figure 3.. Influence of hematocrit on hospitalizations. The values shown are the mean annual total of days spent in hospital and the mean annual rate of admission for six intervals of hematocrit (SEM), calculated in 1,799 patients with a follow-up of at least 1 year.

 
Patients with a hematocrit < 35% were hospitalized 1.41 ± 1.24 (mean ± SD) times per year, with 31.5 ± 42.8 days in the hospital per year. However, patients with a hematocrit ≥ 55% were hospitalized 0.96 ± 0.99 times a year on average, with a mean annual time spent in the hospital of 17.5 ± 23.4 days. Stepwise multivariate regression selected BMI (p < 0.001), hematocrit (p < 0.002), PaCO2 (p = 0.002), and age (p = 0.027) as predictive factors of the annual admission rate, whereas hematocrit (p < 0.001), BMI (p = 0.008), and age (p = 0.017) were predictive of the annual duration of hospitalization.

Comparison of the Patients With and Without a Known Hematocrit Value
These two groups of patients were not significantly different regarding the sex ratio, age, tobacco smoking status, PaO2, VC, and FEV1. The patients with a known hematocrit value had a marginally but significantly higher PaCO2 (48.8 ± 8.8 mm Hg vs 48.2 ± 9.0 mm Hg) and lower BMI (23.2 ± 6.6 kg/m2 vs 23.7 ± 6.6 kg/m2). The outcomes were slightly better in the group with an unknown hematocrit than in the group with a known hematocrit (median survival, 1,154 days vs 1,086 days [p = 0.016, log-rank]; admission rate, 1.07 ± 1.19 vs 1.18 ± 1.21 [p = 0.003]; length of stay, 21.3 ± 31.2 days vs 25.1 ± 35.1 days [p < 0.001]).


   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
This study shows that in a large population of COPD patients treated with LTOT, the prevalence of a low hematocrit at the time the prescription of oxygen is far from negligible (12.6% of the men and 18.5% of the women meeting the World Health Organization definition of anemia [hematocrit < 39%]17). In this particular population, the study also points to a strong association between hematocrit and long-term survival in this population.

These findings seem to contrast with commonly held views. Although an apparent lack of polycythemic response to hypoxia has been noted in COPD patients in early studies,1819 red cell mass has consistently been found increased2021 and anemia never reported with a prevalence such as the one we found. Polycythemia in COPD has been assigned no effect on survival22 or a negative effect.45

Cohort Characteristics, Prognostic Impact, and Shape of Risk
The patients in our cohort were mostly elderly people of the male gender (83%). As expected, they had severe COPD (mean FEV1 in men, 0.92 ± 0.37 L/s; in women, 0.68 ± 0.23 L/s; median survival, 3.0 years). Hematocrit was negatively correlated with age, a common finding in geriatric medicine.23 It was also correlated, less strongly, with BMI and PaCO2. Age and the male gender were identified as negative prognostic factors by the Cox model. This model also indicated that increasing values of PaO2, BMI, and FEV1 percentage of predicted were significantly associated with a better prognosis. These results fit with established facts in COPD.452425 In addition, the Cox model showed that each 5% increase in hematocrit was associated with improved survival, and that hematocrit was the strongest prognostic factor next to age. Even though cross-correlation did exist between some of the model variables, none of their interactions had a significant effect.

The 10-year actuarial survival curve (Fig 2) shows a strong correlation between each 5% stratum of hematocrit and the mortality rate, particularly within the first years. The annual hospital admission rate and the cumulative hospital length of stay were highest in the patients with the lowest hematocrit levels and decreased in a roughly linear manner with hematocrit. This observation may be viewed as surprising, as a U-shaped risk could have been expected, but it may be due to the relatively small number of patients with high or very high hematocrit values. Further studies will be necessary to determine whether the hematocrit-associated risk is gradual or if it has a threshold.

Hypercapnia was positively correlated with hematocrit. If one equates hypercapnia with disease severity, the inverse correlation of hematocrit with survival may then seem paradoxical. However a low hemoglobin level stimulates ventilation and could thus be responsible for "artificially" low values of PaCO2.10 Of note, our first study from the ANTADIR database showed that in COPD patients receiving LTOT, a low PaCO2 had a negative prognostic value.14

Limitations and Strength of the Study
The study has limitations. First, it is a retrospective observational study, and as such it tells nothing on the causative nature of a statistical association between a risk factor and a given outcome. Second, the only hematocrit value considered is the one noted at the time of the initiation of LTOT. As a result, the prognosis value of the dynamics of the hematocrit over time is unknown, as are on the impact of the compliance with oxygen therapy and of changes in smoking status. Third, the study pertains to a fraction of the relevant population, because a hematocrit was available in only one third of the patients meeting the inclusion criteria. A hematocrit should be gathered systematically on ANTADIR forms, and why this is not the case is only too obvious. The comparison of the population with and without known hematocrit values shows only slight differences in characteristics, but indicate differences in prognostic suggesting that somehow clinicians might note down hematocrit in more severe patients. However, we feel that this does not intrinsically undervalue our results, which are what they are in the population studied. Fourth, there is no possibility to identify, from the database, the existence of comorbidities that could either be specific etiologies for the decrease in hemoglobin (eg, chronic renal failure or GI bleeding) or intrinsically aggravate the prognosis. Finally, the database has been in operation over a long time period, during which treatments for COPD and patterns of health-care use have changed, which may have influenced the hematocrit.

These limitations must be taken into account (see "Perspectives") but also weighted against the strengths of the study. The principal of these strengths lie in the size of the cohort and in the nature of the database from which it was derived. Indeed, the ANTADIR observatory has been continuously recording data from LTOT patients > 25 years, and from 23 regions of France. Therefore, we were able to study a very large population of patients characterized in a standard manner in terms of demographic data, pulmonary function tests, and intercurrent events. Although not a typical epidemiologic database (such as the Framingham database, in which all patients are followed up at fixed intervals to collect complete information), the characteristics of the ANTADIR database are such that selection and censoring biases are not likely to be major. The 10-year average follow-up adds weight to our observations.

Possible Mechanisms of Anemia in COPD
Anemia increases in prevalence with age, which may account in part for our observations. GI bleeding; chronic renal failure; deficiencies in vitamin B12, folate, or iron; and myelodysplastic syndromes can coexist with COPD, and should not be overlooked in anemic COPD patients. Chronic infections, chronic inflammation, and neoplastic diseases cause the so-called anemia of chronic disease,26 also a feature of chronic heart failure where anemia is an independent risk factor for mortality.27 These diseases can all coexist with COPD, but COPD itself might cause anemia of chronic disease. A full review of the possible mechanisms is beyond the scope of this article, but some facts warrant attention. In the anemia of chronic disease, shortened survival of RBCs is thought to result from raised levels of IL-1 and TNF.26 These findings are common in COPD and exaggerated during exacerbations.28 IL-1 and TNF also decrease the erythropoietin response to hypoxia, impede iron utilization, and impair marrow erythropoietic response.26 Low hemoglobin levels in COPD patients could thus directly derive from COPD-related inflammation, and be aggravated by undernutrition when present. Dilution due to sodium retention29 could lower hematocrit in COPD, but sodium retention is often associated with hypercapnia,30 which does not fit with what we observed. Theophylline can blunt erythropoietin production.31 Of note, oxygen could aggravate the negative effects of COPD on erythropoiesis by blunting erythropoietin production, which could counterbalance the positive effects of raising PaO2. Another factor to take into account is the tobacco-smoking status and its changes overt time. In the present cohort, approximately 10% of the patients were still smokers at the initiation of LTOT, and possible changes in tobacco-smoking status during the follow-up are not known. Yet, cigarette smoking in COPD patients interferes with RBC production and with the effects of long-term oxygen on this production.32

The Relationship Between Low Hematocrit and Mortality
Anemia is associated with increased mortality in patients with end-stage renal insufficiency,33 malignancy,34 acute myocardial infarction and chronic heart failure,2735 surgical patients in general,36 and critically ill patients.37 In some cases, the causative nature of the association is suspected because correcting hemoglobinemia improves prognosis.38 In heart failure patients, open studies39 suggest that the correction of anemia with erythropoietin improves ejection fraction, reduces symptoms, decreases hospitalizations, and reduces mortality. These data however need confirmation. In other situations, correcting hemoglobinemia does not have a positive influence on the prognosis.40

In COPD patients, Cappell and Nadler41 observed increased mortality in cases of upper-GI bleeding as compared to control subjects (odds ratio, 4.3; 95% CI, 1.22 to 14.8; p < 0.01). Upchurch et al,12 in 158 COPD patients undergoing elective abdominal aortic aneurysmectomy, found than a low preoperative hematocrit was significantly associated with a poor outcome. From these observations, it may be postulated that COPD patients are rendered more sensitive to anemia, acute or chronic, by the prevailing tissue hypoxia. In the BODE index study,13 hematocrit was significantly lower in the patients who died than in those who survived. That this variable was not selected by the statistical process in the BODE index may be surprising in view of our observations. However, the populations of patients are very different, ours being restricted to patients with very severe COPD needing LTOT.

Conclusion and Perspectives
Because of the limitations outlined above, this study cannot be more than a token of the putative clinical relevance of anemia in severe COPD patients. It is, however, an important addition to the existing anecdotal evidence pointing to this common sense possibility. In our view, the observations presented are a strong incentive for confirmatory prospective studies assessing the prognostic value of low hemoglobin levels in severe COPD patients, and in other forms of respiratory insufficiency. It would be useful to assess the effects of oxygen therapy on the production of erythropoietin. Finally, the question of the correction of hemoglobinemia in COPD should be raised and the corresponding pathophysiologic and prognostic effects assessed. Meanwhile, clinicians should be aware that anemia can be an issue in COPD patients; seeking and correcting associated factors such as GI bleeding or folate deficiency is probably particularly important in this setting.


   Acknowledgements
 
The authors thank Dr. D. Veale for editorial assistance and Ms. F. Binet for technical assistance. The authors acknowledge all the regional associations who provide data to the observatory: AIR Angers, AVD Angoulême, DDS Besançon, AVAD Bordeaux, AIR Caen, AIRRA Clermont-Ferrand, ALIZE Dijon, ADAIR Fouquières, AGIR Grenoble, GHAHR Le Havre, ARARR La Réunion, SANTELYS Respiration Lille, ALAIR Limoges, ARARD Marseille, APARD Montpellier, AIR Mulhouse, ARAIRLOR Nancy, ARIRPLO Nantes, CARDIF Paris, ARAIRCHAR Reims, AADAIRC Rochefort, ADIR Rouen, ADIRAL Strasbourg, SADIR Toulouse, and ARAIR Tours.


   Footnotes
 
Abbreviations: ANTADIR = Association Nationale pour le Traitement à Domicile de l’Insuffisance Respiratoire; BMI = body mass index; BODE = body mass index, airflow obstruction, dyspnea, and exercise capacity; CI = confidence interval; IL = interleukin; LTOT = long-term oxygen therapy; TNF = tumor necrosis factor; VC = vital capacity

Dr. Chambellan was supported by a grant from the Association Regionale de l’Insuffisance Respiratoire des Pays de la Loire.

Received for publication January 13, 2005. Accepted for publication February 14, 2005.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Pauwels, RA, Buist, AS, Calverley, PM, et al (2001) Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) Workshop summary. Am J Respir Crit Care Med 163,1256-1276[Free Full Text]
  2. Burrows, B, Bloom, JW, Traver, GA, et al The course and prognosis of different forms of chronic airways obstruction in a sample from the general population. N Engl J Med 1987;317,1309-1314[Abstract]
  3. Traver, GA, Cline, MG, Burrows, B Predictors of mortality in chronic obstructive pulmonary disease: a 15-year follow-up study. Am Rev Respir Dis 1979;119,895-902[ISI][Medline]
  4. Nocturnal Oxygen Therapy Trial Group. Continuous or nocturnal oxygen therapy in hypoxemic chronic obstructive lung disease: a clinical trial Ann Intern Med 1980;93,391-398[CrossRef][ISI][Medline]
  5. Long term domiciliary oxygen therapy in chronic hypoxic cor pulmonale complicating chronic bronchitis and emphysema: report of the Medical Research Council Working Party. Lancet 1981;1,681-686[CrossRef][Medline]
  6. MacNee, W, Wiggs, B, Belzberg, AS, et al The effect of cigarette smoking on neutrophil kinetics in human lungs. N Engl J Med 1989;321,924-928[Abstract]
  7. Wouters, EF Chronic obstructive pulmonary disease: 5. Systemic effects of COPD. Thorax 2002;57,1067-1070[Abstract/Free Full Text]
  8. Di Francia, M, Barbier, D, Mege, JL, et al Tumor necrosis factor-{alpha} levels and weight loss in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1994;150,1453-1455[Abstract]
  9. Landbo, C, Prescott, E, Lange, P, et al Prognostic value of nutritional status in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1999;160,1856-1861[Abstract/Free Full Text]
  10. Schonhofer, B, Wenzel, M, Geibel, M, et al Blood transfusion and lung function in chronically anemic patients with severe chronic obstructive pulmonary disease. Crit Care Med 1998;26,1824-1828[ISI][Medline]
  11. Schonhofer, B, Bohrer, H, Kohler, D Blood transfusion facilitating difficult weaning from the ventilator. Anaesthesia 1998;53,181-184[CrossRef][ISI][Medline]
  12. Upchurch, GR, Jr, Proctor, MC, Henke, PK, et al Predictors of severe morbidity and death after elective abdominal aortic aneurysmectomy in patients with chronic obstructive pulmonary disease. J Vasc Surg 2003;37,594-599[Medline]
  13. Celli, BR, Cote, CG, Marin, JM, et al The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med 2004;350,1005-1012[Abstract/Free Full Text]
  14. Chailleux, E, Fauroux, B, Binet, F, et al Predictors of survival in patients receiving domiciliary oxygen therapy or mechanical ventilation: a 10-year analysis of ANTADIR observatory. Chest 1996;109,741-749[CrossRef][ISI][Medline]
  15. Chailleux, E, Laaban, JP, Veale, D Prognostic value of nutritional depletion in patients with COPD treated by long-term oxygen therapy: data from the ANTADIR observatory. Chest 2003;123,1460-1466[CrossRef][ISI][Medline]
  16. Standardized lung function testing. Official statement of the European Respiratory Society. Eur Respir J Suppl 1993;16,1-100[Medline]
  17. World Health Organization. Nutritional anemias: report of a WHO scientific group. WHO Technical Report Series 405. 1968,1-37 World Health Organization. Geneva, Switzerland:
  18. Baldwin, EF, Cournand, A, Richards, DW Pulmonary insufficiency: III. A study of 122 cases of chronic pulmonary emphysema. Medicine 1949;28,201-210[CrossRef][Medline]
  19. Wilson, RH, Borden, C, Ebert, RV Adaptation to anoxia in chronic pulmonary emphysema. Arch Intern Med 1951;88,581-585[Medline]
  20. Vanier, T, Dulfano, J, Wu, C, et al Emphysema, hypoxia and the polycthemic response. N Engl J Med 1963;269,169-178[Medline]
  21. Cocking, JB, Darke, CS Blood volume studies in chronic obstructive non-specific lung disease. Thorax 1972;27,44-51[Abstract/Free Full Text]
  22. Renzetti, AD, Jr, McClement, JH, Litt, BD The Veterans Administration Cooperative Study of Pulmonary Function: 3. Mortality in relation to respiratory function in chronic obstructive pulmonary disease. Am J Med 1966;41,115-129[CrossRef][ISI][Medline]
  23. Freedman, M, Sutin, D Blood disorders and their management in old age. Brocklehurst’s textbook of geriatric medicine and gerontology 5th ed. 1998,1247-1288 Churchill Livingstone. New York, NY:
  24. Anthonisen, NR, Wright, EC, Hodgkin, JE Prognosis in chronic obstructive pulmonary disease. Am Rev Respir Dis 1986;133,14-20[ISI][Medline]
  25. Wilson, DO, Rogers, RM, Wright, EC, et al Body weight in chronic obstructive pulmonary disease: The National Institutes of Health Intermittent Positive-Pressure Breathing Trial. Am Rev Respir Dis 1989;139,1435-1438[ISI][Medline]
  26. Means, RT, Jr Advances in the anemia of chronic disease. Int J Hematol 1999;70,7-12[ISI][Medline]
  27. Al-Ahmad, A, Rand, WM, Manjunath, G, et al Reduced kidney function and anemia as risk factors for mortality in patients with left ventricular dysfunction. J Am Coll Cardiol 2001;38,955-962[Abstract/Free Full Text]
  28. Chung, KF Cytokines in chronic obstructive pulmonary disease. Eur Respir J Suppl 2001;34,50s-59s[CrossRef][Medline]
  29. de Leeuw, PW, Dees, A Fluid homeostasis in chronic obstructive lung disease. Eur Respir J Suppl 2003;46,33s-40s[CrossRef][Medline]
  30. Farber, MO, Roberts, LR, Weinberger, MH, et al Abnormalities of sodium and H2O handling in chronic obstructive lung disease. Arch Intern Med 1982;142,1326-1330[CrossRef][ISI][Medline]
  31. Oren, R, Beeri, M, Hubert, A, et al Effect of theophylline on erythrocytosis in chronic obstructive pulmonary disease. Arch Intern Med 1997;157,1474-1478[Medline]
  32. Calverley, PM, Leggett, RJ, McElderry, L, et al Cigarette smoking and secondary polycythemia in hypoxic cor pulmonale. Am Rev Respir Dis 1982;125,507-510[Medline]
  33. Foley, RN, Parfrey, PS, Harnett, JD, et al The impact of anemia on cardiomyopathy, morbidity, and mortality in end-stage renal disease. Am J Kidney Dis 1996;28,53-61[ISI][Medline]
  34. Tammemagi, CM, Neslund-Dudas, C, Simoff, M, et al Impact of comorbidity on lung cancer survival. Int J Cancer 2003;103,792-802[CrossRef][ISI][Medline]
  35. Al Falluji, N, Lawrence-Nelson, J, Kostis, JB, et al Effect of anemia on 1-year mortality in patients with acute myocardial infarction. Am Heart J 2002;144,636-641[ISI][Medline]
  36. Carson, JL, Duff, A, Poses, RM, et al Effect of anaemia and cardiovascular disease on surgical mortality and morbidity. Lancet 1996;348,1055-1060[CrossRef][ISI][Medline]
  37. Vincent, JL, Baron, JF, Reinhart, K, et al Anemia and blood transfusion in critically ill patients. JAMA 2002;288,1499-1507[Abstract/Free Full Text]
  38. Wu, WC, Rathore, SS, Wang, Y, et al Blood transfusion in elderly patients with acute myocardial infarction. N Engl J Med 2001;345,1230-1236[Abstract/Free Full Text]
  39. Silverberg, DS, Wexler, D, Sheps, D, et al The effect of correction of mild anemia in severe, resistant congestive heart failure using subcutaneous erythropoietin and intravenous iron: a randomized controlled study. J Am Coll Cardiol 2001;37,1775-1780[Abstract/Free Full Text]
  40. Corwin, HL, Gettinger, A, Pearl, RG, et al The CRIT Study: anemia and blood transfusion in the critically ill; current clinical practice in the United States. Crit Care Med 2004;32,39-52[CrossRef][ISI][Medline]
  41. Cappell, MS, Nadler, SC Increased mortality of acute upper gastrointestinal bleeding in patients with chronic obstructive pulmonary disease: a case controlled, multiyear study of 53 consecutive patients. Dig Dis Sci 1995;40,256-262[CrossRef][ISI][Medline]

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