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Clinical Chemistry 53: 2193-2201, 2007. First published October 19, 2007; 10.1373/clinchem.2007.085688
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(Clinical Chemistry. 2007;53:2193-2201.)
© 2007 American Association for Clinical Chemistry, Inc.

Infectious Disease

Midregional Pro-A-Type Natriuretic Peptide and Carboxy-Terminal Provasopressin May Predict Prognosis in Community-Acquired Pneumonia

Mar Masiá1,a, Jana Papassotiriou2, Nils G. Morgenthaler2, Ildefonso Hernández3, Conrado Shum4 and Félix Gutiérrez1

1 Infectious Diseases Unit, Internal Medicine Department, Hospital General Universitario de Elche, Alicante, Spain.
2 Research Department, BRAHMS AG, Hennigsdorf/Berlin, Germany.
3 Public Health Department, Universidad Miguel Hernández, Elche, Spain.
4 Pneumology Section, Hospital General Universitario de Elche, Alicante, Spain.

aAddress correspondence to this author at: Unidad de Enfermedades Infecciosas, Hospital General Universitario de Elche, Camí de la Almazara 11, 03203 ELCHE, Alicante, Spain. Fax 00-34-96-667 91 56; e-mail marmasia{at}ya.com.


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Background: Markers to better assess severity of disease in patients with community-acquired pneumonia (CAP) would help improve medical care of this condition. The hemodynamic biomarkers carboxy-terminal provasopressin (CT-proAVP; copeptin) and midregional proatrial natriuretic peptide (MR-proANP) are increased under septic conditions, in which MR-proANP has been described as a prognostic predictor. We aimed to explore the diagnostic accuracy of MR-proANP and CT-proAVP to predict mortality in patients with CAP.

Methods: We conducted a prospective observational study of patients with CAP. We measured biomarkers in serum samples obtained at diagnosis and performed univariate and multivariate analyses to identify potential predictors of mortality.

Results: CT-proAVP and MR-proANP concentrations were measured in 173 patients. We found a positive correlation between pneumonia severity index (PSI) and MR-proANP (rs = 0.68, P <0.0001) and between PSI and CT-proAVP (rs = 0.44, P <0.0001). Median (interquartile range) CT-proAVP and MR-proANP values were 8.2 (5.3–16.8) and 73.6 (44.6–144.0) pmol/L, respectively. Nonsurvivors had significantly higher MR-proANP and CT-proAVP than survivors (median 259.0 vs 71.8 pmol/L, P = 0.01, and 24.9 vs 8.1 pmol/L, P = 0.03, respectively). In multivariate analysis including PSI, procalcitonin, C-reactive protein, lipopolysaccharide-binding protein, CT-proAVP, and MR-proANP concentrations, only CT-proAVP remained an independent predictor of death (odds ratio 1.05, P = 0.007). Cutoff values of >18.9 pmol/L for CT-proAVP and >227 pmol/L for MR-proANP showed the highest diagnostic accuracy to predict mortality.

Conclusions: CT-proAVP and MR-proANP may be used to predict prognosis in patients with CAP.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Assessing severity of community-acquired pneumonia (CAP)1 still remains a challenge for clinicians(1)(2). In the last few years, prognostic scoring systems for CAP have been developed to stratify patients on the basis of their risk of mortality, but methods are not ideal(3). The most prominent and validated tool for this purpose, the pneumonia severity index (PSI)(1), is highly complex and can occasionally underestimate the gravity of CAP, especially in young patients without comorbid illnesses(2)(4), because it heavily weights age and comorbidity and does not directly measure CAP-specific disease severity(3).

The use of biomarkers as tools to assess diagnosis, prognosis, and treatment response in infectious diseases, including lower respiratory tract infections and sepsis, constitutes an area of growing interest for investigators(5)(6)(7)(8)(9). Biochemical inflammation and infection markers [e.g., procalcitonin (PCT), C-reactive protein (CRP), and lipopolysaccharide-binding protein (LBP)] have been the subject of intense investigation, but attention has also focused on neurohumoral hemodynamic markers. Peptide hormones involved in cardiovascular/osmotic homeostasis, such as members of the natriuretic peptide family and vasopressin (AVP), are molecules within this class of biomarkers.

Natriuretic peptides, such as atrial natriuretic peptide (ANP), play an important pathophysiological role in cardiovascular diseases(10)(11). Increased concentrations of ANP or ANP prohormone fragment have been reported to indicate cardiovascular dysfunction in septic patients(12)(13)(14). In addition, midregional proANP (MR-proANP) has been shown to be a valuable tool for risk assessment, with utility similar to that of the Acute Physiology and Chronic Health Evaluation II score to predict outcome in septic patients admitted to an intensive care unit (ICU)(14), as well as to categorize patients with CAP from a cohort of patients with lower respiratory tract infection(15).

AVP, a hormone released from the posterior pituitary gland, has vasoconstrictor and antidiuretic properties and potency to restore vascular tone in vasodilatory hypotension(16). AVP is derived from a larger precursor (proAVP) along with 2 other peptides of unknown function, neurophysin II and copeptin, the carboxy-terminal part of the precursor(17). AVP contributes to the pathogenesis of several diseases such as congestive heart failure(18). In recent studies, AVP concentrations have been shown to be increased in critically ill patients, including those with septic shock(19)(20).

We hypothesized that patients with CAP who have poor outcomes might have altered cardiovascular function/hemodynamic function biomarkers. In such patients ANP as well as AVP concentrations might be useful for predicting outcome at the initial assessment. We analyzed data from a population-based study in which patients were prospectively evaluated and an extensive microbiological investigation was carried out. Because of the short half-life of ANP and AVP, as well as instability and platelet binding of AVP(21)(22)(23), precursor fragments of both hormones [MR-proANP and the carboxy-terminal proAVP (CT-proAVP; copeptin)] were analyzed as alternative diagnostic targets. MR-proANP and CT-proAVP concentrations directly reflect the release of their rapidly degraded active hormones ANP and AVP(20)(24).

Other potential predictors of mortality were also explored, including age, sex, comorbidity (diabetes, chronic obstructive pulmonary disease, congestive heart failure, hepatic disease, chronic renal insufficiency, neoplasia, immunodepression, altered mental status, and malnutrition), arterial blood pressure (measured by aneroid sphygmomanometer), laboratory data (including PCT, CRP, and LBP concentrations), and etiology of CAP.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
A prospective population-based investigation of CAP was conducted at Hospital General Universitario de Elche, a 430-bed university-affiliated teaching hospital covering a population of about 275 000 people in Spain, as previously described(25)(26). The study was approved by the local ethics committee. All adult patients (≥15 years) with signs and symptoms compatible with pneumonia occurring during 2 consecutive periods of 12 months were eligible for inclusion in the study. Primary care physicians were asked to refer to the hospital emergency department all patients in whom a diagnosis of CAP was suspected. CAP was defined as an acute illness associated with at least 1 of the following signs or symptoms: fever (axillary temperature ≥38 °C), new cough with or without sputum production, pleuritic chest pain, dyspnea, or altered breath sound on auscultation, plus a chest radiograph showing an opacity compatible with the presence of acute pneumonia. Patients were evaluated clinically and by x-ray at the emergency department, and those with a provisional diagnosis of CAP were seen by a study investigator. Patients in whom diagnosis of pneumonia was not finally confirmed, those with a prior hospitalization within 2 weeks of a current diagnosis of pneumonia, and those in whom measurements were not performed because a serum sample was not available or was insufficient were excluded. During the first 12-month study period, from October 15, 1999, to October 14, 2000, patients gave informed consent, were enrolled in the investigation, and had a blood sample collected within the 1st 24 h after fulfilling the pneumonia criteria for routine blood analysis and measurement of biological markers. Individuals recruited through that time period comprised the cohort included in this study. All patients were followed up for at least 4 weeks or until death. An outpatient visit after discharge for collection of follow-up data was automatically scheduled. Patients who did not turn up for the appointment were interviewed by phone about clinical outcome. To calculate the severity of pneumonia, we used the PSI scoring system, which classifies patients according to age, sex, comorbidity, and clinical and laboratory data. Laboratory work-up for a patient with CAP as well as criteria for etiological diagnosis has been described in detail(25).

Because MR-proANP concentrations are age dependent(24) and CT-proAVP concentrations have been reported to be higher in males than females(20), we included data from an age- and sex-matched healthy reference group (n = 37; mean age 58.2 years; age range 19–91). We collected serum samples from the members of a local health club and employees of a local biotechnology center and their relatives/friends as described in detail(20). Written informed consent was obtained from all healthy volunteers. There was no difference in age (P = 0.76) and sex (P = 0.82) between individuals of the healthy reference group and CAP patients.

For measurement of MR-proANP and CT-proAVP, serum was separated from blood samples at the time of blood draw and frozen at –80 °C until analysis. Measurements were performed in a blinded fashion as a batch analysis by 1 trained laboratory assistant. MR-proANP measurements were performed using an immunoluminometric sandwich assay (MR-proANP LIA; Brahms AG) as described(24), but we changed the calibration of the reported assay from a synthetic peptide to native pro-ANP in human serum, which increased precision and dynamics of the assay; details on this modification have been published(14). The functional assay sensitivity (defined as the lowest value with an interassay CV <20%) was 11 pmol/L. Median MR-proANP of 325 healthy individuals in previous investigations was 45 pmol/L (interassay CV at 45 pmol/L = 10%), and the 97.5th percentile (upper limit of reference interval) was 163.9 pmol/L (interassay CV at 163.9 pmol/L = 7.5%)(24). Because measurements were performed in EDTA-plasma and no equivalence data in serum have been shown so far, we tested 100 matched EDTA-plasma and serum samples from healthy volunteers (mean age 42 years, range 18–74 years). Samples were collected as described(20).

CT-proAVP measurements were performed with a sandwich immunoluminometric assay (CT-proAVP LIA; Brahms AG), as described(20). Briefly, we used 2 polyclonal antibodies to the carboxy-terminal region (covering amino acids 132–164 of preproAVP). In contrast to measurements of mature AVP, no extraction step before measurement was needed, and the analyte showed ex vivo stability for at least 7 days at room temperature. The functional assay sensitivity was 2.25 pmol/L. Median CT-proAVP in 359 healthy individuals in previous investigations was 4.2 pmol/L (interassay CV at 4.2 pmol/L = 14%), and the 97.5th percentile was 11.25 pmol/L (interassay CV at 11.25 pmol/L = 9%)(20). MR-proANP and CT-proAVP are stable at 4 °C for at least 48 h and 14 days, respectively. No signs of degradation were observed. We also measured LBP, CRP, and PCT in serum as described(6)(26).

We tested distribution with the Kolmogorov–Smirnov test. Categorical data among survivors and nonsurvivors were compared with the {chi}2 test, and the Mann–Whitney U-test was used for comparison of continuous variables in 2 groups because they were not gaussian distributed. For multigroup comparisons, we used the Kruskal–Wallis test followed by the Dunn posttest. The relative contributions to mortality of the hemodynamic biomarkers PCT, CRP, LBP, and PSI were estimated using a multivariable logistic regression model. We used a forward-selection procedure: a variable was retained in the model if the LR test P value was <0.05. CIs (95% CI) for the adjusted odds ratios were calculated. Continuous variables were investigated for nonlinearity and fitted as having a linear relationship with the log-odds ratio of death unless there was clear evidence of nonlinearity.

We calculated the correlation between continuous variables using the Spearman correlation coefficient and used ROC curves to identify the best cutoff concentrations to predict mortality risk. Statistical analysis was performed by use of SPSS version 11.


   Results
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 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
In experiments comparing MR-proANP concentrations in 100 matched EDTA-plasma and serum samples from healthy volunteers (mean age 42 years, range 18–74 years) there was a significant correlation (P <0.0001) between MR-proANP in plasma and serum (rs = 0.98; 95% CI 0.96–0.98). Additionally, comparison of the 2 groups by use of the Wilcoxon matched-pairs test revealed no significant difference (P = 0.13) between MR-proANP values of the matched EDTA-plasma and serum samples. These results indicate equivalence of MR-proANP measurements in plasma and serum. The median, 97.5th percentile, and 99th percentile MR-proANP concentrations in serum were 44.1, 161.0, and 198.0 pmol/L, respectively. This population did not serve as a reference group in the present CAP study because of lower age and a lower percentage of men compared with the group of CAP patients.

We measured serum concentrations of MR-proANP and CT-proAVP in 173 (72.1%) of 240 CAP patients from October 15, 1999, to October 14, 2000. In the remaining patients, measurements were not performed because a serum sample obtained within the first 24 h of diagnosis of pneumonia was not available or was insufficient. There were no differences in age, sex, comorbidity, or PSI scores between patients in whom MR-proANP and CT-proAVP were measured and those in whom it was not (data not shown). Baseline characteristics of the patients are described in Table 1 . The mean (SD) age of the 173 patients was 59.3 (20.6) years and 64.2% were male. In 85 patients (49.1%) there was 1 or more underlying disease, mostly diabetes (n = 37, 21.4%) and chronic obstructive pulmonary disease (n = 36, 20.8%). The etiological distribution is shown in Table 2 .


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  		Table 1. Baseline characteristics of the patients with CAP.


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  		Table 2. Distribution of the causative microorganisms in patients admitted to hospital and in outpatients.

Compared with healthy individuals (age- and sex-matched healthy reference group), median [interquartile range (IQR)] values of MR-proANP [73.6 (44.6–144.0) vs 50.1 (32.1–112.5) pmol/L, P = 0.03] and CT-proAVP [8.2 (5.3–16.8) vs 4.3 (2.7–6.6) pmol/L, P <0.0001] were significantly increased in CAP patients, although there was a high degree of overlap between the groups. Patients with pneumonia caused by atypical organisms had lower MR-proANP concentrations than any other etiologic group (P = 0.04), than patients with bacterial pneumonia (P = 0.02), pneumonia of unknown etiology (P = 0.005), and mixed pneumonia (P = 0.03) (Table 2Up ). CT-proAVP concentrations were significantly lower in patients with atypical pneumonia than in patients whose pneumonia was bacterial (P = 0.04) or of unknown origin (P = 0.01). However, for both serum markers, there was again a high overlap between etiological groups.

The median (range) PSI score, which indicates pneumonia severity, was 70.0 (9–177). There was a positive correlation between PSI and MR-proANP concentrations (rs = 0.68, P <0.0001) and between PSI and CT-proAVP concentrations (rs = 0.44, P <0.0001). Concentrations of MR-proANP and CT-proAVP according to PSI risk class are shown in Fig. 1 , A and B. MR-proANP and CT-proAVP values exhibited a gradual increase from risk class I (the lowest risk) to risk class V (highest risk) (P <0.0001 for both cases). A positive correlation was also found for age and both MR-proANP (rs = 0.74, P <0.0001) and CT-proAVP (rs = 0.38, P <0.0001).


Figure 1
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  		Figure 1. Box plots showing MR-proANP (A) and CT-proAVP (B) in CAP patients according to PSI risk class and MR-proANP (C) and CT-proAVP (D) in CAP patients according to survival.

The box plots represent 25th, 50th, and 75th percentiles; whiskers, minimum and maximum values. The P value (Kruskal–Wallis test; top of A and B), significant differences between individual PSI classes (Dunn multiple posttest; values above the solid lines), and number of patients (percentage in parenthesis) in each group are shown. The dotted lines indicate the median MR-proANP concentration in the age- and sex-matched healthy reference group.

Seven (4%) of the 173 patients died. Nonsurvivors had significantly higher MR-proANP concentrations than patients who survived [median (IQR) 259.0 (122–281) vs 71.8 (44.0–129.5) pmol/L, P = 0.01] (Fig. 1CUp ). CT-proAVP concentrations were also significantly higher in patients who died [24.9 (8.2–105.0) vs 8.1 (5.3–16.2) pmol/L, P = 0.03] (Fig. 1DUp ). In univariate analysis, patients who died had significantly higher age (P = 0.003), PCT (P = 0.002), LBP (P = 0.004), CRP (P = 0.006), prothrombin time (P = 0.03), associated comorbidity (diabetes, chronic obstructive pulmonary disease, congestive cardiac failure, hepatic disease, chronic renal insufficiency, neoplasia, immunodepression, altered mental status, or malnutrition) (P = 0.006), and PSI score (P = 0.002) and lower systolic arterial blood pressure (P = 0.005). In multivariate analysis including PSI, PCT, CRP, LBP, and CT-proAVP and MR-proANP concentrations, the only variable that remained an independent predictor of death was CT-proAVP (odds ratio 1.05, 95% CI 1.01–1.09, P = 0.007). Hosmer-Lemeshow c statistic for the model was 5.63 (P = 0.69). When age was included in multivariate analysis, the same results were obtained (data not shown).

Median values of MR-proANP and CT-proAVP according to different dichotomic variables were compared and are summarized in Table 3 . There was no relationship between any of the biomarkers and blood pressure.


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  		Table 3. Univariate analysis of MR-proANP and CT-proAVP concentrations.

A cutoff point for MR-proANP of >227 pmol/L predicted mortality with a sensitivity of 71.4% (95% CI 29.3%–95.5%), specificity of 91% (85.5%–94.9%), positive predictive value of 25%, and negative predictive value (NPV) of 98.7%. Area under the curve was 0.78 (0.71–0.84) (Fig. 2 ). A cutoff concentration for CT-proAVP of >18.9 pmol/L predicted mortality with a sensitivity of 71.4% (29.3%–95.5%), specificity of 79.5% (72.6%–85.4%), positive predictive value of 12.8%, and NPV of 98.5%. The NPV was 100% for patients with PSI risk classes I–III. Area under the curve was 0.75 (0.68–0.81). Although the difference did not reach statistical significance, when all the variables (the combination of MR-proANP, CT-proAVP, and PSI) were analyzed together as predictors of mortality, the area under the curve was higher [0.83 (0.76–0.88)] than that of any single biomarker or PSI score [0.79 (0.72–0.84) for PSI score] separately.


Figure 2
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  		Figure 2. ROC plot analysis of the biomarkers with respect to mortality prediction in patients with CAP.

The arrays indicate the cutoff concentrations for MR-proANP (227 pmol/L) and CT-proAVP (18.9 pmol/L).


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Despite their attractiveness for clinicians, very few biochemical markers add significant information to PSI about prognosis of CAP. Currently, the most useful biomarker in the prediction of outcome of CAP is serum procalcitonin(5)(8)(27). In a previous study, we found that procalcitonin was mainly a marker of poorer outcome in patients with CAP classified into PSI high-severity risk classes(5). In a preliminary study including 58 patients with severe CAP according to PSI score, B-type natriuretic peptide was helpful for the risk stratification of patients compared with PSI(28). Christ-Crain et al.(29) have recently found that proadrenomedullin, a peptide with immune modulating, metabolic, and vascular actions, predicted severity and outcome of patients with CAP with prognostic accuracy similar to that of the PSI, in contrast to other biomarkers such as CRP and leukocyte count.

According to our results, MR-proANP and CT-proAVP could be helpful as prognostic tools. Both biomarkers correlated with PSI, and significantly higher concentrations were found in patients who died compared with survivors. In multivariate analysis of predictors of death, including procalcitonin concentrations and PSI as risk factors, CT-proAVP turned out to be the only biomarker that remained as an independent predictor. Although this finding must be interpreted with caution because of the small number of patients who died, this marker might add complementary information about severity of disease to established prognostic scores or markers such as PSI or procalcitonin, opening a way for future investigation of the role of hemodynamic factors in the prognosis of CAP. Because MR-proANP and CT-proAVP have a very high NPV, especially among PSI risk classes I–III, they could be useful to more accurately identify patients at low risk for death, who do not need admission to hospital. This information may help physicians to make more rational decisions about hospitalization for some patients with CAP.

Other factors might implicate a higher severity of disease in CAP, with high PSI score, leukocyte cell counts, bilateral pulmonary involvement, or age (above 65 years) being associated with significantly higher concentrations of MR-proANP and CT-proAVP. We found a correlation between age and MR pro-ANP and CT pro-AVP concentrations (data not shown). A trend toward a correlation between AVP and age has been reported(18). Other researchers have described a modest influence of age on natriuretic peptides(30), as well as documented hormone deficiency with advanced age(31). Despite this association, when age was included in multivariate analysis, the same results were obtained (data not shown), a finding that may indicate that at least CT-proAVP is independent from age and thus could be a valuable prognostic factor in younger people with CAP. However, no apparent relationship between CT-proAVP or MR-proANP concentrations and arterial blood pressure was found. This discrepancy may be related to earlier hemodynamic dysfunction or vascular tone/myocardial function changes not reflected in arterial blood pressure. We did find a relationship between the biomarkers and other closely related factors such as serum osmolarity, but not with plasma sodium.

Despite their prognostic value, MR-proANP and CT-proAVP had little utility for predicting etiology in CAP. Although patients with atypical pneumonia showed significantly lower concentrations of both markers than patients with pneumonia of other etiologies, there was much overlap between the different etiologic groups, limiting the usefulness of these markers for suggesting etiology.

The main limitation of our current study was the small number of patients who had a poor outcome. Because this was a population-based study, overall prognosis of the patients was good, and the number of those who died or developed complications was low. The associations found were very strong, however, and goodness of fit of the multivariate model indicates that it was well calibrated and fitted the data well. Furthermore, a close relationship of these biomarkers with most of the established prognostic factors of CAP was also observed, thereby confirming their prognostic value. The low number of deaths, however, may limit generalization of the cutoff points identified. Another limitation of the study might be the contribution of the coexisting illnesses, particularly heart disease, to the high MR-proANP concentrations of the patients. The most important factor affecting ANP secretion from the atria is mechanical stretch, such as in heart failure, but cardiac ischemia also stimulates ANP release(32). To address this issue, we excluded from data analysis patients with congestive heart failure or coronary heart disease. With those patients excluded, there were no changes in the relationships of MR-proANP with PSI score and mortality, and the results of multivariate analysis of predictors of mortality did not change (data not shown), suggesting that the prognostic accuracy of MR-proANP in CAP is not due to the presence of coexisting heart disease per se. Likewise, the concentrations of AVP can be increased in many other diseases or situations(33).

In conclusion, MR-proANP and CT-proAVP are predictors of prognosis of CAP that might expand on the information of PSI or procalcitonin. These markers may be useful in the initial management of patients with CAP. Further studies to confirm our results are needed.


   Acknowledgments
 
Grant/funding support: None declared.

Financial disclosures: Mar Masiá, Ildefonso Hernández, and Félix Gutiérrez declare that they have no competing interests. Jana Papassotiriou and Nils Morgenthaler are employees of BRAHMS AG, the manufacturer of the MR-proANP and the CT-proAVP assay.

Acknowledgments: We thank Inmaculada Jarrín (Public Health Department, Universidad Miguel Hernández) for her help in data analysis and Carlos Mirete (Hospital General Universitario de Elche) for his help in data collection. We also thank Frank Bonconseil, Angelina Herzberg, and Johanna Hetzel for excellent technical assistance.


   Footnotes
 
1 Nonstandard abbreviations: CAP, community-acquired pneumonia; PSI, pneumonia severity index; PCT, procalcitonin; CRP, C-reactive protein; LBP, lipopolysaccharide-binding protein; AVP, vasopressin; ANP, atrial natriuretic peptide; MR-proANP, midregional proANP; ICU, intensive care unit; CT-proAVP, carboxy-terminal proAVP; IQR, interquartile range; NPV, negative predictive value.


   References
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 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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