Prognostic value of B-type natriuretic peptide for nursing- and healthcare-associated pneumonia and aspiration pneumonia in comparison with procalcitonin and A-DROP score: a prospective cohort study

Introduction

Pneumonia has become one of the leading clinical problems faced by industrialized countries such as Japan that have aging populations (1). According to statistics provided by the Japanese government, in 2020, pneumonia was the fifth leading cause of death among the Japanese population: combined with aspiration pneumonia (the sixth leading cause), these were the cause of 8.8% of all 2020 deaths in Japan (2,3). Furthermore, less than 3% of pneumonia deaths in Japan are among people younger than 65 (3). The concept of nursing- and healthcare-associated pneumonia (NHCAP) was developed by the Japanese Respiratory Society (JRS), alongside healthcare-associated pneumonia (HCAP) criteria, based on the Japanese systems of medical and social insurance (4). Despite the fact that the American Thoracic Society/Infectious Diseases Society of America Guideline for CAP 2016 recommends removal of the HCAP categorization because of its lack of usefulness in antimicrobial selection (5), the Japanese Respiratory Society Guideline 2017 still recommend the use of the NHCAP category and it is commonly used in Japan (6). Most NHCAP patients are elderly, need nursing care, and suffer from dementia, complications caused by underlying diseases, aspiration difficulties, the discovery of multidrug-resistant bacteria, and have high rates of both in-hospital mortality and recurrence (7,8). The majority of NHCAP patients suffer from aspiration pneumonia (AP) (9). Hospitalized patients commonly experience AP (10). As noted in a report, AP prevalence increases in proportion to the age of hospitalized patients (10). Therefore, it is expected that NHCAP and AP will both increase as society ages, and their treatment will be an important issue.

In Japan, the JRS has adopted a scoring system known as A-DROP score (Age, Dehydration, Respiration, Disorientation, and Blood Pressure) (6,11). In addition to the Pneumonia Severity Index (PSI) and CURB-65, it has been demonstrated that A-DROP score is associated with NHCAP and AP prognoses (12). These scoring systems offer superior prognostic ability for CAP in comparison to NHCAP (13). These scoring systems have the additional downside of being cumbersome, because many items need to be evaluated. This means that a more efficient prognostic method is necessary for primary care physicians whose daily practice involves elderly patients with pneumonia (14). If simple and useful prognostic factors for assessing the severity of NHCAP and AP can be discovered, then pneumonia can be treated more quickly and efficiently.

However, there are still no simple markers that have been established as prognostic factors for NHCAP and AP. The biomarker procalcitonin (PCT) is reportedly useful as a prognostic indicator for CAP (15-17), as well as for NHCAP and AP (18,19). B-type natriuretic peptide (BNP) is used as the main heart failure biomarker (20,21). Hemodynamic stress on the heart caused by factors such as pneumonia is reflected by natriuretic peptides such as B-type natriuretic peptide (BNP), and it has been shown that these are useful in predicting CAP and cardiac failure prognoses (22-27). However, only minimal numbers of reports have evaluated natriuretic peptides’ prognostic value for NHCAP and AP (15,25), and the pneumonia BNP cut-off value has yet to be fully established (14,28). Furthermore, there are no reports that have evaluated the prognostic value of BNP and compared its usefulness to both PCT and A-DROP score.

How does BNP correlate with prognosis of NHCAP and AP, compared to PCT and A-DROP score? If BNP shows a correlation with prognosis of NHCAP and AP, what is the optimal cut-off value? We conducted this prospective cohort study to answer these two questions. We present the following article in accordance with the STROBE reporting checklist (available at https://atm.amegroups.com/article/view/10.21037/atm-22-4151/rc).

Methods

Patients

This prospective single-center cohort study was performed at Kanazawa Medical University Himi Municipal Hospital (a 250-bed community hospital located in Himi City, Toyama Prefecture, Japan). All patients who were diagnosed by physicians with either NHCAP or AP, who were admitted to the hospital between January 1, 2012 and July 31, 2019, and for whom both their BNP and PCT levels were determined during the first 24 hours of admission, were enrolled into the study. The criterion for inclusion was patients who had been diagnosed with NHCAP or AP. Patients who met NHCAP or AP diagnostic criteria were classified as non-CAP. Exclusion criteria for the study were patients who had been diagnosed with CAP, hospital-acquired pneumonia (HAP), pneumonia with acute heart failure (PAHF), or other varieties of pneumonia, including atypical pneumonia. Patients who met the diagnostic criteria for both PAHF and other varieties, and who were excluded, were classified as PAHF. Patients were also excluded if they had no BNP or PCT level data on admission, had other complex infections, were under 18 years old, had cardiac arrest before admission, had obvious traumatic dyspnea, or requested an early transfer to a different hospital. Of the 1,215 patients with pneumonia, 297 finally met the requirements for this study. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by Institutional Ethics Committee of Kanazawa Medical University Himi Municipal Hospital (No. 172). Informed consent was taken from all the patients.

Data collection

We collected data through review of electronic medical records. Data were collected from all participants upon admission regarding their age, sex, and initial clinical assessments and outcomes (including medical history, physical examinations, pulse oximetry (SpO₂), blood tests, arterial blood gas analyses, blood cultures, and chest radiographs or chest CT scans). We followed up with all patients until their discharge from the hospital.

Measurement of BNP and PCT

To measure BNP, we used ethylenediamine tetraacetic acid plasma samples, as well as fluorescence immunoassaying (Biosite Diagnostics, La Jolla, California, USA). To measure PCT, we used ethylenediamine tetraacetic acid plasma samples, as well as a B·R·A·H·M·S PCT-Q assay (Thermo Fisher Scientific, Waltham, MA, USA) rapid measurement kit. According to kit classifications, “PCT-negative” means a PCT concentration of <0.5 ng/mL, while ≥0.5 ng/mL is referred to as “PCT-positive”.

Definitions

At the hospital, physicians used the following signs for comprehensive pneumonia diagnoses. Pneumonia was suspected when at least three of these recently acquired respiratory signs or symptoms were present: cough, sputum production, dyspnea, chest pain, body temperature >38.0 ℃, fatigue, poor appetite, disturbed consciousness, auscultatory findings of abnormal breath sounds or pulmonary rales, white cell counts of >10 or <4×10⁹ cells/L, or other enhanced inflammatory response. A new infiltrate in the chest radiography or chest CT was considered necessary in order to make a diagnosis, but no individual biomarker or pre-specified biomarker level was required for a diagnosis.

We calculated the A-DROP score in accordance with JRS guidelines (6,11). (Age: ≥70 for males or ≥75 for females. Dehydration: blood urea nitrogen ≥20 mg/dL or any physical examination signs of dehydration. Respiration: SpO₂ ≤90% or partial pressure of arterial oxygen ≤60 Torr in room air. Orientation: any new disturbance of consciousness. Blood Pressure: systolic blood pressure ≤90 mmHg). Patients who met three or more of the five criteria were considered critically ill.

Each patient was sorted into one of these pneumonia categories. NHCAP diagnoses were made in accordance with the JRS guidelines (4,6). NHCAP includes patients who: (A) reside in a long-term care hospital or nursing home; (B) have been discharged from hospitalization within the last 90 days; (C) require nursing care because they are elderly or disabled (performance status ≥3); or (D) regularly receive outpatient infusion therapy (chronic dialysis, antibiotics, cancer chemotherapy, or immunosuppressive drugs). AP diagnoses were made based on the JRS guidelines (6,29), apparent aspiration (a condition in which aspiration was strongly expected), or the presence of abnormal swallowing function (dysphagia). In addition, we also performed water swallowing tests or swallowing endoscopy examinations for suspected cases, in order to evaluate patient swallowing function. We diagnosed HAP based on the pneumonia symptoms that had appeared within 48 hours after admission to the hospital. We tentatively defined a PAHF diagnosis, based on the above definition of pneumonia, alongside the Framingham scale (30), which suggests congestive heart failure based on a combination of clinical impression, chest radiograph, and chest CT.

Statistical analysis

The primary outcome was defined as 30-day death. The categorical variables are expressed in terms of both number and percentage, and continuous variables in terms of mean and standard deviation. In the event of missing data for a given parameter, the number of variables is shown in parentheses. We assessed the normal distribution of the continuous variables with a Kolmogorov-Smirnov test. To compare the baseline, demographic, clinical, laboratory characteristics, and outcome data between the groups of survivors and non-survivors, we used univariate analysis. We used logistic regression models to estimate biomarker measurements’ potential clinical relevance. To compare survivors and non-survivors, potential confounding variables were entered into the univariate model. We excluded variables that had a significant amount of missing data, or that were related to A-DROP score, from the multivariate model. For the univariate analysis, we used Student’s t-test for continuous variables, and the chi-square test or Fisher exact test for categorical variables. We applied Cox-regression analysis to identify predictors of death in multivariate analysis. We selected variables that were significant in the univariate model (P<0.05) for the multivariate model. These cut-off values were decided based on the hospital’s specimen inspection cut-off values. Additionally, to evaluate the potential of BNP to predict 30-day mortality, we created receiver operating characteristic (ROC) curve, calculated the cut-off value that maximizes the product of sensitivity and specificity, and compared it to PCT and A-DROP score. We generated several new scores incorporating BNP, PCT, or both into the A-DROP score. We also created ROC curves and analyzed whether the new scores would improve sensitivity and specificity. We performed our statistical analysis using the STATA software package (V.10; STATA Corp LP). We used a statistical two-tailed significance level of 0.05, and tailed all of our hypothesis testing twice.

Results

Baseline characteristics

Figure 1 shows the study flow chart. A total of 1,215 participants were diagnosed with pneumonia during the period of this study. Of these, BNP and PCT levels were measured within the first 24 hours of admission in a total of 297 non-CAP patients, who were therefore included in the analysis. Additionally, 37 participants (12%) died in the first 30 days.

Figure 1 Patient enrollment and outcome in our study. PCT, procalcitonin; BNP, B-type natriuretic peptide; HAP, hospital-acquired pneumonia; PAHF, pneumonia with acute heart failure; CAP, community-acquired pneumonia.

Table 1 shows the baseline, demographic, clinical, and laboratory characteristics, and outcome data for all participants. The mean age was 84.0±8.5. The mean BNP level was 182.6±289.3 pg/mL. There were 122 participants (41%) with PCT levels ≥0.5 ng/mL. There were 125 participants (42%) with A-DROP score ≥3. Some data were confirmed to be missing for some parameters, because physicians at the hospital failed to measure the data.

Prediction of death in analysis

Table 2 shows the results of univariate analysis of non-CAP deaths. In this analysis, BNP, PCT, A-DROP score, systolic blood pressure, heart rate, body temperature, respiratory rate, SpO₂, orientation disturbance, albumin, blood urea nitrogen, C-reactive protein, metabolic acidosis, disseminated intravascular coagulation, and period of hospitalization were significantly associated with death.

Multivariable Cox-regression analysis

Table 3 shows the results of the multivariable Cox-regression analysis of non-CAP deaths. Of the potential confounding variables that were significant in the univariate model, we excluded systolic blood pressure, heart rate, SpO₂, and orientation disturbance as confounding variables for the multivariable Cox-regression analysis, because these were closely related to A-DROP score. Therefore, we added BNP (≥200 pg/mL), PCT (≥0.5 ng/mL), A-DROP score (≥3), albumin (<3.9 mg/dL), C-reactive protein (>10 mg/dL), and disseminated intravascular coagulation to the multivariate model. In this analysis, only BNP level (cut-off value =200 pg/mL) was significant (P=0.008, 95% CI: 1.30–6.06). No significant correlation was obtained in PCT (P=0.529, 95% CI: 0.56–3.14) and A-DROP score (P=0.107, 95% CI: 0.86–4.83).

ROC curve analysis

Figure 2 shows the area under the receiver operating characteristic curve (AUC ROC) of BNP comparing it to PCT and A-DROP score. BNP yielded the highest AUC ROC in predicting non-CAP mortality (0.72) in comparison with PCT (0.67) and A-DROP score (0.69). Table 4 summarizes the likelihood ratios for optimal cut-off value of these three variables. The optimal cut-off value of BNP for predicting death was 179.3 pg/mL, with a sensitivity of 62.2% and a specificity of 76.2%. Its negative likelihood ratio was 0.50%, and the positive likelihood ratio was 2.61%. The optimal cut-off value of A-DROP score was 4.

Figure 2 Receiver operating characteristic curves for BNP (A), PCT (B), A-DROP score (C) in predicting 30-day death of Non-CAP. BNP, B-type natriuretic peptide; PCT, procalcitonin; CAP, community-acquired pneumonia; AUC ROC, area under the receiver operating characteristic curve; CI, confidence interval.

Table S1 compares the sensitivity and specificity of several new scores that incorporate BNP (≥179.3 pg/mL), PCT (≥0.5 ng/mL), or both into the A-DROP score. The A-DROP score with BNP as a single item improved a sensitivity of 64.9%, specificity of 82.3%, positive likelihood ratio of 3.67, and negative likelihood ratio of 0.43.

Discussion

This study revealed two major findings. First, BNP was significantly correlated with prognosis in the univariate analysis for non-CAP as well as for PCT and A-DROP score. However, only BNP was significantly correlated in the multivariate analysis. Second, the optimal cut-off value of BNP for predicting the prognosis of non-CAP was 179.3 pg/mL, and the prognostic ability of BNP exceeded that of PCT and A-DROP. Considering that non-CAP is an important disease, given an aging population and the work required for prognostic scoring of pneumonia, the results of this study may be clinically important.

BNP was significantly correlated with prognosis in univariate analysis for non-CAP as well as PCT and A-DROP score. However, only BNP was significantly correlated in the multivariate analysis. A number of studies have already reported on the usefulness of BNP as a prognostic factor for non-CAP (14,25). PCT is also reportedly useful for predicting NHCAP prognoses (18,19). However, it remains difficult to determine a clear benefit of PCT, due to the large variation in the cut-off values of PCT among these previous studies, as well as the small number of cases. The prognostic value of A-DROP score for NHCAP was lower than CAP’s in a previous study (13), which suggests that the application of A-DROP score to non-CAP may require further investigation. Therefore, we are convinced that BNP is useful as a prognostic biomarker in non-CAP, either used alone or incorporated into pneumonia scoring. This is the first study to compare the usefulness of these prognostic factors for non-CAP.

The optimal cut-off value of BNP was 179.3 pg/mL for predicting the prognosis of non-CAP. Christ-Crain et al. reported a BNP cut-off value of 279 pg/mL for predicting death among 302 CAP patients (28), while Usuda et al. reported a BNP cut-off value of 224.1 pg/mL for predicting death among 137 CAP patients (14). Compared to the results of these previous studies, the cut-off value of 179.3 pg/mL determined through this study seems low. However, there are still no studies that have examined BNP cut-off value for prognosis prediction of non-CAP, and the results of this study are important material toward that end. In this study, heart failure was comprehensively diagnosed according to the Framingham scale, including clinical symptoms and physical findings, and patients with congestive heart failure at the time of admission were excluded. This demonstrated that elevated BNP alone can serve as a prognostic factor for non-CAP in patients without congestive heart failure.

BNP is a simple biomarker that can be measured in about an hour at community hospitals in Japan, because it is already commonly used in heart failure treatment. Therefore, the results of this study may contribute to the rapid and efficient implementation of empiric therapy for non-CAP in primary care. BNP is predominately released by the ventricles of the heart, and it regulates numerous physiological effects, including natriuresis, diuresis, and vasodilatation (31). BNP secretion is stimulated primarily by cardiac stress, as reflected by myocardial stretch, as well as overload of pressure or volume (31). Additional triggers to induce BNP secretion that have been identified include pro-inflammatory cytokines, as well as activation of the sympathetic nervous system (32). Consequently, BNP may reflect the severity of pneumonia, as indicated by pulmonary hypertension, pressure overload of the right ventricle, and inflammatory cytokine response, as well as by heart failure (28). We have identified publications that report on the mechanism of BNP secretion in CAP (28,31,32), but were unable to locate literature on the mechanism of elevation in patients with NHCAP or AP.

This study has several limitations. First, there may be selection bias due to missing data. Second, we could not evaluate both PSI and CURB-65 because of the large amount of missing respiratory rate data. These two pneumonia severity scoring systems are widely used around the world, making it somewhat difficult to interpret the significance of BNP. However, some studies to date have demonstrated comparable prognostic values by comparing A-DROP score with PSI and CURB-65 for NHCAP (12,13). Third, we were unable to evaluate PCT as a continuous variable due to the discriminatory ability of the kit employed in this study. This may have weakened the evaluation of the prognostic value of PCT. However, this does not appear to affect our conclusion regarding the prognostic value of BNP itself. Fourth, microbiological data other than the presence of bacteremia, such as isolated pathogens and susceptibility to antimicrobial agents, were not available in this study. Therefore, we are unable to discuss the relationship between microbiological data and BNP or outcomes in this study. Finally, we did not obtain data on cardiac dynamics such as ECG or echocardiography. Consequently, we cannot deny the possibility that atrial fibrillation or any cardiac structural abnormality may have affected the BNP values. Despite these limitations, studies that have demonstrated the prognostic ability of BNP for non-CAP remain rare. Furthermore, because no previous studies have compared the prognostic ability of BNP with both PCT and A-DROP score and clarified the cut-off value of BNP, we believe that the results of this study are important as a benchmark for future studies. Further large-scale, multinational, multicenter studies to address the issues of this study would be desirable.

In conclusion, BNP may be a more clinically useful prognostic factor for NHCAP and AP than PCT or A-DROP score, and should be considered as a routine test at the beginning of these treatments. Larger studies are needed to validate that BNP is associated with the prognosis of these pneumonias and to elucidate the mechanisms involved.

Acknowledgments

We would like to thank Expressions, Inc. (http://expressions.co.jp/) for English language editing.

Funding: None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://atm.amegroups.com/article/view/10.21037/atm-22-4151/rc

Data Sharing Statement: Available at https://atm.amegroups.com/article/view/10.21037/atm-22-4151/dss

Peer Review File: Available at https://atm.amegroups.com/article/view/10.21037/atm-22-4151/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-22-4151/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by Institutional Ethics Committee of Kanazawa Medical University Himi Municipal Hospital (No. 172). Informed consent was taken from all the patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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