ABSTRACT
It is unclear whether concurrent pneumonia and chronic obstructive pulmonary disease (COPD) have a higher mortality than either condition alone. Further, it is unknown how this interaction changes over time. We explored the effect of pneumonia and COPD on inpatient, 30-day and overall mortality. We used a Veterans Health Affairs database to compare patients who were hospitalized for a COPD exacerbation without pneumonia (AECOPD), patients hospitalized for pneumonia without COPD (PNA) and patients hospitalized for pneumonia who had a concurrent diagnosis of COPD (PCOPD). We studied records of 15,065 patients with the following primary discharge diagnoses: (a) AECOPD cohort (7,154 individuals); (b) PNA cohort (4,433 individuals); and (c) PCOPD (3,478 individuals), comparing inpatient, 30-day and overall mortality in the three study cohorts. We observed a stepwise increase in inpatient mortality for AECOPD, PNA and PCOPD (4.8%, 9.5% and 13.2%, respectively). These differences persisted at 30 days post-discharge (AECOPD = 6.7%, PNA = 12.4% and PCOPD = 14.6%; p < 0.0001), but not throughout the study period (median follow-up: 37 months). With time, the death rate rose disproportionally in patients who had been admitted for AECOPD (AECOPD = 64.5%; PNA = 57.4% and PCOPD 66.2%; p < 0.001). In multivariate analysis, PCOPD predicted the greatest inpatient mortality (p < 0.001). The data showed a progression in inpatient and 30-day mortality from AECOPD to PNA to PCOPD. Pneumonia and COPD differentially affected inpatient, 30-day and overall mortality with pneumonia affecting predominantly inpatient and 30-day mortality while COPD affecting the overall mortality.
Introduction
Chronic obstructive pulmonary disease (COPD) is a progressive illness, characterized by episodes of acute deterioration in respiratory symptoms and lung function and usually requiring hospitalization. COPD is increasing as a major cause of morbidity and mortality worldwide and is now the third leading cause of death in the USA Citation(1).
Pneumonia is the 8th most common cause of death in United States with an age-adjusted death rate of 15.9 per 100,000 living individuals in 2013 Citation(2). Further, pneumonia is a major cause of hospital admission in adults, resulting in substantial morbidity and mortality Citation(3). As both conditions affect the respiratory system and are common in adults, COPD patients are often admitted with worsening respiratory conditions that may be diagnosed as acute exacerbation of COPD (AECOPD) or pneumonia.
Previously published studies of the interaction between pneumonia and COPD have yielded conflicting results. While some have shown that co-morbid COPD increases mortality in patients hospitalized for pneumonia (Citation4–8), others have failed to find such an effect (Citation9–13). A deleterious effect of pneumonia in a COPD-related admission is also controversial (Citation14–18). A recent meta-analysis by Loke and colleagues did not find a robust association between COPD and increased pneumonia-related mortality Citation(19). The studies reviewed in this meta-analysis compared COPD patients with and without pneumonia or pneumonia patients with and without history of COPD. To our knowledge, no three-group comparison of AECOPD, PNA, or PCOPD has been made with patients from the same study population.
To explore the relationship between pneumonia and COPD, and the effects of these conditions singly or together on short- and long-term mortality, we studied a large cohort of hospitalized patients in the Veterans Health Administration (VHA) network over an extended period of time. We hypothesized that admission for PCOPD is associated with a higher mortality than admission for either AECOPD or PNA alone.
Methods
Data in this study were obtained from the VHA Corporate Data Warehouse, a database containing almost all clinical data on VHA patients for the study period. We chose to include all patients from the region 16 network of hospitals during VHA fiscal years (FYs) 2000–2012. Patients who received care in multiple VA facilities were excluded. This research was approved by the Institutional Review Board of Baylor College of Medicine (H-30464), the Research and Development Committee of Michael E. DeBakey Veterans Affairs Medical Center, and the VHA region 16 Corporate Data Warehouse.
We retrospectively stratified patients into three cohorts using International Classification of Diseases (ICD)-9 codes related to the first hospital discharge during the study period at which one of the three following diagnoses was made (): (a) patients having COPD as the primary discharge diagnosis with no concurrent pneumonia diagnostic code (AECOPD cohort); (b) patients having pneumonia as the primary discharge diagnosis with no mention of COPD as inpatient or outpatient during the study period (PNA cohort); and (c) patients having concurrent primary or secondary discharge diagnoses of COPD and pneumonia (PCOPD cohort). Pneumonia was further defined by the presence of a chest imaging during the admission with an official reading by a radiologist based on chest X-ray or computed tomography (CT) scan. However, we did not have access to the content of the interpretation.
Table 1. ICD-9 codes used in this study.
We identified the first admission in the study period that met the inclusion criteria as the inception admission. The inception date for each patient was the day of the inception admission. The inception discharge date, for patients who did not die during the admission, was the date of discharge. The interval from the beginning of FY 2000 to the inception date was considered to be the preinception period. The interval from inception discharge to death, or the end of FY2012, was considered to be the post-admission period.
We extracted variables related to preadmission, admission, discharge and post-discharge periods. In addition to demographic data (age, sex, and race), we collected preinception period data, including chronic co-morbid conditions (), the number of all hospitalizations, emergency room visits, outpatient encounters, influenza and pneumococcal vaccinations (within 1 and 5 years, respectively, during preinception period), smoking status, respiratory and cardiac medication and O2 prescriptions. Patient-level variables at the time of inception admission include BMI, other discharge diagnoses, highest temperature, pulse, and respiratory rates and lowest diastolic and systolic blood pressures within the first 24 hours of inception admission. We additionally obtained post-admission period mortality data, including in-hospital mortality (death during inception admission), 30-day mortality (30 days after inception date) and overall mortality (death within the study period).
Statistical analysis
We used STATA SE version 13.1 (StataCorp, College Station, TX, USA) for data analysis. The primary analysis compared all patients in the three study cohorts. All study variables, including baseline and outcome measures, were analyzed descriptively. Percentages and counts were provided for dichotomous and polychotomous variables. Means and standard deviations were provided for continuous variables. For dichotomous variables, chi-square tests were used to evaluate the statistical significance of differences; ANOVA was used for the means of continuous variables. When three-group comparisons were statistically significant, we compared differences between each pair using Student's t-test for continuous variables with normal distribution and the Wilcoxon rank sum test for non-normally distributed variables. For the inpatient and 30-day mortality rates, we performed multivariate logistic regression analysis. In all regressions, we first included all variables mentioned above and ultimately only kept those in the model that had p-values less than 0.20, deleting one variable at a time while running new iterations of the regression. For inpatient mortality, the key independent variables included age at inception, sex, race, marital status, Charlson comorbidity index, various chronic medical conditions including cardiovascular, neurological, renal, and hepatic conditions, annual admission and outpatient encounters (for up to 3 years prior to inception admission), prescriptions for categories of cardiovascular and respiratory medications, supplemental O2 and systemic steroid administration, and influenza and pneumococcal vaccinations (within 1 and 5 years, respectively, during preinception period) during the preinception period. To assess overall mortality, we used Cox regression analysis, a common method of estimating models in which the dependent variable is a length of time—in this case, months from inception until death. For overall mortality, in addition to variables included in the inpatient mortality model, we included the other discharge diagnoses need for mechanical ventilation, vital signs, and laboratory values at inception admission.
Results
Patient characteristics
During the study period, the cohorts included 7,154 patients with AECOPD, 4,433 patients with PNA and 3,478 patients with PCOPD (total of 15,065 subjects). At baseline () the three cohorts shared a number of similarities. The PCOPD and PNA cohorts were slightly older than the AECOPD cohort and with a slightly lower mean BMI and higher rate of cigarette smoking. The PCOPD cohort had minimally but significantly higher mean Charlson comorbidity indexes compared to the other cohorts. Prior uptake of influenza and pneumococcal vaccines was greater in the PCOPD cohort. The PCOPD cohort more often suffered from cardiac co-morbid conditions, including heart failure, coronary artery disease (CAD), and atrial arrhythmias (particularly atrial fibrillation), and from lung malignancy, pulmonary thromboembolism, pleural effusion, chronic renal failure, chronic liver disease, and advanced neurological diseases. In contrast, the AECOPD cohort showed a slightly higher prevalence of chronic cor pulmonale compared to the PNA and PCOPD cohorts.
Table 2. Demographic and baseline characteristics of three study cohortsFootnote**.
During the inception admission, PCOPD and PNA patients suffered more from acute cardiac ischemia, atrial arrhythmias, lung malignancy, pulmonary thromboembolism, pleural effusion, and acute renal failure than those with AECOPD (all p < 0.0001).
Mortality
shows the mortality and other clinical outcome measures for the study cohorts. During the inception admission, 341 of 7,154 (4.8%) AECOPD patients died, compared to 422 of 4,433 (9.5%) PNA, and 460 of 3,478 (13.2%) PCOPD patients (p < 0.0001). At 30 days after discharge, these differences persisted, with mortality in AECOPD of 6.7% compared to PNA and PCOPD patients of 12.4% and 14.6%, respectively (ANOVA, p < 0.0001). The median hospital length of stay showed a stepwise increase: 4, 6 and 8 days, respectively, for patients with AECOPD, PNA and PCOPD. Requirement for mechanical ventilatory support and the proportion of patients discharged to a long-term facility followed a similar pattern.
Table 3. Mortality and other clinical outcome measures in the study cohorts.
Throughout the entire study period, however, a striking difference in results became apparent. Overall mortalities for the three cohorts, AECOPD, PNA and PCOPD were 64.5%, 57.4%, and 66.2%, respectively (p < 0.0001), suggesting that the diagnosis of COPD was a major factor in predicting mortality. shows results of a Cox regression analysis for long-term mortality of the study patients. In the long term, chronic medical conditions—specifically COPD—played an increasingly important predictive role relative to the effect of an inception admission for PNA. Kaplan–Meier survival estimates () show that while the AECOPD cohort had better survival up to 31 months of follow-up, the PNA cohort's survival surpassed that of patients with COPD.
Table 4. Predictors of long-term mortality.
Figure 1. Kaplan–Meier survival estimates for the study cohorts.
shows results from multivariate logistic regression analysis for inpatient mortality during (N = 13,377). The presence of pneumonia (odds ratio [OR] = 2.80) or COPD (1.43) each predicted inpatient mortality. Other predictors included the patient's age, Charlson comorbidity index, history of atrial arrhythmias, lung malignancy, history of pulmonary thromboembolism, chronic renal failure, and advanced neurological diseases. Prior receipt of pneumococcal vaccine and prescriptions for a statin or a beta-blocker significantly predicted lower inpatient mortality. Higher body temperature and diastolic and systolic blood pressure during the first 24 hours of inception admission predicted lower mortality, whereas variables such as higher pulse rate and higher respiratory rate predicted increased mortality. Prescription for COPD inhalational medications, including inhaled corticosteroid and long acting acetylcholine antagonists, predicted lower inpatient mortality. Predictors of mortality were similar for 30-day mortality except that COPD no longer significantly predicted higher mortality while pneumonia remained a strong predictor of 30-day mortality (OR = 2.06).
Table 5. Predictors of mortality during inception admission.
To assess the goodness of fit of our model in determining yes/no for inception death, we assert that the model predicts death if it yields a probability >0.5 and that the model predicts no death if it yields a probability <0.5. Using this criterion, the model has an error rate of 7.4% (better than the random guess of 50%).
Discussion
This retrospective cohort study was conducted to examine the outcome of hospitalization for concomitant pneumonia and COPD when compared to hospitalization for either condition alone. We chose the comparison to evaluate the interactive effects of an acute on chronic disease model that involves the same organ system. Our data revealed differential effects of pneumonia and COPD on inpatient, 30-day and overall mortality. Comparing three large cohorts of patients with AECOPD, PNA or PCOPD from the same patient population, we documented a stepwise increase in inpatient and 30-day mortality from AECOPD to PNA to PCOPD. In contrast, the presence of chronic co-morbid conditions (like COPD) continued to be an important predictor of overall mortality.
Previous reports have estimated inpatient mortality in patients with AECOPD at 3.6% (ranging from 1.8% to 20.4%), similar to the 4.8% observed in our patients Citation(20,21). In patients with pneumonia without regard to COPD, inpatient and 30-day mortality are about 8–10% and 11–13%, respectively, and 1-year mortality of 21% have been reported Citation(10,22,23). Various studies have reported an inpatient mortality of 10–11% for patients with COPD admitted due to pneumonia Citation(24,25). Reports based on large databases from USA and Canada have noted 8–16% mortality at 30 days and up to 20% mortality at 90 days in patients with COPD admitted due to pneumonia Citation(26,27). Four previous comparative studies have found no significant difference in the rate of death in patients with PCOPD compared to those with PNA alone Citation(9,11–13). Other investigators, however, have reported higher mortality for pneumonia when COPD is a co-morbid condition. In a database study of a large cohort, Holguin and colleagues reported higher inpatient mortality in pneumonia patients with COPD compared to those without COPD (25% vs. 14%) Citation(4). Similar results have been reported by four other studies Citation(5–8). In contrast, Ewig and colleagues reported slightly lower mortality in patients with COPD and pneumonia compared to pneumonia without any reported comorbidity (10.12% vs. 12.95%, respectively) Citation(10). Using 2008 UK National COPD audit data Citation(16) Myint et al, whose study most closely resembles ours, found that patients with COPD and pneumonia had an inpatient and 90-day mortality rate of 11% and 17%, respectively, compared to 7% and 13% in patients with COPD exacerbation but no pneumonia. Our study, which utilized a large single database of veteran patients to examine 3 patient cohorts showed that inpatient and 30-day mortality was greatest during hospitalization and at 90 days in PCOPD patients. The unique feature of the present study, however, was the inclusion of separate cohorts with AECOPD, PNA and PCOPD. Furthermore, because of the long time over which we followed patients, we were able to demonstrate the dominant role of the chronic disease—COPD—in determining the long-term outcome. To our knowledge no other study has reported on this interaction.
Mannino et al. showed that pneumonia is associated with more severe airflow obstruction in patients with COPD Citation(28). Thus, the difference in mortality between the cohorts with and without pneumonia can partially stem from differences in severity of airflow obstruction in the study cohorts. In particular, and consistent with other studies, age independently predicted higher inpatient, 30-day and overall mortality Citation(15).
Not surprisingly, we found that chronic medical conditions were particularly strong predictors of worse outcomes. Prior studies showed that presence of COPD with other diagnoses increase the inpatient mortality Citation(29). In particular, a history of various cardiovascular diseases forecasted unfavorable mortality outcomes. Patil et al. speculated that co-morbid conditions predispose patients to acute decompensation when they are exposed to severe acute illness Citation(30), but Corrales-Medina et al. have related this mortality to the effect of acute inflammation on vulnerable plaques in coronary arteries Citation(31).
The data presented in this study also showed some interventions that may positively affect inpatient, 30-day and overall mortality rates. As in other studies, we found that pneumococcal vaccination reduced in-hospital mortality, although it had no effect on long-term mortality Citation(32). Reduced risk of pneumococcal bacteremia with pneumococcal vaccination may decrease the severity of hospitalized pneumonia and reduce the mortality rate Citation(33). We also found a significant favorable association between statin use and reduced overall mortality. A recent meta-analysis showed a cumulative hazard ratio of 0.61 for in-hospital, pneumonia-related mortality for statin users admitted with severe infection Citation(34). Doshi et al. noted this same effect at a single Veterans Administration medical center; these authors regarded their results as particularly likely to be uninfluenced by a “healthy user” effect Citation(35). Statin use is also linked to reduced mortality in exacerbations of COPD Citation(36).
There are several potential limitations of the present study. First, we examined administrative databases without validating individual cases via medical records. In a careful study that compared VHA data from these databases with written medical records, however, Szeto et al. concluded that, across several visits, the administrative database is accurate and efficient at determining chronic medical diagnoses Citation(37). There may still be variable precision with which diagnoses are confirmed. Additionally, we did not have access to pulmonary function test data to confirm the diagnosis of COPD, nor did we review the imaging or imaging reports to ascertain diagnosis of pneumonia. Similarly, we did not check the chest imaging or its report for presence of infiltrate, which would diagnose pneumonia. Second, the databases may have inconsistent ascertainment, because we did not seek data for veterans who may choose to obtain their medical care outside the VA health-care system. Third, our study was limited to veterans who use the VHA system, consisting of a self-selected group of largely middle-aged men, many of whom have multiple co-morbid conditions. However, VHA VSF contains not only mortality data from VA databases but also contains non-VHA mortality data Citation(38).
Conclusions
The results of this study showed that pneumonia and COPD differentially affected inpatient, 30-day and overall mortality in patients hospitalized for acute lower respiratory disease. Inpatient and 30-day mortality significantly increased in cohorts with AECOPD, PNA and PCOPD, respectively. In contrast, overall mortality appeared to be much more closely related to the presence of a diagnosis of COPD.
Acknowledgments
The authors wish to thank Amelia Catherine Scholtz, PhD for her careful editing of this manuscript. Dr. Sharafkhaneh contributed to the study design, data collection, Institutional Review Board application, statistical analysis, data interpretation, and manuscript composition and revision. He is the guarantor of the content of the manuscript including the data and analysis. Dr. Spiegelman, Mr. Main, Dr. Lan, Dr. Tvakoli-Tabvasi, and Dr. Musher contributed to the study design, data collection, data interpretation, and manuscript composition and revision.
Declaration of interest
The authors declare that there are no conflicts of interest.
Funding
This work is supported by the office of Research and Development at the Department of Veterans Affairs.
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