Author + information
- Received August 21, 2018
- Revision received October 17, 2018
- Accepted October 17, 2018
- Published online January 3, 2019.
- Muhammad S. Panhwar, MDa,
- Ankur Kalra, MDb,∗ (, )
- Tanush Gupta, MDc,
- Dhaval Kolte, MD, PhDd,
- Sahil Khera, MD, MPHe,
- Deepak L. Bhatt, MD, MPHf and
- Mahazarin Ginwalla, MD, MSb
- aDepartment of Medicine, Division of Cardiovascular Medicine, Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, Ohio
- bDivision of Cardiovascular Medicine, Harrington Heart and Vascular Institute, University Hospitals Cleveland Medical Center, Case Western Reserve University School of Medicine, Cleveland, Ohio
- cDivision of Cardiology, Montefiore Medical Center, Albert Einstein College of Medicine, New York, New York
- dDivision of Cardiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
- eDivision of Cardiology, New York-Presbyterian Hospital, Columbia University Medical Center, New York, New York
- fDivision of Cardiovascular Medicine, Brigham and Women’s Hospital Heart and Vascular Center, Harvard Medical School, Boston, Massachusetts
- ↵∗Address for correspondence:
Dr. Ankur Kalra, Division of Cardiovascular Medicine, Department of Medicine, Case Western Reserve University School of Medicine, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Mailstop LKS 5038, Cleveland, Ohio 44106.
Objectives This study sought to determine whether influenza infection increases morbidity and mortality in patients hospitalized with heart failure (HF).
Background Patients with HF may be at increased risk of morbidity and mortality from influenza infection. However, there are limited data for the associated hazards of influenza infection in HF patients.
Methods We queried the 2013 to 2014 National Inpatient Sample database for all adult patients (18 years of age or older) admitted with HF with and without concomitant influenza infection. Propensity score matching was used to match patients across age, race, sex, and comorbidities. Outcomes included in-hospital mortality, in-hospital complications, length of stay, and average hospital costs.
Results Of 8,189,119 all-cause hospitalizations in patients with HF, 54,590 (0.67%) had concomitant influenza infection. Patients with concomitant influenza had higher incidence of in-hospital mortality (6.2% vs. 5.4%, respectively; odds ratio [OR]: 1.15 [95% confidence interval [CI]: 1.03 to 1.30]; p = 0.02), acute respiratory failure (36.9% vs. 23.1%, respectively; OR: 1.95 [95% CI: 1.83 to 2.07]; p < 0.001), acute respiratory failure requiring mechanical ventilation (18.2% vs. 11.3%, respectively; OR: 1.75 [95% CI: 1.62 to 1.89]; p < 0.001), acute kidney injury (AKI) (30.3% vs. 28.7%, respectively; OR: 1.08 [95% CI: 1.02 to 1.15]; p = 0.01), and AKI requiring dialysis (2.4% vs. 1.8%, respectively; OR: 1.37 [95% CI: 1.14 to 1.65]; p = 0.001). Patients with influenza had longer mean lengths of stay (5.9 days vs. 5.2 days, respectively; p <0.001) but similar average hospital costs ($12,137 vs. $12,003, respectively; p = 0.40).
Conclusions Influenza infection is associated with increased in-hospital morbidity and mortality in patients with HF. Our results emphasize the need for efforts to mitigate the incidence of influenza, specifically in this high-risk patient cohort.
Influenza infection is responsible for significant morbidity and mortality, with more than 600,000 reported influenza hospitalizations in 2016 to 2017 in the United States (1). Patients with heart failure (HF) are especially susceptible to influenza-related complications, including acute decompensated HF and secondary pneumonia (2–3). With an estimated 6 million patients in the United States with prevalent HF (4), influenza poses a major socioeconomic and public health concern. To the present authors' knowledge, there are limited data regarding morbidity and mortality of influenza infection in HF patients (2,5–8). The present study used the National Inpatient Sample (NIS), a large, national inpatient database, to examine the additional risk posed by influenza infection in hospitalized HF patients.
The NIS is the largest all-payer inpatient database and includes a sample of more than 94% of discharges across U.S. hospitals (9). The 2013 to 2014 NIS was used to identify all patients ≥18 years of age with HF-associated hospitalizations by using International Classification of Diseases-9th edition-Clinical Modification (ICD-9-CM) codes 402.01, 402.11, 402.91, 404.01, 404.03, 404.11, 404.13, 404.91, 404.93, and 428.XX (10). Cases with concomitant influenza were identified by using ICD-9-CM diagnostic codes 487.0, 487.1, 487.8, 488.01, 488.02, 488.09, 488.11, 488.12, 488.19, 488.81, 488.82, and 488.89. Given the de-identified nature of NIS data, this study was considered exempt from institutional review board approval.
Baseline characteristics included age, race, sex, insurance status, hospital-level characteristics, and comorbidities (Table 1). To reduce confounding from differences in baseline characteristics, 1:1 propensity score matching was performed using “nearest neighbor” matching, with a caliper width of 0.2 across age, race, sex, discharge weights, insurance status, hospital characteristics, and all comorbidities listed in Table 1. In an additional analysis, we included admission month in the propensity score model.
Our primary outcome was in-hospital mortality. Secondary outcomes included incidence of acute kidney injury (AKI), AKI requiring dialysis, acute respiratory failure, acute respiratory failure requiring mechanical ventilation, length of stay, and average hospital costs. We also examined the use of mechanical circulatory support (MCS), defined as the use of either intra-aortic balloon counter-pulsation pump, percutaneous MCS, or extracorporeal membrane oxygenation (see Online Table 1 for ICD-9-CM codes used).
All statistical analyses were conducted, accounting for the complex design of the NIS as recommended by the Agency of Healthcare Research and Quality (9,11). Discharge weights were used to generate national estimates. Propensity score matching was conducted in RStudio version 1.1 software (Boston, Massachusetts), using the MatchIt function. All other statistical analyses were done using SPSS version 25 (IBM, Armonk, New York).
Categorical variables are proportions, and continuous variables are mean ±SD or SE. Categorical variables were compared using the Pearson chi-square test and continuous variables with Student’s t test. In the matched cohort, we used univariate logistic or linear regression models to compare in-hospital outcomes of patients with HF with and without influenza. Unadjusted and adjusted odds ratios are given along with 95% confidence intervals (CIs) to report the results of the regression analyses in the unmatched cohort. Statistical significance for p values was set at <0.05.
Of 8,180,110 (weighted) HF-associated hospitalizations in patients ≥18 years of age during the study period, 54,590 patients (0.67%) had a concomitant discharge diagnosis of influenza.
Patients with influenza were more likely to be older (age 73 ± 14 years vs. 72 ± 13 years, respectively; p = 0.001), women (54.5% vs. 50.9%, respectively; p = 0.001), and white (72.5% vs. 71.5%, respectively; p = 0.03). Baseline characteristics are displayed in Table 1. Propensity score matching resulted in a more balanced population, with 54,585 records in each group. All standardized mean differences were <0.10 in the matched cohorts, indicating adequate balance (12).
In the propensity score-matched population, patients with concomitant influenza had a higher incidence of in-hospital mortality (6.2% vs. 5.4%, respectively; OR: 1.15 [95% CI: 1.03 to 1.30]; p = 0.02), acute respiratory failure (36.9% vs. 23.1%, respectively; OR: 1.95 [95% CI: 1.83 to 2.07]; p < 0.001), acute respiratory failure requiring mechanical ventilation (18.2% vs. 11.3%, respectively; OR: 1.75 [95% CI: 1.62 to 1.89]; p < 0.001), acute kidney injury (AKI; 30.3% vs. 28.7%, respectively; OR: 1.08 [95% CI: 1.02 to 1.15]; p = 0.01), and AKI requiring dialysis (2.4% vs. 1.8%, respectively; OR: 1.37 [95% CI: 1.14 to 1.65]; p = 0.001), but similar use of percutaneous MCS (0.7% for both groups; OR for influenza cohort: 1.01 [95% CI: 0.74 to 1.39]; p = 0.93) (Figure 1, Table 2). Patients with influenza had longer length of stay (mean: 5.9 [0.04] days vs. 5.2 [0.04] days, respectively; p <0.001) but similar average hospital costs ($12,137 [$172] vs. $12,003 [$150], respectively; p = 0.40). In an additional analysis with the admission month included in the propensity score model, the findings were largely similar, except that the association of influenza with higher in-hospital mortality was no longer statistically significant (Online Table 2). Similar results were seen in multivariable regression analysis in the unmatched cohort (Table 2).
In this large, national propensity-matched analysis of more than 100,000 HF-associated hospitalizations, the study found that influenza infection was an independent predictor of in-hospital mortality, adverse clinical outcomes, and increased length of stay.
Patients with HF have limited cardiac, renal, and pulmonary reserve, making them more susceptible to insults from influenza infection. Influenza has been linked to increased incidence of acute myocardial infarction and acute decompensated HF (2–3,5–8). Although the exact cause is still unclear, one proposed mechanism is the activation of inflammatory and immunological pathways leading to acute myocardial dysfunction (13).
In patients with HF, vaccination may reduce HF-associated morbidity and mortality (5,14,15). Although vaccinations are strongly recommended in patients with cardiovascular disease (16), rates of vaccination remain low in the United States. Only 46.8% of all adults were vaccinated during the 2016 to 2017 influenza season (1). This low rate persists in HF patients, with 1 study reporting only 55.5% of HF patients in the U.S. received influenza vaccinations (15).
In summary, analysis of the present findings demonstrates that influenza is associated with significantly increased mortality and morbidity in patients with HF. This has important implications for both patients and providers who take care of HF patients and highlights the need for heightened efforts to prevent influenza infection in this high-risk cohort.
First, the findings may not be generalizable to the outpatient setting because NIS captures only inpatient records. NIS is also reliant on ICD-9 codes; thus, there may be misdiagnoses of HF and influenza based on training and expertise of the coders. It was also not possible to verify diagnosis of influenza (laboratory-confirmed vs. clinical diagnosis), or the type, duration, and severity of HF. Also, the present authors were unable to study the influence of vaccination status on outcomes, as that information is not included in the NIS database. Finally, vitamin D deficiency has been suggested to be associated with influenza infection and HF (17,18). However, the authors were unable to examine its effect in this study due to possible under-coding and lack of information for severity, duration, and treatment status of nutritional deficiencies in administrative databases.
The present study has demonstrated that influenza infection among patients with HF is associated with greater in-hospital mortality and adverse clinical outcomes. Influenza vaccination has been shown to reduce morbidity and mortality in patients with HF, and the results of the present study emphasize the need for increased efforts to increase influenza vaccination rates and develop vaccines that provide more thorough protection.
COMPETENCY IN MEDICAL KNOWLEDGE: Influenza is a major public health challenge and is associated with increased morbidity and mortality in patients hospitalized with HF. Our study highlights the need for efforts to prevent influenza infection in patients with HF, including increasing vaccination rates and development of more effective vaccines.
TRANSLATIONAL OUTLOOK: Although influenza is associated with increased morbidity and mortality in HF patients, the exact pathophysiological mechanism is unclear. Further work to elucidate this link is needed.
Dr. Kalra consults for Medtronic and Philips. Dr. Bhatt is on advisory boards of Cardax, Elsevier Practice Update Cardiology, Medscape Cardiology, and Regado Biosciences; boards of directors of Boston VA Research Institute, Society of Cardiovascular Patient Care, and TobeSoft; is chair of American Heart Association Quality Oversight Committee; is on data monitoring committees for Baim Institute for Clinical Research, Cleveland Clinic, Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine, and Population Health Research Institute; receives honoraria from American College of Cardiology (Senior Associate Editor, Clinical Trials and News; Vice-Chair, ACC Accreditation Committee), Baim Institute for Clinical Research, Belvoir Publications (Editor in Chief, Harvard Heart Letter), Duke Clinical Research Institute (clinical trial steering committees), HMP Global (Editor in Chief, Journal of Invasive Cardiology), Journal of the American College of Cardiology (Guest Editor; Associate Editor), Population Health Research Institute, Slack Publications (Chief Medical Editor, Cardiology Today’s Intervention), Society of Cardiovascular Patient Care (Secretary/Treasurer), WebMD (CME steering committees), Clinical Cardiology (Deputy Editor), NCDR-ACTION Registry Steering Committee (Chair), and VA CART Research and Publications Committee (Chair); receives research funding from Abbott, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Chiesi, Eisai, Ethicon, Forest Laboratories, Idorsia, Ironwood, Ischemix, Lilly, Medtronic, PhaseBio, Pfizer, Regeneron, Roche, Sanofi Aventis, Synaptic, and The Medicines Company; receives royalties from Elsevier (Editor, Cardiovascular Intervention: A Companion to Braunwald’s Heart Disease); is site co-investigator for Biotronik, Boston Scientific, St. Jude Medical, and Svelte; is a trustee of American College of Cardiology; does unfunded research with FlowCo, Merck, Novo Nordisk, PLx Pharma, and Takeda; and serves on the Steering Committee of INVESTED. Dr. Ginwalla is site principal investigator for GALACTIC-HF and PRIME-HF studies; and consults for Xact Labs. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Abbreviations and Acronyms
- acute kidney injury
- heart failure
- Received August 21, 2018.
- Revision received October 17, 2018.
- Accepted October 17, 2018.
- 2018 American College of Cardiology Foundation
- U.S. Centers for Disease Control and Prevention
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