Abstract
Background
Influenza vaccination is recommended to patients with heart failure (HF), who are vulnerable to severe complications from respiratory infections. However, data on its impacts on in-hospital outcomes remain limited.
Methods
We analyzed the National Inpatient Sample (2018 to 2020), including adults (≥ 18 years) hospitalized with acute respiratory infection (ARI) and HF, identified using ICD-10 CM Codes(ARI: J09.x–J11.x, J12.x–J18.x, J20.x, J21.x; HF: I50.x, I0981, I110, I130, I132, I97130, I97131, O29121–O29129, Z95811, Z95812). The primary outcome was in-hospital mortality. Secondary outcomes included mechanical ventilation use, sepsis, length of stay (LOS) in hospital, and inflation-adjusted total hospital charges. Multivariable logistic and linear regression models assessed associations between influenza vaccination and outcomes, adjusting for demographic, clinical, socioeconomic and hospital-level factors.
Results
Among 491,210 hospitalizations for patients with HF and ARI, 28% (137,538) received influenza vaccination. Vaccinated patients with HF had significantly lower odds of in-hospital mortality (OR: 0.32; 95% CI, 0.23–0.46; p < 0.001), mechanical ventilation (OR: 0.67; 95% CI, 0.54–0.83; p < 0.001), and sepsis (OR: 0.63; 95% CI, 0.45–0.88; p = 0.006). They also had lower total hospital charges (β = −$3181; 95% CI, −$5264 to –$1098; p = 0.003). No significant difference was found in LOS (β = −0.05; 95% CI, −0.21 to 0.12; p = 0.6).
Conclusion
Influenza vaccination for ARI is linked to lower mortality, fewer complications, and reduced health care costs. These findings support the promotion of inpatient vaccination to improve outcomes and reduce burden in the high-risk population.
Keywords: Influenza vaccination, Heart failure, Acute respiratory illness, In-hospital mortality
1. Introduction
Heart failure (HF) is a major public health concern, affecting over 6.5 million adults in the United States and contributing significantly to healthcare costs, hospitalizations, and mortality [1], [2]. Despite advances in treatment, HF remains a leading cause of adult hospital admissions [3], with high 30-day (20–25%) and 90-day (over 30%) readmission rates [4], reflecting the clinical instability and vulnerability of this population.
Among the many consequences of this vulnerability is an increased susceptibility to respiratory infections, such as influenza [5], which can trigger HF exacerbations, prolong hospital stays, or result in death due to increased cardiovascular stress during infection [6], [7]. Moreover, seasonal influenza outbreaks are associated with a 30–50% rise in HF-related hospitalizations [6], [8], underscoring the importance of preventive strategies in this high-risk group. Current guidelines, including those from the Heart Failure Society of America, recommend annual influenza vaccination as a cost-effective way to reduce complications [9]. The recommendation is corroborated by the data from observational studies and meta-analyses suggesting that vaccination may reduce HF-related mortality by preventing infections or mitigating inflammation [10], [11]. However, randomized trials have shown inconsistent results, with a 2024 meta-analysis reporting no significant reduction in cardiovascular mortality (RR, 0.80; 95% CI, 0.60–1.07), indicating a mismatch between real-world data and controlled studies [12].
Importantly, influenza vaccination rates in patients with HF remain low, often influenced by socioeconomic factors such as income, education, and healthcare access [13]. Moreover, little is known about how vaccination status affects outcomes when patients with HF are hospitalized for respiratory infections a critical clinical scenario where infection may amplify the risk of severe complications or death. Prior studies using the National Inpatient Sample (NIS) have examined trends and disparities in HF hospitalizations [3], [5], but none have specifically evaluated the impact of vaccination status on in-hospital outcomes in this context [13].
To address this gap, we analyzed data from the NIS to evaluate whether influenza vaccination is associated with improved in-hospital outcomes including mortality, mechanical ventilation use, sepsis, length of stays (LOS) in hospital, and inflation-adjusted total hospital charges among patients with HF and ARI. By leveraging a nationally representative sample, our findings aim to provide practical insights to improve care, reduce hospital burdens, and tackle inequities in managing HF and ARI.
2. Methods
2.1. Study design and data source
This retrospective, cross-sectional study analyzed inpatient admissions for patients with HF and ARI using data from the NIS between January 1, 2018, and December 31, 2020. The NIS, a component of the Healthcare Cost and Utilization Project (HCUP), is sponsored by the Agency for Healthcare Research and Quality (AHRQ) and is the largest publicly available all-payer inpatient healthcare database in the US [14]. The database represents approximately 20% of all US hospitalizations and includes over 7 million unweighted hospitalizations annually. When appropriately weighted, the NIS extrapolates to an estimated 35 million hospitalizations nationwide each year. Due to the structure of the NIS, patients who are discharged more than once during the study period may be represented multiple times in the dataset, as each hospitalization is recorded as a separate event. The dataset captures both patient- and hospital-level information from approximately 1000 hospitals across the US. For each hospitalization, up to 40 discharge diagnoses and 25 procedures are documented using International Classification of Diseases, 10th Revision (ICD-10) codes, ensuring a detailed record of clinical events and interventions. Because the NIS is a de-identified dataset, this study did not require approval from an institutional review board [15].
2.2. Study population
The study population included adults aged 18 years or older who were hospitalized with ARI and HF listed as either a primary or secondary diagnosis between 1 January 2018 and 31 December 2020. ARI hospitalizations were identified using ICD-10-CM codes for influenza (J09.x, J10.x, J11.x), pneumonia (J12.x–J18.x), and acute bronchitis/bronchiolitis (J20.x, J21.x) in patients who also had a documented diagnosis of HF (I50.x, I0981, I110, I130, I132, I97130, I97131, O29121–O29129, Z95811, Z95812). Influenza immunization was recorded during the hospitalization and identified by ICD-10-CM code Z23. Hospitalizations with missing or incomplete data were excluded from the analysis to ensure the reliability and accuracy of the results.
2.3. Data extraction
The primary outcome of interest was in-hospital mortality. Secondary outcomes included LOS in hospital, inflation-adjusted total hospital costs, use of mechanical ventilation, and diagnosis of sepsis. In-hospital mortality was defined as death occurring during the hospitalization and was recorded based on discharge status. LOS was measured as the number of days between hospital admission and discharge, with same-day discharges coded as zero days. Total hospital charges were obtained from the NIS database and adjusted for inflation to 2020 US dollars using the Consumer Price Index (CPI) provided by the US Bureau of Labor Statistics. Use of mechanical ventilation was identified using ICD-10-PCS codes 5A09B5K, 5A09C5K, 5A09D5K, 5A1935Z, 5A1945Z, 5A1955Z. Sepsis was identified using ICD-10-CM codes A40., A41., R6520, R6521. Data were also collected on various demographic, clinical, and socioeconomic variables. Demographic variables included age, sex, race/ethnicity, insurance status, and income quartile based on the patient's residential zip code.
2.4. Statistical analysis
Descriptive statistics were used to summarize the baseline characteristics. Continuous variables were presented as means with standard deviations or medians with interquartile ranges (IQRs). Categorical variables were presented as frequencies and percentages. The Kruskal–Wallis test was applied to compare baseline characteristics for continuous variables, while the chi-square test with Rao and Scott's second-order correction was used for categorical variables. We used multivariable logistic regression to assess the association between influenza immunization and binary in-hospital outcomes, including mortality, mechanical ventilation use, and sepsis, and multivariable linear regression for continuous outcomes, such as total hospital charges and LOS in hospital. Results are presented as adjusted odds ratios (aORs) for logistic models and beta coefficients (β) for linear models, with corresponding 95% confidence intervals (CIs). All models were adjusted for relevant covariates, including age, sex, race/ethnicity, insurance status, income quartile, and comorbidities. Survey-weighted methods were applied to account for the NIS's complex sampling design, and the use of survey weights, strata, and clustering ensured the findings were generalizable to the national US inpatient population. A P value of <0.05 was considered statistically significant in all analyses. All statistical analyses were conducted using R version 4.5.0 (R Foundation for Statistical Computing, Vienna, Austria).
3. Results
3.1. Baseline characteristics
After excluding hospitalizations with missing data, between 2018 and 2020, a total of 491,210 weighted hospitalizations for HF and ARI were identified. Of these, 230,080 (47%) admissions were men. The mean age with standard deviation (SD) of the overall population was 74 [13] years (Table 1). Among hospital admissions for HF and ARI, the number of confirmed influenza cases were 78,030 (16%). 75% (n = 359,090) were for white individuals, while 14% (n = 65,350) of admissions were for Black individuals. Overall, 81% (n = 395,335) of all hospitalized individuals had Medicare coverage, and 9.2% (n = 45,050) had private insurance. 33% (n = 161,030) were from those who belonged to the lowest income quartile by ZIP code ($1–$51,999), while only 16% (n = 76,720) were from those who were in the highest income quartile ($88,000 or more). The percentage of individuals with two or more comorbidities was 92% (n = 453,550).
Table 1.
Baseline characteristics of the study population.
| Characteristic | Overall N = 491,2101 | No N = 476,4351 | Yes N = 14,7751 | p-value2 |
|---|---|---|---|---|
| Age, y | 74 (13) | 74 (13) | 72 (14) | <0.001 |
| Sex | 0.2 | |||
| Female | 261,120 (53%) | 253,425 (53%) | 7695 (52%) | |
| Male | 230,080 (47%) | 223,000 (47%) | 7080 (48%) | |
| Race | <0.001 | |||
| Asian or Pacific Islander | 8955 (1.9%) | 8620 (1.8%) | 335 (2.3%) | |
| Black | 65,350 (14%) | 63,110 (14%) | 2240 (15%) | |
| Hispanic | 34,550 (7.2%) | 33,185 (7.1%) | 1365 (9.4%) | |
| Other | 12,850 (2.7%) | 12,385 (2.7%) | 465 (3.2%) | |
| White | 359,090 (75%) | 348,970 (75%) | 10,120 (70%) | |
| Confirmed influenza | 78,030 (16%) | 76,130 (16%) | 1900 (13%) | <0.001 |
| Income quartile | 0.048 | |||
| $1 - $51,999 | 161,030 (33%) | 156,000 (33%) | 5030 (35%) | |
| $52,000 - $65,999 | 139,075 (29%) | 134,720 (29%) | 4355 (30%) | |
| $66,000 - $87,999 | 107,195 (22%) | 104,105 (22%) | 3090 (21%) | |
| $88,000 or more | 76,720 (16%) | 74,640 (16%) | 2080 (14%) | |
| Insurance payer | <0.001 | |||
| Medicaid | 34,935 (7.1%) | 33,460 (7.0%) | 1475 (10.0%) | |
| Medicare | 395,335 (81%) | 384,415 (81%) | 10,920 (74%) | |
| Other | 15,400 (3.1%) | 14,675 (3.1%) | 725 (4.9%) | |
| Private | 45,050 (9.2%) | 43,415 (9.1%) | 1635 (11%) | |
| Hospital region | <0.001 | |||
| Midwest | 129,785 (26%) | 125,460 (26%) | 4325 (29%) | |
| Northeast | 83,880 (17%) | 82,305 (17%) | 1575 (11%) | |
| South | 202,650 (41%) | 196,295 (41%) | 6355 (43%) | |
| West | 74,895 (15%) | 72,375 (15%) | 2520 (17%) | |
| Hospital bedsize | <0.001 | |||
| Large | 208,725 (42%) | 201,985 (42%) | 6740 (46%) | |
| Medium | 146,795 (30%) | 142,295 (30%) | 4500 (30%) | |
| Small | 135,690 (28%) | 132,155 (28%) | 3535 (24%) | |
| Hospital location/teaching status | <0.001 | |||
| Rural | 84,275 (17%) | 82,210 (17%) | 2065 (14%) | |
| Urban, non-teaching | 111,105 (23%) | 107,485 (23%) | 3620 (25%) | |
| Urban, teaching | 295,830 (60%) | 286,740 (60%) | 9090 (62%) | |
| No. of comorbidities | 0.024 | |||
| No comorbidities | 5 (<0.1%) | 5 (<0.1%) | 0 (0%) | |
| One comorbidity | 37,655 (7.7%) | 36,330 (7.6%) | 1325 (9.0%) | |
| Two or more comorbidities | 453,550 (92%) | 440,100 (92%) | 13,450 (91%) |
Mean (SD); n (%).
Design-based KruskalWallis test; Pearson's X^2: Rao & Scott adjustment.
3.2. In-hospital mortality
The overall in-hospital mortality rate for individuals with HF and ARI was 3.7% (n = 18,410). In the adjusted analysis, patients with HF and ARI who had an immunization exhibited 68% lower odds of in-hospital mortality compared to those who were not vaccinated (OR: 0.32, 95% CI: 0.23–0.46, p < 0.001) (Supplementary Table 1). Increasing age was associated with a modest but statistically significant increase in in-hospital mortality risk (OR: 1.04, 95% CI: 1.03–1.04, p < 0.001). Men had higher odds of in-hospital mortality compared to women (OR: 1.19, 95% CI: 1.11–1.27, p < 0.001). Among racial groups, no statistically significant differences in in-hospital mortality were observed, although Hispanic individuals showed a trend toward lower in-hospital mortality (OR: 0.77, 95% CI: 0.59–1.00, p = 0.051). Confirmed influenza diagnosis was associated with reduced odds of in-hospital mortality (OR: 0.74, 95% CI: 0.66–0.82, p < 0.001).
Socioeconomic and hospital-level factors also influenced mortality outcomes. Individuals in higher income quartiles ($66,000–$87,999 and ≥ $88,000) had significantly lower odds of in-hospital mortality compared to those in the lowest income group (<$65,999), with ORs of 0.85 (95% CI: 0.77–0.94, p = 0.002) and 0.88 (95% CI: 0.79–0.99, p = 0.031), respectively. Insurance status was also significant; individuals with “other” types of insurance had higher odds of in-hospital mortality (OR: 1.59, 95% CI: 1.25–2.03, p < 0.001), while Medicare and private insurance did not show significant associations. Regional variation was evident, with hospitalization in the Northeast or West being associated with higher in-hospital mortality (Northeast OR: 1.35, 95% CI: 1.21–1.52; West OR: 1.27, 95% CI: 1.13–1.43; both p < 0.001) compared to the hospitalizations in the Midwest. Compared to large bed-size hospitals, medium bed-size hospitals and small bed-size hospitals were linked with increased in-hospital mortality (medium OR: 0.90, 95% CI: 0.83–0.99, p = 0.023; small OR: 0.88, 95% CI: 0.80–0.96, p = 0.004). Urban teaching hospitals were associated with an increased in-hospital mortality risk compared to rural hospitals (OR: 1.14, 95% CI: 1.03–1.27, p = 0.015), whereas urban non-teaching hospitals showed no significant difference. Lastly, higher Elixhauser comorbidity index scores were strongly associated with increased in-hospital mortality (OR: 1.18, 95% CI: 1.16–1.20, p < 0.001).
3.3. Mechanical ventilation
The overall mechanical ventilation rate for individuals with HF and ARI was 4.5% (n = 21,925). In the adjusted analysis, vaccinated patients with HF and ARI had 33% lower odds of receiving mechanical ventilation compared to unvaccinated patients (OR: 0.67, 95% CI: 0.54–0.83, p < 0.001) (Supplementary Table 2). Increasing age was associated with a reduced likelihood of receiving mechanical ventilation (OR: 0.97, 95% CI: 0.97–0.98, p < 0.001), while men had higher odds of receiving mechanical ventilation compared to women (OR: 1.13, 95% CI: 1.06–1.20, p < 0.001). White individuals had marginally lower odds of requiring ventilation compared to Asian or Pacific Islander individuals (OR: 0.81, 95% CI: 0.65–1.00, p = 0.05. The presence of confirmed influenza was associated with a modest but statistically significant reduction in the need for mechanical ventilation (OR: 0.88, 95% CI: 0.80–0.96, p = 0.006).
Higher income levels were inversely associated with mechanical ventilation. Compared to individuals in the lowest income quartile (<$65,999), those in the middle quartile ($66,000–$87,999) and highest quartile (≥$88,000) had significantly lower odds of requiring mechanical ventilation (OR: 0.81, 95% CI: 0.74–0.89, p < 0.001; OR: 0.80, 95% CI: 0.72–0.90, p < 0.001, respectively). Insurance status was also a significant factor: individuals with “other” insurance types (OR: 1.31, 95% CI: 1.08–1.58, p = 0.005) or private insurance (OR: 1.22, 95% CI: 1.06–1.40, p = 0.006) had higher odds of requiring mechanical ventilation compared to those with Medicaid. Regional variation was observed, with patients admitted in the Northeast hospitals, South hospitals, and West hospitals all had higher odds of mechanical ventilation compared to those in the Midwest (Northeast OR: 1.42, 95% CI: 1.27–1.58; South OR: 1.20, 95% CI: 1.10–1.31; West OR: 1.18, 95% CI: 1.05–1.32; all p < 0.01).
Hospital status also influenced mechanical ventilation rates. Patients admitted to small bed-size hospitals (OR: 0.77, 95% CI: 0.70–0.83, p < 0.001) or medium bed-size hospitals (OR: 0.88, 95% CI: 0.82–0.95, p = 0.001) had lower odds of requiring mechanical ventilation than those in large bed-size hospitals. Hospital teaching status had a pronounced effect: patients admitted in urban teaching hospitals had nearly double the odds of requiring mechanical ventilation compared to those in rural hospitals (OR: 1.95, 95% CI: 1.74–2.19, p < 0.001), and those in urban non-teaching hospitals also showed increased odds (OR: 1.51, 95% CI: 1.33–1.72, p < 0.001). Lastly, higher Elixhauser comorbidity index scores were strongly associated with increased odds of requiring mechanical ventilation (OR: 1.28, 95% CI: 1.26–1.30, p < 0.001).
3.4. Sepsis
The overall sepsis rate for individuals with HF and ARI was 2.1% (n = 10,075). In the adjusted analysis, patients with HF and ARI who had an immunization exhibited a 37% reduction in the odds of sepsis compared to unvaccinated patients (OR: 0.63, 95% CI: 0.45–0.88, p = 0.006) (Supplementary Table 3). Increasing age was associated with a slight but statistically significant reduction in sepsis risk (OR: 0.99, 95% CI: 0.99–0.99, p < 0.001), while men had higher odds of sepsis compared to women (OR: 1.14, 95% CI: 1.04–1.25, p = 0.004). Race was not a significant predictor of sepsis. Interestingly, the presence of confirmed influenza was marginally associated with increased odds of sepsis, though this finding did not reach conventional significance (OR: 1.13, 95% CI: 1.00–1.27, p = 0.056). Income level, insurance payer, and hospital region were not significantly associated with sepsis risk. Similarly, hospital bed size showed no significant impact on sepsis risk. However, patients admitted to urban non-teaching hospitals had lower odds of developing sepsis compared to those treated in rural hospitals (OR: 0.84, 95% CI: 0.71–0.98, p = 0.026), while admissions to urban teaching hospitals did not show a significant difference. Lastly, a higher Elixhauser comorbidity index was strongly associated with increased odds of sepsis (OR: 1.19, 95% CI: 1.16–1.22, p < 0.001).
3.5. Length of stay in hospital
The overall LOS in hospitals for individuals with HF and ARI was 4.0 days (IQR: 3.0, 7.0). In the adjusted analysis, LOS in hospital was comparable between vaccinated and unvaccinated patients with HF (β = −0.05; 95% CI, −0.21 to 0.12; p = 0.6) (Supplementary Table 4). Age was positively associated with LOS in hospital, with each additional year contributing a small but statistically significant increase (β = 0.01, 95% CI: 0.00 to 0.01, p < 0.001). Men had a significantly shorter LOS in hospital compared to women (β = −0.17, 95% CI: −0.24 to −0.10, p < 0.001). Compared to Asian or Pacific Islander individuals, Hispanic individuals (β = −0.34, 95% CI: −0.67 to −0.01, p = 0.041) and White individuals (β = −0.31, 95% CI: −0.62 to −0.01, p = 0.045) had significantly shorter hospital stays, while differences for other racial groups were not statistically significant.
Patients with confirmed influenza had shorter hospital stays compared to those without (β = −0.22, 95% CI: −0.31 to −0.12, p < 0.001). Socioeconomic status was also associated with LOS: individuals in higher income quartiles had significantly shorter hospital stays, with the largest effect observed in the highest quartile group ($88,000 or more) (β = −0.25, 95% CI: −0.35 to −0.14, p < 0.001), compared to the lower income quartile ($52,000 - $65,999).Compared to Medicaid recipients, those with Medicare (β = −0.32, 95% CI: −0.53 to −0.11, p = 0.003) and “other” insurance types (β = −0.45, 95% CI: −0.74 to −0.16, p = 0.002) also experienced shorter LOS in hospital, although no significant association was observed with private insurance. Regional-related factors had a marked impact on LOS. Patients hospitalized in the Northeast (β = 0.83, 95% CI: 0.71 to 0.95, p < 0.001) and South (β = 0.48, 95% CI: 0.38 to 0.58, p < 0.001) had significantly longer hospital stays than those hospitalized in the Midwest, while those hospitalized in the West had slightly shorter hospital stays (β = −0.15, 95% CI: −0.28 to −0.03, p = 0.014). Compared to large bed-size hospitals, small bed-size hospitals were associated with shorter LOS (β = −0.55, 95% CI: −0.65 to −0.45, p < 0.001). Hospital teaching also influenced LOS; urban teaching hospitals were associated with significantly longer hospital stays (β = 0.84, 95% CI: 0.74 to 0.94, p < 0.001), as were urban non-teaching hospitals (β = 0.52, 95% CI: 0.42 to 0.63, p < 0.001), compared to rural hospitals. Lastly, the higher Elixhauser comorbidity index was strongly associated with increased LOS in hospital (β = 0.48, 95% CI: 0.46 to 0.50, p < 0.001).
3.6. Inflation-adjusted total charge
The overall inflation-adjusted total charge for individuals with HF and ARI was 34,183 (20,287, 60,412). In the adjusted analysis, patients with HF and ARI who had an immunization had, on average, $3181 lower total charges compared to their unvaccinated counterparts (β = −3181, 95% CI: −5264 to −1098, p = 0.003) (Supplementary Table 5). Increasing age was also associated with a modest but statistically significant decrease in total hospital charges (β = −275, 95% CI: −319 to −231, p < 0.001). Men had an insignificant increase in hospital charges compared to women (β = 891, 95% CI: −76 to 1857, p = 0.071).
Significant racial disparities in charges were observed. Compared to Asian or Pacific Islander individuals, Black individuals (β = −11,672, 95% CI: −17,599 to −5744, p < 0.001) and White individuals (β = −14,521, 95% CI: −20,154 to −8888, p < 0.001) incurred significantly lower hospital charges, while differences for Hispanic and “Other” racial groups were not statistically significant. Individuals with confirmed influenza had significantly reduced charges compared to individuals without a confirmed influenza status (β = −4336, 95% CI: −5674 to −2997, p < 0.001). Among income groups, compared to lower income quartiles ($52,000 – $65,999 and $66,000 - $87,999), only individuals in the highest income quartile ($88,000 or more) had significantly higher charges (β = 3997, 95% CI: 1664 to 6331, p < 0.001), whereas differences in other income groups were not significant.
Insurance type did not significantly impact total hospital charges, though patients with “Other” insurance had a borderline reduction in cost (β = −3491, 95% CI: −7482 to 500, p = 0.086). The hospital region influenced hospital charges, with significantly higher costs in hospitals in Northeast (β = 15,454, 95% CI: 12,928 to 17,979, p < 0.001), hospitals in South (β = 10,909, 95% CI: 9496 to 12,322, p < 0.001), and hospitals in West (β = 27,083, 95% CI: 24,581 to 29,585, p < 0.001) compared to the hospitals in Midwest. Compared to large bed-size hospitals, small bed-size hospitals were associated with lower charges (β = −8694, 95% CI: −10,387 to −7001, p < 0.001). Urban hospitals, both non-teaching and teaching, were associated with significantly higher charges compared to rural hospitals (β = 16,951 and 19,235, respectively; p < 0.001 for both). Lastly, the higher Elixhauser comorbidity index was significantly associated with increased hospital charges (β = 6166, 95% CI: 5841 to 6490, p < 0.001).
4. Discussion
This study demonstrates that influenza vaccination is significantly associated with improved clinical outcomes and reduced healthcare costs among patients with HF and ARI. Specifically, vaccination was linked with reduced in-hospital mortality, lower likelihood of requiring mechanical ventilation or developing sepsis, and lower total hospital charges, though it was not significantly associated with LOS in hospital. These findings highlight the potential value of influenza vaccination as a preventive strategy in this high-risk population and underscore the broader implications of vaccination beyond individual-level protection.
The most clinically relevant finding was the strong protective association between influenza vaccination and in-hospital mortality, with vaccinated patients experiencing a 68% reduction in the odds of in-hospital mortality compared to their unvaccinated counterparts. This result is consistent with previous studies suggesting that influenza vaccination reduces the severity of influenza and influenza-related complications in patients with cardiovascular comorbidities [15], [16]. Several mechanisms may explain this protective effect, including reduced systemic inflammation, lower incidence of secondary infections, and prevention of acute decompensated HF triggered by influenza infection [17]. Interestingly, patients with a confirmed diagnosis of influenza were associated with lower mortality, suggesting that earlier identification and management may be beneficial.
Moreover, compared to unvaccinated patients with HF and ARI, vaccinated patients with HF and ARI had significantly lower odds of mechanical ventilation (33%) and lower odds of developing sepsis (37%), reflecting a potential attenuation of disease severity. These findings align with previous studies showing that influenza vaccination is associated with reduced severity of respiratory complications, including lower rates of ICU admission, invasive ventilation, and secondary infections among high-risk populations, such as those with cardiovascular disease [18]. These findings further reinforce the idea that vaccination may reduce the burden of critical illness in vulnerable HF patients, possibly by preventing severe viral or secondary bacterial infections that lead to respiratory failure or systemic inflammatory response [19]. Importantly, a higher Elixhauser comorbidity index, which reflects a greater burden of chronic disease, was independently associated with worse outcomes, emphasizing the risk in multimorbid patients and the importance of preventive strategies like vaccination in this subgroup.
Contrary to prior findings [18], which reported shorter hospital stays among vaccinated patients with influenza, we did not observe a significant association between influenza vaccination and LOS in hospital. This discrepancy could be due to differences in the study populations and settings. For instance, our study included a broader group of patients hospitalized with ARI, not just confirmed influenza, which may have diminished the potential effect of vaccination. Additionally, it is also possible that hospital-level factors, such as variations in discharge practices or access to post-acute care, may have influenced LOS in hospital independently of vaccination status.
However, the analysis of hospital charges revealed a meaningful benefit: compared to unvaccinated patients with HF and ARI, vaccinated patients with HF and ARI incurred $3181 lower total charges, even after adjusting for potential confounders. These findings suggest that influenza vaccination may reduce healthcare resource utilization by preventing ARI or mitigating its severity in patients with HF, thereby lowering the risk of complications such as respiratory failure or sepsis that require intensive interventions [20]. This has meaningful implications for health systems and policymakers, especially considering the high cost of hospitalization for HF patients and the scalability of influenza vaccination programs [21], [22].
Socioeconomic status and hospital characteristics substantially influenced outcomes. Patients from higher income quartiles had lower odds of in-hospital mortality, mechanical ventilation, and shorter hospital stays, reflecting disparities in health access and baseline comorbidity compared to patients from lower income quartiles. Hospital size and region were also important: compared to large bed-size hospitals, small bed-size hospitals were generally associated with lower in- hospital mortality, less mechanical ventilation use, and reduced charges, while large, urban teaching hospitals, despite their specialized care, had worse outcomes and higher costs [23]. Racial disparities were less consistent but still noteworthy. Hispanic individuals had lower in-hospital mortality, while White and Black individuals incurred significantly lower hospital charges compared to Asian or Pacific Islander individuals potentially reflecting differences in access, healthcare utilization, or systemic biases in care delivery [24], [25], [26]. Prior studies have shown that racial and ethnic disparities in influenza vaccination rates persist across the U.S., particularly among Black and Hispanic adults, due in part to differential access to preventive care, trust in healthcare systems, and structural inequities [27], [28]. These results suggest that institutional factors such as case mix (i.e., the overall clinical complexity and comorbidity burden of hospitalized patients), resource availability, and care coordination capacity may influence outcomes independent of individual patient characteristics.
Age and sex showed consistent associations across outcomes. Older age increased mortality but decreased the odds of mechanical ventilation use and sepsis, possibly due to treatment limitations or different disease trajectories in elderly patients [29], [30], [31]. Compared to women, men were associated with worse outcomes, including higher in-hospital mortality, sepsis, and mechanical ventilation, aligning with previous literature suggesting biological and behavioral sex differences in immune responses and healthcare-seeking behaviors [[31], [32]].
Collectively, these findings underscore the critical role of influenza vaccination in mitigating adverse outcomes among patients with HF and ARI. Given the low influenza vaccination rates in HF patients reported in previous studies [33], these results highlight the importance of improving influenza vaccine coverage, particularly among low-income individuals and those with a minority background. Health systems should consider implementing targeted interventions, such as point-of-care vaccination in cardiology clinics or inpatient settings, and policy-level incentives that promote preventive care integration.
Though this study offers valuable real-world evidence on the protective role of influenza vaccination in a high-risk population, there are several important limitations that warrant consideration. First, due to its retrospective and observational nature, causality cannot be definitively established between influenza vaccination and improved clinical outcomes. Although extensive adjustments were made for potential confounders, there is a possibility of residual confounders due to unmeasured variables, such as health-seeking behavior, vaccination adherence, frailty status, or outpatient management. Second, the dataset lacked some clinical details, such as ejection fraction, heart failure severity, timing of vaccination relative to admission, or laboratory parameters, which could refine risk stratification. Third, sepsis identification was based on administrative codes rather than clinical criteria, potentially leading to variation in diagnostic coding practices across institutions. Fourth, socioeconomic and hospital-level variables may not fully capture nuanced differences in care delivery or access, especially in diverse regional or institutional contexts. Lastly, the use of a large national inpatient database limits generalizability to non-hospitalized patients with HF or those treated in outpatient settings.
5. Conclusion
Influenza vaccination is associated with reduced in-hospital mortality, morbidity, and healthcare costs in patients with HF and ARI. These findings provide strong evidence supporting current guideline recommendations for annual influenza vaccination in this population and reinforce the broader public health value of routine immunization programs. Future efforts should focus on addressing disparities in vaccine access and expanding vaccination outreach to ensure optimal protection for this high-risk group.
CRediT authorship contribution statement
Aimen Shafiq: Conceptualization, Methodology, Writing – original draft. Syed Sarmad Javaid: Investigation, Visualization. Apurva Popat: Conceptualization, Methodology, Writing – original draft. Hamza Asif: Conceptualization, Investigation, Methodology. Mahlika Ahmad: Formal analysis, Investigation, Methodology, Validation. Rehan Ali: Data curation, Formal analysis, Software, Visualization. Irfa Zaheer: Methodology, Writing – review & editing. Usama Arshad: Data curation, Formal analysis, Software, Visualization. Dua Jabeen: Formal analysis, Investigation, Methodology, Validation. Alishba Karim Mandokhail: Data curation, Formal analysis, Software, Visualization. Danaish Kumar: Conceptualization, Methodology, Writing – original draft. Saeeda Khanam: Data curation, Formal analysis, Investigation, Methodology. F.N.U. Sagar: Conceptualization, Investigation, Methodology. Muhammad Shariq Usman: Conceptualization, Project administration, Resources, Supervision. Ali Hasan: Software, Writing – review & editing. Raheel Ahmed: Conceptualization, Project administration, Resources, Supervision.
Ethical statement
This study was conducted using the National Inpatient Sample (NIS) database, which is publicly available and de-identified. As such, it does not contain any patient-identifiable information. In accordance with the U.S. Department of Health and Human Services guidelines, the use of this database does not require Institutional Review Board (IRB) approval or informed consent. All methods were carried out in accordance with relevant guidelines and regulations.
Funding
None to declare.
Declaration of competing interest
All authors certify that they have no affiliations with or involvement in any organization or entity with any financial or non-financial interest in the subject matter or materials discussed in this manuscript.
Acknowledgements
None to declare.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.ahjo.2026.100757.
Appendix A. Supplementary data
Supplementary tables
References
- 1.Benjamin E.J., Blaha M.J., Chiuve S.E., Cushman M., Das S.R., Deo R., de Ferranti S.D., Floyd J., Fornage M., Gillespie C., Isasi C.R., Jiménez M.C., Jordan L.C., Judd S.E., Lackland D., Lichtman J.H., Lisabeth L., Liu S., Longenecker C.T., Mackey R.H., Matsushita K., Mozaffarian D., Mussolino M.E., Nasir K., Neumar R.W., Palaniappan L., Pandey D.K., Thiagarajan R.R., Reeves M.J., Ritchey M., Rodriguez C.J., Roth G.A., Rosamond W.D., Sasson C., Towfighi A., Tsao C.W., Turner M.B., Virani S.S., Voeks J.H., Willey J.Z., Wilkins J.T., Wu J.H., Alger H.M., Wong S.S., Muntner P. Heart disease and stroke statistics—2017 update: a report from the American Heart Association. Circulation. 2017;135:e16–e458. doi: 10.1161/CIR.0000000000000485. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Salah H.M., Minhas A.M.K., Khan M.S., Khan S.U., Ambrosy A.P., Blumer V., Vaduganathan M., Greene S.J., Pandey A., Fudim M. Trends in hospitalizations for heart failure, acute myocardial infarction, and stroke in the United States from 2004 to 2018. Am. Heart J. 2022;243:103–109. doi: 10.1016/j.ahj.2021.09.009. [DOI] [PubMed] [Google Scholar]
- 3.Jain V., Minhas A.M.K., Khan S.U., Greene S.J., Pandey A., Van Spall H.G.C., Fonarow G.C., Mentz R.J., Butler J., Khan M.S. Trends in HF hospitalizations among young adults in the United States from 2004 to 2018. JACC. Heart failure. 2022;10(5):350–362. doi: 10.1016/j.jchf.2022.01.021. [DOI] [PubMed] [Google Scholar]
- 4.Khan M.S., Sreenivasan J., Lateef N., Abougergi M.S., Greene S.J., Ahmad T., Anker S.D., Fonarow G.C., Butler J. Trends in 30- and 90-day readmission rates for heart failure. Circ. Heart Fail. 2021;14(4) doi: 10.1161/CIRCHEARTFAILURE.121.008335. [DOI] [PubMed] [Google Scholar]
- 5.Skaarup K.G., Modin D., Nielsen L., Jensen J.U.S., Biering-Sørensen T. Influenza and cardiovascular disease pathophysiology: strings attached. Eur. Heart J. Suppl. 2023;25(Suppl A):A5–A11. doi: 10.1093/eurheartjsupp/suac117. Published 2023 Feb 14. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Panhwar M.S., Kalra A., Gupta T., Kolte D., Khera S., Bhatt D.L., Ginwalla M. Effect of influenza on outcomes in patients with heart failure. JACC Heart Fail. 2019;7(2):112–117. doi: 10.1016/j.jchf.2018.10.011. [DOI] [PubMed] [Google Scholar]
- 7.Fagnoul D., Pasquier P., Bodson L., Ortiz J.A., Vincent J.-L., De Backer D. Myocardial dysfunction during H1N1 influenza infection. J. Crit. Care. 2013;28(4):321–327. doi: 10.1016/j.jcrc.2013.01.010. [DOI] [PubMed] [Google Scholar]
- 8.Kadoglou N.P.E., Bracke F., Simmers T., Tsiodras S., Parissis J. Influenza infection and heart failure-vaccination may change heart failure prognosis? Heart Fail. Rev. 2017;22(3):329–336. doi: 10.1007/s10741-017-9614-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Fukuta H., Hagiwara H., Kamiya T. Influenza vaccination in patients with heart failure: a protocol for meta-analysis of randomized controlled trials. Medicine (Baltimore) 2022;101(6) doi: 10.1097/MD.0000000000028844. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Yedlapati S.H., Khan S.U., Talluri S., et al. Effects of influenza vaccine on mortality and cardiovascular outcomes in patients with cardiovascular disease: a systematic review and Meta-analysis. J. Am. Heart Assoc. 2021;10(6) doi: 10.1161/JAHA.120.019636. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Gotsman I., Shuvy M., Tahiroglu I., Zwas D., Keren A. Influenza vaccination and outcome in heart failure. Am. J. Cardiol. 2020;128:134–139. doi: 10.1016/j.amjcard.2020.05.019. [DOI] [PubMed] [Google Scholar]
- 12.Liu R., Fan Y., Patel A., Liu H., Du X., Liu B., Di Tanna G.L. The association between influenza vaccination, cardiovascular mortality and hospitalization: a living systematic review and prospective meta-analysis. Vaccine. 2024;42(5):1034–1041. doi: 10.1016/j.vaccine.2024.01.040. [DOI] [PubMed] [Google Scholar]
- 13.Papagiannis D., Kourek C., Briasoulis A., Fradelos E.C., Papagianni E.D., Papadimopoulos I., Giamouzis G., Skoularigis J., Xanthopoulos A. Pneumococcal and influenza vaccination coverage in patients with heart failure: a systematic review. J. Clin. Med. 2024;13(11):3029. doi: 10.3390/jcm13113029. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Healthcare Cost and Utilization Project (HCUP) US Agency for Healthcare Research and Quality; Overview of the National (Nationwide) Inpatient Sample (NIS) https://hcup-us.ahrq.gov/nisoverview.jsp [Internet] [cited 2017 Nov 12]. Available from:
- 15.Behrouzi B., Bhatt D.L., Cannon C.P., et al. Association of Influenza Vaccination with Cardiovascular Risk: a Meta-analysis. JAMA Netw. Open. 2022;5(4) doi: 10.1001/jamanetworkopen.2022.8873. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Yedlapati S.H., Khan S.U., Talluri S., Lone A.N., Khan M.Z., Khan M.S., Navar A.M., Gulati M., Johnson H., Baum S., Michos E.D. Effects of influenza vaccine on mortality and cardiovascular outcomes in patients with cardiovascular disease: a systematic review and Meta-analysis. J. Am. Heart Assoc. 2021;10(6) doi: 10.1161/JAHA.120.019636. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Kadoglou N.P.E., Bracke F., Simmers T., Tsiodras S., Parissis J. Influenza infection and heart failure-vaccination may change heart failure prognosis? Heart Fail. Rev. 2017;22(3):329–336. doi: 10.1007/s10741-017-9614-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Udell J.A., Zawi R., Bhatt D.L., Keshtkar-Jahromi M., Gaughran F., Phrommintikul A., Ciszewski A., Vakili H., Hoffman E.B., Farkouh M.E., Cannon CP. Association between influenza vaccination and cardiovascular outcomes in high-risk patients: a meta-analysis. Jama. 2013;310(16) doi: 10.1001/jama.2013.279206. [DOI] [PubMed] [Google Scholar]
- 19.Loeb M., Roy A., Dokainish H., et al. Influenza vaccine to reduce adverse vascular events in patients with heart failure: a multinational randomised, double-blind, placebo-controlled trial [published correction appears in lancet glob health. 2023 Feb;11(2):e196. doi:10.1016/S2214-109X(22)00517-4.] Lancet Glob. Health. 2022;10(12):e1835–e1844. doi: 10.1016/S2214-109X(22)00432-6. [DOI] [PubMed] [Google Scholar]
- 20.Loomba R.S., Aggarwal S., Shah P.H., Arora R.R. Influenza vaccination and cardiovascular morbidity and mortality: analysis of 292,383 patients. J. Cardiovasc. Pharmacol. Ther. 2012;17:277–283. doi: 10.1177/1074248411429965. [DOI] [PubMed] [Google Scholar]
- 21.Kwok C.S., Abramov D., Parwani P., et al. Cost of inpatient heart failure care and 30-day readmissions in the United States. Int. J. Cardiol. 2021;329:115–122. doi: 10.1016/j.ijcard.2020.12.020. [DOI] [PubMed] [Google Scholar]
- 22.Kriss J.L., Black C.L., Razzaghi H., et al. Influenza, COVID-19, and respiratory syncytial virus vaccination coverage among adults - United States, fall 2024. MMWR Morb. Mortal Wkly. Rep. 2024;73(46):1044–1051. doi: 10.15585/mmwr.mm7346a1. 10.15585/mmwr.mm7346a1 Published 2024 Nov 21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Kansagara D., Englander H., Salanitro A., et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306(15):1688–1698. doi: 10.1001/jama.2011.1515. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Riester M.R., Bosco E., Bardenheier B.H., et al. Decomposing racial and ethnic disparities in nursing home influenza vaccination. J. Am. Med. Dir. Assoc. 2021;22(6):1271–1278.e3. doi: 10.1016/j.jamda.2021.03.003. [DOI] [PubMed] [Google Scholar]
- 25.Daley M.F., Reifler L.M., Shoup J.A., et al. Racial and ethnic disparities in influenza vaccination coverage among pregnant women in the United States: the contribution of vaccine-related attitudes. Prev. Med. 2023;177 doi: 10.1016/j.ypmed.2023.107751. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Danziger J., Weinhandl E., Friedman D., Mukamal K.J. Racial and ethnic disparities in seasonal influenza vaccination among Dialysis facilities in the United States. J. Am. Soc. Nephrol. 2020;31(9):2117–2121. doi: 10.1681/ASN.2020040483. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Grandhi G.R., Mszar R., Vahidy F., Valero-Elizondo J., Blankstein R., Blaha M.J., Virani S.S., Andrieni J.D., Omer S.B., Nasir K. Sociodemographic disparities in influenza vaccination among adults with atherosclerotic cardiovascular disease in the United States. JAMA Cardiol. 2021;6:87–91. doi: 10.1001/jamacardio.2020.3978. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Singleton J.A., Wortley P., Lu P.J. Influenza vaccination of persons with cardiovascular disease in the United States. Tex. Heart Inst. J. 2004;31:22–27. [PMC free article] [PubMed] [Google Scholar]
- 29.Davis M.M., Wortley P.M., Ndiaye S.M., Cowan A.E., Osta A.D., Clark S.J. Influenza vaccine for high-risk non-elderly adults: a national survey of subspecialists. Hum. Vaccin. 2008;4:229–233. doi: 10.4161/hv.4.3.5516. [DOI] [PubMed] [Google Scholar]
- 30.Liu I.F., Huang C.C., Chan W.L., Huang P.H., Chung C.M., Lin S.J., Chen J.W., Leu H.B. Effects of annual influenza vaccination on mortality and hospitalization in elderly patients with ischemic heart disease: a nationwide population-based study. Prev. Med. 2012;54:431–433. doi: 10.1016/j.ypmed.2012.03.020. [DOI] [PubMed] [Google Scholar]
- 31.2019. Sex differences in the prevalence of, and trends in, cardiovascular risk factors, treatment, and control in the United States, 2001 to 2016 | Circulation [Internet] [cited 2024 Nov 18]https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.118.035550 Available from: [DOI] [PubMed] [Google Scholar]
- 32.Sciarra F., Campolo F., Franceschini E., Carlomagno F., Venneri M.A. Gender-specific impact of sex hormones on the immune system. Int. J. Mol. Sci. 2023;24(7):6302. doi: 10.3390/ijms24076302. Jan. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Bhatt A.S., Liang L., DeVore A.D., et al. Vaccination trends in patients with heart failure: insights from get with the guidelines-heart failure. JACC Heart Fail. 2018;6(10):844–855. doi: 10.1016/j.jchf.2018.04.012. [DOI] [PubMed] [Google Scholar]
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