Abstract
Background
Acute heart failure (AHF) is a major cause of emergency department (ED) visits and is associated with significant morbidity and mortality. In Thailand, real-world data on AHF presentations and outcomes in the ED remain limited, particularly in resource-constrained settings. This study aimed to describe the clinical characteristics, treatment, and outcomes of AHF patients in a tertiary care ED in Northeastern Thailand and identify factors associated with in-hospital mortality.
Methods
We conducted a retrospective cohort study of adult patients (≥ 18 years) diagnosed with AHF at the ED of Srinagarind Hospital between October 2021 and March 2023. Patients transferred from other hospitals or who were pregnant were excluded. Clinical data were extracted from electronic health records. The primary outcome was in-hospital mortality. Univariable and multivariable logistic regression analyses were performed to identify factors independently associated with in-hospital mortality.
Results
Of 902 eligible AHF patients, the median age was 71 years (IQR: 60–80), and 52.0% were male. The in-hospital mortality rate was 6.0%. Non-survivors were more likely to have a history of congestive heart failure, chronic kidney disease, or cerebrovascular accident, and presented with lower diastolic blood pressure and oxygen saturation. They were also more likely to be triaged as Emergency Severity Index (ESI) level 1 and require ICU admission, ventilatory support, and inotropic support. In multivariable analysis, the need for inotropic support was the only variable independently associated with in-hospital mortality (adjusted OR 3.97; 95% CI 1.91–8.40; p < 0.001).
Conclusion
In this ED-based cohort, the in-hospital mortality of patients with acute heart failure was comparable to international reports. The need for inotropic support was strongly associated with hospital mortality, likely reflecting severe hemodynamic compromise.
Keywords: Emergency department, Acute heart failure
Introduction
Acute heart failure (AHF) is a complex clinical syndrome characterized by signs and symptoms resulting from structural or functional abnormalities that impair ventricular filling or the ejection of blood [1]. This condition is associated with high rates of morbidity and mortality worldwide. The prevalence of AHF ranges from 1% to 4% in developed countries, and the overall number of heart failure patients continues to rise [2, 3]. The American Heart Association guideline found that total deaths caused by heart failure in the U.S. increased from 275,000 in 2009 to 310,000 in 2014 [1].
Emergency department (ED) visits for AHF are common, accounting for approximately 3.9% of all annual ED encounters [4]. Early diagnosis, appropriate management, and safe disposition of patients with AHF are essential, as delays or misdiagnoses have been linked to increased risks of adverse outcomes and mortality [5–8]. In the ED setting, the clinical presentation and outcomes of AHF patients vary based on clinical phenotypes and comorbid conditions [4, 9–11]. Previous systematic reviews have identified risk scores that influence outcomes, incorporating demographic variables, comorbidities, clinical findings in the ED, and laboratory data. However, the majority of these studies have been conducted in European and North American populations [11].
In Thailand, the Heart Failure Council conducted a study from 2006 to 2007 to investigate the clinical characteristics, treatments, and outcomes of patients with acute heart failure (AHF) [12], using data collected from cardiovascular centers in Bangkok and its metropolitan areas. However, this study is now over a decade old. Given the evolving lifestyle patterns and significant advancements in AHF management, our research team recognized the need to re-examine this condition in a more current and regionally relevant context. Therefore, we aimed to investigate the clinical characteristics, treatment strategies, mortality rates, and factors associated with in-hospital mortality among patients with acute heart failure presenting to a single tertiary care emergency department in Northeastern Thailand.
Methods
Study design and population
We conducted a retrospective cohort study to collect data on patients presenting to the emergency department (ED) at Srinagarind Hospital with acute heart failure (AHF) between October 2021 and March 2023. The study was approved by the Human Research Ethics Committee of Khon Kaen University (HE661567). The requirement for informed consent was waived due to the retrospective nature of the study. The research was conducted in accordance with the principles of the Declaration of Helsinki. All data were anonymized to ensure patient confidentiality.
Eligible patients were identified by searching the ED database using diagnostic terms including “acute congestive heart failure”, “acute heart failure”, “heart failure”, “congestive heart failure”, “left ventricular failure”, and “Heart failure\ unspecified” from both principal and non-principal diagnoses. Adult patients (≥ 18 years) with a confirmed diagnosis of AHF were included. The exclusion criteria were patients transferred from other hospitals, due to potential prior treatment affecting baseline assessment, and pregnant patients, due to distinct physiological and hemodynamic characteristics.
The diagnosis of AHF was determined by the attending physician based on routine clinical assessment, incorporating clinical history, physical examination, and available investigations, including chest radiography, echocardiography, and cardiac biomarkers. No standardized adjudication process was applied.
Patient demographics, clinical characteristics, and outcomes were extracted from the electronic medical records. Additional data were obtained through manual review of medical charts and laboratory databases to ensure data completeness and accuracy.
Precipitating factors of AHF
In our cohort, we identified several precipitating factors for acute heart failure, including systemic inflammatory response syndrome (SIRS) based on standard criteria, anemia and hypertensive emergency. The specific definitions and criteria for each factor are provided in the Supplementary file.
Outcome variables
The primary outcome of this study was in-hospital mortality among patients diagnosed with AHF. Secondary outcomes included hospital admission, intensive care unit (ICU) admission and transfer, and the use of interventions such as inotropic support, mechanical ventilation, and Non-Invasive Positive Pressure Ventilation (NIPPV). Baseline clinical characteristics, precipitating factors, and laboratory findings at presentation were analyzed as potential variables associated with in-hospital mortality.
Missing data management
Data completeness was assessed for all variables included in the analysis. There were no missing data for the primary outcome (in-hospital mortality), and secondary outcomes were complete. For baseline clinical characteristics and descriptive analyses, all available data were used, and the number of observations may therefore vary across variables.
For multivariable logistic regression analysis, a complete-case approach was applied. Only patients with complete data for all covariates were included, and cases with missing values in any of the variables entered into the model were excluded. No imputation methods were performed.
Statistical analysis
Descriptive statistics were summarized using frequencies and percentages for categorical variables, and medians with interquartile ranges (IQR) for continuous variables due to non-normal data distribution. Comparisons between survivors and non-survivors were performed using the Chi-squared test or Fisher’s exact test for categorical variables, and the Wilcoxon rank-sum test for continuous variables.
Variables with clinical relevance and those with p < 0.05 in univariable analysis were considered for inclusion in the multivariable logistic regression model. Multivariable logistic regression was performed using complete-case analysis. Adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were reported. Multicollinearity was assessed using variance inflation factors (VIF), with generalized VIF adjusted for degrees of freedom. A two-tailed p-value < 0.05 was considered statistically significant. All analyses were performed using R software (version 4.4.2).
Results
Study population
During the study period, 100,420 patients visited the ED, of whom 944 were diagnosed with AHF. After excluding 40 patients transferred from other hospitals and 2 pregnant patients, a total of 902 patients were included in the final analysis (Fig. 1). Data for the primary and secondary outcomes were complete for all included patients. However, some laboratory measurements, particularly hs-cTnT, were not available for all cases, as shown in Tables 1 and 2.
Fig. 1.
Study flow
Table 1.
Baseline characteristics of patients with acute heart failure presenting to the emergency department
| Variable | Overall, N = 902 |
Survivors, n = 848 |
Non-survivors, n = 54 |
p-value |
|---|---|---|---|---|
| Age, years | 71 (60–80) | 70 (60–80) | 74 (63–85) | 0.030 |
| Male | 469 (52.0%) | 436 (51.4%) | 33 (61.1%) | 0.167 |
| Comorbidities | ||||
| Hypertension | 435 (48.2%) | 404 (47.6%) | 31 (57.4%) | 0.164 |
| Congestive heart failure | 387 (42.9%) | 351 (41.4%) | 36 (66.7%) | < 0.001 |
| Diabetes | 291 (32.3%) | 274 (32.3%) | 17 (31.5%) | 0.899 |
| Chronic kidney disease | 253 (28.0%) | 228 (26.9%) | 25 (46.3%) | 0.002 |
| Dyslipidemia | 247 (27.4%) | 237 (28.0%) | 10 (18.5%) | 0.132 |
| Coronary artery disease | 132 (14.6%) | 124 (14.6%) | 8 (14.8%) | 0.969 |
| Cerebrovascular accident | 90 (10.0%) | 79 (9.3%) | 11 (20.4%) | 0.009 |
| Initial vital signs | ||||
| Temperature, °C | 36.7 (36.4–36.9) | 36.7 (36.4–36.9) | 36.7 (36.2–37.3) | 0.787 |
| Heart rate, /min | 91 (79–100) | 91 (78–100) | 92 (82–99) | 0.714 |
| Respiratory rate, /min | 28 (22–32) | 28 (22–32) | 28 (22–36) | 0.294 |
| DBP, mmHg | 78 (66–92) | 78 (66–93) | 72 (63–84) | 0.010 |
| SBP, mmHg | 139 (121–160) | 140 (121–160) | 135 (114–154) | 0.084 |
| Pulse pressure | 60 (44–79) | 60 (44–80) | 60 (44–74) | 0.600 |
| Oxygen saturation, % | 96 (92–99) | 97 (92–99) | 95 (80–98) | 0.003 |
| ESI triage level | 0.003 | |||
| Level 1 | 152 (16.9%) | 132 (15.6%) | 20 (37.0%) | |
| Level 2 | 622 (69.0%) | 595 (70.2%) | 27 (50.0%) | |
| Level 3 | 109 (12.1%) | 102 (12.0%) | 7 (13.0%) | |
| Level 4 | 18 (2.0%) | 18 (2.1%) | 0 (0.0%) | |
| Level 5 | 1 (0.1%) | 1 (0.1%) | 0 (0.0%) |
Data are presented as n (%) or median (IQR)
The number of observations may vary across variables due to missing data. Analyses were performed using available data
Abbreviations: DBP, diastolic blood pressure; SBP, systolic blood pressure; ESI, Emergency Severity Index
Table 2.
Precipitating factors and laboratory findings in patients with acute heart failure
| Variable | Overall (N = 902) |
Survivors (n = 848) |
Non-survivors (n = 54) |
p-value |
|---|---|---|---|---|
| Met SIRS criteria | 484 (53.7%) | 454 (53.5%) | 30 (55.6%) | 0.773 |
| Temperature > 38.0 °C | 53 (5.9%) | 49 (5.8%) | 4 (7.4%) | 0.542 |
| Temperature < 36.0 °C | 25 (2.8%) | 23 (2.7%) | 2 (3.7%) | 0.652 |
| Heart rate > 90 beats/min | 450 (49.9%) | 424 (50.0%) | 26 (48.1%) | 0.898 |
| Respiratory rate > 20 breaths/min | 740 (82.0%) | 698 (82.3%) | 42 (77.8%) | 0.735 |
| WBC > 12,000/µL | 144 (16.0%) | 130 (15.3%) | 14 (25.9%) | 0.044 |
| WBC < 4,000/µL | 35 (3.9%) | 33 (3.9%) | 2 (3.7%) | > 0.999 |
| Anemia* | 631 (69.9%) | 589 (69.5%) | 42 (77.8%) | 0.168 |
| DBP > 120 mmHg | 25 (2.8%) | 25 (2.9%) | 0 (0.0%) | 0.392 |
| SBP > 180 mmHg | 116 (12.9%) | 111 (13.1%) | 5 (9.3%) | 0.516 |
| Hypertensive emergency | 122 (13.5%) | 117 (13.8%) | 5 (9.3%) | 0.436 |
| SBP < 90 mmHg | 13 (1.4%) | 9 (1.1%) | 4 (7.4%) | 0.004 |
| BUN (mg/dL) | 24 (16–41) | 23 (16–41) | 26 (17–47) | 0.350 |
| Creatinine (mg/dL) | 1.41 (1.00–2.25) | 1.40 (0.99–2.27) | 1.44 (1.14–1.81) | 0.925 |
| Creatinine > 2 mg/dL | 261 (28.9%) | 249 (29.4%) | 12 (22.2%) | 0.241 |
| eGFR (mL/min/1.73 m²) | 45 (25–69) | 46 (24–69) | 40 (29–58) | 0.840 |
| Sodium (mmol/L) | 136 (132–139) | 136 (132–139) | 135 (130–138) | 0.123 |
| Sodium < 130 mmol/L | 123 (13.6%) | 112 (13.2%) | 11 (20.4%) | 0.148 |
| Potassium (mmol/L) | 4.20 (3.80–4.60) | 4.20 (3.80–4.60) | 4.20 (3.70–4.70) | 0.976 |
| Bicarbonate (mmol/L) | 21.6 (19.0–24.2) | 21.6 (19.0–24.2) | 21.6 (18.5–24.1) | 0.705 |
| Initial hs‑cTnT (ng/L) | 58 (29–131) | 57 (29–125) | 63 (39–288) | 0.126 |
Available cases for hs‑cTnT: Overall n = 619, survivors n = 582, non‑survivors n = 37
Data are presented as n (%) or median (IQR)
The number of observations may vary across variables due to missing data. Analyses were performed using available data
Abbreviations: BUN, blood urea nitrogen; DBP, diastolic blood pressure; eGFR, estimated glomerular filtration rate; hs-cTnT, high-sensitivity cardiac troponin T; SBP, systolic blood pressure; SIRS, Systemic Inflammatory Response Syndrome; WBC, white blood cell count
*Anemia defined as hemoglobin < 12 g/dL in females and < 13 g/dL in males
Clinical characteristics
The median age of the study population was 71 years (IQR: 60–80), and 52.0% were male. Compared to survivors, non-survivors were significantly older (74 vs. 70 years, p = 0.030) and more likely to have a history of congestive heart failure (66.7% vs. 41.4%, p < 0.001), chronic kidney disease (46.3% vs. 26.9%, p = 0.002), and cerebrovascular accident (20.4% vs. 9.3%, p = 0.009). Non-survivors also presented with lower diastolic blood pressure (72 vs. 78 mmHg, p = 0.010) and lower oxygen saturation (95% vs. 97%, p = 0.003).
A significantly higher proportion of non-survivors were triaged as Emergency Severity Index (ESI) level 1 (37.0% vs. 15.6%, p = 0.003), reflecting greater initial illness severity. There were no significant differences in heart rate, respiratory rate, or systolic blood pressure between groups (Table 1).
Precipitating factors and laboratory findings
SIRS criteria were met in 54% of patients, with no difference between survivors and non-survivors (p = 0.773). A white blood cell count > 12,000/µL was more common among non-survivors (26% vs. 16%, p = 0.044), and hypotension (SBP < 90 mmHg) was significantly more frequent in non-survivors (7.4% vs. 1.1%, p = 0.004). There were no significant differences between groups in anemia, hypertensive emergency, or laboratory parameters, including sodium, potassium, bicarbonate, and creatinine levels (Table 2).
Treatment and clinical outcomes
Treatment and clinical outcomes are summarized in Table 3. The overall in-hospital mortality rate was 6.0% (54/902). Overall, 85.4% of patients were admitted to the hospital, and 28% required ICU admission. Compared with survivors, non-survivors were more likely to require ICU admission (51.9% vs. 26.4%, p < 0.001), receive inotropic support (61.1% vs. 15.9%, p < 0.001), and require ventilatory support (including HFNC, NIPPV, or mechanical ventilation) (35.2% vs. 22.9%, p = 0.041).
Table 3.
Emergency department disposition and treatments
| Variable | Overall (N = 902) |
Survivors (n = 848) |
Non-survivors (n = 54) |
p-value |
|---|---|---|---|---|
| ED Disposition | 0.019 | |||
| Admit | 770 (85.4%) | 718 (84.7%) | 52 (96.3%) | |
| Discharge | 132 (14.6%) | 130 (15.3%) | 2 (3.7%) | |
| ICU admission | 252 (27.9%) | 224 (26.4%) | 28 (51.9%) | < 0.001 |
| ICU transfer* | 53 (5.9%) | 44 (5.2%) | 9 (16.7%) | 0.003 |
| Inotropic support | 168 (18.6%) | 135 (15.9%) | 33 (61.1%) | < 0.001 |
| Norepinephrine | 138 (15.3%) | 106 (12.5%) | 32 (59.3%) | < 0.001 |
| Epinephrine | 65 (7.2%) | 45 (5.3%) | 20 (37.0%) | < 0.001 |
| Dopamine | 16 (1.8%) | 14 (1.7%) | 2 (3.7%) | 0.248 |
| Use of ≥ 2 inotropes | 45 (5.0%) | 26 (3.1%) | 19 (35.2%) | < 0.001 |
| Low-flow oxygen therapy | 255 (28.3%) | 243 (28.7%) | 12 (22.2%) | 0.299 |
| HFNC or NIPPV or mechanical ventilation | 213 (23.6%) | 194 (22.9%) | 19 (35.2%) | 0.041 |
Values are presented as n (%)
Abbreviations: HFNC, high-flow nasal cannula; ICU, intensive care unit; NIPPV, noninvasive positive pressure ventilation
Note:
*ICU transfer indicates patients initially admitted to a general ward who subsequently required transfer to the intensive care unit during hospitalization
Among inotropic agents, norepinephrine was the most commonly administered, used in 15.3% of patients overall and significantly more frequently in non-survivors than in survivors (59.3% vs. 12.5%, p < 0.001). Epinephrine was administered in 7.2% of patients and was also more frequently used in non-survivors (37.0% vs. 5.3%, p < 0.001). In contrast, dopamine was used infrequently (1.8% overall), with no significant difference between groups (3.7% vs. 1.7%, p = 0.248). The use of multiple inotropic agents was significantly more common among non-survivors than survivors (35.2% vs. 3.1%, p < 0.001).
Factors associated with hospital mortality
A total of 862 patients were included in both the univariable and multivariable analyses after excluding cases with missing data. In univariable analysis, multiple variables were associated with increased odds of hospital death, including ESI level 1 triage, older age, lower oxygen saturation, lower diastolic blood pressure, ICU transfer, inotrope use, history of cerebrovascular accident, and SBP < 90 mmHg. No significant multicollinearity was observed among variables included in the multivariable model (all adjusted VIF values < 2.5). Multivariable logistic regression identified the need for inotropic support as the only variable independently associated with in-hospital mortality (adjusted OR 3.97; 95% CI 1.91–8.40); p < 0.001). Other factors such as age, ESI level, and ICU transfer were not statistically significant after adjustment (Table 4).
Table 4.
Factors associated with in-hospital mortality (n = 862)
| Variable | OR (95% CI) | p-value | aOR (95% CI) | p-value |
|---|---|---|---|---|
| ESI triage level | ||||
| Level 1 | Reference | - | Reference | - |
| Level 2 | 0.30 (0.16, 0.56) | < 0.001 | 0.64 (0.28, 1.53) | 0.305 |
| Level 3 | 0.45 (0.17, 1.07) | 0.084 | 0.98 (0.30, 3.03) | 0.966 |
| Oxygen saturation, % | 0.96 (0.94, 0.98) | < 0.001 | 0.98 (0.95, 1.01) | 0.116 |
| DBP, mmHg | 0.97 (0.96, 0.99) | 0.003 | 0.99 (0.97, 1.00) | 0.114 |
| Age, years | 1.02 (1.00, 1.04) | 0.055 | 1.02 (1.00, 1.05) | 0.074 |
|
HFNC or NIPPV or mechanical ventilation |
1.82 (1.00, 3.22) | 0.044 | 0.64 (0.30, 1.33) | 0.251 |
| WBC > 12,000/µL | 1.90 (0.98, 3.52) | 0.048 | 1.06 (0.46, 2.28) | 0.877 |
| Chronic kidney disease | 2.34 (1.34, 4.09) | 0.003 | 1.61 (0.83, 3.12) | 0.156 |
| Cerebrovascular accident | 2.49 (1.18, 4.86) | 0.011 | 1.13 (0.46, 2.52) | 0.778 |
| Congestive heart failure | 2.83 (1.60, 5.17) | < 0.001 | 1.21 (0.60, 2.43) | 0.596 |
| ICU admission | 3.00 (1.72, 5.25) | < 0.001 | 1.70 (0.78, 3.70) | 0.182 |
| ICU transfer* | 3.65 (1.59, 7.65) | < 0.001 | 2.65 (0.90, 7.36) | 0.067 |
| SBP < 90 mmHg | 8.05 (2.12, 25.7) | < 0.001 | 1.39 (0.28, 6.25) | 0.671 |
| Inotropic support | 8.30 (4.69, 15.0) | < 0.001 | 3.97 (1.91, 8.40) | < 0.001 |
Abbreviations: aOR, adjusted odds ratio; CI, confidence interval; DBP, diastolic blood pressure; ESI, Emergency Severity Index; HFNC, high-flow nasal cannula; ICU, intensive care unit; NIPPV, noninvasive positive pressure ventilation; OR, odds ratio; SBP, systolic blood pressure; WBC, white blood cell count
Note:
*ICU transfer indicates patients initially admitted to a general ward who subsequently required transfer to the intensive care unit during hospitalization
Discussion
Our study provides a focused analysis of patients with AHF in the ED and highlights key prognostic factors in this setting. The in-hospital mortality rate in our cohort was 6.0%, consistent with contemporary global and regional data reporting mortality rates of approximately 4% to 7% [13–16]. Prior studies from Thailand have demonstrated similar outcomes, reflecting comparable patient characteristics and patterns of care [17, 18].
In univariable analysis, several baseline clinical characteristics were associated with in-hospital mortality, including comorbidities such as congestive heart failure, chronic kidney disease, and cerebrovascular disease, as well as markers of acute physiological derangement, including lower diastolic blood pressure and reduced oxygen saturation. Patients with higher triage acuity were also more likely to die, with a substantially greater proportion of non-survivors classified as ESI level 1 at ED presentation. These findings are consistent with prior reports indicating that greater clinical severity at presentation is associated with higher in-hospital mortality [19, 20].
However, in multivariable analysis, the need for inotropic support was the only variable independently associated with in-hospital mortality. This finding should be interpreted with caution, as inotropic support likely represents a marker of severe hemodynamic compromise rather than an early predictive factor.
The association between inotrope use and adverse outcomes has been consistently reported in prior studies. In a recent analysis of patients with acute heart failure, those treated with inotropes had significantly higher rates of in-hospital events (13.3% vs. 1.4%) and 30-day mortality (5.5% vs. 2.5%) than those who did not receive these agents [21]. Similarly, in cohorts with cardiogenic shock, inotropic therapy has been associated with nearly a twofold increase in mortality risk [22]. These findings likely reflect confounding and overlap among variables representing disease severity, where multiple baseline factors are correlated and may not remain significant after adjustment. Future research using alternative modeling approaches, including sensitivity analyses that exclude treatment-related variables, is needed to better identify early predictors of mortality based on data available at ED presentation.
Hypotension at presentation (SBP < 90 mmHg) demonstrated a strong unadjusted association with mortality, consistent with prior studies [23–25]. However, it did not remain significant after adjustment. This likely reflects overlap with downstream treatment variables, particularly inotropic support, which may better capture the severity and progression of hemodynamic compromise over time. From a clinical perspective, these findings highlight an important distinction between early risk stratification and prognostic markers during ED management. While inotropic support is strongly associated with mortality, it is not useful as an early screening variable. Instead, baseline clinical features—such as hypotension, hypoxia, and high-acuity triage level—remain critical for identifying high-risk patients at ED presentation and guiding early management decisions.
Our findings have important implications for emergency care practice. ED physicians should maintain a high index of suspicion for cardiogenic shock, particularly in patients presenting with signs of hypoperfusion. Prompt recognition may facilitate timely escalation of care, including consideration of advanced therapies such as vasopressors, inotropes, and ventilatory support. However, the impact of these interventions on outcomes was not directly assessed in this study.
Inotropic therapy should be used judiciously. Inotropes function as a double-edged intervention—providing short-term hemodynamic support while being associated with increased risks of myocardial stress, arrhythmias, and mortality [21]. Therefore, their use should be guided by careful clinical assessment and reserved for patients with clear evidence of circulatory compromise.
Another implication is the potential role of risk stratification tools in the ED. Advanced risk scores, such as the Emergency Heart Failure Mortality Risk Grade (EHMRG) and the MEESSI score, incorporate multiple variables to predict short-term outcomes and may assist clinicians in triaging patients to the appropriate level of care. Patients identified as high risk may benefit from early ICU admission or closer monitoring, whereas low-risk patients may be suitable for observation or early discharge with appropriate follow-up [26–28].
Strengths and limitations
This study has several notable strengths. First, it is one of the few investigations that provide a comprehensive analysis of AHF patients in the ED setting in Thailand, contributing valuable real-world data to the limited literature from Southeast Asia. The relatively large sample size, along with detailed data from electronic health records, allows for robust statistical analysis and evaluation of multiple factors associated with in-hospital mortality.
However, some limitations must be acknowledged. As a retrospective study, the analysis depended on the accuracy and completeness of electronic medical records, which may have introduced missing or misclassified variables. Nevertheless, the proportion of missing data was low (4.4%), and is unlikely to have materially influenced the results.
Additionally, we could not assess the severity of left ventricular dysfunction, as echocardiographic data were not uniformly available at the time of ED presentation. The study was also conducted at a single tertiary referral center, which may limit the generalizability of findings to other settings, particularly primary or rural hospitals. Furthermore, the observed association between inotrope use and mortality may partly reflect treatment-by-indication bias, as sicker patients were more likely to receive inotropes. Lastly, long-term outcomes beyond hospital discharge were not assessed, and further studies with follow-up are needed to determine whether early management in the ED impacts post-discharge morbidity and mortality.
Conclusion
In this ED-based cohort, in-hospital mortality among patients with acute heart failure was comparable to international reports. The need for inotropic support was strongly associated with mortality and likely reflects severe hemodynamic compromise rather than serving as an early predictive factor. Baseline clinical variables remain essential for early risk stratification at ED presentation, and future studies should focus on prediction models using variables available at triage to improve clinical decision-making.
Acknowledgements
We extend our gratitude to the physicians and nurses at the Accident and Emergency Department of Srinagarind Hospital for their support throughout the study. Although we do not have a formal list of collaborators or a designated study group, the contributions and efforts of all those involved are deeply appreciated.
Abbreviations
- AHF
Acute heart failure
- aOR
adjusted odds ratio
- BUN
Blood urea nitrogen
- CI
Confidence interval
- DBP
Diastolic blood pressure
- ED
Emergency department
- eGFR
estimated glomerular filtration rate
- ESI
Emergency severity index
- HFNC
High-flow nasal cannula
- hs-cTnT
high-sensitivity cardiac Troponin T
- ICU
Intensive care unit
- IQR
Interquartile range
- NIPPV
Non-invasive positive pressure ventilation
- OR
Odds ratio
- SBP
Systolic blood pressure
- SIRS
Systemic inflammatory response syndrome
- WBC
White blood cell count
Author contributions
TT contributed to conceptualization, data curation, formal analysis, funding acquisition, investigation, validation, and writing – original draft and review & editing. PK contributed to conceptualization, data curation, formal analysis, investigation, supervision, and writing – original draft and review & editing. WS contributed to conceptualization, data curation, and writing – original draft and review & editing. TM, MB, and NS contributed to writing – original draft and review & editing. PP contributed to conceptualization, data curation, formal analysis, investigation, supervision, writing – original draft and review & editing, and served as the corresponding author. All authors read and approved the final manuscript.
Funding
None.
Data availability
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethical approval and consent to participate
The study was approved by the Human Research Ethics Committee of Khon Kaen University (HE661567). The need for informed consent was waived due to the retrospective nature of the study.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.