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INTRODUCTION
Acute respiratory failure (ARF) is a severe condition characterized by the inability to maintain normal oxygen delivery to tissues or carbon dioxide removal from tissues [1]. ARF is traditionally defined by an arterial oxygen partial pressure (PaO2) of <60 mm Hg (type 1), an arterial carbon dioxide partial pressure (PaCO2) of >45 mm Hg with a pH of <7.35 (type 2), or a combination of both. ARF is associated with increased healthcare resource utilization, high in-hospital mortality rates, and significant ethical considerations regarding end-of-life decisions. It is also a common reason for admission and transfer to the intensive care unit (ICU) [2,3]. In the United States, 3,213,030 patients were discharged due to ARF in 2017, with an incidence rate of 1,275 cases per 100,000 person-years [4].
ARF treatment is divided into the management of the underlying cause and the provision of supportive oxygen therapy [5]. Supportive oxygen therapy for ARF follows a phased escalation strategy based on various ventilatory and non-ventilatory interventions. The primary goals of treatment are to stabilize the patient while addressing the underlying causes of respiratory failure and preventing or mitigating potential lung damage from interventions such as mechanical ventilation and to reverse the causes of acute respiratory injury [6]. Respiratory support options include conventional oxygen therapy, high-flow nasal cannula (HFNC), non-invasive ventilation (NIV), invasive mechanical ventilation (IMV), and extracorporeal membrane oxygenation (ECMO) [7-13]. However, clinical data on the use of these devices and their associated trends are lacking. Furthermore, large-scale research investigating the frequency and characteristics of type 1, type 2, and combined-type ARF in Korea is limited [1]. This multicenter study aimed to investigate the frequency, causes, and current management practices of ARF.
MATERIALS AND METHODS
Ethics
This study was approved by the Institutional Review Board of Gangnam Severance Hospital (No. 2023-0928-003). As this was a retrospective study that utilized de-identified data, the requirement for informed consent was waived.
Study Design and Data Source
From January 2018 to December 2022, all patients admitted to three hospitals in South Korea (Severance Hospital: 2,499 beds, Gangnam Severance Hospital: 766 beds, and Yongin Severance Hospital: 658 beds) were screened through a retrospective review of electronic medical records (EMRs) using the Severance Clinical Research Analysis Portal (SCRAP) at three hospitals. Patients aged 18 years who were diagnosed with type 1 ARF (PaO₂ <60 mm Hg), type 2 ARF (PaCO₂ >45 mm Hg with a pH of <7.35, or combined-type ARF; whose type 2 ARF developed during the progression of type 1 ARF or vice versa; or whose type 1 ARF developed during the progression of type 2 ARF were included in the study [10]. Conversely, patients who were previously diagnosed with chronic respiratory disease (International Classification of Diseases, Tenth Revision [ICD-10] code J96.1 or J96.9) prior to admission and long-term ventilator support, NIV, or oxygen therapy from previous admissions were excluded (Figure 1).
Data Collection and Outcomes
ICD-10 codes, sex, age, and laboratory results (hemoglobin, white blood cell, platelet, total protein, albumin, aspartate transaminase, alanine transaminase, total bilirubin, sodium, potassium, chloride, and arterial blood gas levels) of patients were extracted from the EMR database. Comorbidities were assessed using the Charlson Comorbidity Index (CCI) [14].
Seventeen disease groups were identified as common causes of ARF [15]. The ICD-10 codes for each condition are as follows: J43.0x-J44.x, excluding J43.0, for chronic obstructive pulmonary disease; J45-J46 for asthma; G10-G14, G20-G41, G70-G83, and G90-G99 for neuromuscular disease; I60-I64 and I69 for stroke; C32-C33, C42-C43, and C70-C72 for neurologic tumor; M40-M54 for musculoskeletal disease; S00-S99 and T00-T99 for trauma; I20-I25 for ischemic heart disease; and I09.9, I11.0, I13.0, I13.2, I25.5, I42.0, I42.5-I42.9, P29.0, I40, and I50 for heart failure. Lung lesions such as pneumonia, pulmonary edema, atelectasis, pneumothorax, pulmonary embolism, and pleural effusion were defined based on the radiologists’ interpretation of the results of all radiologic evaluations performed during the hospital stay. Sepsis was defined based on the Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3) criteria and using the algorithm described by Shashikumar et al. [16,17], which involves a ≥2-point change in the Sequential Organ Failure Assessment (SOFA) score occurring 48 hours before or 24 hours following the onset of infection [18]. The time of infection was defined as the administration of antibiotics between 24 hours before and 72 hours after blood culture acquisition [18]. Acute respiratory distress syndrome (ARDS) was defined according to the Berlin definition [19]. The Berlin definition includes the following criteria: onset within 1 week of a known clinical insult or worsening respiratory symptoms; bilateral opacities on chest imaging not explained by other conditions; respiratory failure not fully attributed to cardiac failure or fluid overload, requiring objective assessment if no risk factors are present; and impaired oxygenation, defined as a PaO₂/FiO₂ ratio of ≤300 mm Hg with a positive end-expiratory pressure or continuous positive airway pressure of ≥5 cm H₂O.
Statistical Analysis
Categorical variables were expressed as frequencies (percentages). Continuous variables were expressed as the mean±standard deviation for normally distributed variables and as the median (interquartile range) for non-normally distributed variables. The normality of continuous variables was confirmed using the Shapiro-Wilk test. Outcomes associated with hospital admissions were assessed at the level of individual admissions, while adjusting for the clustering of multiple admissions within the same patient. P-values for non-normally distributed continuous variables were calculated using a clustered Kruskal-Wallis test with bootstrap sampling. For normally distributed continuous variables and categorical outcomes, Generalized Estimating Equations were used to adjust for within-patient correlation due to repeated admissions. The trend curve was generated using linear regression analysis, and the P for trend was calculated using the proportion trend test. All analyses were performed using R software version 4.4.0 (R Foundation). A P-value of <0.05 was considered significant.
RESULTS
Characteristics of Patients with ARF
Among 768,700 hospitalized patients aged >18 years, 33,278 (4.3%) were diagnosed with ARF (Figure 1). Based on the arterial blood gas analysis results, 13,659 patients (41.0%) had type 1 ARF, 10,459 patients (31.4%) had type 2 ARF, and 9,160 patients (27.5%) had combined-type ARF. The median age of patients with ARF was 68 years (interquartile range, 58–77). Type 1 ARF was significantly more prevalent in older patients compared with type 2 ARF (70 years [59–78] vs. 66 years [57–75], P<0.001) (Table 1). Males (60.0%) were more prevalent than females, accounting for 60.0 % of cases. This trend was consistent across all ARF types (Table 1), with a particularly higher proportion of males observed in type 2 ARF compared to type 1 and combined ARF (61.6%, 58.7%, and 60.1%, respectively; P<0.001). The median body mass index of ARF patients was 23.2 kg/m2 (20.5–25.8). Patients with type 2 ARF had a significantly higher BMI compared to those with type 1 and combined ARF (23.6 kg/m2 [21.1–26.2], 22.8 kg/m2 [20.2–25.4], and 23.1 kg/m2 [20.2–26.0], respectively; P<0.001).
In terms of comorbidities assessed using the CCI, patients with type 1 ARF had significantly higher scores compared to those with type 2 and combined ARF (4.0 [2.0–8.0], 3.0 [1.0–5.0], and 4.0 [2.0–8.0], respectively; P<0.001). The most common comorbidities were malignancy, diabetes mellitus (with or without complications), and chronic pulmonary disease, accounting for 46.3%, 31.9%, and 26.6%, respectively. Most comorbidities were more prevalent in patients with type 1 ARF compared to type 2 ARF (Table 1). However, peripheral vascular disease was significantly more common in type 2 ARF patients than in type 1 ARF patients (15.9% vs. 14.0%, P <0.001) (Table 1).
The combined ARF group was further subdivided based on whether the initial presentation was as type 1 ARF, type 2 ARF, or simultaneous onset of both types. The results of this subgroup analysis are presented in Supplementary Tables 1-5.
Causes of ARF
The causes of ARF are presented in Table 2. Of all cases, 20,848 (62.6%) were complicated by more than one underlying cause (Figure 2A). Combined type was caused by more complex factors compared to type 1 or type 2, with a higher number of associated causes (3.0 [1.0–4.0], 2.0 [1.0–4.0], and 1.0 [1.0–3.0], respectively) (Table 2). The predominant causes of all ARF were sepsis (15,757 cases, 47.3%), pleural effusion (8,501 cases, 25.5%), pneumonia (8,298 cases, 24.9%), atelectasis (7,205 cases, 21.7%), and ischemic heart disease (6,911 cases, 20.8%) (Table 2). Similarly, in type 1 ARF, the leading causes were sepsis (7,197 cases, 52.7%), pleural effusion (4,143 cases, 30.3%), pneumonia (4,075 cases, 29.8%), atelectasis (3,372 cases, 24.7%), and ischemic heart disease (2,769 cases, 20.3%) (Table 2). For type 2 ARF, the most frequent causes were sepsis (3,066 cases, 29.3%), ischemic heart disease (2,063 cases, 19.7%), pleural effusion (1,611 cases, 15.4%), trauma (1,567 cases, 15.0%), and atelectasis (1,516 cases, 14.5%). In the combined type, sepsis (5,494 cases, 60.0%), pneumonia (2,974 cases, 32.5%), pleural effusion (2,747 cases, 30.0%), atelectasis (2,317 cases, 25.3%), and ischemic heart disease (2,079 cases, 22.7%) (Table 2).
Biomarker Values of Patients with ARF
Table 3 presents the differences in biomarker values according to the ARF type. The platelet (type 1 ARF vs. type 2 ARF; 181.0 ×10³/μl [107.0–258.5] vs. 173.0 ×10³/μl [111.0–233.0], P<0.001), creatinine (0.9 [0.6–1.4] mg/dl vs. 0.8 [0.6–1.1] mg/dl, P<0.001), and protein (5.9 g/dl [5.2–6.6] vs. 5.6 g/dl [4.9–6.3], P<0.001) levels were higher in type 1 ARF compared with type 2 ARF. By contrast, the hemoglobin (10.4 g/dl [8.8–12.2] vs. 11.3 g/dl [9.6–12.9], P<0.001), white blood cell (9.7 ×10³/μl [6.6–13.8] vs. 11.2 ×10³/μl [8.0–15.0], P<0.001), sodium (137.0 mmol/L [134.0–140.0] vs. 139.0 mmol/L [136.0–141.0], P<0.001), potassium (4.1 mmol/L [3.6–4.5] vs. 4.2 mmol/L [3.8–4.6], P<0.001), and albumin (3.2 g/dl [2.8–3.7] vs. 3.3 g/dl [2.8–3.7], P<0.001) levels were significantly higher in type 2 ARF compared with type 1. The C-reactive protein levels were significantly elevated in type 1 ARF (69.2 mg/L [19.2–145.8] vs. 16.3 mg/L [2.5–66.4], P<0.001), whereas the chloride (105.0 mmol/L [102.0–108.0] vs. 102.0 mmol/L [98.0–106.0], P<0.001) and creatine kinase (143.0 U/L [75.0–312.0] vs. 88.0 U/L [47.0–203.0], P<0.001) levels were significantly higher in type 2 ARF. These findings suggest distinct differences in inflammatory responses and metabolic profiles between the two ARF types.
Proportion of ICU Transfer, In-Hospital Mortality, and Multiorgan Failure in Patients with ARF
Over 5 years, 55,833 patients required ICU admission, of whom 15,671 (28.1%) were admitted due to ARF. Among all patients with ARF, 15,671 (47.1%) were transferred to the ICU (Table 4). ICU transfer rates were highest in patients with the combined type (71.2%), followed by type 2 (53.2%) and type 1 (26.3%) (Table 4). The in-hospital mortality rate was highest in patients with the combined type (48.2%), followed by type 1 (20.9%) and type 2 (16.4%).
The baseline total SOFA score showed a significant difference among the ARF types (Table 4). Patients with the combined type had the highest baseline SOFA score (9.0 [5.0–13.0]), followed by type 2 (6.0 [3.0–10.0]) and type 1 (5.0 [3.0–8.0]). In all six SOFA categories, patients with the combined type (type C) exhibited a higher proportion of severe cases (indicated by higher scores) compared with those with type 1 or type 2 ARF. However, type 1 and type 2 ARF showed distinct and characteristic distributions within the individual categories. In the respiratory system, a significantly higher proportion of patients with type 2 ARF initially required ventilator support (≥3 points) compared with those with type 1 ARF (≥3 points in respiratory system: type 1 vs. type 2, 1,055 patients [7.8%] vs. 2,432 patients [23.3%]; P<0.001). In the central nervous system, a significantly higher proportion of patients with type 2 ARF obtained a Glasgow Coma Scale score of ≤12 (≥2 points in the central nervous system) compared with those with type 1 ARF (3,597 [26.3%] vs. 5,309 [50.7%], P<0.001). In the cardiovascular system, patients with type 2 ARF more frequently used vasopressors at baseline (score ≥3 points) than those with type 1 ARF (3,022 [22.1%] vs. 3,838 [36.7%], P<0.001). By contrast, liver and renal injuries were more prevalent in patients with type 1 ARF than in those with type 2 ARF. For liver injury, a higher proportion of patients with type 1 ARF obtained a liver SOFA score of ≥1 (4,063 patients, 29.7%) compared with those with type 2 ARF (2,830, 27.1%) (P<0.001). Similarly, renal injury (SOFA score ≥1) was more prevalent in type 1 ARF (5,648, 41.4%) than in those with type 2 ARF (3,363, 32.2%) (P<0.001).
Respiratory Support in ARF
Table 5 summarizes the respiratory support provided during the course of ARF. Conventional oxygen therapy was the most commonly used form of supportive care, administered to 31,356 ARF patients (94.2%), regardless of ARF type. A HFNC was used in 8,089 patients with ARF (24.3%), with the highest usage observed in those with the combined-type ARF (3,921 patients, 42.8%). HFNC was more frequently used in type 1 ARF than in type 2 ARF (2,853 patients [20.9%] vs. 1,315 patients [12.6%], P<0.001). NIV was more frequently used in 625 patients with ARF (1.9%), with the highest usage observed in those with the combined-type ARF (435 patients [4.7%]). NIV was more frequently used in patients with type 2 ARF than in those with type 1 ARF (142 patients [1.4%] vs. 48 patients [0.4%], P<0.001).
IMV was used in 11,810 patients with ARF (35.5%), with the highest usage observed in those with the combined-type ARF (5,905 patients, 64.5%). IMV was significantly more frequently used in patients with type 2 ARF than in those with type 1 ARF (4,220 patients [40.3%] vs. 1,685 patients [12.3%], P<0.001). ECMO was more commonly used in 673 patients with ARF (2.0%), with the highest usage observed in those with the combined-type ARF (480 [5.2%]). ECMO was also more frequently used in type 2 ARF than those with type 1 ARF (70 [0.5%] vs.123 [1.2%], P<0.001).
Annual Trend of Prevalence and Mortality in Patients with ARF
Figure 2 and Supplementary Table 6 present the annual trends in ARF prevalence. The annual prevalence of total ARF among all hospitalized patients over the past 5 years ranged from 3.9% to 4.6% (P for trend [Ptrend]<0.001) (Supplementary Table 6), with a marked increase to over 4.4% during the coronavirus disease 2019 (COVID-19) pandemic period (2020–2022) (Figure 2A). The prevalence of ARF among annual hospitalized patients showed an average increase of 0.175% per year. A consistent annual rise was observed in the proportion of patients aged ≥80 years across all ARF categories, with a statistically significant trend (total ARF-coefficient 0.085, Ptrend<0.001; type 1 ARF-coefficient 0.032, Ptrend<0.001; type 2 ARF-coefficient 0.023, Ptrend<0.001; and combined ARF-coefficient 0.030, Ptrend<0.001) (Figure 2A). The prevalence of ARF among all ICU patients showed a similar annual trend (Figure 2B). In-hospital mortality also showed an annual increasing trend, rising from 25.5% in 2018 to 29.3% in 2022 (coefficient 1.017 and Ptrend<0.001) (Figure 3A, Supplementary Table 6). Even after excluding patients with do-not-resuscitate (DNR) status, the rate increased from 10.4% to 13.4% over the same period (coefficient 0.873, Ptrend<0.001) (Figure 3A). The annual increase in mortality rate was more pronounced in type 1 ARF, increasing from 17.3% to 23.0% (coefficient 1.401, Ptrend<0.001) (Figure 3A). However, after excluding patients with DNR status, the rate of increase was attenuated, from 1.55% to 3.30% (coefficient 0.456, Ptrend<0.001). The mortality trend differed by age group, showing a consistent decline in in-hospital mortality among young patients aged <40 years with ARF (coefficient –1.579, Ptrend=0.013) (Figure 3B). The trends in mortality according to the type of respiratory support are presented in Figure 3C and Supplementary Table 6, with most support types showing an increase in mortality over the 5-year period.
Annual Trend in the Causes of ARF and Respiratory Support Usage
The major causes of ARF, including sepsis (coefficient 0.796, Ptrend<0.001), pneumonia (coefficient 0.728, Ptrend<0.001), and heart failure (coefficient 1.961, Ptrend<0.001), showed an annual increasing trend (Figure 4A, Supplementary Table 6). By contrast, the proportion of respiratory failure caused by trauma has decreased. The primary causes of ARF vary by age group. An increasing trend in sepsis and pneumonia was observed among ARF patients aged ≥60 years. Specifically, in sepsis patients, the coefficient was 0.757 (Ptrend=0.004) among those aged 60–79 years and 1.502 (Ptrend=0.001) among those aged ≥80 years. In pneumonia patients, the corresponding coefficients were 0.612 (Ptrend=0.005) and 1.415 (Ptrend<0.001), respectively. No significant trend was identified in patients aged <60 years (Figure 4B, Supplementary Table 6). Similarly, heart failure exhibited a marked increase over the past 5 years with advancing age. The coefficients for heart failure were 0.742 (Ptrend= 0.111) in patients aged <40 years, 1.278 (Ptrend<0.001) in those aged 40–59 years, 1.960 (Ptrend<0.001) in those aged 60–79 years, and 2.467 (Ptrend<0.001) in those aged ≥80 years.
Figure 5 illustrates the annual changes in respiratory support for ARF. The HFNC usage steadily increased over the past 5 years across all types—type 1, type 2, and combined types (total ARF-coefficient 4.137, Ptrend<0.001; type 1 ARF-coefficient 4.441, Ptrend<0.001; type 2 ARF-coefficient 1.773, Ptrend<0.001; and combined ARF-coefficient 5.639, Ptrend<0.001) (Figure 5A, Supplementary Table 6). In contrast, the use of IMV showed a declining trend across all types (total ARF-coefficient –0.983, Ptrend<0.001; type 1 ARF-coefficient –0.391, Ptrend=0.046; type 2 ARF-coefficient –2.649, Ptrend<0.001; and combined ARF-coefficient –2.038, Ptrend<0.001) (Figure 5A, Supplementary Table 6). A similar trend was observed in both DNR and non-DNR patient groups (Figure 5B and 5C, respectively). In particular, in type 2 ARF, although the use of HFNC significantly increased (coefficient 1.773, Ptrend<0.001) (Figure 5B) and the use of IMV significantly decreased (coefficient –2.649, Ptrend<0.001) (Figure 5B), there was no significant change in mortality (coefficient –0.246, Ptrend=0.409) (Figure 3A).
DISCUSSION
This study presents the frequency, causes, and management practices of ARF within the multicenter cohort in South Korea over a 5-year period. ARF accounted for 4.3% of all hospital admissions and 28.1% of all ICU admissions. The etiology of ARF is complex, with most patients having multiple contributing factors rather than a single cause. The most common etiology was sepsis, which accounted for 47.3% of all ARF cases. Among ARF patients, the most common underlying condition was a tumor. In addition, the study highlighted several significant trends in ARF that warrant attention.
First, the proportion of elderly patients among ARF cases has been consistently increasing. As South Korea becomes an aging society, the growing elderly population has led to healthcare challenges. Among these, respiratory failure is one of the most significant issues. The aging of the ARF patient population may negatively impact ARF outcomes and is likely closely associated with the increase in patients with DNR. The poor outcomes of ARF in elderly patients are well-established [22-25]. Recently, there have been reports focusing on specific mechanisms of ARF in elderly patients. Brown et al. [23] identified key features of lung injury in the elderly, including diminished immune response, alterations in the structural components of the airway and vasculature, changes in lung function and respiratory mechanics (increased compliance and decreased small airway diameter). They reported that these factors may lead to an increased risk of mechanical injury. Therefore, as the number of elderly ARF patients increases, individualized severity assessments and treatment strategies tailored to age and patient condition become essential.
The second key point is that sepsis continues leading cause of ARF, with its proportion showing a consistent upward trend, particularly in elderly patients. Sepsis can directly or indirectly cause respiratory failure, a key criterion for evaluating multiorgan failure using the SOFA score, highlighting the interrelated nature of sepsis and respiratory failure [20]. Sepsis has been consistently reported to have a high prevalence, with an annual increase in incidence [26]. Until the early 2010s, many studies reported a steady decline in sepsis-related mortality [26-28]. However, since the latter half of the 2010s, some studies have reported a rebound in mortality rates [29,30]. This trend may be partly attributed to the adoption of the Sepsis-3 definition, which redefined sepsis, but it also suggests a potential increase in the severity of complications like respiratory failure in patients with sepsis. Prest et al. reported that the mortality rate of pulmonary sepsis increased in both sexes and all age groups [30]. In our study, sepsis and pneumonia were also found to be steadily increasing causes of ARF, especially among patients aged ≥60 years. These conditions are likely major contributors to the increased in-hospital mortality associated with ARF. Further research is warranted to address this issue.
Third, the proportion of cardiogenic has rapidly increased. In respiratory failure, heart failure can influence pulmonary congestion, oxygen delivery, and carbon dioxide transport, potentially leading to type 1 and type 2 ARF [31]. The rising prevalence of heart failure is closely linked to the aging population [32]. In this study, heart failure rapidly became one of the primary causes of ARF within just 5 years. This highlights the importance of early cardiac evaluation in the treatment of ARF, underscoring its significance in clinical practice.
Fourth, the annual increase in HFNC use for ARF supportive care was also significant. HFNC reduces intubation rates in patients with hypoxemic respiratory failure [33]. Recent studies have reported that HFNC may benefit patients with hypercapnic respiratory failure by facilitating the removal of carbon dioxide from the upper airway dead space [33]. Despite its potential, the clinical efficacy of HFNC compared with NIV remains controversial, and it is not yet recommended in clinical guidelines. Interestingly, the increasing use of HFNC in type 2 ARF observed in this study suggests that clinicians in real-world practice are progressively favoring HFNC over NIV for the management of hypercapnic respiratory failure. Moreover, the observed reduction in ICU transfer and mechanical ventilation rates in the past 5 years, without an increase in in-hospital mortality. However, the efficacy of HFNC in the management of type 2 respiratory failure has not been clearly established, and further studies are needed to address this issue.
In addition, laboratory data also highlighted clear distinctions between type 1 and type 2 ARF. Elevated C-reactive protein in type 1 ARF suggests an association with inflammatory response, typical of conditions like pneumonia or ARDS [34,35]. In contrast, type 2 ARF showed relatively stable inflammatory markers but subtle electrolyte imbalances, reflecting hypercapnic compensation [36]. These laboratory profiles likely reflect not only the intrinsic mechanisms of each ARF type, but also the impact of prevalent underlying conditions, such as COPD and asthma. Furthermore, the characteristics of the ARF discussed in this study varied by year, ARF type, and center. The COVID-19 pandemic is thought to have significantly affected the etiology and clinical outcomes of ARF during the study period. Therefore, long-term, large-scale, multicenter studies are essential to further understand the characteristics of ARF and improve its treatment.
This multicenter study, involving hospital care institutions from various regions, included data from more than 30,000 patients, which is a significant strength. However, this study has several limitations. First, the retrospective design may have introduced bias during data collection and analysis. As the study relied on EMRs, it may be limited by missing data, recording errors, and variability in data quality. We performed some data processing to address missing values—for example, when PaO₂ was unavailable for calculating the PaO₂/FiO₂ ratio used in the SOFA score, we estimated PaO₂ based on SpO₂ values. However, this imputation process may have introduced potential bias. Second, the COVID-19 pandemic may have influenced the results, particularly in terms of etiology, clinical outcomes, and ICU transfer patterns. Third, as an observational study, it cannot provide direct evidence of the effects of interventions, which requires careful interpretation of the findings.
In conclusion, ARF is a significant medical issue that affects hospitalized patients and has the potential to become a major societal concern, particularly in the aging population. The frequency of ARF and in-hospital mortality have been steadily increasing, with various etiologies contributing to this trend. However, epidemiological studies and research on individualized treatment for elderly patients are lacking. Therefore, nationwide prospective multicenter studies are required to address these issues.
KEY MESSAGES
▪ Acute respiratory failure remains a growing medical and societal concern, particularly in aging populations.
▪ Its frequency and in-hospital mortality rates are increasing, driven by various etiologies.
▪ Despite these trends, research on the epidemiology and individualized treatments for older patients is limited, highlighting the need for nationwide prospective multicenter studies.
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