1. Introduction
Bronchiectasis is a chronic disease defined radiologically by permanent and abnormal airway dilation and clinically by productive cough, sputum production, and recurrent infectious exacerbations [1]. The disease concept of bronchiectasis includes heterogeneous conditions with various underlying diseases. A previous systematic review of 8608 patients with bronchiectasis found that idiopathic bronchiectasis was the most common underlying condition (44.8%), followed by post-infection (29.9%), immunodeficiency (5.0%), chronic obstructive pulmonary disease (3.9%), and connective tissue disease (3.8%) [2]. However, there is some geographical variation in the incidence, prevalence, and clinical features of bronchiectasis [3,4,5]. Infection by nontuberculous mycobacteria is the most common background in patients with bronchiectasis in Japan and the United States [6,7]. The prevalence of bronchiectasis is increasing globally, and it is reportedly higher among women and older people. One study noted that the prevalence of bronchiectasis in the United Kingdom increased from 350.5 per 100,000 in 2004 to 566.1 per 100,000 in 2013 in women and from 301.2 per 100,000 in 2004 to 485.5 per 100,000 in 2013 in men [8]. Similar results have been reported from other countries [9,10,11].
The management objectives for patients with bronchiectasis are to reduce the frequency of exacerbations to prevent disease progression and improve prognosis. Airway clearance is a key treatment in bronchiectasis management. The British Thoracic Society (BTS) and European Respiratory Society (ERS) guidelines for the management of bronchiectasis in adults recommend long-term oral macrolides or inhaled antibiotics in patients with three or more exacerbations per year in addition to airway clearance [12,13]. Recently, studies focusing on the pathobiological relationships between bronchiectasis and Pseudomonas aeruginosa have been increasingly highlighted [14]. P. aeruginosa is frequently isolated from respiratory samples of patients with bronchiectasis. The European Multicentre Bronchiectasis Audit and Research Collaboration, an international research network for bronchiectasis in Europe, revealed that 3047 of 12,152 patients (25.1%) with bronchiectasis had positive cultures for P. aeruginosa [4]. Chronic P. aeruginosa infection has been linked to poor prognoses, including increases in exacerbations, hospital admissions, and mortality [15]. The BTS guidelines recommend regular sputum microbiology screening for patients with clinically significant bronchiectasis to detect pathogens, including newly isolated P. aeruginosa, suggesting treatment with antipseudomonal antibiotics for exacerbation of bronchiectasis if P. aeruginosa was detected in previous tests [13]. Furthermore, the ERS guidelines suggest that adults with bronchiectasis with a new isolation of P. aeruginosa should be offered eradication antibiotic treatment despite the extremely low quality of evidence [12].
Antibiotics covering P. aeruginosa are used for patients with bronchiectasis who experience bacterial pneumonia or exacerbation of bronchiectasis, especially when P. aeruginosa is isolated from respiratory samples. However, the impact of antibiotics with P. aeruginosa coverage in patients with bronchiectasis has not been fully elucidated. Thus, the effects of such antibiotics on prognosis among patients with bronchiectasis must be clarified to ensure proper antibiotic use. Therefore, we collected medical data on patients with bronchiectasis hospitalized because of bacterial pneumonia or exacerbation of bronchiectasis and evaluated the effectiveness of antipseudomonal therapy using the Japanese Diagnosis Procedure Combination (DPC) database to identify the association between the use of antipseudomonal antibiotics and mortality.
2. Results
2.1. Patients’ Characteristics
We identified 21,300 patients aged 18 years or older with bronchiectasis with an International Classification of Diseases, 10th Revision (ICD-10) code of A162 or J47 between April 2018 and March 2020. After excluding patients who did not receive any antibiotics within 3 days after admission or who died within 24 h after admission, 4943 patients admitted for bacterial pneumonia and 1914 patients admitted for exacerbation of bronchiectasis were included in this study (Figure 1). Of patients with bacterial pneumonia, 2633 and 2310 were classified into the antipseudomonal and nonantipseudomonal groups, respectively, and among those with exacerbation of bronchiectasis, 855 and 1059 were assigned to the antipseudomonal and nonantipseudomonal groups, respectively.
Among patients with bacterial pneumonia, the use of antipseudomonal antibiotics was linked to older age, female sex, lower body mass index (BMI), a higher Barthel index, a lower Charlson comorbidity index, and a higher Hugh–Jones dyspnea scale. Similarly, antipseudomonal antibiotics were more commonly used by patients without impaired consciousness; those who received supplemental oxygen, mechanical ventilation, or renal replacement therapy; those admitted to the intensive care unit (ICU); and those treated with antifungals, inhaled drugs, or vasopressors (Table 1). Meanwhile, among patients with exacerbation of bronchiectasis, antipseudomonal antibiotics were more frequently administered to those with lower BMI, a higher Charlson comorbidity index, and a higher Hugh–Jones dyspnea scale as well as those treated with antifungals or inhaled drugs (Table 2).
2.2. Propensity Score Matching (PSM)
A propensity score was calculated from all variables, and the area under the curve was 0.628 in patients with bacterial pneumonia and 0.609 in patients with exacerbation of bronchiectasis. After PSM, the baseline characteristics were well balanced between the groups for both patients with bacterial pneumonia and exacerbation of bronchiectasis.
2.3. Outcomes
In patients with bacterial pneumonia, the in-hospital mortality rate did not differ between the antipseudomonal and nonantipseudomonal groups (9.0% [185/2045] vs. 7.4% [151/2045]; p = 0.053), as presented in Table 3. Similarly, the length of hospital stay (15 days [interquartile range (IQR) = 10–24] vs. 14 days [IQR = 9–23]; p = 0.875) and total hospitalization costs (4023 US dollars [IQR = 2840–6273] vs. 3643 US dollars [IQR = 2598–5730]; p = 0.053) did not significantly differ between the groups. When patients were divided according to the timing of antibiotic treatment initiation, the in-hospital mortality rate among patients who received antibiotic treatment within 1 day after admission was higher in the antipseudomonal group than in the nonantipseudomonal group (9.1% [185/2041] vs. 7.1% [142/1989]; p = 0.025), whereas the mortality rate among patients who received antibiotic treatment 2 or 3 days after admission was higher in the nonantipseudomonal group than in the antipseudomonal group (16.1% [9/56] vs. 0% [0/4)].
In patients with exacerbation of bronchiectasis, the in-hospital mortality rate also did not differ between the antipseudomonal and nonantipseudomonal groups (5.2% [42/803] vs. 4.1% [33/803]; p = 0.287), as illustrated in Table 4. Although total hospitalization costs did not significantly differ between the groups (4029 US dollars [IQR = 2814–5909] vs. 3610 US dollars [IQR = 2202–5721]; p = 0.076), the length of hospital stay was significantly longer in the antipseudomonal group than in the nonantipseudomonal group (15 days [IQR = 10–22] vs. 12 days [IQR = 7–19]; p < 0.032). The in-hospital mortality rate also did not differ between patients categorized by the timing of antibiotic treatment initiation. Specifically, among patients who received antibiotic treatment within 1 day after admission, the in-hospital mortality rate was 4.8% (34/704) in the antipseudomonal group and 4.2% (26/622) in the nonantipseudomonal group (p = 0.570), whereas among patients who received antibiotic treatment 2 or 3 days after admission, the in-hospital mortality rates in the antipseudomonal and nonantipseudomonal groups were 8.1% (8/99) and 3.9% (7/181), respectively (p = 0.134).
Focusing on the patients’ ages and the types of antipseudomonal antibiotics, the in-hospital mortality rate increased with increasing age, and the in-hospital mortality rate was generally high among patients treated with carbapenems or tazobactam/piperacillin. Meanwhile, the in-hospital mortality rate was low among patients treated with ceftazidime or fluoroquinolones (Supplementary Tables S1 and S2).
3. Discussion
This study revealed that the use of antipseudomonal antibiotics was not associated with in-hospital mortality and total hospitalization costs among patients with bronchiectasis who developed bacterial pneumonia or experienced exacerbation of bronchiectasis. Although the length of hospital stay was significantly longer in the antipseudomonal group than in the nonantipseudomonal group among patients with exacerbation of bronchiectasis, no difference was noted among patients with bacterial pneumonia.
The use of antibiotics covering P. aeruginosa has been recommended for patients with critical conditions attributable to pneumonia, but recent studies failed to identify a benefit of antibiotics with P. aeruginosa coverage even for severe pneumonia [16,17,18]. Along with the severity of pneumonia, risk factors for antimicrobial resistance are considered for the indication of broad-spectrum antibiotics in clinical practice for pneumonia treatment. Although healthcare-associated pneumonia (HCAP) was first described as a concept of pneumonia in patients with frequent healthcare exposure who had a higher risk of infection by drug-resistant organisms, such as P. aeruginosa and methicillin-resistant Staphylococcus aureus (MRSA) [19], the use of antibiotics covering these organisms has not conferred favorable effects on clinical outcomes in patients with HCAP [16,17]. The American Thoracic Society and Infectious Diseases Society of America guidelines for community-acquired pneumonia (CAP) published in 2019 recommend against using the categorization of HCAP to guide the selection of extended-coverage antibiotics in patients with CAP and to select treatment that empirically covers P. aeruginosa or MRSA if they were isolated in previous tests [20]. However, a recent study demonstrated that the use of antibiotics covering P. aeruginosa in older adults who were admitted for CAP and in whom P. aeruginosa was isolated from sputum did not improve their prognosis [21]. The gap between the recommendations and real-world results could be linked to whether the isolation of P. aeruginosa from sputum reflects infection or colonization, as observed for pneumonia in patients in whom MRSA was isolated from respiratory samples [22].
P. aeruginosa is a major pathogen commonly isolated from the respiratory samples of patients with bronchiectasis [4], and it has been linked to poor prognoses [15,23]. Although the current study targeted patients with bronchiectasis, the use of antibiotics covering P. aeruginosa did not significantly decrease in-hospital mortality, suggesting that P. aeruginosa from respiratory samples might reflect colonization rather than infection. However, we could not identify the patients in whom P. aeruginosa was or was not isolated from respiratory samples because microbiological information was not contained in the DPC database. A study focusing on the impact of antibiotics covering P. aeruginosa only among patients with bronchiectasis in whom P. aeruginosa was isolated is required.
Similarly, the use of antipseudomonal antibiotics did not improve the prognosis of patients with exacerbation of bronchiectasis. However, whether attending physicians distinguished between bacterial pneumonia and exacerbation of bronchiectasis among patients in the DPC database remains unclear. As observed for bacterial pneumonia [21], the isolation of P. aeruginosa from respiratory samples might not always reflect respiratory infection. The international guidelines for bronchiectasis management recommend long-term oral macrolides or inhaled antibiotics in patients with three or more exacerbations per year [12,13]. Additionally, eradication antibiotic treatment is recommended for patients with bronchiectasis in whom P. aeruginosa is newly isolated despite an extremely low quality of evidence [12], and a recent study revealed that eradication treatment with combined systemic and inhaled antibiotics achieved higher eradication rates than systemic antibiotic alone [24]. For acute exacerbation of bronchiectasis, the BTS guidelines recommend the use of antibiotics covering P. aeruginosa if P. aeruginosa was detected in previous tests, and the ERS guidelines recommend antibiotic therapy for 14 days [12,13]. The current results suggest that patients with exacerbation of bronchiectasis do not necessarily require treatment with antibiotics covering P. aeruginosa. The need for antibiotics covering P. aeruginosa should be carefully determined on the basis of patients’ backgrounds and the organisms detected in previous respiratory sample cultures in consideration of whether the isolated pathogens reflect colonization or infection [21,25,26].
In the subgroup analyses, the in-hospital mortality rate among patients who received antibiotic treatment within 1 day after admission was higher in the antipseudomonal group than in the nonantipseudomonal group, whereas the mortality rate among patients who received antibiotic treatment 2 or 3 days after admission was likely higher in the nonantipseudomonal group than in the antipseudomonal group. Meanwhile, the mortality rate was higher in patients treated with carbapenems or tazobactam/piperacillin than in those treated with other antipseudomonal antibiotics. However, the timing of treatment initiation and type of antipseudomonal antibiotics were not included as adjustment factors in PSM. Therefore, we could not identify the optimal treatment timing or antipseudomonal antibiotic type for patients who developed bacterial pneumonia or experienced exacerbation of bronchiectasis. Factors not provided by the DPC database might have confounded these associations.
The strength of this study is that we focused on the association between the use of antipseudomonal antibiotics and in-hospital mortality among patients with bronchiectasis who were admitted for bacterial pneumonia or exacerbation of bronchiectasis using a national inpatient database in Japan. We adjusted the patients’ backgrounds by PSM because patients with severe pneumonia might be treated with antibiotics covering P. aeruginosa.
However, the current study had several limitations. First, the reliability and validity of the diagnosis recorded with an ICD-10 code are not strictly guaranteed even when the DPC database is used. The diagnoses of bacterial pneumonia and exacerbation of bronchiectasis in the current study were based on the “admission-precipitating diagnosis” in the DPC database, which was determined by attending physicians. Physicians might not accurately distinguish the exacerbation of bronchiectasis from bacterial pneumonia. Whether the current patients met the international diagnostic criteria also remains uncertain because we could not obtain data on clinical symptoms and radiological features [27]. Moreover, the causative underlying diseases for the development of bronchiectasis were not identified. Second, it is unclear whether P. aeruginosa was detected in respiratory samples because the DPC database does not contain microbiological data. Because of the same reasons, the information regarding the drug susceptibility patterns of P. aeruginosa could not be obtained. Additionally, we could not evaluate the risk factors for antimicrobial resistance among individual patients [28,29]. Third, only limited outcomes could be assessed using the DPC database. Although we examined in-hospital mortality, length of hospital stay, and total hospitalization costs for outcomes, other outcomes and variables, such as clinical cure, the amount of supplemental oxygen, and disease severity, could not be evaluated. Fourth, this study focused on whether antibiotics covering P. aeruginosa were administered within 3 days after admission; thus, the effects of escalation or de-escalation therapy on prognosis was not investigated. Finally, it remains uncertain whether each patient received an adequate dosage of antibiotics. The DPC database lacks serological data, including renal and liver functions, to calculate the appropriate dosage of antibiotics.
4. Methods
4.1. Data Source
This retrospective cohort study used the DPC database, a national inpatient database in Japan. The DPC system has been adopted by 1764 hospitals (approximately 480,000 beds) as of 2022, and it covers most hospital admissions for acute illnesses in Japan [30,31]. This database contains patient data on sex, age, body height and weight, smoking history (Brinkman index), activities of daily living score (Barthel index), state of consciousness (Japan Coma Scale) on admission, Charlson comorbidity index, Hugh–Jones dyspnea scale, diagnoses (“main diagnosis”, “admission-precipitating diagnosis”, “most resource-consuming diagnosis”, “second most resource-consuming diagnosis”, “comorbidities present at time of admission”, and “conditions arising after admission”) recoded with ICD-10 codes, procedures, drug administration, ICU admission, length of hospitalization, total hospitalization costs, and discharge status.
This study was approved by the Institutional Ethics Committee of Oita University Faculty of Medicine (approval no. 2765, 22 March 2024). The requirement for informed consent was waived by the committee because of the retrospective design of the study. Information for this research was posted at the hospital.
4.2. Study Population
Patients with bronchiectasis who were admitted to DPC hospitals because of bacterial pneumonia or exacerbation of bronchiectasis between April 2018 and March 2020 were included in this study. We first extracted patients with an ICD-10 code of A162 or J47, which indicates bronchiectasis as their main diagnosis, admission-precipitating diagnosis, most resource-consuming diagnosis, or second-most resource-consuming diagnosis or as a comorbidity present during admission. Next, patients with bronchiectasis hospitalized because of bacterial pneumonia or exacerbation of bronchiectasis were identified using the “admission-precipitating diagnosis” recorded using an ICD-10 code and Japanese disease names. Patients were grouped according to the receipt of antipseudomonal antibiotics (antipseudomonal antibiotic group or nonantipseudomonal antibiotic group), to which P. aeruginosa is generally considered susceptible, within 3 days after admission. Patients who did not receive any antibiotics within 3 days of admission, those younger than 18 years, and those who died within 24 h after admission were excluded. Our prior study focused on the medical causes of hospitalization among all patients with bronchiectasis using the DPC data of hospitalized patients with bronchiectasis between April 2018 and March 2020 [32]. However, the current study only targeted patients who were admitted for pneumonia or exacerbation of bronchiectasis, as this study’s aim was fundamentally different from that of the previous epidemiology study.
4.3. Data Collection and Outcomes
Patients’ background information, including sex, age, BMI, Brinkman index, Barthel index, Japan Coma Scale on admission, Charlson comorbidity index, Hugh–Jones dyspnea scale, length of hospital stay, and total hospitalization costs (1 US dollar equivalent to 150 Japanese yen), was collected from the DPC database. BMI was categorized using the following ranges in accordance with the World Health Organization definitions: <18.5, 18.5–24.9, 25.0–29.9, and ≥30.0 kg/m2 [33]. The Barthel index was classified into three categories: 0–55, 60–95, and 100. The Charlson comorbidity index was classified into four categories: 0, 1–2, 3–4, and ≥5. The Japan Coma Scale is widely used to assess patients’ consciousness level in Japan, and it is considerably correlated with the Glasgow Coma Scale [34].
To clarify the receipt of antipseudomonal antibiotics within 3 days of admission, the use of antibiotics listed in The Japanese Respiratory Society Guidelines for the Management of Pneumonia in Adults 2024 was investigated [35]. Specifically, piperacillin, tazobactam/piperacillin, ceftazidime, cefepime, cefozopran, cefpirome, imipenem/cilastatin, panipenem/betamipron, meropenem, biapenem, doripenem, tosufloxacin, levofloxacin, sitafloxacin, ciprofloxacin, pazufloxacin mesylate, gentamicin, amikacin, and tobramycin were considered antipseudomonal antibiotics [35,36].
In addition to antibiotics, the following drug administrations and procedures within 7 days were also surveyed: antifungals, including amphotericin B, liposomal amphotericin B, micafungin, caspofungin acetate, fluconazole, fosfluconazole, itraconazole, and voriconazole; inhaled drugs, including inhaled corticosteroids, long-acting β2 agonists, long-acting muscarinic antagonists, combinations of inhaled corticosteroids and long-acting β2 agonists, combinations of long-acting β2 agonists, long-acting muscarinic antagonists, and inhaled corticosteroids, combinations of long-acting β2 agonists and long-acting muscarinic antagonists, short-acting β2 agonists, and short-acting muscarinic antagonists; intravenous vasopressors, including dopamine, dobutamine, noradrenaline, and adrenaline; transfusions, including red blood cell transfusion, fresh frozen plasma transfusion, and platelet transfusion; supplemental oxygen; mechanical ventilation; renal replacement therapy; extracorporeal membrane oxygenation; and ICU admission.
The primary endpoint was in-hospital mortality, and the secondary endpoints were the length of hospitalization and total hospitalization costs.
4.4. PSM
To adjust the baseline characteristics of patients, we used 1:1 PSM with a nearest-neighbor method and set the caliper as 0.2. The propensity score was calculated using a logistic regression model with the following covariates: age, sex, BMI, smoking history, Barthel index, Japan Coma Scale on admission, Charlson comorbidity index, Hugh–Jones dyspnea scale, and treatment within 7 days after admission (antifungals, inhaled drugs, intravenous vasopressors, transfusion, supplemental oxygen, mechanical ventilation, renal replacement therapy, extracorporeal membrane oxygenation, and ICU admission).
4.5. Statistical Analysis
Statistical analyses were performed using the Statistical Package for the Social Sciences version 22 (IBM, Armonk, NY, USA). We performed comparisons between the two groups using a t-test for continuous variables and a chi-squared test or Fisher’s exact test for categorical variables. p-values smaller than 0.05 were considered statistically significant. Additionally, subgroup analyses focusing on the timing of treatment (within 1 day of admission vs. 2 or 3 days after admission), age, and the types of antipseudomonal antibiotics were conducted.
5. Conclusions
Although bronchiectasis is known to be associated with the isolation of P. aeruginosa from respiratory samples, the use of antibiotics covering P. aeruginosa for bacterial pneumonia and exacerbation of bronchiectasis does not necessarily contribute to an improved prognosis. A prospective study focusing on the impact of antibiotics covering P. aeruginosa among patients with bronchiectasis in whom P. aeruginosa was isolated is required.
A.H., K.F., H.S., R.K., S.O., K.H., J.-i.K. and K.K. substantially contributed to the study conceptualization. Material preparation, data collection, and analysis were performed by A.H., K.F., H.S., R.K., S.O. and K.K., A.H. and K.K. substantially contributed to the manuscript drafting. All authors have read and agreed to the published version of the manuscript.
This study was approved by the Institutional Ethics Committee of Oita University, Faculty of Medicine (approval no. 2765, 22 March 2024). All aspects of the study comply with the Declaration of Helsinki.
The need for informed consent was waived by the committee considering the retrospective design of the study. Information on this research was posted at the hospital.
The data are available from the corresponding author upon reasonable request.
We thank Dr. Mari Yamasue (Oita University) for her advice.
The authors declare no conflicts of interest.
Footnotes
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Clinical characteristics of patients with bronchiectasis before and after propensity score matching (admitted for bacterial pneumonia).
| Unmatched | Matched | |||||
|---|---|---|---|---|---|---|
| Antipseudomonal Group | Nonantipseudomonal Group | p | Antipseudomonal Group | Nonantipseudomonal Group | p | |
| Age (years) | 78 (71–84) | 81 (73–86) | <0.001 | 79 (72–85) | 80 (72–86) | 0.557 |
| Sex (female) | 1796 (68.2) | 1507 (65.2) | 0.027 | 1369 (66.9) | 1355 (66.3) | 0.643 |
| Body mass index (kg/m2) | ||||||
| <18.5 | 1388 (52.7) | 1077 (46.6) | <0.001 | 1004 (49.1) | 1004 (49.1) | 1.000 |
| 18.5–24.9 | 951 (36.1) | 899 (38.9) | 0.042 | 780 (38.1) | 784 (38.3) | 0.898 |
| 25.0–29.9 | 114 (4.3) | 105 (4.5) | 0.713 | 96 (4.7) | 96 (4.7) | 1.000 |
| ≥30.0 | 16 (0.6) | 28 (1.2) | 0.024 | 15 (0.7) | 14 (0.7) | 0.852 |
| Missing data | 164 (6.2) | 201 (8.7) | 0.001 | 150 (7.3) | 147 (7.2) | 0.857 |
| Smoking history | ||||||
| Nonsmoker | 1906 (72.4) | 1687 (73.0) | 0.614 | 1493 (73.0) | 1489 (72.8) | 0.888 |
| Current/past smoker | 469 (17.8) | 428 (18.5) | 0.515 | 366 (17.9) | 377 (18.4) | 0.656 |
| Missing data | 258 (9.8) | 195 (8.4) | 0.099 | 186 (9.1) | 179 (8.8) | 0.701 |
| Barthel index | ||||||
| 0–55 | 792 (30.1) | 771 (33.4) | 0.013 | 641 (31.3) | 638 (31.2) | 0.919 |
| 60–95 | 447 (17.0) | 390 (16.9) | 0.930 | 351 (17.2) | 346 (16.9) | 0.835 |
| 100 | 1026 (39.0) | 846 (36.6) | 0.090 | 778 (38.0) | 787 (38.5) | 0.772 |
| Missing data | 368 (14.0) | 303 (13.1) | 0.379 | 275 (13.4) | 274 (13.4) | 0.963 |
| Charlson comorbidity index | ||||||
| 0 | 12 (0.5) | 17 (0.7) | 0.198 | 11 (0.5) | 10 (0.5) | 0.827 |
| 1–2 | 1931 (73.3) | 1522 (65.9) | <0.001 | 1433 (70.1) | 1421 (69.5) | 0.683 |
| 3–4 | 613 (23.3) | 689 (29.8) | <0.001 | 533 (26.1) | 542 (26.5) | 0.749 |
| ≥5 | 77 (2.9) | 82 (3.5) | 0.214 | 68 (3.3) | 72 (3.5) | 0.731 |
| Japan Coma Scale | ||||||
| 0 | 2282 (86.7) | 1925 (83.3) | 0.001 | 1741 (85.1) | 1748 (85.5) | 0.757 |
| 1–3 | 289 (11.0) | 330 (14.3) | <0.001 | 259 (12.7) | 257 (12.6) | 0.925 |
| 10–30 | 45 (1.7) | 48 (2.1) | 0.341 | 39 (1.9) | 35 (1.7) | 0.639 |
| 100–300 | 17 (0.6) | 7 (0.3) | 0.084 | 6 (0.3) | 5 (0.2) | 0.763 |
| Hugh–Jones dyspnea scale | ||||||
| 1 | 376 (14.3) | 365 (15.8) | 0.135 | 321 (15.7) | 322 (15.7) | 0.966 |
| 2 | 428 (16.3) | 357 (15.5) | 0.442 | 336 (16.4) | 334 (16.3) | 0.933 |
| 3 | 393 (14.9) | 304 (13.2) | 0.075 | 276 (13.5) | 286 (14.0) | 0.650 |
| 4 | 513 (19.5) | 422 (18.3) | 0.276 | 386 (18.9) | 384 (18.8) | 0.936 |
| 5 | 442 (16.8) | 332 (14.4) | 0.020 | 302 (14.8) | 304 (14.9) | 0.930 |
| Missing data | 481 (18.3) | 530 (22.9) | <0.001 | 424 (20.7) | 415 (20.3) | 0.727 |
| Supplemental oxygen | 1572 (59.7) | 1168 (50.6) | <0.001 | 1089 (53.3) | 1088 (53.2) | 0.975 |
| Mechanical ventilation | 178 (6.8) | 57 (2.5) | <0.001 | 57 (2.8) | 57 (2.8) | 1.000 |
| Antifungal | 97 (3.7) | 25 (1.1) | <0.001 | 27 (1.3) | 25 (1.2) | 0.780 |
| Inhaled drug | 633 (24.0) | 431 (18.7) | <0.001 | 417 (20.4) | 412 (20.1) | 0.846 |
| Vasopressor | 72 (2.7) | 26 (1.1) | <0.001 | 28 (1.4) | 25 (1.2) | 0.678 |
| Red blood cell transfusion | 33 (1.3) | 20 (0.9) | 0.187 | 17 (0.8) | 20 (1.0) | 0.620 |
| Fresh frozen plasma transfusion | 2 (0.1) | 2 (0.1) | 1 | 0 (0.0) | 1 (0.0) | 1.000 |
| Platelet transfusion | 3 (0.1) | 1 (0.0) | 0.628 | 0 (0.0) | 1 (0.0) | 1.000 |
| Renal replacement therapy | 24 (0.9) | 7 (0.3) | 0.007 | 11 (0.5) | 7 (0.3) | 0.345 |
| ICU admission | 33 (1.3) | 10 (0.4) | 0.002 | 7 (0.3) | 10 (0.5) | 0.466 |
Values are presented as the median (interquartile range) or n (%). ICU, intensive care unit.
Clinical characteristics of patients with bronchiectasis before and after propensity score matching (admitted for exacerbation of bronchiectasis).
| Unmatched | Matched | |||||
|---|---|---|---|---|---|---|
| Antipseudomonal Group | Nonantipseudomonal Group | p | Antipseudomonal Group | Nonantipseudomonal Group | p | |
| Age (years) | 75 (68–81) | 76 (68–82) | 0.645 | 75 (68–82) | 76 (68–82) | 0.802 |
| Sex (female) | 618 (72.3) | 770 (72.7) | 0.834 | 577 (71.9) | 593 (73.8) | 0.369 |
| Body mass index (kg/m2) | ||||||
| <18.5 | 449 (52.5) | 506 (47.8) | 0.039 | 425 (52.9) | 422 (52.6) | 0.881 |
| 18.5–24.9 | 312 (36.5) | 431 (40.7) | 0.060 | 288 (35.9) | 288 (35.9) | 1.000 |
| 25.0–29.9 | 41 (4.8) | 55 (5.2) | 0.691 | 39 (4.9) | 44 (5.5) | 0.573 |
| ≥30.0 | 11 (1.3) | 10 (0.9) | 0.475 | 11 (1.4) | 10 (1.2) | 0.826 |
| Missing data | 42 (4.9) | 57 (5.4) | 0.644 | 40 (5.0) | 39 (4.9) | 0.908 |
| Smoking history | ||||||
| Nonsmoker | 653 (76.4) | 789 (74.5) | 0.345 | 610 (76.0) | 624 (77.7) | 0.408 |
| Current/past smoker | 145 (17.0) | 173 (16.3) | 0.716 | 136 (16.9) | 128 (15.9) | 0.590 |
| Missing data | 57 (6.7) | 97 (9.2) | 0.046 | 57 (7.1) | 51 (6.4) | 0.550 |
| Barthel index | ||||||
| 0–55 | 170 (19.9) | 226 (21.3) | 0.434 | 163 (20.3) | 163 (20.3) | 1.000 |
| 60–95 | 151 (17.7) | 181 (17.1) | 0.744 | 146 (18.2) | 148 (18.4) | 0.897 |
| 100 | 420 (49.1) | 528 (49.9) | 0.749 | 390 (48.6) | 389 (48.4) | 0.960 |
| Missing data | 114 (13.3) | 124 (11.7) | 0.284 | 104 (13.0) | 103 (12.8) | 0.941 |
| Charlson comorbidity index | ||||||
| 0 | 299 (35.0) | 437 (41.3) | 0.005 | 286 (35.6) | 298 (37.1) | 0.534 |
| 1–2 | 431 (50.4) | 476 (44.9) | 0.017 | 402 (50.1) | 394 (49.1) | 0.690 |
| 3–4 | 113 (13.2) | 127 (12.0) | 0.421 | 103 (12.8) | 102 (12.7) | 0.940 |
| ≥5 | 12 (1.4) | 19 (1.8) | 0.501 | 12 (1.5) | 9 (1.1) | 0.510 |
| Japan Coma Scale | ||||||
| 0 | 785 (91.8) | 978 (92.4) | 0.664 | 738 (91.9) | 739 (92.0) | 0.927 |
| 1–3 | 61 (7.1) | 67 (6.3) | 0.482 | 58 (7.2) | 56 (7.0) | 0.846 |
| 10–30 | 8 (0.9) | 10 (0.9) | 0.985 | 7 (0.9) | 8 (1.0) | 0.795 |
| 100–300 | 1 (0.1) | 4 (0.4) | 0.388 | 0 (0.0) | 0 (0.0) | |
| Hugh–Jones dyspnea scale | ||||||
| 1 | 171 (20.0) | 285 (26.9) | <0.001 | 169 (21.0) | 162 (20.2) | 0.666 |
| 2 | 172 (20.1) | 157 (14.8) | 0.002 | 145 (18.1) | 149 (18.6) | 0.796 |
| 3 | 135 (15.8) | 157 (14.8) | 0.560 | 127 (15.8) | 131 (16.3) | 0.786 |
| 4 | 165 (19.3) | 166 (15.7) | 0.037 | 159 (19.8) | 156 (19.4) | 0.850 |
| 5 | 118 (13.8) | 132 (12.5) | 0.388 | 109 (13.6) | 119 (14.8) | 0.475 |
| Missing data | 94 (11.0) | 162 (15.3) | 0.006 | 94 (11.7) | 86 (10.7) | 0.527 |
| Supplemental oxygen | 467 (54.6) | 555 (52.4) | 0.335 | 437 (54.4) | 432 (53.8) | 0.802 |
| Mechanical ventilation | 67 (7.8) | 61 (5.8) | 0.071 | 60 (7.5) | 52 (6.5) | 0.433 |
| Antifungal | 30 (3.5) | 21 (2.0) | 0.039 | 26 (3.2) | 18 (2.2) | 0.221 |
| Inhaled drug | 235 (27.5) | 225 (21.2) | 0.001 | 202 (25.2) | 202 (25.2) | 1.000 |
| Vasopressor | 27 (3.2) | 52 (4.9) | 0.055 | 23 (2.9) | 21 (2.6) | 0.760 |
| Red blood cell transfusion | 14 (1.6) | 19 (1.8) | 0.793 | 13 (1.6) | 13 (1.6) | 1.000 |
| Fresh frozen plasma transfusion | 3 (0.4) | 5 (0.5) | 0.738 | 2 (0.2) | 3 (0.4) | 1.000 |
| Platelet transfusion | 2 (0.2) | 1 (0.1) | 0.589 | 1 (0.1) | 1 (0.1) | 1.000 |
| Renal replacement therapy | 9 (1.1) | 13 (1.2) | 0.721 | 9 (1.1) | 9 (1.1) | 1.000 |
| ICU admission | 17 (2.0) | 19 (1.8) | 0.756 | 14 (1.7) | 13 (1.6) | 0.846 |
Values are presented as the median (interquartile range) or n (%). ICU, intensive care unit.
Outcomes before and after propensity score matching (admitted for bacterial pneumonia).
| Unmatched | Matched | |||||
|---|---|---|---|---|---|---|
| Antipseudomonal Group | Nonantipseudomonal Group | p | Antipseudomonal Group | Nonantipseudomonal Group | p | |
| In-hospital mortality | 274 (10.4) | 174 (7.5) | <0.001 | 185 (9.0) | 151 (7.4) | 0.053 |
| Hospital stay (days) | 15 (10–25) | 14 (9–23) | 0.308 | 15 (10–24) | 14 (9–23) | 0.875 |
| Hospitalization cost (US dollars) | 4165 (2919–6502) | 3661 (2626–5712) | <0.001 | 4023 (2840–6273) | 3643 (2598–5730) | 0.053 |
Values are presented as the median (interquartile range) or n (%).
Outcomes before and after propensity score matching (admitted for exacerbation of bronchiectasis).
| Unmatched | Matched | |||||
|---|---|---|---|---|---|---|
| Antipseudomonal Group | Nonantipseudomonal Group | p | Antipseudomonal Group | Nonantipseudomonal Group | p | |
| In-hospital mortality | 47 (5.5) | 47 (4.4) | 0.287 | 42 (5.2) | 33 (4.1) | 0.287 |
| Hospital stay (days) | 15 (10–22) | 11 (7–18) | 0.004 | 15 (10–22) | 12 (7–19) | 0.032 |
| Hospitalization cost (US dollars) | 4002 (2811–5838) | 3457 (2157–5830) | 0.039 | 4029 (2814–5909) | 3610 (2202–5721) | 0.076 |
Values are presented as the median (interquartile range) or n (%).
Supplementary Materials
The following supporting information can be downloaded at
References
1. O’Donnell, A.E. Bronchiectasis—A Clinical Review. N. Engl. J. Med.; 2022; 387, pp. 533-545. [DOI: https://dx.doi.org/10.1056/NEJMra2202819] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35947710]
2. Gao, Y.H.; Guan, W.J.; Liu, S.X.; Wang, L.; Cui, J.J.; Chen, R.C.; Zhang, G.J. Aetiology of bronchiectasis in adults: A systematic literature review. Respirology; 2016; 21, pp. 1376-1383. [DOI: https://dx.doi.org/10.1111/resp.12832] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27321896]
3. Chandrasekaran, R.; Mac Aogáin, M.; Chalmers, J.D.; Elborn, S.J.; Chotirmall, S.H. Geographic variation in the aetiology, epidemiology and microbiology of bronchiectasis. BMC Pulm. Med.; 2018; 18, 83. [DOI: https://dx.doi.org/10.1186/s12890-018-0638-0]
4. Chalmers, J.D.; Polverino, E.; Crichton, M.L.; Ringshausen, F.C.; De Soyza, A.; Vendrell, M.; Burgel, P.R.; Haworth, C.S.; Loebinger, M.R.; Dimakou, K. et al. Bronchiectasis in Europe: Data on disease characteristics from the European Bronchiectasis registry (EMBARC). Lancet Respir. Med.; 2023; 11, pp. 637-649. [DOI: https://dx.doi.org/10.1016/S2213-2600(23)00093-0]
5. Lee, H.; Choi, H.; Chalmers, J.D.; Dhar, R.; Nguyen, T.Q.; Visser, S.K.; Morgan, L.C.; Oh, Y.M. Characteristics of bronchiectasis in Korea: First data from the Korean Multicentre Bronchiectasis Audit and Research Collaboration registry and comparison with other international registries. Respirology; 2021; 26, pp. 619-621. [DOI: https://dx.doi.org/10.1111/resp.14059]
6. Aksamit, T.R.; Locantore, N.; Addrizzo-Harris, D.; Ali, J.; Barker, A.; Basavaraj, A.; Behrman, M.; Brunton, A.E.; Chalmers, S.; Choate, R. et al. Five-Year Outcomes among U.S. Bronchiectasis and NTM Research Registry Patients. Am. J. Respir. Crit. Care Med.; 2024; 210, pp. 108-118. [DOI: https://dx.doi.org/10.1164/rccm.202307-1165OC]
7. Asakura, T.; Morimoto, K.; Ito, A.; Suzuki, S.; Morino, E.; Oshitani, Y.; Nakagawa, T.; Yagi, K.; Kadowaki, T.; Saito, F. et al. Etiology and health-related quality of life in non-cystic fibrosis bronchiectasis and nontuberculous mycobacterial pulmonary disease: The first analysis of the Japanese Nontuberculous Mycobacteriosis-Bronchiectasis Registry. Am. J. Respir. Crit. Care Med.; 2020; 201, A4370.
8. Quint, J.K.; Millett, E.R.; Joshi, M.; Navaratnam, V.; Thomas, S.L.; Hurst, J.R.; Smeeth, L.; Brown, J.S. Changes in the incidence, prevalence and mortality of bronchiectasis in the UK from 2004 to 2013: A population-based cohort study. Eur. Respir. J.; 2016; 47, pp. 186-193. [DOI: https://dx.doi.org/10.1183/13993003.01033-2015]
9. Lin, J.L.; Xu, J.F.; Qu, J.M. Bronchiectasis in China. Ann. Am. Thorac. Soc.; 2016; 13, pp. 609-616. [DOI: https://dx.doi.org/10.1513/AnnalsATS.201511-740PS]
10. Seitz, A.E.; Olivier, K.N.; Steiner, C.A.; Montes de Oca, R.; Holland, S.M.; Prevots, D.R. Trends and burden of bronchiectasis-associated hospitalizations in the United States, 1993–2006. Chest; 2010; 138, pp. 944-949. [DOI: https://dx.doi.org/10.1378/chest.10-0099]
11. Ringshausen, F.C.; de Roux, A.; Diel, R.; Hohmann, D.; Welte, T.; Rademacher, J. Bronchiectasis in Germany: A population-based estimation of disease prevalence. Eur. Respir. J.; 2015; 46, pp. 1805-1807. [DOI: https://dx.doi.org/10.1183/13993003.00954-2015]
12. Polverino, E.; Goeminne, P.C.; McDonnell, M.J.; Aliberti, S.; Marshall, S.E.; Loebinger, M.R.; Murris, M.; Cantón, R.; Torres, A.; Dimakou, K. et al. European Respiratory Society guidelines for the management of adult bronchiectasis. Eur. Respir. J.; 2017; 50, 1700629. [DOI: https://dx.doi.org/10.1183/13993003.00629-2017] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28889110]
13. Hill, A.T.; Welham, S.A.; Sullivan, A.L.; Loebinger, M.R. Updated BTS Adult Bronchiectasis Guideline 2018: A multidisciplinary approach to comprehensive care. Thorax; 2019; 74, pp. 1-3. [DOI: https://dx.doi.org/10.1136/thoraxjnl-2018-212468] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30545985]
14. Dicker, A.J.; Lonergan, M.; Keir, H.R.; Smith, A.H.; Pollock, J.; Finch, S.; Cassidy, A.J.; Huang, J.T.; Chalmers, J.D. The sputum microbiome and clinical outcomes in patients with bronchiectasis: A prospective observational study. Lancet Respir. Med.; 2021; 9, pp. 885-896. [DOI: https://dx.doi.org/10.1016/S2213-2600(20)30557-9] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33961805]
15. Finch, S.; McDonnell, M.J.; Abo-Leyah, H.; Aliberti, S.; Chalmers, J.D. A Comprehensive Analysis of the Impact of Pseudomonas aeruginosa Colonization on Prognosis in Adult Bronchiectasis. Ann. Am. Thorac. Soc.; 2015; 12, pp. 1602-1611. [DOI: https://dx.doi.org/10.1513/AnnalsATS.201506-333OC]
16. Ito, A.; Ishida, T.; Tachibana, H.; Nakanishi, Y.; Yamazaki, A.; Washio, Y. Is antipseudomonal antibiotic treatment needed for all nursing and healthcare-associated pneumonia patients at risk for antimicrobial resistance?. J. Glob. Antimicrob. Resist.; 2020; 22, pp. 441-447. [DOI: https://dx.doi.org/10.1016/j.jgar.2020.04.021]
17. Matsuda, S.; Ogasawara, T.; Sugimoto, S.; Kato, S.; Umezawa, H.; Yano, T.; Kasamatsu, N. Prospective open-label randomized comparative, non-inferiority study of two initial antibiotic strategies for patients with nursing- and healthcare-associated pneumonia: Guideline-concordant therapy versus empiric therapy. J. Infect. Chemother.; 2016; 22, pp. 400-406. [DOI: https://dx.doi.org/10.1016/j.jiac.2016.03.003]
18. Park, G.E.; Ko, J.H.; Ki, H.K. Clinical Benefits of Piperacillin/Tazobactam versus a Combination of Ceftriaxone and Clindamycin in the Treatment of Early, Non-Ventilator, Hospital-Acquired Pneumonia in a Community-Based Hospital. Int. J. Gen. Med.; 2020; 13, pp. 705-712. [DOI: https://dx.doi.org/10.2147/IJGM.S271301]
19. American Thoracic SocietyInfectious Diseases Society of America. Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia. Am. J. Respir. Crit. Care Med.; 2005; 171, pp. 388-416. [DOI: https://dx.doi.org/10.1164/rccm.200405-644ST]
20. Metlay, J.P.; Waterer, G.W.; Long, A.C.; Anzueto, A.; Brozek, J.; Crothers, K.; Cooley, L.A.; Dean, N.C.; Fine, M.J.; Flanders, S.A. et al. Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America. Am. J. Respir. Crit. Care Med.; 2019; 200, pp. e45-e67. [DOI: https://dx.doi.org/10.1164/rccm.201908-1581ST]
21. Goto, A.; Komiya, K.; Umeki, K.; Hiramatsu, K.; Kadota, J.I. Impact of Pseudomonas aeruginosa coverage on the prognosis of elderly patients with community-acquired pneumonia. J. Infect. Chemother.; 2023; 29, pp. 55-60. [DOI: https://dx.doi.org/10.1016/j.jiac.2022.09.016] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36162646]
22. Goto, A.; Komiya, K.; Yamasue, M.; Yoshikawa, H.; Umeki, K.; Hiramatsu, K.; Kadota, J.I. Methicillin-resistant Staphylococcus aureus among elderly patients with community-acquired pneumonia. J. Infect. Chemother.; 2022; 28, pp. 1138-1142. [DOI: https://dx.doi.org/10.1016/j.jiac.2022.04.012] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35437226]
23. Richardson, H.; Dicker, A.J.; Barclay, H.; Chalmers, J.D. The microbiome in bronchiectasis. Eur. Respir. Rev.; 2019; 28, [DOI: https://dx.doi.org/10.1183/16000617.0048-2019] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31484665]
24. Conceição, M.; Shteinberg, M.; Goeminne, P.; Altenburg, J.; Chalmers, J.D. Eradication treatment for Pseudomonas aeruginosa infection in adults with bronchiectasis: A systematic review and meta-analysis. Eur. Respir. Rev.; 2024; 33, [DOI: https://dx.doi.org/10.1183/16000617.0178-2023] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38296344]
25. Shindo, Y.; Ito, R.; Kobayashi, D.; Ando, M.; Ichikawa, M.; Shiraki, A.; Goto, Y.; Fukui, Y.; Iwaki, M.; Okumura, J. et al. Risk factors for drug-resistant pathogens in community-acquired and healthcare-associated pneumonia. Am. J. Respir. Crit. Care Med.; 2013; 188, pp. 985-995. [DOI: https://dx.doi.org/10.1164/rccm.201301-0079OC]
26. Barreto, J.V.; Dias, C.C.; Cardoso, T. Risk factors for community-onset pneumonia caused by drug-resistant pathogens: A prospective cohort study. Eur. J. Intern. Med.; 2022; 96, pp. 66-73. [DOI: https://dx.doi.org/10.1016/j.ejim.2021.10.005]
27. Aliberti, S.; Goeminne, P.C.; O’Donnell, A.E.; Aksamit, T.R.; Al-Jahdali, H.; Barker, A.F.; Blasi, F.; Boersma, W.G.; Crichton, M.L.; De Soyza, A. et al. Criteria and definitions for the radiological and clinical diagnosis of bronchiectasis in adults for use in clinical trials: International consensus recommendations. Lancet Respir. Med.; 2022; 10, pp. 298-306. [DOI: https://dx.doi.org/10.1016/S2213-2600(21)00277-0]
28. Lewis, P.O. Risk Factor Evaluation for Methicillin-Resistant Staphylococcus aureus and Pseudomonas aeruginosa in Community-Acquired Pneumonia. Ann. Pharmacother.; 2021; 55, pp. 36-43. [DOI: https://dx.doi.org/10.1177/1060028020935106]
29. Metersky, M.L.; Frei, C.R.; Mortensen, E.M. Predictors of Pseudomonas and methicillin-resistant Staphylococcus aureus in hospitalized patients with healthcare-associated pneumonia. Respirology; 2016; 21, pp. 157-163. [DOI: https://dx.doi.org/10.1111/resp.12651]
30. Hayashida, K.; Murakami, G.; Matsuda, S.; Fushimi, K. History and Profile of Diagnosis Procedure Combination (DPC): Development of a Real Data Collection System for Acute Inpatient Care in Japan. J. Epidemiol.; 2021; 31, pp. 1-11. [DOI: https://dx.doi.org/10.2188/jea.JE20200288]
31. Central Social Insurance Medical Council (the Central Social Insurance Medical Council Medical Service Fee Investigation Professional Organization (DPC Evaluation Subcommittee Meeting)). Available online: https://www.mhlw.go.jp/stf/shingi/shingi-chuo_128164.html (accessed on 29 September 2024).
32. Hagiwara, A.; Shuto, H.; Kudoh, R.; Omori, S.; Hiramatsu, K.; Kadota, J.I.; Fushimi, K.; Komiya, K. Medical Causes of Hospitalisation among Patients with Bronchiectasis: A Nationwide Study in Japan. Pathogens; 2024; 13, 492. [DOI: https://dx.doi.org/10.3390/pathogens13060492] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/38921790]
33. Weir, C.B.; Jan, A. BMI Clsassification Percentile and Cut off Points; StatPearls: Treasure Island, FL, USA, 2024.
34. Nakajima, M.; Okada, Y.; Sonoo, T.; Goto, T. Development and Validation of a Novel Method for Converting the Japan Coma Scale to Glasgow Coma Scale. J. Epidemiol.; 2023; 33, pp. 531-535. [DOI: https://dx.doi.org/10.2188/jea.JE20220147] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35851565]
35. The Japanese Respiratory Society. The JRS Guidelines for the Management of Pneumonia in Adults 2024; The Japanese Respiratory Society: Tokyo, Japan, 2024.
36. Tamma, P.D.; Heil, E.L.; Justo, J.A.; Mathers, A.J.; Satlin, M.J.; Bonomo, R.A. Infectious Diseases Society of America 2024 Guidance on the Treatment of Antimicrobial-Resistant Gram-Negative Infections. Clin. Infect. Dis.; 2024; [DOI: https://dx.doi.org/10.1093/cid/ciae403]
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Details
; Kudoh, Ryohei 1 ; Omori, Shota 1
; Hiramatsu, Kazufumi 1 ; Kadota, Jun-ichi 1 ; Fushimi, Kiyohide 2
; Komiya, Kosaku 3
1 Respiratory Medicine and Infectious Diseases, Oita University Faculty of Medicine, 1-1 Idaigaoka, Hasama-machi, Yufu 879-5593, Oita, Japan
2 Department of Health Policy and Informatics, Tokyo Medical and Dental University Graduate School, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8519, Japan
3 Respiratory Medicine and Infectious Diseases, Oita University Faculty of Medicine, 1-1 Idaigaoka, Hasama-machi, Yufu 879-5593, Oita, Japan; Research Center for GLOBAL and LOCAL Infectious Diseases, Oita University Faculty of Medicine, 1-1 Idaigaoka, Hasama-machi, Yufu 879-5593, Oita, Japan