Literature DB >> 26369551

Improvement of antibiotic therapy and ICU survival in severe non-pneumococcal community-acquired pneumonia: a matched case-control study.

Simone Gattarello1,2, Leonel Lagunes3,4, Loreto Vidaur5,6, Jordi Solé-Violán5,7, Rafael Zaragoza8, Jordi Vallés5,9, Antoni Torres5,10, Rafael Sierra11, Rosa Sebastian6, Jordi Rello3,4,5.   

Abstract

INTRODUCTION: We aimed to compare intensive care unit mortality due to non-pneumococcal severe community-acquired pneumonia between the periods 2000-2002 and 2008-2014, and the impact of the improvement in antibiotic strategies on outcomes.
METHODS: This was a matched case-control study enrolling 144 patients with non-pneumococcal severe pneumonia: 72 patients from the 2000-2002 database (CAPUCI I group) were paired with 72 from the 2008-2014 period (CAPUCI II group), matched by the following variables: microorganism, shock at admission, invasive mechanical ventilation, immunocompromise, chronic obstructive pulmonary disease, and age over 65 years.
RESULTS: The most frequent microorganism was methicillin-susceptible Staphylococcus aureus (22.1%) followed by Legionella pneumophila and Haemophilus influenzae (each 20.7%); prevalence of shock was 59.7%, while 73.6% of patients needed invasive mechanical ventilation. Intensive care unit mortality was significantly lower in the CAPUCI II group (34.7% versus 16.7%; odds ratio (OR) 0.78, 95% confidence interval (CI) 0.64-0.95; p = 0.02). Appropriate therapy according to microorganism was 91.5% in CAPUCI I and 92.7% in CAPUCI II, while combined therapy and early antibiotic treatment were significantly higher in CAPUCI II (76.4 versus 90.3% and 37.5 versus 63.9%; p < 0.05). In the multivariate analysis, combined antibiotic therapy (OR 0.23, 95% CI 0.07-0.74) and early antibiotic treatment (OR 0.07, 95% CI 0.02-0.22) were independently associated with decreased intensive care unit mortality.
CONCLUSIONS: In non-pneumococcal severe community-acquired pneumonia , early antibiotic administration and use of combined antibiotic therapy were both associated with increased intensive care unit survival during the study period.

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Year:  2015        PMID: 26369551      PMCID: PMC4570589          DOI: 10.1186/s13054-015-1051-1

Source DB:  PubMed          Journal:  Crit Care        ISSN: 1364-8535            Impact factor:   9.097


Introduction

In Western countries, community-acquired pneumonia (CAP) is the leading cause of death and is associated with high healthcare costs [1]. In the intensive care unit (ICU) setting, it is one of the most common reasons for admission and the most frequent causes of mortality [2]. Antibiotic treatment is the cornerstone for management of pneumonia, and adequate empiric treatment is associated with improved outcomes [1]. The trend in CAP mortality over recent decades remains unclear, despite many efforts to identify it. Contrasting results have been obtained in different publications because most of them did not differentiate between outpatients, patients admitted to the ward and patients admitted to the ICU [3, 4]. Conversely, many recently published studies have found a significant decrease in mortality in septic shock [5-7], or in severe respiratory failure requiring invasive mechanical ventilation (IMV) [8]; therefore, it is reasonable to assume that mortality due to severe pneumonia, especially when complicated with septic shock, may have decreased in the last few years. In a recent study, we found a reduction in mortality due to pneumococcal severe (S)CAP and an association between better management of antibiotic therapy and improved ICU survival [9]. The present study hypothesizes that, as in pneumococcal SCAP [9], an improvement in antibiotic policies will contribute to reducing mortality in non-pneumococcal SCAP. The primary objective was to determine ICU mortality due to non-pneumococcal SCAP, and the secondary objective was to assess whether improvements in antibiotic prescription had been implemented.

Materials and methods

This was a matched case–control study enrolling 144 ICU patients diagnosed with non-pneumococcal SCAP: 72 patients from the CAPUCI I study (2000–2002 period) were paired with 72 patients from the CAPUCI II database (2008–2014 period). CAPUCI I was a multicenter, prospective, observational study carried out in 33 hospitals in Spain between 2000 and 2002. All patients admitted to ICU with diagnosis of SCAP were included. CAPUCI II was a follow-up project endorsed by the European Critical Care Research Network, carried out in 29 European ICUs from 2008 to 2014. In both studies, patients were admitted to the ICU either to undergo IMV or because they were in an unstable clinical condition [1]. All cases were followed until ICU discharge or death, and all clinical decisions were left to the discretion of the attending physician. Data from these cohorts have been reported elsewhere [10]. The Joan XXIII University Hospital Ethics Board (coordinating centre) approved the study (REF 2005/NA); the need for informed consent was waived due to the observational nature of the studies. Pneumonia was diagnosed when a patient had consistent clinical findings plus a new pulmonary infiltrate on chest radiography. Immunocompromise was defined as primary immunodeficiency or immunodeficiency secondary to radiation treatment, use of cytotoxic drugs or steroids (daily doses >20 mg prednisolone or equivalent for >2 weeks), transplantation or AIDS. Shock was defined as the need for a vasopressor during >4 hours after fluid replacement; rapid radiographic spread was defined as an increase in the size of opacities on chest radiograph >50 % at 48 hours. SCAP was defined as pneumonia that required ICU admission, with single or multi-organ failure. Patients proceeding from a long-term care facility, diagnosed with healthcare-associated pneumonia and with a no-cardiopulmonary resuscitation indication were not included. Microbiological diagnosis required a positive result from a respiratory sample or blood culture, or a positive urinary antigen in the case of Legionella spp. infection. Probability of death was predicted according to the “estimated risk of mortality” using the Acute Physiology and Chronic Health Evaluation (APACHE) II score in the CAPUCI I cohort and Simplified Acute Physiology Score (SAPS) III in the CAPUCI II cohort [11, 12]. Monotherapy and combined therapy were defined as administration of the same antibiotic (one or more) during the first 2 days of ICU admission. Early antibiotic administration was defined as administration of the first dose of antibiotic within 3 hours of hospital admission. Patients with pneumonia and negative cultures, documented viral pneumonia or mixed aerobic/anaerobic flora were excluded; likewise, aspiration pneumonia, often associated with impaired clinical status [13], was excluded from the analysis so as to avoid bias. To perform the case–control analysis, each patient from the CAPUCI II group with a confirmed microbial etiology was matched with one from the CAPUCI I group with the same microorganism. Subsequently, the rest of variables used to match patients were: 1) presence of shock at ICU admission; 2) need for IMV; 3) immunosuppression; 4) chronic obstructive pulmonary disease; and 5) age (cut-off, 65 years) [14]; all main determinants for mortality in CAP [15, 16]. All data management and statistical analyses were performed using the SPSS 20 processor (SPSS inc., Chicago, IL). Results are expressed as medians and interquartile range for continuous variables, or as absolute percentages for categorical variables. Continuous variables were compared with the Mann–Whitney U test (non-normally distributed variables). Categorical variables were assessed with the chi-square or two-tailed Fisher exact test. A multivariate model was performed to identify the variables associates with changes in mortality. To construct the model, we performed a logistic regression using all variables from the univariate analysis that were associated with a different mortality as covariates; subsequently, to optimize the model and minimize an overfitting bias, an automatic stepwise backward covariate selection was performed. Thus, multivariate analysis was finally adjusted according to the following variables: shock at admission, acute renal failure, combination therapy and early antibiotic administration. Kaplan-Meier analysis was used to construct survival curves for patients receiving combination and monotherapy regimens and early versus late antibiotic administration.

Results

ICU mortality was significantly lower in the CAPUCI II group (34.7 versus 16.7 %; odds ratio (OR) 0.78, 95 % confidence interval (CI) 0.64–0.95; p = 0.02). Figure 1 shows a flow chart analysis for patient selection; in both CAPUCI I and CAPUCI II populations, mortality among patients enrolled in the analysis was compared with mortality of the rest of patients in the same group, with no significant differences being found (Fig. 1). In both cohorts, mortality of patients enrolled in the case–control analysis did not present significant differences when compared with patients not introduced into the analysis. Mortality in the CAPUCI I cohort was 34.7 % in patients enrolled in the analysis versus 33.8 % in non-matched patients with non-pneumococcal pneumonia with confirmed microorganism (p = 1.00); in CAPUCI II, it was 16.7 % in matched and 17.4 % in non-matched patients, respectively (p = 1.00). Figure 2 depicts survival depending on the microbiological isolate: the most frequent microorganism was Staphylococcus aureus (22.1 %), followed by Legionella pneumophila and Haemophilus influenzae (each 20.7 %). Table 1 shows the variables used to pair patients; individuals selected for the case–control analysis showed a prevalence of shock and IMV of 59.7 % and 73.6 %, respectively. Furthermore, Table 1 shows the prevalence of the matching variables in patients with non-pneumococcal bacterial pneumonia not selected for the matching analysis; no significant differences were observed between matched and non-matched patients. As indicated in Table 2, estimated probability of death was 32.0 % in the CAPUCI II group and 34.0 % in the CAPUCI I group (p = 0.59). Bacteremia was observed in 22.2 % of CAPUCI I and in 30.6 % of CAPUCI II (p = 0.35). No significant differences were observed in length of ICU stay (10.5 versus 12.0 days; p = 0.16) or length of IMV (8.0 versus 10.5 days; p = 0.18). Mortality showed an absolute reduction of 18 % between the CAPUCI II group (34.7 %) and the CAPUCI I group (16.7 %) (p = 0.02). Figure 3 compares ICU mortality between groups. In the CAPUCI II group, it fell significantly in the overall population with an OR of 0.78 (95 % CI 0.64–0.95; p = 0.02); in ventilated patients the OR was 0.70 (95 % CI 0.53–0.91; p = 0.01) while in patients with shock it was 0.60 (95 % CI 0.43–0.84; p < 0.01).
Fig. 1

Flow chart diagram of patient selection and mortality in the different subgroups

Fig. 2

ICU survival according to microorganism

Table 1

Description of matched variables and mortality

VariableCAPUCI I groupCAPUCI I p valueCAPUCI II groupCAPUCI II p value
(n = 72)non-matched(n = 72)non-matched
Age over 65 years32 (44.4)22 (28.6)0.0632 (44.4)23 (41.8)0.86
COPD34 (47.2)24 (31.2)0.0634 (47.2)19 (36.5)0.27
Immunosuppression9 (12.5)17 (22.1)0.149 (12.5)7 (12.5)1.00
Shock43 (59.7)47 (61.0)1.0043 (59.7)24 (43.6)0.08
IMV53 (73.6)57 (74.0)1.0053 (73.6)32 (60.4)0.13
ICU mortality25 (34.7)26 (33.8)1.0012 (16.7)8 (17.4)1.00

Data are presented as n (%). COPD chronic obstructive pulmonary disease, ICU intensive care unit, IMV invasive mechanical ventilation

Table 2

Other demographical data and clinical presentations

VariableCAPUCI I groupCAPUCI II group p value
(n = 72)(n = 72)
Agea 63.0 (47.5–75.0)62.0 (53.0–72.0)0.85
Age under 50 years20 (27.8)14 (19.4)0.33
Age 50–64 years20 (27.8)24 (33.3)0.59
Age 65–74 years13 (18.1)20 (27.8)0.23
Age over 75 years19 (26.4)14 (19.4)0.43
Male gender49 (68.1)54 (75.0)0.46
Active smoker25 (34.7)27 (37.5)0.86
Alcohol use24 (33.3)14 (19.4)0.09
Overweight14 (19.4)21 (29.2)0.24
Diabetes mellitus18 (25.0)15 (20.8)0.69
Cardiomyopathy24 (33.3)17 (23.6)0.27
Cerebral vascular disease4 (5.6)7 (9.7)0.53
Malignancy6 (8.3)4 (5.6)0.75
Estimated probability of deatha 32.0 (19.5–50.0)34.0 (16.0–62.8)0.59
ICU length of staya 10.5 (6.0–20.8)12.0 (7.0–33.0)0.16
Days of mechanical ventilationa 8.0 (4.0–15.3)10.5 (6.0–23.3)0.18
Bacteremia16 (22.2)22 (30.6)0.35
Acute kidney injury31 (43.1)29 (40.3)0.87
Rapid radiographic spread40 (55.6)37 (51.4)0.74
ICU mortality25 (34.7)12 (16.7) 0.02

Data are presented as n (%), unless otherwise indicated: a median (interquartile range 25–75). ICU intensive care unit. Significant p values are indicated in bold

Fig. 3

ICU mortality in the whole population and in different subgroups of patients. ICU intensive care unit, IMV invasive mechanical ventilation

Flow chart diagram of patient selection and mortality in the different subgroups ICU survival according to microorganism Description of matched variables and mortality Data are presented as n (%). COPD chronic obstructive pulmonary disease, ICU intensive care unit, IMV invasive mechanical ventilation Other demographical data and clinical presentations Data are presented as n (%), unless otherwise indicated: a median (interquartile range 25–75). ICU intensive care unit. Significant p values are indicated in bold ICU mortality in the whole population and in different subgroups of patients. ICU intensive care unit, IMV invasive mechanical ventilation Kaplan-Meier survival analysis was performed in the whole population and in the subgroups of patients who underwent IMV or required vasopressors, stratifying by monotherapy versus combined therapy (Fig. 4; log rank p value <0.01 in the three analyses) and early versus non-early antibiotic treatment (Fig. 5; log rank p value <0.01 in all three cases). As shown in Table 3, no significant ldifferences were observed between bacteremic and non-bacteremic patients.
Fig. 4

Kaplan-Meier survival curve stratified for monotherapy versus combined therapy. a The whole population (log rank p < 0.01); b patients with shock (log rank p < 0.01); c patients under mechanical ventilation (log rank p < 0.01). ICU intensive care unit

Fig. 5

Kaplan-Meier survival curve stratified for early versus non-early antibiotic treatment. a The whole population (log rank p < 0.01); b patients with shock (log rank p < 0.01); c patients under mechanical ventilation (log rank p < 0.01). ICU intensive care unit

Table 3

Comparison between bacteremic and non-bacteremic patients

VariableBacteremicNon-bacteremic p value
(n = 38)(n = 106)
Age under 50 years9 (23.7)25 (23.6)1.00
Age 50–64 years13 (34.2)31 (29.2)0.68
Age 65–74 years6 (15.8)27 (25.5)0.27
Age over 75 years10 (26.3)23 (21.7)0.65
Immunocompromised7 (18.4)11 (10.4)0.25
Shock at ICU admission23 (60.5)63 (59.4)1.00
Invasive mechanical ventilation28 (73.7)78 (73.6)1.00
Acute kidney injury17 (44.7)43 (40.6)0.70
Rapid radiographic spread24 (63.2)53 (50.0)0.19
Combined therapy34 (89.5)86 (81.1)0.31
Antibiotic initiated 0 to 3 hours18 (47.4)55 (51.9)0.71
ICU mortality11 (28.9)26 (24.5)0.67

Data are presented as n (%). ICU intensive care unit

Kaplan-Meier survival curve stratified for monotherapy versus combined therapy. a The whole population (log rank p < 0.01); b patients with shock (log rank p < 0.01); c patients under mechanical ventilation (log rank p < 0.01). ICU intensive care unit Kaplan-Meier survival curve stratified for early versus non-early antibiotic treatment. a The whole population (log rank p < 0.01); b patients with shock (log rank p < 0.01); c patients under mechanical ventilation (log rank p < 0.01). ICU intensive care unit Comparison between bacteremic and non-bacteremic patients Data are presented as n (%). ICU intensive care unit Combined therapy was administered in 76.4 % of patients in the CAPUCI I group and in 90.3 % in the CAPUCI II group (p = 0.04) (Table 4). Early antibiotic treatment was also significantly higher in the CAPUCI II group (63.9 versus 37.5 %; p < 0.01). The most frequent antibiotic prescription was a cephalosporin plus a macrolide (Table 5) in 58 out of 144 patients (40.1 %), with ceftriaxone/cefotaxime plus clarithromycin being the most frequent combination (29 patients out of 144, 20.1 %). The most frequent pattern delivered in the CAPUCI I group was ceftriaxone/cefotaxime plus clarithromycin (27 patients out of 72, 37.5 %) while in the CAPUCI II group it was ceftriaxone/cefotaxime plus levofloxacin (21 patients out of 72, 17.3 %). Azithromycin was not available in Spain in parenteral formulation between 2000 and 2002, so it was not used in this group.
Table 4

Characteristics of antibiotic treatment

VariableCAPUCI I groupCAPUCI II group p value
(n = 72)(n = 72)
Previous antibiotic14 (19.4)10 (13.9)0.50
Monotherapy17 (23.6)7 (9.7) 0.04
Combined therapy55 (76.4)65 (90.3) 0.04
Antibiotic initiated 0 to 3 hours25 (37.5)46 (63.9) <0.01
Antibiotic initiated 4 to 6 hours21 (29.2)17 (23.6)0.57
Antibiotic initiated more than 6 hours25 (33.3)9 (12.5) <0.01
Adequate according to 2007 IDSA/ATS guidelines31 (43.1)41 (56.9)0.13

Data are presented as n (%). Significant p values are indicated in bold. IDSA/ATS Infectious Diseases Society of America/American Thoracic Society

Table 5

Most frequent patterns of antibiotic treatment

VariableAll patients CAPUCI I groupCAPUCI II group p value
(n = 144)(n = 72)(n = 72)
Cephalosporin and macrolide58 (40.1)35 (48.5)23 (32.0)0.06
 Ceftriaxone/cefotaxime and clarithromycin29 (20.1)27 (37.5)2 (2.8) <0.01
 Ceftriaxone/cefotaxime and azithromycin18 (12.4)0 (0)18 (25.0) <0.01
 Other cephalosporin and macrolide11 (7.6)8 (11.1)3 (4.2)0.21
Cephalosporin and quinolone31 (21.5)6 (8.4)25 (34.6) <0.01
 Cefotaxime/ceftriaxone and levofloxacin25 (17.3)4 (5.6)21 (29.0) <0.01
 Other cephalosporin and quinolone6 (4.2)2 (2.8)4 (5.6)0.68
Penicillin and macrolide9 (6.3)2 (2.8)7 (9.7)0.17
 Piperacillin-tazobactam and azithromycin5 (3.5)0 (0)5 (6.9)0.06
 Other penicillin and macrolide4 (2.8)2 (2.8)2 (2.8)1.00
Amoxicillin-clavulanate8 (5.6)8 (11.1)0 (0) <0.01
Ceftriaxone/cefotaxime7 (4.9)5 (6.9)2 (2.8)0.44
Levofloxacin6 (4.2)4 (5.6)2 (2.8)0.68
Miscellaneous combined therapy22 (15.3)12 (16.7)10 (13.9)0.78
Miscellaneous monotherapy3 (2.1)0 (0)3 (4.2)0.25
Overall144 (100)72 (100)72 (100)

Data are presented as n (%). Significant p values are indicated in bold. p value calculated between CAPUCI I and CAPUCI II groups

Characteristics of antibiotic treatment Data are presented as n (%). Significant p values are indicated in bold. IDSA/ATS Infectious Diseases Society of America/American Thoracic Society Most frequent patterns of antibiotic treatment Data are presented as n (%). Significant p values are indicated in bold. p value calculated between CAPUCI I and CAPUCI II groups Table 6 shows the empiric antibiotic treatment delivered to each patient, and the appropriateness of the empiric antibiotic treatment with respect to the isolated microorganism. Overall, appropriate therapy based on bacteriology was 91.5 % in CAPUCI I and 92.7 % in CAPUCI II. Appropriate therapy was prescribed in all episodes caused by Staphylococcus aureus, Haemophilus influenzae, Escherichia coli, Klebsiella pneumoniae, Mycoplasma pneumoniae and Enterobacter aerogenes. Inappropriate therapy was only prescribed in episodes caused by Legionella pneumophila (2/15 and 2/15 in CAPUCI I and II, respectively) and Pseudomonas aeruginosa (6/11 and 5/11 in CAPUCI I and II, respectively).
Table 6

Treatment of each case of pneumonia and rate of adequate treatment according with the isolated microorganism

Staphylococcus aureus Legionella pneumophila Haemophilus influenzae Pseudomonas aeruginosa Escherichia coli Klebsiella pneumoniae Mycoplasma pneumoniae Enterobacter aerogenes
C IC IIC IC IIC IC IIC IC IIC IC IIC IC IIC IC IIC IC II
Amoxicillin-clavulanate1 (0)1 (1)5 (3)1 (1)
Cefotaxime/ceftriaxone3 (1)1 (0)2 (2)1 (1)
Levofloxacin1 (0)1 (0)1 (1)1 (1)2 (1)
Piperacillin-tazobactam1 (0)1 (1)1 (0)
Amoxicillin-clavulanate plus macrolide1 (0)1 (1)
Amoxicillin-clavulanate plus clindamycin1 (0)1 (0)
Amoxicillin-clavulanate plus levofloxacin1 (0)1 (1)
Cefotaxime/ceftriaxone plus macrolide9 (2)7 (0)6 (0)5 (2)5 (2)3 (0)4 (2)2 (0)1 (1)2 (0)3 (1)1 (0)1 (0)
Cefotaxime/ceftriaxone plus aztreonam1 (0)
Cefotaxime/ceftriaxone plus clindamycin
Cefotaxime/ceftriaxone plus levofloxacin1 (1)2 (0)1 (1)5 (0)6 (0)2 (0)1 (0)3 (0)1 (1)1 (0)1 (0)1 (0)
Cefepime/ceftazidime plus macrolide1 (0)1 (0)1 (0)3 (0)1 (0)1 (1)1 (1)
Cefepime plus amikacin1 (1)
Cefepime plus ciprofloxacin1 (0)1 (0)
Cefepime plus levofloxacin2 (1)2 (0)
Carbapenem/piperacillin-tazobactam plus amikacin1 (0)
Carbapenem/piperacillin-tazobactam plus clindamycin1 (0)1 (0)
Carbapenem/piperacillin-tazobactam plus ciprofloxacin1 (0)2 (1)1 (0)
Carbapenem/piperacillin-tazobactam plus macrolide1 (0)1 (1)1 (1)4 (1)1 (0)
Levofloxacin plus azithromycin1 (0)1 (0)
Levofloxacin plus tobramycin1 (0)
Piperacillin-tazobactam plus levofloxacin2 (0)1 (0)2 (1)
Overall161615151515111177442222
Adequate according with microorganisma 16 (100)16 (100)13 (86.7)13 (86.7)15 (100)15 (100)5 (45.5)6 (54.5)7 (100)7 (100)4 (100)4 (100)2 (100)2 (100)2 (100)2 (100)

Data are shown as absolute count of patients that received a specific antibiotic regimen; the number of patients who died receiving this antibiotic regimen is shown between parenthesis. a Data are presented as n (%). C I CAPUCI I, C II CAPUCI II

Treatment of each case of pneumonia and rate of adequate treatment according with the isolated microorganism Data are shown as absolute count of patients that received a specific antibiotic regimen; the number of patients who died receiving this antibiotic regimen is shown between parenthesis. a Data are presented as n (%). C I CAPUCI I, C II CAPUCI II Table 7 shows univariate and multivariate analyses for the assessment of variables associated with different mortality rates. In the univariate analysis, variables associated with a significant rise in ICU mortality were shock at ICU admission (p < 0.01), acute kidney injury (p < 0.01), need for IMV (p = 0.02) and alcohol use (p = 0.03); factors associated with lower ICU mortality were combined therapy (p < 0.01) and early antibiotic treatment (p < 0.01).
Table 7

Univariate and multivariate analyses to assess variables associated with changes in ICU mortality

VariableSurvivalNo survivalUnivariate analysisMultivariate analysis:
(n = 107)(n = 37) p valueOR (95 % CI); p value
Age over 65 years46 (43.0)18 (48.6)0.57
Overweight27 (25.2)8 (21.6)0.83
Alcohol use23 (21.5)15 (40.5) 0.03
Active smoker36 (33.6)16 (43.2)0.33
Diabetes mellitus24 (22.4)9 (24.3)0.83
Cardiomyopathy28 (26.2)13 (35.1)0.30
COPD49 (45.8)19 (51.4)0.57
Immunosuppression13 (12.1)5 (13.5)0.78
Shock at ICU admission56 (52.3)30 (81.1) <0.01 3.96 (1.29–12.14); 0.02
Invasive mechanical ventilation73 (68.2)33 (89.2) 0.02
Acute kidney injury36 (33.6)24 (64.9) <0.01 4.56 (1.60–13.02); <0.01
Rapid radiographic spread56 (52.3)21 (56.8)0.70
Bacteremia27 (25.2)11 (29.7)0.67
Combined therapy96 (89.7)24 (64.9) <0.01 0.23 (0.07–0.74); 0.01
AB initiated within 3 hours67 (62.6)6 (16.2) <0.01 0.07 (0.02–0.22); <0.01
Combined BL and M therapy52 (48.6)15 (40.5)0.45
Combined BL and FQ therapy33 (30.8)6 (16.2)0.09

Data are presented as n (%). Significant p values are indicated in bold. AB antibiotic, BL beta-lactam, CI confidence interval, COPD chronic obstructive pulmonary disease, FQ fluoroquinolone, ICU intensive care unit, M macrolide, OR odds ratio

Univariate and multivariate analyses to assess variables associated with changes in ICU mortality Data are presented as n (%). Significant p values are indicated in bold. AB antibiotic, BL beta-lactam, CI confidence interval, COPD chronic obstructive pulmonary disease, FQ fluoroquinolone, ICU intensive care unit, M macrolide, OR odds ratio As shown in Table 7, we explored whether the administration of a specific antibiotic combination was associated with changes in mortality, without observing significant differences. We compared mortality after the administration of either beta-lactam-macrolide (univariate analysis: OR 0.72, 95 % CI 0.34–1.54) or beta-lactam-quinolone (univariate analysis: OR 0.43, 95 % CI 0.17–1.14) regimens, without observing significant differences (data not shown). Variables from the univariate analysis that were associated with significant changes in mortality were introduced in a multivariate model analysis. Acute kidney injury and shock at ICU admission were associated with a higher risk of ICU mortality (OR 4.56, 95 % CI 1.60–13.02; and OR 3.96, 95 % CI 1.29–12.14, respectively. Conversely, early antibiotic treatment (OR 0.07, 95 % CI 0.02–0.22) and combined therapy (OR 0.23, 95 % CI 0.07–0.74) were associated with a lower risk of mortality during ICU admission. Furthermore, we explored if the agreement with 2007 Infectious Diseases Society of America/American Thoracic Society (IDSA/ATS) guidelines was associated with an improved outcome, observing a decreased mortality after delivery of adequate treatment (OR 0.65, 95 % CI 0.48–0.89). When we performed a multivariate analysis (variable introduced in the model: shock at admission, acute renal failure and 2007 IDSA/ATS agreement) the association was still significantly present (OR 0.39, 95 % CI 0.17–0.91). However, the same association was not present when, in the same multivariate model, the variables “combination therapy” and “early antibiotic administration” were added (for mortality for the variable “2007 IDSA/ATS agreement: OR 0.98; 95 % CI 0.32–2.97).

Discussion

The most relevant conclusions of the present analysis were the significant decrease in ICU mortality due to non-pneumococcal SCAP between the two cohorts, and the positive association between improved empirical antibiotic treatment and a lower mortality rate. These findings confirm our primary hypothesis, and are consistent with the results obtained from our previous study in patients with pneumococcal CAP from the same database [9]. Few published studies have assessed changes in mortality due to CAP in recent years. Moreover, as mentioned above, the vast majority did not differentiate between critical and non-critical patients [3, 4]. However, several studies have reported a significant decrease in mortality due to all-source septic shock in recent decades [5-7]. Our results were obtained in a population with a high rate of IMV (73.6 %) or secondary shock (59.7 %). In this setting, during the planning of a study, we believe that is vital to differentiate between critical and non-critical patients. To our knowledge, no studies to date have assessed mortality due to SCAP with regard to etiology. It is worth noting that, during the matching process, we did not set a percentage for each microorganism a priori; instead, we found the number of coincidences between groups according to the above-mentioned variables. Interestingly, the distribution of the identified microorganisms in our sample coincides with literature reports, thus confirming the study’s external reproducibility [1, 17]. As indicated in Table 6, the vast majority of patients received adequate treatment according to microbiology. As expected, appropriateness of treatment in case of infection due to Legionella pneumophila and Pseudomonas aeruginosa was lower. In case of Legionella infection the treatment was adequate in 86.7 % of patients from the CAPUCI I and II groups. On the other hand, treatment was adequate with respect to microbiology respectively in 45.5 and 54.5 % of patients with infection due to Pseudomonas aeruginosa. This is important because an inappropriate treatment can lead to an increased mortality. In fact, the survival rate in case of Pseudomonas pneumonia was the lowest when compared with other etiologies (with the exception of Enterobacter infection; however, this is not significant as only four patients were introduced in the analysis, two in each group), and this is probably due to the low rate of adequate empirical treatment. Despite this, an improvement in mortality was observed between the two periods, and this is probably due to the earlier administration of the first dose of antibiotic and other general improvements that have been made in the last years in the management of ICU patients. When exploring mortality depending on the etiology of pneumonia, we observed an increased survival between the two cohorts when pneumonia was caused by Staphylococcus aureus, Haemophilus influenzae, Pseudomonas aeruginosa, Escherichia coli and Enterobacter aerogenes. No changes were observed in case of Klebsiella infection, and an increased mortality was observed in case of Legionella pneumonia. As shown in Table 3, a higher proportion of patients from CAPUCI II received early combination therapy. When exploring the administration of mono- versus combination therapy, differentiating by the microorganisms, it becomes evident that all cases with the exception of Legionella and Pseudomonas infections received a higher rate of combined therapy if belonging to the CAPUCI II group (Table 6). Thus, it is reasonable to assume that the decrease in mortality in our sample was mainly caused by a higher rate of combination therapy and early antibiotic administration. In the case of pneumonia due to Legionella pneumophila, an increased mortality between the two groups was observed. Fifteen patients with Legionella infection were included in both groups: 3 out of 15 and 5 out 15 died, respectively, in the CAPUCI I and II groups. Among those who died, two individuals out of three from the CAPUCI I cohort received microbiological adequate coverture (one received a quinolone regimen while the other a macrolide regimen); in CAPUCI II, they were three out of five (all received a macrolide regimen) (Table 6). On the other hand, all patients but one (belonging to the CAPUCI II group) received delayed antibiotic treatment. We assume that the small size of the sample, fortuity and probably some unrecognized factor other than antibiotic therapy played a role in the different mortality. Due to the low number of patients that died because of Legionella infection, it is difficult to ascribe changes in mortality because of the use of quinolones rather than macrolides, although it is not possible to exclude it. In the case of Klebsiella infection, due to the reduced number of cases (four patients for each group, with 50 % mortality in both cohorts), it is not possible to take definitive conclusions. Another important finding is the association between lower mortality and an improvement in antibiotic strategies; that is, combined antibiotic therapy and early treatment initiation. Combined therapy has become common practice in the empirical treatment of SCAP [1]. To our knowledge, no current guideline suggests monotherapy as empirical therapy. Generally, the recommendation is a beta-lactam plus either a macrolide or a quinolone. In the CAPUCI I group, monotherapy was administered in 17 patients (23.6 %) and in 7 patients (9.7 %) in the CAPUCI II group. Univariate and multivariate analysis, and Kaplan-Meier survival analysis, all showed a positive association between delivery of combined antibiotic therapy and lower mortality. Previous studies observed that patients with CAP and secondary shock or bacteremia [18, 19] presented lower mortality when combined therapy was delivered. Our results confirm these findings and, furthermore, suggest that all patients with severe pneumonia, with or without shock or need for IMV, may benefit from combined therapy. Even though this may not be a surprising conclusion, it should be noted that a significant percentage of our population and those in other studies still received monotherapy [20]. These findings are consistent with those reported in patients with pneumococcal SCAP [9]. To date, the optimal antibiotic combination choice in severe CAP is still a debated issue; some authors advocate the use of a macrolide-regimen administration, due to the anti-inflammatory effects shown by these molecules [21]. However, not all studies achieved similar results. Although in our cohort the limited size of the sample makes it difficult to explore this issue, we assessed changes in mortality after macrolide or quinolone administration, in the whole population (Table 7) and in the subgroups of patients with shock or under mechanical ventilation (data not shown)—no differences were observed. Furthermore, several studies concluded that quinolone administration is comparable in terms of mortality with a macrolide regimen, but with a higher eradication rate, a lower treatment failure and possibly less cost of treatment [22]; however, concerns about an increased resistance rate after quinolone administration were raised [23]. Moreover, in case of a social environment with high rates of pulmonary tuberculosis, the use of a fluoroquinolone could mask a pulmonary tuberculosis rather than bacterial CAP [24]. In our sample, the use of a quinolone regimen showed a trend to lower mortality, without achieving significant results, in the whole population and in the subgroups of patients with shock or under mechanical ventilation. According to the present results, it is not possible to advocate the use of a specific antibiotic family. In 2006, Kumar et al. showed that mortality rates in septic patients with shock increased in line with the delay in antibiotic initiation [25]. Subsequent other studies of patients with shock confirmed this finding [26]. As shown in the Kaplan-Meier survival analysis (Fig. 5), early antibiotic treatment in our sample was associated with lower mortality not only in the subgroup of patients with shock, but in the overall population and in the subgroup of ventilated patients as well. In view of these findings, each patient who presents at the emergency room with non-pneumococcal SCAP should receive the first dose of antibiotic treatment within the first 3 hours. Indeed, the 2007 IDSA/ATS guidelines recommend initiation of antibiotic therapy before transfer to the ward or to the ICU [1]. We explored if the agreement with the 2007 IDSA/ATS guidelines was associated with different outcomes, and we found a reduced mortality when guideline recommendations were followed. Basically, IDSA/ATS guidelines recommend the administration of an early combination of specific antibiotic families; thus, to better investigate the effects of simple medical actions on mortality, we decided to separate the item “2007 IDSA/ATS adequate treatment” into two variables: “combined therapy” and “early antibiotic treatment”. Thus, after the addition of these two variables in the multivariate model this association was no longer documented. This might suggest that the sum of actions that imply the agreement to international guidelines is better investigated by separating these actions in multiple variables rather that grouping all actions into the variable “2007 IDSA/ATS adequate treatment”. The current study has some limitations that should be mentioned. The most important is its observational nature; however, this approach is the only way to assess changes in outcome over a period of time. Moreover, in the ICU setting in recent decades there have been significant improvements in the management of patients undergoing IMV or resuscitation of septic shock, and in nutrition, in the prevention of ICU-related complications and in the ICU admission criteria as well. Severity-of-illness was recorded with different scores; in CAPUCI I the risk of mortality was estimated using APACHE II score while in CAPUCI II SAPS III was used. However, both scales reflect a reliable risk of death and were widely validated in large-scale studies. For this, after estimating the risk of death with APACHE II and SAPS III scores, we created a variable named “estimated probability of death”, comparing both groups. Furthermore, to avoid an overlap between the same parameters in different variables, we decided not to use severity-score variables to match patients; in fact, both APACHE II and SAPS III scores include parameters of severity for respiratory or cardiac failure, and demographics such as age, which were introduced independently in the matching. Of note, the ICUs that participated in CAPUCI I and II studies were different; in fact, CAPUCI I was developed in 33 Spanish ICUs while CAPUCI II was carried out in 29 ICUs–24 from Spain and 5 from other European countries. This may originate a bias due to a different source of patients; however, after the matching process, we retrospectively observed that all 72 patients from the CAPUCI II cohort were enrolled from Spanish ICUs, thus minimizing the risk of a significant bias. Moreover, we did not perform genetic investigations, although recent publications have identified common variants in specific genes that are associated with different outcomes in severe pneumonia [27]. Finally, as stated by Waterer [28], ICU outcome often differs from hospital outcome or from outcome on day 60 or 90 after admission. However, as shown in the Kaplan-Meier survival analysis, the majority of deaths in our sample occurred within 14 days of admission. Although it is true that ICU mortality may differ from hospital or 3-month outcome, we feel that deferring excessively the time of the study of the outcome may complicate the analysis, because more variables that are difficult to record and interpret have to be introduced in the analysis as confounding variables.

Conclusions

In the current study, mortality due to non-pneumococcal SCAP decreased between the two cohorts, and the use of combined antibiotic therapy and early antibiotic administration were associated with lower mortality. These finding agree with the conclusions obtained in a previous study carried out in patients with pneumococcal SCAP from the same database [9]. More studies to confirm these findings are now needed. In the meantime, all patients presenting at the emergency department with SCAP should receive two antibiotics within 3 hours of admission.

Key messages

In the last 14 years, a significant reduction in ICU mortality due to severe community-acquired pneumonia was observed. In severe non-pneumococcal community-acquired pneumonia, early antibiotic administration and combination therapy were associated with a significant improved survival. A lower mortality was observed following early administration of combination therapy either in the subgroups of patients with shock, under mechanical ventilation and without shock or requirement of mechanical ventilation. The most frequent etiologies in severe CAP in the present cohort were Staphylococcus aureus followed by Legionella pneumophila and Haemophilus influenzae.
  28 in total

1.  Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study.

Authors:  W S Lim; M M van der Eerden; R Laing; W G Boersma; N Karalus; G I Town; S A Lewis; J T Macfarlane
Journal:  Thorax       Date:  2003-05       Impact factor: 9.139

2.  Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock.

Authors:  Anand Kumar; Daniel Roberts; Kenneth E Wood; Bruce Light; Joseph E Parrillo; Satendra Sharma; Robert Suppes; Daniel Feinstein; Sergio Zanotti; Leo Taiberg; David Gurka; Aseem Kumar; Mary Cheang
Journal:  Crit Care Med       Date:  2006-06       Impact factor: 7.598

3.  APACHE II: a severity of disease classification system.

Authors:  W A Knaus; E A Draper; D P Wagner; J E Zimmerman
Journal:  Crit Care Med       Date:  1985-10       Impact factor: 7.598

4.  Severe community-acquired pneumonia in an intensive care unit: risk factors for mortality.

Authors:  Akihiro Yoshimoto; Hiroyuki Nakamura; Masaki Fujimura; Shinji Nakao
Journal:  Intern Med       Date:  2005-07       Impact factor: 1.271

5.  Antibiotic prescription for community-acquired pneumonia in the intensive care unit: impact of adherence to Infectious Diseases Society of America guidelines on survival.

Authors:  M Bodí; A Rodríguez; J Solé-Violán; M C Gilavert; J Garnacho; J Blanquer; J Jimenez; M V de la Torre; J M Sirvent; J Almirall; A Doblas; J R Badía; F García; A Mendia; R Jordá; F Bobillo; J Vallés; M J Broch; N Carrasco; M A Herranz; J Rello
Journal:  Clin Infect Dis       Date:  2005-11-09       Impact factor: 9.079

6.  Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome.

Authors:  Roy G Brower; Michael A Matthay; Alan Morris; David Schoenfeld; B Taylor Thompson; Arthur Wheeler
Journal:  N Engl J Med       Date:  2000-05-04       Impact factor: 91.245

7.  Predictors of aspiration pneumonia in nursing home residents.

Authors:  Susan E Langmore; Kimberly A Skarupski; Pil S Park; Brant E Fries
Journal:  Dysphagia       Date:  2002       Impact factor: 3.438

8.  Combination antibiotic therapy lowers mortality among severely ill patients with pneumococcal bacteremia.

Authors:  Larry M Baddour; Victor L Yu; Keith P Klugman; Charles Feldman; Ake Ortqvist; Jordi Rello; Arthur J Morris; Carlos M Luna; David R Snydman; Wen Chien Ko; M Bernadete F Chedid; David S Hui; Antoine Andremont; Christine C C Chiou
Journal:  Am J Respir Crit Care Med       Date:  2004-06-07       Impact factor: 21.405

9.  SAPS 3--From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission.

Authors:  Rui P Moreno; Philipp G H Metnitz; Eduardo Almeida; Barbara Jordan; Peter Bauer; Ricardo Abizanda Campos; Gaetano Iapichino; David Edbrooke; Maurizia Capuzzo; Jean-Roger Le Gall
Journal:  Intensive Care Med       Date:  2005-08-17       Impact factor: 17.440

10.  Genome-wide association study of survival from sepsis due to pneumonia: an observational cohort study.

Authors:  Anna Rautanen; Tara C Mills; Anthony C Gordon; Paula Hutton; Michael Steffens; Rosamond Nuamah; Jean-Daniel Chiche; Tom Parks; Stephen J Chapman; Emma E Davenport; Katherine S Elliott; Julian Bion; Peter Lichtner; Thomas Meitinger; Thomas F Wienker; Mark J Caulfield; Charles Mein; Frank Bloos; Ilona Bobek; Paolo Cotogni; Vladimir Sramek; Silver Sarapuu; Makbule Kobilay; V Marco Ranieri; Jordi Rello; Gonzalo Sirgo; Yoram G Weiss; Stefan Russwurm; E Marion Schneider; Konrad Reinhart; Paul A H Holloway; Julian C Knight; Chris S Garrard; James A Russell; Keith R Walley; Frank Stüber; Adrian V S Hill; Charles J Hinds
Journal:  Lancet Respir Med       Date:  2014-12-18       Impact factor: 30.700

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  12 in total

Review 1.  South African guideline for the management of community-acquired pneumonia in adults.

Authors:  Tom H Boyles; Adrian Brink; Greg L Calligaro; Cheryl Cohen; Keertan Dheda; Gary Maartens; Guy A Richards; Richard van Zyl Smit; Clifford Smith; Sean Wasserman; Andrew C Whitelaw; Charles Feldman
Journal:  J Thorac Dis       Date:  2017-06       Impact factor: 2.895

2.  Improved survival among ICU-hospitalized patients with community-acquired pneumonia by unidentified organisms: a multicenter case-control study.

Authors:  J Rello; E Diaz; R Mañez; J Sole-Violan; J Valles; L Vidaur; R Zaragoza; S Gattarello
Journal:  Eur J Clin Microbiol Infect Dis       Date:  2016-09-21       Impact factor: 3.267

3.  In sepsis, beyond adherence, timeliness matters.

Authors:  Voon Shiong Ronnie Tan; Jason Phua; Tow Keang Lim
Journal:  J Thorac Dis       Date:  2017-09       Impact factor: 2.895

4.  Invasive Haemophilus influenzae disease among adults in Japan during 2014-2018.

Authors:  Yushi Hachisu; Kosuke Tamura; Koichi Murakami; Jiro Fujita; Hiroshi Watanabe; Yoshinari Tanabe; Koji Kuronuma; Tetsuya Kubota; Kengo Oshima; Takaya Maruyama; Kei Kasahara; Junichiro Nishi; Shuichi Abe; Masahiko Nakamura; Mayumi Kubota; Shinichiro Hirai; Taisei Ishioka; Chiaki Ikenoue; Munehisa Fukusumi; Tomimasa Sunagawa; Motoi Suzuki; Yukihiro Akeda; Kazunori Oishi
Journal:  Infection       Date:  2022-07-28       Impact factor: 7.455

5.  Burden of pneumococcal disease among adults in Southern Europe (Spain, Portugal, Italy, and Greece): a systematic review and meta-analysis.

Authors:  Adoración Navarro-Torné; Eva Agostina Montuori; Vasiliki Kossyvaki; Cristina Méndez
Journal:  Hum Vaccin Immunother       Date:  2021-06-09       Impact factor: 4.526

Review 6.  Epidemiology, virulence factors and management of the pneumococcus.

Authors:  Charles Feldman; Ronald Anderson
Journal:  F1000Res       Date:  2016-09-14

7.  Antibiotic de-escalation principle in elderly patients with chronic obstructive pulmonary disease complicated with severe pneumonia.

Authors:  Baohong Xiao; Mei Wang; Xiaoling Hu; Jinfeng Li; Fangfang Wang; Jiaxing Sun
Journal:  Exp Ther Med       Date:  2017-02-21       Impact factor: 2.447

Review 8.  Severe community-acquired pneumonia: timely management measures in the first 24 hours.

Authors:  Jason Phua; Nathan C Dean; Qi Guo; Win Sen Kuan; Hui Fang Lim; Tow Keang Lim
Journal:  Crit Care       Date:  2016-08-28       Impact factor: 9.097

Review 9.  Community-acquired bacterial pneumonia in adults: An update.

Authors:  Vandana Kalwaje Eshwara; Chiranjay Mukhopadhyay; Jordi Rello
Journal:  Indian J Med Res       Date:  2020-04       Impact factor: 2.375

Review 10.  Appropriate antibiotic management of bacterial lower respiratory tract infections.

Authors:  Charles Feldman; Guy Richards
Journal:  F1000Res       Date:  2018-07-23
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