Literature DB >> 27052675

Characteristics and outcomes of anti-infective de-escalation during health care-associated intra-abdominal infections.

Philippe Montravers1,2, Pascal Augustin3, Nathalie Grall4,5,6, Mathieu Desmard3,7, Nicolas Allou3, Jean-Pierre Marmuse4,8, Jean Guglielminotti3,4,5.   

Abstract

BACKGROUND: De-escalation is strongly recommended for antibiotic stewardship. No studies have addressed this issue in the context of health care-associated intra-abdominal infections (HCIAI). We analyzed the factors that could interfere with this process and their clinical consequences in intensive care unit (ICU) patients with HCIAI.
METHODS: All consecutive patients admitted for the management of HCIAI who survived more than 3 days following their diagnosis, who remained in the ICU for more than 3 days, and who did not undergo early reoperation during the first 3 days were analyzed prospectively in an observational, single-center study in a tertiary care university hospital.
RESULTS: Overall, 311 patients with HCIAI were admitted to the ICU. De-escalation was applied in 110 patients (53%), and no de-escalation was reported in 96 patients (47%) (escalation in 65 [32%] and unchanged regimen in 31 [15%]). Lower proportions of Enterococcus faecium, nonfermenting Gram-negative bacilli (NFGNB), and multidrug-resistant (MDR) strains were cultured in the de-escalation group. No clinical difference was observed at day 7 between patients who were de-escalated and those who were not. Determinants of de-escalation in multivariate analysis were adequate empiric therapy (OR 9.60, 95% CI 4.02-22.97) and empiric use of vancomycin (OR 3.39, 95% CI 1.46-7.87), carbapenems (OR 2.64, 95% CI 1.01-6.91), and aminoglycosides (OR 2.31 95% CI 1.08-4.94). The presence of NFGNB (OR 0.28, 95% CI 0.09-0.89) and the presence of MDR bacteria (OR 0.21, 95% CI 0.09-0.52) were risk factors for non-de-escalation. De-escalation did not change the overall duration of therapy. The risk factors for death at day 28 were presence of fungi (HR 2.64, 95% CI 1.34-5.17), Sequential Organ Failure Assessment score on admission (HR 1.29, 95% CI 1.16-1.42), and age (HR 1.03, 95% CI 1.01-1.05). The survival rate expressed by a Kaplan-Meier curve was similar between groups (log-rank test p value 0.176).
CONCLUSIONS: De-escalation is a feasible option in patients with polymicrobial infections such as HCIAI, but MDR organisms and NFGNB limit its implementation.

Entities:  

Keywords:  Antibiotic therapy; De-escalation; Health care-associated intra-abdominal infections; Multidrug-resistant bacteria; Peritonitis

Mesh:

Substances:

Year:  2016        PMID: 27052675      PMCID: PMC4823898          DOI: 10.1186/s13054-016-1267-8

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


Background

The modern concept of reducing both the spectrum of antimicrobial therapy and its potential to promote resistance [1], usually called de-escalation, is strongly recommended in all of the recently published guidelines for antibiotic stewardship [2, 3]. Several definitions have been used to describe this process [1, 4–7]. Despite the limited evidence, de-escalation has been recommended to decrease the likelihood of emergence of resistant organisms [8], to optimize activity, and to reduce toxicity and costs [3]. Two types of critically ill patients have been investigated: cohorts with a specific disease—mainly ventilator-associated pneumonia (VAP) [5, 9–13]—and large mixed populations with severe sepsis or septic shock or patients who require emergency empiric antibiotic therapy [4, 14–19]. In a recent systematic review, Tabah et al. identified isolation of multiresistant pathogens, polymicrobial infections, and intra-abdominal infections as factors negatively associated with de-escalation [20]. Only a few studies have addressed this issue in the context of intra-abdominal infections [4, 14, 18, 21, 22]. The high frequency of polymicrobial infection [23, 24] and multidrug-resistant (MDR) organisms [23, 24] as well as the presence of fungi [17, 25] in this setting might raise specific concerns, especially in health care-associated intra-abdominal infections (HCIAI). The purpose of the present study was to analyze the frequency of de-escalation, the factors that could interfere with this process, and their clinical consequences in a cohort of intensive care unit (ICU) patients with HCIAI.

Methods

Study population

From January 1999 through December 2011, all consecutive patients admitted to our ICU for the management of HCIAI were prospectively included in a database and their medical charts were retrospectively reviewed. The study was approved by the local institutional review board (CEERB CHU Bichat Paris VII University, APHP, Paris, France), which waived the need for signed informed consent.

Selection of cases and inclusion criteria

Postoperative peritonitis was defined as the first macroscopic findings of intra-abdominal infection combined with positive fluid culture yielding at least one microorganism (bacteria or fungi) at the time of reoperation (day 0) following a first abdominal surgery [24]. Several patients had to be excluded from the analysis due to early change in their clinical status before de-escalation could be instituted: patients who died during the first 3 days following surgery (microbiologic results not yet obtained), those who were discharged during the first 3 days (incapacity to adequately follow clinical outcome and antibiotic therapy), and those who underwent early reoperation during the first 3 days (high proportion of persistent infection and prolonged antibiotic therapy). Similarly, we excluded patients with negative microbiologic samples, since the concept of de-escalation is questionable and the interpretation of the results is difficult. In these patients, empiric anti-infective therapy was discontinued. Drainage of abscesses, debridement of infected and necrotic tissues, abdominal cavity cleansing, irrigation, and definitive control of the source of contamination were performed according to the surgical principles used for the management of abdominal sepsis [26]. Ostomy was preferred to primary anastomosis. No open-wound management was performed, and the abdomen was not irrigated after surgery.

Microbiologic data

Peritoneal fluid samples were systematically collected during surgery and were immediately sent to the bacteriology laboratory [24]. Cultures were performed with identification and susceptibility testing for Gram-positive and Gram-negative aerobe bacteria, anaerobes, and fungi. Antibiotic susceptibility was determined for each organism by the disk diffusion method, according to the criteria of the Antibiogram Committee of the French Society for Microbiology [27]. MDR bacteria were defined as those resistant to three or more antimicrobial classes [28]: methicillin-resistant Staphylococcus aureus and methicillin-resistant coagulase-negative staphylococci; ampicillin-resistant enterococci; Enterobacteriaceae producing an extended-spectrum β-lactamase or producing a derepressed cephalosporinase; and/or nonfermenting Gram-negative bacilli (NFGNB) resistant to piperacillin-tazobactam, ceftazidime, or imipenem-cilastatin, or producing an extended-spectrum β-lactamase.

Management of antibiotic therapy

Empiric anti-infective therapy, systematically started at day 0, took into account the severity of the case and usually combined piperacillin-tazobactam or imipenem-cilastatin with amikacin and vancomycin [23], possibly associated with antifungal therapy (mainly fluconazole) based on presumed risk factors [25, 29]. Definitive anti-infective therapy was adapted on the basis of the results of identification and antibiotic susceptibility testing (≥48 h). In both situations, therapy was considered appropriate when all cultured organisms (bacteria and fungi) were targeted. Anti-infective therapy was prescribed by the senior ICU physicians following discussion with the consultant microbiologist on a daily basis. The following changes were considered to constitute de-escalation [1]: withdrawal of one agent (β-lactam, aminoglycoside, fluoroquinolone, vancomycin, antifungal agent) or narrowing spectrum of activity (β-lactam agents) and/or switch from combination to monotherapy. Discontinuation of unduly administered agents was also recorded. Changes among cefepime, ceftazidime, piperacillin-tazobactam, and ticarcillin-clavulanate were not considered to be significant changes of the spectrum of coverage [1]. In patients without de-escalation, two situations were identified according to previous definitions [4]. Maintained empiric treatment without modification was called unchanged therapy [4]. Escalation was defined as addition or switch to a new broad-spectrum anti-infective agent (carbapenems, glycopeptides, fluoroquinolones) [4] or upgrade to broader-spectrum β-lactams [1]. When changes combined escalation and de-escalation, the patient was assigned to the escalation group [4]. In summary, a patient receiving empiric therapy with piperacillin-tazobactam plus amikacin who was subsequently switched to piperacillin and vancomycin was classified as having withdrawal of one agent and escalation.

Data collection

All patients’ charts were reviewed. Demographic data and severity scores (Simplified Acute Physiology Score II score [30] and Sequential Organ Failure Assessment [SOFA] score [31]) were recorded on admission to the ICU. The severity of the underlying medical condition and the presence of chronic diseases [32] were recorded. The characteristics of initial surgery were recorded. The following clinical and severity characteristics were assessed at day 0, day 3, and day 7 after surgery for patients still in the ICU [24, 33, 34]: temperature, white blood cell count (WBC), serum creatinine, and SOFA score. Patients meeting the following three criteria at day 3 were arbitrarily defined as improving: (1) a SOFA score that decreased more than 2 points at day 3 versus day 0 or a SOFA score of 0 points, (2) a WBC that decreased more than 5000/mm3 between day 0 and day 3 or WBC less than 12,500/mm3, and (3) a temperature decrease greater than 0.5 °C between day 0 and day 3 or temperature greater than or equal to 36.5 °C and less than 38.1 °C. Similar analyses were used at day 7 to compare changes in these criteria between days 3 and 7. Medical and surgical complications, additional reoperations for persistence of the initial infection or superinfections (including MDR organisms), death between days 3 and 28 following surgery, and discharge from the hospital were assessed.

Statistical analysis

Results are expressed as median and interquartile range (IQR) or number and proportion. Statistical significance was defined as p < 0.05. For statistical analysis, we used R version 2.14.1 software (R Foundation for Statistical Computing, Vienna, Austria). For comparisons between antibiotic strategy groups (de-escalation, no change, or escalation), we used the χ2 test and Fisher’s exact test for discrete variables and unpaired Wilcoxon tests for quantitative variables. The effect of antibiotic strategy on day 28 mortality was assessed with a Kaplan-Meier survival curve and tested with a log-rank test. Three multivariable models were developed (1) to identify risk factors for de-escalation and (2) to assess the association between antibiotic strategy (de-escalation, no change, or escalation) and day 28 or in-hospital mortality. In univariate analysis for these three models, we used Fisher’s exact tests and Wilcoxon tests. Unadjusted ORs or HRs were calculated. Variables with a p value less than 0.2 in univariate analysis were entered into a multivariate logistic regression model or a Cox proportional hazards model with backward selection. For day 28 and in-hospital mortality, the antibiotic strategy was forced until the end of the selection process. Logistic models were evaluated for discrimination with the c-statistic and for calibration with the Hosmer-Lemeshow test.

Results

Epidemiologic and clinical characteristics

During the study period, 311 ICU patients were admitted for the management of HCIAI. Figure 1 displays a flowchart of patients through the study. Overall, 105 patients were excluded, resulting in 206 patients for whom the de-escalation process was analyzed. De-escalation was performed in 110 patients (53 % of the analyzed population), and no de-escalation was observed in 96 patients (47 %) (escalation in 65 patients [32 %] and unchanged regimen in 31 patients [15 %]). De-escalation was never performed after discharge from the ICU. The frequency of de-escalation remained stable over the study period, ranging between 47 % and 63 % of the analyzed population (not significant; data not shown). Clinical characteristics were similar at day 0 in both groups (Table 1). In the non-de-escalation group, a significantly increased severity was observed in the patients with an unchanged regimen versus escalation (Table 1).
Fig. 1

Flowchart of the 206 patients studied. ICU intensive care unit

Table 1

Demographic and clinical characteristics of the 206 patients with or without subsequent antibiotic de-escalation

CharacteristicDe-escalation (n = 110)No de-escalation (n = 96)Escalation (n = 65)No change (n = 31)
Male sex, n (%)61 (55)56 (58)35 (54)21 (68)
Age, years, median (IQR)61 (47–72)66 (51–75)a 63 (47–75)70 (58–77)
Comorbidities
 Fatal underlying disease30 (27)32 (33)21 (32)11 (35)
 Cancer, n (%)37 (34)36 (38)23 (35)13 (42)
 Diabetes, n (%)17 (15)15 (16)9 (14)6 (19)
Time since initial surgery, days, median (IQR)7 (5–12)7 (4–10)6 (3–9)8 (5–10)
Antibiotic therapy before reoperation, n (%)73 (66)68 (71)47 (72)21 (68)
Broad-spectrum interim antibiotic, n (%)34 (31)37 (39)27 (42)10 (32)
Intraoperative diagnosis
 Anastomotic leakage, n (%)45 (41)27 (28)19 (29)8 (26)
 Perforation or ischemia, n (%)33 (30)36 (38)20 (31)16 (52)a#
 Purulent collection, n (%)19 (17)17 (18)13 (20)4 (13)
 No cause, n (%)19 (17)20 (21)15 (23)5 (16)
Contamination below transverse mesocolon, n (%)82 (75)74 (77)50 (77)24 (77)
Characteristics at the time of ICU admission
 Bacteremia, n (%)26 (24)17 (18)14 (22)3 (10)
 SAPS II score, median (IQR)45 (34–54)47 (35–57)44 (34–56)51 (42–61)a#
 SOFA score, median (IQR)7 (4–9)8 (4–10)7 (4–9)9 (6–10)
 Hemodynamic failureb, n (%)65 (59)65 (68)41 (63)24 (77)
 Respiratory failureb, n (%)54 (49)40 (42)26 (40)14 (45)
 Renal failureb, n (%)21 (19)18 (19)13 (20)5 (16)

IQR interquartile range, SAPS II Simplified Acute Physiology Score II, SOFA Sequential Organ Failure Assessment

Patients without de-escalation were also analyzed in terms of subsequent antibiotic escalation or no change. Results are expressed as number and proportions or median (IQR)

a p < 0.05 versus de-escalation

bSOFA score of 3 or 4 for each organ

# p < 0.05 versus escalation

Flowchart of the 206 patients studied. ICU intensive care unit Demographic and clinical characteristics of the 206 patients with or without subsequent antibiotic de-escalation IQR interquartile range, SAPS II Simplified Acute Physiology Score II, SOFA Sequential Organ Failure Assessment Patients without de-escalation were also analyzed in terms of subsequent antibiotic escalation or no change. Results are expressed as number and proportions or median (IQR) a p < 0.05 versus de-escalation bSOFA score of 3 or 4 for each organ # p < 0.05 versus escalation

Microbiologic analysis

Overall, 618 microorganisms from peritoneal samples were cultured (311 in patients without de-escalation, including 101 organisms in the unchanged group and 210 in the escalation group). Similar microbiologic results were observed between de-escalation and no de-escalation groups (data not shown), except for lower proportions of Enterococcus faecium (9 [3 %] versus 18 [7 %] without de-escalation, respectively; p < 0.01) and non-fermenting Gram-negative bacilli (9 [3 %] versus 22 [8 %], respectively; p < 0.01). Among patients without de-escalation, increased proportions of Gram-negative bacteria and Enterobacteriaceae were observed in patients with unchanged regimen compared with those whose regimen was escalated (47 [49 %] versus 69 [37 %], respectively [p < 0.05]; and 38 [40 %] versus 52 [28 %] [p < 0.05]). In the de-escalation group, 23 (21 %) of 110 patients harbored MDR strains compared with 54 (56 %) of 96 patients in the non-de-escalation group (p < 0.01) (Table 2).
Table 2

Multidrug-resistant bacteria cultured from peritoneal fluid of patients with or without subsequent antibiotic de-escalation

MicroorganismsDe-escalationNo de-escalationEscalationNo change
Total number of multidrug-resistant bacteria, n (%)29 (9)74 (24)a 58 (28)16 (16)b
Gram-positive bacteria, n (%)15 (5)39 (13)a 33 (16)6 (6)b
 Enterococci, n (%)3 (1)9 (3)7 (3)2 (2)
 Staphylococci, n (%)12 (4)29 (9)25 (12)4 (4)
   Staphylococcus aureus, n (%)8 (3)6 (3)2 (2)
Gram-negative bacteria, n (%)14 (5)35 (11)a 25 (12)10 (10)
Enterobacteriaceae, n (%)10 (3)24 (8)18 (9)6 (6)
   Escherichia coli, n (%)1 (0)11 (4)8 (4)3 (3)
   Enterobacter spp., n (%)5 (2)9 (3)8 (4)1 (1)
 Nonfermenting Gram-negative bacilli, n (%)3 (1)11 (4)7 (3)4 (4)
   Pseudomonas spp., n (%)2 (1)6 (2)4 (2)2 (2)
Total number of cultured bacteria, n 307311210101

Among the 96 patients without de-escalation, the results were analyzed in terms of subsequent antibiotic escalation or no change

a p < 0.01 versus de-escalation

b p < 0.05 versus escalation

Multidrug-resistant bacteria cultured from peritoneal fluid of patients with or without subsequent antibiotic de-escalation Among the 96 patients without de-escalation, the results were analyzed in terms of subsequent antibiotic escalation or no change a p < 0.01 versus de-escalation b p < 0.05 versus escalation

Anti-infective therapy

De-escalation was performed on a microbiologic basis in a median delay of 3 days (IQR 2–4) after surgery. Empiric treatments and the procedures applied for de-escalation at day 3 are described in Table 3. Empiric use of combination therapy, carbapenems, glycopeptides, and antifungal agents were significantly more frequent in the de-escalation group. Among antifungal agents, echinocandins were minimally prescribed for empiric therapy (six patients in the de-escalation group with discontinuation in all but one case and one switch to azoles, one patient in the non-de-escalation group).
Table 3

Anti-infective regimens in patients with or without de-escalation and clinical characteristics at day 3

De-escalation (n = 110)No de-escalation (n = 96)Escalation (n = 65)No change (n = 31)
Empiric antibiotic therapy
 Monotherapy, n (%)13 (12)32 (33)a 20 (31)12 (29)
 Combination of two drugs, n (%)40 (36)34 (35)26 (40)8 (26)
 Combination of three drugs or more, n (%)57 (49)30 (33)b 19 (29)11 (35)
 Carbapenem, n (%)35 (32)15 (16)a 10 (15)5 (16)
 Piperacillin-tazobactam, n (%)67 (61)60 (63)40 (62)20 (65)
 Vancomycin, n (%)57 (52)23 (24)a 15 (23)8 (26)
 Aminoglycosides, n (%)59 (54)33 (34)a 27 (42)6 (19)b
 Fluoroquinolones, n (%)6 (5)11 (11)10 (15)1 (3)
Antifungal therapy, n (%)47 (43)23 (24)a 11 (17)12 (39)b
 Azoles, n (%)41 (37)20 (21)a 9 (14)11 (35)b
Adequate empiric therapy, n (%)100 (91)37 (39)a 9 (14)28 (90)c
Reevaluation of antibiotic therapy
 Discontinuation of carbapenemsd, n (%)27/35 (77)4/15 (27)4/10 (40)
 Discontinuation of piperacillin-tazobactamd, n (%)50/67 (75)25/60 (42)25/40 (63)
 Discontinuation of vancomycind, n (%)46/57 (81)6/23 (26)6/15 (40)
 Discontinuation of aminoglycosidesd, n (%)54/59 (92)21/33 (64)21/27 (78)
 Discontinuation of fluoroquinolonesd, n (%)2/6 (33)6/11 (55)6/10 (60)
 Discontinuation of antifungal agent d, n (%)23/47 (49)4/23 (17)4/11 (36)
 Withdrawal of at least one agent, n (%)110 (100)42 (47)a 42 (65)
 Narrowing spectrum, n (%)74 (67)18 (19)a 18 (28)
 Switch to monotherapy, n (%)54 (49)7 (7)a 7 (11)
 Interruption of unnecessary agent, n (%)78 (71)20 (21)a 20 (31)
Clinical changes between days 0 and 3
 Changes in SOFA score, median (IQR)−2 (−4 to -1)−2 (−4 to 0)−2 (−4 to 0)−2 (−3 to 0)
 Decreased SOFA score, n (%)69 (63)57 (59)38 (58)19 (61)
 Decreased temperature, n (%)69 (63)64 (67)41 (63)23 (74)
 Decreased WBC, n (%)38 (35)32 (33)23 (35)9 (29)
 Clinical improvement at day 3, n (%)17 (15)18 (19)14 (22)4 (13)

IQR interquartile range, SOFA Sequential Organ Failure Assessment, WBC white blood cell count

Among those without de-escalation, the results were analyzed in terms of subsequent antibiotic escalation or no change. Results are expressed as number and proportion of the total number of patients

a p < 0.01 versus de-escalation

b p < 0.05 versus de-escalation

c p < 0.01 versus escalation therapy

dProportions are expressed as the number of discontinuations of the drug to the total number of patients empirically receiving this class of drug

Anti-infective regimens in patients with or without de-escalation and clinical characteristics at day 3 IQR interquartile range, SOFA Sequential Organ Failure Assessment, WBC white blood cell count Among those without de-escalation, the results were analyzed in terms of subsequent antibiotic escalation or no change. Results are expressed as number and proportion of the total number of patients a p < 0.01 versus de-escalation b p < 0.05 versus de-escalation c p < 0.01 versus escalation therapy dProportions are expressed as the number of discontinuations of the drug to the total number of patients empirically receiving this class of drug When taking into account the criteria for de-escalation, we found that 33 patients met three criteria (withdrawing, narrowing, and switching) in the de-escalation group but none of those who did not de-escalate. However, two criteria (withdrawing and narrowing) were reported in 17 patients in the non-de-escalation group. No clinical change between days 0 and 3 allowed patients who were subsequently de-escalated to be differentiated from those who did not (Table 3). Determinants of de-escalation in multivariate analysis were adequate empiric therapy (OR 9.60, 95 % CI 4.02–22.97, p < 0.001), empiric use of vancomycin (OR 3.39, 95 % CI 1.46–7.87, p = 0.004), carbapenems (OR 2.64, 95 % CI 1.01–6.91, p = 0.04), and aminoglycosides (OR 2.31, 95 % CI 1.08–4.94, p = 0.03), while presence of NFGNB (OR 0.28, 95 % CI 0.09–0.89, p = 0.03) and presence of MDR bacteria (OR 0.21, 95 % CI 0.09–0.52, p < 0.001) were the risk factors for non-de-escalation (c-index 0.880, 95 % CI 0.832–0.928, Hosmer-Lemeshow test p = 0.14) (Table 4).
Table 4

Uni- and multivariate analyses of risk factors for de-escalation

Univariate analysisMultivariate analysis
De-escalation (n = 110)No de-escalation (n = 96)Unadjusted odds ratio (95 % CI) p valuea Adjusted odds ratio (95 % CI) p value
At time of admission
 Age, years61 (47–72)66 (51–75)0.98 (0.97–0.99)0.049
 Emergency surgery37 (34)44 (46)0.60 (0.34–1.05)0.087
 Anastomotic leakage45 (41)27 (28)1.76 (0.98–3.17)0.058
 Empiric antibiotic monotherapy13 (12)32 (33)0.26 (0.13–0.54)<0.01
  Initial use of carbapenems35 (32)15 (16)2.52 (1.27–4.98)0.0092.64 (1.01–6.91)0.047
  Initial use of vancomycin57 (52)23 (24)3.41 (1.87–6.21)<0.00013.39 (1.46–7.87)0.004
  Initial use of aminoglycosides59 (54)33 (34)2.20 (1.25–3.88)0.0072.31 (1.08–4.94)0.031
  Initial use of fluoroquinolones6 (5)11 (11)0.44 (0.15–1.22)0.134
  Initial use of antifungal agents47 (43)23 (24)2.36 (1.29–4.32)0.005
At day 3
 Presence of Enterococcus faecium 8 (7)18 (19)0.33 (0.14–0.82)0.019
 Presence of streptococci31 (28)17 (18)1.82 (0.93–3.55)0.098
 Presence of staphylococci25 (23)35 (36)0.51 (0.27–0.94)0.032
 Presence of NFGNB8 (7)22 (23)0.26 (0.11–0.62)0.0020.28 (0.09–0.89)0.031
 Presence of MDR strains23 (21)54 (56)0.20 (0.11– 0.37)<0.00010.21 (0.09–0.52)0.0007
 Presence of fungi30 (27)41 (43)0.50 (0.28–0.90)0.027
 Adequate empiric therapy100 (91)37 (39)15.95 (7.38–34.40)<0.00019.60 (4.02–22.97)<0.0001

MDR multidrug-resistant, NFGNB nonfermenting Gram-negative bacilli

The c-index of the final model is 0.880 (95 % CI 0.832–0.928), and the Hosmer-Lemeshow test p value is 0.14

a p values are derived from Fisher’s exact test or Wilcoxon test

Uni- and multivariate analyses of risk factors for de-escalation MDR multidrug-resistant, NFGNB nonfermenting Gram-negative bacilli The c-index of the final model is 0.880 (95 % CI 0.832–0.928), and the Hosmer-Lemeshow test p value is 0.14 a p values are derived from Fisher’s exact test or Wilcoxon test At day 3, no difference was observed between patients with an unchanged regimen and those who underwent escalation, except for the higher proportions of aminoglycosides and antifungal therapy and the very low proportion adequate empiric therapy (Table 3).

Clinical evaluation following de-escalation

When comparing the patients who were de-escalated and those who did not de-escalate, we found no significant difference between days 3 and 7 (Table 5). In addition, no significant difference in morbidity or mortality criteria was observed between these two groups.
Table 5

Clinical presentation at day 7 of empiric therapy and outcome in patients with or without de-escalation

De-escalation (n = 110)No de-escalation (n = 96)Escalation (n = 65)No change (n = 31)
Definitive anti-infective therapy
 Monotherapy, n (%)64 (58)21 (22)9 (14)12(29)a
 Combination of two drugs, n (%)33 (30)39 (41)31 (48)8 (26)b
 Combination of three drugs or more, n (%)13 (12)36 (38)25 (38)11 (35)
 Use of carbapenems, n (%)5 (5)23 (24)a 18 (28)5 (16)
 Use of piperacillin-tazobactam, n (%)28 (25)39 (41)b 19 (29)20 (65)a
 Use of vancomycin, n (%)11 (10)41 (43)a 33 (51)8 (26)b
 Use of antifungals, n (%)29 (26)43 (45)a 31 (48)12 (39)
 Use of azoles, n (%)28 (25)39 (41)b 28 (43)11 (35)
 Use of echinocandins, n (%)1 (1)3 (3)3 (5)
 Duration of anti-infective therapy, days, median (IQR)10 (10–14)10 (10–14)10 (10–14)10 (10–14)
Clinical changes between days 3 and 7
 Number of cases at day 791755124
  Changes in SOFA scorec, median (IQR)−1 (−3 to 0)−2 (−4 to 0)−2 (−4 to 0)−2 (−4 to 0)
  Decreased SOFA scorec, n (%)57 (63)48 (64)35 (54)13 (42)
  Decreased temperaturec, n (%)38 (42)36 (48)27 (42)9 (29)
  Decreased WBCc, n (%)31 (34)17 (23)12 (18)5 (16)
  Clinical improvement at day 7c, n (%)16 (18)9 (12)9 (14)
 Discharge between days 3 and 7, n (%)20 (22)15 (20)10 (20)5 (21)
 Death between days 3 and 7, n (%)1 (1)3 (4)2 (4)1 (4)
Medical complications12 (12)14 (16)6 (10)8 (29)
Surgical complications26 (25)21 (24)10 (17)11 (39)b
Reoperation, n (%)38 (35)35 (36)19 (29)16 (51)b
Time to reoperation, days, median (IQR)6 (5–9)6 (5–8)5 (4–8)7 (6–10)
Superinfection on subsequent reoperationd, n (%)23 (61)23 (66)13 (68)10 (63)
Emergence of MDR strainsd, n (%)21 (55)20 (57)11 (58)9 (56)
Emergence of ESBL Enterobacteriaceae d, n (%)5 (13)5 (14)3 (16)2 (13)
Emergence of MDR NFGNBd, n (%)9 (24)5 (14)2 (11)3 (19)
Emergence of MRSAd, n (%)9 (24)8 (23)6 (32)2 (13)
Duration of mechanical ventilatione, days, median (IQR)7 (3–13)7 (3–11)7 (2–10)7 (3–15)
ICU length of staye, days, median (IQR)12 (8–20)12 (8–21)12 (8–21)14 (5–23)
Survival at day 28, n (%)91 (83)72 (75)51 (78)21 (68)
ICU mortality rate, n (%)23 (21)32 (33)b 18 (28)14 (45)
Hospital mortality rate, n (%)25 (23)33 (34)19 (29)14 (45)

ESBL extended-spectrum β-lactamase, ICU intensive care unit, IQR interquartile range, MDR multidrug-resistant, MRSA methicillin-resistant Staphylococcus aureus, NFGNB nonfermenting Gram-negative bacilli, SOFA Sequential Organ Failure Assessment, WBC white blood cell count

Among those without de-escalation, the results were analyzed in terms of subsequent antibiotic escalation or no change

a p < 0.01 versus escalation therapy

b p < 0.05 versus escalation therapy

cResults expressed as number of patients at day 7 in the same group

dResults expressed as number of patients who underwent reoperation in the same group

eResults calculated for ICU survivor patients

Clinical presentation at day 7 of empiric therapy and outcome in patients with or without de-escalation ESBL extended-spectrum β-lactamase, ICU intensive care unit, IQR interquartile range, MDR multidrug-resistant, MRSA methicillin-resistant Staphylococcus aureus, NFGNB nonfermenting Gram-negative bacilli, SOFA Sequential Organ Failure Assessment, WBC white blood cell count Among those without de-escalation, the results were analyzed in terms of subsequent antibiotic escalation or no change a p < 0.01 versus escalation therapy b p < 0.05 versus escalation therapy cResults expressed as number of patients at day 7 in the same group dResults expressed as number of patients who underwent reoperation in the same group eResults calculated for ICU survivor patients No significant differences in morbidity or mortality criteria were observed between patients who underwent escalation and those with an unchanged regimen, except for significantly increased proportions of surgical complications and reoperations in patients with an unchanged regimen. The risk factors for death at day 28 following surgery in a Cox model are presented in Table 6. The survival rate expressed by a Kaplan-Meier curve was similar between groups (log-rank test p value 0.176) (Fig. 2).
Table 6

Uni- and multivariate analyses of risk factors for 28-day mortality

Univariate analysisMultivariate analysis
Death at day 28 (n = 43)Survival at day 28 (n = 163)Unadjusted hazard ratio (95 % CI) p valuea Adjusted hazard ratio (95 % CI) p value
Age, years69 (56–78)62 (46–72)1.022 (1.003–1.042)0.0231.034 (1.011–1.059)0.004
Emergency surgery24 (56)57 (35)2.072 (1.135–3.783)0.015
Surgery below the mesocolon28 (65)128 (79)0.561 (0.299–1.050)0.0750.427 (0.215–0.848)0.015
SOFA score10 (7–11)7 (4–9)1.261 (1.153–1.380)<0.00011.291 (1.168–1.427)<0.0001
SAPS II score52 (45–61)44 (32–53)1.039 (1.019–1.060)<0.0001
Initial use of piperacillin-tazobactam22 (51)105 (64)0.636 (0.350–1.157)0.117
Empiric antifungal therapy21 (49)49 (30)1.980 (1.089–3.601)0.029
Other Enterobacteriaceae b 5 (12)34 (21)0.538 (0.212–1.366)0.1950.342 (0.1219–0.961)0.0419
Presence of Candida spp.19 (44)52 (32)1.569 (0.859–2.865)0.1502.641 (1.3471–5.179)0.0047
Decreased SOFA score at day 317 (40)109 (67)0.372 (0.202–0.686)0.00150.311 (0.1632–0.593)0.0004
Antibiotic strategy0.189
 De-escalation19 (44)91 (56)0.488 (0.227–1.051)0.566 (0.2503–1.278)0.171
 No change10 (23)21 (13)ReferenceReferenceReference
 Escalation14 (33)51 (31)0.627 (0.278–1.411)0.508 (0.2154–1.198)0.122

SAPS II Simplified Acute Physiology Score II, SOFA Sequential Organ Failure Assessment

a p values are from Fisher exact tests or Wilcoxon tests

bOther Enterobacteriaceae: analysis of all Enterobacteriaceae except Escherichia coli, Klebsiella spp., and Enterobacter spp.

Fig. 2

Kaplan-Meier survival curves of patients with de-escalation, without any change, and with escalation

Uni- and multivariate analyses of risk factors for 28-day mortality SAPS II Simplified Acute Physiology Score II, SOFA Sequential Organ Failure Assessment a p values are from Fisher exact tests or Wilcoxon tests bOther Enterobacteriaceae: analysis of all Enterobacteriaceae except Escherichia coli, Klebsiella spp., and Enterobacter spp. Kaplan-Meier survival curves of patients with de-escalation, without any change, and with escalation The risk factors of in-hospital mortality on multivariate analysis were the emergency initial surgery (OR 2.81, 95 % CI 1.30–6.05, p = 0.008) and SOFA score on admission (OR 1.42, 95 % CI 1.24–1.62, p < 0.001), while a decreased SOFA score at day 3 had a protective value (OR 0.14, 95 % CI 0.06–0.31, p < 0.001) (c-index 0.852, 95 % CI 0.794–0.910, Hosmer-Lemeshow test p = 0.28).

Discussion

In this single-center observational study, de-escalation was performed in 53 % of patients treated for HCIAI. De-escalation concerned both antibacterial and antifungal therapies. The de-escalation procedure did not modify outcome. No initial clinical characteristic allowed identification of patients who were subsequently de-escalated. The presence of MDR bacteria and NFGNB as well as initial monotherapy were the most relevant factors limiting de-escalation. No emergence of resistant organisms was observed following de-escalation in the patients who underwent subsequent reoperation. In the absence of data in the literature, we consider that our results provide an encouraging perspective for antibiotic de-escalation in ICU patients with abdominal sepsis. However, some limitations should be considered. Only 110 (35 %) of 311 patients treated for HCIAI were de-escalated. This highly selected population and the inclusion and exclusion criteria could be considered to constitute a weakness, but they allow selection of cases in which de-escalation is possible. Our local policy for empiric and definitive antibiotic use and the local characteristics of microbial flora must be considered cautiously and cannot be generalized. The long study duration may also have led to changes in the case mix or in antibiotic susceptibility patterns over time, although our analysis did not confirm this hypothesis. Another major limitation in the interpretation of our results is the lack of assessment of the quality of source control. The exclusion of patients undergoing early reoperation probably limited the importance of this issue. The absence of consensual definitions for de-escalation is another issue to be considered. The quality of de-escalation could be considered incomplete in many patients in whom there is room for improvement, and further reduction of antibiotic use or the use of narrow-spectrum empiric therapy should be considered. Observational and retrospective studies have suggested that the de-escalation strategy is a safe approach in patients with severe sepsis or septic shock [10–12, 15, 18, 19, 22, 35]. In recent European observational trials, the de-escalation rate ranged between 12.8 % of cases in a multicenter study in 41 French ICUs [35] and 64 % in a single-center analysis focused on patients with severe sepsis and septic shock [15]. Some prospective observational studies have suggested that mortality rates were at least not worse than those observed in patients not de-escalated [16, 36–38]. In these reports, the lengths of ICU and hospital stay were not significantly different [36, 37]. Other authors have reported that de-escalation therapy could even significantly improve the prognosis [4, 13, 39]. Prospective randomized trials addressing the issue of de-escalation are extremely rare. In a cohort of 290 patients treated for VAP, Micek et al. reported a decreased duration of antibiotic therapy and no significant differences in terms of secondary episodes of VAP and hospital mortality [37]. In a group of 116 patients with severe sepsis either assigned or not to de-escalation, Leone et al. demonstrated that de-escalation was inferior to continuation of the initial antibiotic therapy with length of stay as the primary outcome parameter [40]. Furthermore, antibiotic use was higher in the de-escalation group with a higher number of superinfections in the de-escalation group, but mortality was similar in the two groups [40]. Only four retrospective, single-center, observational studies have described de-escalation practices for patients with peritonitis [14, 18, 21, 22], including between 113 and 229 patients, 10–38 % of whom presented with peritonitis. Although the observed de-escalation rate was 23–58 % in this population, none of these studies provided any information on the outcome of de-escalated patients. Our analysis is the first to focus on this surgical population, and our results suggest that de-escalation is safe and does not change the clinical outcome. On the basis of our results, a prospective multicenter study would appear to be feasible. Obstacles to de-escalation have been clearly identified in the literature [20]. The lack of appropriate empiric therapy is the first point to be considered [13, 22]. A high rate of MDR bacteria is an obvious reason for inadequate empiric therapy and consequently a recognized factor for limited de-escalation [20]. However, although a recent analysis suggested that polymicrobial infection was a negative factor for de-escalation [20], we did not observe this trend in the patients in our present study. Narrow-spectrum empiric therapy is obviously another important determinant limiting the frequency of de-escalation [22]. However, narrow-spectrum empiric therapy is not an issue in intra-abdominal infections in which treatment should at least target anaerobes and Enterobacteriaceae [41]. On the contrary, monotherapy has been proposed for the treatment of peritonitis [41], and this policy could be a limitation on de-escalation [18]. Poor or absent clinical improvement is another factor limiting de-escalation. In the present study, clinical and laboratory parameters of day 3 were unable to differentiate patients in whom de-escalation would be feasible and those in whom de-escalation could not be performed. Interestingly, Garnacho-Montero et al. reported lower SOFA scores at the time of de-escalation [4], suggesting that the criteria for de-escalation may change from one population to another. This also means that prescribers should rely on microbiologic samples and the laboratory results more than any other criteria. The confidence of prescribers in their initial therapy is also based on two parameters that have been only minimally assessed in the literature: adequacy of source control and pharmacokinetics of anti-infective agents. Several reports have indicated early improvement in patients who underwent de-escalation. Paskovaty et al., in a cohort of adult patients with cancer admitted to the ICU for severe sepsis, reported a significantly decreased SOFA score on day 5 [42]. Two studies of patients with nosocomial pneumonia and ICU-acquired pneumonia reported early decreased SOFA and Acute Physiology and Chronic Health Evaluation II scores in the de-escalation groups [43, 44]. On the contrary, the incidence of organ failure at day 7 was similar in our patients with or without de-escalation. There is no obvious explanation for this discrepancy, but medical and surgical patients with sepsis may respond in different ways. The rate of antibiotic escalation, although regularly discussed, is rarely assessed in the literature. In recent papers, this rate has ranged between 6.6 % and 7.9 % [18, 22]. However, Garnacho et al. reported escalation in 19 % of patients despite adequate empiric therapy [4]. The mortality rate in this cohort was significantly increased compared with de-escalation or unchanged therapy (42.9 % versus 27.4 % and 32.6 %, respectively; p = 0.006) [4], while Gonzales et al. reported that escalation did not induce any significant change in prognosis [22]. In these two studies, the heterogeneous case mix resulted in complex analysis of these data. Few studies have reported the frequency and prognosis of escalation in peritonitis, but the effect of escalation appears to be less obvious in the present cohort. Several beneficial effects of de-escalation have been hypothesized, including preservation of the patient’s ecology and decreased emergence of MDR pathogens [3, 45]. However, these assumptions have never been clearly demonstrated. In the present study, we did not observe any significant change in the emergence of resistant pathogens in either the intra-abdominal site or extra-abdominal sites following de-escalation. This is not surprising, as the detection of emerging MDR organisms was not a specific goal of this study and changes of gut microbiota of our patients were not targeted. Similarly, de-escalation does not change the overall duration of therapy. This point, already mentioned in other studies [22], was also observed in our present study. An abundant literature exists regarding assessment of antibiotic de-escalation, but few data are available for antifungal agents. Several reports in candidemia or invasive candidiasis suggest that antifungal de-escalation is feasible [46-48], but no study has specifically addressed the issue of intra-abdominal infections. Unwarranted antifungal prescription is frequently reported in ICU patients, which raises both ecological and financial concerns [49]. De-escalation and/or discontinuation of antifungal treatments could be proposed more frequently. Our data suggest that antifungal de-escalation could be feasible with no specific complications.

Conclusions

De-escalation is a reasonable option, even in patients with polymicrobial infections such as HCIAI. However, MDR bacteria and NFGNB remain major obstacles to implementation of de-escalation. The prescriber must consider whether the determinants of success have been met, especially an adequate empiric therapy. Although our results are reassuring, this strategy needs to be confirmed in a multicenter, randomized, prospective trial.

Key messages

De-escalation is a reasonable option, even in polymicrobial infections such as health care-associated intra-abdominal infections. Multidrug-resistant bacteria and nonfermenting Gram-negative bacilli remain a major obstacle in de-escalation. The key determinants for de-escalation are susceptible microorganisms and adequate empiric therapy.
  46 in total

Review 1.  Hospital-acquired pneumonia and de-escalation of antimicrobial treatment.

Authors:  M H Kollef
Journal:  Crit Care Med       Date:  2001-07       Impact factor: 7.598

Review 2.  Source control in the management of severe sepsis and septic shock: an evidence-based review.

Authors:  John C Marshall; Ronald V Maier; Maria Jimenez; E Patchen Dellinger
Journal:  Crit Care Med       Date:  2004-11       Impact factor: 7.598

3.  The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine.

Authors:  J L Vincent; R Moreno; J Takala; S Willatts; A De Mendonça; H Bruining; C K Reinhart; P M Suter; L G Thijs
Journal:  Intensive Care Med       Date:  1996-07       Impact factor: 17.440

4.  Emergence of antibiotic-resistant bacteria in cases of peritonitis after intraabdominal surgery affects the efficacy of empirical antimicrobial therapy.

Authors:  P Montravers; R Gauzit; C Muller; J P Marmuse; A Fichelle; J M Desmonts
Journal:  Clin Infect Dis       Date:  1996-09       Impact factor: 9.079

5.  Can yeast isolation in peritoneal fluid be predicted in intensive care unit patients with peritonitis?

Authors:  Hervé Dupont; Agnes Bourichon; Catherine Paugam-Burtz; Jean Mantz; Jean-Marie Desmonts
Journal:  Crit Care Med       Date:  2003-03       Impact factor: 7.598

6.  Experience with a clinical guideline for the treatment of ventilator-associated pneumonia.

Authors:  E H Ibrahim; S Ward; G Sherman; R Schaiff; V J Fraser; M H Kollef
Journal:  Crit Care Med       Date:  2001-06       Impact factor: 7.598

7.  Daily organ-system failure for diagnosis of persistent intra-abdominal sepsis after postoperative peritonitis.

Authors:  C Paugam-Burtz; H Dupont; J-P Marmuse; D Chosidow; L Malek; J-M Desmonts; J Mantz
Journal:  Intensive Care Med       Date:  2002-03-15       Impact factor: 17.440

8.  Empirical antimicrobial therapy of septic shock patients: adequacy and impact on the outcome.

Authors:  Marc Leone; Aurélie Bourgoin; Sylvie Cambon; Myriam Dubuc; Jacques Albanèse; Claude Martin
Journal:  Crit Care Med       Date:  2003-02       Impact factor: 7.598

9.  A randomized controlled trial of an antibiotic discontinuation policy for clinically suspected ventilator-associated pneumonia.

Authors:  Scott T Micek; Suzanne Ward; Victoria J Fraser; Marin H Kollef
Journal:  Chest       Date:  2004-05       Impact factor: 9.410

10.  A new Simplified Acute Physiology Score (SAPS II) based on a European/North American multicenter study.

Authors:  J R Le Gall; S Lemeshow; F Saulnier
Journal:  JAMA       Date:  1993 Dec 22-29       Impact factor: 56.272

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  17 in total

1.  Antibiotic duration can be shortened in postoperative intra-abdominal infection.

Authors:  Im-Kyung Kim; Jae Gil Lee
Journal:  J Thorac Dis       Date:  2018-09       Impact factor: 2.895

2.  Short-course antibiotic therapy for critically ill patients treated for postoperative intra-abdominal infection: the DURAPOP randomised clinical trial.

Authors:  Philippe Montravers; Florence Tubach; Thomas Lescot; Benoit Veber; Marina Esposito-Farèse; Philippe Seguin; Catherine Paugam; Alain Lepape; Claude Meistelman; Joel Cousson; Antoine Tesniere; Gaetan Plantefeve; Gilles Blasco; Karim Asehnoune; Samir Jaber; Sigismond Lasocki; Herve Dupont
Journal:  Intensive Care Med       Date:  2018-02-26       Impact factor: 17.440

3.  Antimicrobial de-escalation in critically ill patients: a position statement from a task force of the European Society of Intensive Care Medicine (ESICM) and European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Critically Ill Patients Study Group (ESGCIP).

Authors:  Alexis Tabah; Matteo Bassetti; Marin H Kollef; Jean-Ralph Zahar; José-Artur Paiva; Jean-Francois Timsit; Jason A Roberts; Jeroen Schouten; Helen Giamarellou; Jordi Rello; Jan De Waele; Andrew F Shorr; Marc Leone; Garyphallia Poulakou; Pieter Depuydt; Jose Garnacho-Montero
Journal:  Intensive Care Med       Date:  2019-11-28       Impact factor: 17.440

4.  What every intensivist should know about the management of peritonitis in the intensive care unit.

Authors:  Jan J De Waele
Journal:  Rev Bras Ter Intensiva       Date:  2018-03

Review 5.  WSES/GAIS/SIS-E/WSIS/AAST global clinical pathways for patients with intra-abdominal infections.

Authors:  Massimo Sartelli; Federico Coccolini; Yoram Kluger; Ervis Agastra; Fikri M Abu-Zidan; Ashraf El Sayed Abbas; Luca Ansaloni; Abdulrashid Kayode Adesunkanmi; Boyko Atanasov; Goran Augustin; Miklosh Bala; Oussama Baraket; Suman Baral; Walter L Biffl; Marja A Boermeester; Marco Ceresoli; Elisabetta Cerutti; Osvaldo Chiara; Enrico Cicuttin; Massimo Chiarugi; Raul Coimbra; Elif Colak; Daniela Corsi; Francesco Cortese; Yunfeng Cui; Dimitris Damaskos; Nicola De' Angelis; Samir Delibegovic; Zaza Demetrashvili; Belinda De Simone; Stijn W de Jonge; Sameer Dhingra; Stefano Di Bella; Francesco Di Marzo; Salomone Di Saverio; Agron Dogjani; Therese M Duane; Mushira Abdulaziz Enani; Paola Fugazzola; Joseph M Galante; Mahir Gachabayov; Wagih Ghnnam; George Gkiokas; Carlos Augusto Gomes; Ewen A Griffiths; Timothy C Hardcastle; Andreas Hecker; Torsten Herzog; Syed Mohammad Umar Kabir; Aleksandar Karamarkovic; Vladimir Khokha; Peter K Kim; Jae Il Kim; Andrew W Kirkpatrick; Victor Kong; Renol M Koshy; Igor A Kryvoruchko; Kenji Inaba; Arda Isik; Katia Iskandar; Rao Ivatury; Francesco M Labricciosa; Yeong Yeh Lee; Ari Leppäniemi; Andrey Litvin; Davide Luppi; Gustavo M Machain; Ronald V Maier; Athanasios Marinis; Cristina Marmorale; Sanjay Marwah; Cristian Mesina; Ernest E Moore; Frederick A Moore; Ionut Negoi; Iyiade Olaoye; Carlos A Ordoñez; Mouaqit Ouadii; Andrew B Peitzman; Gennaro Perrone; Manos Pikoulis; Tadeja Pintar; Giuseppe Pipitone; Mauro Podda; Kemal Raşa; Julival Ribeiro; Gabriel Rodrigues; Ines Rubio-Perez; Ibrahima Sall; Norio Sato; Robert G Sawyer; Helmut Segovia Lohse; Gabriele Sganga; Vishal G Shelat; Ian Stephens; Michael Sugrue; Antonio Tarasconi; Joel Noutakdie Tochie; Matti Tolonen; Gia Tomadze; Jan Ulrych; Andras Vereczkei; Bruno Viaggi; Chiara Gurioli; Claudio Casella; Leonardo Pagani; Gian Luca Baiocchi; Fausto Catena
Journal:  World J Emerg Surg       Date:  2021-09-25       Impact factor: 5.469

Review 6.  What's new in multidrug-resistant pathogens in the ICU?

Authors:  Gabor Zilahi; Antonio Artigas; Ignacio Martin-Loeches
Journal:  Ann Intensive Care       Date:  2016-10-06       Impact factor: 6.925

Review 7.  Management of intra-abdominal infections: recommendations by the WSES 2016 consensus conference.

Authors:  Massimo Sartelli; Fausto Catena; Fikri M Abu-Zidan; Luca Ansaloni; Walter L Biffl; Marja A Boermeester; Marco Ceresoli; Osvaldo Chiara; Federico Coccolini; Jan J De Waele; Salomone Di Saverio; Christian Eckmann; Gustavo P Fraga; Maddalena Giannella; Massimo Girardis; Ewen A Griffiths; Jeffry Kashuk; Andrew W Kirkpatrick; Vladimir Khokha; Yoram Kluger; Francesco M Labricciosa; Ari Leppaniemi; Ronald V Maier; Addison K May; Mark Malangoni; Ignacio Martin-Loeches; John Mazuski; Philippe Montravers; Andrew Peitzman; Bruno M Pereira; Tarcisio Reis; Boris Sakakushev; Gabriele Sganga; Kjetil Soreide; Michael Sugrue; Jan Ulrych; Jean-Louis Vincent; Pierluigi Viale; Ernest E Moore
Journal:  World J Emerg Surg       Date:  2017-05-04       Impact factor: 5.469

8.  Clinical characteristics and prognosis of bacteraemia during postoperative intra-abdominal infections.

Authors:  Adel Alqarni; Elie Kantor; Nathalie Grall; Sebastien Tanaka; Nathalie Zappella; Mathieu Godement; Lara Ribeiro-Parenti; Alexy Tran-Dinh; Philippe Montravers
Journal:  Crit Care       Date:  2018-07-07       Impact factor: 9.097

9.  Feasibility of Antimicrobial Stewardship (AMS) in Critical Care Settings: A Multidisciplinary Approach Strategy.

Authors:  Tamas Tiszai-Szucs; Claire Mac Sweeney; Joseph Keaveny; Fernando A Bozza; Zieta O Hagan; Ignacio Martin-Loeches
Journal:  Med Sci (Basel)       Date:  2018-05-25

Review 10.  Antimicrobials: a global alliance for optimizing their rational use in intra-abdominal infections (AGORA).

Authors:  Massimo Sartelli; Dieter G Weber; Etienne Ruppé; Matteo Bassetti; Brian J Wright; Luca Ansaloni; Fausto Catena; Federico Coccolini; Fikri M Abu-Zidan; Raul Coimbra; Ernest E Moore; Frederick A Moore; Ronald V Maier; Jan J De Waele; Andrew W Kirkpatrick; Ewen A Griffiths; Christian Eckmann; Adrian J Brink; John E Mazuski; Addison K May; Rob G Sawyer; Dominik Mertz; Philippe Montravers; Anand Kumar; Jason A Roberts; Jean-Louis Vincent; Richard R Watkins; Warren Lowman; Brad Spellberg; Iain J Abbott; Abdulrashid Kayode Adesunkanmi; Sara Al-Dahir; Majdi N Al-Hasan; Ferdinando Agresta; Asma A Althani; Shamshul Ansari; Rashid Ansumana; Goran Augustin; Miklosh Bala; Zsolt J Balogh; Oussama Baraket; Aneel Bhangu; Marcelo A Beltrán; Michael Bernhard; Walter L Biffl; Marja A Boermeester; Stephen M Brecher; Jill R Cherry-Bukowiec; Otmar R Buyne; Miguel A Cainzos; Kelly A Cairns; Adrian Camacho-Ortiz; Sujith J Chandy; Asri Che Jusoh; Alain Chichom-Mefire; Caroline Colijn; Francesco Corcione; Yunfeng Cui; Daniel Curcio; Samir Delibegovic; Zaza Demetrashvili; Belinda De Simone; Sameer Dhingra; José J Diaz; Isidoro Di Carlo; Angel Dillip; Salomone Di Saverio; Michael P Doyle; Gereltuya Dorj; Agron Dogjani; Hervé Dupont; Soumitra R Eachempati; Mushira Abdulaziz Enani; Valery N Egiev; Mutasim M Elmangory; Paula Ferrada; Joseph R Fitchett; Gustavo P Fraga; Nathalie Guessennd; Helen Giamarellou; Wagih Ghnnam; George Gkiokas; Staphanie R Goldberg; Carlos Augusto Gomes; Harumi Gomi; Manuel Guzmán-Blanco; Mainul Haque; Sonja Hansen; Andreas Hecker; Wolfgang R Heizmann; Torsten Herzog; Adrien Montcho Hodonou; Suk-Kyung Hong; Reinhold Kafka-Ritsch; Lewis J Kaplan; Garima Kapoor; Aleksandar Karamarkovic; Martin G Kees; Jakub Kenig; Ronald Kiguba; Peter K Kim; Yoram Kluger; Vladimir Khokha; Kaoru Koike; Kenneth Y Y Kok; Victory Kong; Matthew C Knox; Kenji Inaba; Arda Isik; Katia Iskandar; Rao R Ivatury; Maurizio Labbate; Francesco M Labricciosa; Pierre-François Laterre; Rifat Latifi; Jae Gil Lee; Young Ran Lee; Marc Leone; Ari Leppaniemi; Yousheng Li; Stephen Y Liang; Tonny Loho; Marc Maegele; Sydney Malama; Hany E Marei; Ignacio Martin-Loeches; Sanjay Marwah; Amos Massele; Michael McFarlane; Renato Bessa Melo; Ionut Negoi; David P Nicolau; Carl Erik Nord; Richard Ofori-Asenso; AbdelKarim H Omari; Carlos A Ordonez; Mouaqit Ouadii; Gerson Alves Pereira Júnior; Diego Piazza; Guntars Pupelis; Timothy Miles Rawson; Miran Rems; Sandro Rizoli; Claudio Rocha; Boris Sakakushev; Miguel Sanchez-Garcia; Norio Sato; Helmut A Segovia Lohse; Gabriele Sganga; Boonying Siribumrungwong; Vishal G Shelat; Kjetil Soreide; Rodolfo Soto; Peep Talving; Jonathan V Tilsed; Jean-Francois Timsit; Gabriel Trueba; Ngo Tat Trung; Jan Ulrych; Harry van Goor; Andras Vereczkei; Ravinder S Vohra; Imtiaz Wani; Waldemar Uhl; Yonghong Xiao; Kuo-Ching Yuan; Sanoop K Zachariah; Jean-Ralph Zahar; Tanya L Zakrison; Antonio Corcione; Rita M Melotti; Claudio Viscoli; Perluigi Viale
Journal:  World J Emerg Surg       Date:  2016-07-15       Impact factor: 5.469

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