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(Chest. 2003;123:2034-2042.)
© 2003 American College of Chest Physicians

Hospital-Acquired Pneumonia*

Risk Factors for Antimicrobial-Resistant Causative Pathogens in Critically Ill Patients

Olivier Leroy, MD; Sandrine Jaffré, MD; Thibaud d’Escrivan, MD; Patrick Devos; Hugues Georges, MD; Serge Alfandari, MD and Gilles Beaucaire, MD

* From the Service de Réanimation Médicale et Maladies Infectieuses (Drs. Leroy, Jaffré, d’Escrivan, Georges, Alfandari, and Beaucaire), Université de Lille, Center Hospitalier, Tourcoing; and Department of Biostatistics (Mr. Devos), Centre Hospitalier Régional Universitaire, Lille, France.

Correspondence to: Olivier Leroy, MD, Service de Réanimation Médicale et Maladies Infectieuses, Hôpital G. Chatilliez 135 rue du Président Coty, 59208 Tourcoing, France; e-mail: oyleroy{at}caramail.com


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Study objectives: To determine factors associated with antimicrobial-resistant hospital-acquired pneumonia (AR-HAP), to build an algorithm evaluating the risk for such a pneumonia, and to test this algorithm.

Design: Combined observational and validation cohorts over two periods: January 1994 to December 1999, and January 2000 to March 2001.

Setting: One ICU from a university-affiliated urban teaching hospital.

Patients: One hundred twenty-four patients in the observational cohort and 26 patients in the validation cohort exhibiting bacteriologically documented hospital-acquired pneumonia (HAP).

Interventions: Prospective data collection and multivariate analysis using the {chi}2 automatic interaction and detection technique.

Results: In the observational cohort, 39 antimicrobial-resistant bacteria were incriminated in 37 patients (30%). Multivariate analysis identified four independent variables allowing a binary stratification of risk. According to the presence or absence of prior antimicrobial treatment, neurologic disturbances on ICU admission, aspiration on ICU admission, and time elapsed between ICU admission and the onset of pneumonia, we were able to identify and separate patients at high, low, or even no risk for acquiring AR-HAP. In the validation cohort, nine antimicrobial-resistant bacteria were incriminated in nine patients (34.6%). In this cohort, the algorithm performed well allowing the identification of null risk categories: the absence of prior antimicrobial treatment, the presence of prior antimicrobial treatment with neurologic disturbances on ICU admission and an early-onset pneumonia, and the presence of prior antimicrobial treatment without neurologic disturbances but with aspiration on ICU admission were always associated with antimicrobial-susceptible HAP.

Conclusion: We developed and tested a binary algorithm allowing the identification of patients at low risk for acquiring AR-HAP. An antibiotic strategy including an initial antimicrobial treatment guided by such an algorithm, followed, if possible, by a de-escalation when antimicrobial data are available, could increase the administration of adequate initial antimicrobial treatment and help prevent the emergence of antibiotic resistance in the ICU.

Key Words: antimicrobial resistance • antimicrobial therapy • hospital-acquired pneumonia • ICU • pneumonia


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
Hospital-acquired pneumonia (HAP) remains the most frequent and the most severe nosocomial infection encountered in the ICU. Although mortality rates associated with HAP vary widely among studies and the precise prognostic impact of HAP on patient outcome is still debated, it is currently admitted that one third to one half of all HAP deaths are directly attributable to the infection.1 2 3 4 5 6 7 8 9

As demonstrated by several authors, inadequacy of initial empiric antibiotic treatment is closely correlated with high in-hospital mortality rates for patients with ventilator-associated pneumonia (VAP).10 11 Recently, Kollef and Fraser12 underlined that the most usual explanation of this inadequacy was the resistance of causative bacteria to the prescribed antibiotics.

Therefore, as a future prospect, the most pertinent way to decrease the incidence of inadequate antimicrobial treatment is to develop strategies to reduce the emergence of antibiotic-resistant pathogens in the ICU and other hospital wards.12 However, in the meantime, physicians must still use methods to optimize the empirical choice of antimicrobial treatment. Among strategies reducing the frequency of inadequate antibiotic prescriptions, those studying local patterns of antimicrobial resistance, evaluating risk factors of antimicrobial-resistant causative organisms, and providing means to adapt guidelines for antimicrobial therapy, at a local level, appear relevant.12 13

The main objective of the present work was to determine factors associated with antimicrobial-resistant HAP (AR-HAP) and to build an algorithm evaluating the risk for such a HAP in an observational cohort. The secondary objective was to prospectively test this algorithm in a validation cohort.


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Study Location and Selection of Patients
The study was conducted in the Service de Réanimation Médicale et Maladies Infectieuses of Lille University from January 1994 to March 2001. All patients admitted into our ICU for HAP or exhibiting HAP during their ICU stay were enrolled over this period.

Patients enrolled from January 1994 to December 1999 constituted our observational cohort. Those included from January 2000 to March 2001 constituted our validation cohort.

HAP was considered to be present when new and/or progressive chest radiographic infiltrates occurred ≥ 48 h after hospital admission, in conjunction with at least two of the following criteria: purulent respiratory secretions, temperature > 38.5°C or < 35°C, and leukocyte count > 10,000/µL or < 1,500/µL. Only patients exhibiting a bacteriologically documented HAP were studied; establishment of etiologic diagnosis required isolation of bacteria in significant quantity from a sample of lower respiratory tract secretions (endotracheal aspiration > 106 cfu/mL, protected brush catheter > 103 cfu/mL, or BAL > 104 cfu/mL) or isolation of a definitive pathogen from a blood or pleural fluid culture. These latter cultures were considered significant when the same organism as recovered from the sample of respiratory secretions was identified.

Development of the Algorithm Evaluating the Risk for Acquiring AR-HAP (Observational Cohort)
Patient Evaluation, Data Collection, and Definition of Variables: For all study patients, the following characteristics were prospectively collected on ICU admission: age, gender, underlying clinical conditions, nutritional status assessed by serum protein and albumin levels, indication(s) for ICU admission, and severity of illness and vital sign abnormalities. The underlying clinical conditions were classified according to the criteria proposed by McCabe and Jackson14 in three categories: nonfatal, ultimately fatal, and rapidly fatal. Severity of illness was assessed by simplified acute physiology score (SAPS)-II and the acute organ system failure (OSF) scoring system.15 16 Neurologic and mental status were stratified according to Glasgow coma scale score.17

Potential risk factors for the development of HAP were recorded and classified as patient related, procedure related, or drug related. The following characteristics were considered as patient-related risks of HAP: immunosuppression, chronic respiratory insufficiency, chronic neurologic diseases, and aspiration. Procedure-related HAP risk factors were endotracheal tube placement, number of endotracheal tube changes, surgical tracheostomy, nasogastric tube placement, invasive monitoring of BPs (radial artery and/or pulmonary artery catheters), hemodialysis or hemofiltration, and invasive or noninvasive mechanical ventilation (MV). The following therapeutic measures instituted during the ICU stay and prior to the occurrence of HAP were considered as drug-related risk factors: antiacid or histamine type-2 receptor antagonists or omeprazole, sedative drugs, corticosteroids, and inotropic drugs. All antimicrobial agents instituted within 1 month prior to HAP occurrence, except those used as prophylactic antibiotics during surgical procedures, were also considered as drug-related risk factors. When HAP occurred, we recorded its time of onset from hospital admission, ICU admission, and start of MV.

Immunosuppression was defined as a leukocyte count < 1.000/µL, recent use of systemic corticosteroids (> 10 mg/d of prednisone or equivalent for > 2 weeks), underlying malignancy, cytotoxic drugs, radiation treatment, or asplenia. On ICU admission, aspiration was considered to be present when it was observed or when patient exhibited situations predisposing to aspiration (ie, depressed cough and gag reflexes, emesis related to ileus, gastric dilatation or intestinal obstruction, depressed consciousness, seizures, dysphagia, esophageal disease).18 Chronic respiratory insufficiency was considered to be present when the patient exhibited COPD or restrictive lung disease or both. COPD was diagnosed using the standard criteria (clinical assessment, chest radiographic examination, and pulmonary function tests) recommended by the American Thoracic Society.19 Restrictive lung diseases (neuromuscular disease, kyphoscoliosis, tuberculosis sequelae, pneumoconiosis, and fibrosis) were assessed according to spirometric parameters when FVC was < 55% and FEV1 > 60% of the predicted values. Shock was defined as a sustained (≥ 1 h) decrease in the systolic BP of at least 40 mm Hg from baseline or a resultant systolic BP < 90 mm Hg after adequate fluid replacement and in the absence of any antihypertensive drug.20

Factors Associated With AR-HAP: In each HAP episode, all significant isolates were identified by standard laboratory techniques. For each pathogen, its antimicrobial susceptibility was studied. Criteria proposed by the Comité de l’Antibiogramme de la Société Française de Microbiologie were used.21 The following pathogens were considered as antimicrobial-resistant bacteria: penicillin-resistant Streptococcus pneumoniae, methicillin-resistant Staphylococcus sp., ticarcillin-resistant Pseudomonas aeruginosa, and extended spectrum ß-lactamase (ESBL) producing Enterobacteriaceae. All Stenotrophomonas maltophilia and Acinetobacter sp. were considered as antimicrobial-resistant bacteria whatever their antimicrobial susceptibilities. The remaining pathogens were considered antimicrobial susceptible. HAP episode was considered to be antimicrobial-resistant related when one or more of such organisms grew at significant concentrations from a sample of lower respiratory tract secretions.

To determine risk factors associated with AR-HAP, we compared the characteristics of patients exhibiting such an episode of HAP with those found in patients with HAP due to antimicrobial-susceptible bacteria. All variables previously described were compared in the two groups.

Statistical Analysis and Development of the Algorithm Evaluating the Risk for Acquiring AR-HAP
All collected variables were included in univariate analyses. Continuous variables were compared using the Student t test or Mann-Whitney test according to the sample size. Categorical variables were compared using {chi}2 test or Fisher exact test when {chi}2 was not appropriate. When appropriate, some continuous variables were analyzed as categorical variables after determination of a cut-off using receiver operating characteristic (ROC) analysis. Differences between groups were considered to be significant for variables yielding a p value ≤ 0.05.

To build an algorithm stratifying the risk that an episode of HAP was due to antimicrobial-resistant causative pathogen(s), all variables attaining a value of 0.05 were included in a multivariate analysis with the {chi}2 automatic interaction and detection technique.22 All statistical analyses were performed using the SAS software (Version 8.2; SAS Institute; Cary, NC).

Validation of the Algorithm Evaluating the Risk for Acquiring AR-HAP (Validation Cohort)
A prospective evaluation of the algorithm was performed using a separate set of patients. Between January 2000 and March 2001, all patients admitted into our ICU for HAP or exhibiting HAP during their ICU stay were enrolled in a validation cohort.

Patient evaluation and data collection were carried out in the same manner as in the observational cohort. Main patient characteristics in the two cohorts were compared, and the performance of the algorithm was tested in the validation cohort.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Observational Cohort
Patient Characteristics: During the study period, 172 episodes of HAP were collected. One or more causative pathogens were identified in 124 episodes that constituted our observational cohort.

Mean ± SD patient age was 64.4 ± 13.6 years; there were 89 men and 35 women. Indications for ICU admission and parameters assessing the severity of illnesses on ICU admission are reported in Table 1 . One hundred fifty-four causative pathogens were isolated (Table 2 ). Among them, 39 pathogens were antimicrobial-resistant bacteria, which were incriminated in 37 episodes of HAP (30%). They were methicillin-resistant Staphylococcus (n = 11), Acinetobacter species (n = 9), S maltophilia (n = 8), ticarcillin-resistant P aeruginosa (n = 5), ESBL-producing Enterobacteriaceae (n = 4), and penicillin-resistant S pneumoniae (n = 2). Main risk factors for the development of HAP, classified as patient related, procedure related, or drug related, and characteristics of patients at the onset of HAP are summarized in Table 3 .


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  		Table 1.. Main Characteristics of Patients in the Observational and Validation Cohorts*

 

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  		Table 2.. Bacteriologic Data in the Observational and Validation Cohorts of HAP*

 

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  		Table 3.. Main Risk Factors for the Development of HAP and Characteristics of Patients at the Onset of HAP*

 
Risk Factors of AR-HAP Episode: Data comparing characteristics of patients with AR-HAP (n = 37) with those found in patients with antimicrobial-susceptible HAP (n = 87) are reported in Tables 4 5 6 . On ICU admission, age, sex ratio, underlying diseases. stratified according to McCabe and Jackson14 classification, nutritional status, severity of illness evaluated by SAPS-II, Glasgow coma scale score, and OSF scoring were similar in both groups(Table 4) . The only difference was observed among ICU admission indications. In patients having an episode of antimicrobial-susceptible HAP, the frequency of neurologic disturbances as an indication for ICU admission was significantly higher than in the other group (25.3% vs 16.2%, respectively; p = 0.05). Analysis of variables usually considered as risk factors for development of HAP revealed that incidence of aspiration (19.5% vs 5.4%) and reintubation (26.4% vs 13.5%) were significantly higher in patients with antimicrobial-susceptible HAP (Table 5) . Conversely, incidence of tracheostomy (13.5% vs 3.4%), nasogastric tube use (91.9% vs 77%), invasive monitoring of BP (29.7% vs 10.3%), and prior antimicrobial therapy (89.2 vs 65.5%) were significantly higher in patients exhibiting AR-HAP (Table 5) . When HAP occurred, the number of days elapsed from hospital admission, ICU admission, or start of invasive MV to HAP onset were significantly higher in patients with AR-HAP (Table 6) . According to ROC analyses, the time cutoff for ICU admission to HAP onset and for duration of MV separating AR-HAP and antimicrobial-susceptible HAP were as follows: a duration from ICU admission to HAP onset > 8 days and a duration of MV > 6 days. Both were significantly associated in univariate analysis with AR-HAP.


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  		Table 4.. Risk Factors for AR-HAP According to the Characteristics of Patients on ICU Admission (Observational Cohort)*

 

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  		Table 5.. Risk Factors for AR-HAP According to Potential Risk Factors for the Development of HAP (Observational Cohort)*

 

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  		Table 6.. Risk Factors for AR-HAP According to the Characteristics of Patients at the Onset of HAP (Observational Cohort)*

 
Multivariate Analysis: According to the {chi}2 automatic interaction and detection technique, multivariate analysis of factors associated with episodes of AR-HAP revealed that four independent variables allowed a binary stratification of risk. This algorithm is reported in Figure 1 . The variable used in the first step was "previous antimicrobial treatment." In the absence of previous antimicrobial treatment, 12% of our study patients exhibited AR-HAP. In the presence of previous antimicrobial treatment, the overall incidence of AR-HAP reached 37%. In patients with previous antimicrobial treatment, the risk factor evaluated in the second step, was the "presence or absence of neurologic disturbances on ICU admission." When such a risk factor was present, the overall incidence of AR-HAP was 21%, but varied according to a final third step. In this group of patients exhibiting neurologic disturbances on ICU admission, this final step was the "time elapsed between ICU admission and the onset of HAP." When it was < 8 days or > 8 days, the incidence of AR-HAP was 0% or 36%, respectively. In patients with previous antimicrobial treatment and without neurologic disturbances on ICU admission, the overall incidence of AR-HAP was 42%. The third step allowing final evaluation was "aspiration on ICU admission." According to the presence or the absence of this factor, the incidence of AR-HAP was 0% or 46%, respectively.



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  		Figure 1.. Algorithm evaluating the incidence of AR-HAP in the observational cohort.

 
Validation Cohort
From January 2000 to March 2001, 31 episodes of HAP were collected. One or more causative organisms were identified in 26 episodes that constituted our validation cohort.

There were 21 men and 5 women; mean ± SD age was 63.8 ± 15.7 years. Data concerning severity of illnesses on ICU admission and indications for ICU admission are summarized in Table 1 . A total of 33 pathogens were isolated in 26 patients (Table 2) . In nine cases (34.6%), HAP was considered antimicrobial resistant. The nine antimicrobial-resistant causative organisms were S maltophilia (n = 4), ticarcillin-resistant P aeruginosa (n = 2), ESBL-producing Enterobacteriaceae (n = 2), and methicillin-resistant Staphylococcus aureus (n = 1). Risk factors for the development of HAP and characteristics of patients at the onset of HAP are reported in Table 3 .

When characteristics of patients included in this cohort were compared with those of patients included in the observational cohort (Tables 1 2 3) , there were only few statistically significant differences. In the validation cohort, mean albumin concentration on ICU admission was higher (30.6 ± 6.4 g/L vs 21.3 ± 7.2 g/L, p = 0.03) and prevention of GI bleeding during ICU stay was less frequent used (13 of 26 patients vs 94 of 124 patients, p = 0.008). Finally, it seems important to underline that there was no significant difference concerning the number of episodes of HAP due to antimicrobial-resistant pathogens (9 of 26 episodes vs 37 of 124 episodes, p = 0.63) and in main causative pathogens such as Staphylococcus species (5 of 33 episodes vs 30 of 154 episodes, p = 0.74) or P aeruginosa (12 of 33 episodes vs 48 of 154 episodes, p = 0.56).

The algorithm evaluating the incidence of AR-HAP applied in this cohort is reported in Figure 2 . In this cohort, the algorithm appeared to perform well in stratifying patients with low risk of acquiring AR-HAP since it was able to identify three groups of patients exhibiting antimicrobial-susceptible HAP. All patients with HAP without prior antimicrobial treatment (n = 5) and patients with HAP with prior antimicrobial treatment and either exhibiting neurologic disturbances on ICU admission and an early onset HAP (n = 1) or aspiration on ICU admission without neurologic disturbances (n = 2) had antimicrobial-susceptible HAP.



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  		Figure 2.. Algorithm applied to the validation cohort.

 

   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
Our study demonstrates that the risk for acquiring AR-HAP could be stratified according to four independent factors. The algorithm developed in the observational cohort performed well in the validation cohort since all patients with antimicrobial-susceptible HAP were identified. In this cohort, the risk for acquiring MR-HAP was null in the following: (1) the absence of prior antimicrobial treatment, (2) the presence of prior antimicrobial treatment associated with neurologic disturbances on ICU admission and early-onset HAP, and (3) the presence of prior antimicrobial treatment without neurologic disturbances but with aspiration on ICU admission.

Numerous factors predisposing to AR-HAP have been previously identified. Prior use of antimicrobial agent appears as one of the most important items. Trouillet and coworkers23 demonstrated a close correlation between previous use of broad-spectrum antimicrobial agents and potential development of AR-VAP. Similarly, Rello and coworkers24 25 26 found that risks for VAP due to P aeruginosa or methicillin-resistant S aureus were more important in patients who previously received antibiotics. Prolonged length of hospital stay, presence of invasive devices, duration of MV > 7 days, and underlying patient condition (COPD, neurosurgery, large-volume aspiration, head trauma) have also been correlated with occurrence of VAP due to potentially-resistant bacteria or to pathogens such as P aeruginosa or Acinetobacter baumannii.23 25 27 In our study, the major role played by previous antimicrobial treatment must be emphasized since it was the first risk factor used in our binary algorithm. Our study also underlines that factors such as indications for ICU admission, presence or absence of aspiration on ICU admission, and time between ICU admission and HAP onset influence the risk for acquiring AR-HAP. These results raise several issues. Rello and coworkers26 28 demonstrated that coma was an independent risk factor for S aureus HAP and that patients exhibiting oxacillin-susceptible S aureus VAP were more likely than patients with methicillin-resistant S aureus VAP to have cranioencephalic trauma. Because the presence of neurologic disturbances on ICU admission decreased in our series, the risk for acquiring AR-HAP could be considered in accordance with the results of Rello et al.26 28 A duration between ICU admission and HAP onset > 8 days was, in our study, an independent risk factor for AR-HAP. A recent article published by a European task force on VAP29 underlined that definitions of early-onset and late-onset pneumonia remained an unresolved issue, and that it was uncertain whether the threshold referred to the number of days in hospital or the number of days following intubation. In our series, univariate analysis demonstrates that time elapsed from hospital admission, ICU admission and intubation, and occurrence of HAP were significantly different in patients with antimicrobial-susceptible HAP or AR-HAP. Durations were longer in AR-HAP. According to ROC analyses, a number of days in ICU > 8 and a number of days following intubation > 6 were significantly associated with AR-HAP. In multivariate analysis, the independent risk factor for such an HAP was a number of days in ICU > 8. Finally, we found that aspiration on ICU admission was associated with the occurrence of antimicrobial-susceptible HAP. However, we must notice that Baraibar and coworkers27 found that large-volume aspiration was an independent risk factor for A baumannii VAP. In our opinion, such a discrepancy could be explained by the inclusion in the study of Baraibar et al27 of patients with cranial and/or multiple trauma and the absence of such patients in our study. Nevertheless, we must underline that such a risk factor was observed for patients previously treated with antibiotics and exempt from neurologic disturbances on ICU admission.

Actually, the goal of our study was more to build, according to a binary distribution, an algorithm stratifying the risk for acquiring AR-HAP than to identify all independent risk factors for such an HAP. According to this algorithm, we were able to identify and discriminate patients exhibiting high, low, or even no risk. In the observational cohort, 33 of 37 patients exhibiting AR-HAP were correctly classified in high-risk groups. In the validation cohort, nine of nine patients with AR-HAP were also correctly classified in high-risk groups. However, 42 of 75 patients in the observational cohort and 9 of 18 patients in the validation cohort were considered as high risk but exhibited antimicrobial-susceptible HAP. Despite this misclassification, we consider that this algorithm could be useful to increase the likelihood of initial antimicrobial therapy adequacy for HAP and to reduce the emergence of antibiotic resistance in ICU. For patients classified in high-risk groups for acquiring AR-HAP, the use of broad-spectrum ß-lactam combined with aminoglycoside or ciprofloxacin and with vancomycin should be required. In our series, such combinations could have been used for 75 of 124 patients (60%) in the observational cohort and for 18 of 26 patients (69%) in the validation cohort. As suggested by Kollef,30 this broad-spectrum empiric therapy should always be modified and, if possible, narrowed when initial culture results become available. For patients considered at low risk for AR-HAP, initial empiric antimicrobial therapy should be quite different. The most striking point is the uselessness of vancomycin therapy for such patients since the risk of methicillin-resistant S aureus HAP is low or null. In our study, antimicrobial therapy without vancomycin could have been used for 49 of 124 patients (39.5%) and 8 of 26 patients (30.8%) in the two cohorts, respectively. To summarize, our algorithm could have led, in the observational cohort, to broad-spectrum antimicrobial treatment, including vancomycin, for 75 patients (60.5%) and to avoid the use of vancomycin for 49 patients (39.5%). In the validation cohort, they would have been 18 patients (69.2%) and 8 patients (30.8%), respectively. The emergence of vancomycin-resistant strains, potentially favored by an excessive use of glycopeptide, represents a major problem in the ICU.31 32 As previously discussed, Rello and coworkers26 demonstrated that a previous antimicrobial treatment increased the risk for acquiring VAP due to methicillin-resistant S aureus. Consequently, it could lead numerous physicians to use vancomycin for empiric therapy of such patients. Thus, our algorithm allows a decrease in unnecessary prescription of vancomycin even in patients previously treated with antimicrobial agents (15 of 90 patients in the observational cohort and 3 of 21 patients in the validation cohort). Therefore, an antibiotic strategy including initial antimicrobial treatment based on such an algorithm and, if possible, a de-escalation once the HAP causative agent is identified could increase the initial administration of adequate antimicrobial treatment and help prevent the emergence of antibiotic resistance.

Numerous limitations of our study must be addressed. First, one method used to assess the etiologic diagnosis was endotracheal aspiration with quantitative culture. As recent recommendations underline that quantitative procedures based on nonbronchoscopic or bronchoscopic techniques exhibit similar sensitivities, specificities, and positive predictive values, this point could not be considered as a limitation.33 Second, among Gram-negative bacilli, only ticarcillin-resistant P aeruginosa, ESBL-producing Enterobacteriaceae, S maltophilia, and Acinetobacter sp. were considered as antimicrobial-resistant bacteria. The resistance to fluoroquinolones, per se, was not taken into account. Third, our results might only be significant concerning our unit. Numerous studies have demonstrated that HAP causative organisms varied widely from one site to another.34 However, in a recent review performed by a European Task Force on VAP, the experts underlined that:

it is imperative that investigators from different countries and regions exchange precise and updated epidemiologic data on VAP. To do that, every ICU is encouraged to provide these data, thereby enabling comparisons of microbial and susceptibility patterns.29

Moreover, Kollef and Fraser12 suggest that "guidelines for antimicrobial therapy will need to be modified at the local level to take into account local patterns of antimicrobial resistance." Consequently, despite our relatively small sample, this study, contributing in our ICU to develop more rational prescription strategies that can reduce the unnecessary administration of broad-spectrum agents such as vancomycin and avoid inadequate antibiotic treatment for patients with HAP, is in accordance with such recommendations.

In summary, we developed in an observational cohort a binary algorithm identifying patients at low risk for acquiring AR-HAP. Such an algorithm performed well in a validation cohort. An antibiotic strategy including an initial antimicrobial treatment guided by such an algorithm and, if possible, followed by a de-escalation when antimicrobial data are available could increase the administration of adequate initial antimicrobial treatment and help prevent the emergence of antibiotic resistance in the ICU. Of course, a prospective validation in our ICU of such an algorithm in a large-scale study is required, as well as future adaptations guided by modifications of our local epidemiology.


   Footnotes
 
Abbreviations: AR-HAP = antimicrobial-resistant hospital-acquired pneumonia; ESBL = extended-spectrum ß-lactamase; HAP = hospital-acquired pneumonia; MV = mechanical ventilation; OSF = organ system failure; ROC = receiver operating characteristic; SAPS = simplified acute physiology score; VAP = ventilator-associated pneumonia

Received for publication April 15, 2002. Accepted for publication August 27, 2002.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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