The Intensive Care Unit, Part A: HAI Epidemiology, Risk Factors, Surveillance, Engineering and Administrative Infection Control Practices, and Impact

The Intensive Care Unit, Part A: HAI Epidemiology, Risk Factors, Surveillance, Engineering and Administrative Infection Control Practices, and Impact

Didier Pittet

Caroline Landelle

Stephan A. Harbarth

The care of critically ill patients in special high-technology units is a primary component of modern medicine, although the efficacy and long-term benefit of critical care has not been established for all medical conditions (1). Invasive diagnostic and therapeutic procedures are essential for the diagnosis and treatment of critically ill patients. However, life support systems disrupt normal host defense mechanisms, affecting patients with already impaired immune response. Given the severity of the illnesses affecting patients in intensive care units (ICUs), it is not surprising that mortality rates can exceed 25% (2,3). In addition, more than one third of the patients admitted to ICUs experience unexpected complications of medical care (4). Healthcare-associated infection (HAI) is one of the most common medical complications affecting patients in ICUs. Although ICUs make up only 5% to 10% of hospital beds, infections acquired in these units account for >20% of all HAIs (5). Fortunately, systematic studies of the determinants of HAIs, surveillance for infections, and adherence to protocols for preventing infections have been effective in reducing the risk for patients admitted to ICUs.



The dynamics of ICU-acquired HAIs are complex and depend on the contribution of the host’s underlying conditions, the infectious agents, and the unique environment of the ICU. The following discussion will consider the role of each component in the development of HAI.

Host Defenses

The ability of patients in ICUs to ward off infections is seriously compromised. Natural host defense mechanisms might be impaired by underlying diseases or as a result of medical and surgical interventions. All patients admitted to an ICU will have at least one, and often several, indwelling devices that break the normal skin barriers and establish direct access between the external environment and normally sterile body sites. Natural chemical barriers in the stomach are neutralized by administering H2-blockers or antacids that reduce acidity and allow growth of enteric flora. Physiologic mechanisms for evacuating and cleansing hollow organs are disrupted and circumvented by insertion of endotracheal tubes, nasogastric tubes, and urinary catheters.

Specific host defense mechanisms also might be impaired by the underlying diseases. Patients with malignant disorders might have abnormal immune responses as a result of their disease or stemming from therapies that diminish the number of effective phagocyte cells and blunt the normal immune response. Patients admitted to ICUs who are at the extremes of age exhibit selected impairments in natural and specific defense mechanisms that increase the HAI risk (6,7). A historical cohort study from Belgium revealed, however, that the incidence of healthcare-associated bloodstream infection (BSI) was lower among very old ICU patients when compared to middle-aged and old patients. Yet, the adverse impact of this HAI was higher in very old patients (8).

Because of the precarious condition of patients in the ICU, normal food intake often is suspended, leading to under- or malnutrition (9). Injured tissue, perfusion deficits, and infection cause fever and tachycardia through mechanisms mediated by hormones and cytokines, such as endotoxin. The physiologic response to these mediators is an increase in oxygen consumption stemming from an increase in metabolic demand. This response results in breakdown of muscle to meet the body’s demand for energy. The lean body mass declines, resulting in deficits in substrates necessary for recovery (10).

Under-nutrition has been associated with increased complication rates and delayed wound healing (11,12). Several studies suggest that poor nutritional status is a predisposing factor for HAIs (13,14,15). Recent studies have confirmed that the use of enteral nutrition vs. total parenteral nutrition (TPN), early initiation of enteral nutrition, and use of enteral and parenteral glutamine are all associated with reduced infectious morbidity in critically ill patients (16,17,18). For instance, early or glutamineenriched enteral nutrition in critically ill patients has been reported to decrease HAIs and other complications (19,20). Conversely, a meta-analysis including 26 studies which examined the relationship between TPN and mortality rates in critically ill
patients showed that TPN had no effect on mortality and only lowered complication rates in malnourished patients (21). In a meta-analysis of trials comparing enteral nutrition to TPN in ICU patients, Simpson et al. reported that TPN was even associated with an increase in infectious complications (odds ratio [OR] = 1.47; 95% confidence interval [CI] = 0.90 to 2.38) (22). Two other recent meta-analyses reported negative findings. In their systematic review, Peter et al. reported no mortality effect with the type of nutritional supplementation, although early enteral nutrition significantly reduced complication rates (23). Ho et al. performed a meta-analysis, comparing early gastric and postpyloric feeding in critically ill patients and concluded that early use of postpyloric feeding instead of gastric feeding in ICU patients with no evidence of impaired gastric emptying was not associated with significant clinical benefits (24).

Important alterations in T- and B-cell function affecting host defense and resistance to infection are found in critically ill and traumatized patients (25). Alterations in T-cell activation and cytokine production are frequently associated with trauma and hemorrhage. Injury and blood loss result in activation of CD8 T-cell populations capable of altering bacterial antigen-specific B-cell repertoires and suppressing the function of other T cells.

Systemic hypoxia and hypovolemia also are significant contributors to the development of infection. However, significant changes in perioperative care have been introduced in recent years (26,27). The maintenance or restoration of normal physiologic characteristics after surgery becomes the key to preventing complications (28).

Medical Devices

The results of the first European Prevalence of Infection in Intensive Care (EPIC) study (29) highlighted the relative importance of medical devices as risk factors for infections compared with other factors. Factors were collected from >10,000 ICU patients, of whom 2,064 had ICU-acquired infections. Among the seven independent risk factors identified, four were associated with medical devices commonly used in intensive care: central venous catheter (CVC) (OR = 1.35, 95% CI = 1.60 to 1.57), pulmonary artery catheter (OR = 1.20, 95% CI = 1.01 to 1.43), urinary catheter (OR = 1.41, 95% CI = 1.19 to 1.69), and mechanical ventilation (OR = 1.75, 95% CI = 1.51 to 2.03). Other independent risk factors for ICU-acquired infections were stress ulcer prophylaxis (OR = 1.38, 95% CI = 1.20 to 1.60), the presence of trauma on admission (OR = 2.07, 95% CI = 1.75 to 2.44), and the length of ICU stay. The latter constituted the strongest predictor of infection and showed a linear increase in the odds for infection with time spent in the ICU (29). This finding also was confirmed by the second international study of the prevalence and outcomes of infection in ICUs, published in 2009 (2).

Figure 24.1. Kaplan-Meier survival curve of a nonuniform hazard for the development of bloodstream infection (BSI) beginning with all patients (cumulative survival, 1.00) free of BSI. By day 5, 99% of the patients remained free of BSI. By day 16, 94% remained free of BSI. CVL, central venous catheter. (Adapted from McLaws ML, Berry G. Nonuniform risk of bloodstream infection with increasing central venous catheter-days. Infect Control Hospital Epidemiol. 2005;26:715-719, with permission.)

In another interesting cohort study (30), McLaws and Berry analyzed the rate for CVC-associated BSI in 1,375 patients who were monitored for 7,467 days of CVC use. They found significant differences in the BSI rate depending on the length of catheterization (Figure 24.1). The probability of BSI with a CVC in place was 6% by day 15, 14% by day 25, 21% by day 30, and 53% by day 320. Thus, the risk of infection is not homogenous, but increases substantially after prolonged CVC-insertion (>2 weeks).

Underlying Diseases

ICUs, by design, serve patients with severe illnesses that compromise host defense. Each patient must be assessed individually to determine how the underlying illness might interfere with host defense mechanisms. A simple assessment of the severity of underlying illness was developed five decades ago by McCabe and Jackson (31), who stratified patients according
to whether the underlying disease was fatal, ultimately fatal, or nonfatal. Subsequent studies by Britt and colleagues (32) have demonstrated the utility of this simple assessment for estimating the risk of nosocomial BSI. Numerous other studies have found increasing rates of infections among patients with more severe illness (33,34).

Although McCabe’s classification has been useful, it was not designed to assess patients admitted to ICUs. Therefore, several severity-of-illness scoring systems have been proposed to estimate a patient’s risk of death in ICUs objectively. Great progress has been observed in the last 10 years in the accuracy of statistical models to assess critically ill patients and predict survival (35,36). Customized or modified versions of the most frequently used scoring systems (e.g., simplified acute physiology score [SAPS] III; Acute Physiology, Age, and Chronic Health Evaluation [APACHE] III) have been proposed to obtain satisfactory estimates of the probability of death in ICU patients, which depends on the severity of illness, the number of acute organ failures, and the characteristics of underlying disease (37,38,39,40). Nevertheless, limitations persist about the capacity of these scoring systems to integrate differences in overall quality of care (41). Moreover, older versions of these scores, which were developed in the early 1990s, have shown a decline in predictive accuracy as the models age. Therefore, mortality tends to get overpredicted when older models are applied to more contemporary data, which in turn leads to biased benchmarking data of different ICUs (42). Thus, care should be applied when using outdated severity scoring models to contemporary populations.

A group of critical care physicians developed, by consensus, the so-called “Sepsis-Related Organ Failure Assessment” (SOFA) score in 1994, a severity scoring system that targets septic patients (43). Since the score is not specific for sepsis, it was later called “Sequential Organ Failure Assessment.” The SOFA score is composed of scores from six organ systems, graded from 0 to 4 according to the degree of dysfunction. While primarily designed to describe morbidity, several analyses showed a relationship between the SOFA score and mortality and indicated also a good distribution of patients among the different score values (44).

Antimicrobial Usage and Selection Pressure

Different types of epidemiological studies have been used to quantify the association between antibiotic exposure and resistance in critically ill patients (45,46,47,48,49). These studies included outbreak reports, laboratory-based surveys, randomized trials, and prospective or retrospective cohort studies based on analyses of individual-patient-level data or aggregated data. The different methodological approaches are not mutually transposable, and the lack of uniformity makes the comparison of different studies difficult. For instance, the analysis of aggregated data may be limited by “ecologic bias,” which is the failure of group-level-effect estimates to reflect the biological effect of antibiotic use at the individual-patient level (45). This bias is a result of the fact that, unlike individual-level studies, ecologic studies do not link individual outcome events to individual antibiotic exposure histories. Notwithstanding these difficulties, the majority of studies confirm that large differences exist in the pattern of antimicrobial usage and antimicrobial resistance, between different hospitals and ICUs. Usage of antimicrobials may show important variations between institutions facing similar prevalences of highly resistant organisms, confirming that efforts to control resistance should focus on both antimicrobial use and infection control practices (50,51,52).

In ICUs, where antibiotics are used more frequently and in larger amounts than in almost any other unit in the hospital, antimicrobial resistance ensures the survival of some nosocomial pathogens (53). The close proximity of patients facilitates transfer of resistant organisms from patient to patient (54). However, the high prevalence of carriage of multidrug-resistant microorganisms does not automatically translate into higher overall HAI rates in the concerned services (55,56).

It is noteworthy that trends in the pathogens responsible for HAIs in the ICU have shown an increase in infections due to multiply-resistant gram-negative bacteria (e.g., Enterobacter spp., Acinetobacter baumannii) and fungi such as Candida spp. (2). The emergence of these pathogens is due, at least in part, to patterns of antibiotic use and selection pressure and to the development of antibiotic resistance among these isolates (57). In a multicenter study by Meyer et al.(48) performed between 2001 and 2008 in 53 German ICUs, the carbapenem use almost doubled despite no significant change in the total antibiotic use expressed as defined daily doses (DDD)/1,000 patient-days. The exponential increase of third-generation cephalosporin resistance in Escherichia coli and other Enterobacteriaceae reported in this study led to switching empirical therapy to carbapenems to treat infections, with subsequent emergence of carbapenem-resistant Klebsiella pneumoniae, carbapenemase-producing gram-negative pathogens, and imipenem-resistant A. baumannii as a direct consequence. This scenario will affect many ICUs around the world in the near future, although resistance trends and antibiotic consumption rates will still depend on different determinants, that is, ICU characteristics (medical, surgical, general), local antibiotic policies, and physicians’ level of education among others. The heterogeneity of antibiotic prescriptions within ICUs recorded by Meyer and colleagues seems to indicate that antimicrobial use can be improved also in ICU settings by shortening the duration of treatment or antibiotic prophylaxis without affecting patient outcome (58).

In contrast to multidrug-resistant gram-negative bacteria, infection rates seem to have stabilized or declined for multidrug-resistant gram-positive bacteria (e.g., methicillinresistant Staphylococcus aureus [MRSA], vancomycin-resistant enterococcus [VRE]) in ICUs in many high-income countries (59,60,61,62). For instance, Jain et al. (60) evaluated the effectiveness of a quality improvement initiative in preventing the acquisition and spread of MRSA among nearly 2 million patient admissions, including data from 196 ICUs in the United States. During the intervention period—with increased attention to MRSA admission screening, contact precautions, hand hygiene, and emphasis on responsibility of all healthcare workers in prevention procedures—an important decrease in infections not only caused by MRSA, but also by other pathogens was observed (60). However, others have questioned the effectiveness of the intervention and suggest that other non-documented factors may have contributed to the observed reduction in MRSA infection rates in the participating ICUs (63). Despite this ongoing controversy, the positive development of reduced MRSA rates could potentially reduce the necessity of empiric gram-positive coverage in many ICUs, but clinicians seem to be reluctant to adapt their treatment patterns to lower MRSA rates (64).


Host colonization is often a prerequisite for the development of infection. This process involves adherence of organisms to epithelial or mucosal cells, proliferation, and persistence at the site of attachment. Although the factors promoting the progression from colonization to infection are not well understood, almost 50% of the ICU-acquired infections are preceded by host colonization with the same microorganism. Factors associated with microbial colonization are similar to those associated with development of infection. These risk factors include the duration of hospitalization and length of stay in the ICU, invasive devices, prolonged antibiotic therapy, and elimination of normal pharyngeal or bowel flora through the use of broad-spectrum antimicrobial agents (65). Other factors promoting colonization of patients in ICUs include disruption of normal mechanical defense mechanisms (i.e., the bronchial mucociliary “escalator”) by drugs and tracheal intubation, changes in protective antibacterial secretions (i.e., lysozyme, lactoferrin, saliva, and gastric acid) in response to stress and therapeutic agents, and disruption of “colonization resistance.”

A vast literature exists regarding the development of colonization and subsequent infection (66). A few important studies are summarized. The classic article (67) of Johanson et al., written in 1969, showed that severe illness predisposes to oropharyngeal colonization with gram-negative bacilli. In 1974, Schimpff et al. (68) suggested that in critically ill patients, the origin of infection usually is the endogenous flora. Several studies have subsequently confirmed that patients are rapidly colonized by gram-negative bacteria after admission to ICUs, and later develop HAIs with the same organisms (69,70,71,72,73).

In a landmark study, Grundmann et al. (54) prospectively studied cross-infection in critically ill patients admitted to five ICUs in Germany. During 28,498 patient-days, 431 ICU-acquired infections and 141 episodes of nosocomial transmissions were identified. A total of 278 infections were caused by the 10 species that were genotyped, and only 41 of these (14.5%) could be associated with transmissions between patients. Thus, modern typing methods confirmed that the patients’ endogenous flora is the most important source of HAI.

A recently published cohort study confirmed the value of modern molecular genotyping and genome sequencing methods to elucidate exogenous transmission pathways of MRSA during an outbreak in a neonatal ICU in England, similar to an investigation of endemic MRSA transmission routes in a tertiary care center in Thailand (74,75). Consequently, antiseptic body washes are increasingly used to reduce exogenous transmission and acquisition of multiresistant gram-positive bacteria. Several well-designed intervention studies have shown their short-term benefit in reducing MRSA and VRE carriage and infection rates. Chlorhexidine body washes, in particular, have now become standard-of-care in many ICUs to reduce the bacterial load on patients’ skin. A British team of investigators examined the impact of several control interventions aimed at reducing cross-transmission of MRSA (76). An educational campaign and cohorting had little impact on MRSA transmission. The introduction of chlorhexidine as a skin antiseptic reduced MRSA transmission of all but one of the strains prevalent in this ICU: the “TW” strain that carries the qacA/B genes which code for chlorhexidine resistance (76). Due to its chlorhexidine resistance, the acquisition of this MRSA strain increased dramatically during the period of this interrupted time-series study. The emergence of resistance also has been observed with other topical decontamination regimens; thus, it is important to actively look for emerging chlorhexidine resistance in settings with widespread chlorhexidine usage (77,78).

The central role of gastric colonization in the pathogenesis of HAI and pneumonia has been called into question. Based on studying sequences of colonization in ICU patients, Bonten et al. (79) concluded that the stomach is unlikely to be an important source of pathogens leading to healthcare-associated pneumonia, as diagnosed by bronchoalveolar lavage (BAL) or protected specimen brush (PSB). Furthermore, the initial site and route of colonization might not be the same for all microorganisms (79). These results were confirmed in a large, observational cohort study conducted in two medical ICUs, where specimens for culture were taken daily from nares, oropharynx, trachea, and stomach, from the time of admission to the first signs of healthcare-associated pneumonia (80). The stomach was an uncommon source of microorganisms that cause pneumonia in ventilated patients. Preventive regimens should thus be mainly directed against colonization of the oropharynx and trachea (81,82).


Infection Rates and Types of ICU

New insights were recently reported regarding the epidemiology of infection in ICUs. A global, observational study (EPIC II) on the prevalence and outcomes of infection in 1,265 ICUs was conducted in 75 countries in May 2007. Among the 13,796 patients, 9,084 (66%) received an antimicrobial agent and 7,087 (51%) were considered infected at the time of data collection (2). Unfortunately, due to methodological limitations, no clear-cut distinction could be made between community- and HAIs. However, among those patients who had stayed >7 days in the ICU before the study day, >70% were infected, mostly with multidrug-resistant organisms. A clear association was noted between prevalence of infection and hospital mortality, with Greece and Turkey having the highest mortality and Switzerland the lowest (Figure 24.2). These differences are
likely to reflect differences in critical care practices between countries, and underline the importance of controlling for case-mix when interpreting and comparing rates of HAIs between hospitals or countries (5).

Figure 24.2. Hospital mortality in relation to infection prevalence in critically ill patients, stratified by country. (From Vincent JL, Rello J, Marshall J, et al. International study of the prevalence and outcomes of infection in intensive care units. JAMA. 2009;302:2323-2329, with permission.)

Not only at a national or international level the frequency differs with which infections occur, but also at different sites in the ICU and within a hospital. The annual U.S. Centers for Disease Control and Prevention’s (CDC’s) National Nosocomial Infections Surveillance (NNIS)—now known as the National Healthcare Safety Network or NHSN—system report and data from the German ICU surveillance system KISS illustrate these differences in the incidence of HAIs in different types of wards and ICUs (83,84). First, predominant HAIs vary by location. Urinary tract infections predominate in general wards, whereas the most common HAIs in ICUs are lower respiratory tract infections. Second, HAI rates vary by type of ICU. Rates of infection tend to be higher in the surgical ICU than in the medical ICU, and rates in the adult ICUs are generally higher than in pediatric ICUs (except neonatal ICUs) (85). Third, in all types of ICUs, the lower respiratory tract is the most common site of infection (Table 24.1). High rates of pulmonary infections relative to other infection sites are unique to adult critical care units, where patients are frequently admitted because of respiratory distress and require mechanical ventilation. Although primary bacteremia and infections stemming from the presence of vascular cannulas are less common than lower respiratory tract infections, the morbidity and mortality associated with these infections are particularly high (86,87).

In 2000, the CDC reported for the first time a decrease in HAI rates in the ICUs of participating NNIS hospitals from 1990 to 1999 (88). Risk-adjusted infection rates decreased for three body sites (the respiratory tract, the urinary tract, and the bloodstream). The greatest decrease was observed for BSI rates, which decreased in medical ICUs by 44%, in coronary ICUs by 43%, in pediatric ICUs by 32%, and in surgical ICUs by 31%. However, because of a progressively shorter ICU length of stay over the last 20 years, the overall, hospital-wide rate of HAIs per 1,000 patient-days has actually increased by 36%, from 7.2 in 1975 to 9.8 in 1995 (89). The variable use of different denominators also may have an important effect on trend analyses and may bias benchmarking (90).

TABLE 24.1 HAI Rates in German Intensive Care Units (ICUs): Data of the German KISS Surveillance System, 2005 to 2009, According to Type of ICU and Infection (Updated Version Downloadable Under:

Urinary Tract Infection

Central Line-Associated Bloodstream Infection

Ventilator-Associated Pneumonia

Type of ICU

Rates Per 1,000 Device-Days

Rates Per 1,000 Days of Mechanical Ventilation

Inter-disciplinary <400 beds




Inter-disciplinary ≥400 beds
























Cardiac surgical




When rates of HAIs have been compared over shorter increments of time (i.e., by month) wide variations have been noted. Observations in different ICUs suggested that the level of skilled nursing care relative to patient census may be an important determinant of this variation (91,92). Indeed, there are many studies showing that overcrowding, understaffing, or a misbalance between workload and resources are important determinants of HAIs and cross-transmission of microorganisms in ICUs (93,94,95). Importantly, not only the number of staff but also the level of their training affects outcomes. The causal pathway between understaffing and infection is complex, and factors might include lack of time to comply with infection control recommendations, job dissatisfaction, job-related burnout, absenteeism, and a high staff turnover (92).

In summary, rates of HAIs vary considerably within hospitals by the type of ICU. Rates are generally lower in cardiac care units and higher in neonatal, surgical, trauma, and burn units, reflecting the greater risk of infection of patients admitted to these latter types of units (83).

Impact of Infections Acquired in the ICU

ICU-acquired HAIs are harmful for the patients and expensive for society. Several studies suggest that healthcare-associated pneumonia and BSI are associated with a two- to three-fold increased risk of death in critically ill patients (96,97). Crude mortality rates in patients who acquire HAIs in the ICU are estimated to vary between 10% and 80%. The term attributable (or excess) mortality defines the mortality directly associated with the infection, apart from the mortality attributable to underlying conditions. In ICU patients, underlying conditions apart from HAI that may affect the outcome mainly include preexisting comorbidities, severity of acute physiologic disturbance or severity of illness, and complications arising from these conditions (98).

Assessment of mortality attributable to HAIs in the ICU setting is difficult and not straight-forward because HAIs and mortality attributable to other causes share common risk factors that may confound the cause-and-effect relationship. Thus, it is sometimes difficult to estimate whether the critically ill patient would have survived in the absence of HAI. The most
often used approach to estimate the attributable mortality of HAIs in ICU patients is to conduct a matched cohort study. In this type of study design, cases are defined as patients in whom HAIs develop during their ICU stay. These case-patients are subsequently compared with noninfected controls. Case- and control-patients are usually matched for age, the time of the year, the underlying diseases, and additional variables that may contribute to excessive mortality rates of ICU stay independent of the infection itself. In brief, the attributable mortality due to HAI defines the excess mortality due to the infection. For instance, a recent French ICU-based case-control study matched 1,725 deceased patients with 1,725 surviving control-patients to determine the excess mortality related to ICU-acquired infection (3). The adjusted population-attributable fraction of deaths due to ICU-acquired infection for patients who died before their ICU discharge was 14.6% (95% CI, 14.4 to 14.8). The attributable mortality of ventilator-associated pneumonia (VAP) was 6.1% (95% CI, 5.7 to 6.5), an estimate close to the 8.1% (95% CI, 3.1% to 13.1%) provided by a multistate model of another cohort study that appropriately handled VAP as a time-dependent event (36). A large-scale cohort study including 10 European countries and 537 ICUs determined clinical outcomes of patients with HAI admitted to ICUs (99). They found high excess mortality associated with BSI and pneumonia, and substantially increased excess length of stay for pneumonia, but not for BSI. Surprisingly, antimicrobial resistance provided only a small contribution to the overall burden of HAI, with HAI due to Pseudomonas aeruginosa generating the greatest burden (and not MRSA).

For the assessment of the morbidity and economic burden associated with HAI in the ICU, matched cohort studies should not be recommended. This study design has several limitations because of the time-varying nature of the exposure. One source of bias occurs when infected and uninfected patients are compared with regard to total hospital costs or total hospital length of stay. For infected patients, only those costs incurred after the occurrence of the HAI are possibly secondary to infection. Before occurrence of infection, patients are unexposed. The association between preinfection outcome and infection is entirely noncausal from the perspective of measuring the excess burden of infection. Therefore, combining preinfection outcomes with postinfection outcomes dramatically amplifies confounding (100).

Several recent studies have demonstrated the effect of this bias. Outcome analyses that did not account for the time before the occurrence of the infection yielded different results than studies that did account for the time before the infection. Schulgen et al. (101) tested different methods and showed that the use of unmatched or matched comparisons between noninfected and infected patients led to an overestimation of the excess length of stay due to healthcare-associated pneumonia, compared to analyses based on a structural formulation of transitions between different states. In a recently published study, Beyersmann et al. have confirmed the validity of this statistical approach (102). They showed that HAI significantly reduced the discharge hazard (Hazard ratio [HR] = 0.72; 95% CI = 0.63 to 0.82), that is, prolonged ICU stay. Prolongation of ICU length of stay due to HAI was estimated at 5.3 days (±1.6). Another approach to estimating cost and length of stay effects of adverse events is to apply survival models, in which the adverse event is incorporated as a time-dependent variable. This strategy can be applied to costs as well as length of stay (100).

In summary, HAIs in critically ill patients unquestionably have substantial effects on morbidity and mortality. However, the matched cohort study design may produce bias in the estimation of the effects of HAI on length of stay and costs. Cost effects or excess length of stay are likely to be overestimated if the interval to onset of HAI is not properly accounted for in the study design or analysis (100). Since simple prevalence studies or matched cohort studies do not allow drawing any strong causal inferences between infection rates and excess morbidity due to ICU-acquired HAIs, longitudinal cohort studies with more sophisticated analyses have to be conducted.

Causative Agents

Bacteria, fungi, and viruses have been reported as causative agents of HAIs in critically ill patients, and many of the bacterial infections are polymicrobial. The Sepsis Occurrence in Acutely Ill Patients (SOAP) study performed in 2002 (103) investigated a large cohort of septic patients in 198 ICUs in 24 European countries. Among the 279 patients with ICU-acquired sepsis, staphylococci, including MRSA were most frequent (40%), followed by Pseudomonas spp. (21%), streptococci (19%), E. coli (17%), and C. albicans (16%). Patients with ICU-acquired sepsis had a higher incidence of mixed infections (23% vs. 16%) compared with those with non-ICU-acquired sepsis (103).

Although the Sepsis Occurrence in Acutely Ill Patients study reported an equal frequency of gram-positive and gram-negative organism, the most recent EPIC II study on the prevalence and outcomes of infection (community- and HAI) in 1,265 ICUs in 75 countries reported that gram-negative organisms were more commonly isolated than gram-positive organisms (62% vs. 47%) (2). In patients with positive microbiologic results, the most common gram-positive organism was S. aureus (20.5%) including 10.2% of MRSA; the most common gram-negative organisms were Pseudomonas spp. (19.9%), E. coli (16.0%), and Klebsiella spp. (12.7%); 17.0% were Candida spp. Authors reported a significant relationship between the time spent in the ICU before the study day and the development of infection, particularly for infections due to MRSA, Acinetobacter, Pseudomonas, and Candida spp. There also were significant regional differences in the organisms isolated from microbiologic cultures, with a particularly striking variation in the prevalence of Acinetobacter spp. (ranging from 3.7% in North America to 19.2% in Asia) (2).

To illustrate the trends in microbial etiology of device-associated HAIs, we show in Table 24.2 data from the U.S. NHSN and the German ICU surveillance system KISS (84,104). These data are similar and representative of ICUs in the industrialized world. The leading pathogens causing central line-associated bloodstream infections (CLA-BSIs) and surgical site infections (SSIs) were Staphylococcus and Enterococcus species. S. aureus and P. aeruginosa were the most commonly listed pathogens causing VAP and E. coli was the most prevalent isolate of catheter-associated urinary tract infections in the ICU setting.

Marriott and colleagues have undertaken a nationwide prospective clinical and microbiologic cohort study of all episodes of ICU-acquired candidemia occurring in nonneutropenic adults in Australian ICUs between 2001 and 2004 (105,106). Overall, 183 patients had ICU-acquired candidemia with a
30-day case-fatality rate of 56%. Host factors (i.e., older age, mechanical ventilation, and ICU admission diagnosis) and failure to receive systemic antifungal therapy were significantly associated with mortality on multivariate analysis. Process of care measures advocated in recent guidelines was implemented inconsistently: follow-up blood cultures were obtained in 68% of patients, CVCs removed within 5 days in 80%, and ophthalmological examination performed in 36%. This study showed that crude mortality remains high in ICU patients with candidemia and is overwhelmingly related to host factors, but not treatment-related variables (i.e., the time to initiation of antifungals or fluconazole pharmacokinetic and pharmacodynamic factors).

TABLE 24.2 Leading Nosocomial Pathogens by Device- and Procedure-Associated Infections and Frequency

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Jun 16, 2016 | Posted by in INFECTIOUS DISEASE | Comments Off on The Intensive Care Unit, Part A: HAI Epidemiology, Risk Factors, Surveillance, Engineering and Administrative Infection Control Practices, and Impact

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NHSNa 2006-2007 (%)

KISSb 2005-2009 (%)





Enterococcus species



Candida species



S. aureus



K. pneumonia



Enterobacter species



P. aeruginosa



E. coli



A. baumannii




E. coli



Candida species



Enterococcus species



P. aeruginosa



K. pneumoniae



Enterobacter species






S. aureus




S. aureus



P. aeruginosa