A predictive risk index for nosocomial pneumonia in the intensive care unit

A Predictive Risk Index for Nosocomial Pneumonia in the Intensive Care Unit NIRMAL JOSHI, M.D., A. RUSSELLLOCALIO,M.P.H., MS., BRUCEH. HAMORY,M.D., Hershey, Pennsylvania

PU~~POSB To develop a scoring system for stratifying patients in int4msive care units (ICUs) by risk of developing nosocomial pneumonia (NP) and to identify the time period associated with the highest risk. PATIENTS AND MJ!TEOD& Two hundred and three patients 18 years of age or older and residing in the ICU for 72 hours or more were followed until development of NP or death or for 48 hours after discharge from the ICU. After the identification of independent risk factors for NP, a scoring system was developed to arrive at a predictive risk index for NP. RESULFI’EIZ Twenty-six (12.3% ) patients developed NP. The presence of a nasogastric (NG) tube [odds ratio (OR) = 6.43,95% confidence intervals (CI) = 2.11 to 19J2], upper abdominal/ thoracic surgery (OR = 434,95% CI = 1.43 to 13.14), and bronchoscopy (OR = 2.95,95% CI = 1.02 to 852), most commonly performed for respiratory toilet, were identified as independent risk factors on multivariate analysis The risks associated with endotracheal intubation and altered consciousness, although not independently signifiicant, were highest when these factors were present for 1 to 4 days after the 72 hours required for study entry (endotracheal intubation, OR = 2.2 to 23 altered consciousness, OR = 1.4 to 2.0). The risk then declined; ORs of less than 1 were observed at 7 day& The risk associated with the NG tube was highest during the fmt 6 days (OR = 6.0 to 19.5). Although a subsequent decrease in risk was observed, the OR was stillgreaterthan2at7dayuToobtainapredictive risk index for NP, a scoring system was developed using a multivariate model. This system

From the Division of Infectious Diseases and Epidemiology (NJ, BHH), Department of Medicine, and Center for Biostatistics and Epidemiology (ARL). Milton S. Hershey Medical Center, Pennsylvania State University, Hershey, Pennsylvania. Requests for reprints should be addressed to Nirmal Joshi, M.D., 630 Cardinal Drive, Harrisburg, Pennsylvania 17111. Manuscript submitted September 19. 1991. and accepted in revised form April 7, 1992.

has a sensitivity of 35% and a specificity of 66% in predicting NP in this ICU population. CONCLUSION: ICU patients can be stratified into high- and low-risk groups for NP using a bedside scoring system. Rndotracheal intubation, altered mental status, and NG tube are associated with the highest risk of NP during the first 1 to 6 days of their presence after 72 hours of stay in the ICU. After this time period, the risk associated with these factors decreases. Bronchoscopy may be an independent risk factor for NP that has not been previously recognized. This procedure, often done in the ICU for respiratory toilet, may be an avoidable risk in this group of patients.

N

osocomial pneumonia (NP) is the third most common nosocomial infection and the most common cause of death from nosocomial infection in the United States [l]. A high proportion of NPs occur in intensive care units (ICUs). As many as 50% of all NPs occurring among patients on the medical service and 70% of NP among patients on the surgical service occur in ICUs [2]. Case fatality rates of 20% to 50% in some studies of NP [3-51, despite the availability of potent antibiotics, emphasize the need for research directed at its prevention. One potential approach to preventing NP is to stratify patients early in their ICU stay into highand low-risk groups for the development of NP. Interventions can then be directed specifically at the high-risk patients. Although previous studies have identified risk factors for NP [5-S], prospective cohort study designs and statistical methods were used to identify independent risk factors in only two studies [5,6]; both were limited to mechanically ventilated patients. An objective estimate of overall individual patient risk for NP cannot be derived from these studies. To design effective strategies to prevent NP, it is important to identify not only the patients at highest risk for NP, but also the period of stay in the

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ICU associated with such a risk. To our knowledge, no study has attempted to define systematically a relationship between the duration of exposure to one or more risk factors and the development of NP. The current study was designed to develop a simple, easy-to-use predictive model to stratify patients in the ICU into high- and low-risk groups for NP. In addition, we examined the relationship between the duration of several risk factors and the development of NP to identify the period of highest risk.

PATIENTS AND METHODS Patient Population The University Hospital of the Milton S. Hershey Medical Center is a 350-bed tertiary-care hospital with a 27-bed medical-surgical ICU. Of 762 patients admitted to this ICU during the 6 months between August 13,1999, and February 13,1991, all patients 18 years of age or older who resided in this ICU for 72 hours or more were entered into the study. One investigator (NJ) followed this cohort of 203 patients prospectively until one of the following events occurred: development of NP, discharge from the ICU for more than 48 hours, or death. All ventilated patients had ventilator tubing changed and chest radiography performed three times per week (Monday, Wednesday, and Friday). Antipyreties were not used routinely in any subset of patients. Data Collection One of us (NJ) made all of the observations and abstracted relevant data daily by review of the patients’ medical records, bedside flow sheets, and radiographs. At the time of entry into the study, the following data were recorded by chart review: age, sex, admitting service, body weight, smoking history, serum albumin level, and a history of chronic obstructive lung disease (COPD). In addition, the presence or absence of each of the following potential risk factors was recorded daily: endotracheal intubation, tracheostomy, administration of histamine type 2 receptor (Hz) blockers, nasogastric (NG) tube, tube feeding (instillation into the stomach of greater than 506 mL/d of enteral nutrition solution), altered level of consciousness (patient unable to respond to simple commands), upper abdominal/thoracic surgery, and bronchoscopy. The presence of any of these factors within 5 days prior to entry resulted in the classification of “present” on the day of entry. Bronchoscopy was considered a risk factor only if it had been performed 2 or more days prior to NP. Patients were classified as obese if their recorded body weight was 136

August 1992 The American Journal of Medicine

greater than or equal to 106 kg for men and greater than or equal to 80 kg for women, or if the records indicated that they were too heavy to be weighed. A diagnosis of NP required the presence of all the following criteria: fever greater than 38”C, white blood cell count greater than 10,000/mm3, lung infiltrate persisting more than 24 hours not attributable to another etiology (e.g., adult respiratory distress syndrome, congestive heart failure, or pulmonary embolism), and purulent respiratory secretions (greater than 5 polymorphonuclear leukocytes per oil immersion field on Gram stain) yielding growth of microorganisms. A positive culture of blood, pleural fluid, or protected brush sample via bronchoscopy was regarded as additional proof of NP and as definitive for etiology but was not required as a diagnostic criterion. Patients with pneumonia diagnosed on admission to the ICU were not excluded from the study. A diagnosis of NP in this group of patients required, in addition to the above criteria, a worsening of the lung infiltrate and a change in the presumed causative microorganism. Severity of illness was classified according to the method of McCabe and Jackson [lo]. This method was preferred over the recently described, more accurate methods to maintain simplicity and easy application at the bedside. Patient outcome (dead/ alive) was determined at discharge. Statistical Analysis Univariate analysis of the association of outcome (pneumonia or death) with risk factors and patient demographics was done with generalized MantelHaenszel methods [ll]. The test for association was used when the risk factors were not ordinal; the test for differences in mean scores was used when one factor was ordinal. Fisher’s exact test and exact, non-parametric Wilcoxon and stratified trend tests [12] replaced x2 tests when sample sizes were too small to support asymptotic confidence intervals (CIs). Breslow-Day [13] and Zelen’s [14] exact tests were used to determine homogeneity of odds ratios (ORs) across strata. Multivariate analysis proceeded only on models that were a priori judged sound clinically to avoid the pitfalls of producing spuriously significant results with multiple comparisons. Using logistic regression with pneumonia as the outcome and risk factors as predictors, we fit several models to determine the ORs of developing pneumonia while controlling for other factors [15]. Both SAS PROC LOGISTIC and PROC CATMOD with the clogits option produced parameter estimates and model goodness-of-fit statistics [16,17]. Where interest centered on the effects of risk factors over time, we grouped risk factors according to length of patient

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exposureand then enteredeachgroupasa separate indicator in the model. This method allowed for nonlinear dose-response effects.We then fit a series of logistic regressionmodels, eachwith a length of exposureonly for the risk of interest, and with a dichotomous variable for the other factors. Developmentof a Scoring Systemfor Risk Stratification Of severalmodels tested, one model was usedto develop a scoring system for risk stratification. Clinical considerationsin model developmentwere the desire to use predictors that remainedrelevant basedon univariate analysisand on clinically plausible links to pneumonia,and the needto arrive at a parsimoniousmodel for simple application at bedside. Some factors thought to be of clinical relevancewereleft in the model regardlessof statistical significance at p = 0.05. Statistical comparisons were based on model fit (proportion of deviance explainedby the model), adjustedfor the number of predictorsused.Final model selectionamongseveral alternatives with comparable fit and predictive ability wasbasedon the needto limit the number of variables, especially those related to the length of exposure.From the selectedmodel, fitted probabilities and oddsfor eachpatient werecalculatedfrom the parameter estimates. Receiveroperating characteristic (ROC) curve analysis and sensitivity and specificity considerationsdetermined the optimal threshold odds for classifying a patient as “high risk” [181.For field useof the model asa predictive tool, wechoseto round the ORsfor eachpatient risk factor sothat a non-statistician with a handcalculator (or evena pencil and paper) could predict outcome as above or below the odds threshold. The predictive model with rounded parameter estimates wastested against the data to determine the extent of misclassification between rounded and unrounded models. RESULTS Table I summarizesthe baselinecharacteristics and the interventions performed on the 203 patients who were entered in the study. A history of smoking and COPD wasnot recordedin the chart of 41% and 40% of patients, respectively. The most frequent admission diagnoseswere related to the cardiopulmonary system (45%). Patients were almost equally distributed betweenmedical and surgical services.Fifty-eight percent of the patients were intubated. Twenty-six (12.8%)patients met the study definition for NP. The following risk factors were statistically significant on univariate analysis: Hz blocker therapy (OR = 2.75,95%CI = 1.02to 7.40),

TABLE I Characteristicsof the Study Cohort* All Patients No. 96

Patients With Pneumonia % No.

Sex (M)

115

57

18

69

Obesity

17

8

4

15

124

61 27 12

:A 5

3”: 19

9

35

Severity of illness Nonfatal Ultimately fatal Rapidly fatal

!i

Smoking Present Absent Unknown

283

;:41

COPD Present Absent Unknown

1;: 80

ki 40

ii

:i 50

Admission service Medicine Surgery

1;;

zi

2;

2

Admission diagnosis ~;arddcrlmonary Abdominal Central nervous system Multisystem Cancer Others Altered mental status

1: 3

:i

:: 19

45 16 9

; 4

:z 15

87

43

19

73

lntubation

117

58

23

88

Nasogastric tube

108

53

24

92

47

23

0

0

128

63

21

81

Recent bronchoscopy

42

21

10

38

Tracheostomy

25

12

3

12

55

27

12

46

Tube feeding Hz-blockers

Upper abdominal/thoracic

surgery

ke (mean ? SD) = 57.5 r 17.8 for all patients, and 62.7 t 16.9 for patients with pneumonia.

altered mental status (OR = 4.35,95%CI = 1.83to 10.3),endotrachealintubation (OR = 6.77,95%CI = 2.25to 20.4),NG tube (OR = 13.3,95%CI = 4.05 to 43.6),upper abdominal/thoracic surgery (OR = 2.67,95%CI = 1.17to 6.09),recent bronchoscopy (OR = 2.83,95%CI = 1.21to 6.65),and underlying diseasesthat wereultimately fatal (OR = 2.09,95% CI = 1.02to 4.33)and rapidly fatal (OR = 2.89,95% CI = 1.04to 8.26)as comparedwith thosethat were nonfatal (exactWilcoxon, p = 0.035).The incidence of NP increasedwith patient age.NP occurredin 6%of patients 40 yearsold, 11%of patients 40 to 60 years of age, and 16% of patients older than 60 years.This trend, however,did not achievestatisti-

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137

NO9OCOMlAL PNEUMONIA IN THE ICU / JOSH1 ET AL TABLE II Importance of Risk Factorson Multivariate Analysis* Odds Ratio

RiskFactor

95% Confidence Intervals

20

due

1. Age >6Oy

1.93

0.70-5.32

0.19

2. Ultimately fatal disease

2.79

0.90-8.61

0.07

3. Rapidly fatal disease

3.89

0.92-16.40

0.06

4. Upper abdominal/ thoracic surgery

4.34

1.43-13.14

0.008

5. lntubation

2.09

0.49-9.04

0.31

6. Altered mental status

1.62

0.53-4.91

0.39

10 a 6 4 2 nv I NGTUBE

6.48

2.12-19.82

0.0008

8. Hz-blockers

0.92

0.64-6.80

0.21

9. Recent bronchoscopy

2.95

1.02-8.52

0.04

7. Nasogastric tube (l-6

d)

INTUBATION

ALTEREDMENTAL STATUS

Selected RI Faders

Flgure 1. Duration of exposure to selected risks (Day 0 = 72hour ICU stay) and the odds of nosocomial pneumonia relative to patients with no exposure (other risk factors held constant). NG = nasogastric.

Inconditionalk&tic regression.

although not statistically significant, were highest cal significance(p = 0.25).The incidenceof NP also whenthesefactorswerepresentfor 1 to 4 daysafter increasedamongobesepatients (24%in obese,12% the 72 hoursrequiredfor study entry (endotracheal in nonobese)and smokers (17%in smokers,8% in intubation, OR = 2.2to 2.5;altered consciousness, nonsmokers), but these differences also did not OR = 1.4to 2.0).The risk then declined;ORsof less achievestatistical significance. than 1were observedat 7 days.The risk associated Selectedrisk factors were enteredinto a logistic with the NG tube washighestduring the first 6 days regressionmodel, and a multivariate analysis was (OR = 6.0to 19.5).Although a subsequentdecrease performed. Only upper abdominal/thoracic sur- in risk wasobserved,the OR wasstill greaterthan 2 gery,presenceof an NG tube, and recentbronchos- at 7 days. copy emergedas statistically significant, indepenThe case-fatality rate for patients with NP was dent risk factors for NP (Table II). Of the 10 46%comparedwith a crudemortality of 22%among case-patientsin whom bronchoscopywas recorded non-cases(x2 = 7.01, df = 1, p = 0.008).Odds of asa risk factor, two had three or more bronchoscop- death among the caseswere 2.5 (95% CI = 0.946 ic proceduresprior to NP. In addition to the above to 6.57) times the odds among non-cases,when factors,the presenceof ultimately fatal and rapidly controlling for severity of illness (exact Mantelfatal underlying illnessesapproachedstatistical sig- Haenszelp = 0.054).Of 17 case-patientsgreater than 60 years of age, 11 (65%)died as compared nificance (p = 0.07 and 0.06,respectively). The rate of NP alsovaried by admissiondiagno- with 1(14%)of 7 case-patients40 to 60yearsof age. sis. While 5.5%of patients with diagnosesinvolving Neither of two patients lessthan 40 yearsold died. the cardiopulmonary systemdevelopedNP, 23%of These differenceswere statistically significant (x2 patients with diagnosesinvolving the abdominal = 6.36, df = 1, p = 0.012). No other factor was system and 19%of patients with headtrauma and associatedwith an increasedrisk of mortality. central nervoussystem dysfunction developedNP. Although thesedifferenceswerestatistically signif- The ScoringSystemand Its Usein the StudyCohort icant (Fisher’s exactp = 0.015)on univariate analyTable III presentsthe scoring system that was sis, they did not achievestatistical significanceon derived from the selectedlogistic model. The score multivariate analysis. assignedto eachrisk factor representsthe rounded A relationship betweenthe duration of exposure OR for that risk factor from the logistic model. The to each of three identified risk factors and the de- scoresfor eachrisk factor presentin a given patient velopment of NP was sought.The oddsof develop- are multiplied by one another and then multiplied ing NP during each period of exposureto a single by a constant factor or baseodds [K = 0.00251to risk factor while controlling for other risk factors yield the odds of developingNP. As an example,a arepresentedin Figure 1.The risks associatedwith 70-year-oldintubated patient with an NG tube who endotrachealintubation and altered consciousness, has recently undergoneabdominal surgery would

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NOSOCOMIAL PNEUMONIA IN THE ICU / JOSHI ET AL

r TABLEIII Scoring Systemto StratifyPatientsbyRiskof Developing Nosocomial Pneumonia* Score [Sl if Risk Factor Present

Risk Factor 1. Age>60y

2

2. Ultimately fatal disease

3

3. Rapidly fatal disease

4

4. Upper abdominal/thoracic

L

surgery

4

5. lntubation

2

6. Altered consciousness

1.5

7. Nasogastric tube

6.5

8. Hz-blocker therapy

2

9. Recent bronchoscopy

3

0.2

0.6

0.6

1.0

False-Positive Rate

*Calculatedodds of ncsmxmlal pneumonia:odds = K x S1 x S2 x Sq,where S = 1 if factor absent and above score if present and where K = 0.0025 (e.g., patient with factors 3, 4, and 7

present: odds = 0.0025 x 4 x 4 x 6.5 = 0.26; “high risk” if odds >O.ll specificity 66961).

0.4

Flgure

2. the logistic

Receiver model.

operating

characteristic

(ROC)

curve

for

[sensitivity 85%,

have calculated odds of developing NP of 0.13 [O&O25X 2 X 6.5 X 41or 13%: Basedon an analysisof the sensitivity and specificity of the logistic model with different cut-points for the threshold odds of high risk (Figure 2, ROC curve, area under curve = 0.856),we choseoddsof 0.11 (probability of 0.10) as a minimum level for classifying a patient as at high risk for NP. The patient in the above example would therefore be classified as being at high risk. The scoring system, with this break-point, was then applied to estimate the odds of NP for any patient residing in the ICU for 72 hours or more. Using this bedside scoring system, predicted odds of NP were closeto those of the logistic model. At the break-point value of 0.11,4 of 26 patients who eventually developed NP were classified as “low risk.” Using this break-point value,the model hasa positive predictive value of 0.268 and a negative predictive value of 0.967. COMMENTS We have developeda predictive model that may be used to stratify adult patients admitted to the ICU into high- and low-risk groupsfor NP. Patients identified as being at high risk are potentially the most likely to benefit from preventive interventions. This model is simple to useat the bedsideand has a high sensitivity. Eighty-five percent of NP caseswereamongthe 82patients identified as“high risk” by the model. The positive predictive value of the model (0.267)is more than twice the predictive

value of admission to the ICU for 3 days or more (0.128). Thus, the model substantially improves one’sability to segregatehigh-risk patients. At the same time, the high predictive negative value (0.967)ensuresthat few patients who will develop pneumoniaare falsely classified as low risk. Given that the purposeof this model is to classifypatients broadly into risk groups,the false-positive rate of 34%is reasonablylow. When intervention studies are planned, however,an awarenessof the falsepositive rate is especiallyimportant. If, for example, a potentially toxic prophylactic drug regimenis planned for the high-risk patients, this false-positive rate may be viewed as high. In contrast, if a relatively safe,but expensiveprophylactic regimen is beingconsidered,the false-positiverate is acceptably low. Of note,the threshold that wasused(odds = 0.11,probability of NP = 0.10)to stratify patients into high- and low-risk groupswasarbitrary in that it was basedon a nonstatistical evaluation of the relative clinical disadvantagesof misclassifying patients into high- or low-risk groups.Although it is appropriatefor most purposesfor which this model is designed,it could be changedto yield different sensitivities and specificities as is evident from the ROC curve (Figure 2). Choiceof a higher threshold would reducethe false-positiverate but at a cost of increasingthe false-negativerate (onetrue-positive rate) as reflected by movement down the ROC curve. The ability of this model to “flag” certain ICU patients as being at high risk has an additional advantage.In the high-risk patients, infection control precautionsshould be rigorously followed, and the

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NOSOCOMIAL PNEUMONIA IN THE ICU / JOSHI ET AL

need for invasive interventions should be carefully assessed. In a previous study, the overall risk of nosocomial infection was significantly reduced when high-risk patients were identified early in the admission [ 191. Three independent risk factors for NP were identified using multivariate analysis. These included upper abdominal/thoracic surgery, the presence of an NG tube, and recent bronchoscopy. In addition, the presence of ultimately and rapidly fatal illnesses approached conventional statistical significance. Although several of these risk factors have previously been recognized, therapeutic bronchoscopy, performed for respiratory toilet, is a preventable risk factor not emphasized in earlier studies. The infectious complications of fiberoptic bronchoscopy have been reported by other workers. In a retrospective, questionnaire survey, Credle et al [20] reported data on 24,521 bronchoscopies and identified only 2 pneumonias related to the procedure. Noting the obvious shortcomings of such a survey, Pereira and co-workers [21] did a prospective study of 100 fiberoptic bronchoscopies. Fever occurred after the procedure in 16% of cases and parenchymal infiltrates followed in 6%. Although most infiltrates were transient, one patient died of a rapidly progressive pneumonia. Advanced age and the endoscopic finding of an abnormality were noted as possible predisposing factors. A case of a fatal pneumococcal bronchopneumonia with septicemia in an elderly man after bronchoscopy has been described [22]. In addition, two reports [23,24] have emphasized the propensity of elderly patients with underlying medical diseases to develop pneumonia after bronchoscopy. In most of these studies, bronchoscopy was performed for diagnostic purposes. To our knowledge, there are no data on the infectious complications of therapeutic bronchoscopy, a procedure frequently performed in the ICU. In the ICU setting, bronchoscopy is likely to be overlooked as a predisposing factor for NP since patients are perceived as being at high risk independent of the procedure. The association between the use of therapeutic bronchoscopy and the development of NP must be viewed with caution. It is possible that the common indications for which bronchoscopy was performed, i.e., increased respiratory secretions or pulmonary atelectasis, placed this group of patients at a high risk of NP independent of the procedure. Further studies are needed to establish a clear causal relationship between therapeutic bronchoscopy and NP. Several risk factors identified in previous studies did not emerge as statistically significant in this

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study. These include older age, smoking, COPD, obesity, malnutrition (low serum albumin level), and tracheostomy. While a trend towards increased risk of NP was noted in patients older than 60 years and the obese, information on the presence of smoking, COPD, and malnutrition was not available in many patients, restricting the ability to draw meaningful conclusions from these data. There were too few patients with a tracheostomy to make statistical comparisons. Antacids such as Mylanta (alumina, magnesia, and simethicone), were never used alone in our ICU. They were always used with an Hz blocker. Therefore, we chose to combine these variables. The measurement of gastric ph is not performed in our ICU. This study also examined the relationship between the duration of exposure to various risk factors and the subsequent development of NP. An NG tube was associated with the highest risk of NP during the first 1 to 6 days of its presence after 72 hours in the ICU. The risks associated with endotracheal intubation and altered consciousness, although not statistically significant, were highest during the first 1 to 4 days. After this time, the risk associated with these factors decreased. The relationship between the duration of endotracheal intubation and the development of NP has been examined by several authors. Fagon et al [25] estimated an increased risk of lo/o/d of mechanical ventilation. Torres et al [5], using multivariate analysis, reported an increased incidence of NP among patients ventilated for greater than 5 days as compared with less than 5 days. However, only Langer et al [26] have carefully analyzed the effects of increasing lengths of endotracheal intubation on NP. Using life-table analysis, the authors demonstrated a high and constant rate of acquisition of NP in the first 8 to 10 days of endotracheal intubation, with a low rate thereafter. Our data suggest a similar trend for increasing lengths of endotracheal intubation, altered mental status, and the presence of an NG tube. Information on the “dose-response” effect of other risk factors upon NP has not been reported. A unifying pathogenetic explanation for the high initial risk followed by a decline is not obvious. It is tempting to hypothesize that the initial period in the ICU involves the interaction of several risk factors and that this is the cause of the high risk. However, the trend was seen for each of the three risk factors when all other factors were held constant in the model. It is possible that there may be other environmental factors operating in the initial period that were not studied. In addition, host factors may explain this pattern. Immunologic abnormalities have been identified in at least two groups of

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NOWCOMIAL

patients, i.e., those undergoing abdominal surgery and those hospitalized after trauma [27,28]. These abnormalities, especially low immunoglobulin levels, are present during the first few days after the event and then spontaneously normalize. This may, at least in part, explain the increased susceptibility to infection during the early ICU stay. Alternatively, an “exhaustion” of the “susceptible” population of patients with time may account for the decline in the incidence of NP. The crude mortality rate of patients with NP in this study was 46% and is comparable with the mortality rates of 20% to 50% reported in previous studies [3,4]. When underlying severity of illness was controlled for, the risk of death continued to be significantly higher in patients with NP than among controls. A complete analysis of prognostic factors could not be done because of the small number of case-patients. However, a significantly higher mortality rate was noted among patients older than 60 years. The mortality rates in this study emphasize the persisting high mortality associated with NP. Three limitations of our study deserve mention: First, despite a large cohort, the total number of cases of NP meeting our relatively rigorous definition was small. While this may have limited the power of the study to detect some risk factors, several others emerged as statistically significant and have been noted by previous authors as clinically relevant. Second, the first 72 hours of stay in the ICU were not studied. This “cut-off’ was chosen based on previous data indicating that a large proportion of patients admitted to this ICU are discharged within this time period and that this group of patients are at a very low risk of NP. Therefore, this predictive model cannot be applied to patients during their very early ICU stay. Finally, pathologic evidence or protected brush bronchoscopy specimens were not required for diagnosing NP. As a result, some cases with noninfectious etiologies for pulmonary infiltrates may have been misclassified as NP. Again, previous investigators have used similar definitions and have identified similar risk factors [5,6]. Further, the study criteria were practical, yet fairly stringent. During the study period, two infection control nurses performing independent surveillance in the ICU, using criteria developed by the Centers for Disease Control [29], identified 55 cases of NP. These included all the cases identified in the study. Caution is warranted when using this model at the bedside. It applies only to patients residing in the ICU for at least 72 hours and may not be useful in other settings. Also, while it has good predictive

PNEUMONIA

IN THE ICU / JOSHI ET AL

ability in the cohort from which it was derived, it will need to be cross-validated on a separate cohort of ICU patients before its clinical utility is established. With continued use of this model, other factors may be added to increase its sensitivity and specificity. In conclusion, we have developed a clinically useful method to identify those patients in the ICU who are at greatest risk for NP. This study also identified a decline in the relative risk of NP with time associated with endotracheal intubation, altered consciousness, and use of an NG tube. A previously unidentified factor, therapeutic bronchoscopy, was shown to have a significantly increased relative risk for the development of NP. If a causal association is confirmed by further study, the risks and benefits of this procedure in the ICU will need to be re-evaluated.

ACKNOWLEDGMENT We thank John Goldman, M.D., Michael Weitekamp, M.D., and Robert Aber, M.D., for useful suggestions and Joanne Hutton for secretarial support.

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NOSOCOMIAL PNEUMONIA IN THE ICU / JOSHI ET AL 18. Weinstein M, Fineberg HV. Elstein AS, et al. Clinical decision analysis. Philadelphia: Saunders, 1980. 19. Britt MR, Schkupner CJ. Matsumiya S. Severity of underlying disease as a predictor of nosocomial infection. Utility in the control of nosocomial infection. JAMA 1978; 239: 1047-51. 28. Credle WF. Smiddy JF. Elliott RC. Complications of fiberoptic bronchoscopy. Am Rev Respir Dis 1974: 109: 67-72. 21. Pereira W. Kovnat DM, Khan MA. Fever and pneumonia after flexible, fiberoptic bronchoscopy. Am Rev Respir Dis 1975; 112: 59-64. 22. Beyt BE Jr, King DK. Gfew RH. Fatal pneumonitis and septicemia after fiberoptic bronchoscopy. Chest 1977; 72: 105-7. 23. Timms RM. Harrell JH. Bacteremia related to fiberoptic bronchoscopy. A care report. Am Rev Respir Dis 1975; 111: 555-7. 24. Pereira W. Kovnat DM, Snider GL. A prospective co-operative study of complications foflowing fiberoptic bronchoscopy. Chest 1978; 73: 813-6.

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25. Fagon JI, Chastre J. Domart Y, et al. Nosocomial pneumonia in patients receiving continuous mechanical ventilation. Prospective analysis of 52 episodes with use of a protected specimen brush and quantitative culture techniques. Am Rev Respir Dis 1989; 139: 877-84. 28. Langer M, Mosconi P, Cigada M. Mandell M. Long-term respiratory support and risk of pneumonia in critically ill patients. Am Rev Respir Dis 1989; 140: 302-5. 27. Glinz W, Grob PJ, Nydesser VE, et a/. Polyvalent immunoglobulins for prophylaxis of bacterial infections in patients following trauma. A randomized, placebocontrolled study. Intensive Care Med 1985; 11: 288-94. 28. Alexander JW. Stinnett JD. Dgfe CK, et a/. A comparison of immunologic profiles and their influence on bacteremia in surgical patients with a high risk of infection. Surgery 1979; 86: 94-104. 29. Site definitions. In: National Nosocomial Infections Surveillance (NNIS) manual. Atlanta, GA: US Department of Health and Human Services, 1987: Xl 11-3.

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