- Email: [email protected]
Is Fever Protective in Surgical Patients with Bloodstream Infection?
Is Fever Protective in Surgical Patients with Bloodstream Infection? Brian R Swenson, MD, Traci L Hedrick, MD, Kimberley Popovsky, RN, Timothy L Pruett, MD, FACS, Robert G Sawyer, MD, FACS Sepsis from bloodstream infection (BSI) is an important cause of morbidity and mortality among surgical patients. Our hypothesis was that fever and leukocytosis during BSI would be associated with gram-negative pathogens and worse outcomes among hospitalized surgical patients. STUDY DESIGN: A prospectively collected dataset of all infections diagnosed on the adult general and trauma surgery services between December 1996 and December 2005 at the University of Virginia Hospital was reviewed. Fever was considered a temperature of ⱖ 38.5°C, and leukocytosis was defined as a white blood cell count ⱖ 15,000/L within 24 hours of treatment for infection. Logistic regression was used to identify predictors of fever and mortality. RESULTS: Over 9 years, 823 BSIs were analyzed. One hundred forty-eight BSIs resulted in death (18.0%), and 541 (65.7%) patients were febrile at diagnosis; mortality for these two groups were 12.9% and 27.7%, respectively (p ⬍ 0.0001). Febrile patients had a trend toward fewer gram-negative infections (27.0% versus 31.9%, p ⫽ 0.13), 403 had a leukocytosis at diagnosis and 420 did not; mortality for the two groups was 19.1% and 16.9%, respectively (p ⫽ NS). Higher maximum temperature was protective against mortality in the logistic regression analysis (odds ratio ⫽ 0.60 per C°, p ⬍ 0.0001). CONCLUSIONS: Among surgical patients with sepsis, fever during BSI was not associated with a gram-negative cause and correlated with survival, although increasing WBC had little effect. Mortality after BSI appears associated more with an initially blunted physiologic response than with a robust, proinflammatory response. In addition, a threshold for blood culture other than temperature ⱖ 38.5°C should be considered. (J Am Coll Surg 2007;204:815–823. © 2007 by the American College of Surgeons) BACKGROUND:
Bloodstream infections (BSIs) are a prominent cause of morbidity and mortality among surgical patients.1 Fever is considered one of the chief warning signs of BSI and is often the impetus for additional investigation. Persistent fever despite therapy portends incomplete treatment.2 This said, not all BSIs are associated with fever.3 The question of whether the role of fever in major infections in the human is beneficial or detrimental is difficult to answer. Western medicine’s understanding of fever has been derived largely from in vitro and animal studies. Although these models are useful for mapping biochem-
ical and cellular pathways, there are serious limitations in the ability to extrapolate these results to humans.4-6 Human studies also have their disadvantages. Ethical boundaries largely limit clinical studies to observation and therapy trials. Published clinical studies have reported mixed results. Studies of septic human patients have identified fever as both a predictor of mortality7,8 and a predictor of survival.1,9,10 Surgical patients represent an interesting subset of the general medical population. The physiologic responses to operation, with the sizable inflammatory response and immunosuppression11 that accompanies operation, place surgical patients apart from the nonsurgical population. This study aims to evaluate the influence of fever on mortality in a large cohort of hospitalized surgical patients with BSI. Our starting hypothesis was that fever and accompanying leukocytosis during BSI would be associated with gram-negative pathogens, a more pronounced (and deleterious) inflammatory response, and worse outcomes.
Competing Interests Declared: None. Presented at the Southern Surgical Association 118th Annual Meeting, West Palm Beach, FL, December 2006. Received November 28, 2006; Accepted January 16, 2007. From the Department of Surgery, University of Virginia Health System, Charlottesville, VA. Correspondence address: Brian R Swenson, MD, Department of Surgery, University of Virginia Health System, PO Box 801380, Charlottesville, VA 22908-0300. email: [email protected]
© 2007 by the American College of Surgeons Published by Elsevier Inc.
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Table 1. Demographics and Risk Factors Demographics and risk factors
Gender, n (%) Male Female Mean age (y) Race, n (%) Caucasian African American Hispanic Other Pretreatment comorbidities, n (%) Diabetes Cardiac disease Hypertension Peripheral vascular disease Cerebral vascular disease Chronic renal insufficiency* Dialysis dependence Pulmonary diagnosis Ventilator dependence† Active malignancy Hepatic insufficiency Chronic steroid use Psychiatric diagnosis Thyroid disorder Cell product transfusion‡ Location at time of infection, n (%) Home Ward ICU Other Mean WBC count (1,000 cells/L) Mean APACHE II score Mean modified APACHE II score§
Febrile (n ⴝ 541)
Afebrile (n ⴝ 282)
p Value
334 (61.7) 207 (38.3) 51.4
165 (58.5) 117 (41.5) 56.7
0.37 0.37 ⬍0.0001
440 (81.3) 82 (15.2) 10 (1.9) 9 (1.7)
231 (81.9) 47 (16.7) 2 (0.7) 2 (0.7)
0.84 0.57 0.20 0.26
87 (16.1) 83 (15.3) 157 (29.0) 17 (3.1) 16 (3.0) 19 (3.5) 52 (9.6) 47 (8.7) 238 (44.0) 71 (13.1) 15 (2.8) 52 (9.6) 43 (8.0) 25 (4.6) 364 (79.3)
66 (23.4) 65 (23.1) 107 (37.9) 12 (4.3) 8 (2.8) 17 (6.0) 41 (14.5) 46 (16.3) 110 (39.0) 39 (13.8) 16 (5.7) 30 (10.64) 17 (6.0) 16 (5.7) 158 (79.0)
0.010 0.0063 0.0092 0.41 0.92 0.094 0.034 0.0010 0.17 0.78 0.038 0.64 0.31 0.51 0.93
55 (10.2) 187 (34.6) 284 (52.5) 15 (2.8) 15.5 16.8 14.7
77 (27.3) 63 (22.3) 125 (44.3) 17 (6.0) 16.9 16.4 16.4
⬍0.0001 0.0003 0.026 0.022 0.57 0.49 0.0034
*Baseline serum creatinine ⱖ 2.0 mg/dL. † Before infection. ‡ Packed red blood cells or platelets transfused before initiation of treatment for infection. § APACHE II score with temperature contribution removed (for independent analysis of APACHE II score and fever). APACHE II, Acute Physiology and Chronic Health Evaluation II.
METHODS Study design
A prospective cohort of all patients admitted to the adult general surgery and trauma surgery services from December 1996 to December 2005 who were admitted with a BSI or in whom a BSI developed during their hospital stay were included in this study. During the 9-year study period, data were collected prospectively until patient discharge for all BSI episodes among ICU and non-ICU ward general and trauma surgery patients. Data were collected by chart review every
other day, and by patient examination, physician interview, review of pharmacy data, and laboratory and microbiologic data. Per the Centers for Disease Control and Prevention,12 BSI was defined as any specimen of blood drawn with sterile technique growing a bacteria or fungus, with the exception of cultures of coagulase-negative staphylococci, which required positive cultures from two different sites. Viremia was excluded. In cases where positive cultures from another nonblood site matched the organism grown from blood cultures, or if there was a concurrent intraabdominal or mixed skin/skin structure or surgical-site infection, the
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Table 2. Association Between Organism and Fever Febrile (n ⴝ 541) Organism/class
CNS/Staphylococcus epidermidis Staphylococcus aureus MRSA Enterococcus faecalis Candida albicans Pseudomonas aeruginosa Escherichia coli Streptococcus species Enterobacter cloacae Gram-positive Gram-negative Fungi Anaerobes
Afebrile (n ⴝ 282) %
n
%
n
195 64 29 56 38 21 26 16 26 400 146 62 21
36.0 11.8 5.4 10.4 7.0 3.9 4.8 3.0 4.8 73.9 27.0 11.5 3.9
76 30 15 24 20 21 11 20 8 187 90 29 14
27.0 10.6 5.3 8.5 7.1 7.4 3.9 7.1 2.8 66.3 31.9 10.3 5.0
p Value
0.015 0.65 0.99 0.43 0.94 0.025 0.57 0.0054 0.19 0.081 0.13 0.65 0.45
CNS, coagulase-negative Staphylococcus aureus; MSRA, methicillin-resistant Staphylococcus aureus.
BSI was considered secondary; if no concurrent infectious sources were identified, the BSI was considered primary. Episodes of infection were classified separately for a single patient if more than 72 hours apart. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score was determined at the time of study entry as a measure of illness severity. Death before discharge was primary among outcomes measured. Variables recorded at study entry included maximum temperature in the first 24 hours of the infectious episode, age, gender, race, patient location at time of onset of infection (ICU, home, hospital ward), preinfection medical comorbidities (diabetes mellitus, cardiac disease, hypertension, peripheral vascular disease, cerebral vascular disease, chronic renal insufficiency not requiring dialysis, dialysis dependence, pulmonary disease, ventilator dependence, active malignancy, hepatic insufficiency, chronic steroid use, use of blood cell product transfusions [packed red
blood cells or platelets]), and peripheral white blood cell count. Statistical analysis
Data manipulation and statistical analysis were performed with SAS 9.1.3 (SAS Institute). Demographic, preinfection risk factors, infectious organisms, and BSI sources were tabulated and reported. Binary categorical variables were compared with chi-square analysis or Fisher’s exact test, and continuous variables were compared using Student’s t-test. Significance was considered p ⱕ 0.05. Characteristics and organisms with p ⱕ 0.1 from the univariate analysis were included in a logistic regression analysis with in-hospital mortality among outcomes. In the analysis here, each BSI was treated as a separate episode; several patients had more than one nonconcurrent BSI. When the same analysis was performed using a
Table 3. Concurrent Infectious Sources Source
Primary BSI† Secondary BSI Peritoneum Intravascular device Pulmonary Urinary tract Surgical site Skin/skin structure All other sources
n
%*
n
464 359 157 119 76 46 13 9 20
56.4 43.6 19.1 14.5 9.2 5.6 1.6 1.1 2.4
76 72 33 25 21 14 5 0 4
In-hospital mortality %
16.4 20.1 21.0 21.0 27.6 30.4 38.5 0.0 20.0
*Proportion of patients with the listed source of BSI, with the exception of primary BSI patients, can have multiple sources. † BSI in the absence of a concurrent matching culture from another location. BSI, bloodstream infection.
p Value
0.17 0.17 0.27 0.35 0.022 0.024 0.053 0.16 0.81
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Table 4. The Association Between Bloodstream Isolates and Mortality
BSI organism/class
Candida albicans Pseudomonas aeruginosa Streptococcus spp CNS/Staphylococcus epidermidis Enterobacter cloacae Staphylococcus aureus MRSA Escherichia coli Enterococcus faecalis Fungi Anaerobes Gram-negative Gram-positive
In-hospital mortality (%)
Survived (n ⴝ 675)
Died (n ⴝ 148)
n
%
n
%
p Value
32.8 26.2 19.4
39 31 29
5.8 4.6 4.3
19 11 7
12.8 7.4 4.7
0.0027 0.16 0.82
15.9 11.8 11.7 11.4 10.8 10.0 27.5 20.0 19.7 16.2
228 30 83 39 33 72 66 28 188 490
33.8 4.4 12.3 5.8 4.9 10.7 9.8 4.1 27.9 72.6
43 4 11 5 4 8 25 7 46 95
29.1 2.7 7.4 3.4 2.7 5.4 16.9 4.7 31.1 64.2
0.039 0.33 0.087 0.24 0.24 0.051 0.014 0.76 0.47 0.72
BSI, bloodstream infection; CNS, coagulase-negative Staphylococcus aureus; MRSA, methicillin-resistant Staphylococcus aureus.
subset of observations, which limited the contribution of each patient to their first BSI, similar results were obtained.
RESULTS One thousand eighty surgical patients at the University of Virginia Health System were diagnosed with BSI between December 10, 1996 and December 21, 2005. Two hundred fifty-four transplantation patients were excluded because of immunosuppression therapy, and 3 were excluded for blood cultures that grew a viral organism, leaving 823 separate BSI episodes in 619 patients for analysis. Descriptions of the demographic and preinfection risk factors for febrile and afebrile patients are listed in Table 1. Of the included patients, 541 (65.7%) met criteria for fever (maximum temperature during the first 24 hours of the infectious episode ⱖ 38.5°C), and 282 (34.3%) did not. Fever incidence did not appear to be associated with mean white blood cell count or APACHE II score. A modified APACHE II score, with the temperature contribution deducted, was compared between groups and, not surprisingly, showed a statistically significant difference, with the febrile group demonstrating lower modified APACHE II scores (14.7 versus 16.4, p ⫽ 0.0034). Table 2 presents BSI pathogens by incidence and fever proportion. Although coagulase-negative staphylococci/ Staphylococcus epidermidis was notably more likely to be found in febrile patients (36.0% versus 27.0%, p ⫽ 0.015) and Pseudomonas aeruginosa (3.9% versus 7.4%, p ⫽ 0.025) and Streptococcus species (3.0% versus 7.1%, p ⫽ 0.0054) were more common in afebrile patients, no spe-
cific class of pathogens (gram-negative, gram-positive, or fungal) were markedly associated with fever. Primary and secondary BSIs are described in Table 3. Four hundred sixty-four or 56.4% of BSIs did not have the same pathogen isolated from another source and were considered primary BSIs. Three hundred fifty-nine or 43.6% of BSIs occurred simultaneously with an infection from another source with the same organism. The most commonly identified sources of secondary BSIs were peritoneum, intravascular device, and pulmonary, although the highest mortality was associated with surgical-site infections (38.5%). The association between the most common BSI isolates and mortality is outlined in Table 4. Candida albicans was associated with the highest mortality (raw rate 32.8%, relative risk [RR] ⫽ 2.2, p ⫽ 0.0027). Likewise, when organism classes were compared, fungi exhibited the highest mortality (raw rate 27.5%, RR ⫽ 1.7, p ⫽ 0.014) when compared with gram-positive or gramnegative organisms. Infection with coagulase-negative staphylococci/epidermidis was associated with survival (RR ⫽ 0.86, p ⫽ 0.039). The univariate analyses comparing the association between demographics, preinfection risk factors, and physiologic parameters at the time of infection and mortality are summarized in Table 5. Characteristics and organisms with statistical significance or near significance (p ⱕ 0.1) from the univariate analysis were included in the logistic regression model, with results reported in Table 6. Factors with an independent association with mortality included maximum temperature as a continuous variable, baseline serum creatinine ⱖ 2.0 mg/dL, dialysis dependence, pulmonary
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Table 5. Univariate Analysis of the Influence of Risk Factors on Mortality
Risk factors
Fever (temperature ⱖ 38.5°C)† Gender Male Female Race Caucasian African American Hispanic Other Pretreatment comorbidities‡ Diabetes Cardiac disease Hypertension Peripheral vascular disease Cerebral vascular disease Chronic renal insufficiency§ Dialysis dependence Pulmonary diagnosis Ventilator dependence Active malignancy Hepatic insufficiency Chronic steroid use Cell product transfusion储 Location at time of infection Home Ward ICU Other WBC count ⱖ 15,000 cells/L Mean age (y) Mean APACHE II score
In-hospital mortality (%)*
Survived (n ⴝ 675; 82.0%)
Died (n ⴝ 148; 18.0%)
p Value
12.9
471 (69.8)
70 (47.3)
⬍0.0001
17.8 18.2
410 (60.7) 265 (39.3)
89 (60.1) 59 (39.9)
0.89 0.89
18.3 16.3 0.0 36.4
548 (81.2) 108 (16.0) 12 (1.8) 7 (1.0)
123 (83.1) 21 (14.2) 0 (0.0) 4 (2.7)
0.59 0.58 0.10 0.11
23.5 34.5 20.5 34.5 25.0 50.0 34.4 41.9 24.4 29.1 41.9 26.8 22.8
117 (17.3) 97 (14.4) 210 (31.1) 19 (2.8) 18 (2.7) 18 (2.7) 61 (9.0) 54 (8.0) 263 (39.0) 78 (11.6) 18 (2.7) 60 (8.9) 403 (59.7)
36 (24.3) 51 (6.2) 54 (36.5) 10 (6.8) 6 (4.1) 18 (12.2) 32 (21.6) 39 (26.4) 85 (57.4) 32 (21.6) 13 (8.8) 22 (14.9) 119 (80.4)
0.048 ⬍0.0001 0.20 0.019 0.36 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 0.0011 0.0004 0.028 0.0005
7.6 13.2 23.5 28.1 19.1 — —
122 (18.1) 217 (32.2) 313 (46.4) 23 (3.4) 326 (48.3) 50.7 15.4
10 (6.8) 33 (22.3) 96 (64.9) 9 (6.1) 77 (52.0) 64.4 22.7
0.0007 0.018 ⬍0.0001 0.13 0.41 ⬍0.0001 ⬍0.0001
Values in parentheses are percentages. *Proportion of patients with the listed risk factor who died while in the hospital. † Maximum temperature recorded during the first 24 h of treatment. ‡ Before infection. § Baseline serum creatinine ⱖ 2.0 mg/dL. 储 Packed red blood cells and/or platelets transfused before initiation of treatment for infection. APACHE II, Acute Physiology and Chronic Health Evaluation II.
diagnosis, active malignancy, hepatic insufficiency, cellular blood product transfusion, age as a continuous variable, APACHE II score as a continuous variable, and surgical site as the BSI infection source (odds ratio ⫽ 5.2, p ⫽ 0.045).
DISCUSSION In contrast to our initial hypothesis, we found that fever within the first 24 hours of BSI was a powerful independent predictor of survival. Leukocytosis appeared to have no influence on survival. This study can be added to other studies that have found fever to be protective in sepsis.1,9,10
Although strongly suggesting the association between fever and survival, our study design does not allow us to draw firm conclusions as the biologic explanation for these findings. Two theories are suggested: The role of fever in the immune response is intrinsically protective and serves to lessen the impact of the infection on the body as a whole, conveying a survival advantage; or fever is reactionary, and its presence can be viewed as an indicator of the body’s physiologic reserves, suggesting that the absence of a febrile response indicates either a weakened premorbid state or an overwhelming infection of such magnitude that the normal
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Table 6. Logistic Regression Analysis of the Influence of Risk Factors on Mortality Risk factor
Maximum temperature (per °C) Pretreatment comorbidities Diabetes Cardiac disease Peripheral vascular disease Chronic renal insufficiency Dialysis dependence Pulmonary diagnosis Ventilator dependence Active malignancy Hepatic insufficiency Chronic steroid use Cell product transfusion Location at time of infection Home Ward ICU Age (per y) APACHE II score (per point) BSI organism CNS/Staphylococcus epidermidis Enterococcus faecalis Candida albicans BSI source Pulmonary Urinary tract Surgical site
Odds ratio
95% CI
p Value
0.596
0.470–0.756
⬍0.0001
1.496 1.474 1.647 3.967 2.220 3.961 1.310 2.593 3.809 1.038 2.099
0.860–2.604 0.816–2.662 0.554–4.894 1.475–10.665 1.129–4.365 2.053–7.643 0.635–2.705 1.347–4.994 1.440–10.070 0.508–2.118 1.020–4.319
0.15 0.20 0.37 0.0063 0.021 ⬍0.0001 0.47 0.0044 0.0070 0.92 0.044
0.277 0.563 0.796 1.048 1.100
0.070–1.103 0.162–1.958 0.243–2.610 1.028–1.680 1.060–1.141
0.069 0.37 0.71 ⬍0.0001 ⬍0.0001
0.874 0.411 2.063
0.511–1.494 0.166–1.014 0.932–4.565
0.62 0.054 0.074
1.333 1.889 5.239
0.646–2.748 0.774–4.609 1.038–26.438
0.44 0.16 0.045
c statistic ⫽ 0.889 APACHE II, Acute Physiology and Chronic Health Evaluation II; BSI, bloodstream infection; CNS, coagulase-negative Staphylococcus aureus.
physiologic response is preempted. These theories need not be mutually exclusive, and given the complexity of the acute phase response and critically ill patients in general, it is quite possible that elements of both mechanisms are at work in BSI. Another common theory of fever, not observed in this study, is the relationship between gram-negative organisms and fever, based on the presence of endotoxin in these pathogens in contrast to gram-positive pathogens or fungi. We found no difference in fever rates with gram-negative organism and, in fact, we found that infection with P aeruginosa, was statistically associated with absence of fever. In contrast, the most common infecting organism, S epidermidis, was statistically associated with a higher likelihood of fever. Even if the question of fever’s true role in BSI cannot be precisely defined, several clinical points can be taken from this study. Although sensitive for BSI, fever is not specific and its absence is not at all reassuring. The common temperature threshold of 38.5°C for blood culture might need
to be reconsidered. A high index of suspicion should be maintained in treating critically ill patients, and any patient displaying symptoms or abnormal physiology that could potentially be from sepsis should be considered for blood cultures in the absence of an elevated temperature. Although a more-aggressive diagnostic stance would presumably lead to earlier diagnosis of BSI in afebrile patients and higher survival, this remains unproven and would predictably lead to a larger number of false-positive blood cultures. In addition, the exact trigger for acquisition of blood cultures remains entirely undefined. For example, the likelihood that an elevation in WBC count would be any more precise in this regard is limited, given our experience. Perhaps a less-traditional marker, such as procalcitonin or circulating interleukin-6 might eventually prove to be beneficial. The common practice of treating a fever with antipyretics has previously been called into question.13-15 The data presented in this study do not support this practice and we would advocate leaving reasonable temperature elevations
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untreated in patients without substantial discomfort related to fever until additional data accumulates suggesting suppression of the febrile response is clinically beneficial. Although no individual organisms reached statistical significance as independent predictors of mortality in the multivariate analysis, we should not understate the apparent virulence of fungal BSI. Fungi demonstrated the highest mortality of any organism class at 27.5% and C albicans had the highest mortality of any specific organism at 32.8%. Traditionally, fungal BSIs are felt to be the most difficult to diagnose using standard technology, with a considerable percentage of patients dying from disseminated candidiasis noted to have persistently negative blood cultures in the premorbid state. It might be that only the most severe candidemias are detected by our current techniques, leading to an artificially high mortality compared with bacteria. Poor outcomes in any circumstance suggest that prompt, definitive treatment of candidemia is warranted. The multivariate analysis provides several additional factors that demonstrate an independent association with mortality in BSI. Not surprisingly, substantial premorbid predictors of mortality included chronic renal insufficiency (both cases requiring dialysis and not requiring dialysis), any pulmonary diagnosis, active malignancy, hepatic insufficiency, older patient age, an infected surgical site as the source of the BSI and higher APACHE II score. In essence, sicker people tend to die from underlying factors that cannot be changed. On the other hand, we found an association between blood transfusion and mortality. It has previously been suggested that blood cell⫺product transfusion is responsible for a blunted immune response.16-18 This might explain our finding that patients in our study who died were twice as likely to have received a blood cell⫺product transfusion, and suggest that more restrictive transfusion policies can decrease downstream morbidity and mortality. This study does exhibit some limitations. Fever was only assessed at the time of infection. Although this provides very useful data, more could be learned about the role of fever in BSI if temperature were tracked over time, from onset of infection to either resolution or death. In addition, many patients not included in this study who were febrile were never cultured, most notably those in the early postoperative period whose fever was attributed to “atelectasis.” The sensitivity and specificity of blood culture to detect BSI cannot be calculated. Despite these limitations, this study represents a critical view of a very large cohort of patients from a single institution over a 9-year period that suggest possible changes in clinical practice and additional study of this disease in a prospective manner.
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Author Contributions
Study conception and design: Pruett, Sawyer Acquisition of data: Hedrick, Popovsky, Sawyer Analysis and interpretation of data: Swenson, Hedrick, Pruett, Sawyer Drafting of manuscript: Swenson Critical revision: Swenson, Hedrick, Sawyer REFERENCES 1. Mackowiak PA, Browne RH, Southern PM Jr, Smith JW. Polymicrobial sepsis: an analysis of 184 cases using log linear models. Am J Med Sci 1980;280:73–80. 2. Lennard ES, Dellinger EP, Wertz MJ, Minshew BH. Implications of leukocytosis and fever at conclusion of antibiotic therapy for intra-abdominal sepsis. Ann Surg 1982;195:19–24. 3. Pfitzenmeyer P, Decrey H, Auckenthaler R, Michel JP. Predicting bacteremia in older patients. J Am Geriatr Soc 1995;43: 230–235. 4. Ryan M, Levy MM. Clinical review: fever in intensive care unit patients. Crit Care 2003;7:221–225. 5. McCabe WR, Treadwell TL, De Maria A Jr. Pathophysiology of bacteremia. Am J Med 1983;75:7–18. 6. Banet M. Fever in mammals: is it beneficial? Yale J Biol Med 1986;59:117–124. 7. Peres Bota D, Lopes Ferreira F, Melot C, Vincent JL. Body temperature alterations in the critically ill. Intensive Care Med 2004;30:811–816. 8. Barie PS, Hydo LJ, Eachempati SR. Causes and consequences of fever complicating critical surgical illness. Surg Infect (Larchmt) 2004;5:145–159. 9. Bryant RE, Hood AF, Hood CE, Koenig MG. Factors affecting mortality of gram-negative rod bacteremia. Arch Intern Med 1971;127:120–128. 10. Weinstein MP, Iannini PB, Stratton CW, Eickhoff TC. Spontaneous bacterial peritonitis. A review of 28 cases with emphasis on improved survival and factors influencing prognosis. Am J Med 1978;64:592–598. 11. Salo M, Eskola J. Immunosuppression after cholecystectomy. Acta Anaesthesiol Scand 1977;21:509–516. 12. Garner JS, Jarvis WR, Emori TG, et al. CDC definitions for nosocomial infections, 1988. Am J Infect Control 1988;16: 128–140. 13. Schulman CI, Namias N, Doherty J, et al. The effect of antipyretic therapy upon outcomes in critically ill patients: a randomized, prospective study. Surg Infect (Larchmt) 2005;6:369–375. 14. Gozzoli V, Schottker P, Suter PM, Ricou B. Is it worth treating fever in intensive care unit patients? Preliminary results from a randomized trial of the effect of external cooling. Arch Intern Med 2001;161:121–123. 15. Vaughn LK, Veale WL, Cooper KE. Effects of antipyresis on bacterial numbers in infected rabbits. Brain Res Bull 1981;7: 175–180. 16. Tartter PI. The association of perioperative blood transfusion with colorectal cancer recurrence. Ann Surg 1992;216:633–638. 17. Tartter PI. Blood transfusion and infectious complications following colorectal cancer surgery. Br J Surg 1988;75:789–792. 18. Triulzi DJ, Vanek K, Ryan DH, Blumberg N. A clinical and immunologic study of blood transfusion and postoperative bacterial infection in spinal surgery. Transfusion 1992;32:517–524.
Bloodstream infections (BSIs) are a prominent cause of morbidity and mortality among surgical patients.1 Fever is considered one of the chief warning signs of BSI and is often the impetus for additional investigation. Persistent fever despite therapy portends incomplete treatment.2 This said, not all BSIs are associated with fever.3 The question of whether the role of fever in major infections in the human is beneficial or detrimental is difficult to answer. Western medicine’s understanding of fever has been derived largely from in vitro and animal studies. Although these models are useful for mapping biochem-
ical and cellular pathways, there are serious limitations in the ability to extrapolate these results to humans.4-6 Human studies also have their disadvantages. Ethical boundaries largely limit clinical studies to observation and therapy trials. Published clinical studies have reported mixed results. Studies of septic human patients have identified fever as both a predictor of mortality7,8 and a predictor of survival.1,9,10 Surgical patients represent an interesting subset of the general medical population. The physiologic responses to operation, with the sizable inflammatory response and immunosuppression11 that accompanies operation, place surgical patients apart from the nonsurgical population. This study aims to evaluate the influence of fever on mortality in a large cohort of hospitalized surgical patients with BSI. Our starting hypothesis was that fever and accompanying leukocytosis during BSI would be associated with gram-negative pathogens, a more pronounced (and deleterious) inflammatory response, and worse outcomes.
Competing Interests Declared: None. Presented at the Southern Surgical Association 118th Annual Meeting, West Palm Beach, FL, December 2006. Received November 28, 2006; Accepted January 16, 2007. From the Department of Surgery, University of Virginia Health System, Charlottesville, VA. Correspondence address: Brian R Swenson, MD, Department of Surgery, University of Virginia Health System, PO Box 801380, Charlottesville, VA 22908-0300. email: [email protected]
© 2007 by the American College of Surgeons Published by Elsevier Inc.
815
ISSN 1072-7515/07/$32.00 doi:10.1016/j.jamcollsurg.2007.01.033
816
Swenson et al
Bloodstream Infections in Surgical Patients
J Am Coll Surg
Table 1. Demographics and Risk Factors Demographics and risk factors
Gender, n (%) Male Female Mean age (y) Race, n (%) Caucasian African American Hispanic Other Pretreatment comorbidities, n (%) Diabetes Cardiac disease Hypertension Peripheral vascular disease Cerebral vascular disease Chronic renal insufficiency* Dialysis dependence Pulmonary diagnosis Ventilator dependence† Active malignancy Hepatic insufficiency Chronic steroid use Psychiatric diagnosis Thyroid disorder Cell product transfusion‡ Location at time of infection, n (%) Home Ward ICU Other Mean WBC count (1,000 cells/L) Mean APACHE II score Mean modified APACHE II score§
Febrile (n ⴝ 541)
Afebrile (n ⴝ 282)
p Value
334 (61.7) 207 (38.3) 51.4
165 (58.5) 117 (41.5) 56.7
0.37 0.37 ⬍0.0001
440 (81.3) 82 (15.2) 10 (1.9) 9 (1.7)
231 (81.9) 47 (16.7) 2 (0.7) 2 (0.7)
0.84 0.57 0.20 0.26
87 (16.1) 83 (15.3) 157 (29.0) 17 (3.1) 16 (3.0) 19 (3.5) 52 (9.6) 47 (8.7) 238 (44.0) 71 (13.1) 15 (2.8) 52 (9.6) 43 (8.0) 25 (4.6) 364 (79.3)
66 (23.4) 65 (23.1) 107 (37.9) 12 (4.3) 8 (2.8) 17 (6.0) 41 (14.5) 46 (16.3) 110 (39.0) 39 (13.8) 16 (5.7) 30 (10.64) 17 (6.0) 16 (5.7) 158 (79.0)
0.010 0.0063 0.0092 0.41 0.92 0.094 0.034 0.0010 0.17 0.78 0.038 0.64 0.31 0.51 0.93
55 (10.2) 187 (34.6) 284 (52.5) 15 (2.8) 15.5 16.8 14.7
77 (27.3) 63 (22.3) 125 (44.3) 17 (6.0) 16.9 16.4 16.4
⬍0.0001 0.0003 0.026 0.022 0.57 0.49 0.0034
*Baseline serum creatinine ⱖ 2.0 mg/dL. † Before infection. ‡ Packed red blood cells or platelets transfused before initiation of treatment for infection. § APACHE II score with temperature contribution removed (for independent analysis of APACHE II score and fever). APACHE II, Acute Physiology and Chronic Health Evaluation II.
METHODS Study design
A prospective cohort of all patients admitted to the adult general surgery and trauma surgery services from December 1996 to December 2005 who were admitted with a BSI or in whom a BSI developed during their hospital stay were included in this study. During the 9-year study period, data were collected prospectively until patient discharge for all BSI episodes among ICU and non-ICU ward general and trauma surgery patients. Data were collected by chart review every
other day, and by patient examination, physician interview, review of pharmacy data, and laboratory and microbiologic data. Per the Centers for Disease Control and Prevention,12 BSI was defined as any specimen of blood drawn with sterile technique growing a bacteria or fungus, with the exception of cultures of coagulase-negative staphylococci, which required positive cultures from two different sites. Viremia was excluded. In cases where positive cultures from another nonblood site matched the organism grown from blood cultures, or if there was a concurrent intraabdominal or mixed skin/skin structure or surgical-site infection, the
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Table 2. Association Between Organism and Fever Febrile (n ⴝ 541) Organism/class
CNS/Staphylococcus epidermidis Staphylococcus aureus MRSA Enterococcus faecalis Candida albicans Pseudomonas aeruginosa Escherichia coli Streptococcus species Enterobacter cloacae Gram-positive Gram-negative Fungi Anaerobes
Afebrile (n ⴝ 282) %
n
%
n
195 64 29 56 38 21 26 16 26 400 146 62 21
36.0 11.8 5.4 10.4 7.0 3.9 4.8 3.0 4.8 73.9 27.0 11.5 3.9
76 30 15 24 20 21 11 20 8 187 90 29 14
27.0 10.6 5.3 8.5 7.1 7.4 3.9 7.1 2.8 66.3 31.9 10.3 5.0
p Value
0.015 0.65 0.99 0.43 0.94 0.025 0.57 0.0054 0.19 0.081 0.13 0.65 0.45
CNS, coagulase-negative Staphylococcus aureus; MSRA, methicillin-resistant Staphylococcus aureus.
BSI was considered secondary; if no concurrent infectious sources were identified, the BSI was considered primary. Episodes of infection were classified separately for a single patient if more than 72 hours apart. The Acute Physiology and Chronic Health Evaluation II (APACHE II) score was determined at the time of study entry as a measure of illness severity. Death before discharge was primary among outcomes measured. Variables recorded at study entry included maximum temperature in the first 24 hours of the infectious episode, age, gender, race, patient location at time of onset of infection (ICU, home, hospital ward), preinfection medical comorbidities (diabetes mellitus, cardiac disease, hypertension, peripheral vascular disease, cerebral vascular disease, chronic renal insufficiency not requiring dialysis, dialysis dependence, pulmonary disease, ventilator dependence, active malignancy, hepatic insufficiency, chronic steroid use, use of blood cell product transfusions [packed red
blood cells or platelets]), and peripheral white blood cell count. Statistical analysis
Data manipulation and statistical analysis were performed with SAS 9.1.3 (SAS Institute). Demographic, preinfection risk factors, infectious organisms, and BSI sources were tabulated and reported. Binary categorical variables were compared with chi-square analysis or Fisher’s exact test, and continuous variables were compared using Student’s t-test. Significance was considered p ⱕ 0.05. Characteristics and organisms with p ⱕ 0.1 from the univariate analysis were included in a logistic regression analysis with in-hospital mortality among outcomes. In the analysis here, each BSI was treated as a separate episode; several patients had more than one nonconcurrent BSI. When the same analysis was performed using a
Table 3. Concurrent Infectious Sources Source
Primary BSI† Secondary BSI Peritoneum Intravascular device Pulmonary Urinary tract Surgical site Skin/skin structure All other sources
n
%*
n
464 359 157 119 76 46 13 9 20
56.4 43.6 19.1 14.5 9.2 5.6 1.6 1.1 2.4
76 72 33 25 21 14 5 0 4
In-hospital mortality %
16.4 20.1 21.0 21.0 27.6 30.4 38.5 0.0 20.0
*Proportion of patients with the listed source of BSI, with the exception of primary BSI patients, can have multiple sources. † BSI in the absence of a concurrent matching culture from another location. BSI, bloodstream infection.
p Value
0.17 0.17 0.27 0.35 0.022 0.024 0.053 0.16 0.81
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Table 4. The Association Between Bloodstream Isolates and Mortality
BSI organism/class
Candida albicans Pseudomonas aeruginosa Streptococcus spp CNS/Staphylococcus epidermidis Enterobacter cloacae Staphylococcus aureus MRSA Escherichia coli Enterococcus faecalis Fungi Anaerobes Gram-negative Gram-positive
In-hospital mortality (%)
Survived (n ⴝ 675)
Died (n ⴝ 148)
n
%
n
%
p Value
32.8 26.2 19.4
39 31 29
5.8 4.6 4.3
19 11 7
12.8 7.4 4.7
0.0027 0.16 0.82
15.9 11.8 11.7 11.4 10.8 10.0 27.5 20.0 19.7 16.2
228 30 83 39 33 72 66 28 188 490
33.8 4.4 12.3 5.8 4.9 10.7 9.8 4.1 27.9 72.6
43 4 11 5 4 8 25 7 46 95
29.1 2.7 7.4 3.4 2.7 5.4 16.9 4.7 31.1 64.2
0.039 0.33 0.087 0.24 0.24 0.051 0.014 0.76 0.47 0.72
BSI, bloodstream infection; CNS, coagulase-negative Staphylococcus aureus; MRSA, methicillin-resistant Staphylococcus aureus.
subset of observations, which limited the contribution of each patient to their first BSI, similar results were obtained.
RESULTS One thousand eighty surgical patients at the University of Virginia Health System were diagnosed with BSI between December 10, 1996 and December 21, 2005. Two hundred fifty-four transplantation patients were excluded because of immunosuppression therapy, and 3 were excluded for blood cultures that grew a viral organism, leaving 823 separate BSI episodes in 619 patients for analysis. Descriptions of the demographic and preinfection risk factors for febrile and afebrile patients are listed in Table 1. Of the included patients, 541 (65.7%) met criteria for fever (maximum temperature during the first 24 hours of the infectious episode ⱖ 38.5°C), and 282 (34.3%) did not. Fever incidence did not appear to be associated with mean white blood cell count or APACHE II score. A modified APACHE II score, with the temperature contribution deducted, was compared between groups and, not surprisingly, showed a statistically significant difference, with the febrile group demonstrating lower modified APACHE II scores (14.7 versus 16.4, p ⫽ 0.0034). Table 2 presents BSI pathogens by incidence and fever proportion. Although coagulase-negative staphylococci/ Staphylococcus epidermidis was notably more likely to be found in febrile patients (36.0% versus 27.0%, p ⫽ 0.015) and Pseudomonas aeruginosa (3.9% versus 7.4%, p ⫽ 0.025) and Streptococcus species (3.0% versus 7.1%, p ⫽ 0.0054) were more common in afebrile patients, no spe-
cific class of pathogens (gram-negative, gram-positive, or fungal) were markedly associated with fever. Primary and secondary BSIs are described in Table 3. Four hundred sixty-four or 56.4% of BSIs did not have the same pathogen isolated from another source and were considered primary BSIs. Three hundred fifty-nine or 43.6% of BSIs occurred simultaneously with an infection from another source with the same organism. The most commonly identified sources of secondary BSIs were peritoneum, intravascular device, and pulmonary, although the highest mortality was associated with surgical-site infections (38.5%). The association between the most common BSI isolates and mortality is outlined in Table 4. Candida albicans was associated with the highest mortality (raw rate 32.8%, relative risk [RR] ⫽ 2.2, p ⫽ 0.0027). Likewise, when organism classes were compared, fungi exhibited the highest mortality (raw rate 27.5%, RR ⫽ 1.7, p ⫽ 0.014) when compared with gram-positive or gramnegative organisms. Infection with coagulase-negative staphylococci/epidermidis was associated with survival (RR ⫽ 0.86, p ⫽ 0.039). The univariate analyses comparing the association between demographics, preinfection risk factors, and physiologic parameters at the time of infection and mortality are summarized in Table 5. Characteristics and organisms with statistical significance or near significance (p ⱕ 0.1) from the univariate analysis were included in the logistic regression model, with results reported in Table 6. Factors with an independent association with mortality included maximum temperature as a continuous variable, baseline serum creatinine ⱖ 2.0 mg/dL, dialysis dependence, pulmonary
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Table 5. Univariate Analysis of the Influence of Risk Factors on Mortality
Risk factors
Fever (temperature ⱖ 38.5°C)† Gender Male Female Race Caucasian African American Hispanic Other Pretreatment comorbidities‡ Diabetes Cardiac disease Hypertension Peripheral vascular disease Cerebral vascular disease Chronic renal insufficiency§ Dialysis dependence Pulmonary diagnosis Ventilator dependence Active malignancy Hepatic insufficiency Chronic steroid use Cell product transfusion储 Location at time of infection Home Ward ICU Other WBC count ⱖ 15,000 cells/L Mean age (y) Mean APACHE II score
In-hospital mortality (%)*
Survived (n ⴝ 675; 82.0%)
Died (n ⴝ 148; 18.0%)
p Value
12.9
471 (69.8)
70 (47.3)
⬍0.0001
17.8 18.2
410 (60.7) 265 (39.3)
89 (60.1) 59 (39.9)
0.89 0.89
18.3 16.3 0.0 36.4
548 (81.2) 108 (16.0) 12 (1.8) 7 (1.0)
123 (83.1) 21 (14.2) 0 (0.0) 4 (2.7)
0.59 0.58 0.10 0.11
23.5 34.5 20.5 34.5 25.0 50.0 34.4 41.9 24.4 29.1 41.9 26.8 22.8
117 (17.3) 97 (14.4) 210 (31.1) 19 (2.8) 18 (2.7) 18 (2.7) 61 (9.0) 54 (8.0) 263 (39.0) 78 (11.6) 18 (2.7) 60 (8.9) 403 (59.7)
36 (24.3) 51 (6.2) 54 (36.5) 10 (6.8) 6 (4.1) 18 (12.2) 32 (21.6) 39 (26.4) 85 (57.4) 32 (21.6) 13 (8.8) 22 (14.9) 119 (80.4)
0.048 ⬍0.0001 0.20 0.019 0.36 ⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001 0.0011 0.0004 0.028 0.0005
7.6 13.2 23.5 28.1 19.1 — —
122 (18.1) 217 (32.2) 313 (46.4) 23 (3.4) 326 (48.3) 50.7 15.4
10 (6.8) 33 (22.3) 96 (64.9) 9 (6.1) 77 (52.0) 64.4 22.7
0.0007 0.018 ⬍0.0001 0.13 0.41 ⬍0.0001 ⬍0.0001
Values in parentheses are percentages. *Proportion of patients with the listed risk factor who died while in the hospital. † Maximum temperature recorded during the first 24 h of treatment. ‡ Before infection. § Baseline serum creatinine ⱖ 2.0 mg/dL. 储 Packed red blood cells and/or platelets transfused before initiation of treatment for infection. APACHE II, Acute Physiology and Chronic Health Evaluation II.
diagnosis, active malignancy, hepatic insufficiency, cellular blood product transfusion, age as a continuous variable, APACHE II score as a continuous variable, and surgical site as the BSI infection source (odds ratio ⫽ 5.2, p ⫽ 0.045).
DISCUSSION In contrast to our initial hypothesis, we found that fever within the first 24 hours of BSI was a powerful independent predictor of survival. Leukocytosis appeared to have no influence on survival. This study can be added to other studies that have found fever to be protective in sepsis.1,9,10
Although strongly suggesting the association between fever and survival, our study design does not allow us to draw firm conclusions as the biologic explanation for these findings. Two theories are suggested: The role of fever in the immune response is intrinsically protective and serves to lessen the impact of the infection on the body as a whole, conveying a survival advantage; or fever is reactionary, and its presence can be viewed as an indicator of the body’s physiologic reserves, suggesting that the absence of a febrile response indicates either a weakened premorbid state or an overwhelming infection of such magnitude that the normal
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Table 6. Logistic Regression Analysis of the Influence of Risk Factors on Mortality Risk factor
Maximum temperature (per °C) Pretreatment comorbidities Diabetes Cardiac disease Peripheral vascular disease Chronic renal insufficiency Dialysis dependence Pulmonary diagnosis Ventilator dependence Active malignancy Hepatic insufficiency Chronic steroid use Cell product transfusion Location at time of infection Home Ward ICU Age (per y) APACHE II score (per point) BSI organism CNS/Staphylococcus epidermidis Enterococcus faecalis Candida albicans BSI source Pulmonary Urinary tract Surgical site
Odds ratio
95% CI
p Value
0.596
0.470–0.756
⬍0.0001
1.496 1.474 1.647 3.967 2.220 3.961 1.310 2.593 3.809 1.038 2.099
0.860–2.604 0.816–2.662 0.554–4.894 1.475–10.665 1.129–4.365 2.053–7.643 0.635–2.705 1.347–4.994 1.440–10.070 0.508–2.118 1.020–4.319
0.15 0.20 0.37 0.0063 0.021 ⬍0.0001 0.47 0.0044 0.0070 0.92 0.044
0.277 0.563 0.796 1.048 1.100
0.070–1.103 0.162–1.958 0.243–2.610 1.028–1.680 1.060–1.141
0.069 0.37 0.71 ⬍0.0001 ⬍0.0001
0.874 0.411 2.063
0.511–1.494 0.166–1.014 0.932–4.565
0.62 0.054 0.074
1.333 1.889 5.239
0.646–2.748 0.774–4.609 1.038–26.438
0.44 0.16 0.045
c statistic ⫽ 0.889 APACHE II, Acute Physiology and Chronic Health Evaluation II; BSI, bloodstream infection; CNS, coagulase-negative Staphylococcus aureus.
physiologic response is preempted. These theories need not be mutually exclusive, and given the complexity of the acute phase response and critically ill patients in general, it is quite possible that elements of both mechanisms are at work in BSI. Another common theory of fever, not observed in this study, is the relationship between gram-negative organisms and fever, based on the presence of endotoxin in these pathogens in contrast to gram-positive pathogens or fungi. We found no difference in fever rates with gram-negative organism and, in fact, we found that infection with P aeruginosa, was statistically associated with absence of fever. In contrast, the most common infecting organism, S epidermidis, was statistically associated with a higher likelihood of fever. Even if the question of fever’s true role in BSI cannot be precisely defined, several clinical points can be taken from this study. Although sensitive for BSI, fever is not specific and its absence is not at all reassuring. The common temperature threshold of 38.5°C for blood culture might need
to be reconsidered. A high index of suspicion should be maintained in treating critically ill patients, and any patient displaying symptoms or abnormal physiology that could potentially be from sepsis should be considered for blood cultures in the absence of an elevated temperature. Although a more-aggressive diagnostic stance would presumably lead to earlier diagnosis of BSI in afebrile patients and higher survival, this remains unproven and would predictably lead to a larger number of false-positive blood cultures. In addition, the exact trigger for acquisition of blood cultures remains entirely undefined. For example, the likelihood that an elevation in WBC count would be any more precise in this regard is limited, given our experience. Perhaps a less-traditional marker, such as procalcitonin or circulating interleukin-6 might eventually prove to be beneficial. The common practice of treating a fever with antipyretics has previously been called into question.13-15 The data presented in this study do not support this practice and we would advocate leaving reasonable temperature elevations
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untreated in patients without substantial discomfort related to fever until additional data accumulates suggesting suppression of the febrile response is clinically beneficial. Although no individual organisms reached statistical significance as independent predictors of mortality in the multivariate analysis, we should not understate the apparent virulence of fungal BSI. Fungi demonstrated the highest mortality of any organism class at 27.5% and C albicans had the highest mortality of any specific organism at 32.8%. Traditionally, fungal BSIs are felt to be the most difficult to diagnose using standard technology, with a considerable percentage of patients dying from disseminated candidiasis noted to have persistently negative blood cultures in the premorbid state. It might be that only the most severe candidemias are detected by our current techniques, leading to an artificially high mortality compared with bacteria. Poor outcomes in any circumstance suggest that prompt, definitive treatment of candidemia is warranted. The multivariate analysis provides several additional factors that demonstrate an independent association with mortality in BSI. Not surprisingly, substantial premorbid predictors of mortality included chronic renal insufficiency (both cases requiring dialysis and not requiring dialysis), any pulmonary diagnosis, active malignancy, hepatic insufficiency, older patient age, an infected surgical site as the source of the BSI and higher APACHE II score. In essence, sicker people tend to die from underlying factors that cannot be changed. On the other hand, we found an association between blood transfusion and mortality. It has previously been suggested that blood cell⫺product transfusion is responsible for a blunted immune response.16-18 This might explain our finding that patients in our study who died were twice as likely to have received a blood cell⫺product transfusion, and suggest that more restrictive transfusion policies can decrease downstream morbidity and mortality. This study does exhibit some limitations. Fever was only assessed at the time of infection. Although this provides very useful data, more could be learned about the role of fever in BSI if temperature were tracked over time, from onset of infection to either resolution or death. In addition, many patients not included in this study who were febrile were never cultured, most notably those in the early postoperative period whose fever was attributed to “atelectasis.” The sensitivity and specificity of blood culture to detect BSI cannot be calculated. Despite these limitations, this study represents a critical view of a very large cohort of patients from a single institution over a 9-year period that suggest possible changes in clinical practice and additional study of this disease in a prospective manner.
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Author Contributions
Study conception and design: Pruett, Sawyer Acquisition of data: Hedrick, Popovsky, Sawyer Analysis and interpretation of data: Swenson, Hedrick, Pruett, Sawyer Drafting of manuscript: Swenson Critical revision: Swenson, Hedrick, Sawyer REFERENCES 1. Mackowiak PA, Browne RH, Southern PM Jr, Smith JW. Polymicrobial sepsis: an analysis of 184 cases using log linear models. Am J Med Sci 1980;280:73–80. 2. Lennard ES, Dellinger EP, Wertz MJ, Minshew BH. Implications of leukocytosis and fever at conclusion of antibiotic therapy for intra-abdominal sepsis. Ann Surg 1982;195:19–24. 3. Pfitzenmeyer P, Decrey H, Auckenthaler R, Michel JP. Predicting bacteremia in older patients. J Am Geriatr Soc 1995;43: 230–235. 4. Ryan M, Levy MM. Clinical review: fever in intensive care unit patients. Crit Care 2003;7:221–225. 5. McCabe WR, Treadwell TL, De Maria A Jr. Pathophysiology of bacteremia. Am J Med 1983;75:7–18. 6. Banet M. Fever in mammals: is it beneficial? Yale J Biol Med 1986;59:117–124. 7. Peres Bota D, Lopes Ferreira F, Melot C, Vincent JL. Body temperature alterations in the critically ill. Intensive Care Med 2004;30:811–816. 8. Barie PS, Hydo LJ, Eachempati SR. Causes and consequences of fever complicating critical surgical illness. Surg Infect (Larchmt) 2004;5:145–159. 9. Bryant RE, Hood AF, Hood CE, Koenig MG. Factors affecting mortality of gram-negative rod bacteremia. Arch Intern Med 1971;127:120–128. 10. Weinstein MP, Iannini PB, Stratton CW, Eickhoff TC. Spontaneous bacterial peritonitis. A review of 28 cases with emphasis on improved survival and factors influencing prognosis. Am J Med 1978;64:592–598. 11. Salo M, Eskola J. Immunosuppression after cholecystectomy. Acta Anaesthesiol Scand 1977;21:509–516. 12. Garner JS, Jarvis WR, Emori TG, et al. CDC definitions for nosocomial infections, 1988. Am J Infect Control 1988;16: 128–140. 13. Schulman CI, Namias N, Doherty J, et al. The effect of antipyretic therapy upon outcomes in critically ill patients: a randomized, prospective study. Surg Infect (Larchmt) 2005;6:369–375. 14. Gozzoli V, Schottker P, Suter PM, Ricou B. Is it worth treating fever in intensive care unit patients? Preliminary results from a randomized trial of the effect of external cooling. Arch Intern Med 2001;161:121–123. 15. Vaughn LK, Veale WL, Cooper KE. Effects of antipyresis on bacterial numbers in infected rabbits. Brain Res Bull 1981;7: 175–180. 16. Tartter PI. The association of perioperative blood transfusion with colorectal cancer recurrence. Ann Surg 1992;216:633–638. 17. Tartter PI. Blood transfusion and infectious complications following colorectal cancer surgery. Br J Surg 1988;75:789–792. 18. Triulzi DJ, Vanek K, Ryan DH, Blumberg N. A clinical and immunologic study of blood transfusion and postoperative bacterial infection in spinal surgery. Transfusion 1992;32:517–524.