44 Original article
Prediction of bacteremia in the emergency department: an external validation of a clinical decision rule Marie K. Jessena,e, Julie Mackenhauera, Anne Mette S.W. Hvassb, Svend Ellermann-Eriksenc, Simon Skibsteda,e, Hans Kirkegaarda, Henrik C. Schønheyderd and Nathan I. Shapiroe; CONSIDER Sepsis Network Objective The objective of this study was to validate a previously published clinical decision rule for predicting a positive blood culture in emergency department (ED) patients with suspected infection on the basis of major and minor criteria and a total score (Shapiro et al., J Emerg Med, 2008; 35:255–264). Methods This is a retrospective matched cohort study of adult ED patients with blood cultures obtained from 1 January 2011 through to 31 December 2011. ED patients with blood culture-confirmed bacteremia were matched 1 : 3 with patients with negative cultures. The outcome was ‘true bacteremia’. Data on clinical history, comorbid illnesses, physical observations, and laboratory tests were used to evaluate the application of the clinical decision rule. We report the sensitivity, specificity, and area under the curve. Results Among 1526 patients, 105 (6.9%) patients were classified with true bacteremia. The sensitivity of the prediction rule was 94% (95% confidence interval, 88–98%) and the specificity was 48% (95% confidence interval,
Introduction Bacteremia is a common clinical condition with an incidence rate of ∼ 140–160 per 100 000 person-years [1,2]. The clinical spectrum ranges from the innocuous to severe sepsis and septic shock, with mortality rates of 25–50% [3–5]. Identification of emergency department (ED) patients likely to have bacteremia is therefore important. Positive blood cultures confirm the presence of viable bacteria or fungi in the bloodstream and provide the opportunity to optimize the antibiotic treatment and draw attention to possible underlying foci of infection. Blood cultures in the ED tend to be obtained on the basis of clinical judgment and are normally taken before initiation of empiric antibiotic therapy. Guidelines for Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website (www.euro-emergencymed.com). Members of CONSIDER Sepsis Network besides all the authors mentioned in the author group of the paper: Rita Andersen Leth, MPH, PhD; Christian Fynbo Christiansen, MD, PhD; Helle Lykkeskov Nibro, MD, PhD; Lotte Ebdrup, MD, PhD; Kimie Ødorf, BSc; Nicolaj Duus, MD; Betina Hansen, MD; Else Tønnesen, MD, PhD, Dr.Med. The work described in the manuscript has been presented as a poster at Sepsis 2013, ISF’s 6th Annual Symposium, Rio de Janeiro, Brazil, 5–6 November 2013. 0969-9546 Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.
42–53%). The area under the receiver-operating characteristics curve was 0.83. Conclusion The clinical decision rule performed well in our ED setting and is likely to be a useful supplement to clinical judgment. European Journal of Emergency Medicine 23:44–49 Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved. European Journal of Emergency Medicine 2016, 23:44–49 Keywords: bacteremia, clinical prediction rule, emergency department, infectious diseases a
Research Center for Emergency Medicine, Departments of bInfectious Diseases, Clinical Microbiology, Aarhus University Hospital, Aarhus, dDepartment of Clinical Microbiology, Aalborg University Hospital, Aalborg, Denmark and eDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA c
Correspondence to Marie K. Jessen, BSc, Research Center for Emergency Medicine, Aarhus University Hospital, Nørrebrogade 44, building 30, 1st floor, 8000 Aarhus C, Denmark Tel: + 45 7846 1073; fax: +45 7846 2720; e-mail: [email protected] Received 2 April 2014 Accepted 8 August 2014
obtaining blood cultures are sparse and differ among institutions, and ultimately the decision is left to the clinical team, although there is a tendency to overestimate the risk for bacteremia [6,7]. As a result, only 4–8% of blood cultures are ‘true positives’ [8]. In addition, a varying percentage of blood cultures yield microorganisms subsequently classified as contaminants. Depending on the circumstances, contaminated blood cultures may lead to unnecessary antibiotic treatment, increased length of stay, and high expenses for the healthcare system [9,10]. The escalation of antibiotic resistance globally emphasizes the importance of avoiding spurious information from blood cultures [11]. A precise prediction and decision rule for bacteremia among ED patients admitted with suspected infection can be instrumental in reaching this goal. In a prior publication, a clinical decision rule developed by Shapiro et al. [12] demonstrated high sensitivity for the identification of patients unlikely to have bacteremia. They included the following minor criteria: age greater than 65 years, temperature 38.8–39.3°C, chills, vomiting, hypotension, white blood cell count greater than 18 000 cells × 109/l, platelets less than 150 000 cells × 109/l, and creatinine level greater than 177 μmol/l (2.0 mg/dl), and DOI: 10.1097/MEJ.0000000000000203
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Prediction of bacteremia in the ED Jessen et al. 45
Table 1
Decision rule
Major criteria
Minor criteria (1 point each)
Suspected endocarditis (3 points) Temperature > 39.4°C (103.0°F) (3 points) Indwelling vascular catheter (2 points)
Age > 65 years Temperature 38.3–39.3°C Chills Vomiting Hypotension (systolic blood pressure < 90 mmHg) White blood cell count > 18 000 cells × 109/l Bands > 5% (in our setting immature cells > 0.5%) Platelets < 150 000 cells × 109/l Creatinine > 177 µmol/l (2.0 mg/dl)
As per the rule, a blood culture is indicated if at least one major criterion or two minor criteria are present. Otherwise, cultures may be omitted.
the following major criteria: suspicion of endocarditis, temperature greater than 39.4°C, and the presence of indwelling catheters. A blood culture is indicated by the rule if at least one major criterion or two minor criteria are fulfilled (Table 1). In a recent review of prediction rules for bacteremia, this rule was endorsed as promising and was suggested as a better negative predictor of bacteremia than a predictor of the overall clinical impression [13]. Although endorsing the rule, the review also indicated that further validation was needed. The aim of this study was to externally validate the decision rule for predicting a positive blood culture.
Materials and methods Study design and population
This retrospective cohort study included patients presenting to a large urban academic tertiary ED at Aarhus University Hospital, Denmark, with ∼ 56 000 patient visits annually. Eligible patients were identified through a blood culture log recorded in the Laboratory Information System at the Department of Clinical Microbiology, Aarhus University Hospital. The decision to obtain the blood culture was made independently by the patient’s medical care providers, and a certified laboratory technician performed the blood draw. The following patients were eligible for the study: adult ED patients (age > 18 years) with a valid Danish Civil Personal Registration number, who had a blood culture performed in the ED between 1 January 2011 and 31 December 2011. Only the first presentation with blood cultures drawn was included. All permanent residents of Denmark are provided with tax-supported healthcare free of charge from an assigned GP and public hospitals. The assigned Civil Personal Registration number is used for all healthcare contacts and permits unambiguous record linkage to all Danish health registries [14]. The Danish National Patients Register (DNPR) has been used to track all admissions to nonpsychiatric
hospitals in Denmark since 1977, recording dates of admission and discharge, and up to 20 discharge diagnoses. This study was approved by the Danish Data Protection Agency (No. 1-11-02-102-11) and by the Danish Health and Medicines Authority (j.nr.3-3013-221/1). Approval from an ethics committee was not required for this observational study according to Danish law. Demographics and clinical covariates
A combination of physicians’ and nurses’ electronic and written medical records was used to confirm eligibility and fulfillment of major and minor criteria for the blood culture prediction rule (Table 1). Data abstraction was performed by trained study personnel using Filemaker Pro 12 (Filemaker Inc., Santa Clara, California, USA). Charts were reviewed to determine the presence of chills and vomiting, the worst vital signs within 4 h of admission [rectal body temperature (Rectal thermometer, Terumo, Leuven, Belgium) and blood pressure], and the presence of indwelling vascular catheters. Chills were considered present if noted in the chart; otherwise, they were considered absent. Laboratory data included blood leukocyte count, percentage of neutrophils and immature cells, platelet count, and plasma creatinine level. In our setting, we defined bandemia as a ratio greater than 0.5% between the counts of immature neutrophils (metamyelocytes, myelocytes, and promyelocytes) and white blood cells; hence, we used this as the discriminatory level instead of greater than 5% band cells. Calculating bandemia required a complete blood count with a complete differential performed using flow cytometry (Sysmex America Inc., Lincolnshire, Illinois, USA). The source of suspected focal infection was classified on the basis of the physicians’ admission notes, including suspicion of endocarditis. To assess comorbidity, we used the comorbidity index developed by Charlson et al. [15]. The Charlson index score was calculated for each patient based on discharge diagnoses recorded in the DNPR. Bacteremia
Each patient had one to three sets (two to six bottles) of blood cultures, each comprising one aerobic and one anaerobic bottle with a nominal blood sample volume of 10 ml per bottle (BacT/Alert; bioMérieux, Marcy l’Etoile, France). Positive blood cultures were unloaded at fixed time points and examined immediately by Gram staining. Subculturing, identification, and susceptibility testing were carried out using standard methods [16]. Blood culture bottles were incubated for up to 5.7 days [17]. The patient’s clinical team was notified about the Gram staining report over the telephone by a medical staff member at the Department of Clinical Microbiology, making it possible to interpret the significance of the positive blood culture in the clinical context. As soon as a
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46 European Journal of Emergency Medicine 2016, Vol 23 No 1
tentative identification and the antibiotic susceptibility pattern of the isolate(s) were obtained, a second notification was made either to confirm or adjust antibiotic treatment. In the case of likely contamination, this would be communicated in the same manner. Outcomes
Our primary outcome was ‘true bacteremia’, defined as bacterial or fungal growth in blood cultures deemed to have an etiological role on the basis of joint clinical and microbiological assessment. All blood culture isolates Table 2
Patient characteristics Bacteremia (n = 105)
Demographics Age [median, mean (SD)] 77, 71.2 (17) (years) Male sex (%) 50.5 Comorbidities Charlson index score 1, 1.7 (2) [median, mean (SD)] Cerebrovascular disease 21.0 (%) Congestive heart failure 10.5 (%) Human immunodeficiency 1 virus (%) Malignancy (%) 15.2 Diabetes (%) 12.4 Clinical covariates [median, mean (SD)] Systolic blood pressure 123, 123 (30) (mmHg) Initial temperature (°C) 38.7, 38.6 (1) 12.3, 13.9 (8) White blood count 9 (cells × 10 /l) Neutrophil% 88, 85 (12) Immature cell% 0.07, 0.2 (0.4) Platelets (cells × 109/l) 210, 214 (106) Plasma creatinine (μmol/l) 107, 186 (203) Vomiting (%) 27.6 Chills (%) 14.3 Indication of culture Suspected focal infection 61.9 (%) Fever (without source) (%) 16.2 Suspected endocarditis 2.9 (%) Other/unknown (%) 19.0 Suspected infectious foci (%) Unknown 36.1 Pneumonia 25.7 Urinary tract infection/ 25.7 pyelonephritis Intra-abdominal 1.9 Skin and soft tissue 3.8 Meningitis 2.8 Endocarditis 1.9 c 1.1 Other Noninfectiousd 1.0 Length of stay [median, mean 9.6, 14.8 (19) (SD)] (days) Time to culture [median, 53, 104 (197) mean (SD)] (min) In-hospital mortality (%) 14.3 a
Nonbacteremia (n = 315)
P-value
65, 62.5 (20)
< 0.001a
41.4
0.10b
1, 1.4 (2)
0.09a
9.8
0.03b
9.5
0.78b
0
0.56b
13.0 12.7
0.56b 0.93b
130, 132 (28)
0.004a
37.8, 37.8 (1) 10.4, 11.6 (6)
< 0.001a 0.002a
78, 76 (11) 0.04, 0.1 (0.3) 249, 272 (122)
< 0.001a < 0.001a < 0.001a
77, 93 (75) 17.8 10.8
< 0.001a 0.03b 0.33b
60.6 8.3 0.3 30.8 29.5 28.6 8.9
c
Data analysis
Means with SDs, medians, and proportions were used for descriptive statistics, as appropriate. All univariate relationships were examined using a t-test, χ2-test, or Wilcoxon’s rank sum test, as appropriate. Sensitivity and specificity were calculated with binomial 95% confidence intervals (CIs), and the area under the receiver-operating characteristic curve was calculated using the point score given by the rule. Statistical analysis was carried out using STATA 12.0 (StataCorp, College Station, Texas, USA).
Results Population characteristics
During the 1-year study period, a total of 2562 blood culture sets were obtained in the ED from 1578 patients; of these, 1526 met the inclusion criteria. A total of 105 patients (6.9%) had true bacteremia. Fifty (3.3%) had ‘definitely contaminated’ blood cultures, whereas 11 (0.7%) had ‘possible contaminations’ and were all regarded as negative blood cultures. The ‘true bacteremia’ patients were matched with 315 patients with negative blood cultures. The demographics and characteristics of patients, clinical, physiological, and laboratory values, as well as suspected infectious foci are reported in Table 2, stratified by the presence or absence of true bacteremia.
Calculating a total point score for each patient from minor and major criteria, the sensitivity of the prediction rule was 94% (95% CI 88–98%) and specificity 48% (95% CI 42–53%) (Table 3). The area under the receiveroperating characteristic curve was 0.83. < 0.001a
52, 119 (262)
0.45a 0.002b
Student’s t-test. χ -test. Other includes biliary tract infections, indwelling catheter, perforated organs, etc. d No suspicion of infection mentioned in the chart but blood culture obtained. b 2
Patients with true bacteremia were matched at random with patients with either no growth or a growth classified as a true contamination or a possible contamination in the proportion 1 : 3.
Performance of the prediction rule
8.9 10.5 0.6 0.3 4.1 8.6 3.6, 6.4 (9)
5.1
were classified prospectively as being either (i) ‘true bacteremia’, (ii) ‘definite contamination’, or (iii) ‘possible contamination’. In accordance with Weinstein et al. [18] coagulase-negative Staphylococci spp., Corynebacterium spp., Bacillus spp., and Propionibacterium acnes were considered as ‘definite contaminants’, unless they were isolated from two or more separate blood culture sets, and they were considered as ‘true bacteremia’ or ‘possible contamination’ if two of four bottles were positive with the abovementioned bacteria. Polymicrobial bacteremia was defined according to Roberts [19].
Positive and negative predictive values are shown in Appendix 1 (Supplemental digital content 1, http://links. lww.com/EJEM/A81), calculated using the prevalence of bacteremia in the entire population. Patients missed by the prediction rule
The clinical circumstances of the six patients who could have been missed by the rule are summarized in Table 4.
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Prediction of bacteremia in the ED Jessen et al. 47
Table 3
Application of the decision rule
found the sensitivity to perform better than past reports on clinical judgment alone [6,7].
Decision rule fulfilled Blood culture
Yes
No
In total
Positive Negative In total
99 165 264
6 150 156
105 315 420
Estimation of sensitivity and specificity. Results are expressed along with 95% confidence interval sensitivity, 94% (88–98%); specificity, 48% (42–53%).
For two patients (patients 2 and 6), the culture resulted in initiation or change of antibiotic therapy. For patients 1, 2, and 4, the initial antibiotic provided appropriate coverage, whereas patient 3 recovered without antibiotic therapy. Two of the patients (patients 2 and 4) deteriorated in condition during admission day 1, which would have triggered a blood culture by the rule. Both patients recovered with antibiotic therapy. Microbiologic diagnosis
Of the 1526 blood cultures drawn, 4.6% were considered contaminated (false positive). Of the 105 patients with true bacteremia, 55 (52%) cases were due to gramnegative bacteria, 41 (39%) due to gram-positive bacteria, and nine (9%) patients had polymicrobial bacteremia (Appendix 2, Supplemental digital content 2, http:// links.lww.com/EJEM/A82 ).
Discussion In this retrospective cohort study we validated a clinical prediction rule that successfully stratified ED patients according to the likelihood of bacteremia. The result suggests the rule to have the ability to aid the ED physicians in making a rapid bedside estimation of bacteremia risk, thereby supplementing clinical judgment. Of note, in our cohort from Aarhus University Hospital, we Table 4 Patient number
Even when applying a clinical decision rule to a group of patients, good clinical judgment should still be used. Thus, the rule should sometimes be overridden in certain low-risk patients with clinical risk factors to avoid providing inappropriate treatment to patients. Among the patients missed by the rule, only two patients had meaningful changes: (i) cefuroxime, ciprofloxacin, and metronidazole were changed to meropenem because of the detection of Salmonella spp. resistant to cefuroxime and gentamicin, and (ii) initiation of penicillin after verification of Pneumococci spp. growth in the blood culture (Table 4). Thus, in total, there were two patients in the entire population who could have potentially been compromised by application of the rule. This needs to be weighed against the need to ration care at some level, with Departments of Clinical Microbiology receiving increasing numbers of blood cultures exceeding their capacity. It could be even more important that the clinical prediction rule could also be used to identify patients who were at a high risk for bacteremia and therefore could benefit from aggressive empiric antibiotic treatment, in accordance with recent studies linking improved survival with early empiric antibiotic coverage in patients with bacteremia [20]. The fact that the treating physician was contacted by a member of the medical staff of the Department of Clinical Microbiology to discuss and interpret the significance of the blood culture in the clinical context probably minimized costs and unnecessary antibiotic treatment due to false-positive blood cultures or contaminations. However, we lacked specific data on this topic. Prior studies have been performed in the inpatient setting to identify predictors of bacteremia [8,21–24].
Patients missed by the decision rule Clinical circumstances
Outcome
1
87-year-old, unknown site of infection, dizziness, temperature 37.8°C
2
45-year-old man, hepatic encephalopathy, platelets 59 × 109 l, BP decreased at admission day 1 to 79/50 mmHg, creatinine increased to 165 μmol/l 85-year-old woman, diarrhea
Pansensitive Staphylococcus hominis, antibiotic (dicloxacillin) started at admission Salmonella spp. resistant to cefuroxime and gentamicin, antibiotics (cefuroxime, ciprofloxacin, and metronidazole) started when BP decreased and changed to meropenem after growth verification Campylobacter spp. Patient improved without antibiotics. Resistance pattern not described. Pansensitive nonhemolytic Streptococci spp., continued initial antibiotics (cefuroxime) with good response Pansensitive Escherichia coli, piperacillin–tazobactam ordered on admission day 2, no change in antibiotics Pansensitive Pneumococci spp.; penicillin initiated following these culture results
3 4 5 6
96-year-old man, admitted unconscious, verified pneumonia. Temperature increased to 38.6°C. Do not resuscitate 56-year-old man, UTI, because of psychiatric reasons not possible to obtain vital signs; hence, not counted in the rule 65-year-old woman, painful legs, subjective fever at home (not measured), verified endocarditis but no suspicion at admission
This table shows the clinical circumstances in patients with positive blood cultures that would have been missed by the decision rule. Only in patients 2 and 6 were there meaningful changes in antibiotics. Patient 6 had a subjective fever at home but was not counted in rule. The conditions of patients 2 and 4 deteriorated, which would have been an indication for culture. Other patients either had a benign course or responded to their initial empiric antibiotic therapy. BP, blood pressure; UTI, urinary tract infection.
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48 European Journal of Emergency Medicine 2016, Vol 23 No 1
Bates et al. [8] developed and validated a prediction rule for bacteremia in hospitalized patients with an area under the curve of 0.71 and 0.69 in the derivation and the validation set, respectively. Their rule included temperature greater than 38.3°C, the presence of a rapidly (< 1 month) or ultimately (< 5 years) fatal disease, shaking chills, intravenous drug abuse, acute abdomen on examination, and major comorbidity. The overall performance deteriorated to an area under the curve of 0.56 and 0.59 in two external validation settings [25].
can therefore be questioned. The discriminatory level of 0.5% was chosen as the ratio between the upper limit of white blood cell counts and the upper limit of immature cells. A prior study found that bandemia was present in ∼80% of patients with true bacteremia [27]. In our study, only 53 (50%) patients with true bacteremia had more than 0.5% immature cells counted as ‘bandemia’ in the validation of the prediction rule. This could possibly imply an underestimation of the performance of the rule in the Danish setting.
A number of studies have examined predictors of bacteremia in the ED [7,26–28]. Mellors et al. [7] developed a model to identify ED patients with occult bacterial infection. Their model included age greater than 50 years, diabetes, white blood cell count greater than 15 000 cells × 109/l, band cells greater than 1500 cells × 109/l, and an erythrocyte sedimentation rate greater than 30 mm/h. Chase et al. [26] found 10 covariates associated with bacteremia in ED patients (respiratory failure, vasopressor use, neutrophilia, bandemia, thrombocytopenia, indwelling vascular catheter, abnormal temperature, suspected line or urinary infection, or endocarditis), and further covariates were associated with bacteremia with methicillin-resistant Staphylococcus aureus (renal disease and diabetes) or gramnegative bacteremia (vasopressor use in the ED, bandemia, and suspected urinary infection). However, both models were found not to be accurate enough to be widely used in clinical practice [13,26].
Another limitation is the use of rectal temperature, which is not equivalent and generalizable to the use of tympanic, oral, or skin temperature, decreasing the external validity.
In a recent review by Coburn et al. [13], it was concluded that especially the presence of chills, hypotension, and a low platelet count were associated with bacteremia, all of which included in the decision rule by Shapiro et al. [12].
References
Our study has several important limitations. First, in our ED setting there were no formal guidelines for obtaining blood cultures, and some decisions could have been made by the nursing staff with or without consultation with the treating physician. There may have been patients with bacteremia who did not have a blood culture obtained and therefore were not included in the patient population. Furthermore, even the most diligent classification of blood culture isolates as ‘true positive’ versus ‘contaminant’ can be erroneous and may lead to misclassification bias. Still, we believe to have minimized the risk through contemporary consultations. Other limitations include the retrospective nature of the study, as well as the fact that patients with bacteremia for practical reasons were matched to patients without bacteremia. Furthermore, we were not able to blind the study personnel, as bacteremia was mentioned in the charts reviewed during data abstraction. Another limitation is the use of immature cells (promyelocytes, metamyelocytes, and myelocytes) as the best estimate of bandemia, as bandemia is not used clinically in Denmark. The generalizability to the Danish setting
Our study confirmed the clinical decision rule to have the potential to be a good supplement for clinical judgment, guiding the decision on whether to obtain blood cultures in ED. As guidelines for obtaining blood cultures are sparse and are often based on fewer parameters compared with this decision rule, implementing the rule as a supplement could help obtain consensus in the field of blood cultures.
Acknowledgements Conflicts of interest
H.C.S. is a coinventor of a patented adjuvant for proteinconjugated pneumococcal vaccine. For the remaining authors there are no conflicts of interest.
1
Søgaard M, Nørgaard M, Dethlefsen C, Schønheyder HC. Temporal changes in the incidence and 30-day mortality associated with bacteremia in hospitalized patients from 1992 through 2006: a population-based cohort study. Clin Infect Dis 2011; 52:61–69. 2 Laupland KB. Incidence of bloodstream infection: a review of populationbased studies. Clin Microbiol Infect 2013; 19:492–500. 3 Rivers EP, Coba V, Whitmill M. Early goal-directed therapy in severe sepsis and septic shock: a contemporary review of the literature. Curr Opin Anaesthesiol 2008; 21:128–140. 4 Park DW, Chun BC, Kim JM, Sohn JW, Peck KR, Kim YS, et al. Epidemiological and clinical characteristics of community-acquired severe sepsis and septic shock: a prospective observational study in 12 university hospitals in Korea. J Korean Med Sci 2012; 27:1308–1314. 5 Skibsted S, Jones AE, Puskarich MA, Arnold R, Sherwin R, Trzeciak S, et al. Biomarkers of endothelial cell activation in early sepsis. Shock 2013; 39:427–432. 6 Poses RM, Anthony M. Availability, wishful thinking, and physicians' diagnostic judgments for patients with suspected bacteremia. Med Decis Making 1991; 11:159–168. 7 Mellors JW, Horwitz RI, Harvey MR, Horwitz SM. A simple index to identify occult bacterial infection in adults with acute unexplained fever. Arch Intern Med 1987; 147:666–671. 8 Bates DW, Cook EF, Goldman L, Lee TH. Predicting bacteremia in hospitalized patients. A prospectively validated model. Ann Intern Med 1990; 113:495–500. 9 Bates DW, Goldman L, Lee TH. Contaminant blood cultures and resource utilization. The true consequences of false-positive results. JAMA 1991; 265:365–369. 10 Alahmadi YM, Aldeyab MA, McElnay JC, Scott MG, Darwish Elhajji FW, Magee FA, et al. Clinical and economic impact of contaminated blood cultures within the hospital setting. J Hosp Infect 2011; 77:233–236. 11 De Kraker ME, Wolkewitz M, Davey PG, Koller W, Berger J, Nagler J, et al. Burden of antimicrobial resistance in European hospitals: excess mortality and length of hospital stay associated with bloodstream infections due to Escherichia coli resistant to third-generation cephalosporins. J Antimicrob Chemother 2011; 66:398–407.
Copyright r 2016 Wolters Kluwer Health, Inc. All rights reserved.
Prediction of bacteremia in the ED Jessen et al. 49
12
13 14
15
16
17 18
19 20
Shapiro NI, Wolfe RE, Wright SB, Moore R, Bates DW. Who needs a blood culture? A prospectively derived and validated prediction rule. J Emerg Med 2008; 35:255–264. Coburn B, Morris AM, Tomlinson G, Detsky AS. Does this adult patient with suspected bacteremia require blood cultures? JAMA 2012; 308:502–511. Pedersen CB, Gøtzsche H, Møller JO, Mortensen PB. The Danish Civil Registration System. A cohort of eight million persons. Dan Med Bull 2006; 53:441–449. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40:373–383. Søgaard M, Nørgaard M, Schønheyder HC. First notification of positive blood cultures and the high accuracy of the gram stain report. J Clin Microbiol 2007; 45:1113–1117. Kirn TJ, Weinstein MP. Update on blood cultures: how to obtain, process, report, and interpret. Clin Microbiol Infect 2013; 19:513–520. Weinstein MP, Reller LB, Murphy JR, Lichtenstein KA. The clinical significance of positive blood cultures: a comprehensive analysis of 500 episodes of bacteremia and fungemia in adults. I. Laboratory and epidemiologic observations. Rev Infect Dis 1983; 5:35–53. Roberts FJ. Definition of polymicrobial bacteremia. Rev Infect Dis 1989; 11:1029–1030. Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med 2006; 34:1589–1596.
21
22
23
24 25
26
27
28
Leibovici L, Greenshtain S, Cohen O, Mor F, Wysenbeek AJ. Bacteremia in febrile patients. A clinical model for diagnosis. Arch Intern Med 1991; 151:1801–1806. Nakamura T, Takahashi O, Matsui K, Shimizu S, Setoyama M, Nakagawa M, et al. Clinical prediction rules for bacteremia and in-hospital death based on clinical data at the time of blood withdrawal for culture: an evaluation of their development and use. J Eval Clin Pract 2006; 12:692–703. Leth RA, Forman BE, Kristensen B. Predicting bloodstream infection via systemic inflammatory response syndrome or biochemistry. J Emerg Med 2013; 44:550–557. Pfitzenmeyer P, Decrey H, Auckenthaler R, Michel JP. Predicting bacteremia in older patients. J Am Geriatr Soc 1995; 43:230–235. Yehezkelli Y, Subah S, Elhanan G, Raz R, Porter A, Regev A, Leibovici L. Two rules for early prediction of bacteremia: testing in a university and a community hospital. J Gen Intern Med 1996; 11:98–103. Chase M, Klasco RS, Joyce NR, Donnino MW, Wolfe RE, Shapiro NI. Predictors of bacteremia in emergency department patients with suspected infection. Am J Emerg Med 2012; 30:1691–1697. Seigel TA, Cocchi MN, Salciccioli J, Shapiro NI, Howell M, Tang A, Donnino MW. Inadequacy of temperature and white blood cell count in predicting bacteremia in patients with suspected infection. J Emerg Med 2012; 42:254–259. Fontanarosa PB, Kaeberlein FJ, Gerson LW, Thomson RB. Difficulty in predicting bacteremia in elderly emergency patients. Ann Emerg Med 1992; 21:842–848.
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Prediction of bacteremia in the emergency department: an external validation of a clinical decision rule Marie K. Jessena,e, Julie Mackenhauera, Anne Mette S.W. Hvassb, Svend Ellermann-Eriksenc, Simon Skibsteda,e, Hans Kirkegaarda, Henrik C. Schønheyderd and Nathan I. Shapiroe; CONSIDER Sepsis Network Objective The objective of this study was to validate a previously published clinical decision rule for predicting a positive blood culture in emergency department (ED) patients with suspected infection on the basis of major and minor criteria and a total score (Shapiro et al., J Emerg Med, 2008; 35:255–264). Methods This is a retrospective matched cohort study of adult ED patients with blood cultures obtained from 1 January 2011 through to 31 December 2011. ED patients with blood culture-confirmed bacteremia were matched 1 : 3 with patients with negative cultures. The outcome was ‘true bacteremia’. Data on clinical history, comorbid illnesses, physical observations, and laboratory tests were used to evaluate the application of the clinical decision rule. We report the sensitivity, specificity, and area under the curve. Results Among 1526 patients, 105 (6.9%) patients were classified with true bacteremia. The sensitivity of the prediction rule was 94% (95% confidence interval, 88–98%) and the specificity was 48% (95% confidence interval,
Introduction Bacteremia is a common clinical condition with an incidence rate of ∼ 140–160 per 100 000 person-years [1,2]. The clinical spectrum ranges from the innocuous to severe sepsis and septic shock, with mortality rates of 25–50% [3–5]. Identification of emergency department (ED) patients likely to have bacteremia is therefore important. Positive blood cultures confirm the presence of viable bacteria or fungi in the bloodstream and provide the opportunity to optimize the antibiotic treatment and draw attention to possible underlying foci of infection. Blood cultures in the ED tend to be obtained on the basis of clinical judgment and are normally taken before initiation of empiric antibiotic therapy. Guidelines for Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's website (www.euro-emergencymed.com). Members of CONSIDER Sepsis Network besides all the authors mentioned in the author group of the paper: Rita Andersen Leth, MPH, PhD; Christian Fynbo Christiansen, MD, PhD; Helle Lykkeskov Nibro, MD, PhD; Lotte Ebdrup, MD, PhD; Kimie Ødorf, BSc; Nicolaj Duus, MD; Betina Hansen, MD; Else Tønnesen, MD, PhD, Dr.Med. The work described in the manuscript has been presented as a poster at Sepsis 2013, ISF’s 6th Annual Symposium, Rio de Janeiro, Brazil, 5–6 November 2013. 0969-9546 Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved.
42–53%). The area under the receiver-operating characteristics curve was 0.83. Conclusion The clinical decision rule performed well in our ED setting and is likely to be a useful supplement to clinical judgment. European Journal of Emergency Medicine 23:44–49 Copyright © 2016 Wolters Kluwer Health, Inc. All rights reserved. European Journal of Emergency Medicine 2016, 23:44–49 Keywords: bacteremia, clinical prediction rule, emergency department, infectious diseases a
Research Center for Emergency Medicine, Departments of bInfectious Diseases, Clinical Microbiology, Aarhus University Hospital, Aarhus, dDepartment of Clinical Microbiology, Aalborg University Hospital, Aalborg, Denmark and eDepartment of Emergency Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA c
Correspondence to Marie K. Jessen, BSc, Research Center for Emergency Medicine, Aarhus University Hospital, Nørrebrogade 44, building 30, 1st floor, 8000 Aarhus C, Denmark Tel: + 45 7846 1073; fax: +45 7846 2720; e-mail: [email protected] Received 2 April 2014 Accepted 8 August 2014
obtaining blood cultures are sparse and differ among institutions, and ultimately the decision is left to the clinical team, although there is a tendency to overestimate the risk for bacteremia [6,7]. As a result, only 4–8% of blood cultures are ‘true positives’ [8]. In addition, a varying percentage of blood cultures yield microorganisms subsequently classified as contaminants. Depending on the circumstances, contaminated blood cultures may lead to unnecessary antibiotic treatment, increased length of stay, and high expenses for the healthcare system [9,10]. The escalation of antibiotic resistance globally emphasizes the importance of avoiding spurious information from blood cultures [11]. A precise prediction and decision rule for bacteremia among ED patients admitted with suspected infection can be instrumental in reaching this goal. In a prior publication, a clinical decision rule developed by Shapiro et al. [12] demonstrated high sensitivity for the identification of patients unlikely to have bacteremia. They included the following minor criteria: age greater than 65 years, temperature 38.8–39.3°C, chills, vomiting, hypotension, white blood cell count greater than 18 000 cells × 109/l, platelets less than 150 000 cells × 109/l, and creatinine level greater than 177 μmol/l (2.0 mg/dl), and DOI: 10.1097/MEJ.0000000000000203
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Prediction of bacteremia in the ED Jessen et al. 45
Table 1
Decision rule
Major criteria
Minor criteria (1 point each)
Suspected endocarditis (3 points) Temperature > 39.4°C (103.0°F) (3 points) Indwelling vascular catheter (2 points)
Age > 65 years Temperature 38.3–39.3°C Chills Vomiting Hypotension (systolic blood pressure < 90 mmHg) White blood cell count > 18 000 cells × 109/l Bands > 5% (in our setting immature cells > 0.5%) Platelets < 150 000 cells × 109/l Creatinine > 177 µmol/l (2.0 mg/dl)
As per the rule, a blood culture is indicated if at least one major criterion or two minor criteria are present. Otherwise, cultures may be omitted.
the following major criteria: suspicion of endocarditis, temperature greater than 39.4°C, and the presence of indwelling catheters. A blood culture is indicated by the rule if at least one major criterion or two minor criteria are fulfilled (Table 1). In a recent review of prediction rules for bacteremia, this rule was endorsed as promising and was suggested as a better negative predictor of bacteremia than a predictor of the overall clinical impression [13]. Although endorsing the rule, the review also indicated that further validation was needed. The aim of this study was to externally validate the decision rule for predicting a positive blood culture.
Materials and methods Study design and population
This retrospective cohort study included patients presenting to a large urban academic tertiary ED at Aarhus University Hospital, Denmark, with ∼ 56 000 patient visits annually. Eligible patients were identified through a blood culture log recorded in the Laboratory Information System at the Department of Clinical Microbiology, Aarhus University Hospital. The decision to obtain the blood culture was made independently by the patient’s medical care providers, and a certified laboratory technician performed the blood draw. The following patients were eligible for the study: adult ED patients (age > 18 years) with a valid Danish Civil Personal Registration number, who had a blood culture performed in the ED between 1 January 2011 and 31 December 2011. Only the first presentation with blood cultures drawn was included. All permanent residents of Denmark are provided with tax-supported healthcare free of charge from an assigned GP and public hospitals. The assigned Civil Personal Registration number is used for all healthcare contacts and permits unambiguous record linkage to all Danish health registries [14]. The Danish National Patients Register (DNPR) has been used to track all admissions to nonpsychiatric
hospitals in Denmark since 1977, recording dates of admission and discharge, and up to 20 discharge diagnoses. This study was approved by the Danish Data Protection Agency (No. 1-11-02-102-11) and by the Danish Health and Medicines Authority (j.nr.3-3013-221/1). Approval from an ethics committee was not required for this observational study according to Danish law. Demographics and clinical covariates
A combination of physicians’ and nurses’ electronic and written medical records was used to confirm eligibility and fulfillment of major and minor criteria for the blood culture prediction rule (Table 1). Data abstraction was performed by trained study personnel using Filemaker Pro 12 (Filemaker Inc., Santa Clara, California, USA). Charts were reviewed to determine the presence of chills and vomiting, the worst vital signs within 4 h of admission [rectal body temperature (Rectal thermometer, Terumo, Leuven, Belgium) and blood pressure], and the presence of indwelling vascular catheters. Chills were considered present if noted in the chart; otherwise, they were considered absent. Laboratory data included blood leukocyte count, percentage of neutrophils and immature cells, platelet count, and plasma creatinine level. In our setting, we defined bandemia as a ratio greater than 0.5% between the counts of immature neutrophils (metamyelocytes, myelocytes, and promyelocytes) and white blood cells; hence, we used this as the discriminatory level instead of greater than 5% band cells. Calculating bandemia required a complete blood count with a complete differential performed using flow cytometry (Sysmex America Inc., Lincolnshire, Illinois, USA). The source of suspected focal infection was classified on the basis of the physicians’ admission notes, including suspicion of endocarditis. To assess comorbidity, we used the comorbidity index developed by Charlson et al. [15]. The Charlson index score was calculated for each patient based on discharge diagnoses recorded in the DNPR. Bacteremia
Each patient had one to three sets (two to six bottles) of blood cultures, each comprising one aerobic and one anaerobic bottle with a nominal blood sample volume of 10 ml per bottle (BacT/Alert; bioMérieux, Marcy l’Etoile, France). Positive blood cultures were unloaded at fixed time points and examined immediately by Gram staining. Subculturing, identification, and susceptibility testing were carried out using standard methods [16]. Blood culture bottles were incubated for up to 5.7 days [17]. The patient’s clinical team was notified about the Gram staining report over the telephone by a medical staff member at the Department of Clinical Microbiology, making it possible to interpret the significance of the positive blood culture in the clinical context. As soon as a
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46 European Journal of Emergency Medicine 2016, Vol 23 No 1
tentative identification and the antibiotic susceptibility pattern of the isolate(s) were obtained, a second notification was made either to confirm or adjust antibiotic treatment. In the case of likely contamination, this would be communicated in the same manner. Outcomes
Our primary outcome was ‘true bacteremia’, defined as bacterial or fungal growth in blood cultures deemed to have an etiological role on the basis of joint clinical and microbiological assessment. All blood culture isolates Table 2
Patient characteristics Bacteremia (n = 105)
Demographics Age [median, mean (SD)] 77, 71.2 (17) (years) Male sex (%) 50.5 Comorbidities Charlson index score 1, 1.7 (2) [median, mean (SD)] Cerebrovascular disease 21.0 (%) Congestive heart failure 10.5 (%) Human immunodeficiency 1 virus (%) Malignancy (%) 15.2 Diabetes (%) 12.4 Clinical covariates [median, mean (SD)] Systolic blood pressure 123, 123 (30) (mmHg) Initial temperature (°C) 38.7, 38.6 (1) 12.3, 13.9 (8) White blood count 9 (cells × 10 /l) Neutrophil% 88, 85 (12) Immature cell% 0.07, 0.2 (0.4) Platelets (cells × 109/l) 210, 214 (106) Plasma creatinine (μmol/l) 107, 186 (203) Vomiting (%) 27.6 Chills (%) 14.3 Indication of culture Suspected focal infection 61.9 (%) Fever (without source) (%) 16.2 Suspected endocarditis 2.9 (%) Other/unknown (%) 19.0 Suspected infectious foci (%) Unknown 36.1 Pneumonia 25.7 Urinary tract infection/ 25.7 pyelonephritis Intra-abdominal 1.9 Skin and soft tissue 3.8 Meningitis 2.8 Endocarditis 1.9 c 1.1 Other Noninfectiousd 1.0 Length of stay [median, mean 9.6, 14.8 (19) (SD)] (days) Time to culture [median, 53, 104 (197) mean (SD)] (min) In-hospital mortality (%) 14.3 a
Nonbacteremia (n = 315)
P-value
65, 62.5 (20)
< 0.001a
41.4
0.10b
1, 1.4 (2)
0.09a
9.8
0.03b
9.5
0.78b
0
0.56b
13.0 12.7
0.56b 0.93b
130, 132 (28)
0.004a
37.8, 37.8 (1) 10.4, 11.6 (6)
< 0.001a 0.002a
78, 76 (11) 0.04, 0.1 (0.3) 249, 272 (122)
< 0.001a < 0.001a < 0.001a
77, 93 (75) 17.8 10.8
< 0.001a 0.03b 0.33b
60.6 8.3 0.3 30.8 29.5 28.6 8.9
c
Data analysis
Means with SDs, medians, and proportions were used for descriptive statistics, as appropriate. All univariate relationships were examined using a t-test, χ2-test, or Wilcoxon’s rank sum test, as appropriate. Sensitivity and specificity were calculated with binomial 95% confidence intervals (CIs), and the area under the receiver-operating characteristic curve was calculated using the point score given by the rule. Statistical analysis was carried out using STATA 12.0 (StataCorp, College Station, Texas, USA).
Results Population characteristics
During the 1-year study period, a total of 2562 blood culture sets were obtained in the ED from 1578 patients; of these, 1526 met the inclusion criteria. A total of 105 patients (6.9%) had true bacteremia. Fifty (3.3%) had ‘definitely contaminated’ blood cultures, whereas 11 (0.7%) had ‘possible contaminations’ and were all regarded as negative blood cultures. The ‘true bacteremia’ patients were matched with 315 patients with negative blood cultures. The demographics and characteristics of patients, clinical, physiological, and laboratory values, as well as suspected infectious foci are reported in Table 2, stratified by the presence or absence of true bacteremia.
Calculating a total point score for each patient from minor and major criteria, the sensitivity of the prediction rule was 94% (95% CI 88–98%) and specificity 48% (95% CI 42–53%) (Table 3). The area under the receiveroperating characteristic curve was 0.83. < 0.001a
52, 119 (262)
0.45a 0.002b
Student’s t-test. χ -test. Other includes biliary tract infections, indwelling catheter, perforated organs, etc. d No suspicion of infection mentioned in the chart but blood culture obtained. b 2
Patients with true bacteremia were matched at random with patients with either no growth or a growth classified as a true contamination or a possible contamination in the proportion 1 : 3.
Performance of the prediction rule
8.9 10.5 0.6 0.3 4.1 8.6 3.6, 6.4 (9)
5.1
were classified prospectively as being either (i) ‘true bacteremia’, (ii) ‘definite contamination’, or (iii) ‘possible contamination’. In accordance with Weinstein et al. [18] coagulase-negative Staphylococci spp., Corynebacterium spp., Bacillus spp., and Propionibacterium acnes were considered as ‘definite contaminants’, unless they were isolated from two or more separate blood culture sets, and they were considered as ‘true bacteremia’ or ‘possible contamination’ if two of four bottles were positive with the abovementioned bacteria. Polymicrobial bacteremia was defined according to Roberts [19].
Positive and negative predictive values are shown in Appendix 1 (Supplemental digital content 1, http://links. lww.com/EJEM/A81), calculated using the prevalence of bacteremia in the entire population. Patients missed by the prediction rule
The clinical circumstances of the six patients who could have been missed by the rule are summarized in Table 4.
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Prediction of bacteremia in the ED Jessen et al. 47
Table 3
Application of the decision rule
found the sensitivity to perform better than past reports on clinical judgment alone [6,7].
Decision rule fulfilled Blood culture
Yes
No
In total
Positive Negative In total
99 165 264
6 150 156
105 315 420
Estimation of sensitivity and specificity. Results are expressed along with 95% confidence interval sensitivity, 94% (88–98%); specificity, 48% (42–53%).
For two patients (patients 2 and 6), the culture resulted in initiation or change of antibiotic therapy. For patients 1, 2, and 4, the initial antibiotic provided appropriate coverage, whereas patient 3 recovered without antibiotic therapy. Two of the patients (patients 2 and 4) deteriorated in condition during admission day 1, which would have triggered a blood culture by the rule. Both patients recovered with antibiotic therapy. Microbiologic diagnosis
Of the 1526 blood cultures drawn, 4.6% were considered contaminated (false positive). Of the 105 patients with true bacteremia, 55 (52%) cases were due to gramnegative bacteria, 41 (39%) due to gram-positive bacteria, and nine (9%) patients had polymicrobial bacteremia (Appendix 2, Supplemental digital content 2, http:// links.lww.com/EJEM/A82 ).
Discussion In this retrospective cohort study we validated a clinical prediction rule that successfully stratified ED patients according to the likelihood of bacteremia. The result suggests the rule to have the ability to aid the ED physicians in making a rapid bedside estimation of bacteremia risk, thereby supplementing clinical judgment. Of note, in our cohort from Aarhus University Hospital, we Table 4 Patient number
Even when applying a clinical decision rule to a group of patients, good clinical judgment should still be used. Thus, the rule should sometimes be overridden in certain low-risk patients with clinical risk factors to avoid providing inappropriate treatment to patients. Among the patients missed by the rule, only two patients had meaningful changes: (i) cefuroxime, ciprofloxacin, and metronidazole were changed to meropenem because of the detection of Salmonella spp. resistant to cefuroxime and gentamicin, and (ii) initiation of penicillin after verification of Pneumococci spp. growth in the blood culture (Table 4). Thus, in total, there were two patients in the entire population who could have potentially been compromised by application of the rule. This needs to be weighed against the need to ration care at some level, with Departments of Clinical Microbiology receiving increasing numbers of blood cultures exceeding their capacity. It could be even more important that the clinical prediction rule could also be used to identify patients who were at a high risk for bacteremia and therefore could benefit from aggressive empiric antibiotic treatment, in accordance with recent studies linking improved survival with early empiric antibiotic coverage in patients with bacteremia [20]. The fact that the treating physician was contacted by a member of the medical staff of the Department of Clinical Microbiology to discuss and interpret the significance of the blood culture in the clinical context probably minimized costs and unnecessary antibiotic treatment due to false-positive blood cultures or contaminations. However, we lacked specific data on this topic. Prior studies have been performed in the inpatient setting to identify predictors of bacteremia [8,21–24].
Patients missed by the decision rule Clinical circumstances
Outcome
1
87-year-old, unknown site of infection, dizziness, temperature 37.8°C
2
45-year-old man, hepatic encephalopathy, platelets 59 × 109 l, BP decreased at admission day 1 to 79/50 mmHg, creatinine increased to 165 μmol/l 85-year-old woman, diarrhea
Pansensitive Staphylococcus hominis, antibiotic (dicloxacillin) started at admission Salmonella spp. resistant to cefuroxime and gentamicin, antibiotics (cefuroxime, ciprofloxacin, and metronidazole) started when BP decreased and changed to meropenem after growth verification Campylobacter spp. Patient improved without antibiotics. Resistance pattern not described. Pansensitive nonhemolytic Streptococci spp., continued initial antibiotics (cefuroxime) with good response Pansensitive Escherichia coli, piperacillin–tazobactam ordered on admission day 2, no change in antibiotics Pansensitive Pneumococci spp.; penicillin initiated following these culture results
3 4 5 6
96-year-old man, admitted unconscious, verified pneumonia. Temperature increased to 38.6°C. Do not resuscitate 56-year-old man, UTI, because of psychiatric reasons not possible to obtain vital signs; hence, not counted in the rule 65-year-old woman, painful legs, subjective fever at home (not measured), verified endocarditis but no suspicion at admission
This table shows the clinical circumstances in patients with positive blood cultures that would have been missed by the decision rule. Only in patients 2 and 6 were there meaningful changes in antibiotics. Patient 6 had a subjective fever at home but was not counted in rule. The conditions of patients 2 and 4 deteriorated, which would have been an indication for culture. Other patients either had a benign course or responded to their initial empiric antibiotic therapy. BP, blood pressure; UTI, urinary tract infection.
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48 European Journal of Emergency Medicine 2016, Vol 23 No 1
Bates et al. [8] developed and validated a prediction rule for bacteremia in hospitalized patients with an area under the curve of 0.71 and 0.69 in the derivation and the validation set, respectively. Their rule included temperature greater than 38.3°C, the presence of a rapidly (< 1 month) or ultimately (< 5 years) fatal disease, shaking chills, intravenous drug abuse, acute abdomen on examination, and major comorbidity. The overall performance deteriorated to an area under the curve of 0.56 and 0.59 in two external validation settings [25].
can therefore be questioned. The discriminatory level of 0.5% was chosen as the ratio between the upper limit of white blood cell counts and the upper limit of immature cells. A prior study found that bandemia was present in ∼80% of patients with true bacteremia [27]. In our study, only 53 (50%) patients with true bacteremia had more than 0.5% immature cells counted as ‘bandemia’ in the validation of the prediction rule. This could possibly imply an underestimation of the performance of the rule in the Danish setting.
A number of studies have examined predictors of bacteremia in the ED [7,26–28]. Mellors et al. [7] developed a model to identify ED patients with occult bacterial infection. Their model included age greater than 50 years, diabetes, white blood cell count greater than 15 000 cells × 109/l, band cells greater than 1500 cells × 109/l, and an erythrocyte sedimentation rate greater than 30 mm/h. Chase et al. [26] found 10 covariates associated with bacteremia in ED patients (respiratory failure, vasopressor use, neutrophilia, bandemia, thrombocytopenia, indwelling vascular catheter, abnormal temperature, suspected line or urinary infection, or endocarditis), and further covariates were associated with bacteremia with methicillin-resistant Staphylococcus aureus (renal disease and diabetes) or gramnegative bacteremia (vasopressor use in the ED, bandemia, and suspected urinary infection). However, both models were found not to be accurate enough to be widely used in clinical practice [13,26].
Another limitation is the use of rectal temperature, which is not equivalent and generalizable to the use of tympanic, oral, or skin temperature, decreasing the external validity.
In a recent review by Coburn et al. [13], it was concluded that especially the presence of chills, hypotension, and a low platelet count were associated with bacteremia, all of which included in the decision rule by Shapiro et al. [12].
References
Our study has several important limitations. First, in our ED setting there were no formal guidelines for obtaining blood cultures, and some decisions could have been made by the nursing staff with or without consultation with the treating physician. There may have been patients with bacteremia who did not have a blood culture obtained and therefore were not included in the patient population. Furthermore, even the most diligent classification of blood culture isolates as ‘true positive’ versus ‘contaminant’ can be erroneous and may lead to misclassification bias. Still, we believe to have minimized the risk through contemporary consultations. Other limitations include the retrospective nature of the study, as well as the fact that patients with bacteremia for practical reasons were matched to patients without bacteremia. Furthermore, we were not able to blind the study personnel, as bacteremia was mentioned in the charts reviewed during data abstraction. Another limitation is the use of immature cells (promyelocytes, metamyelocytes, and myelocytes) as the best estimate of bandemia, as bandemia is not used clinically in Denmark. The generalizability to the Danish setting
Our study confirmed the clinical decision rule to have the potential to be a good supplement for clinical judgment, guiding the decision on whether to obtain blood cultures in ED. As guidelines for obtaining blood cultures are sparse and are often based on fewer parameters compared with this decision rule, implementing the rule as a supplement could help obtain consensus in the field of blood cultures.
Acknowledgements Conflicts of interest
H.C.S. is a coinventor of a patented adjuvant for proteinconjugated pneumococcal vaccine. For the remaining authors there are no conflicts of interest.
1
Søgaard M, Nørgaard M, Dethlefsen C, Schønheyder HC. Temporal changes in the incidence and 30-day mortality associated with bacteremia in hospitalized patients from 1992 through 2006: a population-based cohort study. Clin Infect Dis 2011; 52:61–69. 2 Laupland KB. Incidence of bloodstream infection: a review of populationbased studies. Clin Microbiol Infect 2013; 19:492–500. 3 Rivers EP, Coba V, Whitmill M. Early goal-directed therapy in severe sepsis and septic shock: a contemporary review of the literature. Curr Opin Anaesthesiol 2008; 21:128–140. 4 Park DW, Chun BC, Kim JM, Sohn JW, Peck KR, Kim YS, et al. Epidemiological and clinical characteristics of community-acquired severe sepsis and septic shock: a prospective observational study in 12 university hospitals in Korea. J Korean Med Sci 2012; 27:1308–1314. 5 Skibsted S, Jones AE, Puskarich MA, Arnold R, Sherwin R, Trzeciak S, et al. Biomarkers of endothelial cell activation in early sepsis. Shock 2013; 39:427–432. 6 Poses RM, Anthony M. Availability, wishful thinking, and physicians' diagnostic judgments for patients with suspected bacteremia. Med Decis Making 1991; 11:159–168. 7 Mellors JW, Horwitz RI, Harvey MR, Horwitz SM. A simple index to identify occult bacterial infection in adults with acute unexplained fever. Arch Intern Med 1987; 147:666–671. 8 Bates DW, Cook EF, Goldman L, Lee TH. Predicting bacteremia in hospitalized patients. A prospectively validated model. Ann Intern Med 1990; 113:495–500. 9 Bates DW, Goldman L, Lee TH. Contaminant blood cultures and resource utilization. The true consequences of false-positive results. JAMA 1991; 265:365–369. 10 Alahmadi YM, Aldeyab MA, McElnay JC, Scott MG, Darwish Elhajji FW, Magee FA, et al. Clinical and economic impact of contaminated blood cultures within the hospital setting. J Hosp Infect 2011; 77:233–236. 11 De Kraker ME, Wolkewitz M, Davey PG, Koller W, Berger J, Nagler J, et al. Burden of antimicrobial resistance in European hospitals: excess mortality and length of hospital stay associated with bloodstream infections due to Escherichia coli resistant to third-generation cephalosporins. J Antimicrob Chemother 2011; 66:398–407.
Copyright r 2016 Wolters Kluwer Health, Inc. All rights reserved.
Prediction of bacteremia in the ED Jessen et al. 49
12
13 14
15
16
17 18
19 20
Shapiro NI, Wolfe RE, Wright SB, Moore R, Bates DW. Who needs a blood culture? A prospectively derived and validated prediction rule. J Emerg Med 2008; 35:255–264. Coburn B, Morris AM, Tomlinson G, Detsky AS. Does this adult patient with suspected bacteremia require blood cultures? JAMA 2012; 308:502–511. Pedersen CB, Gøtzsche H, Møller JO, Mortensen PB. The Danish Civil Registration System. A cohort of eight million persons. Dan Med Bull 2006; 53:441–449. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40:373–383. Søgaard M, Nørgaard M, Schønheyder HC. First notification of positive blood cultures and the high accuracy of the gram stain report. J Clin Microbiol 2007; 45:1113–1117. Kirn TJ, Weinstein MP. Update on blood cultures: how to obtain, process, report, and interpret. Clin Microbiol Infect 2013; 19:513–520. Weinstein MP, Reller LB, Murphy JR, Lichtenstein KA. The clinical significance of positive blood cultures: a comprehensive analysis of 500 episodes of bacteremia and fungemia in adults. I. Laboratory and epidemiologic observations. Rev Infect Dis 1983; 5:35–53. Roberts FJ. Definition of polymicrobial bacteremia. Rev Infect Dis 1989; 11:1029–1030. Kumar A, Roberts D, Wood KE, Light B, Parrillo JE, Sharma S, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med 2006; 34:1589–1596.
21
22
23
24 25
26
27
28
Leibovici L, Greenshtain S, Cohen O, Mor F, Wysenbeek AJ. Bacteremia in febrile patients. A clinical model for diagnosis. Arch Intern Med 1991; 151:1801–1806. Nakamura T, Takahashi O, Matsui K, Shimizu S, Setoyama M, Nakagawa M, et al. Clinical prediction rules for bacteremia and in-hospital death based on clinical data at the time of blood withdrawal for culture: an evaluation of their development and use. J Eval Clin Pract 2006; 12:692–703. Leth RA, Forman BE, Kristensen B. Predicting bloodstream infection via systemic inflammatory response syndrome or biochemistry. J Emerg Med 2013; 44:550–557. Pfitzenmeyer P, Decrey H, Auckenthaler R, Michel JP. Predicting bacteremia in older patients. J Am Geriatr Soc 1995; 43:230–235. Yehezkelli Y, Subah S, Elhanan G, Raz R, Porter A, Regev A, Leibovici L. Two rules for early prediction of bacteremia: testing in a university and a community hospital. J Gen Intern Med 1996; 11:98–103. Chase M, Klasco RS, Joyce NR, Donnino MW, Wolfe RE, Shapiro NI. Predictors of bacteremia in emergency department patients with suspected infection. Am J Emerg Med 2012; 30:1691–1697. Seigel TA, Cocchi MN, Salciccioli J, Shapiro NI, Howell M, Tang A, Donnino MW. Inadequacy of temperature and white blood cell count in predicting bacteremia in patients with suspected infection. J Emerg Med 2012; 42:254–259. Fontanarosa PB, Kaeberlein FJ, Gerson LW, Thomson RB. Difficulty in predicting bacteremia in elderly emergency patients. Ann Emerg Med 1992; 21:842–848.
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