Utility of Previous Culture Results for Guiding Empirical Treatment of Sepsis in The Emergency Department

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Abstract

Background: Sepsis is a serious medical condition and a major cause of morbidity and mortality, and poses challenges in terms of recognition and management. Although studies have investigated the early identification of sepsis and early use of broad-spectrum antibiotics, no clear criteria exist to identify those patients needing additional coverage for resistant organisms.

Aims: This study aims to evaluate the utility of previous positive blood or urine culture results in predicting the presence of resistant organisms in septic patients in the emergency department (ED).

Methods: This retrospective observational study was conducted at King Fahad Medical City (KFMC), a tertiary care centre in Riyadh, Saudi Arabia, between March and August 2021. Patients aged 18 years or older, who visited the ED at KFMC during the study period, were included if they had a positive blood or urine culture and met the sepsis definition.

Result: A total of 133 patients were enrolled (mean age 61.6 [18.3] years), of whom approximately half were male (67, 50.4%). We found that previous colonisation with resistant organisms was more likely in patients with resistant organisms at the time of the enrolled visit (n = 17, 77.3%) than in patients with non-resistant organisms (n = 22, 19.8%, p < .05). Therefore, one statically significant predictor of a current resistant organism is a prior colonisation with a resistant organism (OR = 13.8; 95% CIs 3.6, 51.9; p < .05).

Conclusion: Previous cultures, from within the last 12 months, are useful predictors of current resistant organisms, and are therefore essential in guiding empirical antibiotic treatment in septic patients in the ED. Further more extensive and prospective cohort studies on this subject are now needed to mitigate the burden of sepsis on healthcare systems worldwide.

Keywords: Sepsis, Emergency, Resistant organisms

Introduction

Sepsis is a serious medical condition and a major cause of morbidity and mortality. 1 The recognition and management of sepsis, as well as antibiotic choices for its treatment, continue to pose challenges — especially in the emergency department (ED), due to limited data and short clinical courses. It is established, however, of initiation early that

and mortality reduce antibiotics can limit complications. 2

Although extensive studies and guidelines have investigated the role of early identification and early broad-spectrum antibiotics for sepsis, 2 , 3 no clear cri- teria exist to identify patients who need additional coverage for resistant organisms. Some suggest a review of previous cultures to guide empirical treat- ment; however, the available evidence is limited. Some studies are based on throat swabs in intensive care unit (ICU) settings, with no blood cultures included. 4 Others included screening swabs taken a few days before infection onset. 4 − 7 In addition, most of the included patients in previous studies were in ICU settings, rather than in ED settings. 5 − 7 Some of the studies investigated specific Gram classes but not all organisms. 8 − 10

We hypothesise that positive blood or urine cul- ture results from within the previous 12 months can

predict the presence of resistant organisms in septic ED patients. Therefore, this study aims to evaluate the utility of previous positive blood or urine culture results as predictors of current resistant organisms in septic patients in the ED.

Methods

Study design and patient selection: This retrospective observational study was con- ducted at King Fahad Medical City (KFMC), a tertiary care centre in Riyadh, Saudi Arabia. Patients aged 18 years or older, who visited the ED at KFMC between March and August 2021, had a positive blood or urine culture, and met the sepsis definition, were included. Patients with microbiology reports older than 12 months, as well as any patients discharged from the ED, were excluded. A total of 133 patients were enrolled. If a patient had multiple visits that met the inclusion criteria during the study period, only the most recent visit was included.

We defined sepsis as documented bacteraemia or bacteriuria and a positive systemic inflammatory response syndrome (SIRS) or positive Lactate- enhanced-qSOFA (LqSOFA) in the absence of alter- native conditions. 11 − 14 Prior antibiotic exposure is any receipt of antibiotics within 90 days preceding the enrolled visit. 8 , 15 , 16 An infection was deemed hospital-acquired if the patient was previously ad- mitted in the 90-day period preceding the enrolled

visit. 8 Immunosuppressive therapy is the current use, or use within 30 days preceding the enrolled visit, of the following medication: corticosteroids, cyclosporine A, tacrolimus, rapamycin, cyclophos- phamide, azathioprine, mycophenolate mofetil, methotrexate, etanercept, infliximab, daclizumab, basiliximab, chlorodeoxyadenosine, fludarabine, or

alemtuzumab. 17 Cancer treatment therapy is any exposure to chemotherapy, radiation therapy, or hormonal therapy during or preceding the enrolled

visit by 14 days. 18 An immunocompromised pa- tient is any patient with the following conditions: neutropenia, splenectomy, haematopoietic stem cell transplant, solid organ transplant, or HIV-AIDS. 17

Data sources: Subjects were identified automatically from the electronic medical record, and two trained data collectors obtained the following variables from the same record.

Study variables: Age, gender (male/female), comorbidities (car- diopulmonary disease, medical disease, oncological diseases, neurological disease, rheumatological and immunological diseases, infectious disease, surgical disease, none), prior antibiotic exposure, admission diagnosis (medical/surgical), community-acquired infection, hospital-acquired infection, ICU admis- sion, immunosuppressive therapy, cancer treatment therapy, immunocompromised, organisms identified in the enrolled visit (blood or urine), prior microbi- ology results (blood, urine).

Data management and analysis plan: The analysis used the Statistical Package for So- cial Sciences (SPSS) version 25.0 (IBM-SPSS, Ar- monk, New York, USA). Descriptive statistics were reported as mean and standard deviation for con- tinuous variables and as frequency and percentages for categorical variables. An independent samples t- test was used to compare means for two groups, and analysis of variance was used for three or more groups. The chi-square test was used to determine significant association between categorical groups. A logistic regression analysis was carried out to determine the significant factors associated with current resistance. p-values 0.05 were considered statistically significant.

Ethical considerations: All obtained data were treated with strict con- fidentiality, and any identifying information was excluded from all reports or published documents. Approval was obtained from the Research Ethics Board at KFMC.

Results

A total of 133 patients were enrolled (mean age 61.6 [18.3] years), about half of whom were male (n = 67, 50.4%). The patients were divided into two groups, the first consisting of patients with non- resistant organisms at the time of the enrolled visit (n = 111, 83.5%), and the second group consisting of those with resistant organisms at the time of the enrolled visit (n = 22, 16.5%). No significant differences in age, gender or comorbidities were found between the two groups; however, the second group was less likely to have cardiopulmonary dis- eases (n = 14, 63.6%) than those with non-resistant organisms (n = 92, 82.9%) p < 0 .05. Patients with

resistant organisms were more likely to have prior antibiotic exposure (n = 21, 95.5%) than those with non-resistant organisms (n = 99, 89.2%), although this was not statistically significant (p = 0.36). Fur- thermore, all those in the second group had hospital- acquired infections (n = 22, 100%) and were more likely to have had ICU admissions (n = 19, 86.4%) than patients with non-resistant organisms (n = 77, 69.4%). Overall, the study population consisted of sick patients with an ICU admission rate of 72.2%, 60% receiving immunosuppression therapy, and almost a third receiving cancer treatment (n = 37, 27.8%). In addition, 9.8% were identified as im- munocompromised. Notably, previous colonisation with resistant organisms was more likely in patients with resistant organisms during the enrolled visit (n = 17, 77.3%) than in those with non-resistant organisms (n = 22, 19.8%, p< 0.05). (Table 1).

septic patients and selecting antimicrobial agents; it should also alert the healthcare systems to the real need for efforts aimed at fighting and decreasing hospital- acquired infections.

Multiple factors are advised to guide the admin- istration of empirical antibiotics, one of which is local hospital susceptibility. 2 , 19 , 20 Thus, the predic- tive utility of previous cultures should be paramount in clinical practice, alongside other factors, to avoid unnecessary antibiotic administration and to ensure that appropriate antibiotics are received in the short- est possible time — even before culture results — as these patients’ condition is usually critical. Early appropriate antibiotics are essential, as advised by the guidelines. 2

Although this is an essential outcome of the study, it is crucial to highlight that this study’s population is unique, as it was conducted in a tertiary centre with 38% of the population being oncology and sicker patients. Nevertheless, it is unlikely that this fact affected the results or their application.

Although the literature review was limited on this subject, some studies discussed the utility of previ- ous cultures and examined other risk factors for pre- dicting resistant organisms. For example, MacFad- den’s study concluded that “prior resistant culture results are useful in the selection of empiric therapy for bloodstream infections due to confirmed Gram- negative pathogens”. 8 Other studies found that a history of detected methicillin-resistant Staphylo- coccus aureus on cultures was highly specific for subsequent infection with Staphylococcus aureus. 9

Table 2. shows the odds ratios (OR) and 95% confidence intervals (CI) of predictors of a resistant organism at the time of the enrolled visit. The only statistically significant predictor is previous colonisation with a resistant organism (OR = 13.8; 95% CI 3.6, 51.9; p < 0.05). Figure 1. reports the prevalence of resistant organisms.
results are useful in the selection of empiric therapy
IV. DISCUSSIONfor bloodstream infections due to confirmed Gram-
Reviewing culture results, either blood or urine,negative pathogens”.8 Other studies found that a
from the previous 12 months is crucial in assessinghistory of detected methicillin-resistant Staphylo-
and managing septic patients. Reviewing previouscoccus aureus on cultures was highly specific for
cultures along with historical data such as priorsubsequent infection with Staphylococcus aureus.9
antibiotic exposure, history of recent hospitalisation,When assessing patients with current infection, it is
and comorbidities can help to identify those patientshelpful to review the previous microbiological data
more likely to develop sepsis secondary to a resis-and cultures and recommend empirical antibiotic
tant organism.coverage for the identified resistant organisms.21,22
The results of this study demonstrate that priorA limitation of this study is that it is a retrospec-
colonisation with a resistant organism is a strongtive observational study conducted in a single centre
predictor of a current resistant organism in the samewith a relatively small sample size.
patient. The study also found that patients with
resistant organisms are less likely to be sufferingV. CONCLUSION
from cardiopulmonary disease.Cultures taken within 12 months prior to the
All of the patients in our study who developedcurrent infection, are useful in predicting current
resistant organisms had a history of recent hospi-resistant organisms, and are therefore essential in
talisation, their infection was considered hospital-guiding empirical antibiotic treatment of sepsis in the
acquired, and they had a higher rate of exposure toED. More in-depth studies are needed on this topic
antibiotics. This information highlights the importa-to lower the impact of sepsis on global health- care
ance of identifying these factors when assessingsystems.
Table 1. Demographic and clinical variables among septic patients with occurrence of resistant
organisms in blood orurine culture (N=133)
Variables Patients with non-Patients with p-value All patients
resistantresistant (current)
organismsorganisms n=133
(current)(current)
N=111N=22
Age, mean (SD) 61.9 ± 18.760.5 ± 19.5 0.7* 61.6 ± 18.3
Gender
Male 57 (51.4%)10 (45.5%) 0.6 67 (50.4%)
Female 54 (48.6%)12 (54.5%) 66 (49.6%)
Mean number of comorbidities 2.75 ± 1.52.45 ± 1.4 0.3* 2.70 ± 1.5
Comorbidities
Cardiopulmonary 92 (82.9%)14 (63.6%) 0.04 106 (79.7%)
Medical disease 93 (83.8%)17 (77.3%) 0.4 110 (82.7%)
Oncological 42 (37.8%)9 (40.9%) 0.7 51 (38.3%)
Neurological 56 (50.5%)12 (54.5%) 0.7 68 (51.1%)
Rheumatological 12 (10.8%)0 0.1 12 (9.0%)
Infectious 47 (42.3%)7 (31.8%) 0.3 54 (40.6%)
Surgical disease 54 (48.6%)10 (45.5%) 0.7 64 (48.1%)
Admission diagnosis
Medical 106 (95.5%)20 (90.9%) 126 (94.7%)
Surgical 5 (4.5%)2 (9.1%) 0.3 7 (5.3%)
Prior antibiotic exposure 99 (89.2%)21 (95.5%) 0.3 120 (90.2%)
Community-acquired infection 10 (9.0%)0 0.1 10 (7.5%)
Hospital-acquired infection 101 (91.0%)22 (100%) 0.1 123 (92.5%)
Current ICU admission 77 (69.4%)19 (86.4%) 0.1 96 (72.2%)
Immunosuppressive therapy 72 (64.9%)12 (54.5%) 0.3 84 (63.2%)
Cancer treatment therapy 31 (27.9%)6 (27.3%) 0.9 37 (27.8%)
Immunocompromised 10 (9.0%)3 (16.7%) 0.5 13 (9.8%)
Previous colonisation with 22 (19.8%)17 (77.3%) 39 (29.3%)
resistant organisms< 0.001
No previous colonisation with 89 (80.2%)5 (22.7%) 94 (70.7%)
resistant organisms
* tested by independent samples t-test; the rest by chi-squaretest
4. Sanders KM, Adhikari NKJ, Friedrich JO, Day
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of critical illness in adults. Lancet.analysis from a randomised trial. J Crit Care.
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MM, Antonelli M, Ferrer R, et al. Surviving sepsisHayashi Y, Lipman J, et al. The role of surveillance
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eases Society of America. Guidelines for the man-Waele J De, Hoste E, et al. Colonisation status and
agement of adults with community-acquired pneu-appropriate antibiotic therapy for nosocomial bacteremia
Table 2. Odds ratios (95% CI) of predictors of antibiotic resistance from multi-variable logistic regression analysis
Variable BOR (95% CI) p-value
Age 0.011.01 (0.9, 1.06) 0.6
Gender -0.30.6 (0.1, 2.2) 0.5
Number of comorbidities 1.30.2 (0.003, 22.74) 0.5
Cardiopulmonary disease 2.30.09 (0.010, 0.855) 0.03
Medical disease 2.715.6 (0.09, 248.5) 0.2
Oncological disease 0.72.0 (0.01, 274.6) 0.7
Neurological disease 1.75.6 (0.04, 690.2) 0.4
Rheumatological disease 17.40 (0) 0.9
Infectious disease 0.41.5 (0.01, 211.2) 0.8
Surgical disease 1.65.1 (0.03, 757.0) 0.5
Admission diagnosis 0.21.3 (0.08, 21.5) 0.8
Prior antibiotic exposure 0.31.4 (0.1, 18.9) 0.7
Community-acquired infection 18.70 (0) 0.9
Current ICU admission 0.72.1 (0.3, 12.4) 0.3
Immunosuppressive therapy 0.80.4 (0.1, 1.8) 0.2
Cancer treatment therapy 0.82.2 (0.2, 22.2) 0.4
Immunocompromised 1.44.4 (0.5, 38.3) 0.1
Previous colonisation with resistant organisms 2.613.8 (3.6, 51.9) < .001
Figure 1. The prevalenceof resistant organisms.
2005;26(6):575–9
7. Papadomichelakis E, Kontopidou F,exposure and antimicrobial resistance in invasive
Antoniadou A, Poulakou G, Koratzanis E, Kopteridespneumococcal disease: Results from prospective
P, et al. Screening for resistant Gram-negativesurveillance. Clin Infect Dis. 2014;59(7):944–52.
microorganisms to guide empiric therapy of17. Gea-Banacloche JC, Opal SM, Jorgensen J,
subsequent infection. Intensive Care Med.Carcillo JA, Sepkowitz KA, Cordonnier C. Sepsis
2008;34(12):2169–75.associated with immunosuppressive medications: An
8. MacFadden DR, Coburn B, Shah N, Robicsekevidence-based review. Crit Care Med. 2004;32(11
A, Savage R, Elligsen M, et al. Utility of prior culturesSUPPL.).
in predicting antibiotic resistance of bloodstream18. Cantwell L, Perkins J. Infectious disease
infections due to Gram-negative pathogens: aemergencies in oncology patients. Emerg Med Clin
multicentre observational cohort study. Clin MicrobiolNorth Am. 2018;36(4):795–810.
Infect. 2018;24(5):493–9.19. Kalil AC, Metersky ML, Klompas M,
9. Butler-Laporte G, Cheng MP, Cheng AP,Muscedere J, Sweeney DA, Palmer LB, et al.
McDonald EG, Lee TC. Using MRSA screening testsManagement of adults with hospital-acquired and
to predict methicillin resistance in Staphylococcusventilator- associated pneumonia: 2016 clinical
aureus bacteremia. Antimicrob Agents Chemother.practice guidelines by the Infectious Diseases
2016;60(12):7444–8.Society of America and the American Thoracic
10. MacFadden DR, Elligsen M, Robicsek A,Society. Clin Infect Dis. 2016;63(5):e61–111.
Ricciuto DR, Daneman N. Utility of prior screening for20. Stevens DL, Bisno AL, Chambers HF,
methicillin-resistant Staphylococcus aureus inDellinger EP, Goldstein EJC, Gorbach SL, et al.
predicting resistance of S. aureus infections. CMAJ.Executive summary: Practice guidelines for the
2013;185(15):725–30.diagnosis and management of skin and soft tissue
11. Singer M, Deutschman CS, Seymour C,infections: 2014 update by the Infectious Diseases
Shankar-Hari M, Annane D, Bauer M, et al. The thirdSociety of America. Clin Infect Dis. 2014;59(2):147–
international consensus definitions for sepsis and septic59.
shock (sepsis-3). JAMA - J Am Med Assoc.21. Pien BC, Sundaram P, Raoof N, Costa SF,
2016;315(8):801–10.Mirrett S, Woods CW, Reller LB, Weinstein MP
12. Vincent JL, Moreno R, Takala J, Willatts S,(2010). The clinical and prognostic importance of
De Mendonça A, Bruining H, et al. The SOFA (Sepsis-positive blood cultures in adults. Am. J. Med., 123(9),
related Organ Failure Assessment) score to describe819–828.
organ dysfunction/failure. Intensive Care Med.22. Dickstein Y, Geffen Y, Andreassen S,
1996;22(7):707–10.Leibovici L. Paul M (2016). Predicting antibiotic
13. Bone RC, Balk RA, Cerra FB, Dellinger RP,resistance in urinary tract infection patients with prior
Fein AM, Knaus WA, et al. Definitions for sepsis andurine cultures. Antimicrobial Agents and
organ failure and guidelines for the use of innovativeChemotherapy, 60(8), 4717–4721.
therapies in sepsis. Chest. 1992;101(6):1644–55.
14. Shetty A, MacDonald SPJ, Williams JM, van
Bockxmeer J, de Groot B, Esteve Cuevas LM, et al.
Lactate ≥2 mmol/L plus qSOFA improves utility over
qSOFA alone in emergency department patients
presenting with suspected sepsis. EMA - Emerg Med
Australas. 2017;29(6):626–34.
15. Bidell MR, Opraseuth MP, Yoon M, Mohr J,
Lodise TP. Effect of prior receipt of antibiotics on the
pathogen distribution and antibiotic resistance profile
of key Gram negative pathogens among patients with
The prevalence of resistant organisms.
Figure 1. The prevalence of resistant organisms.

References

  1. Adhikari NKJ, Fowler RA, Bhagwanjee S, Rubenfeld GD. Critical care and the global burden of critical illness in adults. Lancet. 2010;376(9749):1339–46.
  2. Rhodes A, Evans LE, Alhazzani W, Levy MM, Antonelli M, Ferrer R, et al. Surviving sepsis campaign: international guidelines for management of sepsis and septic shock: Intensive Care Medicine. 2017;43:304–377.
  3. American Thoracic Society, Infectious Dis- eases Society of America. Guidelines for the man- agement of adults with community-acquired pneu- monia. Infect Dis Clin Pract. 2005;171(4):388–416. Variables Patients with non- resistant organisms (current) N=111 Age, mean (SD) 61.9 ± 18.7 60.5 ± 19.5 0.7* 61.6 ± 18.3 Gender Male 57 (51.4%) 10 (45.5%) 0.6 67 (50.4%) Female 54 (48.6%) 12 (54.5%) 66 (49.6%) Mean number of comorbidities 2.75 ± 1.5 2.45 ± 1.4 0.3* 2.70 ± 1.5 Comorbidities Cardiopulmonary 92 (82.9%) 14 (63.6%) 0.04 106 (79.7%) Medical disease 93 (83.8%) 17 (77.3%) 0.4 110 (82.7%) Oncological 42 (37.8%) 9 (40.9%) 0.7 51 (38.3%) Neurological 56 (50.5%) 12 (54.5%) 0.7 68 (51.1%) Rheumatological 12 (10.8%) 0 0.1 12 (9.0%) Infectious 47 (42.3%) 7 (31.8%) 0.3 54 (40.6%) Surgical disease 54 (48.6%) 10 (45.5%) 0.7 64 (48.1%) Admission diagnosis Medical 106 (95.5%) 20 (90.9%) 0.3 126 (94.7%) Surgical 5 (4.5%) 2 (9.1%) 7 (5.3%) Prior antibiotic exposure 99 (89.2%) 21 (95.5%) 0.3 120 (90.2%) Community-acquired infection 10 (9.0%) 0 0.1 10 (7.5%) Hospital-acquired infection 101 (91.0%) 22 (100%) 0.1 123 (92.5%) Current ICU admission 77 (69.4%) 19 (86.4%) 0.1 96 (72.2%) Immunosuppressive therapy 72 (64.9%) 12 (54.5%) 0.3 84 (63.2%) Cancer treatment therapy 31 (27.9%) 6 (27.3%) 0.9 37 (27.8%) Immunocompromised 10 (9.0%) 3 (16.7%) 0.5 13 (9.8%) Previous colonisation with resistant organisms 22 (19.8%) 17 (77.3%) < 0.001 No previous colonisation with resistant organisms 89 (80.2%) 5 (22.7%) 94 (70.7%)
  4. Sanders KM, Adhikari NKJ, Friedrich JO, Day A, Jiang X, Heyland D. Previous cultures are not clinically useful for guiding empiric antibiotics in suspected ventilator-associated pneumonia: Secondary analysis from a randomised trial. J Crit Care. 2008;23(1):58–63.
  5. Baba H, Nimmo GR, Allworth AM, Boots RJ, Hayashi Y, Lipman J, et al. The role of surveillance cultures in the prediction of susceptibility patterns of Gram-negative bacilli in the intensive care unit. Eur J Clin Microbiol Infect Dis. 2011;30(6):739–44.
  6. Blot S, Depuydt P, Vogelaers D, Decruyenaere J, Waele J De, Hoste E, et al. Colonisation status and appropriate antibiotic therapy for nosocomial bacteremia caused by antibiotic-resistant Gram-negative bacteria in an intensive care unit. Infect Control Hosp Epidemiol. Patients with resistant organisms (current) N=22 p-value All patients (current) n=133 39 (29.3%) The Journal of Medicine, Law & Public Health Vol 3, No 3. 2023 p252 Table
  7. Odds ratios (95% CI) of predictors of antibiotic resistance from multi-variable logistic regression analysis
  8. Variable BOR (95% CI) p- value Age 0.01 1.01 (0.9, 1.06) 0.6 Gender -0.3 0.6 (0.1, 2.2) 0.5 Number of comorbidities 1.3 0.2 (0.003, 22.74) 0.5 Cardiopulmonary disease 2.3 0.09 (0.010, 0.855) 0.03 Medical disease 2.7 15.6 (0.09, 248.5) 0.2 Oncological disease 0.7 2.0 (0.01, 274.6) 0.7 Neurological disease 1.7 5.6 (0.04, 690.2) 0.4 Rheumatological disease 17.4 0 (0) 0.9 Infectious disease 0.4 1.5 (0.01, 211.2) 0.8 Surgical disease 1.6 5.1 (0.03, 757.0) 0.5 Admission diagnosis 0.2 1.3 (0.08, 21.5) 0.8 Prior antibiotic exposure 0.3 1.4 (0.1, 18.9) 0.7 Community-acquired infection 18.7 0 (0) 0.9 Current ICU admission 0.7 2.1 (0.3, 12.4) 0.3 Immunosuppressive therapy 0.8 0.4 (0.1, 1.8) 0.2 Cancer treatment therapy 0.8 2.2 (0.2, 22.2) 0.4 Immunocompromised 1.4 4.4 (0.5, 38.3) 0.1 Previous colonisation with resistant organisms 2.6 13.8 (3.6, 51.9) < .001 Figure
  9. The prevalence of resistant organisms. The Journal of Medicine, Law & Public Health Vol 3, No 3. 2023 p253 2005;26(6):575–9
  10. Papadomichelakis E, Kontopidou F, Antoniadou A, Poulakou G, Koratzanis E, Kopterides P, et al. Screening for resistant Gram-negative microorganisms to guide empiric therapy of subsequent infection. Intensive Care Med. 2008;34(12):2169–75.
  11. MacFadden DR, Coburn B, Shah N, Robicsek A, Savage R, Elligsen M, et al. Utility of prior cultures in predicting antibiotic resistance of bloodstream infections due to Gram-negative pathogens: a multicentre observational cohort study. Clin Microbiol Infect. 2018;24(5):493–9.
  12. Butler-Laporte G, Cheng MP, Cheng AP, McDonald EG, Lee TC. Using MRSA screening tests to predict methicillin resistance in Staphylococcus aureus bacteremia. Antimicrob Agents Chemother. 2016;60(12):7444–8.
  13. MacFadden DR, Elligsen M, Robicsek A, Ricciuto DR, Daneman N. Utility of prior screening for methicillin-resistant Staphylococcus aureus in predicting resistance of S. aureus infections. CMAJ. 2013;185(15):725–30.
  14. Singer M, Deutschman CS, Seymour C, Shankar-Hari M, Annane D, Bauer M, et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA - J Am Med Assoc . 2016;315(8):801–10.
  15. Vincent JL, Moreno R, Takala J, Willatts S, De Mendonça A, Bruining H, et al. The SOFA (Sepsis- related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Med . 1996;22(7):707–10.
  16. Bone RC, Balk RA, Cerra FB, Dellinger RP, Fein AM, Knaus WA, et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. Chest. 1992;101(6):1644–55.
  17. Shetty A, MacDonald SPJ, Williams JM, van Bockxmeer J, de Groot B, Esteve Cuevas LM, et al. Lactate ≥2 mmol/L plus qSOFA improves utility over qSOFA alone in emergency department patients presenting with suspected sepsis. EMA - Emerg Med Australas. 2017;29(6):626–34.
  18. Bidell MR, Opraseuth MP, Yoon M, Mohr J, Lodise TP. Effect of prior receipt of antibiotics on the pathogen distribution and antibiotic resistance profile of key Gram-negative pathogens among patients with hospital-onset urinary tract infections. BMC Infect Dis. 2017;17(1):176.
  19. Kuster SP, Rudnick W, Shigayeva A, Green K, Baqi M, Gold WL, et al. Previous antibiotic exposure and antimicrobial resistance in invasive pneumococcal disease: Results from prospective surveillance. Clin Infect Dis. 2014;59(7):944–52.
  20. Gea-Banacloche JC, Opal SM, Jorgensen J, Carcillo JA, Sepkowitz KA, Cordonnier C. Sepsis associated with immunosuppressive medications: An evidence-based review. Crit Care Med . 2004;32(11 SUPPL.).
  21. Cantwell L, Perkins J. Infectious disease emergencies in oncology patients. Emerg Med Clin North Am . 2018;36(4):795–810.
  22. Kalil AC, Metersky ML, Klompas M, Muscedere J, Sweeney DA, Palmer LB, et al. Management of adults with hospital-acquired and ventilator- clinical associated pneumonia: 2016 practice guidelines by the Infectious Diseases Society of America and the American Thoracic Society. Clin Infect Dis. 2016;63(5):e61–111.
  23. Stevens DL, Bisno AL, Chambers HF, Dellinger EP, Goldstein EJC, Gorbach SL, et al. Executive summary: Practice guidelines for the diagnosis and management of skin and soft tissue infections: 2014 update by the Infectious Diseases Society of America. Clin Infect Dis. 2014;59(2):147– 59.
  24. Pien BC, Sundaram P, Raoof N, Costa SF, Mirrett S, Woods CW, Reller LB, Weinstein MP (2010). The clinical and prognostic importance of positive blood cultures in adults. Am. J. Med. , 123(9), 819–828.
  25. Dickstein Y, Geffen Y, Andreassen S, Leibovici L. Paul M (2016). Predicting antibiotic resistance in urinary tract infection patients with prior urine cultures. Antimicrobial Agents and Chemotherapy, 60(8), 4717–4721.