IFI in Critical Care setting an unproven story

1. Possibility or probability of
yeasts in the ICU
Do we really need to think them ?
SMR. Hashemian. MD.FCCM
smrhashemian@yahoo.com
American College of Critical Care Medicine Fellowship
Associate Professor of Critical Care /NRITLD/SBMU/Iran
1

2. Epidemiology of Candida BSI
Wisplinghoff H et al. Nosocomial bloodstream infection in US hospitals. Analysis of 24,179 cases
From a prospective nationwide surveillance study. Clin Infect Dis 2004; 39: 309-317.
• 4th
most common cause of nosocomial BSI, 3rd
of ICU BSI
• Represents 8-11% of all nosocomial BSI
• HIGHHIGH mortality + attributable mortality 15-25% for candidaemia
• Non-albicans increasing, especially in cancer patients
• 4th
most common cause of nosocomial BSI, 3rd
of ICU BSI
• Represents 8-11% of all nosocomial BSI
• HIGHHIGH mortality + attributable mortality 15-25% for candidaemia
• Non-albicans increasing, especially in cancer patients
2

3. Independent risk factors for Candida BSI
Independent Variable Relative risk Odds ratio
Abdominal surgery 7.3
Triple lumen CVC 5.4
Acute renal failure 4.2
Parenteral nutrition 3.6
Multiple antibiotics 12.5
Candida elsewhereCandida elsewhere 10.4
ICU > 7 days 9.8
Schelenz S. Management of candidiasis in the intensive care unit. J Antimicrob Chemother 2008; 61 Suppl 1: i31-i34.
Blumberg HM et al. Risk factors for candidal bloodstream infections in surgical intensive care unit patients: the NEMIS
prospective multicenter study. Clin Infect Dis 2001; 33: 177-86.
3

4. 2008
4

5. 5

6. Cultured CandidaCultured Candida
ColonisationColonisation
Signs of sepsis ? sourceSigns of sepsis ? source
ProphylacticProphylactic
Presence of Risk FactorsPresence of Risk Factors
Targeted
Prophylactic
Targeted
Prophylactic
Targeted
Empiric
Targeted
Empiric
Empiric (No
colonisation)
Empiric (No
colonisation)
Candida ColonisationCandida Colonisation
Therapy Classification
TargetedTargeted
Adapted from Grenouillet F et al. J Invasive Fungal Infect 2007; 1(2): 42–9. 6

7. Risk Factor Selection
Underlying
disease
Antibiotics
Colonization
Fever
Selection
Skin or
mucosa
damage
Infection
Malignancy
Diabetes
Renal disease
steroids
Malnutrition on TPN
Mechanical Ventilation > 48h
Burns
Instruments
CV Catheter
Knife

8. What we know…
• Early adequate therapy improves outcome
– OR for death with appropriate therapy = 0.46 (p=0.05)
– Therapy started day 0 mortality = 15%
– Therapy started day 1 mortality = 24%
– Therapy started day 2 mortality = 37%
– Therapy started beyond day 2 mortality = 41%
• Wrong drug at wrong time = poor outcome
Parkins MD et al. J Antimicrob Chemother 2007; 60: 613-8.
Garey KW et al. Clin Infect Dis 2006: 43: 25-31.
Morrell M et al. Antimicrob Agents Chemother 2005: 49: 3640-3645.
8

9. Diagnosis
9

10. Pema´n J et al. Mycoses 2009.
Saragoza R et al. Clin Vaccine Immunol 2009; 16:1527–1528.
•A Spanish group has developed an antibody
test against the germ-tube structure of Candida
albicans cells developing when growing in
culture or invading host tissue (C. albicans IFA
IgG, Vircell, Spain).
•Applying this test to various patients
populations they have observed that patients
with positive CAGTA Candida albicans Germ
Tube Antibody had a better outcome than those
with negative antibodies.
10

11. •Direct molecular detection of Candida DNA
circulating in blood has been tried for almost
two decades, without much success due to the
usually low yeast burden, as well as the
difficulty of extracting yeast DNA and
separating it from human DNA.
Wallet F et al. Clin Microbiol Infect 2010; 16:774–779.
11

12. This increased sensitivity implies mostly C. albicans,
whereas twice more C. glabrata were detected by
blood culture than by SF, but the true clinical
significance of these findings has not been
systematically assessed and reported.
The performance of the Septifast real-time multiplex PCR
10 studies, 100
febrile episodes
or samples each
SEPTIFAST BLOOD CULTURE
19 positive 8 positive
Bille J et al. Curr Opin Crit Care 2010 16:460–464
12

13. NEWER TESTS
- Another commercially available multiplex PCR test
(Vyoo; SIRS-Lab, Jena, Germany) claims to detect
Candida species, but no comparative trial has been
published so far.
- An 18S rRNA broad-range PCR following an
improved DNA detection method (MolYsis; Molzym,
Bremen, Germany) has shown at least twice as many
positive results when compared to blood cultures.
Wellinghausen N et al. J Med Microbiol 2009; 58:1106–1111.
13

14. Recent approaches to reduce the delay of positivity from
blood cultures:
-fluorescence in-situ hybridization test (PNA FISH
AdvanDX, Woburn, Massachusetts, USA) differentiates
the five most prevalent species of Candida.
More time consuming and expensive of FISH, allows the
identification of more species of Candida than the FISH
test does.
PNA FISH
14

15. MALDI-TOF-MS
•The recent application to clinical microbiology of an
old technique based on the measurement of the
molecular masses of proteins and other microbial
components from whole bacterial extracts.
•This approach allows the identification of bacteria and
yeast from isolated colonies in a few minutes with an
accuracy of more than 90% when compared to
conventional identification results.
Seng P et al. Clin Infect Dis 2009; 49:543–551.
Van Veen SQ et al. J Clin Microbiol 2010; 48:900–907.
Marklein G et al. J Clin Microbiol 2009; 47:2912–2917.
15

16. Is MALDI-TOF a revolution in the microbiology
laboratory [Seng P et al. Clin Infect Dis 2009; 49:543–551] ?
16

17. Late diagnosis with culture-based
methods
Slide 17
• Blood cultures lack sensitivity (<50%)
• Positive cultures are usually late
• Invasive tissue sampling is often problematic
• Radiological signs appear often late in the course
of infection

18. Non-culture-based Methods
Slide 18
CLINICAL MICROBIOLOGY REVIEWS, July 2002, p. 465–484

19. IFI diagnostic test
Guery BP et al. Management of invasive candidiasis and candidemia in adult non-neutropenic
intensive care unit patients: Part I. Epidemiology and diagnosis. Intensive Care Med 2008 DOI
10.1007/s00134-008-1338-7
19

20. 2013
20

21. SSC 2013 :Rationale
• The diagnosis of systemic fungal infection
(usually candidiasis) in the critically ill patient can
be challenging, and rapid diagnostic
methodologies, such as antigen and antibody
detection assays, can be helpful in detecting
candidiasis in the ICU patient.
• These suggested tests have shown positive
results significantly earlier than standard culture
methods .
21

22. SSC 2013: We suggest
• the use of the 1,3 β-d-glucan
assay (grade 2B),mannan and
anti-mannan antibody assays
(grade 2C) when invasive candidiasis is in
the differential diagnosis of infection.
22

23. 23

24. IS IA A PROBLEM IN THE ICU?
24

25. Retrospective autopsy-controlled
studies
•127 (6.9%) of 1850 hospitalized patients had
microbiologic or histopathologic evidence of
aspergillosis during their ICU stay, including 89 cases
(70%) in which there was not an underlying hematological
malignancy.
•The observed mortality rate of 80% was much higher
than the mortality rate predicted on the basis of the
Simplified Acute Physiology Score II (48%).
Meersseman W et al. Am J Respir Crit Care Med 2004;170:621–5
•A study sought unsuspected causes of death in a ICU
revealed that, among 100 autopsies, there were 15 cases
of IA, of which 5 were missed before death.
Roosen J et al. Mayo Clin Proc 2000; 75:562–7.
25

26. WHO IS AT RISK OF
DEVELOPING IA
IN THE ICU?
26

27. Meersseman W et al. Clin Infect Dis 2007; 45: 205-16
27

28. Which diseases are
associated to IA in
the ICU?
28

29. COPD AND ASPERGILLOSIS
Lin SJ et al. Clin Infect Dis 2001; 32: 358-66
• In a review of 50 studies, COPD was the underlying
condition in 26 out of 1,941 (1.3%) patients with
aspergillosis
• In one large study, 9% of 595 patients with IA suffered
from pulmonary disease Patterson TF et al. Medicine 2000; 79: 250-60
• Steroids are believed to play a role in the emergence of IA, and some authors have
investigated the correlation between the daily dose of corticosteroids and the probability of
developing IA Leav BA et al. N Engl J Med 2000; 343: 586
29

30. Samarakoon P et al. Chronic Resp Dis 2008; 5: 19-27
30

31. Meersseman W et al. Am J Respir Crit Care Med 2008; 177:27-34
31

32. What is the meaning of
Aspergillus colonization?
32

33. Bouza E et al. J Clin Microbiol 2005; 43:2075-9
33

34. 2008
• Pulmonary Aspergillosis in Solid
Organ Transplant Patients: A
Report From Iran
• M. Marjani, Tabarsi, K. Najafizadeh, F.R. Farokhi, B. Sharifkashani
• , S. Motahari, A. Abbasi, M.R. Masjedi, D. Mansour
Aspergillosis in 8 lung, 3 kidney, andAspergillosis in 8 lung, 3 kidney, and
1 heart recipient, with overall mean1 heart recipient, with overall mean
age of 40.6 yearsage of 40.6 years
34

35. Comparison of Serum and Bronchoalveolar Lavage
Galactomannan in Diagnosing Invasive Aspergillosis in
Solid-Organ Transplant Recipients
•Payam Tabarsi,¹ Abdolreza Soraghi,¹ Majid Marjani,¹ Paris Zandian,¹ Parvaneh Baghaei,¹
Katayoon Najafizadeh,¹ Atoosa Droudinia,¹ Shokooh Azam Sarrafzadeh,² Pedram
Javanmard,¹ Davood Mansouri¹
•17 patients were included (17 patients were included (lung, 15; heart, 1; heart-lung, 1lung, 15; heart, 1; heart-lung, 1). Probable or definite). Probable or definite
invasive aspergillosis was diagnosed in 9 patientsinvasive aspergillosis was diagnosed in 9 patients. With a cutoff ≥ 0.5, serum. With a cutoff ≥ 0.5, serum
galactomannan sensitivity and specificity for diagnosing invasive aspergillosis weregalactomannan sensitivity and specificity for diagnosing invasive aspergillosis were
77.18% and 100%.77.18% and 100%.
•Negative predictive value and positive predictive value were 80% and 100%. TheNegative predictive value and positive predictive value were 80% and 100%. The
sensitivity and specificity of bronchoalveolar lavage galactomannan for diagnosingsensitivity and specificity of bronchoalveolar lavage galactomannan for diagnosing
invasive aspergillosis with cutoff of ≥ 0.5 was 100%.invasive aspergillosis with cutoff of ≥ 0.5 was 100%.
35

36. Candida in ICU
36

37. Candida in the ICU
- Risk factors-
Risk factors for candidemiacandidemia in patients in the ICU
include:
•the use of intravascular catheters,
•parenteral nutrition
•prior abdominal surgery
•the use of broad-spectrum antibacterial therapy
•the use of corticosteroids
•AKI
•a prolonged stay in the ICU,
•and Candida colonization, particularly if it is multifocal.
Bouza E et al. Int J Antimicrob Agents 2008;32(Suppl 2):S87–91.
37

38. Diagnostic Tools
Slide 38

39. The Colonization Index (CI) & CCI
Slide 39
Pittet D et al. Ann Surg. 1994 Dec;220(6):751-8
Number of colonized sites
Number of tested sites
CI=
Number of site with heavy colonization
Number of tested sites
CCI= CI X

40. The Colonization Index (CI) & CCI
Slide 40
Pittet D et al. Ann Surg. 1994 Dec;220(6):751-8

41. The Colonization Index
Slide 41
Pittet D et al. Ann Surg. 1994 Dec;220(6):751-8

42. Candida score
The “Candida score” cut-off value is 2.5 (sensitivity 81%,
specificity 74%)
Leon C et al. Crit Care Med 2006; 34:730–737 42

43. The Candida Score
Slide 43
Leon C et al. Crit Care Med. 2006 Mar;34(3):730-7
Coefficient (β) Rounded
Multifocal Candida species
colonization
1.112 1
Surgery on ICU admission 0.997 1
Severe sepsis 2.038 2
Total parenteral nutrition 0.908 1
Calculation of the Candida score:

44. The Candida Score
Slide 44
Leon C et al. Crit Care Med. 2006 Mar;34(3):730-7
With a cut-off value of 2.5: sensitivity of 81% and a specificity of 74%, we
shall only need the presence of sepsis and any one of the three other
remaining risk factors or the presence of all of them together except sepsis
in order to consider starting antifungal treatment for one particular patient.

45. Prediction
Slide 45

46. 2007 Prediction rule
Ostrosky-Zeichner L et al. Eur J Clin Microbiol Infect Dis 2007; 26:271-276
•Analysis of risk factors in 2,890 patients who stayed in the ICU for
more than 4 days
•The best prediction rule used a combination of the following factors:
-any systemic Antibiotic or presence of central venous catheter and
at least 2 other risk factors, including
- Total Parenteral Nutrition,
- major surgery,
- pancreatitis,
- any use of steroids and use of immunosuppressive agents.
•This prediction rule exhibited a sensitivity of 34%, a specificity of
90%, a positive predictive value of 10% and a negative predictive
value of 97%.
•This clinical rule may therefore help clinicians to rule out invasive
candididiasis.
•Analysis of risk factors in 2,890 patients who stayed in the ICU for
more than 4 days
•The best prediction rule used a combination of the following factors:
-any systemic Antibiotic or presence of central venous catheter and
at least 2 other risk factors, including
- Total Parenteral Nutrition,
- major surgery,
- pancreatitis,
- any use of steroids and use of immunosuppressive agents.
•This prediction rule exhibited a sensitivity of 34%, a specificity of
90%, a positive predictive value of 10% and a negative predictive
value of 97%.
•This clinical rule may therefore help clinicians to rule out invasive
candididiasis.
46

47. One of the
following
factors:
Systemic Antibiotic Presence of CVC
+ at least two
other risk factors
Total parenteral nutrition
Major surgery
Pancreatitis
Any use of steroids
Use of immunosuppressive agents
Clinical Prediction Rule
Slide 47
Ostrosky-Zeichner L et al. Eur J Clin Michrobiol Infect Dis 2007, 26:271-276
Sensitivity of 34% and specificity of 90%, a positive predictive value of
10% an a negative predictive value of 97%.
Mainly helps in ruling out invasive candidiasis

48. Leon C et al. Crit Care Med 2009; 37:1624 –1633
Is the CS useful for discriminating between Candida
colonization and invasive candidiasis in non-
neutropenic critically ill patients?
•Prospective, cohort, observational study on 1107 pts
for >7 d in ICU
•A CS>=3 selected pts at high risk for IC
•IC=2.3% if CS<3
•(1–3)-Beta-D-glucan was also an independent predictor of
IC (odds ratio 1.004, 95% CI 1.0 –1.007)
48

49. 49

50. CS,,,Cristobal Leon 2009 CCM
Leon C et al. Crit Care Med 2009; 37:1624 –1633
50

51. Leon C et al. Crit Care Med 2009; 37:1624 –1633
CS,,,Cristobal Leon 2009 CCM
51

52. 2011
52

53. 53

54. 2011 NMC rule
Nebraska
54

55. 55

56. 56

57. 57

58. 58

59. NMC
59

60. SAT 2012 CCM
60

61. 61

62. 62

63. 63

64. 7.5% SAT,2/3 no IFI
64

65. L.Ostrosky.Z (Purple)KEY
65

66. 66

67. Predictors of SAT
• included
• smaller hospital size, an onsite transplant
• program, and a perceived high incidence
• of Candida infections in the previous year.
• Although there was a trend for improved
• adjusted 28-day survival, the authors
• failed to find any difference in outcome
• for the patients who received SAT.
67

68. 36 ICU Spain,France,Argentina
2012
68

69. 69

70. Tendency
• 38 candidemias were diagnosed in 1,107
patients
Patients with and without candidemia had an
ICU crude mortality of 52.6% versus 20.6%
(P < 0.001)
70

71. Propensity score matching
analysis(PSM)
71

72. Italy 2013
ICU-acquired candidemia in critically illICU-acquired candidemia in critically ill
patients is not associated with an increasepatients is not associated with an increase
in either ICU or hospital mortality.in either ICU or hospital mortality. 72

73. 73

74. 2009
74

75. 2010
75

76. Calibration model
76

77. 77

78. Modification 2013
Modification of Acute Physiology and Chronic Health Evaluation II score through
recalibration of risk prediction model in critical care patients of a respiratory
disease referral center
Ali A. Velayati, Yadollah Mehrabi, Golnar Radmand,1
Ali A Khadem Maboudi,1
Hamid R.
Jamaati,2
A. Shahbazi,3
Seyed A. Mohajerani,3
and Seyed M R. Hashemian
Modification of Acute Physiology and Chronic Health Evaluation II score through
recalibration of risk prediction model in critical care patients of a respiratory
disease referral center
Ali A. Velayati, Yadollah Mehrabi, Golnar Radmand,1
Ali A Khadem Maboudi,1
Hamid R.
Jamaati,2
A. Shahbazi,3
Seyed A. Mohajerani,3
and Seyed M R. Hashemian
78

79. 79

80. Probability
80

81. 81

82. Fungal Infection Risk Evaluation
(FIRE)
2013
Better targeting of antifungal prophylaxis
to improve care and outcomes…

83. FIRE dataset
Dataset defined in five sections:
• Patient details
• Pre-admission
• First 24 hours
• By end of calendar day 3
• Outcomes
83

84. FIRE dataset – Outcomes
– Fungal colonisation
– Invasive fungal disease
– Use of systemic antifungal drugs
– Use of topical antifungal drugs
– Surgery (first during unit stay)
84

85. 85

86. Economic modelling to assess the cost-effectiveness of prophylaxis
based on the risk models for invasive Candida infection
• The decision model was populated with
estimates of positive predictive value (the
proportion of those identified as high risk who
subsequently developed invasive Candida
infection) and negative predictive value (the
proportion of those identified as low risk who did
not subsequently develop invasive Candida
infection)
86

87. Data collection for risk factors and outcomes
of invasive fungal disease
• Data on 60,778 admissions to 96 adult general
critical care units were collected between July
2009 and March 2011. The reliability study
identified substantial over-reporting of IFD in the
original data submissions, suggesting difficulty in
correctly applying the IFD definitions.
87

88. 88