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A clinical algorithm to diagnose invasive pulmonary aspergillosis in critically ill patients

Stijn Blot UGent, Fabio Silvio Taccone, Anne-Marie Van den Abeele, Pierre Bulpa, Wouter Meersseman, Nele Brusselaers UGent, George Dimopoulos, José Artur Paiva, Benoit Misset and Jordi Rello, et al. (2012) AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE. 186(1). p.56-64
abstract
Rationale: The clinical relevance of Aspergillus-positive endotracheal aspirates in critically ill patients is difficult to assess. Objectives: We externally validate a clinical algorithm to discriminate Aspergillus colonization from putative invasive pulmonary aspergillosis in this patient group. Methods: We performed a multicenter (n = 30) observational study including critically ill patients with one or more Aspergillus-positive endotracheal aspirate cultures (n = 524). The diagnostic accuracy of this algorithm was evaluated using 115 patients with histopathologic data, considered the gold standard. Subsequently, the diagnostic workout of the algorithm was compared on the total cohort (n = 524), with the categorization based on the diagnostic criteria of the European Organization for the Research and Treatment of Cancer/Mycoses Study Group. Measurements and Main Results: Among 115 histopathology-controlled patients, 79 had proven aspergillosis. The algorithm judged 86 of 115 cases to have putative aspergillosis. This diagnosis was confirmed in 72 and rejected in 14 patients. The algorithm judged 29 patients to have Aspergillus colonization. This was confirmed in 22 and rejected in 7 patients. The algorithm had a specificity of 61% and a sensitivity of 92%. The positive and negative predictive values were 61 and 92%, respectively. In the total cohort (n = 524), 79 patients had proven invasive pulmonary aspergillosis (15.1%). According to the European Organization for the Research and Treatment of Cancer/Mycoses Study Group criteria, 32 patients had probable aspergillosis (6.1%) and 413 patients were not classifiable (78.8%). The algorithm judged 199 patients to have putative aspergillosis (38.0%) and 246 to have Aspergillus colonization (46.9%). Conclusions: The algorithm demonstrated favorable operating characteristics to discriminate Aspergillus respiratory tract colonization from invasive pulmonary aspergillosis in critically ill patients.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
FUNGAL-INFECTIONS, ATTRIBUTABLE MORTALITY, RISK-FACTORS, INTENSIVE-CARE-UNIT, intensive care unit, diagnosis, invasive fungal disease, Aspergillus, invasive pulmonary aspergillosis, DISEASE, GALACTOMANNAN, CONSENSUS, CANCER
journal title
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
Am. J. Respir. Crit. Care Med.
volume
186
issue
1
pages
56 - 64
Web of Science type
Article
Web of Science id
000305669900014
JCR category
RESPIRATORY SYSTEM
JCR impact factor
11.041 (2012)
JCR rank
1/50 (2012)
JCR quartile
1 (2012)
ISSN
1073-449X
DOI
10.1164/rccm.201111-1978OC
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
2096032
handle
http://hdl.handle.net/1854/LU-2096032
date created
2012-04-27 14:00:57
date last changed
2015-06-17 10:01:47
@article{2096032,
  abstract     = {Rationale: The clinical relevance of Aspergillus-positive endotracheal aspirates in critically ill patients is difficult to assess. 
Objectives: We externally validate a clinical algorithm to discriminate Aspergillus colonization from putative invasive pulmonary aspergillosis in this patient group. 
Methods: We performed a multicenter (n = 30) observational study including critically ill patients with one or more Aspergillus-positive endotracheal aspirate cultures (n = 524). The diagnostic accuracy of this algorithm was evaluated using 115 patients with histopathologic data, considered the gold standard. Subsequently, the diagnostic workout of the algorithm was compared on the total cohort (n = 524), with the categorization based on the diagnostic criteria of the European Organization for the Research and Treatment of Cancer/Mycoses Study Group. 
Measurements and Main Results: Among 115 histopathology-controlled patients, 79 had proven aspergillosis. The algorithm judged 86 of 115 cases to have putative aspergillosis. This diagnosis was confirmed in 72 and rejected in 14 patients. The algorithm judged 29 patients to have Aspergillus colonization. This was confirmed in 22 and rejected in 7 patients. The algorithm had a specificity of 61\% and a sensitivity of 92\%. The positive and negative predictive values were 61 and 92\%, respectively. In the total cohort (n = 524), 79 patients had proven invasive pulmonary aspergillosis (15.1\%). According to the European Organization for the Research and Treatment of Cancer/Mycoses Study Group criteria, 32 patients had probable aspergillosis (6.1\%) and 413 patients were not classifiable (78.8\%). The algorithm judged 199 patients to have putative aspergillosis (38.0\%) and 246 to have Aspergillus colonization (46.9\%). 
Conclusions: The algorithm demonstrated favorable operating characteristics to discriminate Aspergillus respiratory tract colonization from invasive pulmonary aspergillosis in critically ill patients.},
  author       = {Blot, Stijn and Taccone, Fabio Silvio and Van den Abeele, Anne-Marie and Bulpa, Pierre and Meersseman, Wouter and Brusselaers, Nele and Dimopoulos, George and Paiva, Jos{\'e} Artur and Misset, Benoit and Rello, Jordi and Vandewoude, Koenraad and Vogelaers, Dirk and AspICU Study Investigators, the},
  issn         = {1073-449X},
  journal      = {AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE},
  keyword      = {FUNGAL-INFECTIONS,ATTRIBUTABLE MORTALITY,RISK-FACTORS,INTENSIVE-CARE-UNIT,intensive care unit,diagnosis,invasive fungal disease,Aspergillus,invasive pulmonary aspergillosis,DISEASE,GALACTOMANNAN,CONSENSUS,CANCER},
  language     = {eng},
  number       = {1},
  pages        = {56--64},
  title        = {A clinical algorithm to diagnose invasive pulmonary aspergillosis in critically ill patients},
  url          = {http://dx.doi.org/10.1164/rccm.201111-1978OC},
  volume       = {186},
  year         = {2012},
}

Chicago
Blot, Stijn, Fabio Silvio Taccone, Anne-Marie Van den Abeele, Pierre Bulpa, Wouter Meersseman, Nele Brusselaers, George Dimopoulos, et al. 2012. “A Clinical Algorithm to Diagnose Invasive Pulmonary Aspergillosis in Critically Ill Patients.” American Journal of Respiratory and Critical Care Medicine 186 (1): 56–64.
APA
Blot, S., Taccone, F. S., Van den Abeele, A.-M., Bulpa, P., Meersseman, W., Brusselaers, N., Dimopoulos, G., et al. (2012). A clinical algorithm to diagnose invasive pulmonary aspergillosis in critically ill patients. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 186(1), 56–64.
Vancouver
1.
Blot S, Taccone FS, Van den Abeele A-M, Bulpa P, Meersseman W, Brusselaers N, et al. A clinical algorithm to diagnose invasive pulmonary aspergillosis in critically ill patients. AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE. 2012;186(1):56–64.
MLA
Blot, Stijn, Fabio Silvio Taccone, Anne-Marie Van den Abeele, et al. “A Clinical Algorithm to Diagnose Invasive Pulmonary Aspergillosis in Critically Ill Patients.” AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE 186.1 (2012): 56–64. Print.