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Detection of Invasive Pulmonary Aspergillosis in Haematological Malignancy Patients by using Lateral-flow Technology
Published on: March 22, 2012
A clinical algorithm to diagnose invasive pulmonary aspergillosis in critically ill patients
Stijn I Blot1, Fabio Silvio Taccone, Anne-Marie Van den Abeele
1General Internal Medicine and Infectious Diseases, Ghent University Hospital, De Pintelaan 185, Ghent, Belgium. stijn.blot@ugent.be
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.
Insights
A new algorithm effectively distinguishes Aspergillus colonization from invasive aspergillosis in critically ill patients with positive endotracheal aspirates, improving diagnostic accuracy.
Area of Science:
- Critical care medicine
- Infectious diseases
- Mycology
Background:
- Assessing Aspergillus-positive endotracheal aspirates in critically ill patients is challenging.
- Differentiating colonization from invasive pulmonary aspergillosis is crucial for appropriate treatment.
Purpose of the Study:
- To externally validate a clinical algorithm for discriminating Aspergillus colonization from invasive pulmonary aspergillosis.
- To evaluate the algorithm's diagnostic accuracy in critically ill patients.
Main Methods:
- Multicenter observational study of 524 critically ill patients with Aspergillus-positive endotracheal aspirates.
- Algorithm validation using histopathology (gold standard) in 115 patients.
- Comparison with European Organization for the Research and Treatment of Cancer/Mycoses Study Group criteria in the total cohort.
Main Results:
- The algorithm showed 92% sensitivity and 61% specificity in distinguishing aspergillosis.
- In the total cohort, 15.1% had proven invasive pulmonary aspergillosis.
- The algorithm categorized 38.0% as putative aspergillosis and 46.9% as colonization.
Conclusions:
- The validated algorithm demonstrates favorable operating characteristics.
- It can effectively discriminate respiratory tract colonization from invasive pulmonary aspergillosis in critically ill patients.
- This tool aids in better patient management and treatment decisions.
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