Commentaries on ‘Rapid viral diagnosis for acute febrile respiratory illness in children in the Emergency Department’

2010 ◽  
Vol 5 (2) ◽  
pp. 754-757
Author(s):  
Jonathan M. Mansbach ◽  
Carlos A. Camargo ◽  
Amy C. Plint
Keyword(s):  
Emergency Department ◽  
Respiratory Illness ◽  
Febrile Respiratory Illness ◽  
Viral Diagnosis

Emergency Department Management of Febrile Respiratory Illness in Children

2016 ◽  
Vol 32 (7) ◽  
pp. 429-434 ◽  
Author(s):  
Sonal Shah ◽  
Florence Bourgeois ◽  
Rebekah Mannix ◽  
Kyle Nelson ◽  
Richard Bachur ◽  
...  
Keyword(s):  
Emergency Department ◽  
Respiratory Illness ◽  
Emergency Department Management ◽  
Febrile Respiratory Illness ◽  
Department Management

scholarly journals Clinical Validation of a Deep Learning Algorithm for Detection of Pneumonia on Chest Radiographs in Emergency Department Patients with Acute Febrile Respiratory Illness

2020 ◽  
Vol 9 (6) ◽  
pp. 1981
Author(s):  
Jae Hyun Kim ◽  
Jin Young Kim ◽  
Gun Ha Kim ◽  
Donghoon Kang ◽  
In Jung Kim ◽  
...  
Keyword(s):  
Emergency Department ◽  
Deep Learning ◽  
Performance Test ◽  
Respiratory Illness ◽  
Chest Radiographs ◽  
Observer Performance ◽  
Operating Characteristics ◽  
Predictive Values ◽  
Febrile Respiratory Illness ◽  
Sensitivity Specificity

Early identification of pneumonia is essential in patients with acute febrile respiratory illness (FRI). We evaluated the performance and added value of a commercial deep learning (DL) algorithm in detecting pneumonia on chest radiographs (CRs) of patients visiting the emergency department (ED) with acute FRI. This single-centre, retrospective study included 377 consecutive patients who visited the ED and the resulting 387 CRs in August 2018–January 2019. The performance of a DL algorithm in detection of pneumonia on CRs was evaluated based on area under the receiver operating characteristics (AUROC) curves, sensitivity, specificity, negative predictive values (NPVs), and positive predictive values (PPVs). Three ED physicians independently reviewed CRs with observer performance test to detect pneumonia, which was re-evaluated with the algorithm eight weeks later. AUROC, sensitivity, and specificity measurements were compared between “DL algorithm” vs. “physicians-only” and between “physicians-only” vs. “physicians aided with the algorithm”. Among 377 patients, 83 (22.0%) had pneumonia. AUROC, sensitivity, specificity, PPV, and NPV of the algorithm for detection of pneumonia on CRs were 0.861, 58.3%, 94.4%, 74.2%, and 89.1%, respectively. For the detection of ‘visible pneumonia on CR’ (60 CRs from 59 patients), AUROC, sensitivity, specificity, PPV, and NPV were 0.940, 81.7%, 94.4%, 74.2%, and 96.3%, respectively. In the observer performance test, the algorithm performed better than the physicians for pneumonia (AUROC, 0.861 vs. 0.788, p = 0.017; specificity, 94.4% vs. 88.7%, p < 0.0001) and visible pneumonia (AUROC, 0.940 vs. 0.871, p = 0.007; sensitivity, 81.7% vs. 73.9%, p = 0.034; specificity, 94.4% vs. 88.7%, p < 0.0001). Detection of pneumonia (sensitivity, 82.2% vs. 53.2%, p = 0.008; specificity, 98.1% vs. 88.7%; p < 0.0001) and ‘visible pneumonia’ (sensitivity, 82.2% vs. 73.9%, p = 0.014; specificity, 98.1% vs. 88.7%, p < 0.0001) significantly improved when the algorithm was used by the physicians. Mean reading time for the physicians decreased from 165 to 101 min with the assistance of the algorithm. Thus, the DL algorithm showed a better diagnosis of pneumonia, particularly visible pneumonia on CR, and improved diagnosis by ED physicians in patients with acute FRI.

Investigation of an Outbreak of Acute Febrile Respiratory Illness Among Recruits at Lackland Air Force Base, TX

2001 ◽  
Author(s):  
Michelle R. Torok ◽  
Jessia A. Benevento ◽  
Inga R. Heemink ◽  
James S. Neville ◽  
Katerina M. Neuhauser
Keyword(s):  
Air Force ◽  
Respiratory Illness ◽  
Febrile Respiratory Illness ◽  
Air Force Base

scholarly journals Acute Febrile Respiratory Illness in the ICU

CHEST Journal ◽  
2008 ◽  
Vol 133 (5) ◽  
pp. 1221-1231 ◽  
Author(s):  
Christian Sandrock ◽  
Nicholas Stollenwerk
Keyword(s):  
Respiratory Illness ◽  
Febrile Respiratory Illness
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