Correction to: Chest x-ray severity score in COVID-19 patients on emergency department admission: a two-centre study

Abstract Background Integration of imaging and clinical parameters could improve the stratification of COVID-19 patients on emergency department (ED) admission. We aimed to assess the extent of COVID-19 pulmonary abnormalities on chest x-ray (CXR) using a semiquantitative severity score, correlating it with clinical data and testing its interobserver agreement. Methods From February 22 to April 8, 2020, 926 consecutive patients referring to ED of two institutions in Northern Italy for suspected SARS-CoV-2 infection were reviewed. Patients with reverse transcriptase-polymerase chain reaction positive for SARS-CoV-2 and CXR images on ED admission were included (295 patients, median age 69 years, 199 males). Five readers independently and blindly reviewed all CXRs, rating pulmonary parenchymal involvement using a 0–3 semiquantitative score in 1-point increments on 6 lung zones (range 0–18). Interobserver agreement was assessed with weighted Cohen’s κ, correlations between median CXR score and clinical data with Spearman’s ρ, and the Mann-Whitney U test. Results Median score showed negative correlation with SpO2 (ρ = -0.242, p < 0.001), positive correlation with white cell count (ρ = 0.277, p < 0.001), lactate dehydrogenase (ρ = 0.308, p < 0.001), and C-reactive protein (ρ = 0.367, p < 0.001), being significantly higher in subsequently dead patients (p = 0.003). Considering overall scores, readers’ pairings yielded moderate (κ = 0.449, p < 0.001) to almost perfect interobserver agreement (κ = 0.872, p < 0.001), with better interobserver agreement between readers of centre 2 (up to κ = 0.872, p < 0.001) than centre 1 (κ = 0.764, p < 0.001). Conclusions Proposed CXR pulmonary severity score in COVID-19 showed moderate to almost perfect interobserver agreement and significant but weak correlations with clinical parameters, potentially furthering CXR integration in patients’ stratification.

Download Full-text

Ground-glass opacity on Emergency Department chest X-ray: a risk factor for in-hospital mortality and organ failure in elderly admitted for COVID-19

Postgraduate Medicine ◽

10.1080/00325481.2021.2021741 ◽

2021 ◽

Author(s):

Noel Roig-Marín ◽

Pablo Roig-Rico

Keyword(s):

Emergency Department ◽

Risk Factor ◽

Hospital Mortality ◽

Organ Failure ◽

Ground Glass Opacity ◽

Ground Glass ◽

X Ray ◽

Chest X Ray

Download Full-text

The Hanging Chin Sign As A Mortality Predictor In Geriatric Patients At The Emergency Department: A Retrospective Cohort Study

10.21203/rs.3.rs-496256/v1 ◽

2021 ◽

Author(s):

Anneloes NJ Huijgens ◽

Laurens J van Baardewijk ◽

Carolina JPW Keijsers

Keyword(s):

Emergency Department ◽

Cohort Study ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Geriatric Patients ◽

Lateral View ◽

X Ray ◽

Hospital Patients ◽

Chest X Ray

Abstract BACKGROUND: At the emergency department, there is a need for an instrument which is quick and easy to use to identify geriatric patients with the highest risk of mortality. The so- called ‘hanging chin sign’, meaning that the mandibula is seen to project over one or more ribs on the chest X-ray, could be such an instrument. This study aims to investigate whether the hanging chin sign is a predictor of mortality in geriatric patients admitted through the emergency department. METHODS: We performed an observational retrospective cohort study in a Dutch teaching hospital. Patients of ≥ 65 years who were admitted to the geriatric ward following an emergency department visit were included. The primary outcome of this study was mortality. Secondary outcomes included the length of admission, discharge destination and the reliability compared to patient-related variables and the APOP screener.RESULTS: 396 patients were included in the analysis. Mean follow up was 300 days; 207 patients (52%) died during follow up. The hanging chin sign was present in 85 patients (21%). Patients with the hanging chin sign have a significantly higher mortality risk during admission (OR 2.94 (1.61 to 5.39), p < 0.001), within 30 days (OR 2.49 (1.44 to 4.31), p = 0.001), within 90 days (OR 2.16 (1.31 to 3.56), p = 0.002) and within end of follow up (OR 2.87 (1.70 to 4.84),p < 0.001). A chest X-ray without a PA view or lateral view was also associated with mortality. This technical detail of the chest x-ray and the hanging chin sign both showed a stronger association with mortality than patient-related variables or the APOP screener. CONCLUSIONS: The hanging chin sign and other details of the chest x-ray were strong predictors of mortality in geriatric patients presenting at the emergency department. Compared to other known predictors, they seem to do even better in predicting mortality.

Download Full-text

Chest X-ray Utilization in Febrile Infants 60 Days or Less in the Emergency Department

10.1542/peds.147.3_meetingabstract.275-a ◽

2021 ◽

Author(s):

Erin Bell ◽

Kristen Manto ◽

Giang Ha ◽

Nabeal Aljabban ◽

Lilia Reyes

Keyword(s):

Emergency Department ◽

X Ray ◽

Chest X Ray

Download Full-text

Early clinical predictors of severe acute respiratory syndrome in the emergency department

CJEM ◽

10.1017/s148180350000885x ◽

2004 ◽

Vol 6 (01) ◽

pp. 12-21 ◽

Cited By ~ 2

Author(s):

W.N. Wong ◽

Antonio C.H. Sek ◽

Rick F.L. Lau ◽

K.M. Li ◽

Joe K.S. Leung ◽

...

Keyword(s):

Emergency Department ◽

Severe Acute Respiratory Syndrome ◽

Lymphocyte Count ◽

Case Definition ◽

World Health ◽

Clinical Predictors ◽

X Ray ◽

Abnormal Chest ◽

Contact Exposure ◽

Chest X Ray

ABSTRACT Objectives: To assess the association of diagnostic predictors available in the emergency department (ED) with the outcome diagnosis of severe acute respiratory syndrome (SARS). Methods: This retrospective cohort study describes all patients from the Amoy Garden complex who presented to an ED SARS screening clinic during a 2-month outbreak. Clinical and diagnostic predictors were recorded, along with ED diagnoses. Final diagnoses were established independently based on diagnostic tests performed after the ED visit. Associations of key predictors with the final diagnosis of SARS were described. Results: Of 821 patients, 205 had confirmed SARS, 35 undetermined SARS and 581 non-SARS. Multivariable logistic regression showed that the strongest predictors of SARS were abnormal chest x-ray (odds ratio [OR] = 17.4), subjective fever (OR = 9.7), temperature >38°C (OR = 6.4), myalgias (OR = 5.5), chills and rigors (OR = 4.0) and contact exposure (OR = 2.6). In a subset of 176 patients who had a complete blood cell count performed, the strongest predictors were temperature ≥38ºC (OR = 15.5), lymphocyte count <1000 (OR = 9.3) and abnormal chest x-ray (OR = 5.7). Diarrhea was a powerful negative predictor (OR = 0.03) of SARS. Conclusions: Two components of the World Health Organization case definition — fever and contact exposure — are helpful for ED decision-making, but respiratory symptoms do not discriminate well between SARS and non-SARS. Emergency physicians should consider the presence of diarrhea, chest x-ray findings, the absolute lymphocyte count and the platelet count as significant modifiers of disease likelihood. Prospective validation of these findings in other clinical settings is desirable.

Download Full-text

Simple Pneumonia or Something More?: A Case Report and Discussion of Unexpected Empyema Identified by Point-of-Care Ultrasound

CJEM ◽

10.1017/cem.2015.71 ◽

2015 ◽

Vol 18 (5) ◽

pp. 391-394

Author(s):

Michael Romano ◽

Tomislav Jelic ◽

Jordan Chenkin

Keyword(s):

Emergency Department ◽

Point Of Care ◽

Fluid Collection ◽

Chest Ct ◽

Point Of Care Ultrasound ◽

X Ray ◽

Level Of Consciousness ◽

Chest X Ray ◽

Ultrasound Assessment ◽

Higher Sensitivity

AbstractThere is evidence to suggest that point-of-care ultrasound assessment of the lungs has a higher sensitivity and specificity than chest radiography for the diagnosis of pneumonia. It is unknown if the same is true for pneumonia complications. We present and discuss the case of a 61-year-old woman who presented to the emergency department with confusion, decreased level of consciousness, and signs of sepsis. A chest x-ray revealed a right sided infiltrate. An ultrasound of the patient’s lungs was performed, and revealed a complex loculated fluid collection consistent with an empyema. A chest CT confirmed the diagnosis, and immediate percutaneous drainage was performed.

Download Full-text

Aurea diagnosis of pneumomediastinum. A case report

Italian Journal of Medicine ◽

10.4081/itjm.2020.1292 ◽

2020 ◽

Vol 14 (3) ◽

pp. 179-183

Author(s):

Lucio Brugioni ◽

Francesca De Niederhausern ◽

Chiara Gozzi ◽

Pietro Martella ◽

Elisa Romagnoli ◽

...

Keyword(s):

Emergency Department ◽

Case Report ◽

Chest Pain ◽

Correct Diagnosis ◽

Young Male ◽

Differential Diagnoses ◽

Diagnostic Process ◽

Acute Aortic Syndrome ◽

X Ray ◽

Chest X Ray

Pericarditis and spontaneous pneumomediastinum are among the pathologies that are in differential diagnoses when a patient describes dorsal irradiated chest pain: if the patient is young, male, and long-limbed, it is necessary to exclude an acute aortic syndrome firstly. We present the case of a young man who arrived at the Emergency Department for chest pain: an echocardiogram performed an immediate diagnosis of pericarditis. However, if the patient had performed a chest X-ray, this would have enabled the observation of pneumomediastinum, allowing a correct diagnosis of pneumomediastinum and treatment. The purpose of this report is to highlight the importance of the diagnostic process.

Download Full-text

Sensitivity and specificity of artificial intelligence with Microsoft Azure in detecting pneumothorax in emergency department: A pilot study

Hong Kong Journal of Emergency Medicine ◽

10.1177/1024907920948994 ◽

2020 ◽

pp. 102490792094899

Author(s):

Kwok Hung Alastair Lai ◽

Shu Kai Ma

Keyword(s):

Artificial Intelligence ◽

Emergency Department ◽

Sensitivity And Specificity ◽

National Institutes Of Health ◽

Dramatic Improvement ◽

X Ray ◽

Training Images ◽

Normal Chest ◽

Chest X Ray ◽

Microsoft Azure

Background: Artificial intelligence is becoming an increasingly important tool in different medical fields. This article aims to evaluate the sensitivity and specificity of artificial intelligence trained with Microsoft Azure in detecting pneumothorax. Methods: A supervised learning artificial intelligence is trained with a collection of X-ray images of pneumothorax from National Institutes of Health chest X-ray dataset online. A subset of the image dataset focused on pneumothorax is used in training. Two artificial intelligence programs are trained with different numbers of training images. After the training, a collection of pneumothorax X-ray images from patient attending emergency department is retrieved through the Clinical Data Analysis & Reporting System. In total, 115 pneumothorax patients and 60 normal inpatients are recruited. The pneumothorax chest X-ray and the resolution chest X-ray of the above patient group and a collection of normal chest X-ray from inpatients without pneumothorax will be retrieved, and these three sets of images will then undergo testing by artificial intelligence programs to give a probability of being a pneumothorax X-ray. Results: The sensitivity of artificial intelligence-one is 33.04%, and the specificity is at least 61.74%. The sensitivity of artificial intelligence-two is 46.09%, and the specificity is at least 71.30%. The dramatic improvement of 46.09% in sensitivity and improvement of 15.48% in specificity by addition of around 1000 X-ray images is encouraging. The mean improvement of AI-two over AI-one is 19.7% increase in probability difference. Conclusions: We should not rely on artificial intelligence in diagnosing pneumothorax X-ray solely by our models and more training should be expected to explore its full function.

Download Full-text