For people presenting with chest trauma in the emergency department, how does chest ultrasonography compare with supine chest X-ray for the diagnosis of pneumothorax?

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.

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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

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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.

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Pneumomediastinum in Blunt Chest Trauma: A Case Report and Review of the Literature

Case Reports in Emergency Medicine ◽

10.1155/2014/685381 ◽

2014 ◽

Vol 2014 ◽

pp. 1-6 ◽

Cited By ~ 3

Author(s):

Gregory Mansella ◽

Roland Bingisser ◽

Christian H. Nickel

Keyword(s):

Case Report ◽

Physical Examination ◽

Blunt Chest Trauma ◽

Chest Trauma ◽

Common Mechanism ◽

Cervical Trauma ◽

X Ray ◽

Retrosternal Pain ◽

Chest X Ray ◽

Bedside Diagnosis

Blunt trauma is the most common mechanism of injury in patients with pneumomediastinum and may occur in up to 10% of patients with severe blunt thoracic and cervical trauma. In this case report we present a 24-year-old man with pneumomediastinum due to blunt chest trauma after jumping from a bridge into a river. He complained of persistent retrosternal pain with exacerbation during deep inspiration. Physical examination showed only a slight tenderness of the sternum and the extended Focused Assessment with Sonography for Trauma (e-FAST) was normal. Pneumomediastinum was suspected by chest X-ray and confirmed by computed tomography, which showed a lung contusion as probable cause of the pneumomediastinum due to the “Mackling effect.” Sonographic findings consistent with pneumomediastinum, like the “air gap” sign, are helpful for quick bedside diagnosis, but the diagnostic criteria are not yet as well established as for pneumothorax. This present case shows that despite minimal findings in physical examination and a normal e-FAST a pneumomediastinum is still possible in a patient with chest pain after blunt chest trauma. Therefore, pneumomediastinum should always be considered to prevent missing major aerodigestive injuries, which can be associated with a high mortality rate.

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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.

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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.

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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.

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