Title |
Rapid evaluation by lung-cardiac-inferior vena cava (LCI) integrated ultrasound for differentiating heart failure from pulmonary disease as the cause of acute dyspnea in the emergency setting
|
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Published in |
Cardiovascular Ultrasound, December 2012
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DOI | 10.1186/1476-7120-10-49 |
Pubmed ID | |
Authors |
Katsuya Kajimoto, Keiko Madeen, Tomoko Nakayama, Hiroki Tsudo, Tadahide Kuroda, Takashi Abe |
Abstract |
Rapid and accurate diagnosis and management can be lifesaving for patients with acute dyspnea. However, making a differential diagnosis and selecting early treatment for patients with acute dyspnea in the emergency setting is a clinical challenge that requires complex decision-making in order to achieve hemodynamic balance, improve functional capacity, and decrease mortality. In the present study, we examined the screening potential of rapid evaluation by lung-cardiac-inferior vena cava (LCI) integrated ultrasound for differentiating acute heart failure syndromes (AHFS) from primary pulmonary disease in patients with acute dyspnea in the emergency setting. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 11 | 31% |
Spain | 5 | 14% |
Australia | 2 | 6% |
United Arab Emirates | 2 | 6% |
Côte d'Ivoire | 1 | 3% |
Saudi Arabia | 1 | 3% |
Colombia | 1 | 3% |
Brazil | 1 | 3% |
Unknown | 12 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Practitioners (doctors, other healthcare professionals) | 19 | 53% |
Members of the public | 14 | 39% |
Scientists | 1 | 3% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Unknown | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 1% |
United Kingdom | 2 | <1% |
Brazil | 1 | <1% |
Saudi Arabia | 1 | <1% |
Unknown | 195 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 27 | 13% |
Researcher | 25 | 12% |
Other | 24 | 12% |
Student > Postgraduate | 19 | 9% |
Student > Doctoral Student | 15 | 7% |
Other | 51 | 25% |
Unknown | 41 | 20% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 125 | 62% |
Nursing and Health Professions | 11 | 5% |
Engineering | 3 | 1% |
Agricultural and Biological Sciences | 2 | <1% |
Computer Science | 2 | <1% |
Other | 10 | 5% |
Unknown | 49 | 24% |