What’s New in Emergencies, Trauma, and Shock – Point-of-care Algorithms for Ultrasound in Emergency Departments: Need of the Hour

IF 1.2 Q3 EMERGENCY MEDICINE Journal of Emergencies, Trauma, and Shock Pub Date : 2023-01-01 DOI:10.4103/jets.jets_118_23
Tarun Sharma, Ashley Grant
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There are many point-of-care ultrasound algorithms such as Extended Focused Assessment with Sonography in Trauma, Bedside Lung Ultrasound (LUS) in Emergency, Rapid Assessment of Dyspnea with Ultrasound, Rapid Ultrasound in Shock, and Focused Echocardiography in Emergency Life Support that have been developed to aid the physician in caring for critically ill patients. However, these can be difficult to perform in a busy ED. Furthermore, many of these protocols are system specific, which may miss localization of an infective focus within other organ systems. Hence, a point-of-care algorithm is needed that is simple and easy to perform and that which helps in the prognostication and management of the patient presenting with fever. The article by Souvik et al.[1] provides a new possible solution that can improve the care of critically ill patient by following a point-of-care algorithm that meets that criteria. At present, the physician is often challenged by being unable to reach a definitive diagnosis in the ED and is, therefore, forced to provide broad spectrum, empiric antimicrobials, as well as other therapies, in the hopes of avoiding patient decompensation. This uncertainty in the etiology of the fever and combined with the delay in obtaining radiological studies promptly due to patient volume surges, can too often lead to poor patient outcomes. This creates a significant need for point-of-care tests such as ultrasound and ABG, which may be used at secondary and tertiary health-care centers by the ED physician to quickly up triage the acutely febrile patient so that they may receive definitive care promptly. At present, there is no standardized protocol incorporating point-of-care ultrasound and ABG in the work-up of the febrile patient that provides systemic evaluation for the source of fever. Very few institutions in India are incorporating structured algorithms for up-triaging a septic patient that utilizes point-of-care testing. The utility of LUS in the diagnosis and management of patients with respiratory illness is well documented.[2,3] The importance of LUS has been proven in emergency medicine to aid in the diagnosis of lung infection. First, it acts as a visual stethoscope aiding the EP with real-time images of the lung, improving their decision power. Second, LUS helps in preventing the movement of hemodynamically unstable patients on ventilation to a radiology suite, thus reducing unnecessary exposure to health-care workers, decreasing risk during transportation, and even more so reducing exposure to computed tomography radiation. Many studies have tested LUS in COVID-19 patients, confirming its high specificity and sensitivity.[4] LUS has proven beyond a doubt that it can be utilized in the prediction of which patients coming to ED will require ventilation, either by intubation or by noninvasive methods. LUS does have its few limitations; for example, it is operator dependent and requires training for image acquisition and interpretation. Renal arterial resistive index (RI) has shown in various studies that it can be a reliable indicator that accurately reflects renal damage. It is also a harbinger of renal replacement therapy. The association between acute kidney injury (AKI) in sepsis and renal RI suggests a pathophysiological reasoning, reflecting the renal structural alterations in the tubule-interstitial and vascular compartments and consequent increases in renal impedance values.[5] Lactate in ABG suggests the presence of sepsis and has been incorporated as a defining marker by the Center for Disease Control and Prevention Surviving Sepsis Guidelines. The positive association observed between renal RI and lactate could indicate that high renal RI values may be associated with greater clinical severity. These data are corroborated by a recent description of an independent association of renal RI with intensive care unit mortality in patients with high renal RI values measured at the time of AKI diagnosis.[5] Considering the enormous sepsis-induced burden on health-care systems, in conjunction with the complex nature of sepsis-associated causes and symptoms, it is obvious that the integration of point-of-care tests for early diagnosis, management, and triaging of these patients in the ED is not only useful but also of critical importance. The article by Souvik et al.[1] is a step forward in this direction. There is a need for further development of an algorithm for ED patients that readily identifies the source of sepsis. 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Abstract

Sepsis is a syndrome characterized by infection, widespread inflammation, and organ dysfunction affecting millions of people in India and worldwide each year. Although the most common presentation of sepsis is fever, the source of infection is often not known at the time of presentation to the emergency department (ED), requiring physicians to provide broad-spectrum and empiric antibiotics. The incorporation of ultrasound into the point-of-care tests available to the emergency medicine physician, such as arterial blood gas (ABG) and other biomarkers, has become essential in the resuscitation, management, and prognostication of the ED patient. There are many point-of-care ultrasound algorithms such as Extended Focused Assessment with Sonography in Trauma, Bedside Lung Ultrasound (LUS) in Emergency, Rapid Assessment of Dyspnea with Ultrasound, Rapid Ultrasound in Shock, and Focused Echocardiography in Emergency Life Support that have been developed to aid the physician in caring for critically ill patients. However, these can be difficult to perform in a busy ED. Furthermore, many of these protocols are system specific, which may miss localization of an infective focus within other organ systems. Hence, a point-of-care algorithm is needed that is simple and easy to perform and that which helps in the prognostication and management of the patient presenting with fever. The article by Souvik et al.[1] provides a new possible solution that can improve the care of critically ill patient by following a point-of-care algorithm that meets that criteria. At present, the physician is often challenged by being unable to reach a definitive diagnosis in the ED and is, therefore, forced to provide broad spectrum, empiric antimicrobials, as well as other therapies, in the hopes of avoiding patient decompensation. This uncertainty in the etiology of the fever and combined with the delay in obtaining radiological studies promptly due to patient volume surges, can too often lead to poor patient outcomes. This creates a significant need for point-of-care tests such as ultrasound and ABG, which may be used at secondary and tertiary health-care centers by the ED physician to quickly up triage the acutely febrile patient so that they may receive definitive care promptly. At present, there is no standardized protocol incorporating point-of-care ultrasound and ABG in the work-up of the febrile patient that provides systemic evaluation for the source of fever. Very few institutions in India are incorporating structured algorithms for up-triaging a septic patient that utilizes point-of-care testing. The utility of LUS in the diagnosis and management of patients with respiratory illness is well documented.[2,3] The importance of LUS has been proven in emergency medicine to aid in the diagnosis of lung infection. First, it acts as a visual stethoscope aiding the EP with real-time images of the lung, improving their decision power. Second, LUS helps in preventing the movement of hemodynamically unstable patients on ventilation to a radiology suite, thus reducing unnecessary exposure to health-care workers, decreasing risk during transportation, and even more so reducing exposure to computed tomography radiation. Many studies have tested LUS in COVID-19 patients, confirming its high specificity and sensitivity.[4] LUS has proven beyond a doubt that it can be utilized in the prediction of which patients coming to ED will require ventilation, either by intubation or by noninvasive methods. LUS does have its few limitations; for example, it is operator dependent and requires training for image acquisition and interpretation. Renal arterial resistive index (RI) has shown in various studies that it can be a reliable indicator that accurately reflects renal damage. It is also a harbinger of renal replacement therapy. The association between acute kidney injury (AKI) in sepsis and renal RI suggests a pathophysiological reasoning, reflecting the renal structural alterations in the tubule-interstitial and vascular compartments and consequent increases in renal impedance values.[5] Lactate in ABG suggests the presence of sepsis and has been incorporated as a defining marker by the Center for Disease Control and Prevention Surviving Sepsis Guidelines. The positive association observed between renal RI and lactate could indicate that high renal RI values may be associated with greater clinical severity. These data are corroborated by a recent description of an independent association of renal RI with intensive care unit mortality in patients with high renal RI values measured at the time of AKI diagnosis.[5] Considering the enormous sepsis-induced burden on health-care systems, in conjunction with the complex nature of sepsis-associated causes and symptoms, it is obvious that the integration of point-of-care tests for early diagnosis, management, and triaging of these patients in the ED is not only useful but also of critical importance. The article by Souvik et al.[1] is a step forward in this direction. There is a need for further development of an algorithm for ED patients that readily identifies the source of sepsis. This algorithm should be simple and easy to perform while also requiring minimal training to achieve its mastery.
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急诊、创伤和休克的新进展——急诊科超声护理点算法:时间的需要
Souvik等人[1]的文章在这个方向上迈出了一步。有必要进一步发展一种算法,为ED患者容易识别脓毒症的来源。这个算法应该是简单和容易执行的,同时也需要最少的训练来达到它的精通。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.90
自引率
7.10%
发文量
52
审稿时长
39 weeks
期刊最新文献
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