Out-of-hospital Shock Index as an Outcome Predictor in the Emergency Department

2006 ◽  
Vol 13 (5Supplement 1) ◽  
pp. S74-S74
Author(s):  
J. G. McManus
Keyword(s):  
Emergency Department ◽  
Shock Index ◽  
Outcome Predictor

scholarly journals A Study on Shock Index in Early Diagnosis of Sepsis in Emergency Department of Tertiary Care Centre of Nepal

2019 ◽  
Vol 2 (2) ◽  
pp. 37-42
Author(s):  
Manish Nath Pant ◽  
Subash Dawadi ◽  
Ashish Thapa
Keyword(s):  
Emergency Department ◽  
Heart Rate ◽  
Severe Sepsis ◽  
Early Diagnosis ◽  
Blood Lactate ◽  
Lactate Level ◽  
Tertiary Care ◽  
Serum Lactate ◽  
Shock Index ◽  
Tertiary Care Centre

Introduction: Sepsis and its consequences, severe sepsis and septic shock is at menace in country like ours where infectious disease are at toll. Early diagnosis and treatment is very important to decrease the morbidity and mortality. Shock index is one of such tool that is very handy in these situations as this is just a mathematical calculation using heart rate(HR) and systolic blood pressure(SBP). The main aim of this study was to find the effectiveness of using SI as an adjunct to blood lactate in diagnosing patients in sepsis. Methods: This was an observational hospital-based study conducted at Emergency Department of TUTH, Maharajgunj on 104 patients, obtained by purposive sampling method, who had presented to the “Red Area”, aged between 18 to 65 years. These patients were screened for severe sepsis using triage vital signs, basic laboratory tests and an initial serum lactate level. Test characteristics were calculated for hyperlactatemia. I considered the following covariates in our analysis: heart rate >90 beats/min; mean arterial pressure <65 mmHg; respiratory rate > 20 breaths/min; ≥2 SIRS including white blood cell count; SI <0.6; SI 0.6 to 1; SI 1 to 1.4and SI ≥ 1.4.  Results: There was a positive correlation between shock index and blood lactate level, r=0.2, n=104, p=0.042. No relationship was found between SI>=1 and hyperlactemia, X2 (.285, N = 104) = 1, p =.594 and relationship was found between SI >=0.7 and hyperlactemia, X2 (4.1, N = 104) = 1, p =.04. sensitivity and specificity for detecting hyperlactemia of SI>=1, SI.=0.7, SIRS was 84% and 20%, 93% and 0%, 79% and 20% respectively. Conclusions: There was weak correlation between the lactate level and shock index with statistically significant correlation between the shock index grouped >=0.7 and hyperlactatemia with high sensitivity and very low specificity.

A Comparison of the Shock Index and Conventional Vital Signs to Identify Acute, Critical Illness in the Emergency Department

1994 ◽  
Vol 24 (4) ◽  
pp. 685-690 ◽  
Author(s):  
Mohamed Y Rady ◽  
Howard A Smithline ◽  
Heidi Blake ◽  
Richard Nowak ◽  
E Rivers
Keyword(s):  
Emergency Department ◽  
Critical Illness ◽  
Vital Signs ◽  
Shock Index

scholarly journals The Impact of Age and Receipt Antihypertensives to Systolic Blood Pressure and Shock Index at Injury Scene and in the Emergency Department to Predict Massive Transfusion in Trauma Patients

2020 ◽  
Author(s):  
Se Jin Park ◽  
Mi Jin Lee ◽  
Changho Kim ◽  
Haewon Jung ◽  
Seong Hun Kim ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Emergency Department ◽  
Logistic Regression ◽  
Systolic Blood Pressure ◽  
Massive Transfusion ◽  
Red Blood Cell Transfusion ◽  
Trauma Patients ◽  
Shock Index ◽  
Cutoff Value ◽  
The Impact

Abstract Background: Systolic blood pressure (SBP) and shock index (SI) are accurate indicators of hemodynamic instability and the need for transfusion in trauma patients. We aimed to determine whether the utility and cutoff point for SBP and SI are affected by age and antihypertensives. Methods: This was a retrospective observational study of a level 1 trauma center between January 2017 and December 2018. We analyzed the utility and cutoff points of SBP and SI for predicting massive transfusion (MT) and 30-day mortality according to patients’ age and whether they were taking antihypertensives. A multivariable logistic regression analysis was conducted to estimate the association of age and antihypertensives on primary and secondary outcomes. Results: We analyzed 4681 trauma cases. There were 1949 patients aged 65 years or older (41.6%), and 1375 hypertensive patients (29.4%). MT was given to 137 patients (2.9%). The 30-day mortality rate was 6.3% (n = 294). In geriatric trauma patients taking antihypertensives, a prehospital SBP less than 110 mmHg was the cutoff value for predicting MT in multivariate logistic regression analyses; packed red blood cell transfusion volume decreased abruptly based on prehospital SBP of 110 mmHg. Emergency Department SI greater than 1.0 was the cutoff value for predicting MT in patients who were older than 65 years and were not taking antihypertensives. Conclusions: The triage of trauma patients is based on the identification of clinical features readily identifiable by first responders. However, age and medications may also affect the accurate evaluation. In initial trauma management, we must apply SBP and SI differently depending on age, whether a patient is taking antihypertensives, and the time at which the indicators are measured.

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