Literature DB >> 23143055

A new severity predicting index for hemorrhagic shock using lactate concentration and peripheral perfusion in a rat model.

Joon Yul Choi1, Wan Hyung Lee, Tae Keun Yoo, Incheol Park, Deok Won Kim.   

Abstract

Forty percent of trauma deaths are due to hemorrhage, with 33% to 56% occurring in the prehospital environment. This study proposes a new index (NI) based on the ratio of serum lactate concentration (LC) to peripheral perfusion (PP) as an indicator of hemorrhage-induced mortality during the prehospital stage. Thirty-six anesthetized rats were randomized into three groups according to volume of controlled blood loss. We measured heart rate (HR), systolic and diastolic blood pressures (SBP and DBP), mean arterial pressure (MAP), pulse pressure (PPR), respiration rate (RR), temperature (TEMP), LC, PP, shock index (SI = HR/SBP), and proposed the new hemorrhage-induced mortality index (NI = LC/PP). Peripheral perfusion, defined as peripheral tissue perfusion and skin microcirculation, was continuously monitored by laser Doppler flowmetry. All parameters were analyzed for changes between prehemorrhage and posthemorrhage to investigate the effects of hemorrhage on mortality. Areas under a receiver operating characteristic curve (AUCs) in descending order for NI, SI, PP, SBP, MAP, PPR, DBP, TEMP, LC, RR, and HR were 0.975, 0.941, 0.922, 0.919, 0.903, 0.884, 0.847, 0.816, 0.783, 0.744, and 0.672, respectively. The correlation coefficients with mortality for NI, SI, PP, SBP, MAP, PPR, DBP, TEMP, LC, RR, and HR were -0.818, -0.759, 0.726, 0.721, 0.694, 0.662, 0.597, 0.544, -0.487, 0.420, and -0.296, respectively, with the same order as the AUC. NI was shown to be an optimal independent mortality predictor on multivariable logistic regression analysis. In conclusion, the newly proposed hemorrhage-induced mortality index, based on blood lactate/PP ratio, was a better marker for predicting mortality in rats undergoing acute hemorrhage in comparison to the other parameters evaluated in this study.

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Year:  2012        PMID: 23143055     DOI: 10.1097/SHK.0b013e318273299f

Source DB:  PubMed          Journal:  Shock        ISSN: 1073-2322            Impact factor:   3.454


  6 in total

1.  Mortality prediction of rats in acute hemorrhagic shock using machine learning techniques.

Authors:  Kyung-Ah Kim; Joon Yul Choi; Tae Keun Yoo; Sung Kean Kim; Kilsoo Chung; Deok Won Kim
Journal:  Med Biol Eng Comput       Date:  2013-06-23       Impact factor: 2.602

2.  Derivation and Validation of Predictive Factors for Clinical Deterioration after Admission in Emergency Department Patients Presenting with Abnormal Vital Signs Without Shock.

Authors:  Daniel J Henning; Kimie Oedorf; Danielle E Day; Colby S Redfield; Colin J Huguenel; Jonathan C Roberts; Leon D Sanchez; Richard E Wolfe; Nathan I Shapiro
Journal:  West J Emerg Med       Date:  2015-12-08

Review 3.  Modeling trauma in rats: similarities to humans and potential pitfalls to consider.

Authors:  Birte Weber; Ina Lackner; Melanie Haffner-Luntzer; Annette Palmer; Jochen Pressmar; Karin Scharffetter-Kochanek; Bernd Knöll; Hubert Schrezenemeier; Borna Relja; Miriam Kalbitz
Journal:  J Transl Med       Date:  2019-09-05       Impact factor: 5.531

4.  Assessing Hemorrhagic Shock Severity Using the Second Heart Sound Determined from Phonocardiogram: A Novel Approach.

Authors:  Yan Chen; Aisheng Hou; Xiaodong Wu; Ting Cong; Zhikang Zhou; Youyou Jiao; Yungen Luo; Yuheng Wang; Weidong Mi; Jiangbei Cao
Journal:  Micromachines (Basel)       Date:  2022-06-28       Impact factor: 3.523

5.  Capillary lactate concentration on admission of normotensive trauma patients: a prospective study.

Authors:  Pierre Bouzat; Clotilde Schilte; Marc Vinclair; Pauline Manhes; Julien Brun; Jean-Luc Bosson; Jean-François Payen
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2016-06-07       Impact factor: 2.953

6.  Validation of the Shock Index, Modified Shock Index, and Age Shock Index for Predicting Mortality of Geriatric Trauma Patients in Emergency Departments.

Authors:  Soon Yong Kim; Ki Jeong Hong; Sang Do Shin; Young Sun Ro; Ki Ok Ahn; Yu Jin Kim; Eui Jung Lee
Journal:  J Korean Med Sci       Date:  2016-12       Impact factor: 2.153

  6 in total

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