Literature DB >> 25692260

Improving the prediction of mortality and the need for life-saving interventions in trauma patients using standard vital signs with heart-rate variability and complexity.

Nehemiah T Liu1, John B Holcomb, Charles E Wade, Jose Salinas.   

Abstract

The goal of this study was to determine the effectiveness of using traditional and new vital signs (heart rate variability and complexity [HRV, HRC]) for predicting mortality and the need for life-saving interventions (LSIs) in prehospital trauma patients. Our hypothesis was that statistical regression models using traditional and new vital signs would be superior in predictive performance over models using standard vital signs alone. This study involved 108 prehospital trauma patients transported from the point of injury via helicopter. Heart rate variability and HRC were calculated using criterion standard R-R interval sequences manually verified from the patients' electrocardiograms. Means and standard deviations for vital signs, HRV, HRC, and Glasgow coma scale (GCS) scores were obtained for nonsurvivors versus survivors and LSI versus non-LSI patient groups and then compared using Wilcoxon statistical tests. Receiver-operating characteristic curves were also obtained to compare different regression models for predicting mortality and the need for LSIs. Seventeen patients (16%) died. Eighty-two patients (76%) received a total of 142 LSIs. Receiver-operating characteristic curves demonstrated better prediction of mortality and LSI needs using heart rate and HRC (area under the curve [AUC]; AUCs, 0.86 and 0.86) than using heart rate alone (AUCs, 0.79 and 0.57). Likewise, receiver-operating characteristic curves demonstrated better prediction using total GCS score and HRC (AUCs, 0.82 and 0.97) than using total GCS score (AUCs, 0.81 and 0.91). Similar results were obtained for heart rate and HRV (AUCs, 0.86 and 0.73). The major implication of this study was that traditional and new vital signs (HRV and HRC) should be used simultaneously to improve prediction of mortality and the need for LSIs in prehospital trauma patients during all echelons of trauma care. Improvements in the timely use and diagnostic accuracy of transportable vital signs monitors will require use of traditional and new vital signs from the trauma patient cohort.

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Year:  2015        PMID: 25692260     DOI: 10.1097/SHK.0000000000000356

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


  6 in total

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Authors:  Yael Mandel-Portnoy; Matthew A Levin; Sameer Bansilal; Maria Suprun; Hung-Mo Lin; Lynne D Richardson; Gregory W Fischer; Jonathan L Halperin
Journal:  J Clin Monit Comput       Date:  2015-10-17       Impact factor: 2.502

2.  Evaluating performance of early warning indices to predict physiological instabilities.

Authors:  Christopher G Scully; Chathuri Daluwatte
Journal:  J Biomed Inform       Date:  2017-09-20       Impact factor: 6.317

3.  Development of a heart rate variability and complexity model in predicting the need for life-saving interventions amongst trauma patients.

Authors:  Aravin Kumar; Nan Liu; Zhi Xiong Koh; Jayne Jie Yi Chiang; Yuda Soh; Ting Hway Wong; Andrew Fu Wah Ho; Takashi Tagami; Stephanie Fook-Chong; Marcus Eng Hock Ong
Journal:  Burns Trauma       Date:  2019-04-18

4.  An increase in heart rate variability can be an index for end point of resuscitation in trauma patients.

Authors:  Ali Foroutan; Shahram Paydar; Seyyed Taghi Heydari; Leila Mohammadi; Farnaz Rahbar
Journal:  Chin J Traumatol       Date:  2019-04-16

5.  Alteration of Heart Rate Variability in People With Bowel Preparation Before Colonoscopy.

Authors:  Shang-Cheng Huang; Wen-Hui Fang; Chung-Ching Wang; Wei-Liang Chen; Tung-Wei Kao; Ling-Ling Hwang; Chi-Ming Chu; Yaw-Wen Chang
Journal:  Medicine (Baltimore)       Date:  2015-11       Impact factor: 1.889

6.  Dynamic vital signs may predict in-hospital mortality in elderly trauma patients.

Authors:  Kazuhiro Kamata; Toshikazu Abe; Makoto Aoki; Gautam Deshpande; Daizoh Saitoh; Yasuharu Tokuda
Journal:  Medicine (Baltimore)       Date:  2020-06-19       Impact factor: 1.817

  6 in total

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