Literature DB >> 18073594

Prehospital loss of R-to-R interval complexity is associated with mortality in trauma patients.

Andriy I Batchinsky1, Leopoldo C Cancio, Jose Salinas, Tom Kuusela, William H Cooke, Jing Jing Wang, Marla Boehme, Victor A Convertino, John B Holcomb.   

Abstract

BACKGROUND: To improve our ability to identify physiologic deterioration caused by critical injury, we applied nonlinear analysis to the R-to-R interval (RRI) of the electrocardiogram of prehospital trauma patients.
METHODS: Ectopy-free, 800-beat sections of electrocardiogram from 31 patients were identified. Twenty patients survived (S) and 11 died (NonS) after hospital admission. Demographic data, heart rate, blood pressure, field Glasgow Coma Scale (GCS) score, and survival times were recorded. RRI complexity was assessed via nonlinear statistics, which quantify entropy or fractal properties.
RESULTS: Age and field heart rate and blood pressure were not different between groups. Mean survival time (NonS) was 129 hours +/- 62 hours. NonS had a lower GCS score (8.6 +/- 1.7 vs. 13.2 +/- 0.8, p < 0.05). RRI approximate entropy (ApEn; 0.87 +/- 0.06 vs. 1.09 +/- 0.07, p < 0.01), sample entropy (SampEn; 0.80 +/- 0.08 vs. 1.10 +/- 0.05, p < 0.01) and fractal dimension by dispersion analysis (1.08 +/- 0.02 vs. 1.13 +/- 0.01, p < 0.05) were lower in NonS. Distribution of symbol 2 (Dis_2), a symbol-dynamics measure of RRI distribution, was higher in NonS (292.6 +/- 34.4 vs. 222 +/- 21.3, p < 0.10). For RRI data, logistic regression analysis revealed ApEn and Dis_2 as independent predictors of mortality (area under the receiver-operating characteristic curve = 0.96). When GCSMOTOR was considered, it replaced Dis_2 whereas ApEn was retained (area under curve = 0.92). When Injury Severity Score was considered, it replaced GCSMOTOR; ApEn was retained.
CONCLUSIONS: Prehospital loss of RRI complexity, as evidenced by decreased entropy, was associated with mortality in trauma patients independent of GCS score or Injury Severity Score.

Entities:  

Mesh:

Year:  2007        PMID: 18073594     DOI: 10.1097/TA.0b013e318142d2f0

Source DB:  PubMed          Journal:  J Trauma        ISSN: 0022-5282


  22 in total

1.  Reliable real-time calculation of heart-rate complexity in critically ill patients using multiple noisy waveform sources.

Authors:  Nehemiah T Liu; Leopoldo C Cancio; Jose Salinas; Andriy I Batchinsky
Journal:  J Clin Monit Comput       Date:  2013-08-30       Impact factor: 2.502

2.  Effect of methamphetamine dependence on heart rate variability.

Authors:  Brook L Henry; Arpi Minassian; William Perry
Journal:  Addict Biol       Date:  2010-12-23       Impact factor: 4.280

3.  Heart Rate Complexity in US Army Forward Surgical Teams During Pre Deployment Training.

Authors:  Michelle B Mulder; Matthew S Sussman; Sarah A Eidelson; Kirby R Gross; Mark D Buzzelli; Andriy I Batchinsky; Carl I Schulman; Nicholas Namias; Kenneth G Proctor
Journal:  Mil Med       Date:  2020-06-08       Impact factor: 1.437

4.  Multi-scale symbolic entropy analysis provides prognostic prediction in patients receiving extracorporeal life support.

Authors:  Yen-Hung Lin; Hui-Chun Huang; Yi-Chung Chang; Chen Lin; Men-Tzung Lo; Li-Yu Daisy Liu; Pi-Ru Tsai; Yih-Sharng Chen; Wen-Je Ko; Yi-Lwun Ho; Ming-Fong Chen; Chung-Kang Peng; Timothy G Buchman
Journal:  Crit Care       Date:  2014-10-24       Impact factor: 9.097

5.  Characterization of common measures of heart period variability in healthy human subjects: implications for patient monitoring.

Authors:  Caroline A Rickards; Kathy L Ryan; Victor A Convertino
Journal:  J Clin Monit Comput       Date:  2009-11-22       Impact factor: 2.502

6.  Heart rate variability analysis during central hypovolemia using wavelet transformation.

Authors:  Soo-Yeon Ji; Ashwin Belle; Kevin R Ward; Kathy L Ryan; Caroline A Rickards; Victor A Convertino; Kayvan Najarian
Journal:  J Clin Monit Comput       Date:  2013-02-01       Impact factor: 2.502

7.  Tissue hemoglobin monitoring of progressive central hypovolemia in humans using broadband diffuse optical spectroscopy.

Authors:  Jangwoen Lee; Jae G Kim; Sari Mahon; Bruce J Tromberg; Kathy L Ryan; Victor A Convertino; Caroline A Rickards; Kathryn Osann; Matthew Brenner
Journal:  J Biomed Opt       Date:  2008 Nov-Dec       Impact factor: 3.170

Review 8.  Predicting adverse hemodynamic events in critically ill patients.

Authors:  Joo H Yoon; Michael R Pinsky
Journal:  Curr Opin Crit Care       Date:  2018-06       Impact factor: 3.687

9.  Combat casualties undergoing lifesaving interventions have decreased heart rate complexity at multiple time scales.

Authors:  Leopoldo C Cancio; Andriy I Batchinsky; William L Baker; Corina Necsoiu; José Salinas; Ary L Goldberger; Madalena D Costa
Journal:  J Crit Care       Date:  2013-10-17       Impact factor: 3.425

10.  Sympathetic responses to central hypovolemia: new insights from microneurographic recordings.

Authors:  Kathy L Ryan; Caroline A Rickards; Carmen Hinojosa-Laborde; William H Cooke; Victor A Convertino
Journal:  Front Physiol       Date:  2012-04-26       Impact factor: 4.566

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.