Volatility

A new vital sign identified using a novel bedside monitoring strategy

Eric L. Grogan, Patrick R. Norris, Theodore Speroff, Asli Ozdas, Daniel J. France, Paul A. Harris, Judith M. Jenkins, Renee Stiles, Robert S. Dittus, John A. Morris, Errington C. Thompson, Cansfield, Donald D. Trunkey, Thomas Genuit, Ajai K. Malhotra, Blaine Enderson, Mark A. Healey, Deborah A. Kuhls

Research output: Contribution to journalArticle

33 Citations (Scopus)

Abstract

Background: SIMON (Signal Interpretation and Monitoring) monitors and archives continuous physiologic data in the ICU (HR, BP, CPP, ICP, CI, EDVI, S vO 2, S pO 2, SVRI, PAP, and CVP). We hypothesized: heart rate (HR) volatility predicts outcome better than measures of central tendency (mean and median). Methods: More than 600 million physiologic data points were archived from 923 patients over 2 years in a level one trauma center. Data were collected every 1 to 4 seconds, stored in a MS-SQL 7.0 relational database, linked to TRACS, and de-identified. Age, gender, race, Injury Severity Score (ISS), and HR statistics were analyzed with respect to outcome (death and ventilator days) using logistic and Poisson regression. Results: We analyzed 85 million HR data points, which represent more than 71,000 hours of continuous data capture. Mean HR varied by age, gender and ISS, but did not correlate with death or ventilator days. Measures of volatility (SD, % HR > 120) correlated with death and prolonged ventilation. Conclusions: 1) Volatility predicts death better than measures of central tendency. 2) Volatility is a new vital sign that we will apply to other physiologic parameters, and that can only be fully explored using techniques of dense data capture like SIMON. 3) Densely sampled aggregated physiologic data may identify sub-groups of patients requiring new treatment strategies.

Original languageEnglish (US)
Pages (from-to)7-14
Number of pages8
JournalJournal of Trauma - Injury, Infection and Critical Care
Volume58
Issue number1
DOIs
StatePublished - Jan 1 2005

Fingerprint

Volatilization
Vital Signs
Heart Rate
Injury Severity Score
Mechanical Ventilators
Trauma Centers
Ventilation
Logistic Models
Outcome Assessment (Health Care)
Databases

All Science Journal Classification (ASJC) codes

  • Surgery
  • Critical Care and Intensive Care Medicine

Cite this

Grogan, E. L., Norris, P. R., Speroff, T., Ozdas, A., France, D. J., Harris, P. A., ... Kuhls, D. A. (2005). Volatility: A new vital sign identified using a novel bedside monitoring strategy. Journal of Trauma - Injury, Infection and Critical Care, 58(1), 7-14. https://doi.org/10.1097/01.TA.0000151179.74839.98

Volatility : A new vital sign identified using a novel bedside monitoring strategy. / Grogan, Eric L.; Norris, Patrick R.; Speroff, Theodore; Ozdas, Asli; France, Daniel J.; Harris, Paul A.; Jenkins, Judith M.; Stiles, Renee; Dittus, Robert S.; Morris, John A.; Thompson, Errington C.; Cansfield; Trunkey, Donald D.; Genuit, Thomas; Malhotra, Ajai K.; Enderson, Blaine; Healey, Mark A.; Kuhls, Deborah A.

In: Journal of Trauma - Injury, Infection and Critical Care, Vol. 58, No. 1, 01.01.2005, p. 7-14.

Research output: Contribution to journalArticle

Grogan, EL, Norris, PR, Speroff, T, Ozdas, A, France, DJ, Harris, PA, Jenkins, JM, Stiles, R, Dittus, RS, Morris, JA, Thompson, EC, Cansfield, Trunkey, DD, Genuit, T, Malhotra, AK, Enderson, B, Healey, MA & Kuhls, DA 2005, 'Volatility: A new vital sign identified using a novel bedside monitoring strategy', Journal of Trauma - Injury, Infection and Critical Care, vol. 58, no. 1, pp. 7-14. https://doi.org/10.1097/01.TA.0000151179.74839.98
Grogan, Eric L. ; Norris, Patrick R. ; Speroff, Theodore ; Ozdas, Asli ; France, Daniel J. ; Harris, Paul A. ; Jenkins, Judith M. ; Stiles, Renee ; Dittus, Robert S. ; Morris, John A. ; Thompson, Errington C. ; Cansfield ; Trunkey, Donald D. ; Genuit, Thomas ; Malhotra, Ajai K. ; Enderson, Blaine ; Healey, Mark A. ; Kuhls, Deborah A. / Volatility : A new vital sign identified using a novel bedside monitoring strategy. In: Journal of Trauma - Injury, Infection and Critical Care. 2005 ; Vol. 58, No. 1. pp. 7-14.
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AU - Grogan, Eric L.

AU - Norris, Patrick R.

AU - Speroff, Theodore

AU - Ozdas, Asli

AU - France, Daniel J.

AU - Harris, Paul A.

AU - Jenkins, Judith M.

AU - Stiles, Renee

AU - Dittus, Robert S.

AU - Morris, John A.

AU - Thompson, Errington C.

AU - Cansfield,

AU - Trunkey, Donald D.

AU - Genuit, Thomas

AU - Malhotra, Ajai K.

AU - Enderson, Blaine

AU - Healey, Mark A.

AU - Kuhls, Deborah A.

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N2 - Background: SIMON (Signal Interpretation and Monitoring) monitors and archives continuous physiologic data in the ICU (HR, BP, CPP, ICP, CI, EDVI, S vO 2, S pO 2, SVRI, PAP, and CVP). We hypothesized: heart rate (HR) volatility predicts outcome better than measures of central tendency (mean and median). Methods: More than 600 million physiologic data points were archived from 923 patients over 2 years in a level one trauma center. Data were collected every 1 to 4 seconds, stored in a MS-SQL 7.0 relational database, linked to TRACS, and de-identified. Age, gender, race, Injury Severity Score (ISS), and HR statistics were analyzed with respect to outcome (death and ventilator days) using logistic and Poisson regression. Results: We analyzed 85 million HR data points, which represent more than 71,000 hours of continuous data capture. Mean HR varied by age, gender and ISS, but did not correlate with death or ventilator days. Measures of volatility (SD, % HR > 120) correlated with death and prolonged ventilation. Conclusions: 1) Volatility predicts death better than measures of central tendency. 2) Volatility is a new vital sign that we will apply to other physiologic parameters, and that can only be fully explored using techniques of dense data capture like SIMON. 3) Densely sampled aggregated physiologic data may identify sub-groups of patients requiring new treatment strategies.

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