Feasibility of continuous multiorgan variability analysis in the intensive care unit

Journal of Critical Care

Volumn 27, Issue 2, 2012, Pages 218.e9-218.e20

  Bradley, Beverly ^a   Green, Geoffrey C ^a   Batkin, Izmail ^a   Seely, Andrew J E ^a,b  

^a OTTAWA HOSPITAL RESEARCH INSTITUTE   (Canada)

^b UNIVERSITY OF OTTAWA   (Canada)

Author keywords

Continuous waveform monitoring; Data loss; Data quality; Heart rate variability; Multiorgan; Respiratory rate variability

Indexed keywords

HYPERTENSIVE FACTOR;

ADULT; ARTICLE; BREATHING RATE; CAPNOGRAPHY; CLINICAL ARTICLE; CLINICAL ASSESSMENT TOOL; CONTINUOUS INDIVIDUALIZED MULTIORGAN VARIABILITY ANALYSIS; CONTROLLED STUDY; CRITICALLY ILL PATIENT; ELECTROCARDIOGRAM; ENTROPY; FEASIBILITY STUDY; FEMALE; HEART ATRIUM FIBRILLATION; HEART RATE VARIABILITY; HUMAN; INFORMATION PROCESSING; INTENSIVE CARE UNIT; INTUBATION; MALE; RESPIRATORY RATE VARIABILITY; STATISTICAL ANALYSIS; WAVEFORM;

EID: 84858624423     PISSN: 08839441     EISSN: 15578615     Source Type: Journal    
DOI: 10.1016/j.jcrc.2011.09.009     Document Type: Article

References (29)

1. Schenkman K.A. Clinical data collection in the information era. Pediatr Crit Care Med 2007, 8:588-589.
2. Vinecore K., et al. Design and implementation of a portable physiologic data acquisition system. Pediatr Crit Care Med 2007, 8:563-569.
3. Lapinsky S.E., Holt D., Hallett D., et al. Survey of information technology in intensive care units in Ontario, Canada. BMC Med Inform Decis Mak 2008, 8:5.
4. Siachalou E.J., Kitas I.K., Panoulas K.J., et al. ICASP: an intensive-care acquisition and signal processing integrated framework. J Med Syst 2005, 29:633-646.
5. Kropyvnytskyy I., Saunders F., Schierek P., et al. A computer system for continuous long-term recording, processing, and analysis of physiological data of brain injured patients in ICU settings. Brain Inj 2001, 15:577-583.
6. Saeed M., Lieu C., Raber G., et al. MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring. Comput Cardiol 2002, 29:64-644.
7. Metnitz P.G.H., Laback P., Popow C., et al. Computer assisted data analysis in intensive care: the ICDEV project-development of a scientific database system for intensive care. Intl J Clin Monit Comput 1995, 12:147-159.
8. Goldstein B., McNames J., McDonald B.A., et al. Physiologic data acquisition system and database for the study of disease dynamics in the intensive care unit. Crit Care Med 2003, 31:433-441.
9. Norris P.R., Dawant B.M., Geissbuhler A. Web-based data integration and annotation in the intensive care unit. Proc AMIA Annu Fall Symp 1997, 794-798.
10. Seely A.J., Christou N.V. Multiple organ dysfunction syndrome: exploring the paradigm of complex nonlinear systems. Crit Care Med 2000, 28:2193-2200.
11. Seely A.J., Macklem P.T. Complex systems and the technology of variability analysis. Crit Care 2004, 8:R367-R384.
12. Buchman T.G., Stein P.K., Goldstein B. Heart rate variability in critical illness and critical care. Curr Opin Crit Care 2002, 8:311-315.
13. Korach M., et al. Cardiac variability in critically ill adults: influence of sepsis. Crit Care Med 2001, 29:1380-1385.
14. Piepoli M., Garrard C.S., Kontoyannis D.A., Bernardi L. Autonomic control of the heart and peripheral vessels in human septic shock. Intensive Care Med 1995, 21:112-119.
15. Annane D., et al. Inappropriate sympathetic activation at onset of septic shock: a spectral analysis approach. Am J Respir Crit Care Med 1999, 160:458-465.
16. Pontet J., Contreras P., Curbelo A., et al. Heart rate variability as early marker of multiple organ dysfunction syndrome in septic patients. J Crit Care 2003, 18:156-163.
17. Chen W.L., Chen J.H., Huang C.C., et al. Heart rate variability measures as predictors of in-hospital mortality in ED patients with sepsis. Am J Emerg Med 2008, 26:395-401.
18. Papaioannou V.E., Chouvarda I., Maglaveras N., Dragoumanis C., Pneumatikos I. Changes of heart and respiratory rate dynamics during weaning from mechanical ventilation: a study of physiologic complexity in surgical critically ill patients. J Crit Care 2011, 26:262-272.
19. Bien M.Y., Hseu S.S., Yien H.W., et al. Breathing pattern variability: a weaning predictor in postoperative patients recovering from systemic inflammatory response syndrome. Intensive Care Med 2004, 30:241-247.
20. El-Khatib M., Jamaleddine G., Soubra R., et al. Pattern of spontaneous breathing: potential marker for weaning outcome. Intensive Care Med 2001, 27:52-58.
21. Engoren M. Approximate entropy of respiratory rate and tidal volume during weaning from mechanical ventilation. Crit Care Med 1998, 26:1817-1823.
22. Wysocki M., Cracco C., Teixeira A. Reduced breathing variability as a predictor of unsuccessful patient separation from mechanical ventilation. Crit Care Med 2006, 34:2076-2083.
23. White C.E., Batchinsky A.I., Necsoiu C., et al. Lower interbreath interval complexity is associated with extubation failure in mechanically ventilated patients during spontaneous breathing trials. J Trauma 2010, 68:1310-1316.
24. Goldberger A.L., Amaral L.A., Glass L., et al. PhysioBank, PhysioToolkit, and PhysioNet: Components of a new research resource for complex physiologic signals. Circulation 2000, 101:e215-220.
25. Ahmad S., Ramsay T., Huebsch L., et al. Continuous multi-parameter heart rate variability analysis heralds onset of sepsis in adults. PLoS ONE 2009, 4:e6642.
26. Zhang Q., Manriquez A., Medigue C., Papelier Y., Sorine M. Robust and efficient location of T-wave ends in electrocardiogram. Comput Cardiol 2005, 32:711-714.
27. Chen W., et al. Unconstrained detection of respiration rhythm and pulse rate with one under-pillow sensor during sleep. Med Biol Eng Comput 2005, 43:306-312.
28. Logan B, Healey J. Robust detection of atrial fibrillation for a long term telemonitoring system. 32:(2005);619-622.
29. Cysarz D., Zerm R., Bettermann H., et al. Comparison of respiratory rates derived from heart rate variability, ECG amplitude, and nasal/oral airflow. Ann Biomed Eng 2008, 36:2085-2094.