Temperature curve complexity predicts survival in critically ill patients

American Journal of Respiratory and Critical Care Medicine

Volumn 174, Issue 3, 2006, Pages 290-298

  Varela, Manuel ^a   Churruca, Juan ^b   Gonzalez, Ana ^b   Martin, Alfredo ^b   Ode, Jesus ^b   Galdos, Pedro ^b  

^a HOSPITAL DE MÓSTOLES   (Spain)

^b NONE

Author keywords

Multiple organ failure; Nonlinear dynamics; Severity of Illness Index

Indexed keywords

ADULT; AGED; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; CRITICAL ILLNESS; DYING; ENTROPY; FEMALE; HUMAN; LOGISTIC REGRESSION ANALYSIS; MALE; MULTIPLE ORGAN FAILURE; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SCORING SYSTEM; TEMPERATURE SENSITIVITY;

ADOLESCENT; ADULT; AGED; AGED, 80 AND OVER; APACHE; BODY TEMPERATURE REGULATION; CRITICAL CARE; FEMALE; HUMANS; LOGISTIC MODELS; MALE; MIDDLE AGED; MULTIPLE ORGAN FAILURE; NONLINEAR DYNAMICS; PROGNOSIS; ROC CURVE; SEVERITY OF ILLNESS INDEX; SKIN TEMPERATURE; SURVIVAL ANALYSIS;

EID: 33746589419     PISSN: 1073449X     EISSN: 1073449X     Source Type: Journal    
DOI: 10.1164/rccm.200601-058OC     Document Type: Article

References (32)

1. Lipsitz LA, Goldberger AL. Loss of "complexity" and aging: potential applications of fractals and chaos theory to senescence. JAMA 1992;267:1806-1809.
2. Iyengar N, Peng CK, Morin R, Goldberger AL, Lipsitz A. Age related alterations in fractal scaling of cardiac interbeat interval dynamics. Am J Physiol 1996;271:R1078-R1084.
3. Pikkujämsä SM, Mäkikallio TH, Sourander LB, Räihä IJ, Puuka P, Skyttä J, Peng CK, Goldberger AL, Huikuri HV. Cardiac interbeat interval dynamics from childhood to senescence: comparison of conventional and new measures based on fractals and chaos theory. Circulation 1999;100:393-399.
4. Varela M, Jimenez L, Fariña R. Complexity analysis of the temperature curve: new information from body temperature. Eur J Appl Physiol 2003;89:230-237.
5. Peng CK, Havlin S, Hausdorff JM, Mietus JE, Stanley HE, Goldberger AL. Fractal mechanisms and heart rate dynamics: long-range correlations and their breakdown with disease. J Electrocardiol 1995;28 (Suppl):59-65.
6. Bigger JT, Steinman RC, Rolnitzky LM, Fleiss JL, Albrecht P, Cohen RJ. Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction and patients with heart transplants. Circulation 1996;93:2142-2151.
7. Goldberger AL. Fractal variability versus pathologic periodicity: complexity loss and stereotypy in disease. Perspect Biol Med 1997;40:543-561.
8. Hausdorff JM, Mitchell SL, Firtion R, Peng CK, Cudkowicz ME, Wei JY, Goldberger AL. Altered fractal dynamics of gait: reduced stride-interval correlations with aging and Huntington's disease. J Appl Physiol 1997;82:262-269.
9. Huikuri HV, Mäkikallio TH, Airaksinen J, Seppänen T, Puuka P, Räihä IJ, Sourander LB. Power-law relationship of heart rate variability as a predictor of mortality in the elderly. Circulation 1998;97:2031-2036.
10. Mäkikallio TH, Hoiber S, Kober L, Torp-Pederson C, Peng CK, Goldberger AL, Huikuri HV. Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. Am J Cardiol 1999;83:836-839.
11. Vikman S, Mäkikallio TH, Yli-Mäyri S, Pikkujämsä S, Koivisto AM, Reinikainen P, Airsksinen KEJ, Huikuri HV. Altered complexity and correlation properties of R-R interval dynamics before the spontaneous onset of paroxysmal atrial fibrillation. Circulation 1999;100:2079-2084.
12. Toweill D, Sonnenthal K, Lai S, Goldstein B. Linear and nonlinear analysis of hemodynamic signals during sepsis and septic shock. Crit Care Med 2000;28:2051-2057.
13. Seely AJ, Christou NV. Multiple organ dysfunction syndrome: exploring the paradigm of complex nonlinear systems. Crit Care Med 2000;28:2193-2200.
14. Marshal JC. Complexity, chaos, and incomprehensibility: parsing the biology of critical illness [editorial]. Crit Care Med 2000;28:2646-2648.
15. Mäkikallio TH, Huikuri HV, Hintze U, Videbaek J, Mitrani R, Castellanos A, Myerburg R, Moller M. Fractal analysis and time- and frequencydomain measures of heart rate variability as predictors of mortality in patients with heart failure. Am J Cardiol 2001;87:178-182.
16. Goldberger AL, Amaral LAN, Hausdorff JM, Ivanov PCh, Peng CK, Stanley HE. Fractal dynamics in physiology: alterations with disease and aging. Proc Natl Acad Sci USA 2002;99:2466-2472.
17. Rassias AJ, Holzberger PT, Givan AL, Fahrner SC, Yeager MP. Decreased physiologic variability as a generalized response to human endotoxemia. Crit Care Med 2005;33:512-519.
18. Varela M, Calvo M, Chana M, Gomez-Mestre I, Asensio R, Galdos P. Clinical implications of temperature curve complexity in critically ill patients. Crit Care Med 2005;33:2764-2771.
19. Working Group on Blood Pressure and Heart Variability, European Society of Hypertension. Terms used in time series analysis of cardiovascular data. Available from: http://www.cbi.dongnocchi.it/glossary/Home.html [accessed June 12, 2006]
20. Vincent JL, Moreno E, Takala J, Willats S, de Mendoça A, Bruining H, Renhart CK, Suter PM, Thijs LG. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Med 1996;22:707-710.
21. Vincent JL, Mendoça A, Cantraine F, Moreno R, Takala J, Suter PM, Sprung CL, Colardyn F, Blecher S. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on "sepsis related problems" of the European Society of Intensive Care Medicine. Crit Care Med 1998;26:1793-1800.
22. Lopes Ferreira F, Peres Bota D, Bross A, Mellot C, Vincent JL. Serial evaluation of the SOFA score to predict outcome in critically ill patients. JAMA 2001;286:1754-1758.
23. Peres Bota D, Melot C, Lopes Ferreira F, Nguyen Ba V, Vincent JL. The Multiple Organ Dysfunction Score (MODS) versus the Sequential Organ Failure Assessment (SOFA) score in outcome prediction. Intensive Care Med 2002;28:1619-1624.
24. Timsit JF, Fosse JP, Troché G, Lassence A, Alberti C, Garrouste-Oregas M, Bornstain C, Adrie C, Cheval C. Chevret S, for the OUTCOMEREA Study Group. Calibration and discrimination by daily Logistic Organ Dysfunction scoring comparatively with daily Sequential Organ Failure Assessment scoring for predicting hospital mortality in critically ill patients. Crit Care Med 2002;30:2002-2013.
25. Pincus SM, Gladstone IM, Ehrenkranz RA. A regularity statistic for medical data analysis. J Clin Monit 1991;7:335-345.
26. Pincus SM. Approximate entropy as a measure of system complexity. Proc Natl Acad Sci USA 1991;88:2297-2301.
27. Pincus SM, Goldberger AL. Physiological time-series analysis: what does regularity quantify? Am J Physiol 1994;266:H1643-H1656.
28. Peng CK, Havlin S, Stanley HE, Goldberger AL. Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos 1995;5:82-87.
29. Peng CK, Hausdorff JM, Goldberger AL. Fractal mechanisms in neural control: Human heartbeat and gait dynamics in health and disease. Available from: www.physionet.org/tutorials/fmnc/index.shtml [accessed June 9, 2006]
30. Moody GB. Approximate entropy (ApEn). PhysioToolkit: open source software for biomedical science and engineering. Available from: http://www.physionet. org/physiotools/ApEn/ [accessed June 12, 2006]
31. Pincus SM. Assessing serial irregularity and its implications for health. Ann N Y Acad Sci 2001;954:245-267.
32. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307-310.