Hostname: page-component-cd9895bd7-q99xh Total loading time: 0 Render date: 2024-12-26T16:26:05.870Z Has data issue: false hasContentIssue false
  • English
  • Français

The use of APACHE II prognostic system in difficult-to-wean patients after long-term mechanical ventilation

Published online by Cambridge University Press:  23 December 2004

B. Schönhofer ,
J. J. Guo ,
S. Suchi ,
D. Köhler  and
R. Lefering
B. Schönhofer
Affiliation:
Krankenhaus Kloster Grafschaft, Zentrum für Pneumologie, Beatmungs- und Schlafmedizin, Schmallenberg, Germany
J. J. Guo
Affiliation:
Krankenhaus Kloster Grafschaft, Zentrum für Pneumologie, Beatmungs- und Schlafmedizin, Schmallenberg, Germany
S. Suchi
Affiliation:
Krankenhaus Kloster Grafschaft, Zentrum für Pneumologie, Beatmungs- und Schlafmedizin, Schmallenberg, Germany
D. Köhler
Affiliation:
Krankenhaus Kloster Grafschaft, Zentrum für Pneumologie, Beatmungs- und Schlafmedizin, Schmallenberg, Germany
R. Lefering
Affiliation:
University of Cologne, 2nd Department of Surgery, Biochemical and Experimental Division, Cologne, Germany
Get access

Extract

Summary

Background and objective: To examine the calibration of the prognostic system Acute Physiology and Chronic Health Evaluation Score (APACHE II) regarding hospital mortality and predicting weaning outcome after long-term mechanical ventilation of the lungs.

Methods: Prospective observational cohort study performed in a respiratory intensive care unit including 246 patients whose lungs were ventilated for 42.1 ± 37.8 (median 30) days in the referring hospital. APACHE II (24 h after admission to our respiratory intensive care unit) and the cause of respiratory failure, underlying disease, prior duration of mechanical ventilation and gender were recorded. The predictive power was evaluated with sensitivity and specificity for different cut-off points and summarized in a receiver operating characteristic curve.

Results: No difference was found between survivors (APACHE II 16.0 ± 4.3) and non-survivors (APACHE II 16.9 ± 5.1). In a mean time of 8.0 ± 10.3 days, 146 patients (59.3%) were successfully weaned (APACHE II 15.2 ± 3.5). One-hundred patients (40.7%) were considered unweanable (APACHE II 17.7 ± 5.3). Recalibration of APACHE II to predict weaning failure was possible, resulting in an area under the receiver operating characteristic curve (AUC) of 0.638. Furthermore the AUC improved to 0.723 by changing the weights of selected APACHE items and introducing external factors. Diagnostic accuracy fell from group with mechanical ventilation ≤25 days (AUC 0.770) to group with mechanical ventilation >50 days (AUC 0.517).

Conclusions: APACHE II did not predict hospital mortality after long-term mechanical ventilation of the lungs. Not the original APACHE II but a recalibrated and adapted APACHE II can be useful to predict weaning outcome in patients with less than 25 days of prior lung ventilation.

Keywords

HEALTH STATUS INDICATORS, APACHE IIHOSPITAL MORTALITYPULMONARY DISEASE, chronic obstructiveRESPIRATORY THERAPY, respiration, artificial, ventilator weaning
Type
Original Article
Information
European Journal of Anaesthesiology , Volume 21 , Issue 7 , July 2004 , pp. 558 - 565
Copyright
2004 European Society of Anaesthesiology

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Carson SS, Bach PB, Brzozowski L, Leff A. Outcomes after long-term acute care. An analysis of 133 mechanically ventilated patients. Am J Respir Crit Care Med 1999; 159: 1568–1573.Google Scholar
Stauffer JL, Fayter NA, Graves B, Cromb M, Lynch JC, Goebel P. Survival following mechanical ventilation for acute respiratory failure in adult men. Chest 1993; 104: 1222–1229.Google Scholar
Daly BJ, Rudy EB, Thompson KS, Happ MB. Development of a special care unit for chronically critically ill patients. Heart Lung 1991; 20: 45–51.Google Scholar
Lynn J, Ely EW, Zhong Z, et al. Living and dying with chronic obstructive pulmonary disease. J Am Geriatr Soc 2000; 48 (Suppl 5): S91–S100.Google Scholar
Connors JrAF, Dawson NV, Thomas C, et al. Outcomes following acute exacerbation of severe chronic obstructive lung disease. The SUPPORT investigators (Study to Understand Prognoses and Preferences for Outcomes and Risks of Treatments). Am J Respir Crit Care Med 1996; 154: 959–967.Google Scholar
Seneff MG, Zimmerman JE, Knaus WA, Wagner DP, Draper EA. Predicting the duration of mechanical ventilation. The importance of disease and patient characteristics. Chest 1996; 110: 469–479.Google Scholar
Scheinhorn DJ, Chao DC, Stearn-Hassenpflug M, LaBree LD, Heltsley DJ. Post-ICU mechanical ventilation: treatment of 1123 patients at a regional weaning center. Chest 1997; 111: 1654–1659.Google Scholar
Gracey DR, Hardy DC, Naessens JM, Silverstein MD, Hubmayr RD. The mayo ventilator-dependent rehabilitation Unit: a 5-year experience. Mayo Clin Proc 1997; 72: 13–19.Google Scholar
Schönhofer B, Euteneuer S, Nava S, Suchi S, Köhler D. Survival of mechanically ventilated patients admitted to a specialised weaning centre. Intensive Care Med 2002; 28: 908–916.Google Scholar
Gillespie DJ, Marsh HM, Divertie MB, Meadows JA. Clinical outcome of respiratory failure in patients requiring prolonged (greater than 24 hours) mechanical ventilation. Chest 1986; 90: 364–369.Google Scholar
Schönhofer B. Predictors of weanability. Monaldi Arch Chest Dis 2000; 55: 339–344.Google Scholar
Tobin MJ, Alex CG. Discontinuation of mechanical ventilation. In: Tobin MJ, ed. Principles and Practice of Mechanical Ventilation. New York, USA: McGraw-Hill, 1994: 1177–1206.
Yang KL, Tobin MJ. A prospective study of indexes predicting the outcome of trials of weaning from mechanical ventilation. New Engl J Med 1991; 324: 1445–1450.Google Scholar
Clochesy JM, Daly BJ, Montenegro HD. Weaning chronically critically ill adults from mechanical ventilatory support: a descriptive study. Am J Respir Crit Care Med 1995; 4: 93–99.Google Scholar
Jubran A, Mathru M, Dries D, Tobin MJ. Continuous recordings of mixed venous oxygen saturation during weaning from mechanical ventilation and the ramifications thereof. Am J Respir Crit Care Med 1998; 158: 1763–1769.Google Scholar
Mohsenifar Z, Hay A, Hay J, Lewis MI, Koerner SK. Gastric intramural pH as a predictor of success or failure in weaning patients from mechanical ventilation. Ann Intern Med 1993; 119: 794–798.Google Scholar
Sapijaszko MJ, Brant R, Sandham D, Berthiaume Y. Nonrespiratory predictor of mechanical ventilation dependency in intensive care unit patients. Crit Care Med 1996; 24: 601–607.Google Scholar
Scheinhorn DJ, Hassenpflug M, Artinian BM, LaBree L, Catlin JL. Predictors of weaning after 6 weeks of mechanical ventilation. Chest 1995; 107: 500–505.Google Scholar
Knaus WA, Zimmerman JE, Wagner DP, Draper EA, Lawrence DE. APACHE – acute physiology and chronic health evaluation: a physiologically based classification system. Crit Care Med 1981; 9: 591–597.Google Scholar
Knaus WA, Draper EA, Wagner DP, et al. Evaluating outcome from intensive care: a preliminary multihospital comparison. Crit Care Med 1982; 10: 491–496.Google Scholar
Knaus WA, Le Gall JR, Wagner DP, et al. A comparison of intensive care in the U.S.A. and France. Lancet 1982; ii: 642–646.Google Scholar
Vitacca M, Clini E, Porta R, Foglio K, Ambrosino N. Acute exacerbations in patients with COPD: predictors of need for mechanical ventilation. Eur Respir J 1996; 9: 1487–1493.Google Scholar
Afessa B, Hogans L, Murphy R. Predicting 3-day and 7-day outcomes of weaning from mechanical ventilation. Chest 1999; 116: 456–461.Google Scholar
Carson SS, Bach PB. Predicting mortality in patients suffering from prolonged critical illness. Chest 2001; 120: 928–933.Google Scholar
Suistomaa M, Niskanen M, Kari A, Hynynen M, Takala J. Customised prediction models based on APACHE II and SAPS II scores in patients with prolonged length of stay in the ICU. Intens Care Med 2002; 28: 479–485.Google Scholar
Knaus W, Draper E, Wagner D, Zimmerman J. APACHE II: a severity of disease classification system. Crit Care Med 1985; 13: 818–829.Google Scholar
Knaus WA. Prognosis with mechanical ventilation: the influence of disease, severity of disease, age, and chronic health status on survival from an acute illness. Am Rev Respir Dis 1989; 140: S8–S13.Google Scholar
Angus DC, Clermont G, Kramer J, Linde-Zwirble WT, Pinsky MR. Short-term and long-term outcome prediction with acute physiology and chronic health evaluation II system after orthotopic liver transplantation. Crit Care Med 2000; 28: 150–156.Google Scholar
Janssens U, Jordan A, Graf J, Grenner H, Hanrath P. Vergleich von APACHE II, SAPS und TISS im täglichen Einsatz bei Patienten einer kardiologischen Intensivstation. Intensivmedizin und Notfallmedizin 2000; 37: 31–43.Google Scholar
Metz CE. Basic principles of ROC analysis. Semin Nucl Med 1978; 8: 283–298.Google Scholar
Beck JR, Shultz EK. The use of relative operating characteristic (ROC) curves in test performance evaluation. Arch Pathol Lab Med 1986; 110: 13–20.Google Scholar
Centor RM, Schwartz JS. An evaluation of methods for estimating the area under the receiver operating characteristic (ROC) Curve. Med Decis Making 1985; 5: 149–156.Google Scholar
Collett D. Modelling Survival Data in Medical Research.London, UK: Chapman & Hall, 1994.
Lemeshow S, Hosmer JrDW. A review of goodness of fit statistics for use in the development of logistic regression models. Am J Epidemiol 1982; 115: 92–106.Google Scholar
Dragsted L, Jorgensen J, Jensen NH, et al. Interhospital comparisons of patient outcome from intensive care: importance of lead-time bias. Crit Care Med 1989; 17: 418–422.Google Scholar
Feinleib M, Zelen M. Some pitfalls in the evaluation of screening programs. Arch Environ Health 1969; 19: 412–415.Google Scholar
Tunnell RD, Millar BW, Smith GB. The effect of lead time bias on severity of illness scoring, mortality prediction and standardised mortality ratio in intensive care – a pilot study. Anaesthesia 1998; 53: 1045–1053.Google Scholar
Knaus WA, Draper EA, Wagner DP, Zimmerman JE. An evaluation of outcome from intensive care in major medical centers. Ann Intern Med 1986; 104: 410–418.Google Scholar
Quellette DR, Quinn MW, Emmons EE, Gallup RA. Decreased hemoglobin associated with impaired weaning from mechanical ventilation. Am J Respir Crit Care Med 2000; 161: A560.Google Scholar
Schönhofer B, Wenzel M, Geibel M, Köhler D. Blood transfusion and lung function in chronically anemic patients with severe chronic obstructive pulmonary disease. Crit Care Med 1998; 26: 1824–1828.Google Scholar