Outcome prediction for patients with cirrhosis of the liver in a medical ICU: A comparison of the APACHE scores and liver-specific scoringsystems

Zauner, Christian; Apsner, Robert; Kranz, Alexander; Kramer, Ludwig; Madl, Christian; Schneider, Barbara; Schneeweiß, Bruno; Ratheiser, Klaus; Stockenhuber, Felix; Lenz, Kurt

doi:10.1007/bf01708096

Cited by 81 publications

(48 citation statements)

References 16 publications

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“…less sick patients. Indeed, although APACHE II works well for severely ill cirrhotic patients admitted to ICUs (13,17,29,(36)(37)(38), this is not the case when its predictive value is assessed in a population of cirrhotic patients with mortality rate of only 11.5% (41). Thus, our results are somewhat surprising, because the mortality rate in our sample was only 9.7% and nevertheless the scores showed an excellent performance.…”

Section: Discussionmentioning

confidence: 58%

“…These findings support the importance of evaluating the performance of a predictive model not only in terms of its discriminative capacity but also its calibration. If, as in some studies (13,17,36,38), we had based the evaluation on discriminative ability alone, we would say that the SAPS II and CPT scores had the best performance. Nevertheless, we found that the best calibration results were obtained by the SOFA and MELD scores.…”

Section: Discussionmentioning

confidence: 96%

“…These results are somewhat unsurprising if we bear in mind that the prognosis of acutely ill patients with cirrhosis is influenced not only by the severity of hepatic insufficiency but mainly by the dysfunction of other organ systems and that cirrhotics admitted to ICUs often have extrahepatic organ dysfunction and die of multiple organ failure (12)(13)(14)(34)(35)(36)(37)(38)(39).…”

Section: Introductionmentioning

confidence: 99%

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Prognostic scores in cirrhotic patients admitted to a gastroenterology intensive care unit

Freire

Romãozinho²,

Amaro³

et al. 2011

Rev. esp. enferm. dig.

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Aim: to assess the prognostic accuracy of Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) II, Sequential Organ Failure Assessment (SOFA), Model for End-stage Liver Disease (MELD) and ChildPugh-Turcotte (CPT) in predicting GICU mortality in cirrhotic patients.Methods: the study involved 124 consecutive cirrhotic admissions to a GICU. Clinical data, prognostic scores and mortality were recorded. Discrimination was evaluated with area under receiver operating characteristic curves (AUC). Calibration was assessed with Hosmer-Lemeshow goodness-of-fit test.Results: GICU mortality was 9.7%. Mean APACHE II, SAPS II, SOFA, MELD and CPT scores for survivors (13.6, 25.4, 3.5, 18.0 and 8.6, respectively) were found to be significantly lower than those of non-survivors (22.0, 47.5, 10.1, 30.7 and 12.5, respectively) (p < 0.001). All the prognostic systems showed good discrimination, with AUC = 0.860, 0.911, 0.868, 0.897 and 0.914 for APACHE II, SAPS II, SOFA, MELD and CPT, respectively. Similarly, APACHE II, SAPS II, SOFA, MELD and CPT scores achieved good calibration, with p = 0.146, 0.120, 0.686, 0.267 and 0.120, respectively. The overall correctness of prediction was 81.9%, 86.1%, 93.3%, 90.7% and 87.7% for the APA-CHE II, SAPS II, SOFA, MELD and CPT scores, respectively.Conclusions: in cirrhotics admitted to a GICU, all the tested scores have good prognostic accuracy, with SOFA and MELD showing the greatest overall correctness of prediction. INTRODUCTIONPrognostic models are used for comparison and quality assessment of different Intensive Care Units (ICUs) and within the same ICU over time, for audit and clinical research, for evaluating therapeutic effectiveness and for guiding discussions between clinicians and families (1-6).The incidence of liver cirrhosis is increasing exponentially and cirrhotic patients admitted to ICUs have high mortality rates and a high rate of consumption of resources (7-18). Furthermore, a significant percentage (36.7%) of the total cost of ICU care for cirrhotic patients is spent on those who do not survive (11,16,19). Additionally, it must be borne in mind that ICUs are a very limited health resource (10,11,18). Thus, predictive models could be very important decision-making tools in this setting.Two types of prognostic scores can be used in cirrhotics admitted to ICUs: general prognostic models and disease-specific models. The general prognostic models include two main categories: firstly, those evaluating severity of illness, namely the Acute Physiology and Chronic Health Evaluation (APACHE) II (20) and Simplified Acute Physiology Score (SAPS) II (21); secondly, models quantifying organ dysfunction and failure, of which the most widely-used is the Sequential Organ Failure Assessment (SOFA) (22,23 Vol. 103. N.° 4, pp. 177-183, 2011 Received: 04-10-10. Accepted: 02-12-10.

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Section: Discussionmentioning

confidence: 58%

Section: Discussionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prognostic scores in cirrhotic patients admitted to a gastroenterology intensive care unit

Freire

Romãozinho²,

Amaro³

et al. 2011

Rev. esp. enferm. dig.

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“…Limitations of this scoring system for deciding timings of liver transplantation include limited discriminative ability, variability in measurement of clinical and laboratory determinants [7] of this scoring system and, importantly, limited ability to predict short-term mortality. Several other scoring systems have been described that attempt to evaluate prognosis of patients with cirrhosis of liver (Table 1) [8][9][10][11][12][13][14][15][16][17][18][19]. However, none of these are applied widely in clinical practice because of their limited predictive ability and unacceptable complexity.…”

Section: Introductionmentioning

confidence: 99%

Models for prediction of mortality from cirrhosis with special reference to artificial neural network: a critical review

Ghoshal

Das

2007

Hepatol Int

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Prediction of mortality of patients with cirrhosis of liver, a common and potentially fatal disease, is important for timely listing of patients for liver transplantation. The Child-Pugh scoring system has been widely used for predicting the outcome of liver cirrhosis. The Model for End-Stage Liver Disease (MELD) score has recently become popular for prediction of short-term mortality for organ allocation. A few studies that evaluated artificial neural network (ANN)-based model for prediction of outcome of cirrhosis of liver in terms of mortality have consistently shown it to be superior to Child-Pugh scoring and logistic regression-based models; it is worth noting that MELD score is also derived using the logistic regression model. Due to the inherent ability of neural network-based systems in identifying complex nonlinear interactions, ANN-based models are expected to perform better than most linear models, such as regression-based models. More studies are needed on ANN-based models for prediction of mortality of patients with cirrhosis of liver and its value in prioritization of organ allocation for treatment of patients with cirrhosis of liver.

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“…When critically ill patients with clearly de®ned problems, such as obstetric patients [18] and trauma victims [19], are studied, the discriminatory power of prognostic equations appears good. However, if the critically ill patients have complex multisystem disease, for example patients with hepatic cirrhosis [20] or sepsis [21], then the model's ability to assimilate the complex interactions between a combination of physiological abnormalities is not so good and the discriminatory power declines. When the clinical picture is complex, more¯exible systems, for example a neural network, may offer better performance [22].…”

Section: Discussionmentioning

confidence: 99%

Validation of outcome prediction in elderly patients

Jandziol¹,

Ridley

2000

Anaesthesia

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SummaryWe recently described an equation for predicting the 1-year survival of critically ill patients aged over 70 years. The aim of this study was to check the performance of this equation in a validation group of 555 patients. The required demographic details (age, diagnosis, acute physiology score) of all elderly patients admitted between 1/4/95 and 31/9/96 were recorded and patients were followed for 1 year. One hundred and six patients died on the intensive care unit (19% mortality) and a further 134 died within 1 year (43% total 1-year mortality). The performance of the predictive equation was modest; the goodness-of-®t p-value was 0.04 and the area under the receiver operating characteristic curve was 0.75. For both groups, the combined 1-year survival of all critically ill elderly patients was 55% but the outcome of patients aged over 85 years remains poor (37%).

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Outcome prediction for patients with cirrhosis of the liver in a medical ICU: A comparison of the APACHE scores and liver-specific scoringsystems

Cited by 81 publications

References 16 publications

Prognostic scores in cirrhotic patients admitted to a gastroenterology intensive care unit

Prognostic scores in cirrhotic patients admitted to a gastroenterology intensive care unit

Models for prediction of mortality from cirrhosis with special reference to artificial neural network: a critical review

Validation of outcome prediction in elderly patients

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