Predicting in-hospital mortality in patients with cirrhosis: Results differ across risk adjustment methods

Myers, Robert P.; Quan, Hude; Hubbard, James; Shaheen, Abdel Aziz; Kaplan, Gilaad G.

doi:10.1002/hep.22676

Cited by 83 publications

(73 citation statements)

References 37 publications

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“…Second, the possibility of errors in coding of the diagnoses and procedures cannot be avoided [7]; however, misclassification mistakes distribute evenly in large-scale studies [53]. Third, the NHDS database does not include data regarding the timing of diagnoses, which hinders the differentiation of baseline comorbidities from complications [36]. Analyses of risk-adjusted mortality rates should adjust mortality rates only for baseline comorbid diseases, not complications that arise from surgery [15].…”

Section: Discussionmentioning

confidence: 99%

“…Analyses of risk-adjusted mortality rates should adjust mortality rates only for baseline comorbid diseases, not complications that arise from surgery [15]. The degree to which this issue influenced our results is unclear, although it has been reported that the majority of common diagnoses are comorbidities rather than adverse events [15,30,36]. Fourth, the NHDS enabled only ascertainment of inpatient outcomes, and thus postdischarge complications [24,40,58].…”

Section: Discussionmentioning

confidence: 99%

“…Further research comparing the Charlson and Elixhauser methods with the less accessible (costwise) risk adjustment methods of Disease Staging (Thomson Medstat Inc, Ann Arbor, MI, USA) and All Patient Refined Diagnosis Related Groups (3M Health Information Systems, Wallingford, CT, USA) is warranted [36]. In addition, we currently are testing and validating a specific comorbiditybased measure for outcome prediction after orthopaedic surgery.…”

Section: Discussionmentioning

confidence: 99%

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The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

Menendez

Neuhaus

Dijk

et al. 2014

Clinical Orthopaedics &Amp; Related Research

436

292

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Background Scores derived from comorbidities can help with risk adjustment of quality and safety data. The Charlson and Elixhauser comorbidity measures are wellknown risk adjustment models, yet the optimal score for orthopaedic patients remains unclear. Questions/purposes We determined whether there was a difference in the accuracy of the Charlson and Elixhauser comorbidity-based measures in predicting (1) in-hospital mortality after major orthopaedic surgery, (2) in-hospital adverse events, and (3) nonroutine discharge. Methods Among an estimated 14,007,813 patients undergoing orthopaedic surgery identified in the National Hospital Discharge Survey (1990Survey ( -2007, 0.80% died in the hospital. The association of each Charlson comorbidity measure and Elixhauser comorbidity measure with mortality was assessed in bivariate analysis. Two main multivariable logistic regression models were constructed, with in-hospital mortality as the dependent variable and one of the two comorbidity-based measures (and age, sex, and year of surgery) as independent variables. A base model that included only age, sex, and year of surgery also was evaluated. The discriminative ability of the models was quantified using the area under the receiver operating characteristic curve (AUC). The AUC quantifies the ability of our models to assign a high probability of mortality to patients who die. Values range from 0.50 to 1.0, with 0.50 indicating no ability to discriminate and 1.0 indicating perfect discrimination. Results Elixhauser comorbidity adjustment provided a better prediction of in-hospital case mortality (AUC, 0.86; 95% CI, 0.86-0.86) compared with the Charlson model (AUC, 0.83; 95% CI, and to the base model with no comorbidities (AUC, 0.81; 95% CI, 0.81-0.81). In terms of relative improvement in predictive performance, the Elixhauser measure performed 60% better than the Charlson score in predicting mortality. The Elixhauser model discriminated inpatient morbidity better than the Charlson measure, but the discriminative ability of the model was poor and the difference in the absolute improvement in predictive power between the two models (AUC, 0.01) is of dubious clinical importance. Both comorbidity models exhibited the same degree of discrimination for estimating nonroutine discharge (AUC, 0.81; 95% CI, 0.81-0.82 for both models). Conclusions Provider-specific outcomes, particularly inpatient mortality, may be evaluated differently depending on the comorbidity risk adjustment model selected. Future research assessing and comparing the performance of the

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

Menendez

Neuhaus

Dijk

et al. 2014

Clinical Orthopaedics &Amp; Related Research

436

292

View full text Add to dashboard Cite

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“…[3][4][5][6][7][8][9] These patients also have high risk for other complications such as spontaneous bacterial peritonitis (SBP), hyponatremia and hepatorenal syndromes, which increase the risk of fatal outcome. 1,3,[7][8][9][10][11][12][13][14][15][16] Several scores have been developed in order to predict severity of the disease and prognosis in order to consider liver transplantation as a potential treatment option. 2 These scores are Child Turcotte Pugh and MELD; however, they were designed for predicting liver transplantation requirements and mortality in the short term, but not while in hospital.…”

Section: Introductionmentioning

confidence: 99%

In-hospital mortality risk factors in patients with ascites due to cirrhosis

Vicco¹,

Rodeles²,

Ferini³

et al. 2015

Rev. Assoc. Med. Bras.

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Conflict of interest: noneIntroduction: ascites is one of the most common complications of cirrhosis associated with a high rate of mortality. Although several scores have been developed in order to assess the prognosis of the disease, they were designed for predicting liver transplantation requirements and mortality in the short term, but not while in hospital. The aim of this study was to weigh risk factors for in-hospital mortality in adult patients with ascites due to alcoholic cirrhosis. Material and methods: we performed a cross-sectional study in 180 adult patients with diagnosis of cirrhosis with portal hypertension associated with high alcohol intake. The diagnosis of cirrhosis was made by liver echography and portal hypertension was defined by clinical features plus serum-ascites albumin gradient. Sampled individuals were subjected to complete clinical examination. Child Pugh and the MELD scores were applied in all the patients. Results: nineteen patients died while in-hospital. Mortality was associated with increased levels of serum white blood cell, urea, creatinine, prolonged prothrombin time, aspartate aminotransferase and alanine aminotransferase. We conducted a multiple binary logistic to predict in-hospital mortality which yielded that serum urea, creatinine and prothrombin time made a significant contribution to prediction with an OR 14 (95% CI 12.8 -16.7 p = 0.03), 2 (95% CI 0.5 -3.47, p = 0.04), and 2 (95% CI 1.03 -2.31, p = 0.01) linearly-related. Conclusions: our results suggest that acute renal failure and prolonged prothrombin time are predictors of in-hospital mortality in patients with portal hypertension due to alcoholic cirrhosis.

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“…We also adjusted for case mix with the Elixhauser algorithm rather than the Charlson/Deyo algorithm because it is more discriminative in patients with liver disease. 8,9 Finally, we performed a sensitivity analysis excluding patients with acute HCV (ICD-9-CM codes 070.41 and 070.51) because differentiating viral ALI versus drugrelated ALI is difficult in this setting. All analyses employed SAScallable SUDAAN (version 9.0.1, Research Triangle Institute, Research Triangle Park, NC) to account for the complexities of Nationwide Inpatient Sample data.…”

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confidence: 99%

Hepatitis C, alcohol abuse, and unintentional overdoses are risk factors for acetaminophen-related hepatotoxicity

Myers

Shaheen

2009

Hepatology

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Predicting in-hospital mortality in patients with cirrhosis: Results differ across risk adjustment methods

Cited by 83 publications

References 37 publications

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

The Elixhauser Comorbidity Method Outperforms the Charlson Index in Predicting Inpatient Death After Orthopaedic Surgery

In-hospital mortality risk factors in patients with ascites due to cirrhosis

Hepatitis C, alcohol abuse, and unintentional overdoses are risk factors for acetaminophen-related hepatotoxicity

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