scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Ability of King's College Criteria and Model for End-Stage Liver Disease Scores to Predict Mortality of Patients With Acute Liver Failure: A Meta-analysis

01 Apr 2016-Clinical Gastroenterology and Hepatology (Clin Gastroenterol Hepatol)-Vol. 14, Iss: 4, pp 516-525
TL;DR: Based on a meta-analysis of studies, the KCC more accurately predicts hospital mortality among patients with AALF, whereas MELD scores more accurately predict mortalityamong patients with NAALF.
About: This article is published in Clinical Gastroenterology and Hepatology.The article was published on 2016-04-01 and is currently open access. It has received 91 citations till now. The article focuses on the topics: King's College Criteria & Model for End-Stage Liver Disease.

Summary (2 min read)

Jump to: [INTRODUCTION][METHODS][NAALF).][RESULTS][DISCUSSION] and [OLT.]

INTRODUCTION

  • Acute Liver Failure (ALF) is a rare, but devastating illness with a high risk of progression to multi-organ failure and death1-3.
  • The key clinical issue remains to accurately identify patients with ALF who will die without ELT, and those who will survive with medical management alone.
  • One particularly salient difference is the treatment of transplanted patients.
  • To date, there have been three meta-analyses23 of the performance of the KCC in ALF.
  • The first included only Acetaminophen-induced ALF (AALF) identifying nine studies in total, and concluded that the KCC had limited sensitivity13.

METHODS

  • All potential articles were assessed independently by two researchers (HF, MM) according to prospectively defined eligibility criteria, and disagreements were resolved by consensus or consultation with a third author (WB).
  • If this was not possible or there was doubt over the 2 x 2 calculation, the study was excluded from the subsequent analysis.
  • The DerSimonian-Laird random effects method was used to produce summary estimates of sensitivity, specificity, likelihood ratios (LR) and diagnostic odds ratio (DOR, defined as the ratio of positive to negative likelihood ratios).

NAALF).

  • A funnel plot and effective sample size (ESS) regression analysis (the logarithm of the DOR plotted against 1/√ESS) was used to investigate publication bias.
  • Data analyses were performed using the freeware Meta-Disc version 1.4 (Universidad Complutense, Madrid, Spain) and Eggers statistic calculated in Excel (Microsoft Corporation, Redmond WA)33.

RESULTS

  • The search strategy identified 4,063 potentially relevant studies.
  • Subgroup analysis was performed to assess differences in heterogeneity and diagnostic accuracy between the groups specified earlier.
  • Furthermore Egger's statistic was not significant again suggesting publication bias was not present.

DISCUSSION

  • This meta-analysis confirms that when comparing KCC and MELD for outcome prediction in ALF KCC have lower sensitivity and MELD lower specificity.
  • The sROC analysis is therefore a more valid way to pool the results of studies with varying thresholds.
  • This is no doubt a consequence of the fact that the KCC were derived from an ALF cohort, whereas MELD was developed from results in chronic liver disease patients undergoing TIPS.
  • This may be why KCC is preferred in countries facing such organ shortages and with high rates of AALF.
  • Clearly such delays are relatively short but in cases of fulminant hepatic failure it is clearly advantageous to use simpler bedside tests during the evolution of disease.

OLT.

  • Information on prothrombin time measurements and assay details were not available in all studies and may have contributed to heterogeneity or threshold effects.
  • The potential benefits of combining the specificity of the KCC with the sensitivity of MELD are attractive.
  • Such novel methods would require data for each patient rather than summative as presented for publication.
  • Many new biomarkers have been proposed in ALF but have failed to be validated in larger studies or are deemed not ready for widespread distribution.
  • Neither KCC nor MELD are optimal in all circumstances so there remains an urgent need for more accurate outcome prediction systems in ALF.

Did you find this useful? Give us your feedback

Citations
More filters
Journal ArticleDOI
TL;DR: The novel nomogram is an accurate and efficient mortality prediction method for HEV-ALF patients and both discriminative ability and threshold probabilities of the nomogram were superior to those of the MELD and CLIF-C-ACLFs models.
Abstract: Timely and effective assessment scoring systems for predicting the mortality of patients with hepatitis E virus-related acute liver failure (HEV-ALF) are urgently needed. The present study aimed to establish an effective nomogram for predicting the mortality of HEV-ALF patients.

10 citations

Journal ArticleDOI
TL;DR: In a Portuguese cohort of patients with ALF, non-paracetamol etiologies were predominant and hospital mortality was much lower amongst transplanted patients, while KCC were not associated with hospital mortality, but they were significantly associated with LT.

10 citations

Journal ArticleDOI
TL;DR: In this article, a microRNA signature associated with successful regeneration post-auxiliary liver transplant and with recovery from acute liver failure was used to develop outcome prediction models for APAP-ALF.

9 citations

Journal ArticleDOI
TL;DR: Peds-HAV model is a simple, bedside, dynamic, etiology (HAV) specific prognostic model based on 3 objective parameters with optimum sensitivity and specificity, hence should be used as liver transplant listing criteria in HAV induced PALF.
Abstract: Hepatitis A virus (HAV) is the commonest cause of pediatric acute liver failure (PALF) in developing countries. Our objective was to develop and validate a HAV-etiology specific prognostic model in PALF. All children with HAV induced PALF (IgM HAV reactive) were included. Outcome was defined at day 28. Only those with death or native liver survival were included. The model (Peds-HAV) was derived using the independent predictors of outcome and validated in a prospective independent cohort. Hepatitis A accounted for 131 (45.9%) of total 285 PALF. After excluding 11 children who underwent liver transplant, 120 children (74 survivors and 46 death) were included. The first 75 patients formed the derivation cohort and the next 45 patients formed the prospective validation cohort. In the derivation cohort, INR: OR 2.208, (95% CI 1.321–3.690), p = 0.003, grade of hepatic encephalopathy (HE): OR 3.078, (95% CI 1.017–9.312), p = 0.047 and jaundice-to-HE interval: OR 1.171, (95% CI 1.044–1.314), p = 0.007 were independent predictors of death. The final model comprised three criteria: (1) presence of grade 3–4 HE, (2) INR greater than 3.1, and (3) jaundice to HE interval more than 10 days. Presence of 2 or more of these criteria predicted death with 90% sensitivity, 81.4% specificity and 84.9% accuracy. Peds-HAV model was superior to existing prognostic models. In the validation cohort, Peds-HAV model predicted death with 83.3% sensitivity and 92.6% specificity. Peds-HAV model is a simple, bedside, dynamic, etiology (HAV) specific prognostic model based on 3 objective parameters with optimum sensitivity and specificity, hence should be used as liver transplant listing criteria in HAV induced PALF.

9 citations

Journal ArticleDOI
TL;DR: Approaches in critical care, prognostic modeling, and medical evaluation of the acute liver failure transplant candidate are summarized to summarized.
Abstract: Acute liver failure is a unique clinical phenomenon characterized by abrupt deterioration in liver function and altered mentation. The development of high-grade encephalopathy and multisystem organ dysfunction herald poor prognosis. Etiologic-specific treatments and supportive measures are routinely employed; however, liver transplantation remains the only chance for cure in those who do not spontaneously recover. The utility of artificial and bioartificial assist therapies as supportive care—to allow time for hepatic recovery or as a bridge to liver transplantation—has been examined but studies have been small, with mixed results. Given the severity of derangements, intensive critical care is needed to successfully bridge patients to transplant, and evaluation of candidates occurs rapidly in parallel with serial reassessments of operative fitness. Psychosocial assessment is often suboptimal and relative contraindications to transplant, such as ventilator-dependence may be overlooked. While often employed to guide evaluation, no single prognostic model discriminates those who will spontaneously recover and those who will require transplant. The purpose of this review will be to summarize approaches in critical care, prognostic modeling, and medical evaluation of the acute liver failure transplant candidate.

9 citations


Cites background from "Ability of King's College Criteria ..."

  • ...McPhail et al.(79) KCC All 2153 Unknown 0....

    [...]

  • ...McPhail et al.(79) MELD All 2153 Unknown 0....

    [...]

  • ...The MELD score, widely used for liver prioritization/allocation in chronic liver disease, has been investigated in ALF with similar performance to that of the KCC.(79) An emerging theme in ALF prognostication is the need for individualized, dynamic assessments as opposed to historically static ones at presentation....

    [...]

  • ...A number of other scoring systems have been proposed to identify candidates most at risk for death and need for LT. Non-liver specific indices, such as the sequential organ failure assessment which is widely used to quantify severity of multiorgan failure in other forms of critical illness, have Journal of Clinical and Translational Hepatology 2019 vol. 7 | 384–391 387 been utilized with comparable performance to KCC in prediction of non-survival; although, their organ “non-specificity” compromises applicability in determining benefit with LT and use is limited.77,78 The MELD score, widely used for liver prioritization/allocation in chronic liver disease, has been investigated in ALF with similar performance to that of the KCC.79 An emerging theme in ALF prognostication is the need for individualized, dynamic assessments as opposed to historically static ones at presentation....

    [...]

References
More filters
Journal ArticleDOI
04 Sep 2003-BMJ
TL;DR: A new quantity is developed, I 2, which the authors believe gives a better measure of the consistency between trials in a meta-analysis, which is susceptible to the number of trials included in the meta- analysis.
Abstract: Cochrane Reviews have recently started including the quantity I 2 to help readers assess the consistency of the results of studies in meta-analyses. What does this new quantity mean, and why is assessment of heterogeneity so important to clinical practice? Systematic reviews and meta-analyses can provide convincing and reliable evidence relevant to many aspects of medicine and health care.1 Their value is especially clear when the results of the studies they include show clinically important effects of similar magnitude. However, the conclusions are less clear when the included studies have differing results. In an attempt to establish whether studies are consistent, reports of meta-analyses commonly present a statistical test of heterogeneity. The test seeks to determine whether there are genuine differences underlying the results of the studies (heterogeneity), or whether the variation in findings is compatible with chance alone (homogeneity). However, the test is susceptible to the number of trials included in the meta-analysis. We have developed a new quantity, I 2, which we believe gives a better measure of the consistency between trials in a meta-analysis. Assessment of the consistency of effects across studies is an essential part of meta-analysis. Unless we know how consistent the results of studies are, we cannot determine the generalisability of the findings of the meta-analysis. Indeed, several hierarchical systems for grading evidence state that the results of studies must be consistent or homogeneous to obtain the highest grading.2–4 Tests for heterogeneity are commonly used to decide on methods for combining studies and for concluding consistency or inconsistency of findings.5 6 But what does the test achieve in practice, and how should the resulting P values be interpreted? A test for heterogeneity examines the null hypothesis that all studies are evaluating the same effect. The usual test statistic …

45,105 citations

Journal ArticleDOI
TL;DR: The MELD scale is a reliable measure of mortality risk in patients with end‐stage liver disease and suitable for use as a disease severity index to determine organ allocation priorities in patient groups with a broader range of disease severity and etiology.

4,184 citations

Journal ArticleDOI
TL;DR: This Mayo TIPS model may predict early death following elective TIPS for either prevention of variceal rebleeding or for treatment of refractory ascites, superior to both the Child‐Pugh classification and the Child-Pugh score in predicting survival.

2,479 citations

Journal ArticleDOI
TL;DR: Data suggest that the MELD score is able to accurately predict 3-month mortality among patients with chronic liver disease on the liver waiting list and can be applied for allocation of donor livers.

2,225 citations

Journal ArticleDOI
TL;DR: The effective sample size funnel plot and associated regression test of asymmetry should be used to detect publication bias and other sample size related effects in meta-analyses of test accuracy.

2,191 citations

Related Papers (5)
Frequently Asked Questions (2)
Q1. What have the authors contributed in "Meta-analysis of king's college criteria and model for end stage liver disease to predict outcome in acute liver failure" ?

The authors assessed the accuracy of King 's College Criteria ( KCC ) versus the Model-forEnd-Stage-Liver-Disease ( MELD ) in ALF through meta-analysis of studies which report the accuracy of both tests. 

The authors hope these data help inform such decisions and future research. A worsening grade of HE can be detected at the bedside and incorporated into KCC without awaiting further biochemical analysis.