Accuracy of chronic liver failure consortium (CLIF-C) ACLF score compared with meld, MELD-NA and CTP as a mortality predictor in acute on chronic liver failure patients admitted to tertiary rural care hospital

Nitish Batra; Shilpa Gaidhane; Sourya Acharya; Sunil Kumar

doi:10.12688/f1000research.144938.1

Home Browse Accuracy of chronic liver failure consortium (CLIF-C) ACLF score compared...

ALL Metrics

Views

Downloads

Get PDF

Get XML

Export

▬

✚

Study Protocol

Accuracy of chronic liver failure consortium (CLIF-C) ACLF score compared with meld, MELD-NA and CTP as a mortality predictor in acute on chronic liver failure patients admitted to tertiary rural care hospital

[version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]

Nitish Batra ¹, Shilpa Gaidhane¹, Sourya Acharya¹, Sunil Kumar¹

PUBLISHED 29 Apr 2024

Author details Author details

¹ Medicine, Datta Meghe Institute of Higher Education and Research, Wardha, 442001, India

Nitish Batra
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Shilpa Gaidhane
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Sourya Acharya
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Sunil Kumar
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Datta Meghe Institute of Higher Education and Research collection.

Abstract

Background

Chronic Liver Failure Consortium (CLIF-C) ACLF score, Model for End-Stage Liver Disease (MELD), MELD-Na, and Child-Pugh (CTP) are established scoring systems for predicting mortality in Acute on Chronic Liver Failure (ACLF) patients. However, their comparative accuracy, especially in rural care settings, still needs to be explored. This study aims to assess and compare the predictive performance of these scoring systems, providing a nuanced understanding of their applicability in a tertiary rural care hospital.

Method

This prospective observational cohort study will be conducted at Acharya Vinoba Bhave Rural Hospital, following approval from the institutional ethical committee. ACLF patients aged 18 and above, presenting within one week of onset, will be included. Data collection will involve comprehensive assessments, including scoring system calculations, clinical examinations, and relevant investigations. Statistical analyses, encompassing descriptive statistics, comparative analyses, survival analyses, and multivariate models, will elucidate the accuracy and independent predictors of 28-day mortality.

Expected Outcome

Anticipated outcomes include a comprehensive understanding of the strengths and limitations of the CLIF-C ACLF score, MELD, MELD-Na, and CTP in predicting mortality among ACLF patients in a rural care context. The study aims to identify potential correlations and independent predictors, offering valuable insights for risk stratification. These findings are expected to guide clinicians in optimising prognostic assessments and decision-making, thereby improving the care and outcomes of ACLF patients in rural healthcare settings.

Keywords

Acute on Chronic Liver Failure, CLIF-C ACLF Score, Model for End-Stage Liver Disease (MELD), Rural Care Hospital, Mortality Prediction, Tertiary Healthcare

Corresponding author: Nitish Batra

Competing interests: No competing interests were disclosed.

Grant information: The author(s) declared that no grants were involved in supporting this work.

Copyright: © 2024 Batra N et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Batra N, Gaidhane S, Acharya S and Kumar S. Accuracy of chronic liver failure consortium (CLIF-C) ACLF score compared with meld, MELD-NA and CTP as a mortality predictor in acute on chronic liver failure patients admitted to tertiary rural care hospital [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2024, 13:419 (https://doi.org/10.12688/f1000research.144938.1) First published: 29 Apr 2024, 13:419 (https://doi.org/10.12688/f1000research.144938.1) Latest published: 29 Apr 2024, 13:419 (https://doi.org/10.12688/f1000research.144938.1)

Introduction

Chronic liver diseases represent a substantial global health burden, contributing significantly to morbidity and mortality.¹ Among the various clinical manifestations of liver dysfunction, Acute Chronic Liver Failure (ACLF) is a critical syndrome characterised by acute decompensation in the setting of pre-existing chronic liver disease. ACLF is associated with high short-term mortality rates, necessitating accurate prognostication for timely and appropriate interventions.²

Several scoring systems have been developed to assess the severity of liver disease and predict mortality, each with advantages and limitations.³ The Chronic Liver Failure Consortium (CLIF-C) ACLF score, Model for End-Stage Liver Disease (MELD), MELD-Na, and Child-Pugh (CTP) are prominent examples widely utilised in clinical practice. However, their comparative accuracy in predicting mortality, especially in the specific context of rural healthcare settings, remains an area warranting investigation.⁴

Rural healthcare facilities often need help with unique challenges, including limited resources and different demographic profiles compared to urban centres. Understanding the performance of scoring systems in these settings is crucial for tailoring prognostic strategies to the specific needs of the population.⁵ This study seeks to address this gap by assessing and comparing the accuracy of CLIF-C ACLF score, MELD, MELD-Na, and CTP in predicting 28-day mortality in ACLF patients admitted to a tertiary rural care hospital.

The choice of scoring system can significantly impact clinical decision-making, resource allocation, and patient outcomes. While the MELD score is widely utilised, the CLIF-C ACLF score, incorporating dynamic clinical parameters, may offer enhanced prognostic accuracy, particularly during acute exacerbations in chronic liver disease. This study aims to provide evidence-based insights into the optimal choice of scoring systems in rural care settings, contributing to the refinement of risk stratification and ultimately improving the management and outcomes of ACLF patients.

Aim

The primary aim of this study is to assess the accuracy of the Chronic Liver Failure Consortium (CLIF-C) ACLF score in predicting 28-day mortality in patients with Acute Chronic Liver Failure (ACLF) admitted to a tertiary rural care hospital. This will be compared with the widely used Model for End-Stage Liver Disease (MELD), MELD-Na, and Child-Pugh (CTP) scoring systems.

Objectives

• Estimation of scoring systems: To calculate and compare the CLIF-C ACLF score, MELD, MELD-Na, and CTP score in patients with ACLF.
• Comparison of sensitivity and specificity: To evaluate and compare the sensitivity and specificity of the CLIF-C ACLF score against MELD, MELD-Na, and CTP as indicators of 28-day mortality in ACLF patients.

Methods

Study design

This study will employ a prospective observational cohort design, aiming to assess and compare the predictive accuracy of the Chronic Liver Failure Consortium (CLIF-C) ACLF score with MELD, MELD-Na, and Child-Pugh (CTP) in predicting 28-day mortality in Acute on Chronic Liver Failure (ACLF) patients.

Study population

The study will focus on patients diagnosed with ACLF, presenting within one week of onset, aged 18 years and above, and providing informed consent for participation.

Place of study

The study will be conducted at Acharya Vinoba Bhave Rural Hospital (A.V.B.R.H.), a tertiary care teaching hospital in the rural Wardha District area.

Inclusion criteria

Patients meeting the following criteria will be included in the study:

• Diagnosed with Acute Chronic Liver Failure (ACLF).
• Age 18 years and above.
• Presentation within one week of ACLF onset.
• Willingness to provide informed consent.

Exclusion criteria

Patients meeting any of the following criteria will be excluded from the study:

• Chronic liver disease treated outside the hospital before emergency presentation.
• Lack of informed consent for participation in the study.

Bias

Bias in a study can affect the validity and reliability of its results. In the context of this study, potential biases need to be acknowledged and addressed to ensure the robustness of the findings.

Enrollment bias

• Selection bias: The inclusion criteria focus on ACLF patients presenting within one week of onset, potentially excluding patients with a delayed presentation. This could introduce bias if there are systematic differences between early and delayed presenters. Efforts will be made to minimise this bias by clearly defining and adhering to the enrollment criteria.
• Volunteer bias: Patients providing informed consent may differ from those who decline participation. To mitigate this bias, efforts will be made to explain the study comprehensively, emphasising its importance and the non-invasive nature of data collection. Additionally, the potential impact of volunteer bias will be acknowledged in interpreting results.
• Exclusion criteria bias: The exclusion of patients with chronic liver disease treated outside the hospital may lead to the exclusion of a subset of ACLF patients with different characteristics. This bias will be addressed by clearly justifying the exclusion criteria and considering potential implications in the discussion of results.

Data collection

Patient identification will commence in the Medicine ward and Intensive Care Unit (ICU) of Acharya Vinoba Bhave Rural Hospital (AVBRH). Eligible patients meeting the inclusion criteria will be approached for participation, where the research team will provide a detailed explanation of the study's purpose, procedures, and potential risks. Informed consent will be sought from willing participants, emphasising the voluntary nature of their involvement.

Once consent is obtained, comprehensive baseline information will be gathered. This will include demographic details, medical history, family history, and lifestyle factors such as smoking and alcohol intake. A thorough physical examination will be conducted, focusing on symptoms indicative of Acute or Chronic Liver Failure (ACLF), such as right upper quadrant pain, jaundice, mental status changes, and abdominal distention.

Calculating various scoring systems will be a crucial component of data collection. The Chronic Liver Failure Consortium (CLIF-C) ACLF score.² Additionally, the Child-Pugh-Turcotte Score (CTP)⁶ will be determined through the evaluation of prothrombin time (or INR), encephalopathy, albumin, bilirubin, and ascites. The Model for End-Stage Liver Disease (MELD) and MELD-Na scores⁷ will be calculated using the specified formulas.

Relevant investigations will be conducted to support the diagnosis and assess liver function. These may include blood tests measuring bilirubin, INR, and creatinine, as well as imaging studies and ultrasonography of the abdomen.

Patients will be followed throughout their hospital stay until discharge, death, or 28 days post-discharge, whichever occurs first. Any events, interventions, or changes in clinical status will be meticulously documented to provide a comprehensive dataset for analysis.

Data management will involve recording collected information in a structured electronic database, ensuring accuracy and maintaining confidentiality. Regular training sessions for data collectors will be conducted to uphold standardised data collection procedures. Periodic audits will be performed to validate data accuracy.

The study will strictly adhere to ethical guidelines, with a formal submission of the study protocol for ethical approval. Any modifications to the protocol will be communicated to the relevant authorities. Implementing a predefined timeline will guide the data collection process, ensuring efficiency and completion within the specified timeframe. Through this comprehensive and systematic approach, the study aims to gather reliable and pertinent information for the subsequent analysis of scoring system accuracy in predicting mortality in ACLF patients.

Sample size

Calculated by following the formula where:

n = (Z alpha / 2 square X P (1 - P)) / d square

Were,

Z alpha/2 is the level of significance at 5%, i.e., 95% confidence interval = 1.96

P = Prevalence of Acute on chronic liver disease = 12% - 40%

d = desired error of margin = 4 %

So, the minimum sample size required will be 386 patients.

Statistical methods

The statistical analysis for this prospective observational cohort study will be conducted to comprehensively assess the accuracy of scoring systems in predicting mortality among patients with Acute Chronic Liver Failure (ACLF). A detailed overview of the study population's baseline demographic characteristics will be provided through descriptive statistics, including means and standard deviations for continuous variables and frequencies for categorical variables.

In the comparative analysis, the sensitivity and specificity of the Chronic Liver Failure Consortium (CLIF-C) ACLF score will be compared with the widely used Model for End-Stage Liver Disease (MELD), MELD-Na, and Child-Pugh (CTP) score in predicting 28-day mortality in ACLF patients. The discriminatory power of each scoring system will be assessed using Receiver Operating Characteristic (ROC) curve analysis.

Survival analysis will be employed to illustrate the survival distribution among patients based on different scoring systems. Kaplan-Meier survival curves will be generated, and the log-rank test will be utilized to identify significant differences in mortality rates. Multivariate logistic regression models will be used for in-depth analysis, identifying independent predictors of 28-day mortality while considering various clinical and demographic variables. Adjusted odds ratios will quantify the strength of these associations.

Correlation analysis, employing Pearson or Spearman correlation coefficients, will assess the degree of correlation between different scoring systems, providing insights into their interrelationships. Subgroup analyses will be conducted to explore the performance of scoring systems within specific patient subpopulations, accounting for factors such as age, comorbidities, and the severity of liver disease. Statistical analysis will be performed using dedicated software such as by using R studio version 4.3.1., with statistical significance set at the conventional alpha level of 0.05. The results will be interpreted in the context of clinical relevance, contributing valuable insights into predicting mortality in ACLF patients within a rural care setting.

Expected outcome

The study anticipates providing valuable insights into the predictive accuracy of various scoring systems, including the Chronic Liver Failure Consortium (CLIF-C) ACLF score, Model for End-Stage Liver Disease (MELD), MELD-Na, and Child-Pugh (CTP), in forecasting 28-day mortality among patients with Acute on Chronic Liver Failure (ACLF) in a rural care setting. The analysis is expected to elucidate each scoring system's strengths and limitations, aiding clinicians in better assessing the prognosis of ACLF patients.

Furthermore, the study aims to identify potential correlations and associations between different clinical and demographic variables, shedding light on factors that may independently predict mortality in this patient population. This information can potentially refine risk-stratification strategies and enhance clinical decision-making in managing ACLF cases.

The anticipated outcomes will contribute to the academic understanding of ACLF prognosis and have practical implications for healthcare practitioners, potentially influencing the selection and utilisation of scoring systems in real-world clinical scenarios. Ultimately, the study aspires to offer evidence-based recommendations to optimise the care and outcomes of patients experiencing Acute or Chronic Liver Failure in rural healthcare settings.

Ethical considerations

Ethical considerations play a paramount role in this study, as evidenced by the approval from the institutional ethical committee of Datta Meghe Institute of Medical Sciences (DU). The approval reference number is DMIMS. (DU)/IEC/2022/1095 signifies the adherence to ethical standards in the research protocol. A crucial aspect of ethical practice involves maintaining the confidentiality of participants. Stringent measures will be implemented to ensure the confidential status of all gathered data, safeguarding the privacy and rights of the individuals involved in the study.

Dissemination

After the completion of the study, we will publish it in an indexed journal or conference.

Study status

The study has yet to start. After the publication of the protocol, we will start recruitment in the study.

Discussion

The proposed study aims to contribute valuable insights into scoring systems' predictive accuracy in Acute on Chronic Liver Failure (ACLF) patients admitted to a tertiary rural care hospital. The selection of appropriate scoring systems is crucial for effective prognostication and clinical decision-making in this patient population.

The Chronic Liver Failure Consortium (CLIF-C) ACLF score, Model for End-Stage Liver Disease (MELD), MELD-Na, and Child-Pugh (CTP) are well-established tools for assessing the severity of liver disease and predicting mortality. The proposed study compares these scoring systems, considering their applicability in rural care. This approach aligns with existing research emphasising the need for tailored prognostic tools that account for variations in patient demographics and healthcare resources.⁸^,⁹

Existing literature suggests that while the MELD score is widely used for liver disease severity assessment, the CLIF-C ACLF score may offer additional prognostic accuracy, particularly in acute exacerbations in chronic liver disease.¹⁰^,¹¹ This study's focus on rural care is essential, as healthcare disparities between urban and rural settings can impact the applicability and generalizability of scoring systems.¹²

Using a prospective observational cohort design enhances the study's credibility, enabling the examination of real-world clinical scenarios and outcomes. However, it is essential to acknowledge potential limitations, such as selection bias, which may arise from the exclusion of patients treated outside the study hospital before presentation. Efforts will be made to mitigate this bias by clearly justifying the exclusion criteria and considering its potential impact on the study's external validity.

The anticipated outcomes of the study include a refined understanding of scoring system accuracy and the identification of potential predictors for 28-day mortality in ACLF patients in a rural care context. These findings may inform clinical practice by aiding healthcare providers in selecting the most appropriate scoring system for prognosis, ultimately improving patient care and outcomes.

Trial registration

This study protocol has been registered with the Clinical Trials Registry – India (CTRI) - CTRI REF/2023/07/069843.

Data availability

No data are associated with this article.

References

1. Cheemerla S, Balakrishnan M: Global Epidemiology of Chronic Liver Disease. Clin Liver Dis (Hoboken). 2021; 17: 365–370. Publisher Full Text
2. CLIF-C ACLF (Acute-on-Chronic Liver Failure): MDCalc. Accessed: November 9, 2023. Reference Source
3. Barosa R, Roque Ramos L, Patita M, et al.: CLIF-C ACLF score is a better mortality predictor than MELD, MELD-Na and CTP in patients with Acute on chronic liver failure admitted to the ward. Rev. Esp. Enferm. Dig. 2017; 109: 399–405. Publisher Full Text
4. Ramzan M, Iqbal A, Murtaza HG, et al.: Comparison of CLIF-C ACLF Score and MELD Score in Predicting ICU Mortality in Patients with Acute-On-Chronic Liver Failure. Cureus. 12; e7087. Publisher Full Text
5. Chen X, Orom H, Hay JL, et al.: Differences in Rural and Urban Health Information Access and Use. J. Rural. Health. 2019; 35: 405–417. Publisher Full Text
6. Tsoris A, Marlar CA: Use Of The Child-Pugh Score In Liver Disease. StatPearls. Treasure Island (FL): StatPearls Publishing; 2023.
7. Singal AK, Kamath PS: Model for End-stage Liver Disease. J. Clin. Exp. Hepatol. 2013; 3: 50–60. Publisher Full Text
8. Challen R, Brooks-Pollock E, Read JM, et al.: Risk of mortality in patients infected with SARS-CoV-2 variant of concern 202012/1: matched cohort study. BMJ. 2021; 372: n579. Publisher Full Text
9. Smith AC, Thomas E, Snoswell CL, et al.: Telehealth for global emergencies: Implications for coronavirus disease 2019 (COVID-19). J. Telemed. Telecare. 2020; 26: 309–313. Publisher Full Text
10. Kamath PS, Kim WR: Advanced Liver Disease Study Group: The model for end-stage liver disease (MELD). Hepatology. 2007; 45: 797–805. Publisher Full Text
11. Moreau R, Jalan R, Gines P, et al.: Acute-on-chronic liver failure is a distinct syndrome that develops in patients with acute decompensation of cirrhosis. Gastroenterology. 2013; 144: 1426–37. 1437.e1-9. Publisher Full Text
12. Hart LG, Larson EH, Lishner DM: Rural definitions for health policy and research. Am. J. Public Health. 2005; 95: 1149–1155. Publisher Full Text

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 29 Apr 2024

Author details Author details

¹ Medicine, Datta Meghe Institute of Higher Education and Research, Wardha, 442001, India

Nitish Batra
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Shilpa Gaidhane
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Sourya Acharya
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Sunil Kumar
Roles: Methodology, Project Administration, Writing – Original Draft Preparation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

The author(s) declared that no grants were involved in supporting this work.

Article Versions (1)

version 1

Published: 29 Apr 2024, 13:419

https://doi.org/10.12688/f1000research.144938.1

© 2024 Batra N et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Download

Export To

metrics

	Views	Downloads
F1000Research	-	-
PubMed Central Data from PMC are received and updated monthly.	-	-

Citations

SEE MORE DETAILS

CITE

how to cite this article

Batra N, Gaidhane S, Acharya S and Kumar S. Accuracy of chronic liver failure consortium (CLIF-C) ACLF score compared with meld, MELD-NA and CTP as a mortality predictor in acute on chronic liver failure patients admitted to tertiary rural care hospital [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2024, 13:419 (https://doi.org/10.12688/f1000research.144938.1)

NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.

track

receive updates on this article

Track an article to receive email alerts on any updates to this article.

Open Peer Review

Current Reviewer Status: ?

Key to Reviewer Statuses VIEW HIDE

ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions

Version 1

VERSION 1

PUBLISHED 29 Apr 2024

Views

Reviewer Report 03 Jun 2024

Alexandra Alexopoulou, 2nd Dept of Medicine, Medical School, Kapodistrian University of Athens, Hippokration General Hospital, Athens, Greece

Approved

https://doi.org/10.5256/f1000research.158808.r280745

The study protocol entitled "Accuracy of chronic liver failure consortium (CLIF-C) ACLF score compared with meld, MELD-NA and CTP as a mortality predictor in acute on chronic liver failure patients admitted to tertiary rural care hospital" is very interesting, aiming to compare the predictive performance of scoring systems commonly used for the estimation of acute on chronic liver failure in a rural caring environment.

The authors are aware of the literature, their rationale and objectives were well described and their methods are clearly presented.

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Cirrhosis and complications

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

CITE

Report a concern

Respond or Comment

Views

Reviewer Report 03 Jun 2024

Yu Chen, Capital Medical University, Beijing, China

Yuan Gao, Capital Medical University, Beijing, China

Not Approved

https://doi.org/10.5256/f1000research.158808.r280740

"Acute on chronic liver failure" and "acute chronic liver failure" should be uniformly referred to in this protocol.
The ACLF diagnostic criteria vary between the Asia-Pacific and EASL. As a protocol, could

"Acute on chronic liver failure" and "acute chronic liver failure" should be uniformly referred to in this protocol.
The ACLF diagnostic criteria vary between the Asia-Pacific and EASL. As a protocol, could you mention which standard you're using to include patients?
As a comparative study of model scores, please clarify why there is no validation cohort in this study.
All participants in the study are ACLF patients, and you calculated the sample size based on ACLF incidence rates. This is methodologically or logically incorrect.

Is the rationale for, and objectives of, the study clearly described?

Partly
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

No
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests: No competing interests were disclosed.

We confirm that we have read this submission and believe that we have an appropriate level of expertise to state that we do not consider it to be of an acceptable scientific standard, for reasons outlined above.

CITE

Report a concern

Respond or Comment

Views

Reviewer Report 29 May 2024

Jonathan Soldera, University of South Wales, Cardiff, UK; Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil

Approved with Reservations

https://doi.org/10.5256/f1000research.158808.r280742

This study protocol aims to evaluate the accuracy of the Chronic Liver Failure Consortium (CLIF-C) ACLF score in predicting mortality among acute on chronic liver failure (ACLF) patients in a tertiary rural care hospital, compared with other established scoring systems like MELD, MELD-Na, and CTP. It is a prospective observational cohort study involving comprehensive assessments and statistical analyses to identify the best predictors of 28-day mortality in ACLF patients.
Congratulations to the authors on undertaking this important study. Investigating the performance of CLIF-C ACLF, MELD, MELD-Na, and CTP scores in a rural healthcare setting is crucial for improving prognostic accuracy and patient outcomes in these environments.
To enhance the robustness and depth of the study, the authors should consider reviewing the following papers:

A systematic review on the use of these scoring systems for ACLF to provide a comprehensive background and context: (Rashed et al.,2022) (ref-5)
Recent research articles that discuss advancements in liver failure prognostication tools in multiple scenarios, such as SBP and variceal bleeding: (Jonathan,2023) (ref-1) ; (Grochot et al.)(ref-2); (Terres et,al.,2020)(Ref-5) ; (Jacques et al.,2020)(Ref-6) ; (Grochot et.,2020) (Ref-10);(Jacques et al.,2021) (Ref-7); (Terres et al., 2021) (Ref-8); (Terres.,2023)(Ref-9) ; (Ndomba et al.,2023)(ref-3)

Additionally, improving the language clarity in the manuscript is recommended, as some sentences are challenging to understand. This will ensure the findings are communicated more effectively to a broader audience.

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Partly

References

1. S, Jonathan: ARTIFICIAL INTELLIGENCE AS A PROGNOSTIC TOOL FORGASTROINTESTINAL TRACT PATHOLOGIES. https://revistamedicavozandes.com/wp-content/uploads/2023/07/02_EDITORIAL-1.html. 2023.
2. RM, Grochot LB, Luz R, Garcia RA, et al.: Clif-Sofa is Superior to Other Liver-Specific Scores for Predicting Mortality in Acute-on-Chronic Liver Failure and Decompensated Cirrhosis. https://austinpublishinggroup.com/gastroenterology/fulltext/ajg-v6-id1105.php. 2019.
3. Ndomba N, Soldera J: Management of sepsis in a cirrhotic patient admitted to the intensive care unit: A systematic literature review.World J Hepatol. 2023; 15 (6): 850-866 PubMed Abstract | Publisher Full Text
4. Rashed, E Soldera, J: CLIF-SOFA and CLIF-C scores for the prognostication of acute-on-chronic liver failure and acute decompensation of cirrhosis: A systematic review. https://www.wjgnet.com/1948-5182/full/v14/i12/2025.htm. 2022. Publisher Full Text
5. A, Terres RS, Balbinot Ana, Muscope, M, et al.: Predicting mortality for hepatorenal syndrome with liver-specific scores. https://onlinelibrary.wiley.com/doi/10.1002/ygh2.429. 2020. Publisher Full Text
6. Oliveira Coberllini Jacques R, Silva Massignan L, Schumacher Winkler M, Sartori Balbinot R, et al.: Liver‐specific scores as predictors of mortality in spontaneous bacterial peritonitis. GastroHep. 2020; 2 (5): 224-231 Publisher Full Text
7. Jacques ROC, Massignan LDS, Winkler MS, Balbinot RS, et al.: ACUTE-ON-CHRONIC LIVER FAILURE IS INDEPENDENTLY ASSOCIATED WITH LOWER SURVIVAL IN PATIENTS WITH SPONTANEOUS BACTERIAL PERITONITIS.Arq Gastroenterol. 2021; 58 (3): 344-352 PubMed Abstract | Publisher Full Text
8. Terres A, Balbinot R, Muscope A, Eberhardt L, et al.: Predicting mortality for cirrhotic patients with acute oesophageal variceal haemorrhage using liver‐specific scores. GastroHep. 2021; 3 (4): 236-246 Publisher Full Text
9. Terres AZ, Balbinot RS, Muscope ALF, Longen ML, et al.: Acute-on-chronic liver failure is independently associated with higher mortality for cirrhotic patients with acute esophageal variceal hemorrhage: Retrospective cohort study.World J Clin Cases. 2023; 11 (17): 4003-4018 PubMed Abstract | Publisher Full Text
10. RM, Grochot LB, Luz R, Garcia RA, et al.: ACUTE-ON-CHRONIC LIVER FAILURE DATA FROM A TEACHING HOSPITAL IN BRAZIL. A HISTORICAL COHORT. https://www.worldwidejournals.com/international-journal-of-scientific-research-(IJSR)/article/acuteandndash-onandndash-chronic-liver-failure-data-from-a-teaching-hospital-in-brazil-a-historical-cohort/MjUzNTk. 2020. Publisher Full Text

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Acute on Chronic Liver Failure and Inflammatory Bowel Disease.

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

CITE

Report a concern

Author Response 11 Sep 2025

nitish batra, Medicine, Datta Meghe Institute of Higher Education and Research, Wardha, 442001, India

11 Sep 2025

Author Response

Thank you for your thoughtful and encouraging feedback on our study protocol. I greatly appreciate your recognition of the importance of evaluating the prognostic accuracy of scoring systems such as ... Continue reading Thank you for your thoughtful and encouraging feedback on our study protocol. I greatly appreciate your recognition of the importance of evaluating the prognostic accuracy of scoring systems such as CLIF-C ACLF, MELD, MELD-Na, and CTP in a rural tertiary care setting.
I acknowledge and value your suggestions regarding the inclusion of key references to strengthen the background and contextual framework of our study.
I have incorporated the following sources into the revised manuscript, particularly focusing on the systematic review by Rashed et al. (2022) [Ref-5], and recent advancements discussed in works by Jonathan (2023) [Ref-1], Grochot et al. [Refs-2,10], Terres et al. [Refs-5,8,9], Jacques et al. [Refs-6,7], and Ndomba et al. (2023) [Ref-3]. These studies will enrich our literature review and support the rationale for comparing multiple prognostic tools in different clinical scenarios such as spontaneous bacterial peritonitis and variceal bleeding.
I also appreciate your recommendation to improve the clarity and precision of the manuscript’s language. A thorough revision for readability and grammatical accuracy will be undertaken to ensure clear and effective communication of our methodology and findings to a broader clinical and research audience.
Regarding your comments on dataset presentation, we acknowledge that some aspects of our data formatting may need refinement. I shall work on enhancing the accessibility and structure of our datasets to facilitate usability and replication by other researchers.
Thank you once again for your constructive input, which will significantly contribute to improving the quality and impact of our study.
Thank you for your thoughtful and encouraging feedback on our study protocol. I greatly appreciate your recognition of the importance of evaluating the prognostic accuracy of scoring systems such as CLIF-C ACLF, MELD, MELD-Na, and CTP in a rural tertiary care setting.
I acknowledge and value your suggestions regarding the inclusion of key references to strengthen the background and contextual framework of our study.
I have incorporated the following sources into the revised manuscript, particularly focusing on the systematic review by Rashed et al. (2022) [Ref-5], and recent advancements discussed in works by Jonathan (2023) [Ref-1], Grochot et al. [Refs-2,10], Terres et al. [Refs-5,8,9], Jacques et al. [Refs-6,7], and Ndomba et al. (2023) [Ref-3]. These studies will enrich our literature review and support the rationale for comparing multiple prognostic tools in different clinical scenarios such as spontaneous bacterial peritonitis and variceal bleeding.
I also appreciate your recommendation to improve the clarity and precision of the manuscript’s language. A thorough revision for readability and grammatical accuracy will be undertaken to ensure clear and effective communication of our methodology and findings to a broader clinical and research audience.
Regarding your comments on dataset presentation, we acknowledge that some aspects of our data formatting may need refinement. I shall work on enhancing the accessibility and structure of our datasets to facilitate usability and replication by other researchers.
Thank you once again for your constructive input, which will significantly contribute to improving the quality and impact of our study.
Competing Interests: No competing interests were disclosed. Close
Report a concern
Respond or Comment

COMMENTS ON THIS REPORT

Author Response 11 Sep 2025

nitish batra, Medicine, Datta Meghe Institute of Higher Education and Research, Wardha, 442001, India

11 Sep 2025

Author Response

Thank you for your thoughtful and encouraging feedback on our study protocol. I greatly appreciate your recognition of the importance of evaluating the prognostic accuracy of scoring systems such as ... Continue reading Thank you for your thoughtful and encouraging feedback on our study protocol. I greatly appreciate your recognition of the importance of evaluating the prognostic accuracy of scoring systems such as CLIF-C ACLF, MELD, MELD-Na, and CTP in a rural tertiary care setting.
I acknowledge and value your suggestions regarding the inclusion of key references to strengthen the background and contextual framework of our study.
I have incorporated the following sources into the revised manuscript, particularly focusing on the systematic review by Rashed et al. (2022) [Ref-5], and recent advancements discussed in works by Jonathan (2023) [Ref-1], Grochot et al. [Refs-2,10], Terres et al. [Refs-5,8,9], Jacques et al. [Refs-6,7], and Ndomba et al. (2023) [Ref-3]. These studies will enrich our literature review and support the rationale for comparing multiple prognostic tools in different clinical scenarios such as spontaneous bacterial peritonitis and variceal bleeding.
I also appreciate your recommendation to improve the clarity and precision of the manuscript’s language. A thorough revision for readability and grammatical accuracy will be undertaken to ensure clear and effective communication of our methodology and findings to a broader clinical and research audience.
Regarding your comments on dataset presentation, we acknowledge that some aspects of our data formatting may need refinement. I shall work on enhancing the accessibility and structure of our datasets to facilitate usability and replication by other researchers.
Thank you once again for your constructive input, which will significantly contribute to improving the quality and impact of our study.
Thank you for your thoughtful and encouraging feedback on our study protocol. I greatly appreciate your recognition of the importance of evaluating the prognostic accuracy of scoring systems such as CLIF-C ACLF, MELD, MELD-Na, and CTP in a rural tertiary care setting.
I acknowledge and value your suggestions regarding the inclusion of key references to strengthen the background and contextual framework of our study.
I have incorporated the following sources into the revised manuscript, particularly focusing on the systematic review by Rashed et al. (2022) [Ref-5], and recent advancements discussed in works by Jonathan (2023) [Ref-1], Grochot et al. [Refs-2,10], Terres et al. [Refs-5,8,9], Jacques et al. [Refs-6,7], and Ndomba et al. (2023) [Ref-3]. These studies will enrich our literature review and support the rationale for comparing multiple prognostic tools in different clinical scenarios such as spontaneous bacterial peritonitis and variceal bleeding.
I also appreciate your recommendation to improve the clarity and precision of the manuscript’s language. A thorough revision for readability and grammatical accuracy will be undertaken to ensure clear and effective communication of our methodology and findings to a broader clinical and research audience.
Regarding your comments on dataset presentation, we acknowledge that some aspects of our data formatting may need refinement. I shall work on enhancing the accessibility and structure of our datasets to facilitate usability and replication by other researchers.
Thank you once again for your constructive input, which will significantly contribute to improving the quality and impact of our study.
Competing Interests: No competing interests were disclosed. Close
Report a concern

Comments on this article Comments (0)

Version 1

VERSION 1 PUBLISHED 29 Apr 2024

Open Peer Review

Reviewer Status

Reviewer Reports

	Invited Reviewers
	1	2	3
Version 1 29 Apr 24	read	read	read

Jonathan Soldera, University of South Wales, Cardiff, UK; Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil
Yu Chen, Capital Medical University, Beijing, China

Yuan Gao, Capital Medical University, Beijing, China
Alexandra Alexopoulou, Kapodistrian University of Athens, Hippokration General Hospital, Athens, Greece

Comments on this article

All Comments(0)

Add a comment

Browse by related subjects

Back to all reports

Reviewer Report

5 Views

03 Jun 2024 | for Version 1

Alexandra Alexopoulou, 2nd Dept of Medicine, Medical School, Kapodistrian University of Athens, Hippokration General Hospital, Athens, Greece

5 Views Cite this report Responses(0)

Approved

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Cirrhosis and complications

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

2 Views

03 Jun 2024 | for Version 1

Yu Chen, Capital Medical University, Beijing, China

Yuan Gao, Capital Medical University, Beijing, China

2 Views Cite this report Responses(0)

Not Approved

"Acute on chronic liver failure" and "acute chronic liver failure" should be uniformly referred to in this protocol.
The ACLF diagnostic criteria vary between the Asia-Pacific and EASL. As a protocol, could you mention which standard you're using to include patients?
As a comparative study of model scores, please clarify why there is no validation cohort in this study.
All participants in the study are ACLF patients, and you calculated the sample size based on ACLF incidence rates. This is methodologically or logically incorrect.

Is the rationale for, and objectives of, the study clearly described?

Partly
Is the study design appropriate for the research question?

Partly
Are sufficient details of the methods provided to allow replication by others?

No
Are the datasets clearly presented in a useable and accessible format?

Not applicable

Competing Interests

No competing interests were disclosed.

Respond to this report

Responses (0)

Back to all reports

Reviewer Report

11 Views

29 May 2024 | for Version 1

Jonathan Soldera, University of South Wales, Cardiff, UK; Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil

11 Views Cite this report Responses(1)

Approved With Reservations

Is the rationale for, and objectives of, the study clearly described?

Yes
Is the study design appropriate for the research question?

Yes
Are sufficient details of the methods provided to allow replication by others?

Yes
Are the datasets clearly presented in a useable and accessible format?

Partly

References

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Acute on Chronic Liver Failure and Inflammatory Bowel Disease.

Respond to this report

Responses (1)

Author Response

11 Sep 2025

nitish batra, Medicine, Datta Meghe Institute of Higher Education and Research, Wardha, 442001, India

Thank you for your thoughtful and encouraging feedback on our study protocol. I greatly appreciate your recognition of the importance of evaluating the prognostic accuracy of scoring systems such as CLIF-C ACLF, MELD, MELD-Na, and CTP in a rural tertiary care setting.
I acknowledge and value your suggestions regarding the inclusion of key references to strengthen the background and contextual framework of our study.
I have incorporated the following sources into the revised manuscript, particularly focusing on the systematic review by Rashed et al. (2022) [Ref-5], and recent advancements discussed in works by Jonathan (2023) [Ref-1], Grochot et al. [Refs-2,10], Terres et al. [Refs-5,8,9], Jacques et al. [Refs-6,7], and Ndomba et al. (2023) [Ref-3]. These studies will enrich our literature review and support the rationale for comparing multiple prognostic tools in different clinical scenarios such as spontaneous bacterial peritonitis and variceal bleeding.
I also appreciate your recommendation to improve the clarity and precision of the manuscript’s language. A thorough revision for readability and grammatical accuracy will be undertaken to ensure clear and effective communication of our methodology and findings to a broader clinical and research audience.
Regarding your comments on dataset presentation, we acknowledge that some aspects of our data formatting may need refinement. I shall work on enhancing the accessibility and structure of our datasets to facilitate usability and replication by other researchers.
Thank you once again for your constructive input, which will significantly contribute to improving the quality and impact of our study.

View more View less

Competing Interests

No competing interests were disclosed.

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] 1. Cheemerla S, Balakrishnan M: Global Epidemiology of Chronic Liver Disease. Clin Liver Dis (Hoboken). 2021; 17: 365–370. Publisher Full Text

[2] 2. CLIF-C ACLF (Acute-on-Chronic Liver Failure): MDCalc. Accessed: November 9, 2023. Reference Source

[3] 3. Barosa R, Roque Ramos L, Patita M, et al.: CLIF-C ACLF score is a better mortality predictor than MELD, MELD-Na and CTP in patients with Acute on chronic liver failure admitted to the ward. Rev. Esp. Enferm. Dig. 2017; 109: 399–405. Publisher Full Text

[4] 4. Ramzan M, Iqbal A, Murtaza HG, et al.: Comparison of CLIF-C ACLF Score and MELD Score in Predicting ICU Mortality in Patients with Acute-On-Chronic Liver Failure. Cureus. 12; e7087. Publisher Full Text

[5] 5. Chen X, Orom H, Hay JL, et al.: Differences in Rural and Urban Health Information Access and Use. J. Rural. Health. 2019; 35: 405–417. Publisher Full Text

[6] 6. Tsoris A, Marlar CA: Use Of The Child-Pugh Score In Liver Disease. StatPearls. Treasure Island (FL): StatPearls Publishing; 2023.

[7] 7. Singal AK, Kamath PS: Model for End-stage Liver Disease. J. Clin. Exp. Hepatol. 2013; 3: 50–60. Publisher Full Text

[8] 8. Challen R, Brooks-Pollock E, Read JM, et al.: Risk of mortality in patients infected with SARS-CoV-2 variant of concern 202012/1: matched cohort study. BMJ. 2021; 372: n579. Publisher Full Text

[9] 9. Smith AC, Thomas E, Snoswell CL, et al.: Telehealth for global emergencies: Implications for coronavirus disease 2019 (COVID-19). J. Telemed. Telecare. 2020; 26: 309–313. Publisher Full Text

[10] 10. Kamath PS, Kim WR: Advanced Liver Disease Study Group: The model for end-stage liver disease (MELD). Hepatology. 2007; 45: 797–805. Publisher Full Text

[11] 11. Moreau R, Jalan R, Gines P, et al.: Acute-on-chronic liver failure is a distinct syndrome that develops in patients with acute decompensation of cirrhosis. Gastroenterology. 2013; 144: 1426–37. 1437.e1-9. Publisher Full Text

[12] 12. Hart LG, Larson EH, Lishner DM: Rural definitions for health policy and research. Am. J. Public Health. 2005; 95: 1149–1155. Publisher Full Text

Accuracy of chronic liver failure consortium (CLIF-C) ACLF score compared with meld, MELD-NA and CTP as a mortality predictor in acute on chronic liver failure patients admitted to tertiary rural care hospital

Abstract

Background

Method

Expected Outcome

Keywords

Introduction

Aim

Objectives

Methods

Study design

Study population

Place of study

Inclusion criteria

Exclusion criteria

Bias

Enrollment bias

Data collection

Sample size

Statistical methods

Expected outcome

Ethical considerations

Dissemination

Study status

Discussion

Trial registration

Data availability

References

Comments on this article Comments (0)

Open Peer Review

Comments on this article Comments (0)

Open Peer Review

Reviewer Status

Reviewer Reports

Comments on this article

Browse by related subjects

Competing Interests Policy

Stay Updated