[version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]
No competing interests were disclosed.
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.
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.
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.
Chronic liver diseases represent a substantial global health burden, contributing significantly to morbidity and mortality.
Several scoring systems have been developed to assess the severity of liver disease and predict mortality, each with advantages and limitations.
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.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
Calculated by following the formula where:
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.
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.
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 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.
After the completion of the study, we will publish it in an indexed journal or conference.
The study has yet to start. After the publication of the protocol, we will start recruitment in the study.
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.
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.
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.
This study protocol has been registered with the Clinical Trials Registry – India (CTRI) - CTRI REF/2023/07/069843.
No data are associated with this article.
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 study design appropriate for the research question?
Yes
Is the rationale for, and objectives of, the study clearly described?
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
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.
"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 study design appropriate for the research question?
Partly
Is the rationale for, and objectives of, the study clearly described?
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
Reviewer Expertise:
NA
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.
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 study design appropriate for the research question?
Yes
Is the rationale for, and objectives of, the study clearly described?
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
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.
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.