Effect of Sugarcane Juice on Liver Patients

Overview

This study aims to investigate the potential benefits of sugarcane juice on liver health in patients who are suffering from liver-related conditions. We hypothesize that regular consumption of sugarcane juice may improve liver function and alleviate symptoms in patients with liver disease. Patients participating in this study will consume a specified amount of sugarcane juice daily for 90 days, and their liver health will be monitored to assess any improvements. This study could help identify a natural, accessible treatment option to support liver health in patients with liver disease, potentially improving their quality of life.

This randomized controlled trial (RCT) is designed to evaluate the impact of sugarcane juice on liver health in patients diagnosed with liver-related conditions, including cirrhosis, hepatitis, and fatty liver disease. The study aims to assess whether sugarcane juice, administered in varying dosages, has a therapeutic effect on liver enzyme levels and overall liver function. Study Design This is an interventional study using a randomized controlled trial (RCT) design. Participants will be randomly assigned to one of four groups: three treatment groups and one control group. The treatment groups will receive daily doses of sugarcane juice at 170mL, 230mL, and 300mL, respectively, along with their prescribed medicine, for a duration of three months. The control group will receive no sugarcane juice but will continue their prescribed medication regimen. Intervention Details Control Group: Receives no sugarcane juice, only prescribed medication. Group 1: Receives 170mL of sugarcane juice daily along with prescribed medication. Group 2: Receives 230mL of sugarcane juice daily along with prescribed medication. Group 3: Receives 300mL of sugarcane juice daily along with prescribed medication. Duration of the Study The study will span three months, during which participants' liver health will be monitored at regular intervals. Outcome Measures Primary Outcome Measures: Levels of liver enzymes: Alanine Aminotransferase (ALT), Aspartate Aminotransferase (AST), Alkaline Phosphatase (ALP), and Total Bilirubin. Secondary Outcome Measures: Changes in liver-related symptoms, including jaundice, abdominal pain, fatigue, and nausea. Sample Size The study will enroll a total of 400 participants. The participants will be divided into four groups: Control Group: 100 participants Group 1: 100 participants Group 2: 100 participants Group 3: 100 participants Inclusion and Exclusion Criteria Inclusion Criteria: Patients diagnosed with liver disease, including but not limited to cirrhosis, hepatitis, or fatty liver disease. Age group 20-60 years. Symptoms criteria based on liver disease include jaundice, abdominal pain, fatigue, nausea, and elevated liver enzymes (ALT, AST) as per standard diagnostic criteria. Exclusion Criteria: Patients younger than 20 years or older than 60 years. Patients with a history of other chronic conditions that may interfere with liver function, such as chronic kidney disease or heart failure. Patients who have undergone liver transplantation. Patients currently participating in another clinical trial related to liver disease. Pregnant or breastfeeding women. Statistical Analysis Plan The data will be analyzed using SPSS (version 27). A Two-Way ANOVA will be used to compare the effects of different dosages of sugarcane juice on liver enzyme levels across the treatment groups and control group. Post hoc analysis will be conducted using Tukey's Honest Significant Difference (HSD) test to identify specific group differences. Quality Assurance Measures Data Validation: Rigorous input checks, automated testing, and manual reviews will be implemented to ensure data accuracy. Site Monitoring: Real-time monitoring tools will be employed to track site performance and swiftly identify any data issues. Auditing: Regular audits will be performed to ensure compliance with the study protocol and to maintain the integrity of the data. Handling Missing Data Data Imputation: Both simple and advanced methods will be employed to impute missing data, ensuring the robustness of the dataset. Data Cleansing: Consistency checks and outlier detection methods will be implemented to correct data errors. User Feedback: Tools will be provided to allow users to report and correct missing or inconsistent data promptly.