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Evaluating the Outcomes in Patients with Colorectal Cancer Using the Malnutrition Universal Screening Tool: A
Calin Muntean1, Andiana Roxana Blidari2, Alaviana Monique Faur3
1Medical Informatics and Biostatistics, Department III-Functional Sciences, "Victor Babes" University of Medicine and Pharmacy Timisoara, Timisoara, Romania.
Background:
The current systematic review aimed to evaluate the Malnutrition Universal Screening Tool (MUST) for its effectiveness in determining patient outcomes (length of hospital stay, postoperative complications, infection rates, and survival) for colorectal cancer.
Methods:
Utilizing a comprehensive search strategy, this review mined literature up to December 2023 from the PubMed, Scopus, and Embase databases. The focus was on identifying studies that scrutinize the prognostic value of MUST in relation to hospital outcomes in colorectal cancer contexts. Adherence to PRISMA guidelines ensured a systematic approach, encompassing various study designs and outcome measures.
Results:
Among the seven studies incorporating 1950 patients, a significant correlation emerged between MUST scores and key hospital outcomes. Specifically, patients categorized as high MUST risk faced longer hospital stays, with a mean length of stay for high-risk patients extending up to 26.6 days compared to 14 days for those at lower risk. The prevalence of postoperative complications was substantially higher in the high-risk group, with up to 41.4% of high MUST risk patients experiencing severe complications (Clavien-Dindo 3-5) compared to 8.5% in the low-risk category. Notably, the review found that high MUST scores were strongly predictive of increased postoperative complications and a prolonged hospital stay, underscoring the tool's critical predictive utility for quality of life and use in clinical settings.
Conclusions:
Therefore, MUST's capability to predict longer hospital stays and a higher incidence of postoperative complications among high-risk patients highlights its essential function in preoperative evaluations and supports the integration of MUST into routine clinical assessments.
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