Evidence map›Paper›PMID 41171421›Full record

ArticleSurgical endoscopy2026

MELD score is predictive of postoperative morbidity and mortality in patients with acute appendicitis undergoing appendectomy: ACS-NSQIP data analysis.

Fady Daniel, Mariam Baydoun, Ali R Chaitou, Rudy Mrad, Maha Makki, Mohamad Khalife, Hani Tamim

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Article in Surgical endoscopy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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7 authors.

Fady DanielDivision of Gastroenterology and Hepatology, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon. fd21@aub.edu.lb.
Mariam BaydounDivision of Gastroenterology and Hepatology, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon.
Ali R ChaitouDivision of Gastroenterology and Hepatology, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon.
Rudy MradDivision of Gastroenterology and Hepatology, Department of Internal Medicine, American University of Beirut Medical Center, Beirut, Lebanon.
Maha MakkiDepartment of Internal Medicine, Clinical Research Institute, American University of Beirut Medical Center, Beirut, Lebanon.
Mohamad KhalifeDivision of General Surgery, Department of Surgery, American University of Beirut Medical Center, Beirut, Lebanon.
Hani TamimDepartment of Internal Medicine, Clinical Research Institute, American University of Beirut Medical Center, Beirut, Lebanon.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe model for end-stage liver disease (MELD) score has been shown to be a valid predictive tool for postoperative risks across various types of surgeries, after initially being restricted to liver transplantation eligibility assessment in cirrhotic patients. Since appendectomy is one of the most common surgical procedures, our objective is to compare the impact of the three versions of the MELD score (1.0, 2.0, and 3.0) on the risk assessment of 30-day postoperative morbidity and mortality in patients undergoing appendectomy for acute appendicitis.

methodsData on patients undergoing appendectomy for acute appendicitis were collected from the ACS-NSQIP database from 2018 to 2022 using the Current Procedural Terminology (CPT) codes 44,950, 44,960, and 44,970. The different MELD scores and outcomes were compared using the Chi-square test. The outcomes measured included 30-day mortality, wound infection, cardiac, respiratory, urinary, and central nervous system complications, thromboembolism, sepsis, bleeding, return to the operating room, and composite morbidity.

resultsA total of 121,207 patients were included, with a mean age of 45.31 ± 17.89 years, of which 58,495 (48.3%) were females. The majority, 102,895 (90.7%) patients, underwent laparoscopic appendectomy, whereas 10,599 (9.3%) had open appendectomy. The overall 30-day surgical mortality was 0.5% (567/121,207), and postoperative sepsis was observed in 5.8% (7,063/121,207). All the MELD score versions significantly predicted the outcomes independently of the surgical approach (laparoscopic/open appendectomy, simple/complicated appendicitis) with means of 8.21 ± 2.81, 9.01 ± 3.39, and 9.21 ± 3.26 for MELD 1.0, MELD 2.0, and MELD 3.0 scores, respectively. MELD 3.0 score noticeably outperformed its predecessors regarding all the outcomes. Patients with a score ≥ 11 had a higher prevalence of postoperative complications.

conclusionThe MELD score, in its three versions, is a valid tool for assessing 30-day morbidity and mortality risk following appendectomy for acute appendicitis. MELD 3.0, with a cutoff of 11, demonstrated superior predictive performance.

Indexed as

AppendectomyAppendicitisEnd Stage Liver DiseasePostoperative ComplicationsAcute DiseaseAdultFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentSeverity of Illness IndexAppendectomyAppendicitisMELD scoreMortalityNSQIPSepsis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.