Evidence map›Paper›PMID 42263377›Full record

ArticleJournal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract2026

Age-stratified risk profiles for emergency colorectal cancer resection: A machine-learning analysis.

Trisha Lal, Fangzhou Liu, Alexander Cabulong, Christine O Kang, Richard S Hoehn, Johnie Rose, Siran M Koroukian

Abstract read
In one paragraph

Article in Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

7 authors.

Trisha LalDivision of Surgical Oncology, University Hospitals Cleveland Medical Center, Cleveland, OH, United States. Electronic address: trisha.lal@uhhospitals.org.
Fangzhou LiuCase Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, OH, United States; Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, United States.
Alexander CabulongDepartment of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, United States.
Christine O KangDepartment of Family Medicine and Community Health, University Hospitals Cleveland Medical Center, Cleveland, OH, United States.
Richard S HoehnDivision of Surgical Oncology, University Hospitals Cleveland Medical Center, Cleveland, OH, United States; Case Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, OH, United States.
Johnie RoseCase Comprehensive Cancer Center, School of Medicine, Case Western Reserve University, Cleveland, OH, United States; Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, United States; Center for Community Health Integration, School of Medicine, Case Western Reserve University, Cleveland, OH, United States.
Siran M KoroukianDepartment of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, United States; Center for Community Health Integration, School of Medicine, Case Western Reserve University, Cleveland, OH, United States.

Funding

TUMOR METABOLISM PROGRAMP30CA043703 · NCI · CASE WESTERN RESERVE UNIVERSITY · PI Amar Desai · 1987 to 2026
$142.3M
NCI NIH HHS P30 CA043703
6 · The paper itself

Abstract

backgroundEmergency colorectal cancer resection (ECCR) is associated with worse perioperative and oncologic outcomes than elective surgery. As the incidence of colorectal cancer rises among younger adults and disparities persist across the life course, we examined how clinical and sociodemographic factors intersect to shape ECCR risk across age groups.

methodsWe conducted a retrospective cohort study of adult colorectal cancer resection admissions in the National Inpatient Sample between 2018 and 2022. Multivariable logistic regression and classification and regression tree (CART) analyzes were used to identify independent predictors of ECCR and age-specific high-risk phenotypes.

resultsAmong 510,135 resection admissions, 64,175 (12.6%) were ECCR. ECCR admissions more often involved patients with compromised health (weight loss, anemia, coagulopathy, and electrolyte disorders), metastatic disease, and ≥3 comorbidities across all ages. Among younger and middle-aged adults, ECCR disproportionately involved patients who were on Medicaid or who were uninsured and those from lower-income communities. In multivariable models, female sex and higher income were associated with protection across most age groups, whereas being on Medicaid or uninsured status, having a higher comorbidity burden, and admission during the COVID-19 pandemic era were more frequently associated with higher odds of ECCR. CART analysis identified age-specific phenotypes, with insurance status predominating in patients younger than 75 years, and clinical complexity and pandemic-era timing predominating in those aged 76 years or older.

conclusionECCR risk reflects different dominant mechanisms across age groups, suggesting that a one-size-fits-all approach is unlikely to reduce emergency presentations. Age-tailored strategies that address access barriers and optimize management of medically complex older adults may improve timely, equitable colorectal cancer care.

Indexed as

ColectomyColorectal NeoplasmsMachine LearningAdultAgedAge FactorsColorectal Surgical ProceduresEmergenciesFemaleHumansMaleMiddle AgedRetrospective StudiesRisk AssessmentRisk FactorsSocioeconomic Disparities in HealthColorectal cancerEmergency colorectal cancer resectionMachine learningSocial determinants of health

Identifiers

PMID42263377
PMCPMC13251322

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Registered trials

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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.