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Identifying those at risk: predicting patient factors associated with worse EGS outcomes.

Publication ,  Journal Article
Abdul Rahim, K; Shaikh, NQ; Lakhdir, MPA; Merchant, AAH; Afzal, N; Mahmood, SBZ; Bakhshi, SK; Ali, M; Samad, Z; Haider, AH
Published in: Trauma Surg Acute Care Open
2025

BACKGROUND: Comorbidity has a detrimental impact on Emergency General Surgery (EGS) outcomes. In lesser-developed countries with inconsistent documentation of comorbid conditions, undiagnosed and progressively worsening comorbidities can worsen EGS outcomes. We aimed to discern the comorbidity index as a predictor of complications and inpatient mortality in EGS using a large South Asian sample population. MATERIALS AND METHODS: Data of adult patients with AAST-defined EGS diagnoses at primary index admission from 2010 to 2019 were retrieved. Patients were categorized into predefined EGS groups using ICD-9 CM codes. Primary exposure was comorbidity using the Charlson Comorbidity Index (CCI). The primary outcome was inpatient mortality, and the secondary outcome was complication status. Multiple logistic and Cox regression with Weibull distribution was performed. RESULTS: Analysis of 32 280 patients showed a mean age of 40.06±16.87 years. Overall comorbidity, inpatient mortality, and complication rates were 44.6%, 2.42% and 36.37%, respectively. Patients with moderate CCI had the highest complications (AOR 6.61, 95% CI 5.91, 7.37), and severe comorbidity had the highest hazards (AOR 3.79, 95% CI 2.89, 4.98). Male gender, increasing age, emergent admission status, and lack of insurance were associated with moderate and severe CCI, resulting in prolonged length of stay (5.72 and 5.83 days), reduced survival time (20.04 and 21.95 days), and higher mortality rates (10.52% and 9.48%). CONCLUSIONS: We identified predictive patient-level factors associated with higher CCI and worse EGS outcomes. Our findings can help stratify population subsets at risk of worse outcomes, provide valuable insight into disease progression, and aid decision-making in EGS patients. LEVEL OF EVIDENCE: III.

Duke Scholars

Published In

Trauma Surg Acute Care Open

DOI

EISSN

2397-5776

Publication Date

2025

Volume

10

Issue

2

Start / End Page

e001690

Location

England
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Abdul Rahim, K., Shaikh, N. Q., Lakhdir, M. P. A., Merchant, A. A. H., Afzal, N., Mahmood, S. B. Z., … Haider, A. H. (2025). Identifying those at risk: predicting patient factors associated with worse EGS outcomes. Trauma Surg Acute Care Open, 10(2), e001690. https://doi.org/10.1136/tsaco-2024-001690
Abdul Rahim, Komal, Namra Qadeer Shaikh, Maryam Pyar Ali Lakhdir, Asma Altaf Hussain Merchant, Noreen Afzal, Saad Bin Zafar Mahmood, Saqib Kamran Bakhshi, Mushyada Ali, Zainab Samad, and Adil H. Haider. “Identifying those at risk: predicting patient factors associated with worse EGS outcomes.Trauma Surg Acute Care Open 10, no. 2 (2025): e001690. https://doi.org/10.1136/tsaco-2024-001690.
Abdul Rahim K, Shaikh NQ, Lakhdir MPA, Merchant AAH, Afzal N, Mahmood SBZ, et al. Identifying those at risk: predicting patient factors associated with worse EGS outcomes. Trauma Surg Acute Care Open. 2025;10(2):e001690.
Abdul Rahim, Komal, et al. “Identifying those at risk: predicting patient factors associated with worse EGS outcomes.Trauma Surg Acute Care Open, vol. 10, no. 2, 2025, p. e001690. Pubmed, doi:10.1136/tsaco-2024-001690.
Abdul Rahim K, Shaikh NQ, Lakhdir MPA, Merchant AAH, Afzal N, Mahmood SBZ, Bakhshi SK, Ali M, Samad Z, Haider AH. Identifying those at risk: predicting patient factors associated with worse EGS outcomes. Trauma Surg Acute Care Open. 2025;10(2):e001690.

Published In

Trauma Surg Acute Care Open

DOI

EISSN

2397-5776

Publication Date

2025

Volume

10

Issue

2

Start / End Page

e001690

Location

England