Identifying those at risk: predicting patient factors associated with worse EGS outcomes
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...
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| Format: | Article |
| Language: | English |
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BMJ Publishing Group
2025-05-01
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| Series: | Trauma Surgery & Acute Care Open |
| Online Access: | https://tsaco.bmj.com/content/10/2/e001690.full |
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| author | Adil H Haider Maryam Pyar Ali Lakhdir Zainab Samad Noreen Afzal Asma Altaf Hussain Merchant Komal Abdul Rahim Namra Qadeer Shaikh Saad bin Zafar Mahmood Saqib Kamran Bakhshi Mushyada Ali |
| author_facet | Adil H Haider Maryam Pyar Ali Lakhdir Zainab Samad Noreen Afzal Asma Altaf Hussain Merchant Komal Abdul Rahim Namra Qadeer Shaikh Saad bin Zafar Mahmood Saqib Kamran Bakhshi Mushyada Ali |
| author_sort | Adil H Haider |
| collection | DOAJ |
| description | 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 |
| format | Article |
| id | doaj-art-67cefdb76dad436b8317f8c08cd9fc3a |
| institution | DOAJ |
| issn | 2397-5776 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | Trauma Surgery & Acute Care Open |
| spelling | doaj-art-67cefdb76dad436b8317f8c08cd9fc3a2025-08-20T03:05:35ZengBMJ Publishing GroupTrauma Surgery & Acute Care Open2397-57762025-05-0110210.1136/tsaco-2024-001690Identifying those at risk: predicting patient factors associated with worse EGS outcomesAdil H Haider0Maryam Pyar Ali Lakhdir1Zainab Samad2Noreen Afzal3Asma Altaf Hussain Merchant4Komal Abdul Rahim5Namra Qadeer Shaikh6Saad bin Zafar Mahmood7Saqib Kamran Bakhshi8Mushyada Ali9Department of Surgery, The Aga Khan University, Medical College, Karachi, PakistanDepartment of Community Health Sciences, Aga Khan University, Karachi, Sindh, PakistanDepartment of Medicine, The Aga Khan University Medical College, Karachi, PakistanDean’s Office, The Aga Khan University, Karachi, PakistanThe Aga Khan University, Karachi, PakistanMedical College, The Aga Khan University, Karachi, PakistanMedical College, The Aga Khan University, Karachi, PakistanDepartment of Medicine, The Aga Khan University Medical College, Karachi, PakistanSection of Neurosurgery, Department of Surgery, The Aga Khan University, Medical College, Karachi, PakistanDepartment of Medicine, The Aga Khan University Medical College, Karachi, PakistanBackground 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 IIIhttps://tsaco.bmj.com/content/10/2/e001690.full |
| spellingShingle | Adil H Haider Maryam Pyar Ali Lakhdir Zainab Samad Noreen Afzal Asma Altaf Hussain Merchant Komal Abdul Rahim Namra Qadeer Shaikh Saad bin Zafar Mahmood Saqib Kamran Bakhshi Mushyada Ali Identifying those at risk: predicting patient factors associated with worse EGS outcomes Trauma Surgery & Acute Care Open |
| title | Identifying those at risk: predicting patient factors associated with worse EGS outcomes |
| title_full | Identifying those at risk: predicting patient factors associated with worse EGS outcomes |
| title_fullStr | Identifying those at risk: predicting patient factors associated with worse EGS outcomes |
| title_full_unstemmed | Identifying those at risk: predicting patient factors associated with worse EGS outcomes |
| title_short | Identifying those at risk: predicting patient factors associated with worse EGS outcomes |
| title_sort | identifying those at risk predicting patient factors associated with worse egs outcomes |
| url | https://tsaco.bmj.com/content/10/2/e001690.full |
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