Clinical trial · Observational
Predictive Time-to-Event Model for Major Medical Complications After Colectomy
Development and Internal Validation of Models to Predict Time-to-event for Major Medical Complications Within 30-days After Planned Colectomy: a Retrospective Population Cohort Study
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Purpose: The purpose of this study is to create prediction models for when major complications occur after elective colectomy surgery. Justification: After surgery, patients can have multiple complications. Accurate risk prediction after surgery is important for determining an appropriate level of monitoring and facilitating patient recovery at home. Objectives: Investigators aim to develop and internally validate prediction models to predict time-to-complication for each individual major medical complications (pneumonia, myocardial infarction (MI) (i.e. heart attacks), cerebral vascular event (CVA) (i.e. stroke), venous thromboembolism (VTE) (i.e. clots), acute renal failure (ARF) (i.e. kidney failure), and sepsis (i.e. severe infections)) or adverse outcomes (mortality, readmission) within 30-days after elective colectomy. Data analysis: Investigators will be analyzing a data set provided by the National Surgical Quality Improvement Program (NSQIP). Descriptive statistics will be performed. Cox proportional hazard and machine learning models will be created for each complication and outcome outlined in "Objectives". The performances of the models will be assessed and compared to each other.
Conditions
Conditions (6)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Colectomy | — | UNRESOLVED | — |
| Colorectal Cancer | Malignant Colorectal Neoplasm | CURATED_BROADER | 0.80 |
| Complications, Postoperative | — | UNRESOLVED | — |
| Diverticulitis | — | UNRESOLVED | — |
| Inflammatory Bowel Diseases | — | UNRESOLVED | — |
| Predictive Model | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| No Intervention | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- label
- Entire Cohort
- description
- Patients undergoing elective colectomy with data that has been collected in the NSQIP® Procedure Targeted Colectomy dataset from 2014-2019 with American Society of Anesthesiologists (ASA) Physical Status I-IV. Patients will not be included in this cohort with urgent or emergency colectomy or indication for colectomy consisting of "Acute diverticulitis", "Enterocolitis (e.g. C. Difficile)", and "Volvulus", patients with disseminated cancer, wound infection, systemic sepsis or ventilator-dependence preoperatively.
- interventionNames
- Other: No Intervention
Primary outcomes (6)
- measure
- Pneumonia
- timeFrame
- Within 30 days post-operatively
- description
- Occurrence of pneumonia within 30 days post-operatively.
- measure
- Myocardial Infarction (MI)
- timeFrame
- Within 30 days post-operatively
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * undergoing elective colectomy * data has been collected in the NSQIP® Procedure Targeted Colectomy dataset from 2014-2019 Exclusion Criteria: * American Society of Anesthesiologists (ASA) Physical Status (PS) V (defined as "5-Moribund") (ASA PS 6 - organ donation is not included within NSQIP) * undergoing urgent or emergency surgery * indication for colectomy consisting of "Acute diverticulitis", "Enterocolitis (e.g. C. Difficile)", and "Volvulus" due to the non-elective nature of these pathologies * patient with disseminated cancer * wound infection (i.e. potentially recent surgery) * systemic sepsis * ventilator-dependence preoperatively
References
Publications (6)
- BACKGROUNDMorris MS, Deierhoi RJ, Richman JS, Altom LK, Hawn MT. The relationship between timing of surgical complications and hospital readmission. JAMA Surg. 2014 Apr;149(4):348-54. doi: 10.1001/jamasurg.2013.4064. PMID 24522747
- BACKGROUNDScarborough JE, Schumacher J, Kent KC, Heise CP, Greenberg CC. Associations of Specific Postoperative Complications With Outcomes After Elective Colon Resection: A Procedure-Targeted Approach Toward Surgical Quality Improvement. JAMA Surg. 2017 Feb 15;152(2):e164681. doi: 10.1001/jamasurg.2016.4681. Epub 2017 Feb 15. PMID 27926773
- BACKGROUNDThompson JS, Baxter BT, Allison JG, Johnson FE, Lee KK, Park WY. Temporal patterns of postoperative complications. Arch Surg. 2003 Jun;138(6):596-602; discussion 602-3. doi: 10.1001/archsurg.138.6.596. PMID 12799329
- BACKGROUNDLuo W, Phung D, Tran T, Gupta S, Rana S, Karmakar C, Shilton A, Yearwood J, Dimitrova N, Ho TB, Venkatesh S, Berk M. Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View. J Med Internet Res. 2016 Dec 16;18(12):e323. doi: 10.2196/jmir.5870. PMID 27986644
- BACKGROUNDRiley RD, Snell KI, Ensor J, Burke DL, Harrell FE Jr, Moons KG, Collins GS. Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes. Stat Med. 2019 Mar 30;38(7):1276-1296. doi: 10.1002/sim.7992. Epub 2018 Oct 24. PMID 30357870
- DERIVEDKe JXC, Jen TTH, Gao S, Ngo L, Wu L, Flexman AM, Schwarz SKW, Brown CJ, Gorges M. Development and internal validation of time-to-event risk prediction models for major medical complications within 30 days after elective colectomy. PLoS One. 2024 Dec 2;19(12):e0314526. doi: 10.1371/journal.pone.0314526. eCollection 2024. PMID 39621640