Long-term Outcomes Following Emergency General Surgery in Older Adults
Bibliographic record
Abstract
Introduction: Emergency general surgery (EGS) conditions represent a large and growing burden for patients and healthcare systems alike, particularly among older adults (age ≥ 65). While the short-term risks of EGS among older adults have been studied, little is known about long-term functional outcomes in this population. This knowledge gap raises questions about the pursuit of high-intensity EGS care in older adults, limits surgeons’ abilities to counsel patients, and may lead to decision making that is not patient-centred. Methods: We developed a population-based cohort of older adults hospitalized in Ontario from 2006-2016 for one of eight EGS diagnoses. We then matched this cohort to a control group based on demographics and health status and compared long-term function, measured as time spent alive and living at home, between groups over five years. Next, we used a multivariable Cox regression model to determine the association between timely primary care physician (PCP) follow-up after EGS and long-term function. Finally, we used a multistate model to describe the functional trajectories experienced by older adults in the five years following EGS. Results: We identified 105,925 older adults with an EGS admission. While EGS cases experienced less time alive and at home compared to controls (mean 43 vs. 50 months, p<0.001), 57% remained alive and at home after five years. Nonetheless, older EGS patients were at higher risk for nursing home admission or death for at least five years compared to controls (HR 1.17-5.11). Timely follow-up with a PCP was associated with a reduced risk of nursing home admission or death compared to no follow-up (HR 0.87, 95% CI 0.84–0.91). Over the five years following EGS admission, 32% of older adults experienced functional decline requiring new assistance from home care services; functional recovery ranged from 36-43% annually over five years. Conclusions: The majority of older adults have favorable functional outcomes following EGS admission suggesting that high-intensity EGS care should not be withheld based on age alone. Nonetheless, our findings indicate that older adults require long-term supports following EGS to mitigate the risk of functional decline and recover from temporary losses of function when they occur.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".