The impact of unexpected intensive care unit admission after cancer surgery on long-term symptom burden among older adults: a population-based longitudinal analysis
Bibliographic record
Abstract
Abstract Background Older adults are at high-risk for a post-operative intensive care unit (ICU) admission, yet little is known about the impact of these admissions on quality of life. The objective of this study was to evaluate the impact of an unexpected post-operative ICU admission on the burden of cancer symptoms among older adults who underwent high-intensity cancer surgery and survived to hospital discharge. Methods We performed a population-based cohort study of older adults (age ≥ 70) who underwent high-intensity cancer surgery and survived to hospital discharge in Ontario, Canada (2007–2017). Using the Edmonton Symptom Assessment System (ESAS), a standardized tool that quantifies patient-reported physical, mental, and emotional symptoms, we described the burden of cancer symptoms during the year after surgery. Total symptom scores ≥ 40 indicated a moderate-to-severe symptom burden. Modified log-Poisson analysis was used to estimate the impact of an unexpected post-operative ICU admission (admission not related to routine monitoring) on the likelihood of experiencing a moderate-to-severe symptom burden during the year after surgery, accounting for potential confounders. We then used multivariable generalized linear mixed models to model symptom trajectories among patients with two or more ESAS assessments. A 10-point difference in total symptom scores was considered clinically significant. Results Among 16,560 patients (mean age 76.5 years; 43.4% female), 1,503 (9.1%) had an unexpected ICU admission. After accounting for baseline characteristics, patients with an unexcepted ICU admission were more likely to experience a moderate-to-severe symptom burden relative to those without an unexpected ICU admission (RR 1.64, 95% CI 1.31–2.05). Specifically, among patients with an unexcepted ICU admission the average probability of experiencing moderate-to-severe symptoms ranged from 6.9% (95 CI 5.8–8.3%) during the first month after surgery to 3.2% (95% CI 0.9–11.7%) at the end of the year. Among the 11,229 (67.8%) patients with multiple ESAS assessments, adjusted differences in total scores between patients with and without an unexpected ICU admission ranged from 2.0 to 5.7-points throughout the year (p < 0.001). Conclusion While unexpected ICU admissions are associated with a small increase in the likelihood of experiencing a moderate-to-severe symptom burden, most patients do not experience a high overall symptom burden during the year after surgery. These findings support the role of aggressive therapy among older adults after major surgery.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".