Elevated Resting Heart Rate Is an Independent Risk Factor for Mortality in Patients with Colorectal Cancer: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Although lifestyle factors are associated with resting heart rate (RHR), its association with mortality in patients with colorectal cancer has not been fully understood. Therefore, we sought to determine whether RHR is associated with all-cause and colorectal cancer-specific mortality in patients with stage I to III colorectal cancer. METHODS: We included a total of 3,631 patients from the Severance Hospital Colorectal Cancer Registry (Seoul, South Korea) who underwent surgery for stage I to III colorectal cancer. RHR data were collected on the day of surgery. We utilized multivariable Cox proportional hazards models to estimate HRs and 95% confidence intervals (CI) for the association between RHR and all-cause and colorectal cancer-specific mortality. RESULTS: During a median follow-up of 3.0 years, there were 292 all-cause and 177 colorectal cancer-specific deaths. Patients in the highest quintile of RHR [≥88 beats per minute (bpm)] versus patients in the lowest quintile of RHR (≤66 bpm) showed a 3.33-fold increased risk of all-cause mortality (95% CI, 1.85-5.99) and a 2.98-fold increased risk of colorectal cancer-specific mortality (95% CI, 1.72-5.16). For every 10-bpm increase in RHR, there was a 1.44-fold increase in all-cause mortality (95% CI, 1.32-1.58) and a 1.50-fold increase in colorectal cancer-specific mortality (95% CI, 1.33-1.69). CONCLUSIONS: Elevated RHR on the day of surgery for colorectal cancer is associated with a higher risk of all-cause/colorectal cancer-specific mortality. IMPACT: Our data suggest that RHR may serve as a clinically relevant predictor of mortality in patients who undergo surgery for colorectal cancer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".