Phase Angle as a Biomarker for Frailty and Postoperative Mortality: The BICS Study
Bibliographic record
Abstract
Background Phase angle (PA) is a bioimpedance measurement that is determined lean body mass and hydration status. Patients with low PA values are more likely to be frail, sarcopenic, or malnourished. Previous work has shown that low PA predicts adverse outcomes after cardiac surgery, but the effect of PA on survival has not previously been assessed in this setting. Methods and Results The BICS (Bioimpedance in Cardiac Surgery) study recruited 277 patients undergoing major cardiac surgery at 2 university-affiliated hospitals in Montreal, QC, Canada. Bioimpedance measurements as well as frailty and nutritional assessments were performed preoperatively. The primary outcome was all-cause mortality. Secondary outcomes were 30-day mortality, postoperative morbidity, and hospital length of stay. There were 10 deaths at 1 month of follow-up and 16 deaths at 12 months of follow-up. PA was associated with age, sex, body mass index, comorbidities, and frailty, as measured by the Short Physical Performance Battery and Fried scales. After adjusting for Society of Thoracic Surgeons-predicted mortality, lower PA was associated with higher mortality at 1 month (adjusted odds ratio, 3.57 per 1° decrease in PA ; 95% confidence interval, 1.35-9.47) and at 12 months (adjusted odds ratio, 3.03 per 1° decrease in PA ; 95% confidence interval, 1.30-7.09), a higher risk of overall morbidity (adjusted hazard ratio, 2.51 per 1° decrease in PA ; 95% confidence interval, 1.32-4.75), and a longer hospital length of stay (adjusted β, 4.8 days per 1° decrease in PA ; 95% confidence interval, 1.3-8.2 days). Conclusions Low PA is associated with frailty and is predictive of mortality, morbidity, and length of stay after major cardiac surgery. Further work is needed to determine the responsiveness of PA to interventions aimed at reversing frailty.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".