Cytosolic calcium handling signature: integration with clinical predictors enhances prediction of post-operative atrial fibrillation
Bibliographic record
Abstract
BACKGROUND AND AIMS: Atrial fibrillation (AF) is a prevalent complication after cardiac surgery, worsening patient outcomes. Considering the established role of Ca2+-handling abnormalities in AF pathogenesis, this study aimed to evaluate if integrating cytosolic Ca2+-handling measurements with clinical risk factors enhances the risk prediction of post-operative AF. METHODS: Clinical data from 558 patients undergoing cardiac surgery without pre-existing AF from two centres were analysed. From 94 of these patients, atrial cardiomyocytes were isolated from collected right atrial appendages and Ca2+ handling (L-type Ca2+ current, intracellular Ca2+ concentration) was assessed using patch-clamp. The predictive performance of combining both clinical and single-cell Ca2+ handling parameters was tested using sequential feature selection and logistic regression models. RESULTS: Single-cell Ca2+-handling parameters through cluster analysis correlated with post-operative AF development and several cardiac diseases. Integration of Ca2+-handling parameters into a new post-operative AF risk prediction model improved its predictive accuracy by increasing the areas under the receiver operating characteristic (ROC) curves from 0.69 to 0.71 in the training and 0.76 to 0.79 in the validation cohort. Systolic Ca2+ level, along with clinical parameters such as age, left atrial dilatation, valvular heart disease, impaired renal function, and serum magnesium, was identified as an independent risk factor for post-operative AF. Additionally, a predictive score for AF occurrence at discharge and during rehabilitation has been developed, with area under the curve (AUC) values of 0.84 and 0.71, respectively. Incorporating the occurrence of AF during the immediate post-operative period as an additional predictor significantly enhanced the prediction of AF at discharge, achieving an AUC value of 0.94. CONCLUSIONS: Integrating cellular Ca2+ handling signature with clinical predictors improves the prediction of post-operative AF, highlighting the potential of incorporating functional cellular data into clinical risk models.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".