Prognostic Value of Right Atrial Pressure-Corrected Cardiac Power Index in Cardiogenic Shock
Bibliographic record
Abstract
Abstract Aim The pulmonary artery catheter (PAC)-derived cardiac power index (CPI) has been found of prognostic value in cardiogenic shock (CS) patients. The original CPI equation included the right atrial pressure (RAP), accounting for heart filling pressure as a determinant of systolic myocardial work, but this term was subsequently omitted. We hypothesized that the original CPI formula (CPIRAP) is superior to current CPI for risk stratification in CS. Methods and results A single-centre cohort of 80 consecutive Society for Cardiovascular Angiography and Interventions (SCAI) B-D CS patients with available PAC records was included. Overall in-hospital mortality was 21.3%. Results showed CPIRAP to be the strongest haemodynamic predictor of in-hospital death (padj = 0.038), outperforming CPI [area under the receiver operating characteristic (ROC) curves: 0.726 and 0.673, P-for-difference = 0.025]. When the population was stratified according to the identified CPIRAP (0.28 W/m2) and accepted CPI (0.32 W/m2) thresholds, the cohort with discordant indexes (low CPIRAP and high CPI) comprised a group of 13 patients featuring a congested phenotype with frequent right ventricle or biventricular involvement. In this group, in-hospital mortality was high (30.8%) similar to those with concordant low CPI and CPIRAP. Conclusion Incorporating RAP in CPI calculation (CPIRAP) improves the prognostic yield in patients with CS SCAI B-D. A cut-off of 0.28 W/m2 identifies patients at higher risk of in-hospital mortality. The improved prognostic value of CPIRAP may derive from identification of patients with more intravascular congestion who may experience substantial in-hospital mortality, uncaptured by the commonly used CPI equation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".