Characteristics and prognostic implications of pre-shock and normotensive cardiogenic shock in the Critical Care Cardiology Trials Network Registry
Bibliographic record
Abstract
Abstract Background Limited data exist regarding the epidemiology and prognostic implications of pre-shock and normotensive cardiogenic shock (CS) states. Moreover, optimal staging of risk for pts with isolated hypotension versus isolated hypoperfusion remains unclear. Purpose We sought to compare characteristics and outcomes of pre-shock states and normotensive CS as compared with conventional CS. Methods The Critical Care Cardiology Trials Network (CCCTN) is an investigator-initiated multicenter registry of CICUs coordinated by the TIMI Study Group. Consecutive admissions (n=22,869) from 42 centers (2017-2022) were stratified into groups of isolated low CO, isolated hypotension, normotensive CS, and SCAI Stage C CS using criteria in Fig A. Results A total of 1,754 were stratified into one of the four groups: 5% isolated low CO, 9% isolated hypotension, 13% normotensive CS, and 74% SCAI stage C CS. Prior HF was more common in pts w/ isolated low CO (73%) and normotensive CS (60%), compared to pts w/ isolated hypotension (44%) or SCAI stage C CS (55%) (global p<0.001). Overall, in-hospital mortality was 18.4% with marked differences among groups (global p < 0.001; Fig B). Specifically, mortality was significantly lower in those with an isolated low CO or isolated hypotension than among the normotensive CS group (pairwise p [isolated hypotension vs. normotensive CS] = 0.03; Fig B). In contrast, mortality rates among admissions with normotensive CS vs. SCAI stage C CS did not significantly differ (pairwise p=0.08; Fig B). Conclusions Normotensive CS is associated with a >2-fold higher in-hospital mortality compared with isolated hypotension or an isolated low CO state. These findings indicate that the presence of malperfusion, irrespective of hypotension, is associated with worse outcomes in CS. These data may inform refinement of CS staging with respect to pre-shock states.Figure
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".