Prognostic Factors Associated with Mortality in Cardiogenic Shock — A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Cardiogenic shock remains highly associated with early mortality, with mortality often exceeding 50%. We sought to determine the association between prognostic factors and in-hospital and 30-day mortality in cardiogenic shock. METHODS: We performed a systematic review and meta-analysis of prognostic factors in cardiogenic shock, searching MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials for records up to June 5, 2023. English-language studies that investigated prognostic factors and in-hospital and/or 30-day mortality in cardiogenic shock were included. Studies were excluded if they evaluated the pediatric population, were postmortem studies, or included fewer than 100 patients. The primary aim was to identify modifiable and non-modifiable prognostic factors associated with in-hospital and 30-day mortality in cardiogenic shock. RESULTS: We identified 160 studies, including 2,459,703 patients with a median in-hospital mortality of 41.4% (interquartile range, 33.6% to 49.2%). The majority were retrospective cohort studies. Patient factors potentially associated with an increase in early mortality included an age greater than or equal to 75 years of age, peripheral arterial disease, chronic kidney disease, and female sex. Procedural and presentation factors potentially associated with increased mortality included out-of-hospital cardiac arrest, left main culprit artery, left ventricular ejection fraction less than 30%, dialysis, and need for mechanical circulatory support. Revascularization in the form of coronary artery bypass graft and percutaneous coronary intervention were potentially associated with reduced in-hospital mortality. CONCLUSIONS: This analysis quantifies the association between patient, presentation, and treatment-related factors and early mortality in cardiogenic shock. Increased certainty in the association of these prognostic factors with cardiogenic shock outcomes can aid in clinical risk assessment, development of risk tools, and analysis of clinical trials.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.031 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".