Renal Insufficiency and Early Bystander CPR Predict In-Hospital Outcomes in Cardiac Arrest Patients Undergoing Mild Therapeutic Hypothermia and Cardiac Catheterization: Return of Spontaneous Circulation, Cooling, and Catheterization Registry (ROSCCC Registry)
Bibliographic record
Abstract
Objective. Out of hospital cardiac arrest (OHCA) patients are a critically ill patient population with high mortality. Combining mild therapeutic hypothermia (MTH) with early coronary intervention may improve outcomes in this population. The aim of this study was to evaluate predictors of mortality in OHCA patients undergoing MTH with and without cardiac catheterization. Design. A retrospective cohort of OHCA patients who underwent MTH with catheterization (MTH + C) and without catheterization (MTH + NC) between 2006 and 2011 was analyzed at a single tertiary care centre. Predictors of in-hospital mortality and neurologic outcome were determined. Results. The study population included 176 patients who underwent MTH for OHCA. A total of 66 patients underwent cardiac catheterization (MTH + C) and 110 patients did not undergo cardiac catheterization (MTH + NC). Immediate bystander CPR occurred in approximately half of the total population. In the MTH + C and MTH + NC groups, the in-hospital mortality was 48% and 78%, respectively. The only independent predictor of in-hospital mortality for patients with MTH + C, after multivariate analysis, was baseline renal insufficiency (OR = 8.2, 95% CI 1.8-47.1, and p = 0.009). Conclusion. Despite early cardiac catheterization, renal insufficiency and the absence of immediate CPR are potent predictors of death and poor neurologic outcome in patients with OHCA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".