Disseminated Intravascular Coagulation Score Is Related to Short-term Mortality in Patients Undergoing Venoarterial Extracorporeal Membrane Oxygenation After Cardiac Surgery
Bibliographic record
Abstract
Disseminated intravascular coagulation (DIC) score is associated with short-term mortality in various conditions but has not been studied in postcardiotomy cardiogenic shock (PCS) patients supported with venoarterial extracorporeal membrane oxygenation (VA-ECMO). The objective of this study was to evaluate the relationship between DIC score at day 1 from VA-ECMO initiation and short-term mortality. We included all PCS patients supported with VA-ECMO at the Beijing Anzhen Hospital between January 2015 and December 2018. Multivariable logistic regression analysis was performed to assess the relationship between DIC score at day 1 and in-hospital mortality, and adjust for potential confounding variables. Of 222 PCS patients treated with VA-ECMO, 145 (65%) patients were weaned from VA-ECMO, and median (IQR) ECMO support duration was five (3-6) days. In-hospital mortality was 53%. The median (IQR) DIC score at day 1 was five (4-6). Patients with DIC score ≥5 at day 1 (overt DIC) had higher in-hospital mortality as compared with patients with DIC score <5 (64% vs. 22%; P < 0.001). After adjusting for age, sex, ECMO indication, and peak serum lactate, a one-point rise in DIC score [OR, 2.20; 95% confidence intervals (CI), 1.64-2.95] or DIC score ≥5 at day 1 (OR, 4.98; 95% CI, 2.42-10.24) was associated with an increased risk of in-hospital mortality. The area under the receiver operating characteristic curve for DIC score at day 1 was 0.76 (95% CI, 0.69-0.82). Our study suggests that DIC score at day 1 is associated with short-term mortality in patients undergoing VA-ECMO after cardiac surgery, independent of age, sex, disease characteristics, and severity of illness.
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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 | 0.003 |
| 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 | 0.000 |
| 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".