Impact of Hemoglobin Levels on Composite Cardiac Arrest or Stroke Outcome in Patients With Respiratory Failure Due to COVID-19
Bibliographic record
Abstract
OBJECTIVES: Anemia has been associated with an increased risk of both cardiac arrest and stroke, frequent complications of COVID-19. The effect of hemoglobin level at ICU admission on a composite outcome of cardiac arrest or stroke in an international cohort of COVID-19 patients was investigated. DESIGN: Retrospective analysis of prospectively collected database. SETTING: A registry of COVID-19 patients admitted to ICUs at over 370 international sites was reviewed for patients diagnosed with cardiac arrest or stroke up to 30 days after ICU admission. Anemia was defined as: normal (hemoglobin ≥ 12.0 g/dL for women, ≥ 13.5 g/dL for men), mild (hemoglobin 10.0-11.9 g/dL for women, 10.0-13.4 g/dL for men), moderate (hemoglobin ≥ 8.0 and < 10.0 g/dL for women and men), and severe (hemoglobin < 8.0 g/dL for women and men). PATIENTS: Patients older than 18 years with acute COVID-19 infection in the ICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 6926 patients (median age = 59 yr, male = 65%), 760 patients (11.0%) experienced stroke (2.0%) and/or cardiac arrest (9.4%). Cardiac arrest or stroke was more common in patients with low hemoglobin, occurring in 12.8% of patients with normal hemoglobin, 13.3% of patients with mild anemia, and 16.7% of patients with moderate/severe anemia. Time to stroke or cardiac arrest by anemia status was analyzed using Cox proportional hazards regression with death as a competing risk. Covariates selected through clinical knowledge were age, sex, comorbidities (diabetes, hypertension, obesity, and cardiac or neurologic conditions), pandemic era, country income, mechanical ventilation, and extracorporeal membrane oxygenation. Moderate/severe anemia was associated with a higher risk of cardiac arrest or stroke (hazard ratio, 1.32; 95% CI, 1.05-1.67). CONCLUSIONS: In an international registry of ICU patients with COVID-19, moderate/severe anemia was associated with increased hazard of cardiac arrest or stroke.
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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 | 0.000 | 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 | 0.000 |
| 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".