Red blood cell transfusion in patients with subarachnoid hemorrhage: a multidisciplinary North American survey
Bibliographic record
Abstract
INTRODUCTION: Anemia is associated with poor outcomes in patients with aneurysmal subarachnoid hemorrhage (SAH). It remains unclear whether this association can be modified with more aggressive use of red blood cell (RBC) transfusions. The degree to which restrictive thresholds have been adopted in neurocritical care patients remains unknown. METHODS: We performed a survey of North American academic neurointensivists, vascular neurosurgeons and multidisciplinary intensivists who regularly care for patients with SAH to determine hemoglobin (Hb) concentrations which commonly trigger a decision to initiate transfusion. We also assessed minimum and maximum acceptable Hb goals in the context of a clinical trial and how decision-making is influenced by advanced neurological monitoring, clinician characteristics and patient-specific factors. RESULTS: The survey was sent to 531 clinicians, of whom 282 (53%) responded. In a hypothetical patient with high-grade SAH (WFNS 4), the mean Hb concentration at which clinicians administered RBCs was 8.19 g/dL (95% CI, 8.07 to 8.30 g/dL). Transfusion practices were comparatively more restrictive in patients with low-grade SAH (mean Hb 7.85 g/dL (95% CI, 7.73 to 7.97 g/dL)) (P < 0.0001) and more liberal in patients with delayed cerebral ischemia (DCI) (mean Hb 8.58 g/dL (95% CI, 8.45 to 8.72 g/dL)) (P < 0.0001). In each setting, there was a broad range of opinions. The majority of respondents expressed a willingness to study a restrictive threshold of ≤8 g/dL (92%) and a liberal goal of ≥10 g/dl (75%); in both cases, the preferred transfusion thresholds were significantly higher for patients with DCI (P < 0.0001). Neurosurgeons expressed higher minimum Hb goals than intensivists, especially for patients with high-grade SAH (β = 0.46, P = 0.003), and were more likely to administer two rather than one unit of RBCs (56% vs. 19%; P < 0.0001). Institutional use of transfusion protocols was associated with more restrictive practices. More senior clinicians preferred higher Hb goals in the context of a clinical trial. Respondents were more likely to transfuse patients with brain tissue oxygen tension values <15 mmHg and lactate-to-pyruvate ratios >40. CONCLUSIONS: There is widespread variation in the use of RBC transfusions in SAH patients. Practices are heavily influenced by the specific dynamic clinical characteristics of patients and may be further modified by clinician specialty and seniority, the use of protocols and advanced neurological monitoring.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".