Utilization of technologies to reduce allogeneic blood transfusion in the United States
Bibliographic record
Abstract
Concern over safety of the blood supply has led to the use of technologies to reduce allogeneic blood transfusion. The objective of this research was to determine the utilization of these technologies in the United States. We evaluated the following techniques: preoperative autologous donation (PAD), cell salvage (CS) and acute normovolemic haemodilution (ANH); and the following pharmaceuticals: aprotinin (APR), epsilon-aminocaproic acid (EACA), tranexamic acid (TXA), desmopressin (DDAVP) and recombinant human erythropoietin (EPO). In 1997, we conducted a cross-sectional mail survey of service chiefs at 1000 US hospitals randomly selected and stratified by status as a provider of open-heart surgery, geographical location and hospital bed size. Sixty-nine per cent (690) of hospitals responded to at least one of the four surveys sent to each hospital. Hospitals reported use of techniques more than pharmaceuticals (P < 0.001); PAD (83%, n = 206) and CS (82% n = 420) were used most frequently. Lack of familiarity was the most common reason cited for infrequent use of pharmaceuticals. Organizational characteristics (e.g. provision of open-heart surgery, size, geographical location, teaching status and type of hospital) were differentially associated with technology use. There is greater use of techniques than pharmaceuticals in US hospitals to reduce the need for allogeneic blood in the peri-operative setting. Providing open-heart surgery is strongly associated with the utilization of these technologies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".