Efficacy of intraoperative cell salvage in decreasing perioperative blood transfusion rates in first-time cardiac surgery patients: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Evidence regarding the safety and efficacy of intraoperative cell salvage (ICS) in transfusion reduction during cardiac surgery remains conflicting. We sought to evaluate the impact of routine ICS on outcomes following cardiac surgery. METHODS: We conducted a retrospective analysis of patients who underwent nonemergent, first-time cardiac surgery 18 months before and 18 months after the implementation of routine ICS. Perioperative transfusion rates, postoperative bleeding, clinical and hematological outcomes, and overall cost were examined. We used multivariable logistic regression modelling to determine the risk-adjusted effect of ICS on likelihood of perioperative transfusion. RESULTS: A total of 389 patients formed the final study population (186 undergoing ICS and 203 controls). Patients undergoing ICS had significantly lower perioperative transfusion rates of packed red blood cells (pRBCs; 33.9% v. 45.3% p = 0.021), coagulation products (16.7% v. 32.5% p < 0.001) and any blood product (38.2% v. 52.7%, p = 0.004). Patients receiving ICS had decreased mediastinal drainage at 12 h (mean 320 [range 230-550] mL v. mean 400 [range 260-690] mL, p = 0.011) and increased postoperative hemoglobin (mean 104.7 ± 13.2 g/L v. 95.0 ± 11.9 g/L, p < 0.001). Following adjustment for other baseline and intraoperative covariates, ICS emerged as an independent predictor of lower perioperative transfusion rates of pRBCs (odds ratio [OR] 0.52, 95% confidence interval [CI] 0.31-0.87), coagulation products (OR 0.41, 95% CI 0.24-0.71) and any blood product (OR 0.47, 95% CI 0.29-0.77). Additionally, ICS was associated with a cost benefit of $116 per patient. CONCLUSION: Intraoperative cell salvage could represent a clinically cost-effective way of reducing transfusion rates in patients undergoing cardiac surgery. Further research on systematic ICS is required before recommending it for routine use.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.000 | 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".