Preoperative hemoglobin and perioperative blood transfusion in major head and neck surgery: A systematic review and meta-analysis
Bibliographic record
Abstract
Background There is a growing concern with inappropriate, excessive perioperative blood transfusions. Understanding the influence of low preoperative hemoglobin (Hgb) on perioperative blood transfusion (PBT) in head and neck cancer (HNC) surgery with free flap reconstruction may help guide clinical practice to reduce inappropriate treatment among these patients. The objective is to synthesize evidence regarding the association between preoperative Hgb and PBT among major HNC free flap surgeries. Methods Terms and synonyms for HNC surgical procedures, Hgb and PBT were used to search MEDLINE, Embase, CINAHL, Cochrane Central Register of Controlled Trials and Cochrane Database of Reviews from inception to February 2020. Reference lists of included full texts and studies reporting the preoperative Hgb, anemia or hematocrit (exposure) and the PBT (outcome) in major HNC surgery with free flap reconstruction were eligible. Studies examining esophageal, thyroid and parathyroid neoplasms were excluded; as were case reports, case series (n < 20), editorials, reviews, perspectives, viewpoints and responses. Two independent, blinded reviewers screened titles, abstracts and full texts in duplicate. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses was followed. A random-effects model was used to pool reported data. The primary outcome was the proportion of patients who had a PBT. Subgroup analysis examined sources of heterogeneity for perioperative predictors of PBT (age, sex, flap type, flap site and preoperative Hgb). We also examined mean preoperative Hgb in the PBT and no PBT groups. Results Patients with low preoperative Hgb were transfused more than those with normal Hgb (47.62%, 95% CI = 41.19–54.06, I 2 = 0.00% and 13.92%, 95% CI = 10.19–17.65, I 2 = 20.69%, respectively). None of the predictor variables explained PBT. The overall pooled mean preoperative Hgb was 12.96 g/dL (95% CI = 11.33–14.59, I 2 = 0.00%) and was 13.58 g/dL (95% CI = 11.95–15.21, I 2 = 0.00%) in the no PBT group and 12.05 g/dL (95% CI = 10.01 to 14.09, I 2 = 0.00%) in the PBT group. Conclusions The heterogeneity between studies, especially around the trigger for PBT, highlights the need for additional research to guide clinical practice of preoperative Hgb related to PBT to enhance patient outcomes and improve healthcare stewardship. Graphical Abstract
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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 | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.031 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".