Clinical utility of routine postoperative serial hemoglobin measurements in patients undergoing radical cystectomy for urothelial carcinoma
Bibliographic record
Abstract
INTRODUCTION: Routine measurements of serum hemoglobin (sHgb) are common after abdominal surgery; however, prolonged measurements may be associated with patient anxiety, increased costs, and longer hospitalization without clinical benefit. The objective of this study was to determine the utility of routine sHgb measurements after radical cystectomy (RC) and factors associated with transfusion of packed red blood cell (pRB C) beyond postoperative day (POD ) 2. METHODS: We retrospectively reviewed patients who underwent RC between 2009 and 2019 at a single academic tertiary care center. The number of sHgb measurements for each patient was examined and pRB C transfusion rates were calculated. Multivariable logistic regression was used to determine factors associated with transfusion beyond POD 2. RESULTS: The median number of sHgb measurements per patient during admission was nine (interquartile range [IQR] 7, 25). Overall, 69/240 (28.7%) patients received a postoperative transfusion, including 46/240 (19.2%) patients receiving a transfusion beyond POD 2. Among patients with a sHgb ≥100 g/L on POD 2, 7/85 (8.2%) went on to receive a transfusion beyond this day compared with 39/155 (25.2%) patients with sHgb <100 g/L. On multivariable analysis, risk factors associated with pRB C transfusion beyond POD 2 included older age, lower sHgb on POD 2, and longer length of stay in hospital. CONCLUSIONS: Transfusion of pRB Cs beyond POD 2 was found to be common; however, patients with sHgb ≥100 g/L on POD 2 were at low risk of requiring subsequent transfusion. Discontinuing further routine sHgb checks in these patients may serve to decrease patient anxiety, healthcare costs, and delays in hospital discharge.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".