Examining the utility of routine perioperative hemoglobin monitoring in patients undergoing radical nephrectomy
Bibliographic record
Abstract
INTRODUCTION: Patients undergoing radical nephrectomy (RN) are often admitted with protocolized bloodwork for several days following their operation, yet the clinical value of serial hemoglobin (Hgb) measurements has not been established. This can lead to unnecessary costs and can prolong patient stay, despite the absence of an intervention based on these lab values. This study sought to examine perioperative Hgb values and identify those patients at high risk of bleeding requiring intervention, as well as those patients who are unlikely to require further monitoring. METHODS: Patient and perioperative factors were retrospectively examined for a cohort of 259 radical nephrectomy patients from 2015-2021 in Atlantic Canada. Postoperative Hgb values and transfusion rates were recorded. A multivariate logistic regression analysis was performed to identify variables associated with requiring a blood transfusion. RESULTS: Overall, 31 (12%) patients required a blood transfusion in the postoperative period. Median estimated blood loss (EBL) was 150 (interquartile range [IQR] 100-300) ml, with a median Hgb change of 15 (IQR 9-22) g/L from preoperative to postoperative day 1 (POD1). In patients with a Hgb loss of ≤15 g/L (n=131), transfusion was only required in four patients (3.1%). Among those with a POD1 Hgb >100 g/L (n=199), only four (2%) required transfusion. These patients were identified as having complications based on hemodynamic instability. On multivariate regression analysis, factors found to be associated with higher transfusion risk were age and intraoperative EBL, while higher preoperative Hgb was found to be associated with a lower transfusion risk. CONCLUSIONS: In patients who have a reassuring POD1 Hgb value, with a drop of <15 g/L or an absolute value of >100 g/L, consideration can be made towards discontinuing routine Hgb testing in the absence of a clinical indication. Age, blood loss, and preoperative Hgb are factors that may affect a patient's overall risk of transfusion.
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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 | 0.004 |
| 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".