Dobutamine and Goal-Directed Fluid Therapy for Improving Tissue Oxygenation in Deep Inferior Epigastric Perforator (DIEP) Flap Breast Reconstruction Surgery: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Breast reconstruction is an integral part of breast cancer care. There are 2 main types of breast reconstruction: alloplastic (using implants) and autologous (using the patient's own tissue). The latter creates a more natural breast mound and avoids the long-term need for surgical revision-more often associated with implant-based surgery. The deep inferior epigastric perforator (DIEP) flap is considered the gold standard approach in autologous breast reconstruction. However, complications do occur with DIEP flap surgery and can stem from poor flap tissue perfusion/oxygenation. Hence, the development of strategies to enhance flap perfusion (eg, goal-directed perioperative fluid therapy) is essential. Current perioperative fluid therapy is traditionally guided by subjective criteria, which leads to wide variations in clinical practice. OBJECTIVE: The main objective of this trial is to determine whether the use of minimally invasive cardiac output (CO) monitoring for guiding intravenous fluid administration, combined with low-dose dobutamine infusion (via a treatment algorithm), will increase tissue oxygenation in patients undergoing DIEP flap surgery. METHODS: With appropriate institutional ethics board and Health Canada approval, patients undergoing DIEP flap surgery are randomly assigned to receive CO monitoring for the guidance of intraoperative fluid therapy in addition to a low-dose dobutamine infusion (which potentially improves flap oxygenation) versus the current standard of care. The primary outcome is tissue oxygenation measured via near-infrared spectroscopy at the perfusion zone furthest from the perforator vessels 45 minutes after vascular reanastomosis of the DIEP flap. Low dose (2.5 μg/kg/hr) dobutamine infusion continues for up to 4 hours postoperatively, provided there are no associated complications (ie, persistent tachycardia). Flap oxygenation, hemodynamic parameters, and any medication-associated side effects/complications are monitored for up to 48 hours postoperatively. Complications, rehospitalizations, and patient satisfaction are also collected until 30 days postoperatively. RESULTS: Funding and regulatory approvals were obtained in 2019, but the study recruitment was interrupted by the COVID-19 pandemic. As of October 4, 2023, 34 participants have been recruited. Because of the significant delays associated with the pandemic, the expected completion date was extended. We expect the study to be completed and ready for potential news release (as appropriate) and publication by July 2024. No patients have suffered any adverse effects/complications from participating in this study, and none have been lost to follow-up. CONCLUSIONS: CO-directed fluid therapy in combination with a low-dose dobutamine infusion via a treatment algorithm has the potential to improve DIEP flap tissue oxygenation and reduce complications following DIEP flap breast reconstruction surgery. However, given that the investigators remain blinded to group randomization, no comment can be made regarding the efficacy of this intervention for improving tissue oxygenation at this time. Nevertheless, no patients have been withdrawn for safety concerns thus far, and compliance remains high. TRIAL REGISTRATION: Clinicaltrials.gov NCT04020172; https://clinicaltrials.gov/study/NCT04020172.
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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 | 0.019 | 0.021 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.057 | 0.008 |
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".