Point-of-Care Tissue Oxygenation Assessment with SnapshotNIR for Alloplastic and Autologous Breast Reconstruction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: In breast reconstruction, mastectomy and free flaps are susceptible to vascular compromise and tissue necrosis. The SnapshotNIR device (Kent Imaging, Calgary, AB, Canada) utilizes near-infrared spectroscopy to measure tissue oxygen saturation (StO 2 ) and hemoglobin concentration. Here, we report on the use of this device for StO 2 monitoring among patients receiving alloplastic or autologous breast reconstruction. Methods: Patients receiving immediate alloplastic reconstruction after mastectomy or autologous reconstruction were enrolled. Preoperative, intraoperative, and postoperative images were taken of the flaps. StO 2 and hemoglobin were measured at the following locations: superior and inferior breast, free flap skin paddle (when applicable), and un-operated control skin. Linear mixed effects model for repeated measurements was used to model measurements to estimate the area effect difference across time, time effect difference across area, and pairwise comparisons between two areas at each time point. Results: Thirty-two breasts underwent alloplastic reconstruction; 38 breasts underwent autologous reconstruction. No enrollees developed skin necrosis. StO 2 was highest after mastectomy and closure in alloplastic reconstructions. StO 2 was observed to decline at follow-up in autologous reconstructions. Mean preoperative StO 2 was highest in breasts that had previously undergone mastectomy and alloplastic reconstruction. Conclusions: The SnapshotNIR device detected normal spatial and temporal differences in tissue oxygenation over the operative course of alloplastic and autologous breast reconstruction. A multi-institutional, prospective clinical trial is needed to determine the sensitivity and specificity of this device for detecting skin flap necrosis.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it