A Paradigm Shift in Critical Care Infrastructure in Complex Settings: Evaluating an Ultraportable Operating Room to Improve Field Surgical Safety
Bibliographic record
Abstract
INTRODUCTION: Scarcity of operating rooms and personal protective equipment in far-forward field settings make surgical infections a potential concern for combat mortality and morbidity. Surgical and transport personnel also face infectious risks from bodily fluid exposures. Our study aimed to describe the serial, proof-of-concept testing of the SurgiBox technology: an inflatable sterile environment that addresses the aforementioned problems, fits on gurneys and backpacks, and drapes over incisions. MATERIALS AND METHODS: The SurgiBox environmental control unit and inflatable enclosure were optimized over five generations based on iterative feedback from stakeholders experienced in surgery in austere settings. The airflow system was developed by analytic modeling, verified through in silico modeling in SOLIDWORKS, and confirmed with prototype smoke-trail checking. Particulate counts evaluated the enclosure's ability to control and mitigate users' exposures to potentially infectious contaminants from the surgical field in various settings. SurgiBox enclosures were setup over a mannequin's torso, in a configuration and position for either thoracic or abdominal surgery. A particle counter was serially positioned in sternotomy and laparotomy positions, as well as bilateral flank positions. This setup was repeated with open ports exposing the enclosure to the external environment. To simulate stress scenarios, sampling was repeated with enclosure measurements during an increase in external particulate concentration. RESULTS: The airflow technology effectively kept contaminants away from the incision and maintained a pressure differential to reduce particle entry. Benchtop testing demonstrated that even when ports were opened or the external environment had high contaminant burden, the enclosed surgical field consistently registered 0 particle count in all positions. Time from kit opening to incision averaged 54.5 seconds, with the rate-limiting step being connecting the environmental control unit to the enclosure. The portable kit weighted 5.9 lbs. CONCLUSIONS: Analytic, in silico, and mechanical airflow modeling and benchtop testing have helped to quantify the SurgiBox system's reliability in creating and maintaining an operating room-quality surgical field within the enclosure as well as protecting the surgical team outside the enclosure. More recent and ongoing work has focused on specifying optimal use settings in the casualty chain of care, expanding support for circumferential procedures, automating airflow control, and accelerating system setup. SurgiBox's ultimate goal is to take timely, safe surgery to patients in even the most austere of settings.
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How this classification was reachedexpand
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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".