Assessment of the Association Between Lung POCUS Findings During Preoperative Assessment and Cardiopulmonary Outcomes in Patients Undergoing Major Abdominal Surgery: A Pilot Study Protocol
Bibliographic record
Abstract
Abdominal surgeries make up a significant portion of all surgical procedures performed worldwide. Despite advances in surgical techniques, there is significant morbidity and mortality associated with abdominal surgeries. Cardiopulmonary complications in the postoperative period play an important part in the elevated risk associated with these surgeries. Preoperative medical assessments have therefore become the standard of care to evaluate the risk of surgery, optimize a patient's medical conditions, and mitigate the perioperative risk. While there has been increasing utilization of lung point of care ultrasound (POCUS) in the immediate preoperative setting, the use of lung POCUS at the preoperative medical assessment clinic visit has not been studied. While using risk stratification tools is common in current practice, the role of adjunctive office-based techniques like lung POCUS have not been studied in this setting. We conducted an observational prospective pilot study to evaluate the association of lung POCUS findings in the preoperative visit on the risk of adverse cardiopulmonary outcomes in the 30-day postoperative period after major abdominal surgery. A standardized scoring system called integrated lung ultrasound score (iLUS) is used for objective assessment. Our study attempted to determine whether the addition of lung POCUS can be used to better stratify the risk for postoperative complications.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 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".