Identifying Predictors of Airway Complications in Conscious Sedation Procedures
Bibliographic record
Abstract
Problem: Conscious sedation procedures are complicated by unanticipated airway compromise and obstruction. The STOP-Bang questionnaire (University of Toronto, 2012) is a validated obstructive sleep apnea (OSA) screening questionnaire used as a pre-procedure evaluation tool to assess a patient’s risk for OSA. There are four verifiable, objective questions and four subjective questions. This study examines to what extent the STOP-Bang score question variables reliably predict airway complications during conscious sedation procedures. Method: The method was a retrospective review of data from the electronic medical record (EMR) of patients who had conscious sedation for endoscopy procedures. The individual questions of the STOP-Bang questionnaire were manually collected as independent predictor variables. Physiologic signs of airway compromise and documented airway maneuvers to relieve airway obstruction were collected as dependent outcome variables. Logistic regression analysis was preformed to predict outcome severity based on individual and total STOP-Bang questionnaire scores. Results: A STOP-Bang threshold score of greater than 5, indicating a high risk for OSA, was determined to be predictive of a heart rate change greater than 10% from baseline during the procedure (p =.021) and periods of apnea of (respiratory rate less than or equal to 8 seconds) (p = .038), indicating airway compromise. The STOP-Bang threshold score of greater than 5 was statistically significantly when correlated to the patient requiring arousal-relieved airway obstruction by verbal or tactile stimulation (p = .023). For the predictor variable of every point of increase in Body Mass Index (BMI), there was a statistically significant correlation with an increase in heart rate during the procedure by 10%, (p = .046), a drop in oxygen saturation as measured by pulse oximetry (SpO2) (p = .002), and periods of apnea (respiratory rate less than or equal to 8) (p = .003). Additionally, for every point of increase in BMI there was 1.212 times the odds of requiring verbal or tactile stimulation to relieve airway obstruction (p = .002). The predictor variable of an STOP-Bang score between 3 and 4, indicating intermediate risk for OSA, was correlated to the development of abnormal CO2 values during the procedure (p = 0.15). Conclusion: With these findings, proactive safety measures can be instituted for additional airway management for identified at-risk patients. This information has application in the clinical consideration of monitoring protocols, medication administration, equipment availability, and staffing for patients with a high probability for airway obstruction during conscious sedation.
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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 | 0.010 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".