Airway management in the presence of cervical spine instability: A cross-sectional survey of the members of the Indian Society of Neuroanaesthesiology and Critical Care
Bibliographic record
Abstract
Background and Aims: There is a paucity of clinical practice guidelines for the ideal approach to airway management in patients with cervical spine instability (CSI). The aim of this survey was to evaluate preferences, perceptions and practices regarding airway management in patients with CSI among neuroanaesthesiologists practicing in India. Methods: A 25-item questionnaire was circulated for cross-sectional survey to 378 members of the Indian Society of Neuroanaesthesiology and Critical Care (ISNACC) by E-mail. We sent four reminders and again submitted our survey to non-responders during the 2017 annual ISNACC meeting. Apart from demographic information, the survey captured preferred methods of intubation and airway management for patients with CSI and their justification. Regression analysis was used to identify factors associated with the use of indirect technique for intubation. Results: Only 122 out of the 378 anaesthesiologists responded to our survey. Most respondents were senior consultants, working in training hospitals, and performed ≥25 intubations per year for CSI patients. The majority of neuroanaesthesiologists (78.7%; n = 96) preferred indirect techniques for elective intubation. However, 45 anaesthesiologists (36.9%) preferred indirect techniques for emergency intubation. In an adjusted analysis, preference for patients to be conscious during intubation was significantly associated with the use of indirect techniques (odds ratio = 3.79; confidence interval = 1.52–9.49, P < 0.01). Conclusions: Among ISNACC members, indirect techniques are preferred for elective intubation of patients with CSI, while direct laryngoscopy is preferred for emergency intubation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".