A Survey of Intubation of COVID-19 Patients in the Critical Care Units to Assess Adherence to Guidelines and Critical Events Encountered
Bibliographic record
Abstract
Background: The Coronavirus disease (COVID-19) pandemic affected the health care personnel with the worse outcome as compared to the general population.Anaesthesiologists,being the first responders in critical care units (ICU) for aerosol-generating procedures like endotracheal intubation are at higher risk of getting infected with the virus.The updated SARS guideline (Severe Acute Respiratory Syndrome) of the 2003 epidemic in Toronto, Canada, is quite instructive for endotracheal intubation. This study was intended with the primary objective to find out the adherence of guidelines among the anaesthesiologists while doing endotracheal intubation and the secondary objective is to assess the incidence of other critical events. Methods: This survey was conducted in a tertiary care centre among the anaesthesiologists about their first COVID-19 patient intubation,based on a 40-point questionnaire about adherence of guidelines and critical event encountered. All the responses collected in google form which was further evaluated with the help of SPSS-17. Results: Total of 112 patients intubated in the ICU, out of which 62% were emergency intubation, aerosol boxes used while intubation in 20% cases. Hand hygiene before the procedure was not followed in 25% and no gowns used while doing the procedure was recorded in 34% respondents. Clamping ET tube and use of hydrophobic filter was missed in 15% and 22% cases. The surroundings contaminated in 51% of respondents. Hypoxia, hypotension, arrhythmia, hypertension, cardiac arrest and aspiration during intubation was observed in 58%, 62%, 29%, 21%, 22%, 11% cases respectively. Conclusion: With the anaesthesiologists getting adapted to the new norms of intubation in COVID days, the adherence to guidelines is suboptimal, and the complication rate was high during the first intubation attempts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".