Bibliographic record
Abstract
To the Editor: In their survey of Canadian anesthesiologists’ preferred interventions after failed intubation and the more critical “cannot intubate–cannot ventilate” (CICV) situation, Wong et al. (1) indicate that only 57% of respondents had ever encountered the CICV scenario in their practice. This is not surprising, given the (fortunate) rarity of this event, with an estimated frequency of <0.1% (2–4). However, as an anesthesiologist who has (unfortunately) actually experienced such an emergency several years ago, I found the design of this survey perplexing. The authors solicited responses to two hypothetical clinical scenarios: 1) failed intubation with adequate mask ventilation, and 2) CICV in a critically hypoxic patient. Only in the first scenario was the use of an intubating laryngeal mask airway (LMA) an option. In the second circumstance, the authors specifically eliminated the option of an LMA by asking respondents to choose among various infraglottic (invasive) devices for securing the airway. Not surprisingly, fewer than 10% of respondents had any clinical experience with these techniques. In the CICV emergency that I experienced, neither an experienced nurse anesthetist nor I could intubate or ventilate the airway of an elderly patient requiring emergency laparotomy. Based on history and preoperative examination, we did not suspect a difficult airway despite the fact that the patient had, coincidentally, a large, vascular goiter with a palpable thrill. However, with the patient exhibiting rapidly worsening hypoxemia after our failure to intubate or ventilate her airway, it was abundantly clear that attempting to restore gas exchange by use of an invasive transtracheal device was not an option, as it would likely have resulted in severe hemorrhage. Fortunately, all anesthesia machines in our operating suite were equipped with #4 LMAs specifically intended for unanticipated emergencies; in my patient’s case, its use proved lifesaving. Such an experience remains permanently etched in one’s professional memory, and thus it seems to me particularly odd that in the portion of a survey designed to assess anesthesiologists’ responses to the CICV emergency, the LMA (intubating or standard) was not offered as an option. With adequate experience, failed LMA placement is a very rare event. Moreover, its use as a critical rescue device in airway emergencies has been so widely accepted that the American Society of Anesthesiologists modified its original Practice Guidelines for Management of the Difficult Airway to include the use of the LMA as a first response to the CICV situation (5–7). Perhaps Wong et al. assumed that the critical importance of the LMA in the CICV scenario is so implicit that it is not necessary to include it as an option in a survey of anesthesiologists’ responses to this exigency. However, given its acceptance as a critical rescue device and my own personal experience as described, this absence seems a perplexing oversight. Robert F. Atkins, MD Department of Anesthesiology Abington Memorial Hospital Abington, PA [email protected]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".