Unrecognised benefit of oesophageal doppler monitoring
Bibliographic record
Abstract
We report a previously unrecognised benefit of using oesophageal doppler monitoring, that of an early warning system for major oesophageal reflux. We anaesthetised a fit young woman for an emergency laparotomy for sub-acute intestinal obstruction. Following rapid sequence induction, the patient’s trachea was intubated and a large bore nasogastric tube was inserted. Oesophageal doppler monitoring (Deltex Medical, Chichester, UK) was instituted to guide fluid resuscitation. Intra-operatively, the surgeon informed us that he was manually moving the obstructed bowel contents proximally towards the stomach. We placed a Yankauer sucker in the nasogastric tube port but could aspirate nothing. The surgeon continued to massage the bowel contents proximally. Suddenly the noise signal from the oesophageal doppler monitoring changed. The distinctive beat to beat sound was overcome with ‘white noise’. The change in the graphical display was very distinctive as well (Fig. 3). We deduced that this must represent gastric secretions refluxing to the level of the doppler probe. We promptly placed the suction in the patient’s oropharynx and approximately 5 s later proceeded to aspirate 1800 ml of faeculent gastric contents. Distinctive change in waveform morphology with massive oesophageal reflux. The patient benefited from our observation in two ways. Firstly, prompt recognition of faeculent gastric secretions in the oropharynx and their immediate removal almost certainly reduced the chance of significant tracheal soiling. Gastro-oesophageal reflux has an incidence of 16–47% in elective surgery [1]. Blunt et al. [2] showed that endotracheal cuff leakage of supraglottic secretions can occur in 11% of patients. This can increase to 83% if the cuff is not lubricated properly. Secondly, timely detection of the reflux prevented an overflow situation in which the faeculent fluid could have contaminated the patients’ mouth, nose, ears, eyes, hair, neck, adjacent IV lines, and bedding. We are not advocating routine use of oesophageal doppler monitoring to detect gastro-oesophageal reflux. However, when present, oesophageal doppler monitoring may provide an early warning of significant gastro-oesophageal reflux, even when an alert anaesthetist is aware that this is highly likely during such a manoeuvre.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".