Lactate and carbon monoxide poisoning
Bibliographic record
Abstract
We read with interest the study by Dogan et al. and question the authors’ interpretation. The study’s primary outcome is to determine whether serum lactate correlates with hyperbaric oxygen (HBO) therapy. The main rationale for HBO in carbon monoxide (CO) poisoning is to reduce the risk of delayed neurologic sequelae. However, HBO is a treatment modality and not a measurable clinical outcome. The decision to initiate HBO is dependent on multiple factors, and administration of HBO does not necessarily indicate more severe poisoning. Furthermore, the authors state, ‘‘a lactate value greater than 1.85 mmol/L predicts the need for HBO.’’ We find this problematic when the normal range for serum lactate is below 2.1 mmol/L. It is concerning to state that a normal laboratory result should be an indication of severity of disease as well as a trigger to initiate HBO. In this study, a lactate value of 1 mmol/L has a negative predictive value of 96.3%. This negative predictive value does not predict disease severity but rather whether HBO was initiated. While patients with low lactate values are less likely to have significant COrelated symptoms (e.g. neurologic impairment, altered mental status, ischemic symptoms, and hemodynamic instability), a patient who has these clinical findings would be considered severely CO poisoned despite the normal serum lactate. We commend the authors’ efforts in this study. However, we believe it is premature to utilize the lactate level as a marker of CO poisoning based on this study.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".