Erratum: Concordance and limits between transcutaneous and arterial carbon dioxide pressure in emergency department patients with acute respiratory failure: a single-center, prospective, and observational study
Bibliographic record
Abstract
Abstract After publication of this article (Scand J Trauma Resusc Emerg Med 23:40, 2015), it came to light that an earlier version had been published in error. This erratum contains the correct version of the article, which incorporates revisions made in response to reviewer comments. Additionally, one of the authors was inadvertently omitted from the author list. This author, Justin Yan, has been included in the corrected author list above. Background Transcutaneous CO2 (PtCO2) is a continuous and non-invasive measure recommended by scientific societies in the management of respiratory distress. The objective of this study was to evaluate the correlation between PtCO2 and arterial partial pressure of CO2 (PaCO2) by arterial blood gas analysis in emergency patients with dyspnoea, and to determine the factors that interfere with this correlation. Methods From January to June 2014, all adult patients admitted to the RR with dyspnoea during business hours were included in the study if arterial blood gas measurements were indicated. A sensor measuring the PtCO2 was attached to the ear lobe of the patient before the gas analysis. Anamnesis, clinical and laboratory parameters were identified. Results Ninety patients with dyspnoea were included (104 pairs of measurements). The median (IQR) age was 79 years (69 – 85). The correlation between PtCO2 and PaCO2 was R2 =.83 (p<.001) but became lower for values of PaCO2 above 60 mm Hg. The mean bias (± SD) between the two methods of measurement (Bland-Altman analysis) was −1.4 mm Hg (± 7.7) with limits of agreement from −16.4 to 13.7 mm Hg. In univariate analysis, PaO2 interfered with this correlation. After multivariate analysis, temperature (OR = 3.01; 95 % CIs [1.16, 7.80]) and PaO2 (OR = 1.22; 95 % CIs [1.02, 1.47]) significantly interfered with this correlation. Conclusions There is a significant correlation between PaCO2 and PtCO2 values for patients admitted to the emergency department for acute respiratory failure. One limiting factor to routine use of PtCO2 measurements in the emergency department is the presence of hyperthermia.
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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 | 0.006 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".