Rebuttal from Gerard F. Curley, John G. Laffey and Brian P. Kavanagh
Bibliographic record
Abstract
Beitler et al.'s (2013) review of the benefits and mechanisms of avoiding high tidal volume are right on the mark. In addition, they provide a sound biophysical basis for our concern about increasing respiratory rate to offset hypercapnic acidosis (HCA). However, the parallels drawn from other clinical contexts are problematic. For example, the trial of intravenous salbutamol for acute lung injury – stopped early due to harm – is a poor choice. Key concerns regarding salbutamol in that study are rare with moderate hypercapnia such as arrhythmia (Amato et al. 1998; Stewart et al. 1998; Brower et al. 1999), lactic acidosis (hypercapnia reduces it) (Higgins et al. 2009), and impaired oxygen supply–demand balance (hypercapnia improves it) (Wang et al. 2008). Likewise, HCA may certainly worsen pulmonary hypertension, and potentially the outcome; however, it attenuates a key antecedent of pulmonary hypertension, namely oxidant stress (Kantores et al. 2006). Elevated pulmonary vascular pressure in acute respiratory distress syndrome (ARDS) appears not to worsen mortality during low tidal volume ventilation (Osman et al. 2009). Indeed, HCA can augment ventilation–perfusion matching and thereby minimize the need for additional (harmful) ventilatory support (Ketabchi et al. 2009). The sedation issue is confounded as reports exist of HCA increasing (Stewart et al. 1998) or not increasing (Brower et al. 1999) sedative use; in the absence of protocolized sedation the evidence remains deficient. Moreover, the important patient–ventilator dyssynchrony mentioned by Beitler et al. may be due to inappropriate ventilator volume or flow, rather than hypercapnia per se. Immunosuppression from HCA is definitely a concern, especially in sepsis. However, the host response to infection may also contribute to organ injury. It is reassuring that with appropriate antibiotic use HCA does not increase bacterial load or organ injury in experimental pneumonia (Chonghaile et al. 2008); this parallels the conventional use of indicated immunosuppressive therapy in critically ill patients where the risk–benefit ratio is understood and surveillance undertaken. Should HCA during low tidal volume ventilation be treated with buffering agents? Buffering may ablate the protective effects of HCA (Laffey et al. 2000); indeed, while tris-hydroxymethyl amino-methane (THAM) may be preferable to sodium bicarbonate (less intracellular acidosis), the evidence from Dr Hubmayr's laboratory (Caples et al. 2009) indicates that this approach may be harmful. In summary, hypercapnia has beneficial and deleterious effects, depending on its level, timing and context. This is true of most therapies. The cumulative evidence suggests that appropriate use of permissive hypercapnia in ARDS might eventually prove beneficial. Readers are invited to give their views on this and the accompanying CrossTalk articles in this issue by submitting a brief comment. Comments may be posted up to 6 weeks after publication of the article, at which point the discussion will close and authors will be invited to submit a ‘final word’. To submit a comment, go to http://jp.physoc.org/letters/submit/jphysiol;591/11/2771 Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. J. G. Laffey is supported by a Merit award and G. F. Curley by a Clinician Scientist Transition award, from the Department of Anesthesia at the University of Toronto.
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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 | 0.011 |
| 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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.166 | 0.107 |
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".