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Record W2144418950 · doi:10.1113/jphysiol.2013.255638

Rebuttal from Gerard F. Curley, John G. Laffey and Brian P. Kavanagh

2013· letter· en· W2144418950 on OpenAlexafffundabout
Gerard F. Curley, John G. Laffey, Brian P. Kavanagh

Bibliographic record

VenueThe Journal of Physiology · 2013
Typeletter
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsHospital for Sick ChildrenUniversity of TorontoSt. Michael's Hospital
FundersUniversity of Toronto
KeywordsHypercapniaMedicineTidal volumeHypocapniaAnesthesiaCardiologyIntensive care medicineInternal medicineAcidosisRespiratory system

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.166
Threshold uncertainty score0.555

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.1660.107

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.

Opus teacher head0.019
GPT teacher head0.250
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations1
Published2013
Admission routes3
Has abstractyes

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