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Record W2106673089 · doi:10.1186/cc8926

Bench-to-bedside review: Carbon dioxide

2010· review· en· W2106673089 on OpenAlexafffund
Gerard F. Curley, John G. Laffey, Brian P. Kavanagh

Bibliographic record

VenueCritical Care · 2010
Typereview
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
FundersCanadian Institutes of Health Research
KeywordsHypocapniaHypercapniaMedicineIntensive care medicineHyperventilationAnesthesiaAcidosis

Abstract

fetched live from OpenAlex

Carbon dioxide is a waste product of aerobic cellular respiration in all aerobic life forms. PaCO2 represents the balance between the carbon dioxide produced and that eliminated. Hypocapnia remains a common - and generally underappreciated - component of many disease states, including early asthma, high-altitude pulmonary edema, and acute lung injury. Induction of hypocapnia remains a common, if controversial, practice in both adults and children with acute brain injury. In contrast, hypercapnia has traditionally been avoided in order to keep parameters normal. More recently, advances in our understanding of the role of excessive tidal volume has prompted clinicians to use ventilation strategies that result in hypercapnia. Consequently, hypercapnia has become increasingly prevalent in the critically ill patient. Hypercapnia may play a beneficial role in the pathogenesis of inflammation and tissue injury, but may hinder the host response to sepsis and reduce repair. In contrast, hypocapnia may be a pathogenic entity in the setting of critical illness. The present paper reviews the current clinical status of low and high PaCO2 in the critically ill patient, discusses the insights gained to date from studies of carbon dioxide, identifies key concerns regarding hypocapnia and hypercapnia, and considers the potential clinical implications for the management of patients with acute lung injury.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.064
GPT teacher head0.416
Teacher spread0.352 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations160
Published2010
Admission routes2
Has abstractyes

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