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Use of high-frequency oscillatory ventilation in burn patients

2005· review· en· W2041847206 on OpenAlexaff
Robert Cartotto, Sandi Ellis, Terry Smith

Bibliographic record

VenueCritical Care Medicine · 2005
Typereview
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineARDSSmoke inhalationAnesthesiaOxygenationVentilation (architecture)Smoke Inhalation InjuryMean airway pressureBurn injurySurgeryLungInhalationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Patients with major burn injuries frequently develop acute respiratory distress syndrome (ARDS). High-frequency oscillatory ventilation (HFOV) has been used successfully in our regional burn center since 1999 for the management of oxygenation failure secondary to ARDS and as a method of intraoperative ventilation to allow surgical burn wound excision to proceed, despite the presence of severe ARDS. OBJECTIVE: The objective of this article is to review the use of HFOV in burn patients, with an emphasis on the indications and selection criteria for the initiation of HFOV, special considerations for patients with smoke inhalation injury, and our approach to intra-operative HFOV. SETTING: Adult regional burn center in a university-affiliated tertiary care hospital. RESULTS: We have now used HFOV in 36 severely burned patients, 33% of whom had an associated smoke inhalation injury. HFOV produced significant improvements in oxygenation among burn patients with oxygenation failure secondary to ARDS. HFOV produced a slower and less robust reversal of oxygenation failure in those with smoke inhalation compared with patients with burns alone. HFOV has been used intraoperatively for 33 procedures in 18 patients without complications. CONCLUSION: HFOV has been an indispensable ventilation modality in our burn center, and has played an important role in reversing oxygenation failure in patients with ARDS and in facilitating early excision and closure of the burn wound in these patients.

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 score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.087
GPT teacher head0.387
Teacher spread0.300 · 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

Citations47
Published2005
Admission routes1
Has abstractyes

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