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Record W4398156029 · doi:10.25270/wmp.22094

The Effect of Hyperbaric Oxygen Therapy on Psychological State and Wound Healing: A Case Report

2024· article· en· W4398156029 on OpenAlexaff
Flavia Tasmin Techera Antunes, Mariana Campos Duarte Machado, Alice Bartolomeu Garavini, Vanice Paula Ricardo Carvalho, Alessandra Hübner de Souza

Bibliographic record

VenueWound Management & Prevention · 2024
Typearticle
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHyperbaric oxygenWound healingState (computer science)PsychologyPsychotherapistMedicineSurgeryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Hyperbaric oxygen therapy (HBOT), in which patients receive high concentrations of oxygen in a pressurized chamber, has been used in clinical practice to improve wound healing. More recent applications of HBOT have resulted in successful management of a wide range of conditions; however, the psychosomatic factors associated with these conditions remain understudied and require clarification. PURPOSE: To investigate the effects of HBOT in a female patient without diabetes who presented with an atypical wound of 9 years' duration with no sign of healing as well as with psychosomatic factors. CASE REPORT: The patient underwent 20 once-daily sessions of HBOT for 120 minutes per session every Monday through Friday for 4 weeks at 2.4 ATA (atmosphere absolute pressure) and received daily dressing changes with a nonadherent dressing containing silver, alginate, and carboxymethylcellulose. The 36-Item Short Form Health Survey and the Hospital Anxiety and Depression Scale quality-of-life questionnaires were administered before treatment and after 1 year of treatment. HBOT resulted in complete lasting wound remission as well as subjective improvement in quality of life and in levels of anxiety and depression. CONCLUSION: HBOT has known therapeutic effects on wound healing, and it may also have a substantial effect on psychosomatic mechanisms.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.482

Codex and Gemma teacher scores by category

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

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 head0.023
GPT teacher head0.351
Teacher spread0.328 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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
Published2024
Admission routes1
Has abstractyes

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