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Record W2334066012 · doi:10.1248/yakushi.131.1677

Stimulating Oral and Nasal Chemoreceptors for Preventing Aspiration Pneumonia in the Elderly

2011· review· en· W2334066012 on OpenAlexaff
Satoru Ebihara, Takae Ebihara, Miyako Yamasaki, Masahiro Kohzuki

Bibliographic record

VenueYAKUGAKU ZASSHI · 2011
Typereview
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsInstitute of Aging
FundersMinistry of Education, Culture, Sports, Science and TechnologySuzuken Memorial Foundation
KeywordsSwallowingReflexDysphagiaMedicineAspiration pneumoniaAnesthesiaPharyngeal reflexTRPM8TRPV1PneumoniaInternal medicineSurgeryReceptorTransient receptor potential channel

Abstract

fetched live from OpenAlex

Aspiration pneumonia remains a major cause of death in the elderly. However, fundamental and effective treatment has not been established yet. Onset of aspiration pneumonia is based on the presence of dysphagia, such as delayed triggering of the swallowing reflex. The swallowing reflex in the elderly is temperature sensitive, even if it is impaired. Swallowing reflex was delayed when the temperature of the food was close to body temperature. The actual swallowing time shortened when the temperature difference increases. The improvement of swallowing reflex by temperature stimuli could be mediated by the temperature-sensitive TRP channel. Administration of the TRPV1 agonists improves the delay of the swallowing reflex. Red wine polyphenols have been suggested to improve the swallowing reflex by increasing TRPV1 response. Food with menthol, an agonist of TRPM8 which is a cold temperature receptor, also decreased the delay in swallowing reflex. Olfactory stimuli, such as black pepper, can be a useful tool to improve swallowing reflex in people with lower ADL and consciousness levels. By combining these various sensory stimuli, we developed a protocol to start oral intake in patients with aspiration pneumonia This protocol shall continue to contribute to the ingestion of many older people.

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)0.003
metaresearch head score (Gemma)0.000
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 score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.211
GPT teacher head0.493
Teacher spread0.282 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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