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Record W2067086741 · doi:10.3143/geriatrics.40.325

Cerebrovascular disease and pneumonia in the elderly

2003· article· en· W2067086741 on OpenAlexaff
Toshifumi Matsui, Takae Ebihara, Takashi Ohrui, Mutsuo Yamaya, Hiroyuki Arai, Hidetada Sasaki

Bibliographic record

VenueNippon Ronen Igakkai Zasshi Japanese Journal of Geriatrics · 2003
Typearticle
Languageen
FieldHealth Professions
TopicDysphagia Assessment and Management
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsMedicineAspiration pneumoniaPneumoniaSwallowingPharyngeal reflexDopaminergicCough reflexAnesthesiaReflexDysphagiaAmantadineDopamineInternal medicineIntensive care medicinePharmacologySurgery

Abstract

fetched live from OpenAlex

Pneumonia is a common cause of death in elderly people. A series of our studies have demonstrated that pneumonia in the elderly is characterized by silent aspiration, impaired swallowing and cough reflex, partly due to cerebral infarctions at basal ganglia. These infarctions probably induce the disruption of the specific central neurotransmitter system including dopamine and substance P, which plays an important role for swallowing and cough reflex. Use of ACE inhibitor and stimulation of the oral cavity by simple oral care, which are effective in increasing substance P. reduced the incidence of aspiration pneumonia. Moreover, use of a dopamine agonist such as amantadine hydrochloride and a folic acid supplement that are known to potentiate dopaminergic neurons also prevented aspiration pneumonia. For patients bedridden due to lowered ADL, it is essential for them to keep an upright position a few hours after meals to prevent aspiration pneumonia caused by the reflux of ingested foods. Also, administration of neuroleptics may cause aspiration pneumonia by suppression of dopaminergic neurons.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.337
Teacher spread0.312 · 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 designObservational
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

Citations3
Published2003
Admission routes1
Has abstractyes

Explore more

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