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Record W2017410542 · doi:10.1177/146642400512500113

Effectiveness of saliva substitute products in the treatment of dry mouth in the elderly: a pilot study

2005· article· en· W2017410542 on OpenAlexaff
David Matear, John Barbaro

Bibliographic record

VenueThe Journal of the Royal Society for the Promotion of Health · 2005
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Disorders and Functions
Canadian institutionsBaycrest HospitalBarrie Urology GroupUniversity of Toronto
Fundersnot available
KeywordsDry mouthSalivaMedicineDentistryEnvironmental healthFood scienceChemistryInternal medicine

Abstract

fetched live from OpenAlex

The aging population is susceptible to developing dry mouth (xerostomia). Elderly patients present all of the major risk factors to acquiring dry mouth which include systemic diseases and disorders, such as diabetes and depression, and the use of numerous medications, including anti-hypertensives and anti-depressants. The consequences of untreated dry mouth are severe limitations of masticatory function and speech, and increased risk of developing caries, periodontal diseases and fungal infections. Assessment of xerostomia, which includes a set of signs and symptoms that impact on the individual, can only be fully explored through a thorough medical history, intra-oral examination and recording the subjective views of patients. This study suggests a methodology for the assessment of xerostomia through a xerostomia questionnaire, which was used to evaluate the effectiveness and acceptability of a saliva substitute product (Biotène) in the treatment of xerostomia in 20 elderly patients exhibiting both severe and moderate symptoms. Wilcoxon signed-ranked tests revealed significant improvements in the number and severity of symptoms between the pre-test and the post-test groups. Biotène products were also found to be effective in the treatment of both severe and moderate symptoms of xerostomia. Biotène saliva substitutes are an acceptable and effective method of treatment for elderly people suffering from dry mouth.

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)0.007
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.252

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
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 head0.055
GPT teacher head0.322
Teacher spread0.267 · 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 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

Citations19
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Royal Society for the Promotion of HealthSame topicSalivary Gland Disorders and FunctionsFrench-language works237,207