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Record W2051703993 · doi:10.1177/171516350714000323

New Tools and Insights: Hyperhidrosis in a Community Setting

2007· article· en· W2051703993 on OpenAlexvenueno aff
Veronique Koo, Dipen Kalaria, Willem Wassenaar

Bibliographic record

VenueCanadian Pharmacists Journal / Revue des Pharmaciens du Canada · 2007
Typearticle
Languageen
FieldMedicine
TopicSympathectomy and Hyperhidrosis Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsHyperhidrosisMedicineFeelingPsychosocialEmbarrassmentPhysical therapyPsychologySurgeryPsychiatryPsychotherapist

Abstract

fetched live from OpenAlex

Background: While excessive sweating is considered by many to be a benign condition, the physical and psychosocial impact it can have on hyperhidrosis sufferers is not always fully appreciated. Methods: A retrospective review of our pharmacy's patient records with the presenting complaint of sweating was conducted. The review covered a 2-year span and consisted of 2517 records. Using a structured questionnaire, patient information was collected via e-mail, as well as telephone and face-to-face interviews by pharmacists. Patients described their difficulties and the different coping methods they would employ to alleviate or hide their excessive sweating on different areas such as the underarms, face/scalp, hands, feet, and torso/groin. Results: Underarm sweating is the most frequent area for which both male and female patients seek help, followed by hands, feet, and face/neck. For males over 40, face and neck sweating is the most frequent area of concern, whereas for females over 40, underarms remain a top priority. Patients report numerous instances of feeling isolated, depressed, and a lack of self-confidence in all areas of professional and social life. Conclusion: It is important to recognize that for some patients, excessive sweating can be a severely debilitating condition. Appropriate action must be taken in order to improve the patient's quality of life.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.041
GPT teacher head0.288
Teacher spread0.247 · 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 designCase report
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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Pharmacists Journal / Revue des Pharmaciens du CanadaSame topicSympathectomy and Hyperhidrosis TreatmentsFrench-language works237,207