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Clinical characteristics of generalized idiopathic pruritus in patients from a tertiary referral center in Singapore

2007· article· en· W2066788427 on OpenAlexaboutno aff
Anthony Goon, Gil Yosipovitch, Yiong‐Huak Chan, Chee‐Leok Goh

Bibliographic record

VenueInternational Journal of Dermatology · 2007
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEveningSensationBurning SensationPain sensationPhysical therapyAnxietyItchingDermatologyAnesthesiaPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Generalized idiopathic pruritus is a rarely studied heterogeneous condition, where patients with non-inflamed, non-pathologic skin complain of widespread pruritus. METHODS: We had administered a detailed pruritus questionnaire, based on the short form of the McGill pain questionnaire, on 75 patients with this condition. RESULTS: All 75 patients recruited with generalized idiopathic pruritus completed the questionnaire. In 92% of the patients, pruritus appeared on a daily basis. Most patients experienced pruritus at night (56%) and in the evening (61%) and 69% had difficulty falling asleep. Pruritus mainly involved the legs (79%), arms (76%) and back (68%). Accompanying symptoms were heat sensation (17%) and pain (13%). 80% had been prescribed antihistamines, of whom 56% obtained short-term relief. The sensation of itch has been reported to be crawling (33%), tickling (20%), stinging (19%) and burning (19%). Patients also reported that the itch was unbearable (73%), bothersome (72%), annoying (67%) and worrisome (45%). The worst-state VAS scores were significantly higher in patients who reported agitation (P = 0.006), difficulty in concentration (P= 0.010) and anxiety (P= 0.033). CONCLUSION: This study describes the sensory and affective dimensions of generalized idiopathic pruritus, and this questionnaire has been found to be a useful tool for evaluating pruritus in this condition.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.393

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.343
Teacher spread0.322 · 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

Citations33
Published2007
Admission routes1
Has abstractyes

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