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Record W2594271836 · doi:10.1155/2017/3829168

Characteristics and Etiologies of Chronic Scrotal Pain: A Common but Poorly Understood Condition

2017· article· en· W2594271836 on OpenAlexaff
Aosama Aljumaily, Hind Abdul Jaleel Al-Khazraji, Allan Gordon, Susan Lau, Keith Jarvi

Bibliographic record

VenuePain Research and Management · 2017
Typearticle
Languageen
FieldHealth Professions
TopicMale Reproductive Health Studies
Canadian institutionsLunenfeld-Tanenbaum Research InstituteUniversity of TorontoMount Sinai Hospital
Fundersnot available
KeywordsEtiologyMedicineScrotal PainPhysical examinationNeuropathic painSurgeryPhysical therapyInternal medicinePediatricsAnesthesiaScrotum

Abstract

fetched live from OpenAlex

Chronic scrotal pain (CSP) is a common and debilitating condition, but the underlying characteristics and etiology of CSP are poorly understood. The objective of this study is to identify the characteristic and etiologies of CSP. Men presenting for management of CSP completed a standardized questionnaire and underwent a complete physical examination. From Feb 2014 to Sep 2015, a total of 131 men (mean age 43) with CSP were studied. The CSP was of long duration (mean of 4.7 ± 5.95 years) and dramatically affected men's lives, with adverse effects on normal activities (71.%), ability to work (51.90%), and sexual functioning (61.8%). 50.4% felt depressed on most days, and 67.17% felt either unhappy or terrible with their present condition. Physical examination revealed that the epididymis was the most common tender area found in 70/131 men (53.43%), though a musculoskeletal source for the pain was found in 9.9%. Neuropathic changes were found in 30%. For close to half of the men (43.5%) we were unable to identify any potential cause for the CSP. This study characterizes the dramatic impact that CSP has on the lives of men, while providing an understanding of the common etiologies.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.253
GPT teacher head0.520
Teacher spread0.266 · 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

Citations29
Published2017
Admission routes1
Has abstractyes

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