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Record W4293255307 · doi:10.48083/whll5336

Epidemiology and Clinical Characteristics of Urogenital Tuberculosis in Sabah, Malaysia

2022· article· en· W4293255307 on OpenAlexvenueno aff
Karthikayenee Ramasamy, Shankaran Thevarajah

Bibliographic record

VenueSociété Internationale d’Urologie Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and treatment of tuberculosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineEpidemiologyTuberculosisRetrospective cohort studyAbdominal painGenitourinary systemMedical recordPediatricsSurgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

Abstract Objectives We aimed to describe the epidemiology and clinical characteristics of urogenital tuberculosis (UGTB) in Sabah, Malaysia. Methods We performed a retrospective, descriptive study based on medical records of UGTB cases identified between January 1, 2014, and November 30, 2020. Results We identified 131 cases of UGTB in Sabah. Patient gender was balanced except for a mild male predominance in the 35 to 44 age group. No cases were reported in children. The majority of the patients (96%) were diagnosed in the government facility. Among the UGTB cases, 72% of patients were from rural areas, and 29% were illiterate. The commonest presentation was frequency of micturition (28%), followed by abdominal pain (26%) and loss of appetite (26%). The common sites included renal (32%) and scrotal (25%). Diagnosis was achieved via histopathology in 39.7% of patients and smear microscopy in 35.9%. Anti-tubercular treatment duration was 8.6 (±SD 4.0) months, and 81% of patients have completed treatment. A total of 50.4% of patients had received surgical intervention; 10.7% had undergone incision and drainage, 9.9% had cystoscopy, and 6.9% underwent orchidectomy. Conclusion UGTB has varied non-specific symptoms, which poses a diagnostic challenge, leading to morbidity. Ensuring awareness via widespread education within government and private health care, along with rural outreach programs, will contribute to early recognition and treatment.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.385
Teacher spread0.319 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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