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Record W2060196402 · doi:10.5539/gjhs.v7n4p110

Clinical Manifestation and Risk Factors of Tuberculosis Infection in Malaysia:Case Study of a Community Clinic

2015· article· en· W2060196402 on OpenAlexvenueno aff
R Shanmuganathan, Indra Devi Subramaniam

Bibliographic record

VenueGlobal Journal of Health Science · 2015
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTuberculosisDiabetes mellitusRisk factorDiseaseIncidence (geometry)Alcohol abuseMedical recordHuman immunodeficiency virus (HIV)Substance abuseInternal medicinePediatricsFamily medicinePsychiatryPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: The main aim of this study was to describe the clinical manifestation of tuberculosis infection cases in Malaysia and to determine the individual risk factors for their occurrence. METHODOLOGY: The study adopted a quantitative research approach with use of descriptive statistical approach. The study setting was a community clinic which treats walk in patients who are mainly living and working in the surrounding areas. The study was conducted for a period of one year. All tuberculosis patients who sought treatment in the clinic during the time were included in this study. The total number of cases was 40. Data was collected from the medical records of the tuberculosis patients. The risk factors selected for investigation were demographic characteristics of age and sex, personal habits such as smoking, drug use and alcohol and presence of diseases such as human immunodeficiency virus positive (HIV+), diabetes mellitus, cancer, cyanotic heart disease, renal failure and steroid use. RESULTS: Patients in the age group ranging from 41 to 50 years had the highest incidence of the infection. Smoking appears to be the most important risk factor for contracting followed by drug abuse, HIV+ infection and diabetes mellitus. CONCLUSIONS: People with diseases such as diabetes mellitus and HIV that are high risk factors for TB should be screened for TB so that early detection and intervention is possible. Educational programs should be carried out to create awareness among the at risk groups.

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)0.020
metaresearch head score (Gemma)0.005
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 score0.044
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.176
GPT teacher head0.507
Teacher spread0.331 · 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

Citations30
Published2015
Admission routes1
Has abstractyes

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