The Prevalence and Risk Factors of Gallstone among Adults in Karachi, South Pakistan: A Population-Based Study
Bibliographic record
Abstract
INTRODUCTION: The present study was aimed to determine the prevalence and risk factors of GSD among a sample of general population in Karachi, South Pakistan. METHODOLOGY: A multistage random sampling method was employed on 30 clusters, where 60 subjects of age>=25 years were randomly recruited from the study population from June 2013 till March 2015. Finally, data was analyzed and logistic regression models were used to find the correlation between selected variables and gallstone disease. RESULTS: It was found that 184 patients had echogenic mass with shadowing on ultrasonography; yielding a prevalence of 10.2% for gallstones in the study participants. The occurrence was higher in females (14.8%) than in male participants (5.7%). Further, participants over 40 years of age and single, widow/separated subjects had higher incidence of gallstones than married individuals. Moreover, an indirect correlation was obtained with daily physical activity, consumption of fruits, vegetables and fish with development of GD. CONCLUSION: It can be evaluated that daily physical activity, female gender, increasing age and marital status play an important role in progression of GSD. Understanding pathogenesis and physiological mechanism involved in GSD can help to determine therapeutic options other than surgical treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".