Health care risk factors among women and personal behaviours among men explain the high prevalence of hepatitis C virus infection in Karachi, Pakistan
Bibliographic record
Abstract
To estimate the prevalence and identify factors associated with hepatitis C virus (HCV) infection among men and women in Karachi, Pakistan. We conducted a cross-sectional study of adult men and women in a peri-urban community of Karachi (Jam Kandah). Households were selected through systematic sampling from within all villages in the study area. All available adults within each household were interviewed about potential HCV risk factors. A blood specimen was collected to test for anti-HCV antibodies by enzyme immunoassay. We used generalized estimating equations while accounting for correlation of responses within villages to identify the factors associated with HCV infection. Of 1997 participants, 476 (23.8%) were anti-HCV positive. Overall, HCV infection was significantly associated with increasing age, ethnicity, and having received > or =2 blood transfusions, > or =3 hospitalizations, dental treatment and >5 injections among women. Among women, > or =2 blood transfusions [adjusted odds ratio (aOR) = 2.32], >5 injections during the past 6 months (aORs = 1.47), dental treatment (aOR = 1.31) and increasing age(aOR = 1.49), while among men, extramarital sexual intercourse (aOR = 2.77), at least once a week shave from barber (aOR = 5.04), > or =3 hospitalizations (aOR = 2.50) and increasing age (aOR = 1.28) were associated with HCV infection. A very high prevalence of HCV was found in the study population. Among women, unsafe health care practices, while among men extramarital sex, shaving from a barber and hospitalizations were associated with HCV infection. Efforts are needed to improve the safety of medical procedures to reduce the transmission of HCV in Pakistan [Corrections made in Summary after initial online publication.].
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".