Prevalence of Urinary Schistosomiasis among Clients Attending Private Medical Laboratory Diagnostic Center in Karshi, Abuja, Nigeria
Bibliographic record
Abstract
Urinary Schistomiasis is one of the global public health problems. A study on the prevalence of urinary Schistosomiasis was carried out among clients attending private medical laboratory center in Karshi, Abuja, Nigeria. The study was carried out among 210 clients comprised 50 males and 70 females aged 11-50years between August 2019 to February, 2020.Single urine samples were collected from the clients between 10.00hours and 14.00hours were examined for the presence of S. haematobium in eggs using centrifuged techniques. Morbidity indicators of haematuria and proteinuria was determined using reagents strips. Out of 210 subjects examined 16(7.6%) had the eggs of S. haematobium in their urine. The results show that males were more infected than the females with 4.8% and 2.8% respectively. The infection rate varied according to age group where 21-30 years age group had highest infection rate 3.3% and age 41-50years had the least prevalence rate 1.0%.The chemical analysis carried out shows that proteinuria had highest prevalence 20.5% and haematuria had 16.7%.Distribution according to marital status show that single had higher prevalence of 5.7% and married had the least 1.9%.There was no statistically significance relationship between all the variables and prevalence of urinary schistosomiasis. From the results of this study, it was concluded that schistosoma haematobium was less prevalent in this study area. Studies strongly suggest that health education on the modes of transmission be promoted and strengthened to achieved total eradication of the disease in the area. Authors recommended the inclusion of private medical laboratory into the government health policies on urinary schistosomiasis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".