Epidemiology of Pathogens Causing Urinary Tract Infections in Rural Communities of Enugu State, Nigeria
Bibliographic record
Abstract
Urinary tract infection (UTI) is the infection of any part of the urinary tract, and about 150 million people worldwide develop UTI each year. Its is caused by bacteria, though fungi and viruses are etiologic agents, and can occur in community and hospital settings. This study was conducted to determine the epidemiology of pathogens causing urinary tract infections in Rural Communities of Enugu State, Nigeria. A total of 735 clean catch mid-stream urine samples were collected and tested for bacteriuria from February, 2021 to June, 2021. The participants were assessed clinically to ascertain eligibility for participation, and urine samples were assessed microbiologically to isolate pathogens causing UTI. Pathogens isolated were identified morphologically, and biochemically, and results were tabulated, with respect to participants demographics. Total number of participants that participated in urine culture was 735, of this number, 172(23.40%) were males, whereas 563(76.60) were females. 510(69.39%) were married whereas 225(30.61%) were single. Total number of bacterial isolates obtained was 649 (88.30%). Of this, Escherichia coli was the most prevalent, 316 (48.7%), followed by Staphylococci, 154 (27.7%). The least represented isolate was Pseudomonas, 2 (0.3%). Of the total number of isolates obtained, 151(23.27%) came from males, whereas 498 (76.73%) were from females. Total number of married participants with positive bacteriuria was 449 (69.18%), and those of them that were single constituted 198(30.51%). Age range of 31-40 gave the highest level of bacteriuria 151 (23.27%), followed by age range of 21-30, 146 (22.50%). The least representation of bacteriuria was seen among age group 10-20, 39(6.01%). The prevalent of UTI in this study was high, and females, youths, and married people showed a positive correlation with community acquired urinary tract infection. Intermittent screening of rural dwellers for positive bacteriuria, with emphasis paid on clinical symptoms and proper treatment will go a long way in tackling the menace of urinary tract infection in our rural communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".