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Record W3173842715 · doi:10.4081/aiua.2021.2.206

Prevalence of urinary tract infection in children in the kingdom of Saudi Arabia

2021· article· en· W3173842715 on OpenAlexaff
Mariam Alrasheedy, Hoda Jehad Abousada, M. Abdulhaq, Raghad Abdulelah Alsayed, Khalid Abdullah Alghamdi, Fayez Dhyefallah Alghamdi, Abdullah F Al Muaibid, Refal Ghassan Ajjaj, Seham Salem Almohammadi, Sarah Salem Almohammadi, Wajd Adnan Alfitni, Abdulrahman Mohamed Homsi, Meqbel Majed Alshelawi, Hassan A. Alshamrani, Abdulrauf Abdulatif Tashkandi, Sara Mannan, Salihah Attiah Alsamiri

Bibliographic record

VenueArchivio Italiano di Urologia e Andrologia · 2021
Typearticle
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsKamloops Art Gallery
Fundersnot available
KeywordsMedicinePediatricsChristian ministryUrethritisCross-sectional studyMultivitaminUrinary systemInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Urinary tract infection (UTI) is a common disorder in childhood. Early identification and appropriate antibiotic use are essential to avoid long-term sequels. The trial objective was to identify the prevalence of URI in children, and the risk factors. METHODS: This is an analytical cross-sectional study conducted in the Saudi Arabia, from April 4th 2020 till July 30th 2020. The sample was randomly selected from children who presented to the ministry of health tertiary hospitals. People answered a questionnaire of 10 items. RESULTS: 1083 people participated in the current trial. The prevalence of UTI was 25.8%. The mean age was 4.5-5 years. UTI was commoner in females than males. Urethritis was the main presenting complaint. Western region was the commonest identified area. Those with multivitamin deficiency had the highest prevalence. CONCLUSION: UTI is not a very common problem for children in Saudi Arabia. Western region had the highest prevalence and the peak age ranged from 4.5 to 5 years. Additionally, nearly a sixth of children could develop severe/complicated UTI.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.018
GPT teacher head0.267
Teacher spread0.249 · 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

Citations17
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueArchivio Italiano di Urologia e AndrologiaSame topicPediatric Urology and Nephrology StudiesFrench-language works237,207