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Kidney Ultrasonography After First Febrile Urinary Tract Infection in Children

2023· review· en· W4378744917 on OpenAlexafffund
Sarah Yang, Peter J. Gill, Mohammed Rashidul Anwar, Kimberly M. Nurse, Quenby Mahood, Cornelia M. Borkhoff, Vid Bijelić, Patricia C. Parkin, Sanjay Mahant, Ann Bayliss, Mahmoud Sakran, Kim Zhou, Rachel Pearl, Lucy Giglia, Radha Jetty, Anupam Sehgal, Sepideh Taheri, Geert 'tJong, Kristopher T. Kang, Jessica L. Foulds, Gemma Vomiera, Raman Chawla, Joanna Holland, Olivier Drouin, Evelyn Constantin, Patricia Li

Bibliographic record

VenueJAMA Pediatrics · 2023
Typereview
Languageen
FieldMedicine
TopicPediatric Urology and Nephrology Studies
Canadian institutionsHospital for Sick ChildrenPublic Health OntarioUniversity of TorontoChildren's Hospital of Eastern OntarioInstitute for Clinical Evaluative SciencesUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineUrinary systemCINAHLPediatricsInternal medicineUltrasonographySurgeryPsychological intervention

Abstract

fetched live from OpenAlex

Importance: Controversy exists on the clinical utility of kidney ultrasonography after first febrile urinary tract infection (UTI), and clinical practice guideline recommendations vary. Objective: To determine the prevalence of urinary tract abnormalities detected on kidney ultrasonography after the first febrile UTI in children. Data Sources: The MEDLINE, EMBASE, CINAHL, PsycINFO, and Cochrane Central Register of Controlled Trials databases were searched for articles published from January 1, 2000, to September 20, 2022. Study Selection: Studies of children with first febrile UTI reporting kidney ultrasonography findings. Data Extraction and Synthesis: Two reviewers independently screened titles, abstracts, and full texts for eligibility. Study characteristics and outcomes were extracted from each article. Data on the prevalence of kidney ultrasonography abnormalities were pooled using a random-effects model. Main Outcomes and Measures: The primary outcome was prevalence of urinary tract abnormalities and clinically important abnormalities (those that changed clinical management) detected on kidney ultrasonography. Secondary outcomes included the urinary tract abnormalities detected, surgical intervention, health care utilization, and parent-reported outcomes. Results: Twenty-nine studies were included, with a total of 9170 children. Of the 27 studies that reported participant sex, the median percentage of males was 60% (range, 11%-80%). The prevalence of abnormalities detected on renal ultrasonography was 22.1% (95% CI, 16.8-27.9; I2 = 98%; 29 studies, all ages) and 21.9% (95% CI, 14.7-30.1; I2 = 98%; 15 studies, age <24 months). The prevalence of clinically important abnormalities was 3.1% (95% CI, 0.3-8.1; I2 = 96%; 8 studies, all ages) and 4.5% (95% CI, 0.5-12.0; I2 = 97%; 5 studies, age <24 months). Study recruitment bias was associated with a higher prevalence of abnormalities. The most common findings detected were hydronephrosis, pelviectasis, and dilated ureter. Urinary tract obstruction was identified in 0.4% (95% CI, 0.1-0.8; I2 = 59%; 12 studies), and surgical intervention occurred in 1.4% (95% CI, 0.5-2.7; I2 = 85%; 13 studies). One study reported health care utilization. No study reported parent-reported outcomes. Conclusions and Relevance: Results suggest that 1 in 4 to 5 children with first febrile UTI will have a urinary tract abnormality detected on kidney ultrasonography and 1 in 32 will have an abnormality that changes clinical management. Given the considerable study heterogeneity and lack of comprehensive outcome measurement, well-designed prospective longitudinal studies are needed to fully evaluate the clinical utility of kidney ultrasonography after first febrile 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.086
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.086
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0040.006
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.024
GPT teacher head0.301
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations24
Published2023
Admission routes2
Has abstractyes

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