MétaCan
Menu
Back to cohort

Predicting the development of urosepsis: predictors, techniques, technologies

2025· article· W7117584309 on OpenAlexaboutno aff
K. A. Ershova, N. V. Shindyapina, A. V. Kuligin

Bibliographic record

VenueMessenger of Anesthesiology and Resuscitation · 2025
Typearticle
Language
FieldMedicine
TopicSepsis Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsExacerbationInclusion and exclusion criteriaSystematic reviewBiomarkerSepsisScale (ratio)Cohort

Abstract

fetched live from OpenAlex

Introduction. The article presents an analysis of modern approaches to predicting urosepsis development, focusing on biomarker research and diagnostic methods. The study is relevant due to the high prevalence of urosepsis, which accounts for 31.4% of all clinical forms of sepsis. The objective was to determine the diagnostic significance and systematization of biomarkers of urosepsis in acute purulent pyelonephritis, to identify existing contradictions for further study of this problem. Materials and methods. A systematic literature review was conducted using the PRISMA for Scoping Reviews (PRISMA-ScR) methodology, searching PubMed, Cochrane Database of Systematic Reviews, and Google Scholar with keywords: «biomarkers» OR «cytokines» OR «gene expression» OR «interleukin-6» AND «sepsis» AND «systemic inflammatory response syndrome» AND «pyelonephritis» (last search: May 30, 2025), with inclusion criteria based on PICOD: (P - population) patients with urosepsis due to acute purulent pyelonephritis; (I - intervention) prediction of urosepsis development using biomarkers; (C - comparison) patients with uncomplicated acute purulent pyelonephritis; (O - outcomes) development of sepsis in acute purulent pyelonephritis; (D - study design) prospective/retrospective cohort studies, and exclusion criteria: insufficient relevant data or interesting results, duplicate publications, uncomplicated course of acute (or exacerbation of chronic) pyelonephritis, lack of full-text version, reviews and meta-analyses, with research quality analysis conducted using the Newcastle–Ottawa Scale (NOS). Results. A total of 39 studies involving 38,021 patients were selected, with the majority receiving more than 6 points on the Newcastle–Ottawa Scale (NOS), indicating high-quality research, and during the systematization of the obtained data, biomarkers were categorized according to the degree of their implementation in clinical practice; in terms of functionality and mechanism of action. Conclusion. The findings of the scoping review identified reliable predictors of urosepsis development and progression, which can significantly improve the quality of diagnosis and treatment.

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 score0.181
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.310
Teacher spread0.278 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueMessenger of Anesthesiology and ResuscitationSame topicSepsis Diagnosis and TreatmentFrench-language works237,207