Predictive Value of a Diagnostic Five-Gene Biomarker for Pediatric Sepsis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38595339", "kind": "science-record", "revision": 3, "content_hash": "sha256:bd68607e9929b36b3c4ede44f590027294cc89cd9f808976810a11fb4e155b02", "created_at": "2026-11-01T19:20:33Z", "updated_at": "2026-11-01T22:11:38Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Predictive Value of a Diagnostic Five-Gene Biomarker for Pediatric Sepsis.", "doi": "10.2147/JIR.S447588", "pmid": "38595339", "authors": ["Yulong Xiao", "Genhao Zhang"], "journal": "Journal of inflammation research", "year": 2024, "abstract": "Background: Pediatric sepsis has a very high morbidity and mortality rate. The purpose of this study was to evaluate diagnostic biomarkers and immune cell infiltration in pediatric sepsis.\nMethods: Three datasets (GSE13904, GSE26378, and GSE26440) were downloaded from the gene expression omnibus (GEO) database. After identifying overlapping genes in differentially expressed genes (DEGs) and modular sepsis genes selected via a weighted gene co-expression network (WGCNA) in the GSE26378 dataset, pivotal genes were further identified by using LASSO regression and random forest analysis to construct a diagnostic model. Receiver operating characteristic curve (ROC) analysis was used to validate the efficacy of the diagnostic model for pediatric sepsis. Furthermore, we used qRT-PCR to detect the expression levels of pivotal genes and validate the diagnostic model's ability to diagnose pediatric sepsis in 65 actual clinical samples.\nResults: Among 294 overlapping genes of DEGs and modular sepsis genes, five pivotal genes (STOM, MS4A4A, CD177, MMP8, and MCEMP1) were screened to construct a diagnostic model of pediatric sepsis. The expression of the five pivotal genes was higher in the sepsis group than in the normal group. The diagnostic model showed good diagnostic ability with AUCs of 1, 0.986, and 0.968. More importantly, the diagnostic model showed good diagnostic ability with AUCs of 0.937 in the 65 clinical samples and showed better efficacy compared to conventional inflammatory indicators such as procalcitonin (PCT), white blood cell (WBC) count, C-reactive protein (CRP), and neutrophil percentage (NEU%).\nConclusion: We developed and tested a five-gene diagnostic model that can reliably identify pediatric sepsis and also suggest prospective candidate genes for peripheral blood diagnostic testing in pediatric sepsis patients.", "claims": [{"id": "claim-method", "statement": "Finally, the receiver operating characteristic curve (ROC) analysis in both the training and testing sets was used to assess the validity of the diagnostic model, and the area under the curve (AUC) was generated to assess the algorithm’s prediction capability.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38595339", "locator": "sections[5] \"Diagnostic Markers Construction by the Least Absolute Shrink and Selection Operator (LASSO) Regression and Random Forests (RF) Algorithms\" paragraph 2", "quote": "Finally, the receiver operating characteristic curve (ROC) analysis in both the training and testing sets was used to assess the validity of the diagnostic model, and the area under the curve (AUC) was generated to assess the algorithm’s prediction capability."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38595339", "locator": "sections[17] \"Data Sharing Statement\" paragraph 2", "quote": "The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request."}], "state": "complete"}, {"id": "claim-target-result", "statement": "More importantly, the diagnostic model showed good diagnostic ability with AUCs of 1 in the GSE26378 cohort, 0.986 in the GSE26440 cohort, and 0.968 in the GSE13904 cohort, respectively (Figure 5C).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38595339", "locator": "sections[11] \"Diagnostic Markers Construction in Pediatric Sepsis\" paragraph 2", "quote": "More importantly, the diagnostic model showed good diagnostic ability with AUCs of 1 in the GSE26378 cohort, 0.986 in the GSE26440 cohort, and 0.968 in the GSE13904 cohort, respectively (Figure 5C)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "More importantly, the diagnostic model showed good diagnostic ability with AUCs of 1 in the GSE26378 cohort, 0.986 in the GSE26440 cohort, and 0.968 in the GSE13904 cohort, respectively (Figure 5C).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:38595339"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13904"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "blocked", "blocked_on": "method:machine_learning_random_forest", "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13904"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:run_analysis blocked on method:machine_learning_random_forest"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38595339", "role": "manuscript", "format": "xml", "media_type": "application/xml", 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"title": "Expression data from validation cohort of children with septic shock", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE26440", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE26440", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE26440", "version": null, "note": "The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.", 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