Nomogram construction based on characteristic genes and clinical variables to predict the risk of multiple organ dysfunction syndrome caused by influenza in children.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39944873", "kind": "science-record", "revision": 3, "content_hash": "sha256:e28b20653647d46f5f4c72044609a8bb61990f767288d92a0b6ae5708c8c316f", "created_at": "2026-11-01T20:30:12Z", "updated_at": "2026-11-01T22:13:39Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Nomogram construction based on characteristic genes and clinical variables to predict the risk of multiple organ dysfunction syndrome caused by influenza in children.", "doi": "10.21037/tp-24-386", "pmid": "39944873", "authors": ["Ming Chi", "Fei Liu", "Haifeng Chi", "Ping Liu", "Bo Xu", "Dawei Zhang"], "journal": "Translational pediatrics", "year": 2025, "abstract": "Background: Screening for risk factors for the occurrence of multiple organ dysfunction syndrome (MODS) caused by pediatric influenza is an essential approach to improving treatment interventions and stratifying prognosis. This study aimed to select characteristic genes in MODS samples, demonstrate the correlation between characteristic genes and clinical variables, show the changes in expression levels of characteristic genes in the progression of MODS, and establish a predictive prolonged MODS (PM) line chart model.\nMethods: We downloaded the pediatric influenza blood messenger ribonucleic acid (mRNA) dataset (GSE236877) from the Gene Expression Omnibus (GEO) database. Multiple logistic regression analyses were employed to screen for risk factors and independent risk factors, and to establish nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive efficacy of variables on disease occurrence, where a larger area under the curve (AUC) indicates better predictive performance. Calibration curves and the Hosmer-Lemeshow goodness-of-fit test were utilized to describe whether the curves exhibited deviation. Decision curve analysis (DCA) was employed to assess the predictive efficacy of the model.\nResults: SLC12A7 was an independent risk factor that increased the risk of PM (OR =0.356, P<0.001). GNA15 (OR =4.598, P<0.001) and EMP1 (OR =2.158, P=0.002) were protective factors that reduced the risk of PM occurrence. These three genes were combined with clinical variables, including age, influenza virus type, and bacterial co-infection, to construct a nomogram model for predicting the risk of MODS in children with influenza. The AUC of the nomogram score was 0.946, which was larger than the AUC of individual genes and clinical variables. Nomogram model can increase the net benefit of patients compared with clinical variables.\nConclusions: TGFBI, SLC12A7, LY86, HAL, CASP5, RETN, ESPL1, TULP2, DEFB114, EMP1, GNA15, GPAA1 were characteristic genes that distinguished between never MODS (NM) and PM samples. SLC12A7, GNA15, and EMP1 can serve as independent predictive factors for MODS. A nomogram model based on SLC12A7, GNA15, EMP1, and clinical variables (age, influenza virus type, and bacterial co-infection status) demonstrated better predictive performance for the risk of MODS in children with influenza compared to clinical variables and single genes.", "claims": [{"id": "claim-method", "statement": "Multiple logistic regression analyses were employed to screen for risk factors and independent risk factors, and to establish nomogram model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39944873", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Multiple logistic regression analyses were employed to screen for risk factors and independent risk factors, and to establish nomogram model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We downloaded the pediatric influenza blood mRNA dataset (GSE236877) from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39944873", "locator": "sections[4] \"Data download\" paragraph 2", "quote": "We downloaded the pediatric influenza blood mRNA dataset (GSE236877) from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "ROC curve showed that the AUC of the nomogram score was 0.946, which was larger than the AUC of individual genes and clinical variables (Figure 7C).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39944873", "locator": "sections[15] \"Diagnostic model construction\" paragraph 2", "quote": "ROC curve showed that the AUC of the nomogram score was 0.946, which was larger than the AUC of individual genes and clinical variables (Figure 7C)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "ROC curve showed that the AUC of the nomogram score was 0.946, which was larger than the AUC of individual genes and clinical variables (Figure 7C).", "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:39944873"], "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:GSE236877"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "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:GSE236877"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39944873", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.21037/tp-24-386", "sha256": "sha256:85db94a66044c62150d33fd29a20118307bb43057c15a7330a1ddd5aab9de58d", "bytes": 33485, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.21037/tp-24-386", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11811593", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE236877", "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=GSE236877", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE236877", "version": null, "note": "We downloaded the pediatric influenza blood mRNA dataset (GSE236877) from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo).", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "We downloaded the pediatric influenza blood mRNA dataset (GSE236877) from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo).", "access_statement_kind": "repository_route_statement", "sample_accessions": ["GSM7578343", "GSM7578344", "GSM7578345", "GSM7578346", "GSM7578347", "GSM7578348", "GSM7578349", "GSM7578350", "GSM7578351", "GSM7578352", "GSM7578353", "GSM7578354", "GSM7578355", "GSM7578356", "GSM7578357", "GSM7578358", "GSM7578359", "GSM7578360", "GSM7578361", "GSM7578362", "GSM7578363", "GSM7578364", "GSM7578365", "GSM7578366", "GSM7578367", "GSM7578368", "GSM7578369", "GSM7578370", "GSM7578371", "GSM7578372", "GSM7578373", "GSM7578374", "GSM7578375", "GSM7578376", "GSM7578377", "GSM7578378", "GSM7578379", "GSM7578380", "GSM7578381", "GSM7578382", "GSM7578383", "GSM7578384", "GSM7578385", "GSM7578386", "GSM7578387", "GSM7578388", "GSM7578389", "GSM7578390", "GSM7578391", "GSM7578392", "GSM7578393", "GSM7578394", "GSM7578395", "GSM7578396", "GSM7578397", "GSM7578398", "GSM7578399", "GSM7578400", "GSM7578401", "GSM7578402", "GSM7578403", "GSM7578404", "GSM7578405", "GSM7578406", "GSM7578407", "GSM7578408", "GSM7578409", "GSM7578410", "GSM7578411", "GSM7578412", "GSM7578413", "GSM7578414", "GSM7578415", "GSM7578416", "GSM7578417", "GSM7578418", "GSM7578419", "GSM7578420", "GSM7578421", "GSM7578422", "GSM7578423", "GSM7578424", "GSM7578425", "GSM7578426", "GSM7578427", "GSM7578428", "GSM7578429", "GSM7578430", "GSM7578431", "GSM7578432", "GSM7578433", "GSM7578434", "GSM7578435", "GSM7578436", "GSM7578437", "GSM7578438", "GSM7578439", "GSM7578440", "GSM7578441", "GSM7578442", "GSM7578443", "GSM7578444", "GSM7578445", "GSM7578446", "GSM7578447", "GSM7578448", "GSM7578449", "GSM7578450", "GSM7578451", "GSM7578452", "GSM7578453", "GSM7578454", "GSM7578455", "GSM7578456", "GSM7578457", "GSM7578458", "GSM7578459", "GSM7578460", "GSM7578461", "GSM7578462", "GSM7578463", "GSM7578464", "GSM7578465", "GSM7578466", "GSM7578467", "GSM7578468", "GSM7578469", "GSM7578470", "GSM7578471", "GSM7578472", "GSM7578473", "GSM7578474", "GSM7578475", "GSM7578476", "GSM7578477", "GSM7578478", "GSM7578479", "GSM7578480", "GSM7578481", "GSM7578482", "GSM7578483", "GSM7578484", "GSM7578485", "GSM7578486", "GSM7578487", "GSM7578488", "GSM7578489", "GSM7578490", "GSM7578491", "GSM7578492", "GSM7578493", "GSM7578494", "GSM7578495", "GSM7578496", "GSM7578497", "GSM7578498", "GSM7578499", "GSM7578500", "GSM7578501", "GSM7578502", "GSM7578503", "GSM7578504", "GSM7578505", "GSM7578506", "GSM7578507", "GSM7578508", "GSM7578509", "GSM7578510", "GSM7578511", "GSM7578512", "GSM7578513", "GSM7578514", "GSM7578515", "GSM7578516", "GSM7578517", "GSM7578518", "GSM7578519", "GSM7578520", "GSM7578521", "GSM7578522", "GSM7578523", "GSM7578524", "GSM7578525", "GSM7578526", "GSM7578527", "GSM7578528", "GSM7578529", "GSM7578530", "GSM7578531", "GSM7578532", "GSM7578533", "GSM7578534", "GSM7578535", "GSM7578536", "GSM7578537", "GSM7578538", "GSM7578539", "GSM7578540", "GSM7578541", "GSM7578542", "GSM7578543", "GSM7578544", "GSM7578545", "GSM7578546", "GSM7578547", "GSM7578548", "GSM7578549", "GSM7578550", "GSM7578551", "GSM7578552", "GSM7578553", "GSM7578554", "GSM7578555", "GSM7578556", "GSM7578557", "GSM7578558", "GSM7578559", "GSM7578560", "GSM7578561", "GSM7578562", "GSM7578563", "GSM7578564", "GSM7578565", "GSM7578566", "GSM7578567", "GSM7578568", "GSM7578569", "GSM7578570", "GSM7578571", "GSM7578572", "GSM7578573", "GSM7578574", "GSM7578575", "GSM7578576", "GSM7578577", "GSM7578578"], "sample_count": 236, "group_sizes": null, "group_sizes_basis": null, "platform": "33557", "taxon": "Homo sapiens", "title": "Transcriptomic Profiles of Multiple Organ Dysfunction Syndrome Phenotypes in Pediatric Critical Influenza", "resolution_checked_at": "2026-11-01T20:16:08Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE236877 not downloaded", "asset:data:geo:GSE236877 licence not read"]}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "regression_modelling", "specific": "logistic", "label": "Regression modelling", "dsl_operations": ["glm_logit_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Multiple logistic regression analyses were employed to screen for risk factors and independent risk factors, and to establish nomogram model."}}, {"id": "method-2", "family": "group_comparison", "specific": "mann_whitney", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_mann_whitney"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Mann-Whitney"}}, {"id": "method-3", "family": "model_calibration", "specific": "decision_curve", "label": "Model calibration / clinical utility", "dsl_operations": ["calibration_bins", "net_benefit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictions_and_outcomes"], "evidence": {"score": 0.7, "band": "medium", "quote": "Decision curve analysis"}}, {"id": "method-4", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "χ2"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["glm_logit_fit"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: logistic."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE236877"], "resolved_accessions": ["GSE236877"], "statements": ["We downloaded the pediatric influenza blood mRNA dataset (GSE236877) from the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo)."], "basis": "The paper names GSE236877 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["glm_logit_fit"], "assets": ["source:pmid:39944873", "data:geo:GSE236877"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE236877"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:46:08Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": null}, "calls": 5, "usage": {"prompt_tokens": 9200, "completion_tokens": 655, "cached_tokens": 264}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:39944873", "type": "paper", "label": "pmid:39944873"}, {"id": "source:pmid:39944873", "type": "manuscript", "label": "PMID 39944873 full text"}, {"id": "data:geo:GSE236877", "type": "dataset", "label": "GEO GSE236877"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39944873", "type": "paper", "label": "pmid:39944873"}, {"id": "source:pmid:39944873", "type": "manuscript", "label": "PMID 39944873 full text"}, {"id": "data:geo:GSE236877", "type": "dataset", "label": "GEO GSE236877"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39944873", "type": "extraction", "used": ["source:pmid:39944873"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE236877", "type": "accession_resolution", "used": ["data:geo:GSE236877"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:39944873", "parent_hash": "sha256:00346d13a69f2c739072d18e5264d15a7f7a258f7af02e3fedb1503dc10d9e64", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE236877 licence not read", "asset:data:geo:GSE236877 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "analysis", "definition_id": "regression_modelling", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["glm_logit_fit"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Multiple logistic regression analyses were employed to screen for risk factors and independent risk factors, and to establish nomogram model."], "order_basis": "analysis_only", "id": "assay:1"}]}