2026-10-07T01:47:17Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34002297 2026-09-26T05:58:59Z category_29890 item_type_3 month_year_09_2026

Clinical Evidence Calibration in Acute Ischemic Stroke: Derived Evidence Profiles and Independent Replication Outputs Osuke Doijiri (24913549) Statistical data science Clinical Evidence Calibration Acute Ischemic Stroke Evidence Integration Clinical Reasoning Interpretable Statistics <p dir="ltr">This dataset contains derived analytical outputs from the development and independent replication of Clinical Evidence Calibration (CEC), an interpretable statistical framework for integrating heterogeneous clinical findings on a common evidence scale.</p><p dir="ltr">CEC represents individual clinical variables as signed evidence contributions and distinguishes unique evidence, shared or overlapping evidence, synergistic interactions, and conflicting evidence. The dataset contains patient-level derived CEC scores, evidence-conflict measures, model coefficients, shared-evidence summaries, and interaction-selection stability obtained using nested cross-validation.</p><p dir="ltr">The framework was evaluated using three independently available acute ischemic stroke datasets comprising 3,073 analyzed records in total. The development analysis used a MIMIC-IV-derived acute ischemic stroke dataset (Zenodo DOI: 10.5281/zenodo.13980269). Independent replication was performed using the NS-STROKE Trial dataset (Mendeley Data DOI: 10.17632/mkf7ffnb2z.1) and the supporting dataset from Hemmati et al., PLOS ONE 2025;20(5):e0323995 (DOI: 10.1371/journal.pone.0323995).</p><p dir="ltr">The original source datasets are not redistributed in this package. This repository contains only newly generated derived analytical outputs. Users should obtain and cite the original datasets from their respective repositories or publications.</p><p dir="ltr">The replication analyses re-estimated the CEC framework within each dataset and therefore represent independent replication of the methodological framework rather than external validation of a single fixed prediction model. Interaction findings should be regarded as exploratory rather than as established biological mechanisms.</p> 2026-09-26T05:58:59Z Dataset Dataset 10.6084/m9.figshare.34002297.v1 https://figshare.com/articles/dataset/Clinical_Evidence_Calibration_in_Acute_Ischemic_Stroke_Derived_Evidence_Profiles_and_Independent_Replication_Outputs/34002297 CC BY 4.0