Reproducibility materials for: Mapping the Rapid Growth of Post-Intensive Care Syndrome Research Across the COVID-19 Era — A Bibliometric and Thematic Analysis

Reproducibility materials for the bibliometric study "Mapping the Rapid Growth of Post-Intensive Care Syndrome Research Across the COVID-19 Era: A Bibliometric and Thematic Analysis" (Kaykaç M, Gürsoy Çirkinoğlu G). This repository contains the processed data, thesaurus files, and analysis code needed to reproduce every number, table, and figure reported in the associated manuscript. Three bibliographic databases were searched on 18–19 March 2026 (Web of Science Core Collection, Scopus, and PubMed). The Web of Science Core Collection dataset (n = 1,186 records after year filtering, 2012–2025) served as the sole analytical source for all network, subject-category, citation, era-stratified, and Callon-style thematic-map analyses; Scopus (n = 1,515) and PubMed (n = 1,072) were used only for cross-database coverage comparison. Contents: processed_aggregate_data.xlsx — all aggregate tables (annual distribution, top countries, authors, journals, cited articles, subject categories, thematic clusters, era comparison) search_strategy/ — the exact search strings for all three databases, plus the PubMed Supplementary Concept sensitivity query and result counts keyword_thesaurus.txt, country_thesaurus.txt, source_thesaurus.txt — the VOSviewer thesaurus files used to standardise author keywords, country names, and source titles analysis_scripts/ — Python scripts for the thematic analysis (parsing, descriptive counts, era stratification, keyword co-occurrence, Louvain community detection with resolution 1.0 and seed 42, Callon centrality/density, threshold sensitivity) and figure generation, with a requirements.txt listing all dependencies figure_source_data/ — CSV source data for Figures 2, 4, 5, and Supplementary Figure S1 README.md, LICENSE, CITATION.cff Note on raw data: The raw Web of Science and Scopus exports are not redistributed because of provider licensing restrictions. The repository contains processed aggregate outputs sufficient to verify the reported descriptive results and to reproduce the figures and thematic analyses; anyone with institutional database access can regenerate the source data by re-running the documented queries and applying the provided thesaurus files and code. Software: VOSviewer 1.6.20 (networks and clustering); Python 3.12 with networkx 3.6, matplotlib 3.10, pandas, numpy, openpyxl, and Pillow. License: Source code is released under the MIT License; data, tables, thesaurus files, and figure source data are released under CC BY 4.0.