{"doi":"10.1016/j.ccrj.2026.100168","title":"Sample size requirements and intra-cluster correlations for stepped wedge cluster randomised trials in intensive care medicine: A practical guide","abstract":null,"journal":"Critical Care and Resuscitation","year":2026,"id":646856,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1631842,"name":"Diva Baggio","orcid":"0000-0002-6327-6069","position":1,"is_corresponding":false},{"id":1685005,"name":"Edward Litton","orcid":null,"position":2,"is_corresponding":false},{"id":623857,"name":"David Pilcher","orcid":"0000-0002-8939-7985","position":3,"is_corresponding":false},{"id":1363378,"name":"Paul J. Young","orcid":"0000-0002-3428-3083","position":4,"is_corresponding":false},{"id":675022,"name":"Jessica Kasza","orcid":"0000-0002-8940-0136","position":5,"is_corresponding":false},{"id":1685004,"name":"Thomas Hughes-Gooding","orcid":"0000-0001-8483-5686","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Sample size requirements and intra-cluster correlations for stepped wedge cluster randomised trials in intensive care medicine: A practical guide","abstract":"<h4>Objective</h4>To estimate key statistical parameters and provide practical guidance for planning stepped wedge cluster randomised trials in Australian and New Zealand intensive care units (ICUs).<h4>Design</h4>Cross-sectional retrospective observational study using routinely collected ICU data.<h4>Setting</h4>Adult public hospital ICUs contributing to the Australian and New Zealand Intensive Care Society Adult Patient Database between 2010 and 2023.<h4>Participants</h4>All adult ICU admissions to 132 ICUs. Subgroups included unplanned admissions and admissions involving invasive mechanical ventilation or vasopressor use.<h4>Main outcome measures</h4>In-hospital mortality during the index hospitalisation within 90 days of ICU admission. Intra-cluster correlation coefficients (ICCs) and cluster auto-correlations (CACs) were estimated using exchangeable, block-exchangeable, and discrete time decay models using a cross-sectional design.<h4>Results</h4>Among 1,291,849 eligible ICU admissions, observed mortality ranged from 10.3% (all ICU admissions) to 23.0% (non-elective invasively ventilated patients in Mega-ROX ICUs). ICCs ranged from 0.008 to 0.022 and CACs from 0.83 to 1.00, with block-exchangeable or discrete time decay models most often providing the best fit. In a worked example, a 50-ICU stepped wedge trial with 10 steps (11 two-month periods) enrolling 45 unplanned ventilated patients per ICU per period (total ≈24,750 patients) would have 81.6% power to detect an absolute mortality reduction of 2.7%.<h4>Conclusions</h4>Stepped wedge cluster randomised trials are feasible for evaluating ICU-wide interventions when routine data are available. The ICC and CAC estimates presented here provide Australian and New Zealand-specific parameters for future trial planning and demonstrate the potential of this design for pragmatic large-scale ICU research.","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"41767642","pmcid":"PMC12936732","openalex_id":null,"authors":[],"funders":[{"funder_name":"National Health and Medical Research Council","grant_id":"2033380","title":null},{"funder_name":"Health Research Council of New Zealand","grant_id":"","title":null}],"total_grants":2,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.1016/j.ccrj.2026.100168","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S1441277226000074?httpAccept=text/xml","host_type":"publisher"},{"url":"https://api.elsevier.com/content/article/PII:S1441277226000074?httpAccept=text/plain","host_type":"publisher"},{"url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12936732/","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC12936732","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC12936732?pdf=render","host_type":"Europe_PMC"}],"fields_of_study":[],"mesh_terms":[],"keywords":["Intensive care units","Sample Size Determination","Cluster Randomised Trial","Intra-cluster Correlation","Stepped Wedge Trial"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"doi"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-09T15:22:00.656906Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}