{"doi":"10.1101/2022.08.04.22278439","title":"Who is pregnant? defining real-world data-based pregnancy episodes in the National COVID Cohort Collaborative (N3C)","abstract":"Objective: To define pregnancy episodes and estimate gestational aging within electronic health record (EHR) data from the National COVID Cohort Collaborative (N3C). Materials and Methods: We developed a comprehensive approach, named H ierarchy and rule-based pregnancy episode I nference integrated with P regnancy P rogression S ignatures (HIPPS) and applied it to EHR data in the N3C from 1 January 2018 to 7 April 2022. HIPPS combines: 1) an extension of a previously published pregnancy episode algorithm, 2) a novel algorithm to detect gestational aging-specific signatures of a progressing pregnancy for further episode support, and 3) pregnancy start date inference. Clinicians performed validation of HIPPS on a subset of episodes. We then generated three types of pregnancy cohorts based on the level of precision for gestational aging and pregnancy outcomes for comparison of COVID-19 and other characteristics. Results: We identified 628,165 pregnant persons with 816,471 pregnancy episodes, of which 52.3% were live births, 24.4% were other outcomes (stillbirth, ectopic pregnancy, spontaneous abortions), and 23.3% had unknown outcomes. We were able to estimate start dates within one week of precision for 431,173 (52.8%) episodes. 66,019 (8.1%) episodes had incident COVID-19 during pregnancy. Across varying COVID-19 cohorts, patient characteristics were generally similar though pregnancy outcomes differed. Discussion: HIPPS provides support for pregnancy-related variables based on EHR data for researchers to define pregnancy cohorts. Our approach performed well based on clinician validation. Conclusion: We have developed a novel and robust approach for inferring pregnancy episodes and gestational aging that addresses data inconsistency and missingness in EHR data.","journal":"medRxiv","year":2022,"id":297746,"datarank":0.41720530925172783,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"self_citation_contribution":0.32958368660043297,"citation_network_contribution":0.08762162265129485,"self_endowment_contribution":0.32958368660043297,"citer_contribution":0.08762162265129485,"corpus_percentile":55.581341378510096,"corpus_rank":5743,"citation_count":8,"citer_count":4,"citers_with_citation_signal":2,"citers_with_endowment":2,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.6389,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":432001,"name":"Katie R. Bradwell","orcid":"0000-0002-9730-1808","position":1,"is_corresponding":false},{"id":49928,"name":"Lauren E Chan","orcid":"0000-0002-7463-6306","position":2,"is_corresponding":false},{"id":986275,"name":"Courtney Olson‐Chen","orcid":"0000-0003-3767-0502","position":3,"is_corresponding":false},{"id":927996,"name":"Jessica Tarleton","orcid":"0000-0001-8650-6878","position":4,"is_corresponding":false},{"id":391138,"name":"Kenneth J. Wilkins","orcid":"0000-0003-0531-7165","position":5,"is_corresponding":false},{"id":362223,"name":"Qiuyuan Qin","orcid":"0000-0002-5587-9177","position":6,"is_corresponding":false},{"id":790246,"name":"Emily A. Groene","orcid":"0000-0003-1636-7061","position":7,"is_corresponding":false},{"id":760793,"name":"Yan Kwan Lau","orcid":"0000-0002-1612-9912","position":8,"is_corresponding":false},{"id":490260,"name":"Catherine Xie","orcid":"0000-0003-1636-5509","position":9,"is_corresponding":false},{"id":973722,"name":"Yu-Han Kao","orcid":"0000-0003-2416-4395","position":10,"is_corresponding":false},{"id":986276,"name":"Michael Liebman","orcid":"0000-0002-8626-8432","position":11,"is_corresponding":false},{"id":948885,"name":"Federico Mariona","orcid":null,"position":12,"is_corresponding":false},{"id":676633,"name":"Anup P. Challa","orcid":"0000-0002-8886-7308","position":13,"is_corresponding":false},{"id":2699,"name":"Li Li","orcid":"0000-0001-6746-4297","position":14,"is_corresponding":false},{"id":59351,"name":"Sarah J. Ratcliffe","orcid":"0000-0002-6644-8284","position":15,"is_corresponding":false},{"id":49908,"name":"Julie A. McMurry","orcid":"0000-0002-9353-5498","position":16,"is_corresponding":false},{"id":4026,"name":"Melissa A Haendel","orcid":"0000-0001-9114-8737","position":17,"is_corresponding":false},{"id":404274,"name":"Rena C. Patel","orcid":"0000-0001-9893-5856","position":18,"is_corresponding":false},{"id":266572,"name":"Elaine Hill","orcid":"0000-0003-2494-317X","position":19,"is_corresponding":false},{"id":427794,"name":"Sara Jones","orcid":"0000-0003-1877-9406","position":0,"is_corresponding":true}],"reference_count":20,"raw_metadata":null,"created_at":"2026-07-19T00:31:31.270564Z","pmid":"35982668","pmcid":"PMC9387155","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":[]}