{"doi":"10.1101/2021.02.25.21252410","title":"Consistency of performance of adverse outcome prediction models for hospitalized COVID-19 patients","abstract":"BACKGROUND: We previously reported and validated a risk prediction tool based on COVID-19 hospitalizations prior to June 2020. Here, we report performance of that model on subsequent data from 6 hospitals and among individual patient subgroups. METHOD: We included individuals age 18 or older hospitalized at one of 2 academic medical centers and 4 community hospitals from 6/7/2020 through 1/22/2021 with positive PCR test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within 5 days of admission. Coefficients from our previously reported least absolute shrinkage and selection operator (Lasso) risk models were applied to estimate probability of a mortality, as well as a composite severe illness outcome, including admission to the ICU, mechanical ventilation or mortality. RESULTS: Overall model performance for mortality included AUC of 0.83 (95% CI:0.80-0.87) for mortality, with a PPV 0.55 and NPV of 0.95 when using a cutoff corresponding to the highest 20% of predicted risk derived in the training set. For all adverse outcomes, AUC was 0.79 (95% CI:0.75-0.81) and PPV 0.48 and NPV 0.98 in the top 20% risk group. Model discrimination was generally similar between genders and race/ethnicity groups, but markedly poorer for younger age groups. CONCLUSION: Although the population of individuals hospitalized for COVID-19 has shifted and outcomes have improved overall, prediction models derived earlier in the pandemic may maintain utility.","journal":"medRxiv","year":2021,"id":223418,"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":0.8924,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":808901,"name":"Thomas H. McCoy","orcid":"0000-0002-5624-0439","position":1,"is_corresponding":false},{"id":254136,"name":"Roy H. Perlis","orcid":"0000-0002-5862-6757","position":2,"is_corresponding":false},{"id":274491,"name":"Víctor M. Castro","orcid":"0000-0001-7390-6354","position":0,"is_corresponding":true}],"reference_count":5,"raw_metadata":null,"created_at":"2026-07-18T23:54:11.061295Z","pmid":"33688684","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":[]}