{"id":"W4410513099","doi":"10.3899/jrheum.2025-0390.pv052","title":"PREDICTORS OF MECHANICAL VENTILATION IN SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS WITH CORONAVIRUS DISEASE 2019: INSIGHTS FROM NATIONAL INPATIENT DATA","year":2025,"lang":"en","type":"article","venue":"The Journal of Rheumatology","topic":"Long-Term Effects of COVID-19","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Mechanical ventilation; Coronavirus disease 2019 (COVID-19); Systemic disease; Disease; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Intensive care medicine; Lupus erythematosus; 2019-20 coronavirus outbreak; Systemic lupus erythematosus; Internal medicine; Immunology; Virology; Infectious disease (medical specialty); Antibody; Outbreak","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008026123,0.0001741264,0.000275449,0.0007544427,0.0002164491,0.000480094,0.0003173923,0.000272936,0.001229933],"category_scores_gemma":[0.003911049,0.0001651219,0.0004282462,0.00138712,0.0001024688,0.0003518761,0.0006941252,0.0004740859,0.0002321056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000371275,"about_ca_system_score_gemma":0.0004480644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009520929,"about_ca_topic_score_gemma":0.01737342,"domain_scores_codex":[0.9992648,0.0002053023,0.0001619181,0.0001175456,0.0001298222,0.0001205996],"domain_scores_gemma":[0.9969251,0.0004861015,0.001804182,0.0001176281,0.0003180293,0.0003490428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001396998,0.000006393258,0.9991646,0.000007757948,0.00001409193,0.0000103688,0.00001492739,0.00002000254,0.00001847301,0.000006265095,0.0001629212,0.0005602873],"study_design_scores_gemma":[0.000001743827,0.00001345172,0.9995021,0.000009833639,0.000007729782,0.00005388125,0.00009501961,0.0001839895,0.00001638737,0.00000724219,0.0001073778,0.000001322492],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954979,0.0002586077,0.00008153091,0.0001568347,0.000007063766,0.000008434088,0.003509301,0.000004632743,0.0004756738],"genre_scores_gemma":[0.9958398,0.0001882758,0.000109682,0.00004445213,0.00001458275,0.00001474293,0.003710116,0.000001618488,0.0000767258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009520929,"threshold_uncertainty_score":0.01893097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01483177373355871,"score_gpt":0.2870509745431494,"score_spread":0.2722192008095907,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}