2023
Causal Bayesian machine learning to assess treatment effect heterogeneity by dexamethasone dose for patients with COVID-19 and severe hypoxemia
Blette B, Granholm A, Li F, Shankar-Hari M, Lange T, Munch M, Møller M, Perner A, Harhay M. Causal Bayesian machine learning to assess treatment effect heterogeneity by dexamethasone dose for patients with COVID-19 and severe hypoxemia. Scientific Reports 2023, 13: 6570. PMID: 37085591, PMCID: PMC10120498, DOI: 10.1038/s41598-023-33425-3.Peer-Reviewed Original ResearchConceptsCritical COVID-19Better long-term outcomesCOVID-19Entire trial populationStandardized dosing protocolsMultiple patient characteristicsDose of dexamethasoneLong-term outcomesIL-6 inhibitorsDexamethasone doseSevere hypoxemiaMost patientsPatient characteristicsRespiratory supportDiabetes mellitusClinical outcomesDosing protocolTrial populationTreatment effect heterogeneityPatient featuresPatientsAdditional studiesDexamethasoneDoseMore evidence
2022
Effect of intravenous antihypertensives on outcomes of severe hypertension in hospitalized patients without acute target organ damage
Ghazi L, Li F, Simonov M, Yamamoto Y, Nugent J, Greenberg J, Bakhoum C, Peixoto A, Wilson F. Effect of intravenous antihypertensives on outcomes of severe hypertension in hospitalized patients without acute target organ damage. Journal Of Hypertension 2022, 41: 288-294. PMID: 36583354, PMCID: PMC9799038, DOI: 10.1097/hjh.0000000000003328.Peer-Reviewed Original ResearchConceptsAcute target organ damageTarget organ damageSevere hypertensionOrgan damageIntravenous antihypertensivesBP elevationClinical outcomesMyocardial injuryTarget end-organ damageOverlap propensity scoreSevere BP elevationAcute kidney injuryBlood pressure reductionEnd-organ damageRisk of strokeInpatient hypertensionCardiovascular eventsIndex hospitalizationKidney injuryRetrospective studyHypertensionAntihypertensivesHospitalizationCox modelPatients