2025
Development and Validation of Models to Estimate the Incident Risk of Cognitive Impairment and Atherosclerotic Cardiovascular Disease in Older Adults.
Nanna M, Wojdyla D, Peterson E, Navar A, Williamson J, Colantonio L, Wang S, Jamil Y, Bertoni A, Nahid M, Damluji A, Goyal P, Chaudhry S, Gill T, Alexander K. Development and Validation of Models to Estimate the Incident Risk of Cognitive Impairment and Atherosclerotic Cardiovascular Disease in Older Adults. Journal Of The American Heart Association 2025, 14: e038949. PMID: 40401627, DOI: 10.1161/jaha.124.038949.Peer-Reviewed Original ResearchConceptsRisk of cognitive impairmentAtherosclerotic cardiovascular disease eventsAtherosclerotic cardiovascular diseaseRisk prediction modelCognitive impairmentOlder adultsMeasures of healthIncident cognitive impairmentOlder person's riskPooled Cohort EquationsCardiovascular diseaseRisk of deathCohort EquationsFramingham OffspringOlder personsExternal validationFunctional statusPersonal riskIncidence riskValidation cohortYoung adultsInternal validityFraminghamCohortTreatment decisions2024 American College of Rheumatology (ACR) Guideline for the Screening, Treatment, and Management of Lupus Nephritis
Sammaritano L, Askanase A, Bermas B, Dall'Era M, Duarte‐García A, Hiraki L, Rovin B, Son M, Alvarado A, Aranow C, Barnado A, Broder A, Brunner H, Chowdhary V, Contreras G, Felix C, Ferucci E, Gibson K, Hersh A, Izmirly P, Kalunian K, Kamen D, Rollins B, Smith B, Thomas A, Timlin H, Wallace D, Ward M, Azzam M, Bartels C, Cunha J, DeQuattro K, Fava A, Figueroa‐Parra G, Garg S, Greco J, Cuéllar‐Gutiérrez M, Iyer P, Johannemann A, Jorge A, Kasturi S, Kawtharany H, Khawandi J, Kirou K, Legge A, Liang K, Lockwood M, Sanchez‐Rodriguez A, Turgunbaev M, Williams J, Turner A, Mustafa R. 2024 American College of Rheumatology (ACR) Guideline for the Screening, Treatment, and Management of Lupus Nephritis. Arthritis & Rheumatology 2025 PMID: 40331662, DOI: 10.1002/art.43212.Peer-Reviewed Original ResearchManagement of lupus nephritisLupus nephritisAmerican College of Rheumatology (ACRTreatment decisionsLupus nephritis therapyBest practice statementsQuality of evidencePulse glucocorticoidsGlucocorticoid taperingImmunosuppressive agentsRenal responseRecommendations AssessmentNephritisAmerican CollegeVoting panelClinical situationsGRADE recommendationsIndividual patientsTherapyPractice statementsEvidence-basedPICO questionClinical questionsPICO formatSystematic literature reviewShared decision-making for multiple sclerosis using the MS-SUPPORT tool: a plain language summary
Col N, Solomon A, Alvarez E, Pbert L, Ionete C, Morales I, Chester J, Kutz C, Iwuchukwu C, Livingston T, Springmann V, Col H, Ngo L. Shared decision-making for multiple sclerosis using the MS-SUPPORT tool: a plain language summary. Neurodegenerative Disease Management 2025, 15: 97-106. PMID: 40329687, PMCID: PMC12118401, DOI: 10.1080/17582024.2025.2493028.Peer-Reviewed Original ResearchQuality of lifeMental healthDays of poor mental healthPoor mental healthMultiple sclerosisHealthcare professionalsHealthcare providersTreatment journeyPrescribed treatment planImprove communicationMS symptomsDisease-modifying therapiesTreatment planningHealthcareTreatment decisionsHealthDoctorsPlain Language SummaryCliniciansPeopleSummaryDecision-makingLanguage SummaryProvidersProfessionalsA Comparative Assessment of Molecular-Based Prognostic Models in CMML
Aguirre L, Al Ali N, Ball S, Jain A, Sallman D, Kuykendall A, Walker A, Sweet K, Lancet J, Padron E, Komrokji R. A Comparative Assessment of Molecular-Based Prognostic Models in CMML. Blood Neoplasia 2025, 100116. DOI: 10.1016/j.bneo.2025.100116.Peer-Reviewed Original ResearchChronic myelomonocytic leukemiaIPSS-MMedian overall survivalCPSS-MolMyelodysplastic syndromePrognostic accuracyCumulative incidenceChronic myelomonocytic leukemia patientsHypomethylating agent therapyIPSS-RAML evolutionAgent therapyLeukemic evolutionOverall survivalMyelomonocytic leukemiaRisk stratificationFrequent mutationsTreatment decisionsPrognostic modelPrognostic systemPatientsRisk categoriesMolecular dataRiskTreatmentEvidence-based personalised medicine in critical care: a framework for quantifying and applying individualised treatment effects in patients who are critically ill
Munroe E, Spicer A, Castellvi-Font A, Zalucky A, Dianti J, Linck E, Talisa V, Urner M, Angus D, Baedorf-Kassis E, Blette B, Bos L, Buell K, Casey J, Calfee C, Del Sorbo L, Estenssoro E, Ferguson N, Giblon R, Granholm A, Harhay M, Heath A, Hodgson C, Houle T, Jiang C, Kramer L, Lawler P, Leligdowicz A, Li F, Liu K, Maiga A, Maslove D, McArthur C, McAuley D, Neto A, Oosthuysen C, Perner A, Prescott H, Rochwerg B, Sahetya S, Samoilenko M, Schnitzer M, Seitz K, Shah F, Shankar-Hari M, Sinha P, Slutsky A, Qian E, Webb S, Young P, Zampieri F, Zarychanski R, Fan E, Semler M, Churpek M, Goligher E, investigators P, Group E. Evidence-based personalised medicine in critical care: a framework for quantifying and applying individualised treatment effects in patients who are critically ill. The Lancet Respiratory Medicine 2025, 13: 556-568. PMID: 40250459, DOI: 10.1016/s2213-2600(25)00054-2.Peer-Reviewed Original ResearchConceptsAverage treatment effectCritical careHeterogeneity of treatment effectsTreatment decisionsTreatment effectsCritical care syndromesResponse to treatmentClinical careRandomised clinical trialsCareRandomised trialsEffects of treatmentTreatment responseClinical trialsAggregate differencesPatientsOutcomesPersonalised medicineTreatmentEffect ITrialsLater midline shift is associated with better post-hospitalization discharge status after large middle cerebral artery stroke
Song J, Stafford R, Pohlmann J, Kim I, Cheekati M, Dennison S, Brush B, Chatzidakis S, Huang Q, Smirnakis S, Gilmore E, Mohammed S, Abdalkader M, Benjamin E, Dupuis J, Greer D, Ong C. Later midline shift is associated with better post-hospitalization discharge status after large middle cerebral artery stroke. Scientific Reports 2025, 15: 11738. PMID: 40188256, PMCID: PMC11972405, DOI: 10.1038/s41598-025-95954-3.Peer-Reviewed Original ResearchConceptsMiddle cerebral arteryPeak edemaMiddle cerebral artery strokeMidline shiftCerebral edemaDecompressive hemicraniectomyRetrospective study of patientsMiddle cerebral artery territory infarctionStudy of patientsDischarge statusFavorable discharge statusAssociated with higher oddsRetrospective studyTerritory infarctionCerebral arteryEdemaTreatment decisionsPatientsIschemic strokeHigher oddsMultivariate modelArtery strokeUnfavorable dischargeTwo-centerUrine Dipstick for the Diagnosis of Urinary Tract Infection in Febrile Infants Aged 2 to 6 Months.
Hunt K, Green R, Sartori L, Aronson P, Chamberlain J, Florin T, Michelson K, Monuteaux M, Chaudhari P, Nigrovic L. Urine Dipstick for the Diagnosis of Urinary Tract Infection in Febrile Infants Aged 2 to 6 Months. 2025, 155 PMID: 40122108, DOI: 10.1542/peds.2024-068671.Peer-Reviewed Original ResearchConceptsDiagnosis of urinary tract infectionUrinary tract infectionUrine WBC countUrine dipstickUrine cultureAged 2 to 6Receiver Operating CharacteristicWhite blood cellsTract infectionsColony-forming unitsUrine white blood cellsWBC countCatheterized urine culturePositive urine dipstickInitial treatment decisionsAccurate diagnostic testCross-sectional studyBacterial uropathogensFebrile infantsLaboratory urinalysisTreatment decisionsDiagnostic testsEmergency departmentUrinalysisUrineElectronic health record nudges to optimize guideline-directed medical therapy for heart failure
Fuery M, Clark K, Sikand N, Tabtabai S, Sen S, Wilson F, Desai N, Ahmad T, Samsky M. Electronic health record nudges to optimize guideline-directed medical therapy for heart failure. Heart Failure Reviews 2025, 30: 771-776. PMID: 40106122, DOI: 10.1007/s10741-025-10503-4.Peer-Reviewed Original ResearchConceptsElectronic health recordsClinical decision supportGuideline-directed medical therapyPotential of electronic health recordsElectronic health record systemsDiverse healthcare settingsGDMT adherenceCare qualityClinician workflowHealth recordsAlert contentHF careHealthcare settingsPatient careInformed treatment decisionsTargeted alertingQuality gapEnhanced usabilityImprove heart failureHeart failureDecision supportReal-timeCareTreatment decisionsAlerting strategyThe Central Vein Sign as a Radiologic Tool to Predict the Diagnosis of Radiation Necrosis in Intracranial Metastatic Cancer Patients
Antonios J, Adenu-Mensah N, Theriault B, Millares-Chavez M, Huttner A, Aboian M, Chiang V. The Central Vein Sign as a Radiologic Tool to Predict the Diagnosis of Radiation Necrosis in Intracranial Metastatic Cancer Patients. Clinical And Translational Neuroscience 2025, 9: 10. DOI: 10.3390/ctn9010010.Peer-Reviewed Original ResearchCentral vein signRadiation necrosisTumor progressionDiagnosis of radiation necrosisDifferentiate RNCerebral radiation necrosisIntracranial metastatic diseaseCancer therapy responseMetastatic cancer patientsNon-invasive markerMetastatic diseaseSurgical biopsyTherapy responsePredictive markerPatient cohortPrimary treatmentRadiological toolsCancer patientsRadiological imagingTreatment decisionsPerivascular spacesPatientsTreatmentNecrosisMarkersSerial Lactate in Clinical Medicine - A Narrative Review.
Falter F, Tisherman S, Perrino A, Kumar A, Bush S, Nordström L, Pathan N, Liu R, Mebazaa A. Serial Lactate in Clinical Medicine - A Narrative Review. Journal Of Intensive Care Medicine 2025, 8850666241303460. PMID: 39925111, DOI: 10.1177/08850666241303460.Peer-Reviewed Original ResearchResponse to therapyWarning ScoreAcute clinical areasHospital IT systemsElectronic patient recordsPoint of careNursing workforceClinical medicineDeteriorating patientsClinical areasSerial lactateMultidisciplinary groupHospital areasPrognostic guidePatient recordsLactate clearanceTreatment decisionsClinical utilityIntensive careEmergency roomPatient statusLactate levelsDisciplines of clinical medicineTherapyOperating roomProtocol of a decisional intervention for older adults with newly diagnosed acute myeloid leukemia and their caregivers: UR-GOAL 3
Loh K, Ng Q, Mohile S, Norton S, Epstein R, Sohn M, Richardson D, Jamy O, Hedjri S, Blumberg R, Nafis L, Jensen-Battaglia M, Wang Y, Mendler J, Liesveld J, Huselton E, Rodenbach R, Moore J, Maguire C, Buechler S, Hodges S, Klepin H. Protocol of a decisional intervention for older adults with newly diagnosed acute myeloid leukemia and their caregivers: UR-GOAL 3. Journal Of Geriatric Oncology 2025, 16: 102187. PMID: 39828449, PMCID: PMC11890953, DOI: 10.1016/j.jgo.2025.102187.Peer-Reviewed Original ResearchConceptsShared decision makingDecisional conflictOlder adultsAging-related conditionsOutcome measuresGoal-concordant careEducational videosAssociated with poor qualityPerceptions of prognosisReduce patient distressLife-prolonging treatmentIncreased healthcare utilizationSecondary outcome measuresAcute myeloid leukemiaValues clarification processRandomized Controlled TrialsDistress ThermometerMulticenter randomized controlled trialPrimary outcome measureTreatment decisionsCaregiver distressHealthcare utilizationReduce distressPatient distressPsychological distressFactors associated with tuberculosis treatment initiation among bacteriologically negative individuals evaluated for tuberculosis: An individual patient data meta-analysis.
Kim S, Can M, Agizew T, Auld A, Balcells M, Bjerrum S, Dheda K, Dorman S, Esmail A, Fielding K, Garcia-Basteiro A, Hanrahan C, Kebede W, Kohli M, Luetkemeyer A, Mita C, Reeve B, Silva D, Sweeney S, Theron G, Trajman A, Vassall A, Warren J, Yotebieng M, Cohen T, Menzies N. Factors associated with tuberculosis treatment initiation among bacteriologically negative individuals evaluated for tuberculosis: An individual patient data meta-analysis. PLOS Medicine 2025, 22: e1004502. PMID: 39804959, PMCID: PMC11729971, DOI: 10.1371/journal.pmed.1004502.Peer-Reviewed Original ResearchConceptsIndividual Patient Data Meta-AnalysisPatient data meta-analysisTreatment initiationData Meta-AnalysisBacteriological test resultsTB treatmentFactors associated with treatment initiationMultiple factors influence decisionsAssociated with treatment initiationTuberculosis treatment initiationMeta-analysisNegative test resultsPositive test resultsFactors influence decisionsHIV infectionPulmonary tuberculosisSmear microscopyNight sweatsClinical examinationMale sexClinical criteriaHierarchical Bayesian logistic regressionCohort studySystematic reviewTreatment decisions
2024
Practice Patterns and Trends in the Surgical Management of Mismatch Repair Deficient Colon Cancer
Gupta P, Zhan P, Leeds I, Mongiu A, Reddy V, Pantel H. Practice Patterns and Trends in the Surgical Management of Mismatch Repair Deficient Colon Cancer. Journal Of Surgical Research 2024, 304: 371-382. PMID: 39615154, DOI: 10.1016/j.jss.2024.10.041.Peer-Reviewed Original ResearchLynch syndromePractice patternsCancers associated with Lynch syndromeColorectal cancerColon cancerNonmetastatic colorectal cancerDiagnosed CRC patientsMismatch repairDetect mismatch repairSurgical managementMMR-DMMR testingCRC patientsSurgical practice patternsAssociated with decreased ratesBlack raceRate of extended resectionDNA mismatch repairMismatch repair-proficient tumorsNational Cancer DatabaseNonmetastatic CRC patientsColon cancer patientsGermline mutationsCancer patientsTreatment decisionsPATCH (Preferred Attachment Strategy for Optimal Electrocardiograms)-1 Study
Becker R, Harnett B, Wayne D, Mardis R, Meganathan K, Steen D. PATCH (Preferred Attachment Strategy for Optimal Electrocardiograms)-1 Study. Clinical Research In Cardiology 2024, 114: 497-506. PMID: 39527276, DOI: 10.1007/s00392-024-02572-6.Peer-Reviewed Original ResearchStable cardiovascular diseaseAmbulatory clinic visitsAmbulatory clinic settingCardiovascular diseaseS-ECGClinical research coordinatorsClinical indicationsClinic visitsResearch coordinatorsValvular heart diseaseCoronary artery diseaseMedical practiceParticipantsEssential hypertensionClinical settingLead placementAtrial fibrillationHeart diseaseHeart failureTreatment decisionsArtery diseaseST-TElectrocardiographyBaselineHeart rhythmManagement of Patients with Advanced Prostate Cancer. Report from the 2024 Advanced Prostate Cancer Consensus Conference (APCCC)
Gillessen S, Turco F, Davis I, Efstathiou J, Fizazi K, James N, Shore N, Small E, Smith M, Sweeney C, Tombal B, Zilli T, Agarwal N, Antonarakis E, Aparicio A, Armstrong A, Bastos D, Attard G, Axcrona K, Ayadi M, Beltran H, Bjartell A, Blanchard P, Bourlon M, Briganti A, Bulbul M, Buttigliero C, Caffo O, Castellano D, Castro E, Cheng H, Chi K, Clarke C, Clarke N, de Bono J, De Santis M, Duran I, Efstathiou E, Ekeke O, El Nahas T, Emmett L, Fanti S, Fatiregun O, Feng F, Fong P, Fonteyne V, Fossati N, George D, Gleave M, Gravis G, Halabi S, Heinrich D, Herrmann K, Hofman M, Hope T, Horvath L, Hussain M, Jereczek-Fossa B, Jones R, Joshua A, Kanesvaran R, Keizman D, Khauli R, Kramer G, Loeb S, Mahal B, Maluf F, Mateo J, Matheson D, Matikainen M, McDermott R, McKay R, Mehra N, Merseburger A, Morgans A, Morris M, Mrabti H, Mukherji D, Murphy D, Murthy V, Mutambirwa S, Nguyen P, Oh W, Ost P, O'Sullivan J, Padhani A, Parker C, Poon D, Pritchard C, Rabah D, Rathkopf D, Reiter R, Renard-Penna R, Ryan C, Saad F, Sade J, Sandhu S, Sartor O, Schaeffer E, Scher H, Sharifi N, Skoneczna I, Soule H, Spratt D, Srinivas S, Sternberg C, Suzuki H, Taplin M, Thellenberg-Karlsson C, Tilki D, Türkeri L, Uemura H, Ürün Y, Vale C, Vapiwala N, Walz J, Yamoah K, Ye D, Yu E, Zapatero A, Omlin A. Management of Patients with Advanced Prostate Cancer. Report from the 2024 Advanced Prostate Cancer Consensus Conference (APCCC). European Urology 2024, 87: 157-216. PMID: 39394013, DOI: 10.1016/j.eururo.2024.09.017.Peer-Reviewed Original ResearchConceptsAdvanced Prostate Cancer Consensus ConferenceProstate Cancer Consensus ConferenceAdvanced prostate cancerProstate cancerClinical managementLack high-level evidenceConsensus conferenceManagement of patientsHigh-level evidenceEvidence-based guidelinesModified Delphi processCancer characteristicsClinical evidenceClinical trialsImpact daily practiceTreatment decisionsWeb-based surveyConsensus questionsPC expertsPatientsMeta-analysisCancerDelphi processDaily practicePanel membersRisk of bleeding in patients with essential thrombocythemia and extreme thrombocytosis
Venkat R, Redd R, Harris A, Aryee M, Marneth A, Kamaz B, Kim C, Wazir M, Weeks L, Stahl M, DeAngelo D, Lindsley R, Luskin M, Hobbs G, How J. Risk of bleeding in patients with essential thrombocythemia and extreme thrombocytosis. Blood Advances 2024, 8: 6043-6054. PMID: 39293089, PMCID: PMC11635702, DOI: 10.1182/bloodadvances.2024013777.Peer-Reviewed Original ResearchConceptsRisk of bleedingClinically relevant nonmajor bleedingEssential thrombocythemiaBleeding riskPlatelet countCumulative incidenceDana-Farber Cancer Institute and Massachusetts General HospitalAssociated with acquired von Willebrand syndromeCumulative incidence of thrombosisCumulative incidence of bleedingIncreased bleeding riskIncidence of bleedingReduced bleeding riskVon Willebrand syndromeIncidence of thrombosisNonmajor bleedingDNMT3A mutationsMassachusetts General HospitalThrombotic eventsDana-FarberDiabetes mellitusBleedingPatientsRisk factorsTreatment decisionsPatient Perspectives on Social and Identity Factors Affecting Multiple Myeloma Care: Barriers and Opportunities
Neparidze N, Godara A, Lin D, Le H, Fixler K, Shea L, Everson S, Brittle C, Brunisholz K. Patient Perspectives on Social and Identity Factors Affecting Multiple Myeloma Care: Barriers and Opportunities. Healthcare 2024, 12: 1587. PMID: 39201146, PMCID: PMC11354118, DOI: 10.3390/healthcare12161587.Peer-Reviewed Original ResearchDisease journeyHealth care providersImprove patient supportCare providersPatient prioritiesPatient advocatesPatient perspectiveMedical appointmentsMultiple myelomaPatient supportMultiple barriersInformed treatment decisionsPrioritized needsMultidisciplinary teamTreatment adherenceDisease burdenFocus group researchComprehensive supportImprove outcomesSocial workersTreatment decisionsInsurance optionsMixing methodBurdenSupportRelationship between updated MELD and prognosis in alcohol-associated hepatitis: Opportunities for more efficient trial design
Al-Karaghouli M, Ventura-Cots M, Wong Y, Genesca J, Bosques F, Brown R, Mathurin P, Louvet A, Shawcross D, Vargas V, Verna E, Schnabl B, Caballeria J, Shah V, Kamath P, Lucey M, Garcia-Tsao G, Bataller R, Abraldes J. Relationship between updated MELD and prognosis in alcohol-associated hepatitis: Opportunities for more efficient trial design. Hepatology Communications 2024, 8: e0495. PMID: 39082963, DOI: 10.1097/hc9.0000000000000495.Peer-Reviewed Original ResearchConceptsAlcohol-associated hepatitisTrial designRandomized Controlled TrialsShort-term mortalityInclusion criteriaPredictive valuePrognostic valueControlled TrialsShort-term benefitsEfficient trial designTrial outcomesAssociated with significant mortalityCourse of AHCohort of patientsTreatment decisionsSample sizeOrdinal outcomesMortalityOrdinal scaleMELD valuesLandmark analysisTransplant allocationTrialsOutcomesTransplantationDeep learning survival model predicts outcome after intracerebral hemorrhage from initial CT scan
Chen Y, Rivier C, Mora S, Lopez V, Payabvash S, Sheth K, Harloff A, Falcone G, Rosand J, Mayerhofer E, Anderson C. Deep learning survival model predicts outcome after intracerebral hemorrhage from initial CT scan. European Stroke Journal 2024, 10: 225-235. PMID: 38880882, PMCID: PMC11569453, DOI: 10.1177/23969873241260154.Peer-Reviewed Original ResearchIntracerebral Hemorrhage ScoreNon-contrast CT scanIntracerebral hemorrhageCT scanFUNC scoreIntracerebral hemorrhage patientsNon-contrast CTFunctional impairmentSevere disabilityDependent living statusLong-term functional impairmentC-indexPrognostic toolFunctional outcomesTreatment decisionsAcute settingClinical implementationRehabilitation strategiesDependent livingPatientsPredicting functional impairmentLong-term care needsPlanning of patient careDeep learning modelsHemorrhage108TiP CINDERELLA clinical trial: Using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions
Pfob A, Bonci E, Kaidar-Person O, Antunes M, Ciani O, Cruz H, Di Micco R, Gentilini O, Heil J, Kabata P, Romariz M, Gonçalves T, Martins H, Borsoi L, Mika M, Romem N, Schinköthe T, Silva G, Bobowicz M, Cardoso M. 108TiP CINDERELLA clinical trial: Using artificial intelligence-driven healthcare to enhance breast cancer locoregional treatment decisions. ESMO Open 2024, 9: 103179. DOI: 10.1016/j.esmoop.2024.103179.Peer-Reviewed Original Research
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