2025
Nexfin versus conventional oscillometric cuff for blood pressure monitoring during neuro-endovascular procedures
Chen H, Njonkou-Tchoquessi R, Colasurdo M, Cobb C, Payabvash S, Malhotra A, Gandhi D. Nexfin versus conventional oscillometric cuff for blood pressure monitoring during neuro-endovascular procedures. Brain Circulation 2025 DOI: 10.4103/bc.bc_146_24.Peer-Reviewed Original ResearchNeuro-endovascular proceduresBlood pressureSystolic BPArterial lineNeurological injurySingle-center retrospective studyPredictive valueNegative predictive valuePositive predictive valueAcute neurological injuryBlood pressure monitoringArterial line measurementsConsecutive patientsRelative hypotensionRetrospective studyNeuro-endovascular treatmentNeuroendovascular interventionsNeuroendovascular proceduresSBP dropNexfinClinical scenariosNoninvasive blood pressureBP monitoringPatientsConventional cuffPrimary Care Physician Use of Elastic Scattering Spectroscopy on Skin Lesions Suggestive of Skin Cancer
Merry S, Croghan I, Dukes K, McCormick B, Considine G, Duvall M, Thompson C, Leffell D. Primary Care Physician Use of Elastic Scattering Spectroscopy on Skin Lesions Suggestive of Skin Cancer. Journal Of Primary Care & Community Health 2025, 16: 21501319251344423. PMID: 40470593, PMCID: PMC12144386, DOI: 10.1177/21501319251344423.Peer-Reviewed Original ResearchConceptsPrimary care physiciansElastic scattering spectroscopySkin lesionsSkin cancerPredictive valueSquamous cell cancerNegative predictive valuePositive predictive valueMulticenter pivotal studyAdjunctive diagnostic deviceCell cancerPrimary care physicians' useBiopsy specimensAdult patientsPivotal studiesKeratinocyte carcinomaDiagnostic performanceSubgroup analysisPrimary care settingHistopathological analysisCancerLesionsPatientsClinical interestAge groupsAssociation of dilated aortic root on point-of-care ultrasound with aortic aneurysm and dissection
Hesami M, Denkewicz R, Boivin Z, Bhalodkar S, Li J, Moore C. Association of dilated aortic root on point-of-care ultrasound with aortic aneurysm and dissection. The American Journal Of Emergency Medicine 2025, 95: 89-94. PMID: 40440820, DOI: 10.1016/j.ajem.2025.05.039.Peer-Reviewed Original ResearchThoracic aortic aneurysmThoracic aortic dissectionPoint-of-care ultrasound measurementsPoint-of-care ultrasoundPositive predictive valueAortic aneurysmEfficacy of point-of-care ultrasoundAccuracy of point-of-care ultrasoundDiagnostic accuracy of point-of-care ultrasoundCardiac point-of-care ultrasoundAssociated with thoracic aortic dissectionPredictive valueDilated aortic rootAssociated with thoracic aortic aneurysmAortic root measurementsLife-threatening conditionBland-Altman plotsChest CTAortic measurementsPrompt diagnosisAortic dissectionAortic rootDiagnostic accuracyPatientsMedical records0728 Predicting Sleep State from Continuous Positive Airway Pressure Flow in Patients with Obstructive Sleep Apnea
Ahsan M, Yaggi H, Anwar A, Chen H, Chen C, Zinchuk A, Wu H. 0728 Predicting Sleep State from Continuous Positive Airway Pressure Flow in Patients with Obstructive Sleep Apnea. Sleep 2025, 48: a316-a317. DOI: 10.1093/sleep/zsaf090.0728.Peer-Reviewed Original ResearchObstructive sleep apneaApnea-hypopnea indexBody mass indexNegative predictive valuePositive predictive valueResidual apnea-hypopnea indexSleep apneaObstructive sleep apnea patientsPredictive valuePositive airway pressureSleep stateFirst-line treatmentFlow signalsCPAP effectsCPAP titrationCPAP adherenceCPAP devicesCPAP levelAirway pressureSleep centerCPAPPolysomnography recordingsMass indexInclusion criteriaRespiratory rate variabilityDetection of Hypertrophic Cardiomyopathy on Electrocardiogram Using Artificial Intelligence.
Hillis J, Bizzo B, Mercaldo S, Ghatak A, MacDonald A, Halle M, Schultz A, L'Italien E, Tam V, Bart N, Moura F, Awad A, Bargiela D, Dagen S, Toland D, Blood A, Gross D, Jering K, Lopes M, Marston N, Nauffal V, Dreyer K, Scirica B, Ho C. Detection of Hypertrophic Cardiomyopathy on Electrocardiogram Using Artificial Intelligence. Circulation Heart Failure 2025, e012667. PMID: 40365710, DOI: 10.1161/circheartfailure.124.012667.Peer-Reviewed Original ResearchHypertrophic cardiomyopathyDetection of hypertrophic cardiomyopathyAssociated with significant morbidityPredictive valueNegative predictive valueArea under the curvePositive predictive valueSudden cardiac deathSignificant morbidityChart reviewCardiac deathScreening electrocardiogramDiagnostic codesCardiac imagingClinical expertisePopulation prevalenceBinary outcomesCardiomyopathyElectrocardiogramDiagnosisImprove detectionPrevalenceElectrocardiogram featuresValidity of Diagnostic Codes and Laboratory Tests to Identify Cholangiocarcinoma and Its Subtypes
Ferrante N, Hubbard R, Weinfurtner K, Mezina A, Newcomb C, Furth E, Bhattacharya D, Njei B, Taddei T, Singal A, Hoteit M, Park L, Kaplan D, Re V. Validity of Diagnostic Codes and Laboratory Tests to Identify Cholangiocarcinoma and Its Subtypes. Pharmacoepidemiology And Drug Safety 2025, 34: e70154. PMID: 40328444, PMCID: PMC12055315, DOI: 10.1002/pds.70154.Peer-Reviewed Original ResearchConceptsPositive predictive valueVeterans Health AdministrationExtrahepatic cholangiocarcinomaValidity of diagnostic codesInternational Classification of Diseases for OncologyUS Veterans Health AdministrationConfidence intervalsPharmacoepidemiological studiesICD-O-3Days of diagnosisVA dataHealth AdministrationIntrahepatic cholangiocarcinomaDiagnostic codesHistology codesCholangiocarcinomaUnique patientsInclusion criteriaCholangiocarcinoma subtypesTopography codesPredictive valuePatientsEvaluate medicationsSubtypesEvaluate determinantsImpact of Concomitant Hormone Therapy on the Diagnostic Performance of 18F‐Piflufolastat PET/CT in Prostate Cancer Patients: A Sub‐Group Analysis of OSPREY Cohort B
Saperstein L, Rowe S, Gorin M, Pienta K, Siegel B, Morris M, Baskaran S, Stambler N, DiPippo V, Denes B. Impact of Concomitant Hormone Therapy on the Diagnostic Performance of 18F‐Piflufolastat PET/CT in Prostate Cancer Patients: A Sub‐Group Analysis of OSPREY Cohort B. The Prostate 2025, 85: 1005-1015. PMID: 40320701, PMCID: PMC12211537, DOI: 10.1002/pros.24909.Peer-Reviewed Original ResearchConceptsProstate-specific antigenPositive predictive valueMetastatic prostate cancerCohort B patientsConcomitant HTConcurrent HTHormone therapyDiagnostic performanceTestosterone levelsB patientsProstate cancerCohort BBaseline serum prostate-specific antigenMedian baseline prostate-specific antigenBaseline prostate-specific antigenMedian prostate-specific antigenElevated prostate-specific antigenSerum prostate-specific antigenImpact of hormone therapyConcomitant hormonal therapySuspected local recurrenceProstate cancer patientsSub-group analysisMedian exposure durationMetastatic diseasePreoperative Multivariable Model for Risk Stratification of Hypoxemia During One-Lung Ventilation
Zorrilla-Vaca A, Grant M, Mendez-Pino L, Rehman M, Sarin P, Nasra S, Varelmann D. Preoperative Multivariable Model for Risk Stratification of Hypoxemia During One-Lung Ventilation. Anesthesia & Analgesia 2025, 140: 1029-1036. PMID: 39773746, DOI: 10.1213/ane.0000000000007306.Peer-Reviewed Original ResearchOne-lung ventilationArea under the receiver operating curveRisk of hypoxemiaIntraoperative hypoxemiaRisk stratificationClinical variablesRisk of intraoperative hypoxemiaEpisodes of oxygen desaturationBody mass index >Preoperative clinical variablesStratification modelLung perfusion scanElective lung surgeryLateral decubitus positionPositive predictive valueRetrospective cohort studyCongestive heart failureHighest Youden indexPreoperative multivariable modelLogistic regressionRisk stratification modelRight-sided surgeryMultivariate logistic regressionIncidence of hypoxemiaDouble lumen tubeUso da Inteligência Artificial Aplicada ao Eletrocardiograma para Diagnóstico de Disfunção Sistólica Ventricular Esquerda
de Santana W, Pinto M, Barreto S, Foppa M, Giatti L, Khera R, Ribeiro A. Uso da Inteligência Artificial Aplicada ao Eletrocardiograma para Diagnóstico de Disfunção Sistólica Ventricular Esquerda. Arquivos Brasileiros De Cardiologia 2025, 122: e20240740. PMID: 40396866, PMCID: PMC12108124, DOI: 10.36660/abc.20240740.Peer-Reviewed Original ResearchConceptsLeft ventricular systolic dysfunctionLeft ventricular ejection fractionNegative predictive valueDiagnostic odds ratioPositive predictive valueHeart failureDetect left-ventricular systolic dysfunctionPredictive valueVentricular systolic dysfunctionVentricular ejection fractionNegative likelihood ratioPositive likelihood ratioDiagnostic accuracy cross-sectional studyLikelihood ratioCross-sectional studySystolic dysfunctionEjection fractionEvaluating HFAUC-ROCElectrocardiographic alterationsOdds ratioEchocardiogramROC curveScreening toolElectrocardiogramA Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials
Nallapu B, Petersen K, Qian T, Demirsoy I, Ghanbarian E, Davatzikos C, Lipton R, Ezzati A, Weiner M, Aisen P, Petersen R, Weiner M, Aisen P, Petersen R, Jack C, Jagust W, Landau S, Rivera-Mindt M, Okonkwo O, Shaw L, Lee E, Toga A, Beckett L, Harvey D, Green R, Saykin A, Nho K, Perrin R, Tosun D, Sachdev P, Green R, Drake E, Montine T, Conti C, Weiner M, Nosheny R, Sacrey D, Fockler J, Miller M, Conti C, Kwang W, Jin C, Diaz A, Ashford M, Flenniken D, Kormos A, Petersen R, Aisen P, Rafii M, Raman R, Jimenez G, Donohue M, Salazar J, Fidell A, Boatwright V, Robison J, Zimmerman C, Cabrera Y, Walter S, Clanton T, Shaffer E, Webb C, Hergesheimer L, Smith S, Ogwang S, Adegoke O, Mahboubi P, Pizzola J, Jenkins C, Beckett L, Harvey D, Donohue M, Saito N, Diaz A, Hussen K, Okonkwo O, Rivera-Mindt M, Amaza H, Thao M, Parkins S, Ayo O, Glittenberg M, Hoang I, Germano K, Strong J, Weisensel T, Magana F, Thomas L, Guzman V, Ajayi A, Di Benedetto J, Talavera S, Jack C, Felmlee J, Fox N, Thompson P, DeCarli C, Forghanian-Arani A, Borowski B, Reyes C, Hedberg C, Ward C, Schwarz C, Reyes D, Gunter J, Moore-Weiss J, Kantarci K, Matoush L, Senjem M, Vemuri P, Reid R, Malone I, Thomopoulos S, Nir T, Jahanshad N, Knaack A, Fletcher E, Harvey D, Tosun-Turgut D, Chen S, Choe M, Crawford K, Yushkevich P, Das S, Jagust W, Landau S, Koeppe R, Rabinovici G, Villemagne V, LoPresti B, Perrin R, Morris J, Franklin E, Bernhardt H, Cairns N, Taylor-Reinwald L, Shaw L, Lee E, Lee V, Korecka M, Brylska M, Wan Y, Trojanowki J, Toga A, Crawford K, Neu S, Saykin A, Nho K, Foroud T, Jo T, Risacher S, Craft H, Apostolova L, Nudelman K, Faber K, Potter Z, Lacy K, Kaddurah-Daouk R, Shen L, Karlawish J, Erickson C, Grill J, Largent E, Harkins K, Weiner M, Thal L, Kachaturian Z, Frank R, Snyder P, Buckholtz N, Hsiao J, Ryan L, Molchan S, Khachaturian Z, Carrillo M, Potter W, Barnes L, Bernard M, González H, Ho C, Hsiao J, Jackson J, Masliah E, Masterman D, Okonkwo O, Perrin R, Ryan L, Silverberg N, Silbert L, Kaye J, White Salazar S, Pierce A, Thomas A, Clay T, Schwartz D, Devereux G, Taylor J, Ryan J, Nguyen M, DeCapo M, Shang Y, Schneider L, Munoz C, Ferman D, Conant C, Martin K, Oleary K, Pawluczyk S, Trejo E, Dagerman K, Teodoro L, Becerra M, Fairooz M, Garrison S, Boudreau J, Avila Y, Brewer J, Jacobson A, Gama A, Kim C, Little E, Frascino J, Ferng N, Trujillo S, Heidebrink J, Koeppe R, MacDonald S, Malyarenko D, Ziolkowski J, O'Connor J, Robert N, Lowe S, Rogers V, Petersen R, Hackenmiller B, Boeve B, Kreuger C, Jones D, Knopman D, Botha H, Magnuson J, Graff-Radford J, Crawley K, Schumacher M, McKinzie S, Smith S, Helland T, Lowe V, Ramanan V, Pavlik V, Faircloth J, Bishop J, Nath J, Chaudhary M, Kataki M, Yu M, Pacini N, Barker R, Brooks R, Aggarwal R, Honig L, Stern Y, Mintz A, Cordona J, Hernandez M, Long J, Arnold A, Groves A, Middleton A, Vogler B, McCurry C, Mayo C, Raji C, Amtashar F, Klemp H, Elmore H, Ruszkiewicz J, Kusuran J, Stewart J, Horenkamp J, Greeson J, Wever K, Vo K, Larkin K, Rao L, Schoolcraft L, Gallagher L, Paczynski M, McMillan M, Holt M, Gagliano N, Henson R, LaBarge R, Swarm R, Munie S, Cepeda S, Winterton S, Hegedus S, Wilson T, Harte T, Bonacorsi Z, Geldmacher D, Watkins A, Barger B, Smelser B, Bates C, Stover C, McKinley E, Ikner G, Hendrix H, Cooper H, Mahaffey J, Robbins L, Ashley L, Natelson-Love M, Carter P, Solomon V, Grossman H, Groome A, Ardolino A, Kaplan A, Sheppard F, Burgos-Rivera G, Garcia-Camilo G, Lim J, Neugroschl J, Jackson K, Evans K, Soleimani L, Sano M, Ghesani N, Binder S, Apuango X, Sood A, Troutman A, Blanchard K, Richards A, Nelson G, Hendrickson K, Yurko E, Plenge J, Rufo V, Shah R, Duara R, Lynch B, Chirinos C, Dittrich C, Campbell D, Mejia D, Perez G, Colvee H, Gonzalez J, Gondrez J, Knaack J, Acevedo M, Cereijo M, Greig-Custo M, Villar M, Wishnia M, Detling S, Barker W, Albert M, Moghekar A, Rodzon B, Demsky C, Pontone G, Pekar J, Farrington L, Pomper M, Johnson N, Alo T, Sadowski M, Ulysse A, Masurkar A, Marti B, Mossa D, Geesey E, Petrocca E, Schulze E, Wong J, Boonsiri J, Kenowsky S, Martinez T, Briglall V, Doraiswamy P, Nwosu A, Adhikari A, Hellegers C, Petrella J, James O, Wong T, Hawk T, Vaishnavi S, McCoubrey H, Nasrallah I, Rovere R, Maneval J, Robinson E, Rivera F, Uffelman J, Combs M, O'Donnell P, Manning S, King R, Nieto A, Glueck A, Mandal A, Swain A, Gamble B, Meacham B, Forenback D, Ross D, Cheatham E, Hartman E, Cornell G, Harp J, Ashe L, Goins L, Watts L, Yazell M, Mandal P, Buckler R, Vincent S, Rudd T, Lopez O, Malia A, Chiado C, Zik C, Ruszkiewicz J, Savage K, Fenice L, Oakley M, Tacey P, Berman S, Bowser S, Hegedus S, Saganis X, Porsteinsson A, Mathewson A, Widman A, Holvey B, Clark E, Morales E, Young I, Ruszkiewicz J, Hopkins K, Martin K, Kowalski N, Hunt R, Calzavara R, Kurvach R, D'Ambrosio S, Thai G, Vides B, Lieb B, McAdams-Ortiz C, Toso C, Mares I, Moorlach K, Liu L, Corona M, Nguyen M, Tallakson M, McDonnell M, Rangel M, Basheer N, Place P, Romero R, Tam S, Nguyen T, Thomas A, Frolov A, Khera A, Browning A, Kelley B, Dawson C, Mathews D, Most E, Phillips E, Nguyen L, Nunez M, Miller M, Jones M, Martinez N, Logan R, McColl R, Pham S, Fox T, Moore T, Levey A, Brown A, Kippels A, Ellison A, Lyons C, Hales C, Parry C, Williams C, McCorkle E, Harris G, Rose H, Jooma I, Al-Amin J, Lah J, Webster J, Swiniarski J, Chapman L, Donnelly L, Mariotti L, Locke M, Vaughn P, Penn R, Carpentier S, Yeboah S, Basadre S, Malakauskas S, Lyron S, Villinger T, Burney T, Burns J, Abusalim A, Dahlgren A, Montero A, Arthur A, Dooly H, Kreszyn K, Berner K, Gillen L, Scanlan M, Madison M, Mathis N, Switzer P, Townley R, Fikru S, Sullivan S, Wright E, Beigi M, Daley A, Ko A, Luong B, Nyborg G, Morales J, Durbin K, Garcia L, Parand L, Macias L, Monserratt L, Farchi M, Wu P, Hernandez R, Rodriguez T, Graff-Radford N, Marolt A, Thomas A, Aloszka D, Moncayo E, Westerhold E, Day G, Chrestensen K, Imhansiemhonehi M, McKinzie S, Stephens S, Grant S, Brosch J, Perkins A, Saunders A, Kovac D, Polson H, Mwaura I, Mejia K, Britt K, King K, Nichols K, Lawrence K, RankinW L, Farlow M, Wiesenauer P, Bryant R, Herring S, Lynch S, Wilson S, Day T, Korst W, van Dyck C, Mecca A, Miller A, Brennan A, Khan A, Ruan A, Gunnoud C, Mendonca C, Raynes-Goldfinger D, Salardini E, Hidalgo E, Cooper E, Singh E, Murphy E, May J, Stanhope J, Lam J, Waszak J, Nelsen K, Sacaza K, Hasbani M, Donahue M, Chen M, Barcelos N, Eigenberger P, Bonomi R, O'Dell R, Jefferson S, Khasnavis S, Smilowitz S, DeStefano S, Good S, Camarro T, Clayton V, Cavrel Y, Lu Y, Chertkow H, Bergman H, Hosein C, Black S, Kapadia A, Bhan A, Lam B, Scottc C, Gabriel G, Bray J, Zotovic L, Gutierrez M, Masellis M, Farshadi M, Gui M, Mitchellc M, Taylor R, Endre R, Taghi-Zada Z, Hsiung R, English C, Kim E, Yau E, Tong H, Barlow L, Jennings L, Assaly M, Nunes P, Marian T, Kertesz A, Rogers J, Trost D, Wint D, Bernick C, Munic D, Grant I, Korkoyah A, Raja A, Lapins A, Ryan C, Pejic J, Basham K, Lukose L, Haddad L, Quinlan L, Houghtaling N, Sadowsky C, Martinez W, Villena T, Reynolds B, Forero A, Ward C, Brennan E, Figueroa E, Esposito G, Mallory J, Johnson K, Turner K, Seidenberg K, McCann K, Bassett M, Chadwick M, Turner R, Bean R, Sharma S, Marshall G, Haviari A, Pietras A, Wallace B, Munro C, Rivera-Delpin G, Hustead H, Levesque I, Ramirez J, Nolan K, Glennon K, Palou M, Erkkinen M, DaSilva N, Friedman P, Silver R, Salazar R, Polleys R, McGinnis S, Gale S, Hall T, Luu T, Chao S, Lin E, Coleman J, Epperson K, Vasanawala M, Atri A, Rangel A, Evans B, Monarrez C, Cline C, Liebsack C, Bandy D, Goldfarb D, Intorcia D, Olgin J, Clark K, King K, York K, Reade M, Callan M, Glass M, Johnson M, Gutierrez M, Goddard M, Trncic N, Choudhury P, Reyes P, Lowery S, Hall S, Olgin S, de Santiago S, Alosco M, Ton A, Jimenez A, Ellison A, Tran A, Anderson B, Carter D, Veronelli D, Lenio S, Steinberg E, Mez J, Weller J, Johns J, Mez J, Harkins J, Puleio A, Hoti I, Mwicigi J, Puleio A, Alosco M, Schultz O, Lauture M, Steinberg E, Denis R, Killiany R, Singh S, Lenio S, Qiu W, Devis Y, Obisesan T, Stone A, Ordor D, Udodong I, Okonkwo I, Khan J, Turner J, Hughes K, Kadiri O, Duffy C, Moss A, Stapleton K, Toth M, Sanders M, Ayres M, Hamski M, Fatica P, Ogrocki P, Ash S, Pot S, Chen D, Soto A, Tanase C, Bissig D, Vanya H, Russell H, Patel H, Zhang H, Wallace K, Ayers K, Gallegos M, Forloines M, Sinn M, Kahulugan Q, Isip R, Calderon S, Hamm T, Borrie M, Lee T, Bartha R, Johnson S, Asthana S, Carlsson C, Perrin A, Tariot P, Fleisher A, Reeder S, Capote H, Emborsky A, Mattle A, Ajtai B, Wagner B, Myers B, Slazyk D, Fragale D, Fransen E, Macnamara H, Falletta J, Hirtreiter J, Mechtler L, King M, Asbach M, Rainka M, Zawislak R, Wisniewski S, O'Malley S, Jimenez-Knight T, Peehler T, Aladeen T, Bates V, Wenner V, Elmalik W, Scharre D, Ramamurthy A, Bouchachi S, Kataki M, Tarawneh R, Kelley B, Celmins D, Leader A, Figueroa C, Bauerle H, Patterson K, Reposa M, Presto S, Ahmed T, Stewart W, Pearlson G, Blank K, Anderson K, Santulli R, Schwartz E, Williamson J, Jessup A, Williams A, Duncan C, O'Connell A, Gagnon K, Zamora E, Bateman J, Crawford F, Thompson D, Walker E, Rowell J, White M, Ledford P, Bohlman S, Henkle S, Bottoms J, Moretz L, Hoover B, Shannon M, Rogers S, Baker W, Harrison W, Wu C, DeMarco A, Stipanovich A, Arcuri D, Clark J, Davis J, Doyon K, Amoyaw M, Acosta M, Bailey R, Warren S, Fogerty T, Sanborn V, Hospital B, Riddle M, Salloway S, Malloy P, Correia S, Windon C, Blackburn M, Rosen H, Miller B, Smith A, Mba I, Echevarria J, Janavs J, Roglaski E, Yong M, Devine R, Okhravi H, Rivera E, Kalowsky T, Smith C, Rosario C, Masdeu J, Le R, Gurung M, Sabbagh M, Garcia A, Slaughter M, Elayan N, Acothley S, Pomara N, Hernando R, Pomara V, Reichert C, Brawman-Mintzer O, Acree A, Williams A, Long C, Long R, Newhouse P, Hill S, Boegel A, Seshadri S, Saklad A, Jones F, Hu W, Sotelo V, Rojas Y, Mintzer J, Longmire C, Spicer K. A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials. Neurology 2025, 104: e213490. PMID: 40132145, DOI: 10.1212/wnl.0000000000213490.Peer-Reviewed Original ResearchConceptsClinically meaningful cognitive declineAlzheimer's Disease Neuroimaging InitiativeCognitive declineAD clinical trialsAlzheimer's Disease Neuroimaging Initiative participantsBase prevalencePredicting cognitive declineAlzheimer's diseaseNeuropsychological testsPlacebo armValidation sampleAlzheimer's disease clinical trialsIndependent validation samplePositive predictive valueDetect treatment effectsTreatment trialsVolumetric MRIPlacebo treatmentMild dementiaAmyloid burdenAD trialsInternal validation sampleParticipantsTreatment effectsAPOE genotypeA computable electronic health record ARDS classifier recapitulates an association between the MUC5B promoter polymorphism and ARDS in critically ill adults.
Kerchberger V, McNeil J, Zheng N, Chang D, Rosenberger C, Rogers A, Bastarache J, Feng Q, Wei W, Ware L. A computable electronic health record ARDS classifier recapitulates an association between the MUC5B promoter polymorphism and ARDS in critically ill adults. CHEST Critical Care 2025, 100150. DOI: 10.1016/j.chstcc.2025.100150.Peer-Reviewed Original ResearchElectronic health recordsCritically ill adultsElectronic health record dataMUC5B promoter polymorphismIll adultsAt-risk adultsNegative predictive valuePositive predictive valueDiagnostic billing codesHealth recordsHospital participationGenetic risk factorsDNA biobanksBilling codesBioVUStudy designPromoter polymorphismCohort of critically ill adultsAt-riskCohen's kappaModerate agreementRisk factorsGenotyped cohortPredictive valueBiobankPrognosis of p16 and Human Papillomavirus Discordant Oropharyngeal Cancers and the Exploration of Using Natural Language Processing to Analyze Free-Text Pathology Reports
Shin E, Choi J, Hung T, Poon C, Riaz N, Yu Y, Kang J. Prognosis of p16 and Human Papillomavirus Discordant Oropharyngeal Cancers and the Exploration of Using Natural Language Processing to Analyze Free-Text Pathology Reports. JCO Clinical Cancer Informatics 2025, 9: e2400177. PMID: 39965177, DOI: 10.1200/cci-24-00177.Peer-Reviewed Original ResearchConceptsProgression-free survivalCancer-specific survivalOropharyngeal cancerHPV testingPathology reportsTreatment de-escalationCurative radiation therapyHPV+ oropharyngeal cancerPrimary end pointMinority of patientsPositive predictive valueStandard-of-careCancer-related deathsIn situ hybridizationStatistically significant differenceP16 statusP16-negativeHPV statusRadiation therapyInferior prognosisOverall survivalConsecutive patientsAcademic cancer centerDiscordant tumorsTreatment deintensificationIsolated subsegmental pulmonary embolism identification based on international classification of diseases (ICD)-10 codes and imaging reports
Rashedi S, Bejjani A, Hunsaker A, Aghayev A, Khairani C, McGonagle B, Lo Y, Mahajan S, Caraballo C, Jimenez J, Krishnathasan D, Zarghami M, Monreal M, Barco S, Secemsky E, Klok F, Muriel A, Hussain M, Appah-Sampong A, Rahaghi F, Sadeghipour P, Lin Z, Mojibian H, Aneja S, Konstantinides S, Goldhaber S, Wang L, Zhou L, Jimenez D, Krumholz H, Piazza G, Bikdeli B, Investigators T. Isolated subsegmental pulmonary embolism identification based on international classification of diseases (ICD)-10 codes and imaging reports. Thrombosis Research 2025, 247: 109271. PMID: 39862754, DOI: 10.1016/j.thromres.2025.109271.Peer-Reviewed Original ResearchInternational Classification of Diseases (ICD)-10 codesICD-10International ClassificationPositive predictive valueDischarge diagnosisAccuracy of ICD-10Radiology reportsPrincipal discharge diagnosisSecondary discharge diagnosisIsolated subsegmental pulmonary embolismMedical records of adult patientsHealth systemRecords of adult patientsPredictive valueBlinded re-evaluationExpert radiologistsSubsegmental pulmonary embolismQuality improvementMedical recordsChart reviewPresence of PEProximal PEPulmonary embolismAdult patientsImaging Reporting
2024
Accuracy of a Rapid-Response EEG's Automated Seizure-Burden Estimator
Sheikh Z, Dhakar M, Fong M, Fang W, Ayub N, Molino J, Haider H, Foreman B, Gilmore E, Mizrahi M, Karakis I, Schmitt S, Osman G, Yoo J, Hirsch L. Accuracy of a Rapid-Response EEG's Automated Seizure-Burden Estimator. Neurology 2024, 104: e210234. PMID: 39724534, DOI: 10.1212/wnl.0000000000210234.Peer-Reviewed Original ResearchConceptsElectrographic status epilepticusNegative predictive valueStatus epilepticusTreat nonconvulsive status epilepticusPredictive valueCo-primary outcome measuresNonconvulsive status epilepticusPositive predictive valueRetrospective observational studyClass II evidenceLow-to-moderate sensitivityLimited-resource settingsII evidenceTriage patientsObservational studyPatientsRegional hospitalOutcome measuresExpert reviewEpilepticusScreening toolCommunity hospitalBurden estimatesEEGPPVQuantitative susceptibility mapping is more sensitive and specific than phase imaging in detecting chronic active multiple sclerosis lesion rims: pathological validation
Gillen K, Nguyen T, Dimov A, Kovanlikaya I, Luu H, Demmon E, Markowitz D, Bagnato F, Pitt D, Gauthier S, Wang Y. Quantitative susceptibility mapping is more sensitive and specific than phase imaging in detecting chronic active multiple sclerosis lesion rims: pathological validation. Brain Communications 2024, 7: fcaf011. PMID: 39916751, PMCID: PMC11800486, DOI: 10.1093/braincomms/fcaf011.Peer-Reviewed Original ResearchPhase imagesQuantitative susceptibility mappingPerls' stainPredictive valueLesion rimFrequency of clinical relapsesNegative predictive valuePositive predictive valuePathological validationDecreased brain volumeProgression to disabilityQuantitative susceptibility mapping imagesClinical relapseBrain volumeMicroglial markersGold standardLesionsMultiple sclerosis lesionsParamagnetic rimMap imagesNatural Language Processing to Identify Infants Aged 90 Days and Younger With Fevers Prior to Presentation.
Aronson P, Kuppermann N, Mahajan P, Nielsen B, Olsen C, Meeks H, Grundmeier R. Natural Language Processing to Identify Infants Aged 90 Days and Younger With Fevers Prior to Presentation. Hospital Pediatrics 2024, 15: e1-e5. PMID: 39679596, PMCID: PMC12163744, DOI: 10.1542/hpeds.2024-008051.Peer-Reviewed Original ResearchElectronic health recordsEmergency departmentNatural language processing algorithmsElectronic health record dataPediatric Emergency Care Applied Research Network RegistryFebrile infantsNatural language processingCross-sectional studyTrauma-related diagnosesPositive predictive valueHealth recordsHealth systemDocumented feverClinical notesPre-EDNetwork registryCohort identificationVisitsLanguage processingNLP algorithmsPredictive valueInfantsFeverResearch studiesEnhancing Histology Detection in MASH Cirrhosis for Artificial Intelligence Pathology Platform by Expert Pathologist Training
Goodman Z, Akbary K, Noureddin M, Ren Y, Chng E, Tai D, Boudes P, Garcia‐Tsao G, Harrison S, Chalasani N. Enhancing Histology Detection in MASH Cirrhosis for Artificial Intelligence Pathology Platform by Expert Pathologist Training. Liver International Communications 2024, 5 DOI: 10.1002/lci2.70007.Peer-Reviewed Original ResearchArtificial intelligenceAI modelsPositive predictive valuePathologist annotationsSmooth muscle actinLiver biopsyValidation cohortNodule annotationsPre-trainingRe-trainingHistopathological assessmentPathologist trainingAnnotationAssessment of liver biopsiesImproved accuracySirius RedAlgorithmHistopathological assessment of liver biopsiesExpert hepatopathologistsArtificialComparison of the GoCheck Kids and Spot Screener photoscreening devices for the detection of amblyopia risk factors using 2021 AAPOS recommendations
Applebaum S, Sopeyin A, Mohamedali A, Walsh E, Rotruck J, Njike V, Howard M. Comparison of the GoCheck Kids and Spot Screener photoscreening devices for the detection of amblyopia risk factors using 2021 AAPOS recommendations. Journal Of American Association For Pediatric Ophthalmology And Strabismus 2024, 28: 104035. PMID: 39528078, DOI: 10.1016/j.jaapos.2024.104035.Peer-Reviewed Original ResearchAmblyopia risk factorsComplete eye examinationPositive predictive valueAAPOS guidelinesVision screeningDetection of amblyopia risk factorsPediatric vision screeningFailed vision screeningReceiver operating characteristicRisk factorsPhotoscreening devicesPediatric ophthalmologistsAAPOSEye examinationPrimary outcomeStatistically significant differencePredictive valueGuidelinesSignificant differenceParticipantsPhotoscreeningStrabismusScreeningYearsOperating characteristicsValidating International Classification of Diseases Code 10th Revision algorithms for accurate identification of pulmonary embolism
Bikdeli B, Khairani C, Bejjani A, Lo Y, Mahajan S, Caraballo C, Jimenez J, Krishnathasan D, Zarghami M, Rashedi S, Jimenez D, Barco S, Secemsky E, Klok F, Hunsaker A, Aghayev A, Muriel A, Hussain M, Appah-Sampong A, Lu Y, Lin Z, Mojibian H, Aneja S, Khera R, Konstantinides S, Goldhaber S, Wang L, Zhou L, Monreal M, Piazza G, Krumholz H, Investigators P. Validating International Classification of Diseases Code 10th Revision algorithms for accurate identification of pulmonary embolism. Journal Of Thrombosis And Haemostasis 2024, 23: 556-564. PMID: 39505153, DOI: 10.1016/j.jtha.2024.10.013.Peer-Reviewed Original ResearchDischarge codesInternational ClassificationICD-10Yale New Haven Health SystemPositive predictive valueMass General Brigham hospitalsAccuracy of ICD-10ICD-10 codesPulmonary embolismHealth systemImage codingElectronic databasesF1 scorePre-specified protocolExcellent positive predictive valueIndependent physiciansHighest F1 scoreIdentification of pulmonary embolismAcute pulmonary embolismSecondary codePE codesScoresIdentified PERevised algorithmA Validated Algorithm to Identify Hepatic Decompensation in the Veterans Health Administration Electronic Health Record System
Haque L, Tate J, Chew M, Caniglia E, Taddei T, Re V. A Validated Algorithm to Identify Hepatic Decompensation in the Veterans Health Administration Electronic Health Record System. Pharmacoepidemiology And Drug Safety 2024, 33: e70024. PMID: 39477692, PMCID: PMC11631147, DOI: 10.1002/pds.70024.Peer-Reviewed Original ResearchConceptsVeterans Health Administration dataHealth administrative dataAdministrative dataElectronic health record systemsHealth record systemsInternational Classification of DiseasesCoding algorithmOutpatient International Classification of DiseasesPositive predictive valueClassification of DiseasesHepatic decompensationDiagnosis codesPharmacoepidemiologic researchMedical recordsVeteransRecording systemValidation algorithmAlgorithmChronic liver diseaseDecompensationLiver diseasePredictive valueRecordsDiagnosis
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