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Title:
Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database
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Goodin A, Chen M, Raissi D, Han Q, Xiao H and J Brown. Patient and hospital characteristics predictive of inferior vena cava filter usage in venous thromboembolism patients: A study from the 2013 to 2014 Nationwide Readmissions Database. Medicine 2018;97:12.
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Goodin, Amie
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Wolters Kluwer
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Abstract:
Objective: To examine the association between patient and hospital characteristics and inferior vena cava filter (IVCF) utilization in patients with venous thromboembolism (VTE). Methods: The 2013 to 2014 Nationwide Readmissions Database was used to define a cohort of patients with VTE aged ≥18 after a primary VTE diagnosis. Comorbidities of interest were classified via diagnosis codes and IVCF placement was identified via procedure code. Chi square analysis tested differences between patient and hospital-level characteristics and whether or not IVCFs were placed. A hierarchical logistic regression model estimated the relationship between patient-level factors (demographics, socioeconomic status, comorbidities), hospital-level factors (bed size, teaching status, urbanity) and whether or not IVCFs were placed. Additional models were specified to examine goodness of fit across methodological alternatives. Results: There were 212,395 VTE hospitalizations, with 12.18% (n=25,877) receiving IVCF placement. There were significant differences between those who did and did not receive IVCF placement; notably, those receiving IVCFs were older (P<.001), had Medicare insurance more than private (P<.001), longer lengths of stay (P<.001), and were in privately owned hospitals (P<.001). IVCF placement remained significantly associated with patient and hospital-level characteristics following multivariate adjustment via hierarchical logistic regression; notably, age >80 (adjusted Odds Ratio [aOR]: 2.53, 95% confidence interval [CI]: 2.25–2.85), ≥13 comorbid conditions (aOR: 3.85, 95% CI: 3.25–4.27), and privately owned hospitals (aOR: 1.21, 95% CI: 1.08–1.36). Optimal goodness-of-fit was achieved with a combination of random effects and patient-level fixed effects. Discussion: These findings provide evidence that combinations of patient and hospital-level factors are related to whether patients with VTE receive IVCFs.
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Collected for University of Florida's Institutional Repository by the UFIR Self-Submittal tool. Submitted by Amie Goodin.

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Patientandhospitalcharacteristicspredictive ofinferiorvenacava lterusageinvenous thromboembolismpatientsAstudyfromthe2013to2014NationwideReadmissions DatabaseAmieGoodin,PhD,MPPa, ,MingChen,MSa,DrissRaissi,MDb,QiongHan,MD,PhDb, HongXiao,PhDa,JoshuaBrown,PharmD,PhDaAbstractToexaminetheassociationbetweenpatientandhospitalcharacteristicsandinferiorvenacava lter(IVCF)utilizationinpatientswith venousthromboembolism(VTE). The2013to2014NationwideReadmissionsDatabasewasusedtode neacohortofpatientswithVTEaged 18afteraprimary VTEdiagnosis.Comorbiditiesofinterestwereclassi edviadiagnosiscodesandIVCFplacementwasidenti edviaprocedurecode. Chisquareanalysistesteddifferencesbetweenpatientandhospital-levelcharacteristicsandwhetherornotIVCFswereplaced.A hierarchicallogisticregressionmodelestimatedtherelationshipbetweenpatient-levelfactors(demographics,socioeconomicstatus, comorbidities),hospital-levelfactors(bedsize,teachingstatus,urbanity)andwhetherornotIVCFswereplaced.Additionalmodels werespeci edtoexaminegoodnessof tacrossmethodologicalalternatives. Therewere212,395VTEhospitalizations,with12.18%(n = 25,877)receivingIVCFplacement.Thereweresigni cantdifferences betweenthosewhodidanddidnotreceiveIVCFplacement;notably,thosereceivingIVCFswereolder( P < .001),hadMedicare insurancemorethanprivate( P < .001),longerlengthsofstay( P < .001),andwereinprivatelyownedhospitals( P < .001).IVCF placementremainedsigni cantlyassociatedwithpatientandhospital-levelcharacteristicsfollowingmultivariateadjustmentvia hierarchicallogisticregression;notably,age > 80(adjustedOddsRatio[aOR]:2.53,95%con denceinterval[CI]:2.25 – 2.85), 13 comorbidconditions(aOR:3.85,95%CI:3.25 – 4.27),andprivatelyownedhospitals(aOR:1.21,95%CI:1.08 – 1.36).Optimal goodness-oftwasachievedwithacombinationofrandomeffectsandpatient-level xedeffects. These ndingsprovideevidencethatcombinationsofpatientandhospital-levelfactorsarerelatedtowhetherpatientswithVTE receiveIVCFs.Abbreviations:ACCP = AmericanCollegeofChestPhysicians,AHRQ = AgencyforHealthcareResearchandQuality,AIC = Akaikeinformationcriterion,BIC = Bayesianinformationcriterion,CI = con denceinterval,DVT = deepveinthrombosis,ICC = intraclasscorrelationcoef cient,ICD = InternationalClassi cationofDisease,IVCF = inferiorvenacava lter,NRD = Nationwide ReadmissionsDatabase,PE = pulmonaryembolism,SIR = SocietyforInterventionalRadiology,VTE = venousthromboembolism.Keywords:claimsdata,inferiorvenacava lters,venousthromboembolism1.IntroductionInferiorvenacava lters(IVCFs)maybeusedassecondary preventionaftervenousthromboembolism(VTE),andarealso usedprophylacticallyforthepreventionofpulmonaryembolism (PE)inpatientsmeetingcertainhigh-riskcriteriasuchasfailedor contraindicatedanticoagulation.[1]Despitetheincreasedriskfor VTErecurrenceafterIVCFplacement,[2,3]device-relatedcomplications,[4]andrecommendationthatindicationsforIVCFsbe “ rare ” inpatientswithdeepveinthrombosis(DVT)andPE,[5]IVCFscontinuetobeemployedprophylacticallyandtherapeuticallyinpatientswithVTE. In2005,thePREPICstudyconductedarandomizedcontrolled trialofpermanentIVCFplacementsinpatientswithDVTand followedupfor8years;itwasreportedthatIVCFsreducedPE riskbutincreasedDVT,withoverallnoeffectonsurvivalrates.[3]A2015randomizedcontrolledtrial(thePREPIC2study)of retrievableIVCFsreachedsimilarconclusions:wherepatients withVTEweregiveneitherretrievableIVCFsandanticoagulationoranticoagulationalonetherewerenodiscernible differencesinrecurrentPEafter3months.[6]EvidenceonIVCF effectivenessfromstudiesinparticularsubgroupsremainsmixed. Oneobservationalstudyin2012reportedthatin-hospital mortalityrateswerelowerinstablepatientswhoreceivedIVCFs aswellasinunstablepatientsreceivingthrombolytictherapy.[7] Editor:DannyChu. Nofundingsourcewasprovideddirectlyforthisproject.Theauthorshaveno con ictsofinteresttodisclose.aUniversityofFloridaCollegeofPharmacy,PharmaceuticalOutcomesand Policy,Gainesville,FL,bUniversityofKentuckyCollegeofMedicine,Lexington,KY.Correspondence:AmieGoodin,UniversityofFloridaCollegeofPharmacy, PharmaceuticalOutcomesandPolicy,1225CenterDr,Gainesville,FL32610 (e-mail:amie.goodin@u .edu). Copyright 2018theAuthor(s).PublishedbyWoltersKluwerHealth,Inc. ThisisanopenaccessarticledistributedundertheCreativeCommons Attribution-NoDerivativesLicense4.0,whichallowsforredistribution,commercial andnon-commercial,aslongasitispassedalongunchangedandinwhole,with credittotheauthor. Medicine(2018)97:12(e0149) Received:10October2017/Receivedin nalform:21February2018/ Accepted:27February2018 http://dx.doi.org/10.1097/MD.0000000000010149 ObservationalStudy Medicine OPEN 1

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A2014observationalstudyalsoreportedadecreaseininhospitalmortalityinunstableadultswithPEthatreceived IVCFs.[8]RecentstudiesofIVCFusageincancerpatientswithVTEhave demonstratedclinicallypooroutcomes.One2017populationbasedstudyofhospitaldischargerecordsfoundahigher180-day riskofrecurrentDVTinpatientswithcancerwhoreceived IVCFs,whereasthesepatientsreceivednoreductionofeither 180-dayPEriskor30-daymortality.[9]Another2017retrospectivecohortanalysisofcancerandnoncancerCanadianpatients foundthat21%ofIVCFplacementsoccurredinpatientswithno anticoagulationcontraindicationandthatagreaterproportionof thesepatients(31%)hadactivecancer(s)andahighshort-term mortalityrate,whichsuggestspossibleinappropriateIVCF placementinend-of-lifecaresettingsinthispopulation.[10]In addition,a2017meta-analysisofIVCFplacementsfrom randomizedcontrolledtrialsincancerandnoncancerPEpatients concludedthatthereisnoevidenceforroutineIVCFuseinthese populationsasevidencedbyalackofreductioninbothabsolute andrelativeriskafterIVCFplacement.[11]Emergingevidenceintheliteraturesuggeststhatpatientswith VTEwitheitherDVTorPEaremorelikelytoreceiveanIVCF placementiftheyhavecertaintypesofcancers,iftheyhave characteristicsdeemedhighriskforbleedingfromanticoagulationtherapies,oriftheyaretreatedinhospitalsthathavecertain characteristics.[12]Thepurposeofthisstudyistoexpandon previousworktoexaminetheassociationbetweenpatientand hospitalcharacteristicsandIVCFutilizationinpatientswithVTE usingalargesampleretrospectivecohortdesign.2.MaterialsandmethodsTheAgencyforHealthcareResearchandQuality(AHRQ)2013 and2014NationwideReadmissionsDatabase(NRD)wereused inthisretrospectivecohortstudy.TheNRDdatabaseincludes all-payeradministrativehospitaldischargeclaimsfrom21states in2013and22statesin2014withuniquepatientidenti ersto facilitatefollow-upwithineachcalendaryear,whichaccountsfor 85%ofthedischargesfromalltheStateInpatientDatabase.In additiontopatientdemographicinformation(eg,age,sex,race, andzip-codeincome),anddiagnosticandproceduralinformationfromtheNRDCoreFile,informationonseverityofillness andcomorbiditieswerealsoidenti edbylinkagesviapatient identi cationnumberintheNRDSeverityFile.Hospital characteristics(eg,bedsize,ownership,teachingstatus,rural, orurban)wereincludedfromtheNRDHospitalFileandlinked viahospitalidenti erstopatientdatawithineachcalendaryear. NRDdataaredeidenti edandpubliclyavailable;hence,this studywasdeemedexemptfrominstitutionalreviewboard review. 2.1.Studypopulation:cohortde nition Thestudycohortwasde nedasallVTEcasesinpatientsaged18 yearsandolder,basedon InternationalClassi cationofDisease Codesversion9 ( ICD-9 ),withprimarydiagnosesofeitherDVT ( ICD-9 Codes451.xxand453.xx)orPE( ICD-9 Codes415.1x). IndexhospitalizationforpatientswithVTEwasidenti edasthe rsthospitalizationwithineachcalendaryear.Electiveindex hospitalizationswereexcluded.IVCFplacementswereidenti ed by ICD-9 proceduralcode38.7atanypointinthe2013to2014 datafollowinginitialPEorDVTdiagnosis.Hospitalsthatdidnot havethecapacitytoconductIVCFplacement,de nedas performingzeroIVCFprocedureswithinthestudyperiod,were excludedtoavoidbiasofhospital-levelcharacteristics.Hospitals werealsorequiredtohaveaminimumof55VTEhospitalizations duringthestudyperiodtocalculatereliablepointestimatesand 95%con denceintervals(CIs). 2.2.Variablede nitions PatientswithVTEwerecategorizedasDVTorPEaccordingto bloodclotlocation.PatientswithDVTwerefurtherclassi edby locationofDVTtolower( ICD-9 Codes451.0x,451.1x,451.2x, 451.81,453.4,453.5,453.6),deep( ICD-9 Codes451.1x, cc451.81,453.4,453.5,453.72,453.82),proximal( ICD-9 Codes451.81,453.41,453.51),andmigrantDVT( ICD-9 Codes 453.1).Patientdemographic,admission-related,andsocioeconomicvariableswerealsoincluded.Agewascategorizedby10yearintervals,(eg,18 – 29,30 – 39,39 – 40,etc).Admissionday wascategorizedasontheweekendoronaweekday.Patient healthinsurancewasclassi edasMedicare,Medicaid,private insurance,self-pay,nocharge,orothertypeofhealthinsurance. Medianhouseholdincomewasreportedasaquartileclassi cationofthepatient ’ szipcodeofresidence.Patientlocationwas classi edinto3levels:thelargemetropolitanareas,small metropolitanareas,andthemicropolitanwithotherareas(rural). Countofchronicconditionswereaggregatedintothefollowing categories:0conditions,1to3conditions,4to6,7to9,10to12, and 13. Comorbiditymeasuresincluded28AHRQscomorbiditiesand othercomorbiditiesofinterest.AHRQcomorbiditiesandother comorbiditiesofinterestwereidenti edfromtheNRDseverity data le,andwereselectedbasedonpreviouslypublishedcoding algorithms.[13]Comorbiditiesofinterestincludedhyperlipidemia,chronicobstructivepulmonarydisorder,stroke,sepsis, infection,trauma,bleeding,thrombolysis,embolectomy,andthe “ unstable, ” whichreferstopatientswithshockorventilatoruse. Hospitalcharacteristicsincludedhospitalownership(eg, Government,non-Federal;privatelyownednon-pro t;private, investment-owned),bedsize,teachingstatus,andurban-rural designation.Bedsizeclassi cationsof “ Small ”“ Medium, ” and “ Large, ” areoperationalizedbyNRDaccordingtoacombinationofhospitallocationandteachingstatus(ie,a “ Small ” bed sizeinaruralnortheastUnitedStatesareamayhave49beds,but 49bedsisclassi edas “ Medium ” bedsizeintherural MidwesternUnitedStates).[14]Urbanandruralclassi cation werebasedonpopulationthresholdsofresidentsinthehospital county,wherecategoriesweregroupedintolargemetropolitan areas( 1millionresidents),smallmetropolitanareas(metropolitanareawith < 1millionresidents),andmicropolitanandother ruralareas. 2.3.Statisticalanalysis Bivariateanalysisviachisquareanalysiswasperformedto comparepatientandhospitalcharacteristicsbetweenIVCFusers andnonusersafterDVTorPEdiagnosisathospitalization. Bivariatetestingforanypatientcharacteristicorconditionwith < 30patientswasconductedviaFisherexacttest.Ahierarchical logisticregressionmodelwasconstructedtoanalyzevariancein thebinaryoutcomeIVCFuse,duetopatientdemographicand clinicalcharacteristicsandhospitalcharacteristicsbeingat hierarchicallevels.Adjustedoddsratiosand95%CIswere calculatedaftercontrollingforthesefactors,withapriori signi cancesetat0.05.Goodinetal.Medicine(2018)97:12 Medicine 2

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Fourhierarchicalmodelswithhospitalasrandomeffectsand potentialriskfactorsatthepatientleveland/oratthehospital levelas xedeffectswerespeci edtotestassumptionsofthe originalmodelandtoexploregoodnessof tacrossmethodologicalalternatives.Theintraclasscorrelationcoef cient(ICC) wascalculatedtoquantifythevarianceofIVCFusebetween hospitalsandwithinhospitals.ToaccountforvariationofIVCF usebyhospitals,arandomeffectsonlymodelwasbuiltasModel 1.Model2onlyincludedlevel-1(patientlevel) xedeffects,that is,thepatientcharacteristicspotentiallyassociatedwithIVCFuse as xedeffects.Model3wasrestrictedtolevel-2(hospital-level) xedeffects.Afullmodelincludingbothlevel-1andlevel-2was subsequentlyperformedasmodel4.C-statisticswereusedasa measureofdiscriminationabilitybetweenIVCFuseandnoIVCF use.Akaikeinformationcriterion(AIC)andBayesianinformationcriterion(BIC)werecalculatedtoassessthemodel tacross the5speci edhierarchicalmodels.Allanalysiswasconducted usingSASversion9.4(SASInstitute,Cary,NC).3.ResultsTherewere212,395patientswithVTEintheNRDdatabasewith aprimarydiagnosisofeitherDVT(n = 89,482)orPE(n = 122,913).Approximately12.18%(n = 25,877)oftheseunderwentIVCFplacementduringthestudyperiodandn = 186,518 didnotreceiveanIVCF.Therewere1524hospitalsthat performedatleast55IVCFprocedures,witharangeof0.60%of patientswithVTEreceivingIVCFto47.10%ofpatientswith VTEreceivingIVCFinthesehospitals.Table1providesa summaryofpatientandhospitalcharacteristics,bypatientswho Table1 Patientandhospitalcharacteristicsbyinferiorvenacava lteruseinalldeepveinthrombosisandpulmonaryembolismpatients,fromthe 2013to2014NationwideReadmissionsDatabase. Characteristics VTEpatientsreceiving VCFs(N = 25,877) VTEpatientswhodidnot receiveVCFs(N = 186,518) %Receiving VCF Patientcharacteristics(level1)n(%)n(%) P % Age 18 – 29444(1.72)7876(4.22) < .00015.34 30 – 39848(3.28)13,200(7.08)6.04 40 – 492061(7.96)22,784(12.22)8.30 50 – 593770(14.57)32,800(17.59)10.31 60 – 695432(20.99)37,907(20.32)12.53 70 – 795832(22.54)36,582(19.61)13.75 80+7490(28.94)35,369(18.96)17.48 Sex Male12,282(47.46)89,095(47.77).358112.12 Female13,595(52.54)97,423(52.23)12.25 Admissionday Workdays20,445(79.01)145,720(78.13).001312.30 Weekends5432(20.99)40,798(21.87)11.75 Insurance Medicare16,515(63.82)98,027(52.56) < .000114.42 Medicaid1982(7.66)20,119(10.79)8.97 Privateinsurance5788(22.37)51,888(27.82)10.04 Self-pay729(2.82)8614(4.62)7.80 Nocharge136(0.53)1515(0.81)8.24 Other727(2.81)6355(3.41)10.27 Medianhouseholdincome 0 – 25thpercentile7022(27.14)50,616(27.14).068812.18 26th – 50thpercentile6651(25.70)48,547(26.03)12.05 51st – 75thpercentile6106(23.60)44,707(23.97)12.02 76th – 100thpercentile6098(23.57)42,648(22.87)12.51 Patientlocation(urban/ruralstatus) Largemetropolitan15,581(60.21)109,404(58.66) < .000112.47 Smallmetropolitan7684(29.69)59,097(31.68)11.51 Micropolitan/others2612(10.09)18,017(9.66)12.66 Numberofchronicconditions 0353(1.36)7049(3.78) < .00014.77 1 – 35282(20.41)56,207(30.13)8.59 4 – 69888(38.21)68,439(36.69)12.62 7 – 96956(26.88)38,188(20.47)15.41 10 – 122672(10.33)13,161(7.06)16.88 13+726(2.81)3474(1.86)17.29 DVTtype LowerDVT21,052(81.35)97,409(52.22) < .000117.77 DeepDVT20,850(80.57)98241(52.67) < .000117.51 ProximalDVT13,286(51.34)55,161(29.57) < .000119.41 MigransDVT32(0.12)90(0.05) <.000126.23 ( continued ) Goodinetal.Medicine(2018)97:12 www.md-journal.com 3

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Table1 (continued). Characteristics VTEpatientsreceiving VCFs(N = 25,877) VTEpatientswhodidnot receiveVCFs(N = 186,518) %Receiving VCF Patientcharacteristics(level1)n(%)n(%) P % AHRQcomorbidity Acquiredimmunede ciencysyndrome67(0.26)546(0.29).34210.93 Alcoholabuse963(3.72)5899(3.16) < .000114.03 De ciencyanemia7283(28.14)38,158(20.46) < .000116.03 Rheumatoidarthritis/collagenvasculardiseases971(3.75)7013(3.76).95212.16 Chronicbloodlossanemia756(2.92)1557(0.83) < .000132.68 Congestiveheartfailure2466(9.53)21,307(11.42) < .000110.37 Chronicpulmonarydisease5600(21.64)40,308(21.61).912312.20 Coagulopathy3134(12.11)12,226(6.55) < .000120.40 Depression2848(11.01)21,515(11.54).012311.69 Diabetes,uncomplicated5501(21.26)35,799(19.19) < .000113.32 Diabeteswithchroniccomplications922(3.56)7078(3.79).066511.53 Drugabuse475(1.84)6078(3.26) < .00017.25 Hypertension,uncomplicatedandcomplicated16,224(62.7)109,133(58.51) < .000112.94 Hypothyroidism3514(13.58)23,114(12.39) < .000113.20 Liverdisease850(3.28)4802(2.57) < .000115.04 Lymphoma477(1.84)2833(1.52) < .000114.41 Fluidandelectrolytedisorders7576(29.28)37,457(20.08) < .000116.82 Metastaticcancer3006(11.62)12,482(6.69) < .000119.41 Otherneurologicaldisorders3062(11.83)15,210(8.15) < .000116.76 Obesity4591(17.74)36,827(19.74) < .000111.08 Paralysis1042(4.03)3993(2.14) < .000120.70 Peripheralvasculardisorders2013(7.78)7246(3.88) < .000121.74 Psychoses1056(4.08)8595(4.61).000110.94 Pulmonarycirculationdisorders2429(9.39)25,516(13.68) < .00018.69 Renalfailure3795(14.67)24,326(13.04) < .000113.50 Solidtumorwithoutmetastasis2171(8.39)9720(5.21) < .000118.26 Pepticulcerdiseaseexcludingbleeding15(0.06)45(0.02).003025.00 Valvulardisease1139(4.4)9835(5.27) < .000110.38 Weightloss2110(8.15)8138(4.36) < .000120.59 Othercomorbidities Hyperlipidemia9115(35.22)63,043(33.8) < .000112.63 COPD7425(28.69)48,292(25.89) < .000113.33 Stroke1485(5.74)6189(3.32) < .000119.35 Sepsis666(2.57)1835(0.98)< .000126.63 Infection/pneumonia5201(20.1)28,650(15.36) < .000115.36 Trauma852(3.29)2924(1.57) < .000122.56 Bleeding2020(7.81)3432(1.84) < .000137.05 Thrombolysis2456(9.49)4793(2.57) < .000133.88 Embolectomy332(1.28)321(0.17) < .000150.84 Unstable1054(4.07)2388(1.28) < .000130.62 Hospitalcharacteristics(level2) Bedsize Small1807(6.98)15,613(8.37) < .000110.37 Medium6765(26.14)50,992(27.34)11.71 Large17,305(66.87)119,913(64.29)12.61 Ownership Government,nonfederal2851(11.02)21,291(11.41) < .000111.81 Private,notpro t18,483(71.43)135,931(72.88)11.97 Private,invest-own4543(17.56)29,296(15.71)13.43 Urban-ruraldesignation Largemetropolitanareas16,277(62.9)112,746(60.45) < .000112.62 Smallmetropolitanareas8835(34.14)66,493(35.65)11.73 Nonmetropolitanareas765(2.96)7279(3.9)9.51 Teachingstatus Nonteaching11,134(43.03)78,359(42.01).001912.44 Teaching14,743(56.97)108,159(57.99)12.00AHRQ = AgencyforHealthcareResearchandQuality,COPD = chronicobstructivepulmonarydisorder,DVT = deepveinthrombosis,VCF = inferiorvenacava lter,VTE = venousthromboembolism.Goodinetal.Medicine(2018)97:12 Medicine 4

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underwenttheIVCFprocedureandpatientswhodidnot.In bivariateanalysis,patientswhoreceivedIVCFwereolder ( P < .001),wereadmittedonaweekdaymorefrequentlythan ontheweekend( P = .013),hadMedicaremoreoftenthanprivate insurance(63.82%IVCFMedicarevs52.56%noIVCF Medicare; P < .001),andhadagreaternumberofchronic conditions( P < .001).PatientswithDVTandPEreceivingIVCF alsoweremorelikelytobetreatedinlargemetropolitanhospitals ( P < .001),nonteachinghospitals( P < .001),andprivate,investment-ownedhospitals( P < .001),thanpatientswhodidnot receiveIVCF. Table2detailsresultsfromthehierarchicallogisticregression resultsestimatingtherelationshipbetweenpatientandhospital characteristicsassociatedwithIVCFutilization.Following multivariateadjustment,severalpatientandhospital-level characteristicsthatwereassociatedwithIVCFplacement remainedstatisticallysigni cant.PatientswithDVTandPE withprivateinsurancewere1.07timesmorelikelytoreceive Table2 Theassociationbetweeninferiorvenacava lterutilizationandpatient andhospitalcharacteristicsinpatientswithdeepveinthrombosisor pulmonaryembolism,hierarchicallogisticregression(n = 212,395). Characteristics Adjusted oddsratio95%CI Patientcharacteristics(level1) Age 18 – 29Ref.Ref. 30 – 391.060.93 – 1.20 40 – 491.31.16 – 1.46 50 – 591.491.34 – 1.67 60 – 691.751.56 – 1.95 70 – 791.911.70 – 2.15 80+2.532.25 – 2.85 Sex MaleRef.Ref. Female10.97 – 1.03 Admissionday WorkdaysRef.Ref. Weekends0.990.96 – 1.03 Insurance MedicareRef.Ref. Medicaid0.930.88 – 0.99 Privateinsurance1.071.02 – 1.12 Self-pay0.890.81 – 0.98 Nocharge0.90.74 – 1.10 Other1.020.93 – 1.11 Medianhouseholdincome 0 – 25thpercentileRef.Ref. 26th – 50thpercentile10.96 – 1.05 51st – 75thpercentile1.061.02 – 1.11 76th – 100thpercentile1.061.00 – 1.11 Patientlocation(urban/ruralstatus) Micropolitan/otherruralRef.Ref. Smallmetropolitan0.810.76 – 0.87 Largemetropolitan0.760.70 – 0.82 Numberofchronicconditions 0Ref.Ref. 1 – 31.571.40 – 1.77 4– 62.211.96 – 2.49 7 – 92.792.45 – 3.17 10 – 123.342.90 – 3.85 13+3.853.25 – 4.57 DVTType LowerDVT3.323.04 – 3.63 DeepDVT1.161.06 – 1.26 ProximalDVT1.221.18 – 1.26 MigransDVT1.631.02 – 2.59 AHRQcomorbidity Acquiredimmunede ciencysyndrome0.870.66 – 1.14 Alcoholabuse1.181.09 – 1.28 De ciencyanemias1.151.11 – 1.19 Rheumatoidarthritis/collagenvasculardiseases0.890.82 – 0.96 Chronicbloodlossanemia2.592.33 – 2.88 Congestiveheartfailure0.680.64 – 0.71 Chronicpulmonarydisease0.210.19 – 0.22 Coagulopathy1.331.26 – 1.39 Depression0.870.83 – 0.91 Diabetes,uncomplicated0.950.92 – 0.99 Diabeteswithchroniccomplications0.730.67 – 0.79 Drugabuse0.720.65 – 0.80 Hypertension,uncomplicatedandcomplicated0.880.85 – 0.91 Hypothyroidism0.920.88 – 0.96 Liverdisease1.080.99 – 1.17 Lymphoma1.030.93 – 1.15 ( continued ) Table2 (continued). Characteristics Adjusted oddsratio95%CI Fluidandelectrolytedisorders1.241.20 – 1.28 Metastaticcancer1.631.55 – 1.72 Otherneurologicaldisorders1.181.13 – 1.24 Obesity1.010.97 – 1.06 Paralysis1.351.24 – 1.48 Peripheralvasculardisorders1.911.80 – 2.04 Psychoses0.90.84 – 0.97 Pulmonarycirculationdisorders0.280.26 – 0.30 Renalfailure0.760.73 – 0.80 Solidtumorwithoutmetastasis1.661.57 – 1.75 Pepticulcerdiseaseexcludingbleeding0.610.32 – 1.16 Valvulardisease0.720.67 – 0.77 Weightloss1.191.12 – 1.26 Othercomorbidities Hyperlipidemia0.870.84 – 0.90 COPD5.14.69 – 5.55 Stroke1.171.09 – 1.27 Sepsis1.241.11 – 1.40 Infection/pneumonia1.191.14 – 1.24 Trauma2.031.86 – 2.22 Bleeding3.533.30 – 3.77 Thrombolysis3.152.97 – 3.34 Embolectomy4.453.72 – 5.33 Unstable1.961.78 – 2.15 Hospitalcharacteristics(level2) Bedsize SmallRef.Ref. Medium1.10.99 – 1.22 Large1.221.10 – 1.35 Hospitalownership Government,nonfederalRef.Ref. Private,notpro t0.960.87 – 1.06 Private,invest-own1.211.08 – 1.36 Urban-ruraldesignation NonmetropolitanareasRef.Ref. Smallmetropolitanareas1.481.26 – 1.72 Largemetropolitanareas1.691.44 – 1.99Teachingstatus NonteachingRef.Ref. Teaching0.980.91 – 1.04AHRQ = AgencyforHealthcareResearchandQuality,CI = con denceinterval,COPD = chronic obstructivepulmonarydisorder,DVT = deepveinthrombosis.Goodinetal.Medicine(2018)97:12 www.md-journal.com 5

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IVCFswhencomparedwithpatientswithMedicare(95%CI: 1.02 – 1.12),whereaspatientswithMedicaidinsurancewere7% lesslikelytoreceiveIVCFswhencomparedwithpatientswith Medicare(95%CI:0.88 – 0.99).Olderpatients,speci callythose olderthan80years,were2.53timesmorelikelytoreceiveIVCFs thanyoungerpatientsaged18to29years(95%CI:2.25 – 2.85). Patientswhohadmanychronicconditionswerealsomorelikely toreceiveIVCFs;thosewith13orgreaterconditionswere3.85 timesmorelikelytoreceiveIVCF(95%CI:3.25 – 4.57)compared topatientswithoutchronicconditions.Asolidtumorwithout metastasisdiagnosisresultedin1.66timesgreaterlikelihoodof receivingIVCFplacement(95%CI:1.57 – 1.75). Atthehospitallevel,teachingstatuswasnotasigni cant predictorofwhetherornotaDVTorPEpatientreceivedIVCF. Private,investmentownershipofahospital,however,was associatedwitha1.21timesgreaterlikelihoodofIVCF placement(95%CI:1.08 – 1.36).Largemetropolitanhospitals alsoplacedIVCFs1.69timesmoreoftenthanmicropolitan/rural hospitals(95%CI:1.44 – 1.99),asdidsmallmetropolitan hospitals(adjustedOddsRatio[aOR]:1.48;95%CI:1.26 – 1.72),andhospitalswithlargebedsizes(aOR:1.22;95%CI: 1.10 – 1.35). Table3includesacomparisonofthe tstatisticresultsfor4 model ttingmethodologies.Completeregressionresultsforeach model ttingareavailablefromtheauthors.Takenin combination,AICandBICresults(lowerscoresarebetter)also suggestthatthefullModel4,whichincluded xedeffectsfor hospitalandpatientcharacteristicsandtherandomeffects interceptforbetweenhospitalvariation,wasoptimal.Model4 also tthedatawellwithac-statisticsof0.80.Inthis nalmodel, theICCshowedthat7.51%ofthemodelvariationwasexplained bythebetweenhospitalvariation,thatis,therandomeffects intercept.4.DiscussionApreviousstudyemployingthisdesignwaslimitedtodischarge datainasinglestate(Kentucky).[13]Overall,the ndingsusing thislargercohortandnationwidedatasuggestthatpatientswith DVTandPEwhoaretreatedatlarge,investment-ownedprivate hospitalsmaybemorelikelytoreceiveanIVCFplacementthan similarpatientstreatedatsmaller,nonpro t,and/orGovernment hospitals.PatientcharacteristicssuchashavingmanycomorbiditiesarealsoassociatedwithwhetherornottheyreceiveIVCF placementandthissupports ndingsfromtheKentuckystudy. Thisstudydidnotincludeasmanycancer-relatedcomorbidities asinpreviouswork,however,whichwerefoundtobesigni cant patient-levelfactorsrelatedtoIVCFutilizationandsoshouldbe exploredinfutureanalysesusingthelarger,nationwidecohort. Inaddition,itshouldbenotedthattheoverallhospital-level factors,asgaugedbyhospital-levelrandomeffects,werefoundto beasmallercontributortovariationinIVCFutilizationwhen comparedwithpatient-levelfactorsinthisstudy.These ndings supportevidencefromthepreviousKentuckystudythatreached similarconclusionsusingasingle-stateanalysisofhospital variationinIVCFutilization,whereresidualvariationbetween hospitalIVCFutilizationrateswasreportedtobelowafter controllingforpatientcasemixandhospitalcharacteristics.[15]ThepresentstudyandthepreviousKentuckystudyshowed smallervariationthanaCalifornia-basedstudyinwhichthe between-hospitalvariationwasapproximately12%andthe rangeinIVCFusewasmoredispersed.[12]AlthoughtheNRD datadidnotpermitastate-basedanalysis,comparingtheresults implynotonlyhospitallevelvariation,butstate-basedvariation inIVCFuseaswell. AlthoughanticoagulationisthemainstayofVTEtreatment, IVCFplacementisindicatedforpatientswhenanticoagulationis contraindicated,forexample,concurrentintracranialhemorrhage,massivegastrointestinalbleed,orimminentplanned surgery,orwhenpatienthasfailedanticoagulationtherapy,for example,developmentofPEwhileonanticoagulationtherapy.[1]Inotherwords,thedecisionforIVCFplacementislargely clinical,andthetypeofpatientcohortateachinstitutionor practiceislikelytodictatethepercentageofpatientswithVTE receivingIVCFs,leadingtomuchvariationinIVCFusageacross differentinstitutions.Furthermore,thecurrentguidelineencouragestheusageoftemporaryinsteadofpermanentIVCFand lter retrievalassoonasclinicallyappropriate;[16]although,emerging evidencesuggeststhattheinitiationofanticoagulationtherapyis onlyweaklyassociatedwithtemporaryIVCFretrieval,which wouldindicatethatthereareotherbarrierstothetimelyretrieval ofIVCFsafterplacement.[17]IntheUnitedStates,thereare2majorguidelinestatementsthat addressIVCFimplantationpracticesinpatientswithVTE:the AmericanCollegeofChestPhysicians(ACCP)guidelinesonthe managementofVTEandtheSocietyforInterventional Radiology(SIR)guidelinesforthemanagementofPE.ACCP guidelinesdonotcallforprophylacticuseandonlyrecommend Table3 Comparisonof tstatisticsforhierarchicalregressionmodelingintheassociationofinferiorvenacava lterutilizationandpatientand hospitalcharacteristics. Model1Model2Model3Model4 Random effectsonly Model1+level1 xedeffects Model1+level2† xedeffects Model1+level1and level2 xedeffects Intercept(SE) 2.10(0.015)5.47(0.480) 1.82(0.046)5.72(0.481) Hospitalrandomeffects(SE)0.28(0.014)0.28(0.015)0.26(0.013)0.27(0.014) ICC(%)‡7.827.937.417.51 C-statistic0.660.800.650.80 AICx154,280.70132,038.50154,210.00131,962.70 BICx154,291.50132,406.80154,258.80132,369.00AIC = Akaikeinformationcriterion,BIC = Bayesianinformationcriterion,ICC = intraclasscorrelationcoef cient,SE = standarderror.Level1:patient-levelcharacteristics.†Level2:hospital-levelcharacteristics.‡TheICCaccountsforthevarianceofVCFusebetweenhospitalsandwithinhospitals.xAICandBICassessthemodel tbypenalizingtheadditionofparameters(eg,smallervaluesindicatebetter t).Goodinetal.Medicine(2018)97:12 Medicine 6

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IVCFplacementincasesofcontraindicationforanticoagulation.[1]SIRguidelines,however,recommendprophylacticusein patientswithVTEathighriskforbleedingand/orare contraindicatedforanticoagulationtherapy.[18]Theinconsistenciesbetweentheseintersocietalguidelines,alongwithloose adherencetothesesocietalguidelinesandtheincreasein availabilityofretrievableIVCF,allhavebeenblamedfor signi cantoveruseinIVCF.[19]Althoughtheaforementioned factorsmayplayasigni cantroleinthevariationofIVCF placementacrosstheUnitedStates,severalotherfactorsmay havebeenlargelyoverlooked.[20]IVCFusevariesfromcountryto country,amongthestateswithintheUnitedStatesandevenatthe countyleveldespiteadjustingforclinicalandsocioeconomic status.[12,21,22]Giventhattheef cacyofIVCF ltersandits impactonpatient ’ soutcomeremainahighlydebatedtopic[23]ourstudywasdesignedtoshedsomelightonpotential underlyinghospital-andpatientpopulation – relatedfactorsthat maybecontributingtowhetherpatientsreceiveornotreceive IVCFsassuggestedbyseveralarticles.[13,24]Inourstudy12.18%ofpatientswithDVTandPEreceivedan IVCFplacementduringthestudyperiod,whichisonthehigher sideoftheIVCFplacementratesreportedontheliterature.Thisis amorefrequentoccurrencethanthecurrentlyrecommended “ rare ” usageofIVCFs.[5]Ourresultsaresuggestiveofthefact thatcertain nancialfactorsmayhavesomelevelofin uenceon theratesofIVCFsplaced.PatientswithVTEwithprivate insurancearemorelikelytoreceiveIVCFs,andpatientsadmitted toinvestment-ownedprivatehospitalsarealsomorelikelytohave anIVCFplaced.These ndingsmayalsoexplainthefactthat Medicare(moregenerousreimbursementthanMedicaid)patients alsohaveahigherIVCFplacementratethantheirMedicaid counterparts;however,thiscouldbelimitedbyselectionbiasgiven thefactthattheMedicarepopulationisgenerallyolderwithoverall highercomorbiditiesandincreasedratesofabsoluteorrelative contraindicationsforanticoagulationtherapy,leadingtomore IVCFcandidatesinthispopulation.[25]Forasimilarreason,such demographicfactors,suchasolderageorMedicaidinsurance,can alsodecreasetheIVCFretrievalrate.[26]Beyond nancialfactors,expertiseavailablymayalsohavean impactonIVCFplacementratesassuggestedbythehigher placementratesinurbansettingsandduringweekdaysas comparedwithweekends.Severalnonteachinghospitalshave limitedaccesstoIVCFimplantingspecialists,andthesameistrue fornonurbanhospitals.Manyofthesepatientsendup transferredtoanotherfacilityfor lterplacement,orsimply awaitregularworkinghoursduringtheweekdays.Thesepractice patternscouldexplainsomeofthedynamicsofIVCFplacement acrossthecountry.Also,therapeuticIVCFplacementisnot usuallyconsideredaweekendemergencyandtheimplanting physicianmaydeferplacementtothe rstweekdayinmany clinicalcircumstances.Asexpected,thepresenceofmore comorbiditiesdidshowastatisticallysigni cantcorrelation withincreasedIVCFplacementrate;a “ sickercohort ” would likelyhaveoverallclusteringofunderlingVTEriskfactorssuch ascancerandalsohigherlikelihoodofhavinganticoagulation contraindications. Thereareseverallimitationswiththeanalysisandstudy design.First,follow-upaftertheinitialDVTorPEdiagnosiswas limitedtothe2013to2014studyperiod,whichmeansthat patientswithVTEmayhavereceivedanIVCFplacementatsome pointafterthestudyperiodandthesepatientswouldnotbe labeledinouranalysisasreceivingIVCF.Longitudinaltracking wasnotavailableforindividualpatientsacrosscalendaryears duetoalackofpatientidenti cationlinkagevariable,so individualpatientscanonlybeanalyzedwithinayear.No medicationusedatawereavailable;hence,wecouldnotcompare patientswhoarecontraindicatedtoanticoagulation,orpatients withanticoagulationfailure.Inaddition,patientswhoreceiveda DVTorPEdiagnosisatanNRDparticipatinghospitalmayhave receivedIVCFatahospitalthatdoesnotreportreadmission statisticstoNRD,whichwouldrenderourestimatesofIVCF usageasconservative.Therearealsolimitationswithunderreportingandmisclassi cationinherenttotheuseofadministrativedataanddiagnosis/procedurecodes,soitispossiblethat IVCFusageisconservativelyrecordedinthisdata.Also, informationonracewasnotincludedinNRDsoracecannot beexaminedusingthisdata.Theretrospectivecohortstudy designallowsfortheconstructionofahighlypoweredstatistical analysiswithlargesamplesizes,butdoespresentlimitationsto thegeneralizabilityoftheseresultsduetothepossibilityof selectionbias.Last,thedatausedfromthisstudywereentirely collectedintheUnitedStates,sogeneralizationtoIVCFusagein othercountriesislimited.5.ConclusionThisstudywasundertakentoassesswhetheracombinationof patientandhospital-levelfactorscorrelateswiththerateofIVCF placementinpatientswithVTE.The ndingsinthisstudy contributetothegrowingbodyofevidencethatIVCFsmaybe inappropriatelyemployedincertainpopulationsandthathospitals shouldevaluatetheirdisseminationofthemostrecentclinical guidelinesfortreatmentof “ high-risk ” DVTandPEpatients.This studyindicatedtheneedforadditionalresearchtoinvestigate whethertheutilizationofIVCFscouldbeexplainedbyhospital variationandpatientcharacteristicsatanationallevel.AuthorcontributionsConceptualization: A.Goodin,J.Brown. Datacuration: M.Chen. Formalanalysis: M.Chen. Methodology: A.Goodin,J.Brown. Supervision: J.Brown. Writing – originaldraft: A.Goodin. Writing – review&editing: A.Goodin,M.Chen,D.Raissi, Q.Han,H.Xiao,J.Brown.References[1]KearonC,AklEA,OrnelasJ,etal.AntithrombotictherapyforVTE disease:chestguidelineandexpertpanelreport.Chest2016;149:315 – 52. [2]NaddourM,KalaniM,HattabY,etal.Prognosisandmonitoringof VTE.CritCareNursQ2017;40:288 – 300. [3]DecoususH,Buchmuller-CordierA,CarbonnierB,etal.Eight-year follow-upofpulmonaryembolism:thePREPICrandomizedstudy. Circulation2005;112:416 – 22. [4]EverhartD,VaccaroJ,WorleyK,etal.Retrospectiveanalysisof outcomesfollowinginferiorvenacava(IVC) lterplacementina managedcarepopulation.JThrombThrombolysis2017;44:179 – 89. [5]WilburJ,ShianB.Deepvenousthrombosisandpulmonaryembolism: currenttherapy.AmFamPhysician2017;95:295 – 302. [6]MismettiP,LaporteS,PellerinO,etal.Effectofaretrievableinferior venacava lterplusanticoagulationvsanticoagulationaloneonriskof recurrentpulmonaryembolism:arandomizedclinicaltrial.JAMA 2015;313:1627 – 35. [7]SteinPD,MattaF,KeyesDC,etal.Impactofvenacava ltersoninhospitalcasefatalityratefrompulmonaryembolism.AmJMed 2012;125:478 – 84.Goodinetal.Medicine(2018)97:12 www.md-journal.com 7

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[8]SteinPD,MattaF.Venacava ltersinunstableelderlypatientswith acutepulmonaryembolism.AmJMed2014;127:222 – 5. [9]BrunsonA,HoG,WhiteR,etal.Inferiorvenacava ltersinpatientswith cancerandvenousthromboembolism(VTE)doesnotimproveclinical outcomes:apopulation-basedstudy.ThrombRes2017;153:57 – 64. [10]WassefA,LimW,WuC.Indications,complicationsandoutcomesof inferiorvenacava lters:aretrospectivestudy.ThrombRes 2017;153:123 – 8. [11]Jerjes-SanchezC,RodriguezD,NavarreteA,etal.Inferiorvenacava ltersinpulmonaryembolism:ahistoriccontroversy.ArchCardiolMex 2017;87:155 – 66. [12]WhiteRH,GeraghtyEM,BrunsonA,etal.Highvariationbetween hospitalsinvenacava lteruseforvenousthromboembolism.JAMA InternMed2013;173:506 – 12. [13]BrownJD,TalbertJC.Hospitalvariationandpatientcharacteristics associatedwithvenacava lterutilization.MedCare2017;55:31 – 6. [14]De nitionsforBedsizesofHospitalsintheNationwideReadmissions Database.Availableat:https://www.hcup-us.ahrq.gov/db/vars/hos p_bedsize/nrdnote.jsp.AccessedJuly3,2017. [15]BrownJD,TalbertJC.Variationintheuseofvenacava ltersforvenous thromboembolisminhospitalsinKentucky.JAMASurg2016;151:984 – 6. [16]SutphinPD,ReisSP,McKuneA,etal.Improvinginferiorvenacava lter retrievalrateswiththede ne,measure,analyze,improve,control methodology.JVascIntervRadiol2015;26:491.e1 – 8.e1. [17]BrownJD,RaissiD,HanQ,etal.Venacava lterretrievalratesand factorsassociatedwithretrievalinalargeUScohort.JAmHeartAssoc 2017;6:pii:e006708. [18]CaplinDM,NikolicB,KalvaSP,etal.Qualityimprovementguidelinesfor theperformanceofinferiorvenacava lterplacementforthepreventionof pulmonaryembolism.JVascIntervRadiol2011;22:1499 – 506. [19]KaufmanJA,KinneyTB,StreiffMB,etal.Guidelinesfortheuseof retrievableandconvertiblevenacava lters:reportfromtheSocietyof InterventionalRadiologymultidisciplinaryconsensusconference.JVasc IntervRadiol2006;17:449 – 59. [20]KnudsonM.Hospital-speci criskfactorsfor lterfever.JAMASurg 2013;148:687 – 8. [21]AlkhouliM,BashirR.Inferiorvenacava ltersintheUnitedStates:lessis more.IntJCardiol2014;177:742 – 3. [22]BikdeliB,WangY,MingesKE,etal.Venacaval lterutilizationand outcomesinpulmonaryembolism:Medicarehospitalizationsfrom1999 to2010.JAmCollCardiol2016;67:1027 – 35. [23]WhiteRH,ZhouH,KimJ,etal.Apopulation-basedstudyofthe effectivenessofinferiorvenacava lteruseamongpatientswithvenous thromboembolism.ArchInternMed2000;160:2033 – 41. [24]SarosiekS,CrowtherM,SloanJM.Indications,complications,and managementofinferiorvenacava lters:theexperiencein952patientsat anacademichospitalwithalevelItraumacenter.JAMAInternMed 2013;173:513 – 7. [25]PickhamDM,CallcutRA,MaggioPM,etal.Payerstatusisassociated withtheuseofprophylacticinferiorvenacava lterinhigh-risktrauma patients.Surgery2012;152:232 – 7. [26]SmithSC,ShanksC,GuyG,etal.Socialanddemographicfactors in uencinginferiorvenacava lterretrievalatasingleinstitutioninthe UnitedStates.CardiovascInterventRadiol2015;38:1186 – 91.Goodinetal.Medicine(2018)97:12 Medicine 8