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A broad-spectrum beta-lactam-sparing stewardship program in a middle-income country public hospital: antibiotic use and expenditure outcomes and antimicrobial susceptibility profiles

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brazjinfectdis2020;24(3):221–230

w w w . e l s e v i e r . c o m / l o c a t e / b j i d

The

Brazilian

Journal

of

INFECTIOUS

DISEASES

Original

article

A

broad-spectrum

beta-lactam-sparing

stewardship

program

in

a

middle-income

country

public

hospital:

antibiotic

use

and

expenditure

outcomes

and

antimicrobial

susceptibility

profiles

Tiago

Zequinao

a

,

Juliano

Gasparetto

a

,

Dayana

dos

Santos

Oliveira

a

,

Gabriel

Takahara

Silva

a

,

João

Paulo

Telles

b,c

,

Felipe

Francisco

Tuon

b,∗

aSchoolofMedicine,PontifíciaUniversidadeCatólicadoParaná,Curitiba,PR,Brazil

bLaboratoryofEmergingInfectiousDiseases,PontifíciaUniversidadeCatólicadoParaná,Curitiba,PR,Brazil cACCamargoCancerCenter,SãoPaulo,SP,Brazil

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received18January2020 Accepted7May2020 Availableonline3June2020

Keywords: Antimicrobialstewardship Hospitalsetting Tertiarycare Traumaemergency Middle-incomecountry

a

b

s

t

r

a

c

t

Background:Antimicrobialstewardshipprogramsareanefficientwaytoreduce inappropri-ateuseofantimicrobialsandcosts;however,supportingdataarescarceinmiddle-income countries. Theaim ofthisstudy wastoevaluate antibioticuse, bacterialsusceptibility profiles,andtheeconomicimpactfollowingimplementation ofa broad-spectrum beta-lactam-sparingantimicrobialstewardshipprogram.

Methods:An interrupted time-seriesanalysis was performed toevaluate antibiotic use and expenditureovera 24-monthperiod (12monthsbeforetheantimicrobial steward-shipprogramandinthe12monthsafterimplementationoftheantimicrobialstewardship program).Antibioticswereclassifiedintooneoftwogroups:beta-lactamantibioticsand beta-lactam-sparingantibiotics.Wealsocomparedtheantimicrobialsusceptibilityprofiles ofkeypathogensineachperiod.

Results:Beta-lactam antibiotics use decreased by 43.04 days of therapy/1000 patient-days(p=0.04)immediatelyfollowingantimicrobialstewardshipprogramimplementation, whereasbeta-lacta-sparingantibioticsuseincreasedduringtheinterventionperiod(slope change6.17daysoftherapy/1000patient-days,p<0.001).Expendituredecreasedby$2089.99 (p<0.001)immediatelyafterinterventionandwasmaintainedatthisleveloverthe inter-ventionperiod($−38.45;p=0.24).Wealsoobservedthatagreaterproportionofpathogens weresusceptibletocephalosporinsandaminoglycosidesaftertheantimicrobial steward-shipprogram.

Conclusions: The antimicrobial stewardship program significantly reduced the use of broad-spectrum beta-lactam-antibiotics associated witha decrease in expenditureand maintenanceofthesusceptibilityprofileinGram-negativebacteria.

©2020SociedadeBrasileiradeInfectologia.PublishedbyElsevierEspa ˜na,S.L.U.Thisis anopenaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/ licenses/by-nc-nd/4.0/). ∗ Correspondingauthor.

E-mailaddress:felipe.tuon@pucpr.br(F.F.Tuon). https://doi.org/10.1016/j.bjid.2020.05.005

1413-8670/©2020SociedadeBrasileiradeInfectologia.PublishedbyElsevierEspa ˜na,S.L.U.ThisisanopenaccessarticleundertheCC BY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.0/).

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and SouthAfrica; alsoreferred toas BRICS) accounted for three-quartersoftheglobalincreaseinantibiotic consump-tion inthepastdecade.5 However,onlyasmallnumber of

studieshaveexaminedstrategiestoimproveantibiotic con-sumptioninthesecountries.6,7

Thehighprevalenceofextended-spectrumbeta-lactamase (ESBL)-producing bacteria in hospitals has been observed worldwide.TheprevalenceofESBL-producingEscherichiacoli

andKlebsiellapneumoniaereached17.6%and38.9%inEurope, 8.5%and8.8%inUS,40.8%and21.5%intheAsia-Pacificregion, and 26.8% and 37.7% in South America, respectively.8–10 Consequently,consumptionof“last-resort”antibiotics,such as carbapenems and polymyxins, has increased. Between 2000and2010,theglobalconsumptionofcarbapenemsand polymyxinsincreasedby45%and13%,respectively,5followed

byanincreasingtrenduntil2015.11However,antibiotic

con-sumptionisadeterminantdriverforAMR.12–16

Strategies such as antimicrobial stewardship programs (ASP)appeartobeanefficientwaytoimprove clinicaland microbialoutcomes;suchprogramsaimtoreducethe inade-quateuseofantibioticsandtheassociatedexpenditure.17,18

The aim of this study was to evaluate antibiotic use, the associatedcosts,andthebacterialsusceptibilityprofilesafter implementation of a broad-spectrum beta-lactam-sparing ASP.

Methods

Studydesignandsetting

Thiswas asingle-center,retrospective time-series analysis studyfollowingimplementationofanASPandtheevaluation oftheassociatedimpactonantibioticuse,expenditure,and antimicrobialsusceptibility.Thestudywasconductedthrough aperiodof24months(pre-interventionperiod,July1,2016to June30,2017;andinterventionperiod,August1,2017toJuly 31,2018)atHospitalUniversitárioCajuru(HUC).HUC,inthe cityofCuritiba,Brazil,isa207-bed,tertiarycare,medicaland surgicalacademicteaching hospital,isareferralcenter for traumapatientswithapproximately1100inpatientsand4800 patient-dayspermonth.

Antimicrobialstewardshipprogram

Priortoimplementationofthe ASP,the conceptofrational antibioticusehadalreadyinfluencedstandardpracticeinour

1),and withdrewunnecessaryantibioticsfrom thehospital formulary.A prospectiveauditing andfeedback processfor allantimicrobialprescriptionswasadoptedand,ifnecessary, interventionwasinitiatedwithin24h.TheASPteamworked full-timewiththeclinicalpharmacistandpart-timewiththe infectious disease physicianduring regular officehours on weekdays.Patientsreceivingantibioticswereincludedinthe ASP analysisthroughelectronic datafrom the prescription system.Dose,lengthoftreatmentadjustment,de-escalation, route ofadministration, and side effects were determined undertheguidanceofaclinicalpharmacist.

Theprotocolforempiricaltreatmentofinfectionscaused by Gram-negative bacteria outlines the substitution of beta-lactam antibiotics (BLAs: carbapenems, piperacillin-tazobactam,or thirdand fourth-generationcephalosporins) forbeta-lactam-sparingantibiotics(BLSAs:aminoglycosides orfluoroquinolones).Theseoptionswere basedonthe sus-ceptibilityprofiles to mostlocalGram-negativebacteria. In addition, BLSAsare less expensivethanBLAs, and alterna-tive formulations offluoroquinolones are availablefororal administration.

Assessmentandoutcomes

The primary endpoint was monthly use of antibiotics expressedasdaysoftherapyper1000patient-days(DOT/1000 patient-days) for both the restricted antibiotics (BLA) and theBLSA19periods.Asasecondaryoutcome,monthly

ATM-related coststo the hospitalpharmacyfor thesegroupsof antibioticswasanalyzed.Weusedtheaveragevialortablet purchasecostinUnitedStatesdollars(USD)foreachantibiotic inthetwoperiods.Acomparativeanalysisoftheaverageuse andcostofeachclassofantibioticswasperformedbetween thetwoperiods.Inaddition,thesusceptibilityprofilestoeach of these antibiotics (carbapenems, piperacillin-tazobactam, thirdandfourth-generationcephalosporins,aminoglycosides, andfluoroquinolones)werealsocomparedbetweenperiods; susceptibilityprofilesweregeneratedforGram-negative bac-teriaisolatedfromclinicalsamplesobtainedforthediagnosis ofhospitalinfections.

Statisticalanalysis

To estimate changes in the level and trends in monthly antibioticuseandexpenditure,weusedaninterrupted time-series(ITS)analysis.20ThemodelwasgeneratedinSPSS21.0

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base-brazj infect dis.2020;24(3):221–230

223

Fig.1–MonthlyantibioticuseexpressedasDOT/1000patient-days.DOT,daysoftherapy;BLA,beta-lactamantibiotics: meropenem,imipenem,ceftriaxone,ceftazidime,cefepime,piperacillin-tazobactam;BLSA,beta-lactam-sparingantibiotics: amikacin,gentamicin,ciprofloxacin,levofloxacin,moxifloxacin.Lineartrendswerefittedtothedataforeachgroupand period.

linetrendslopeandtoestimatechangesinslopeandlevel beforeandafterintervention.21WeusedtheStudent’st-test

orMann–Whitney testtocompareutilization and costsfor eachclassofantibioticsbetweenthe twoperiods.To com-paretheproportionsofsusceptiblebacteria,weusedFisher’s exact test. ThemonthofJuly 2017wasexcluded from the analysesbecauseitwasconsideredatransitionalperiodfor implementationandadjustmentsofantibioticuseprotocols, presentationofthenewinfectiousdiseasephysicianto pre-scribers,andmainlybecauseoftheintroductionofrestrictive formulariesattheendofJuly,whichmayhavebeena con-founderregardingATMuseresults.Forallanalyses,p-values

of<0.05wereconsideredstatisticallysignificant.Alltestswere computedbyusingSPSS21.0 anddescriptivestatistics and graphswereproducedinMicrosoftTMExcel2013.

Results

Antibioticuse

The ITS (Fig. 1) showed that both BLA and BLSA con-sumptionremainedstableduringthepre-interventionperiod (−0.48and−0.17DOT/1000patient-dayspermonth, respec-tively) (Table 1). BLA use decreased by 43.04 DOT/1000 patient-days(p=0.04)immediatelyfollowingASP implemen-tation, whereas BLSA use remained constant. Following ASP implementation, the BLA slope change was not sig-nificantly altered (−3.20 DOT/1000 patient-days, p=0.27), whereas the BLSA use trend increased (slope change 6.17 DOT/1000 patient-days, p<0.001). In a secondary analysis (Table 2), mean overall antibiotic use decreased by 37.82 DOT/1000 patient-days (p=0.002) between pre-intervention and interventionperiods, drivenbya reductioninthe use ofthird-generationcephalosporins(−29.59DOT/1000 patient-days,p<0.001),carbapenems(−22.32DOT/1000patient-days,

p<0.001), and piperacillin-tazobactam (−11.01 DOT/1000 patient-days,p<0.001);incontrast,themeanuseof fluoro-quinolonesincreased(23.22DOT/1000patient-days,p<0.001).

There was no significant change in fourth-generation cephalosporinoraminoglycosideusebetweenperiods. Antibioticexpenditure

Baseline antibiotic expenditure in the first month of the studywas$9162.39(Fig.2)andhadalreadystartedtodecline by$269.65(p<0.001)permonthduringthepre-intervention period (Table 3). After the intervention, antibiotic costs decreasedsharply,by$2089.99(p<0.001),followedbyatrend toward stabilization (slope change, $231.20, p<0.001). The mean monthly overall antibiotic expenditure decreased by 53.62%duringtheinterventionperiod($7336.95vs.$3402.54,

p<0.001); this was particularly influenced by a decline in spending on carbapenems ($3118.08 vs. $1628.44, p<0.001) andfluoroquinolones($1562.17vs.$390.28,p=0.002)(Table4). A significant decrease inexpenditure was observed for all classesofantibiotics,withtheexceptionofaminoglycosides. Microbialsusceptibilityprofiles

During the intervention period, we observed a significant increase in the proportion of Klebsiella spp. isolates that were susceptibletothird-generationcephalosporins (22.5%,

p=0.02)andfourth-generationcephalosporins(20.9%,p=0.03) (Table 5). Similarly, a significantly higher proportion of

Acinetobacter baumanniiisolates demonstrated susceptibility to aminoglycosides during the intervention phase (42.33%,

p<0.001).

Discussion

ThisstudyevaluatedtheimpactofanASPfocusedon reduc-ingtheuseofbroad-spectrumbeta-lactamsinahospitalina middle-incomecountry.Theprogramwasassociatedwithan 11.33%reductionintheoverallantibioticuse.DOTwith broad-spectrum beta-lactams decreasedby anaverage of24.58%, withthechangeobservedimmediatelyafterimplementation oftheASP.Incontrast,useofbeta-lactam-sparingantibiotics

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r a z j i n f e c t d i s . 2 0 2 0; 2 4(3) :221–230 374.06) BLA 273.60(242.96, 304.24) −0.48(−4.65,3.70) 0.81 −43.04(−84.13, −1.95) 0.04 −3.19(−9.09,2.71) 0.27 −3.67(−7.83,0.49) 0.08 Carbapenems 52.16(29.33,74.98) −0.18(−3.23,2.87) 0.90 −15.74(−43.96, 12.47) 0.26 −0.78(−5.28,3.72) 0.72 −0.96(−4.01,2.09) 0.52 3rd-gen. cephalosporins 141.65(128.86, 154.44) −0.78(−2.54,0.97) 0.36 −5.84(−23.54,11.87) 0.50 −2.75(−5.16,−0.34) 0.03 −3.54(−5.29,1.78) <0.001 4th-gen. cephalosporins 62.57(48.28,76.87) 1.35(−0.61,3.31) 0.17 −17.65(−37.36,2.05) 0.08 −0.31(−3.02,2.40) 0.81 1.04(−0.92,3.01) 0.28 Pip-taz 16.18(9.38,22.98) −0.74(−1.66,0.18) 0.11 −4.56(−13.51,4.40) 0.30 0.47(−0.84,1.79) 0.46 −0.26(−1.18,0.66) 0.56 BLSA 64.09(52.30,75.88) −0.17(−2.09,1.44) 0.83 −2.97(−19.05,13.11) 0.70 6.17(3.94,8.40) <0.001 5.99(4.38,5.10) <0.001 Aminoglycosides 15.18(9.38,22.98) 1.95(0.87,3.03) <0.001 −26.31(−37.12, −15.51) <0.001 1.54(0.03,3.05) 0.05 3.49(2.40,4.58) <0.001 Fluoroquinolones 48.72(38.92,58.52) −2.09(−3.43,−0.75) <0.001 22.84(9.50,36.18) <0.001 4.64(2.78,6.50) <0.001 2.55(1.21,3.89) <0.001 DOT,daysoftherapy;BLA,beta-lactamantibiotics;BLSA,beta-lactam-sparingantibiotics.

Carbapenems:meropenem,imipenem.3rd-gen.cephalosporins:ceftriaxone,ceftazidime.4th-gen.cephalosporins:cefepime. Pip-taz:Piperacillin-tazobactam.Aminoglycosides:amikacin,gentamicin.Fluoroquinolones:ciprofloxacin,levofloxacin,moxifloxacin.

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Table2–Comparisonofmeanmonthlyantibioticuse,expressedasDOT/1000patient-days,inthepre-interventionand interventionperiods. Pre-intervention periodmean(SD) Interventionperiod mean(SD) Percentage meanchange (%) p Overallantibiotics 333.69(±27.29) 295.87(±25.60) −11.33 0.002 BLA 270.65(±20.12) 204.12(±25.02) −24.58 <0.001 Carbapenems 51.28(±13.72) 28.97(±11.90) −43.51 <0.001 3rd-gen.cephalosporins 136.18(±13.02) 106.59(±17.23) −21.73 <0.001 4th-gen.cephalosporins 71.64(±12.77) 68.02(±12.36) −5.05 0.489 Pip-taz 11.55(±6.83) 0.54(±1.42) −95.32 <0.001 BLSA 63.04(±12.57) 91.75(±24.57) 45.54 0.002 Aminoglycosides 27.88(±9.86) 33.38(±14.05) 19.73 0.279 Fluoroquinolones 35.16(±12.79) 58.38(±11.34) 66.04 <0.001

DOT,daysoftherapy;BLA,beta-lactamantibiotics;BLSA,beta-lactam-sparingantibiotics.

Carbapenems:meropenem,imipenem.3rd-gen.cephalosporins:ceftriaxone,ceftazidime.4th-gen.cephalosporins:cefepime. Pip-taz:Piperacillin-tazobactam.Aminoglycosides:amikacin,gentamicin.Fluoroquinolones:ciprofloxacin,levofloxacin,moxifloxacin.

Fig.2–Monthlyantibioticexpenditure(USD).Lineartrendswerefittedtothedataforeachperiod.

gradually increasedduring the intervention period, result-inginatotalincreaseof45.54%bytheendofthe12-month intervention.Costsattributedtoantibioticusewerereduced by$3934.41per monthin the interventionperiod(an esti-matedone-yearsavingof$47,212.92).Adownwardtrendin monthlyantibioticexpenditurewasnotedpriortotheformal initiationofASP,attributedtothewithdrawalofintravenous ciprofloxacinfromantibioticsformularythreemonthsbefore theASPwasimplemented(supplementarymaterial2). How-ever,amoresubstantialdropwasobservedimmediatelyafter ASPimplementation, which was sustained throughoutthe interventionperiod.Therewasanincreaseinfluoroquinolone use,althoughexpenditureonfluoroquinolonesdecreasedin theinterventionperiodowingtotheincreasedconsumption oforalformulations.Ahigherproportionofdrug-susceptible Klebsiellaspp. and aminoglycoside-susceptible A. baumannii wereisolatedduringtheinterventionperiod.

Priortothisstudyourhospitalhadlimitedexperiencewith formal programs promotingthe rational use of medicines, beyond standard antibiotic prescription protocols without auditormanagement.Wespeculatedthatthiswasthe rea-sonwhybaselinebroad-spectrumantibioticusewassohigh

and believethat this providedan excellent opportunity to moderate usage. Ourbaselinemean monthly consumption of carbapenems was 51.28 DOT/1000 patient-days, almost double than that reported in hospitals inthe US, and our useofthirdandfourth-generationcephalosporinswasmore thandouble.22Asobservedinsimilarstudiesinhigh-income countries, we have demonstrated success in reducing the use of selected antibiotics and their associated costs. Our interventionresultedinan11.3%reductioninantibioticuse anda53%($3934.41)reductioninassociatedmonthly expen-diture, which was sustained throughoutthe study period. Similarly,Campbelletal.reducedantibioticuseina hospi-talsurgicalwardby12%byapplyinganon-restrictivepolicy; this was accompaniedby a 35–41%reductionin antibiotic costs.23InastudybyBordeetal.,afteranintensive

educa-tionprogramaimedatdiscouragingtheuseofquinolonesand cephalosporins,theassociatedobservedreductionwas14.2% in the medicalwards, witha saving ofD135,000 annually, excludingpersonnelcosts.24AstudybyJenkinsetal.,usinga

semi-restrictivemethodologyforbroad-spectrumantibiotics similartoours,demonstrateda14.2%reductionintotal antibi-oticuseand a30%reductioninthe useofbroad-spectrum

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r a z j i n f e c t d i s . 2 0 2 0; 2 4(3) :221–230 BLA 6112.79(5455.00, 6770.58) −63.20(−153.50, 27.07) 0.16 −2037.52(−2945.31, −1129.74) <0.001 −5.55(−129.57, 112.46) 0.93 −68.75(−158.62, 21.12) 0.13 Carbapenems 3065.03(2206.27, 3923.79) 8.40(−110.04,126.84) 0.89 −1171.96(−2376.90, 32.98) 0.06 −76.71(−239.76, 86.34) 0.34 −68.31(−186.87, 50.25) 0.24 3rd-gen. cephalosporins 685.97(596.60, 775.34) −6.58(−18.82,5.66) 0.27 −136.00(−257.72, −14.28) 0.03 1.39(−15.77,18.55) 0.87 5.19(−7.18,17.56) 0.39 4th-gen. cephalosporins 1022.31(768.20, 1276.42) −0.81(−36.10,34.48) 0.96 −283.58(−651.91, 84.75) 0.12 12.83(−35.04,60.70) 0.58 12.01(−24.01,48.03) 0.49 Pip-taz 1289.28(685.84, 1892.72) −65.45(−146.60, 15.70) 0.11 −266.94(−1033.93, 500.05) 0.48 43.58(−74.56,161.72) 0.45 −21.88(−102.44, 58.68) 0.58 BLSA 3023.88(2531.90, 3515.86) −206.33(−273.50, −139.12) <0.001 −4.138(−675.11, 666.84) 0.99 234.62(121.70, 327.53) <0.001 28.28(−38.96,95.53) 0.39 Aminoglycosides 64.93(21.38,108.48) 4.58(−1.30,10.46) 0.12 −91.70(−148.32, −35.08) 0.003 9.96(1.49,18.43) 0.02 14.54(8.64,20.44) <0.001 Fluoroquinolones 2955.32(2454.24, 3456.40) −210.66(−279.11, −142.21) <0.001 92.29(−591.11, 775.69) 0.78 223.64(128.94, 318.34) <0.001 12.96(−55.56,81.48) 0.68

BLA,beta-lactamantibiotics;BLSA,beta-lactam-sparingantibiotics.

Carbapenems:meropenem,imipenem.3rd-gen.cephalosporins:ceftriaxone,ceftazidime.4th-gen.cephalosporins:cefepime. Pip-taz:Piperacillin-tazobactam.Aminoglycosides:amikacin,gentamicin.Fluoroquinolones:ciprofloxacin,levofloxacin,moxifloxacin.

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Table4–Comparisonofmeanmonthlyantibioticexpenditure(USD)betweenpre-interventionandinterventionperiods.

Pre-intervention periodmean(SD) Interventionperiod mean(SD) Percentagemean change(%) p Overallantibiotics 7336.95(±1260.96) 3402.54(±615.32) −53.62 <0.001 BLA 5679.64(±637.72) 2899.50(±706.59) −48.95 <0.001 Carbapenems 3118.08(±677.26) 1628.44(±634.07) −47.77 <0.001 3rd-gen.cephalosporins 638.73(±81.22) 445.13(±94.96) −30.31 <0.001 4th-gen.cephalosporins 1023.96(±243.60) 791.96(±155.06) −22.66 0.01 Pip-taz 898.87(±556.82) 33.98(±104.82) −96.22 <0.001 BLSA 1657.31(±967.65) 503.04(±215.43) −69.65 0.002 Aminoglycosides 95.14(±31.15) 112.76(±61.37) 18.52 0.39 Fluoroquinolones 1562.17(±983.01) 390.28(±189.70) −75.02 0.002

BLA,beta-lactamantibiotics;BLSA,beta-lactam-sparingantibiotics.

Carbapenems:meropenem,imipenem.3rd-gen.cephalosporins:ceftriaxone,ceftazidime.4th-gen.cephalosporins:cefepime. Pip-taz:Piperacillin-tazobactam.Aminoglycosides:amikacin,gentamicin.Fluoroquinolones:ciprofloxacin,levofloxacin,moxifloxacin.

Table5–Comparisonofantimicrobialsusceptibilityprofilesforkeypathogensinthepre-interventionandintervention periods,presentedasproportionofsusceptibleorganismsforeachclassofantibiotics.

Microorganism-Antibiotic Pre-intervention periodsusceptible,n % Interventionperiod susceptible,n % Difference(%) p-Value Escherichiacoli Aminoglycosides 61/74 82.4 48/51 94.1 11.7 0.06 Carbapenems 74/74 100.0 51/51 100.0 0.0 1.00 3rd-gen.cephalosporins 61/74 82.4 36/51 70.6 −11.8 0.13 4th-gen.cephalosporins 61/74 82.4 37/51 72.5 −9.9 0.19 Fluoroquinolones 56/74 75.7 44/51 86.3 10.6 0.17 Klebsiellaspp. Aminoglycosides 32/63 50.8 33/47 70.2 19.4 0.05 Carbapenems 47/63 74.6 40/47 85.1 10.5 0.24 3rd-gen.cephalosporins 22/63 34.9 27/47 57.4 22.5 0.02 4th-gen.cephalosporins 23/63 36.5 27/47 57.4 20.9 0.03 Fluoroquinolones 26/63 41.3 29/47 61.7 20.4 0.05 Enterobacterspp. Aminoglycosides 43/53 81.1 45/60 75.0 −6.1 0.50 Carbapenems 51/51 100.0 58/60 96.7 −3.3 0.50 3rd-gen.cephalosporins 14/53 26.4 12/54 22.2 −4.2 0.66 4th-gen.cephalosporins 39/53 73.6 41/60 68.3 −5.2 0.68 Fluoroquinolones 40/51 78.4 47/59 79.7 1.2 1.00 Pseudomonasaeruginosa Aminoglycosides 60/79 75.9 33/37 89.2 13.2 0.13 Carbapenems 68/79 86.1 32/37 86.5 0.4 1.00 3rd-gen.cephalosporins 57/79 72.2 28/37 75.7 3.5 0.82 4th-gen.cephalosporins 58/79 73.4 29/37 78.4 5.0 0.65 Fluoroquinolones 63/79 79.7 32/36 88.9 9.1 0.29 Acinetobacterbaumannii Aminoglycosides 18/57 31.6 34/46 73.9 42.3 <0.001 Carbapenems 6/57 10.5 9/46 19.6 9.0 0.26 3rd-gen.cephalosporins 4/57 7.0 9/46 19.6 12.6 0.08 4th-gen.cephalosporins 4/57 7.0 9/46 19.6 12.6 0.08 Fluoroquinolones 5/57 8.8 9/46 19.6 10.8 0.15

agents;thisimpactwasobservedshortlyafterthestartofthe programandwasassociatedwitha27.9%decreasein antibi-oticexpenditure.25

Inasystematicreviewandmeta-analysis,Karanikaetal. evaluatedtheeconomicoutcomesof26studiesandrevealed a19.1%reductionintotalantibioticconsumptionand26.6% reductionintheuseofrestrictedantibiotics,26similartoour

reductionof 24.6%.Although there isan absolute need to reduceantibioticconsumptioninBRICScountries,sofaronly

asmallnumberofstudieshavebeenpublishedonthistopic fromlowtomiddle-incomecountries.Forexample,inastudy conductedinacardiologyhospitalinBrazil,Magedanzetal. demonstrateda25%and69%reductioninantibiotic consump-tionandcost,respectively;thisstudyattributedthesuccessto collaborationbetweentheclinicalpharmacistandinfectious diseasesspecialistandtotheuseofanon-restrictivepolicy.27

We observed that the use of restricted antibiotics in our studyfellimmediatelyafterimplementationoftheASPand

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susceptibility of E. coli, Enterobacter spp., and Pseudomonas aeruginosa.Wealsoexpectedanimprovementinsusceptibility tobeta-lactamsinthemajorityofbacteriastrains,especially forcarbapenems,forwhichreductionbetweenperiodswas the greatest. Despite adramatic increase inthe consump-tion offluoroquinolones,we didnot see any worsening in theresistanceprofileofE.coliandK.pneumoniae,whichhas beenreportedinsomestudies.30,31Itisdifficulttorelatethese

results only to the control of antimicrobials, and there is hugevariation betweenstudy models, consumptionof dif-ferent drugs, and follow-up time. Therefore, it is unclear howtheASPimplementationimpactsbacterialsusceptibility profiles.13,16,25,32 Anotherpotentialsourceofbiasrelatedto

thechangeisthemethodforlaboratoryidentificationof bac-teria,whichwaspreviouslyperformedmanuallybymeansof cultureanddisk-diffusionantibiograms,whereasinthe inter-vention period, by automated methods. The susceptibility profileofAcinetobacterspp.toaminoglycosidesincreasedfrom 31%to73%withimplementationoftheASP.Thisfindinghas notbeenreportedelsewhereintheliterature,butweproposed thefollowinghypothesis.Thecarbapenem-resistant Acineto-bacterspp. in ourhospital isendemicand associated with OXA-23carbapenemase.33Resistancetoaminoglycosidescan

bemediatedbymethylases,otheraminoglycoside-modifying enzymes,andeffluxpumps.Themainpumpassociateswith amikacinresistanceistheadeABC.34TheadeABCgeneis

over-expressedbycarbapenem.35 Thus,withadecreaseduse of

carbapenem,it ispossiblethatadeABCgeneisnot overex-pressedandsusceptibilitytoamikacinisthereforeincreased. Althoughthesafetyofaminoglycosideshasbeendiscussed widelyintheliteraturefromtheperspectiveof nephrotoxic-ity,theexchangeofbeta-lactamsforthisclasswasinitially encouragedbythefavorablesusceptibilityprofilesof Gram-negativebacteriatoamikacinandgentamicin.Furthermore, previousstudieshavecorroboratedthesafetyofthesedrugs whenusedinadjusteddosesandwithserummonitoring.36,37

In addition, a new meta-analysis highlighted the associa-tionofacuterenalinjurywithpatientsreceivingconcomitant piperacillin-tazobactam and vancomycin, which reinforced ourexchangestrategy.38

Thisstudyhassomelimitations.First,thecollectionof ret-rospectivedatalimitsthediscussionofresults,especiallyin thecaseofactionsperformedinthepre-interventionperiod. Second,theecologicalstudydesignallowedustohypothesize onASPoutcomes;however,wecannotsaythattheactionsof theprogramweretheonlydriverofresults.Thisisespecially relevantregardingbacterialsusceptibilityprofiles,whichare

In summary, a semi-restrictive ASP based on sparing extended-spectrumbeta-lactamswasaneffectivestrategyfor reducing targetedantibioticconsumptioninahospital set-tingandmaintainingsusceptibilityprofilesinGram-negative bacteria.Thisstudyalsofitswiththeglobaleffortstoreduce inappropriate prescription of last-resortantibiotics, mainly inmiddle-incomecountries,anddemonstratedacost-saving strategythatwasachievablewithasmall,specializedteam.

Funding

Thisresearchdidnotreceiveanyspecificgrantsfromfunding agenciesinthepublic,commercial,ornot-for-profitsectors.

Conflicts

of

interest

Theauthorsdeclarenoconflictsofinterest.

Authors

contributions

TiagoZequinao, Pharm–wrotemanuscriptsand statistical analysis.

JulianoGasparetto–revisedthemanuscriptanddatabase evaluation.

Dayana dos Santos Oliveira – database evaluation and revisedthemanuscript.

GabrielTakaharaSilva–dataevaluation.

João Paulo Telles - database evaluationand revised the manuscript.

FelipeFranciscoTuon–wroteandrevisedthemanuscript.

Appendix

A.

Supplementary

data

Supplementary material related to this article can be found, in the online version, at https://doi.org/10. 1016/j.bjid.2020.05.005.

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