COMBACTE-MAGNET WP5

APRIL 2017 VIENNA, AUSTRIA

Miquel Pujol, MD

Results of the

RESCUING STUDY

WP5 “RESCUING”

REtrospective observational Study to assess the

clinical management and outcomes of hospitalised

patients with Complicated Urinary tract Infection in

countries with a high prevalence of multidrug

resistant Gram-negative bacteria

Rationale • cUTI are among most frequent community as well

health-care related infections

• Increasing prevalence of MDR-GNB (multi-drug resistant Gram-negative bacteria) worldwide is a major concern

• To provide current data from European regions with a high prevalence of MDR GNB regarding:

– Antimicrobial resistance among patients with cUTI

– Clinical management and outcomes of hospitalised patients with cUTI

– Costs of cUTI

Complicated

Urinary Tract Infection (cUTI)

Complicated urinary tract infection occurs in individuals with

functional or structural abnormalities of the genitourinary

tract, including pyelonephritis

FDA 2015.cUTI: Developing Drugs for Treatment Guidance for Industry

Pyelonephritis Catheter-related UTI

Nephrolithiasis Urinary diversion

Selected Countries

Spain

Italy

Hungary

Romania

Bulgaria

Greece

Turkey

Israel

1,006 episodes 1,148 isolates

Country Hospital Principal Investigator

Bulgaria Emergency Hospital Pirogov Prof. Dora Tancheva

Bulgaria University Hospital Queen Joanna Prof. Rossitza Vatcheva-

Dobrevska

Greece Attikon University Hospital Prof. Sotirios Tsiodras

Greece Hippokration Hospital Prof. Emmanuel Roilides

Hungary Kenezy Gyula Hospital Prof. Istvan Várkonyi

Hungary Soproni Erzsébet Oktató Kórház és Rehabilitációs Intézet Dr. Judit Bodnár

Hungary Szabolcs-Szatmár-Bereg Megyei Kórházak és Egyetemi

Oktatókórház Dr. Aniko Farkas

Israel Beilinson Hospital, Rabin Medical Center Dr. Noa Eliakim

Israel Rambam Health Care Campus Prof. Mical Paul

Israel Tel Aviv Medical Center Prof. Yehuda Carmeli

Italy AORN dei Colli Monaldi Prof. Emanuele Durante

Italy Azienda ospedaliero-universitaria policlinico di modena Prof. Cristina Mussini

Italy National Institute for Infectious Diseases L. Spallanzani Dr. Nicola Petrosillo

Romania Infectious Diseases Hospital Sfanta Parascheva Iasi Dr. Andrei Vata

Romania National Institute for Infectious Diseases "Prof Dr Matei Bals" Prof. Adriana Hristea

Spain Bellvitge University Hospital Dr. Miquel Pujol

Spain Hospital Universitario 12 de Octubre Dr. Julia Origüen

Spain Hospital Universitario Virgen Macarena Prof. Jesus Rodriguez-Baño

Turkey Ankara Numune Egitim ve Araştırma Hastanesi Dr. Arzu Yetkin

Turkey Istanbul University Cerrahpasa Medical School Prof. Nese Saltoglu

RESCUING: Epidemiological characteristics

Nº of episodes: 1006 episodes

Gender (F/M) 545 (54%) / 461 (46%)

Age (mean, SD) 66y (+ 17.8)

Admission: (cUTI/Other reason)

651 (64.7%)/ 355 (35.3%)

Admitted from:

Home 828 (82.3%)

LTCF 48 (4.8%)

Nursing Home 45 (4.5%)

Other hospital 85 (8.5%)

Charlson Score (median IQR) 2 (1-4)

Discharge

Died before discharge 90 (8.9%)

Home 805 (80%)

Hospital/LTCF 111 (11,1%)

Nº of episodes

Functional capacity

Independent 535 (53%)

Needs assistance 219 (21.8%)

Does not leave home 89 (8.8%)

Bedridden 160 (15.9%)

UTI within year 263 (26.1%)

Antibiotic within 30 days 203 (20.2%)

FQ 54/203 (26,6%)

Amoxi-clav 32 (15.7%)

2nd G Cephaloporins 6 (2.9%)

3erd G Cephalosporins 19 (9.3%)

Carbapenems 17 (8.3%)

Fosfomycin 9 (4.4%)

Nº of episodes

cUTI acquisition site

Community 556 (55.3%)

Healthcare related 254 (25.2%)

Hospital 196 (19.5%)

Infection source

Indwelling urinary catheterisation 340 (33.8%)

Pyelonephritis normal anatomy 200 (19.9%

Obstructive uropathy 157 (15.6%)

Urinary tract diversion 92 (9.1%)

Other events 217 (21.6%)

Infection severity

Septic shock/severe sepsis 149/938 (15.9%)

Bloodstream infection 241 (24%)

Aetiology (1148 isolates) / Source of Infection (1006 episodes)

Source E coli n=565 (49%)

KP n=168 (15%)

P.aeruginosa

n=97 (8%)

P.mirabilis n=79 (7%)

Enteroc spp n=82

Indwelling urinary catheterisation

(n=340)

127/340 37%

63/340 18.5%

58/340 17%

40/340 11.7%

49/340 14.4%

Pyelonephritis normal anatomy

(n=200)

151/200 75%

25/200 12.5%

4/200 2%

13/200 6.5%

1/200 0.5%

Obstructive uropathy (n=157)

100/157 63%

26/157 16.5%

12/200

6%

11/157 7%

9/157 5.7%

Urinary tract diversion (n=92)

48/92 52%

19/92 20%

10/200 5%

2/92 2.1%

12/92 13%

Others (n=217) 139/217

64% 35/217

16% 13/200

6.5% 13/217 10.6%

11/217 5%

Patterns of antimicrobial resistance by the four

main identified bacteria

AMG-

R

FQ-

R

3rd Gen

Ceph-R

PIP/TAZ

-R

CARB-

R

Resistance to

>3antimicrobial

categories

(MDR)

Resistance

>5antimicrobial

categories

(XMDR)

E. coli

n=565 (49.2%) 18.5% 39.0% 24.1% 10.4% 1.8% 14.5% 0.4%

K. pneumoniae

n=168 (14.6%) 49.4% 61.4% 63.7% 40.5% 17.9% 53% 13.1%

P. aeruginosa

n=97 (8.4%) 31.9% 43.3% 50.5% 24.7% 37.1% 37.1% 14.4%

P. mirabilis

n=79 (6.9%) 36.7% 55.7% 25.4% 7.6% 5.0% 24.1% 1.3%

Magiorakos, Clin Microbiol Infect 2012; 18: 268–281

MDR and XMDR / Source of Infection

Source (episodes) MDR (>3)

XMDR

(>5)

Indwelling urinary catheterisation (n=340)

136/340 40%

27/340 7.9%

Pyelonephritis normal anatomy (n=200)

34/200 17%

5/200 2.5%

Obstructive uropathy (n=157)

41/157 26.1%

7/157 4.4%

Urinary tract diversion (n=92) 22/92 23.9

7/92 7.6%

Others (n=217) 50/217

23% 11/217

5%

AG, FQ, BL-I, 3GC, CP

Predictive factors for multidrug

resistance (MDR)

Predictive factors of MDR. Univariate analysis

14

Susceptible

n (%)

MDR

n (%) p value (*)

Mean age +SD 65+18.7 66+16.8 0.526

Male gender 270 (39.1) 150 (67.1) <0.001

Admission: Elective 97 (14) 44 (17.1) 0.236

Admission reason: UTI 477 (69) 145 (56.4) <0.001

Admitted from Health Care System 98 (14.2) 67 (26.1) <0.001

Underlying disease

Congestive Heart failure 134 (19.4) 47 (18.3%) 0.701

Cerebral-vascular disease 122 (17.7) 60 (23.3) 0.048

Chronic pulmonary disease 91 (13.2) 44 (17.1) 0.122

Diabetes mellitus 186 (26.9) 64 (24.9) 0.531

Chronic kidney disease 191 (27.6) 72 (28) 0.909

Chronic Liver disease 35 (5.1) 15 (5.8) 0.637

Charlson > 3 299 (43.3) 119 (46.3) 0.403

Organ transplant 45 (6.5) 20 (7.8 0.492

Immunosuppression 64 (9.3) 30 (11.7) 0.270

Steroids 46 (6.7) 22 (8.6) 0.313

Functional capacity: Dependent 298 (43.3%) 138 (53.9) 0.003

15

Susceptible

n (%)

MDR

n (%)

p value

(*)

Source

Indwelling urinary

catheterisation

189 (27.4) 119 (46.3) <0.001

Pyelonephritis normal

tract anatomy

164 (23.7) 32 (12.5) <0.001

Obstructive uropathy 114 (16.5) 38 (14.8) 0.523

Anatomical tract

modification

64 (9.3) 20 (7.8) 0.476

Other 160 (23.2) 48 (18.7) 0.139

Shock - Severe sepsis 104 (16.2) 36 (14.9) 0.635

Aetiology

E. coli 478 (69.2) 81 (31.5%) <0.000

K.pneumoniae 81 (11.7) 87 (33.9) <0.001

P.aeruginosa 57 (8.2) 38 (14.8) <0.003

P. mirabilis 56 (8.1) 23 (8.9) 0.676

Predictive factors of MDR. Univariate analysis

% MDR infection by COUNTRY

20

40

60

Bulgaria Greece Turkey Italy Israel Romania Hungary Spain

%M

R in

fectio

n

Bulgaria

Greece

Turkey

Italy

Israel

Romania

Hungary

Spain

% MDR infection by CENTER

0

20

40

60

80

MR

infe

ctio

n

Emergency Hospital Pirogov

Hippokration Hospital

Ankara Numune Research and Training Hospital

Nat. Inst. for Infectious Diseases L.Spallanzani

Kenezy Gyula Hospital

Univ.Hosp. Queen Joanna

Rambam Health Care Campus

Nat. Inst. for Infectious Diseases M.Bals

AORN dei Colli - Monaldi

Policlinico di Modena

Szabolcs-Szatmár-Bereg Megyei Kórházak és Egyetemi Oktatókórház

Cerrahpasa Medical School

Rabin Medical Center Campus Beilinson

Tel Aviv Medical Center

Infectious Diseases Hospital Sfanta Parascheva Iasi

Hosp.Univ.12 de Octubre

Hosp.Univ.Virgen Macarena

Attikon University Hospital

Hosp.Univ.Bellvitge

Soproni Erzsébet Oktató Kórház és Rehabilitációs Intézet

Predictive model

multiresistance

• Patients from 20 different hospitals (8 countries) to study factors that predict multiresistant infection.

• Hospitals/ countries presented higher or lower % of MR, so the baseline probability of MDR infection into each of the hospitals is different.

• Model estimation:

• Mixed effects logistic regression.

• Stepwise selection method based on Akaike Information Criteria (AIC) to identify the variables that explain the bulk of the MR infection.

• Bootstrapping resampling method.

Methods

• Potential predictors include patient’s age, sex, source, admitted

from, functional capacity score, myocardial infarction, congestive

heart failure, peripheral vascular disease, cerebrovascular

disease, dementia, chronic pulm disease,ulcer disease,diabetes

mellitus, chronic kidney disease, hemiplegia, solid tumour, liver

disease, metastatic, Charlson, acquisition site, indwelling urinary

catheter, urinary retention, organ transplant, organ transplant

kidney, immunosuppressive therapy, active chemotherapy,

corticosteroid therapy, uti within year, antibiotic within 30d, QUIN,

PEN, CEFA, CARBA, OTHER, infection severity, neurogenic

bladder, obstructive uropathy, renal impairment and urinary tract

modification.

Estimated predictive

model for MDR

Factors OR CI95% p-value

(Intercept) 0.10 0.06 0.15 <0.00001

Gender (Male) 1.80 1.29 2.51 0.00050

Admitted from medical facility 1.33 0.86 2.08 0.19762

Acquisition in a medical facility 2.47 1.66 3.67 <0.00001

Indwelling urinary catheter 1.36 0.92 2.01 0.11857

UTI within year 2.03 1.36 3.03 0.00051

Antibiotic within 30d 1.55 1.03 2.34 0.03753

OR: Odds Ratio; CI95%: confidence interval at 95%

Ranking of importance of predictors

Adquisition medical facility

Gender (Male)

UTI within year

Indwelling urinary catheter

Admited from medical facility

Antibiotic within 30d

0 5 10 15 20 25F value

ROC Curve

Model performance

Specificity

Sensitiv

ity

1.0 0.8 0.6 0.4 0.2 0.0

0.0

0.2

0.4

0.6

0.8

1.0

AUC= 0.78 CI95% 0.74 - 0.81

Observed vs predicted by center

10

20

30

Attikon University HospitalSoproni Erzsébet Oktató Kórház és Rehabilitációs IntézetHosp.Univ.BellvitgeHosp.Univ.Virgen MacarenaKenezy Gyula HospitalSzabolcs-Szatmár-Bereg Megyei Kórházak és Egyetemi OktatókórházCerrahpasa Medical SchoolHosp.Univ.12 de OctubrePoliclinico di ModenaAORN dei Colli - MonaldiRabin Medical Center Campus BeilinsonTel Aviv Medical CenterUniv.Hosp. Queen JoannaInfectious Diseases Hospital Sfanta Parascheva IasiNat. Inst. for Infectious Diseases L.SpallanzaniNat. Inst. for Infectious Diseases M.BalsRambam Health Care CampusHippokration HospitalAnkara Numune Research and Training HospitalEmergency Hospital Pirogov

centre_name

Ob

se

rved

Pre

dic

ted

Conclusions

• The epidemiology of cUTI is changing

• There's an increasing importance of cUTI-HCR infections and

among them of MDR K.pneumoniae isolates

• Rates of antibiotic resistance vary according to source of

infection and aetiology

• Our model performed among patients with cUTI selected:

gender, admission, acquisition, indwelling urinary catheter, uti

within year and antibiotics within 30d as significant predictive

factors for MDR pathogens

25

26

WP5 Team (Alphabetically)

• Addy, Ibironke AiCuris Anti-infective Cures, EFPIA, WP5 Lead

• Babich, Tanya Tel-Aviv University

• Carratala, Jordi Bellvitge University Hospital, Barcelona

• Corthals, Sophie University Medical Centre Utrecht

• Couperus, Janet University Medical Centre Utrecht

• Cuperus, Nienke University Medical Centre Utrecht

• Eliakim-Raz, Noa Tel-Aviv University

• Gibbs, Julie North Bristol NHS Trust

• Grier, Sally North Bristol NHS Trust

• McGowan, Alasdair North Bristol NHS Trust

• Morris, Steve University College London

• Leibovici, Leonard Tel-Aviv University, Academic WP5 Lead

• Pujol, Miquel Bellvitge University Hospital, Academic WP5 Lead

• Shaw, Evelyn Bellvitge University Hospital

• Vallejo-Torres, Laura University College London

• Vigo, Joan Miquel Area d'Informàtica FICF

• van den Heuvel, Leo University Medical Centre Utrecht

• Vank,Christiane AiCuris Anti-infective Cures, EFPIA

• Vuong, Cuong AiCuris Anti-infective Cures, EFPIA

Country Hospital Principal Investigator

Bulgaria Emergency Hospital Pirogov Prof. Dora Tancheva

Bulgaria University Hospital Queen Joanna Prof. Rossitza Vatcheva-Dobrevska

Greece Attikon University Hospital Prof. Sotirios Tsiodras

Greece Hippokration Hospital Prof. Emmanuel Roilides

Hungary Kenezy Gyula Hospital Prof. Istvan Várkonyi

Hungary Soproni Erzsébet Oktató Kórház és Rehabilitációs Intézet Dr. Judit Bodnár

Hungary Szabolcs-Szatmár-Bereg Megyei Kórházak és Egyetemi

Oktatókórház Dr. Aniko Farkas

Israel Beilinson Hospital, Rabin Medical Center Dr. Noa Eliakim

Israel Rambam Health Care Campus Prof. Mical Paul

Israel Tel Aviv Medical Center Prof. Yehuda Carmeli

Italy AORN dei Colli Monaldi Prof. Emanuele Durante

Italy Azienda ospedaliero-universitaria policlinico di modena Prof. Cristina Mussini

Italy National Institute for Infectious Diseases L. Spallanzani Dr. Nicola Petrosillo

Romania Infectious Diseases Hospital Sfanta Parascheva Iasi Dr. Andrei Vata

Romania National Institute for Infectious Diseases "Prof Dr Matei Bals" Prof. Adriana Hristea

Spain Bellvitge University Hospital Dr. Miquel Pujol

Spain Hospital Universitario 12 de Octubre Dr. Julia Origüen

Spain Hospital Universitario Virgen Macarena Prof. Jesus Rodriguez-Baño

Turkey Ankara Numune Egitim ve Araştırma Hastanesi Dr. Arzu Yetkin

Turkey Istanbul University Cerrahpasa Medical School Prof. Nese Saltoglu

Thank you very much