Results of the RESCUING STUDY - COMBACTE
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PowerPoint-presentatiepatients with Complicated Urinary tract
Infection in
countries with a high prevalence of multidrug
resistant Gram-negative bacteria
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
functional or structural abnormalities of the genitourinary
tract, including pyelonephritis
Pyelonephritis Catheter-related UTI
Nephrolithiasis Urinary diversion
Bulgaria University Hospital Queen Joanna Prof. Rossitza Vatcheva-
Dobrevska
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 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 Aratrma Hastanesi Dr. Arzu Yetkin
Turkey Istanbul University Cerrahpasa Medical School Prof. Nese Saltoglu
RESCUING: Epidemiological characteristics
Gender (F/M) 545 (54%) / 461 (46%)
Age (mean, SD) 66y (+ 17.8)
Admission: (cUTI/Other reason)
Discharge
Home 805 (80%)
Hospital/LTCF 111 (11,1%)
Nº of episodes
Bedridden 160 (15.9%)
Antibiotic within 30 days 203 (20.2%)
FQ 54/203 (26,6%)
Amoxi-clav 32 (15.7%)
Carbapenems 17 (8.3%)
Fosfomycin 9 (4.4%)
Nº of episodes
cUTI acquisition site
Community 556 (55.3%)
Obstructive uropathy 157 (15.6%)
Other events 217 (21.6%)
Bloodstream infection 241 (24%)
Source E coli n=565 (49%)
KP n=168 (15%)
48/92 52%
19/92 20%
10/200 5%
2/92 2.1%
12/92 13%
main identified bacteria
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)
136/340 40%
27/340 7.9%
34/200 17%
5/200 2.5%
7/92 7.6%
Predictive factors for multidrug
14
Susceptible
n (%)
MDR
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
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 (%)
Pyelonephritis normal
tract anatomy
Obstructive uropathy 114 (16.5) 38 (14.8) 0.523
Anatomical tract
Other 160 (23.2) 48 (18.7) 0.139
Shock - Severe sepsis 104 (16.2) 36 (14.9) 0.635
Aetiology
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
% M
Kenezy Gyula Hospital
Univ.Hosp. Queen Joanna
AORN dei Colli - Monaldi
Cerrahpasa Medical School
Tel Aviv Medical Center
Hosp.Univ.12 de Octubre
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.
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.
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
ROC Curve
Model performance
it y
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0
10
20
30
centre_name
• 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
gender, admission, acquisition, indwelling urinary catheter, uti
within year and antibiotics within 30d as significant predictive
factors for MDR pathogens
• Babich, Tanya Tel-Aviv University
• Eliakim-Raz, Noa Tel-Aviv University
• 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 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 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 Aratrma Hastanesi Dr. Arzu Yetkin
Turkey Istanbul University Cerrahpasa Medical School Prof. Nese Saltoglu
Thank you very much
countries with a high prevalence of multidrug
resistant Gram-negative bacteria
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
functional or structural abnormalities of the genitourinary
tract, including pyelonephritis
Pyelonephritis Catheter-related UTI
Nephrolithiasis Urinary diversion
Bulgaria University Hospital Queen Joanna Prof. Rossitza Vatcheva-
Dobrevska
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 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 Aratrma Hastanesi Dr. Arzu Yetkin
Turkey Istanbul University Cerrahpasa Medical School Prof. Nese Saltoglu
RESCUING: Epidemiological characteristics
Gender (F/M) 545 (54%) / 461 (46%)
Age (mean, SD) 66y (+ 17.8)
Admission: (cUTI/Other reason)
Discharge
Home 805 (80%)
Hospital/LTCF 111 (11,1%)
Nº of episodes
Bedridden 160 (15.9%)
Antibiotic within 30 days 203 (20.2%)
FQ 54/203 (26,6%)
Amoxi-clav 32 (15.7%)
Carbapenems 17 (8.3%)
Fosfomycin 9 (4.4%)
Nº of episodes
cUTI acquisition site
Community 556 (55.3%)
Obstructive uropathy 157 (15.6%)
Other events 217 (21.6%)
Bloodstream infection 241 (24%)
Source E coli n=565 (49%)
KP n=168 (15%)
48/92 52%
19/92 20%
10/200 5%
2/92 2.1%
12/92 13%
main identified bacteria
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)
136/340 40%
27/340 7.9%
34/200 17%
5/200 2.5%
7/92 7.6%
Predictive factors for multidrug
14
Susceptible
n (%)
MDR
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
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 (%)
Pyelonephritis normal
tract anatomy
Obstructive uropathy 114 (16.5) 38 (14.8) 0.523
Anatomical tract
Other 160 (23.2) 48 (18.7) 0.139
Shock - Severe sepsis 104 (16.2) 36 (14.9) 0.635
Aetiology
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
% M
Kenezy Gyula Hospital
Univ.Hosp. Queen Joanna
AORN dei Colli - Monaldi
Cerrahpasa Medical School
Tel Aviv Medical Center
Hosp.Univ.12 de Octubre
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.
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.
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
ROC Curve
Model performance
it y
0 .0
0 .2
0 .4
0 .6
0 .8
1 .0
10
20
30
centre_name
• 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
gender, admission, acquisition, indwelling urinary catheter, uti
within year and antibiotics within 30d as significant predictive
factors for MDR pathogens
• Babich, Tanya Tel-Aviv University
• Eliakim-Raz, Noa Tel-Aviv University
• 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 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 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 Aratrma Hastanesi Dr. Arzu Yetkin
Turkey Istanbul University Cerrahpasa Medical School Prof. Nese Saltoglu
Thank you very much
