Resultados de un programa hospitalario para la optimización del uso de los antimicrobianos basado en medidas educativas. Nuevos diseños de intervención frente a las resistencias bacterianas

TESIS DOCTORAL Doctorando: José Molina Gil-Bermejo Director: José Miguel Cisneros Herreros Tutor: Jerónimo Pachón Díaz Departamento de Medicina. Universidad de Sevilla. Resultados de un programa hospitalario para la optimización del uso de los antimicrobianos basado en medidas educativas. Nuevos diseños de intervención frente a las resistencias bacterianas. ! ! El Dr. Jerónimo Pachón Díaz, Profesor Emérito de la Universidad de Sevilla, como Tutor de la Tesis Doctoral, y el Dr. José Miguel Cisneros Herreros, Jefe de Servicio de Enfermedades Infecciosas del Hospital Virgen del Rocío, como Director de la Tesis Doctoral, CERTIFICAN: Que la Tesis para optar al grado de Doctor por la Universidad de Sevilla titulada “Resultados de un programa hospitalario para la optimización del uso de los antimicrobianos basado en medidas educativas. Nuevos diseños de intervención frente a las resistencias bacterianas” ha sido realizada por el Licenciado D. José Molina Gil- Bermejo bajo nuestra supervisión, considerando que reúne los requisitos necesarios para su presentación. Y para que conste los efectos oportunos, expiden la presente certificación en Sevilla a 1 de septiembre de 2021. Fdo.: Jerónimo Pachón Díaz Fdo.: José Miguel Cisneros Herreros Tutor de la Tesis Doctoral Director de la Tesis Doctoral CISNEROS HERREROS JOSE MIGUEL - 24160698A Firmado digitalmente por CISNEROS HERREROS JOSE MIGUEL - 24160698A Fecha: 2021.09.04 18:31:46 +02'00' PACHON DIAZ JERONIMO - 28377156D Firmado digitalmente por PACHON DIAZ JERONIMO - 28377156D Nombre de reconocimiento (DN): c=ES, serialNumber=IDCES-2837 7156D, givenName=JERONIMO, sn=PACHON DIAZ, cn=PACHON DIAZ JERONIMO - 28377156D Fecha: 2021.09.04 18:55:39 +02'00' ! !" 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'8$" ,&$%,-)9-0." 0&" /.$" ()%-:-@%-+.$;" Y(" +.,,&+%(" &3(/*(+-@)" 0&" /.$" BCEF"0&:&"-)+/*-,"-)0-+(0.,&$"0&"%,&$"%-5.$V"+/H)-+.$6"'-+,.:-./@9-+.$6"=" 0&" 5,.+&$.6" +.'." $&" 4(" 0&$+,-%." ()%&,-.,'&)%&;" #$5&+-(/'&)%&" ! !k" -'5.,%()%&" $&,8" 0&1-)-," /(" $.$%&)-:-/-0(0" (" /(,9." 5/(2." 0&" /(" -)%&,3&)+-@)eO6eU6"*)"($5&+%."7*&")."4("$-0."&3(/*(0."&)"/("'(=.,H("0&" -)%&,3&)+-.)&$" 5*:/-+(0($!b6" =" 7*&" 5.)&" &)" ,-&$9." /(" %,($/(+-@)" 0&" ,&$*/%(0.$"("/("3-0(",&(/; ! ! ! ! !f" " V(1)(!C*!@$#(%!8$-/$-'($-(%!.#!-0"#%'-4(,-20!8($(!)/%!<=>?! e!qeU *! A. Generar nueva evidencia clínica sobre uso apropiado de antimicrobianos Estrategias de tratamiento óptimo (dosis, vía de administración, duración) en los síndromes infecciosos más prevalentes. Estrategias de tratamiento y profilaxis antimicrobianas óptimas en poblaciones especiales: inmunodeprimidos, obesos, etc. Efectividad de las estrategias de simplificación: esquemas libres de carbapenémicos, monoterapia frente a tratamiento combinado, etc. Programas de diagnóstico microbiológico rápido y su impacto clínico real. Monitorización de niveles plasmáticos de antimicrobianos y su impacto clínico real. B. Identificar los tipos de intervención y estrategias de implementación más eficientes Análisis comparativos de intervenciones en términos de efectividad, viabilidad y costes. Identificar elementos que garanticen la sostenibilidad en el tiempo de los PROA. Diseños en atención primaria, urgencias, centros sociosanitarios y otros entornos no hospitalarios. Definir elementos facilitadores para la implementación de los PROA en ámbitos sin disponibilidad de expertos en terapia antimicrobiana: personal necesario (en especial, el papel de Enfermería), formación a distancia, herramientas de soporte electrónico a decisiones clínicas, etc. Identificar los factores de comportamiento (sociales, organizativos, emocionales, culturales) que condicionan el uso de antibióticos e incorporarlos al diseño de los PROA. C. Desarrollar diseños y metodologías óptimas para establecer la efectividad de los PROA Inversión en infraestructuras que faciliten las intervenciones y análisis de resultados nivel individual y poblacional. Establecer estándares para los indicadores de proceso y de resultado en estudios cuasiexperimentales y observacionales. Priorizar el diseño de estudios de efectividad que eviten el riesgo de sesgos: ensayos aleatorizados, aleatorización de grupos, estudios cuasi-experimentales controlados con análisis de tendencia. Aplicación de nuevos métodos estadísticos para evaluar los beneficios y riesgos de las nuevas estrategias de tratamiento: DOOR/RADAR, etc. ! Oc" V(1)(!C!K,/0'*L*!@$#(%!8$-/$-'($-(%!.#!-0"#%'-4(,-20!8($(!)(%!<=>?*! ! D. Definir indicadores adecuados para evaluar el impacto de los PROA Indicadores de resultados clínicos: definir y validar un conjunto de indicadores clínicos estandarizados que aporten información significativa sobre el impacto en salud de los PROA. Indicadores de consumo de antimicrobianos: definir y validar indicadores de consumo de antibióticos en entornos extrahospitalarios, para las prescripciones realizadas tras el alta hospitalaria, y para definir el uso apropiado de antimicrobianos. Indicadores de resistencias microbianas: cuantificar el riesgo de desarrollo de resistencias en función de la selección, dosis y duración del tratamiento antimicrobiano. Indicadores de proceso: definir y validar indicadores de proceso que permitan establecer una relación demostrable con resultados clínicos clínicamente significativos de los PROA. ! ! " " ! Od" " " " " " " " Fundamento ! ! 2. FUNDAMENTO. #/"-)+,&'&)%."'*)0-(/"0&"/($",&$-$%&)+-($":(+%&,-()($"*,9&"("/("+.'*)-0(0" +-&)%H1-+(" (" 0&$(,,.//(," '&+()-$'.$" &1-+(+&$" 5(,(" +.)%,./(," $*" &`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c" 4. OBJETIVOS. 4.a. 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TT" " " " Artículo 1 TU" Clinical Infectious Diseases 1992 • CID 2017:65 (15 December) • Molina etal Long-Term Impact of an Educational Antimicrobial Stewardship Program on Hospital-Acquired Candidemia and Multidrug-Resistant Bloodstream Infections: AQuasi-Experimental Study of Interrupted Time-Series Analysis JoséMolina, 1 GermánPeñalva, 1 María V.Gil-Navarro, 2 JuliaPraena, 1 José A.Lepe, 1 María A.Pérez-Moreno, 2 CarmenFerrándiz, 3 TeresaAldabó, 3 ManuelaAguilar, 1 PeterOlbrich, 4 Manuel E.Jiménez-Mejías, 1 María L.Gascón, 3 RosarioAmaya-Villar, 3 OlafNeth, 4 María J.Rodríguez-Hernández, 1 AntonioGutiérrez-Pizarraya, 1 JoséGarnacho-Montero, 5 CristinaMontero, 6 JosefinaCano, 6 JuliánPalomino, 1 RaquelValencia, 1 RocíoÁlvarez, 1 ElisaCordero, 1 MartaHerrero, 1 and José M.Cisneros 1 ; for the PRIOAM team Departments of 1 Infectious Diseases, Microbiology and Preventive Medicine, 2 Pharmacy, 3 Critical Care, and 4 Pediatric Infectious Diseases and Immunodeficiency, Institute of Biomedicine of Seville, University Hospital Virgen del Rocio, Spanish National Research Council, University of Seville, and 5 Department of Critical Care, University Hospital Virgen Macarena, University of Seville and 6 Department of Pediatric Critical Care and Emergency, University Hospital Virgen del Rocio, Seville, Spain Background. The global crisis of bacterial resistance urges the scientific community to implement intervention programs in healthcare facilities to promote an appropriate use of antibiotics. However, the clinical benefits or the impact on resistance of these interventions has not been definitively proved. Methods. We designed a quasi-experimental intervention study with an interrupted time-series analysis. Amultidisciplinary team conducted a multifaceted educational intervention in our tertiary-care hospital over a 5-year period. The main activity of the program consisted of peer-to-peer educational interviews between counselors and prescribers from all departments to reinforce the principles of the proper use of antibiotics. We assessed antibiotic consumption, incidence density of Candida and multidrug-resist- ant (MDR) bacteria bloodstream infections (BSIs) and their crude death rate per 1000 occupied bed days (OBDs). Results. A quick and intense reduction in antibiotic consumption occurred 6months after the implementation of the intervention (change in level, −216.8 defined daily doses per 1000 OBDs; 95% confidence interval, −347.5 to −86.1), and was sustained during subsequent years (average reduction, −19,9%). In addition, the increasing trend observed in the preintervention period for the incidence density of candidemia and MDR BSI (+0.018 cases per 1000 OBDs per quarter; 95% confidence interval, −.003 to .039) reverted toward a decreasing trend of −0.130 per quarter (change in slope, −0.029; −.051 to −.008), and so did the mortality rate (change in slope, −0.015; −.021 to −.008). Conclusions. This education-based antimicrobial stewardship program was effective in decreasing the incidence and mortality rate of hospital-acquired candidemia and MDR BSI through sustained reduction in antibiotic use. Keywords. Antimicrobial stewardship programs; antimicrobial resistance; educational interviews; hospital-acquired infections; multidrug-resistant bloodstream infections. The global increase of bacterial resistance over recent decades has been recognized by public health organizations as a priority threat that needs to be addressed urgently by the scientific community [1]. Infections caused by resistant bacteria produce increased morbidity and mortality rates, as well as higher healthcare costs [2], and the inappropriate use of antimicrobial agents is probably the most important factor responsible for these increases [3]. In this setting, healthcare centers have been encouraged to implement antimicrobial stewardship programs (ASPs) to improve antibiotic misuse and fight back against bacterial resistance [4]. Evidence supporting the efficacy of ASPs is still incomplete, and recent meta-analysis has shown that up to 80% of reviewed studies lacked a minimum methodological quality required to obtain reliable and reproducible conclusions on the clinical impact of ASPs [5]. Although many of these programs have proved effective in reducing antibiotic consumption and improving the quality of prescriptions, there is still a lack of evidence supporting clear clinical benefits (ie, reduction in mortality rate related to infections) [5, 6]. The question regarding which indicators are best to assess the clinical impact of ASPs also remains unanswered [7]. MAJOR ARTICLE © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: [email protected]. DOI: 10.1093/cid/cix692 Received 9 June 2017; editorial decision 19 July 2017; accepted 3 August 2017; published online August 7, 2017. Correspondence: J.M. Cisneros, Department of Infectious Diseases, Microbiology and Preventive Medicine, University Hospital Virgen del Rocio, Avenue Manuel Siurot, 41013, Seville, Spain ([email protected]). Clinical Infectious Diseases ® 2017;65(12):1992–9 STANDARD XX XXXX Downloaded from https://academic.oup.com/cid/article-abstract/65/12/1992/4069913 by Biblioteca Virtual del Sistema Sanitario Público de Andalucía user on 29 June 2018 ! Te" " Long-Term Impact of an EducationalASP • CID 2017:65 (15 December) • 1993 Data on the real impact of these programs on bacterial resistance are also incomplete. Although antibiotic pressure is a well-known risk factor for Candida spp. and multidrug-resistant (MDR) bacteria bloodstream infections (BSIs) [8–10], the reverse effect—that is, reduced consumption of antibiotics bringing susceptible microorganisms back to a center or geographic area—has not been so well established. Hitherto, different ASPs have achieved reductions in specific mechanisms of resistance by restricting concrete antibiotic classes [11–13], but a global improvement in bacterial ecology of healthcare centers has rarely been reported, and only the short-term impact has been described in most studies [5, 6]. The Institutional Program for the Optimization of Antimicrobial Treatment (PRIOAM) is an educational ASP started at our hospital in January 2011, which resulted in a reduction in antimicrobial consumption within 1year after its implementation [14]. We hypothesized that, if this reduction in antibiotic pressure was maintained throughout time, a significant decrease should also be observed in the incidence of hospital-acquired BSIs produced by MDR bacteria and Candida spp., as well as in associated mortalityrates. METHODS StudyDesign The study was an interrupted time-series (ITS) quasi-experi- mental before-after study, based on an ecological time-trend analysis, compliant with the ORION statement. Setting The program was performed at the University Hospital Virgen del Rocio (Seville, Spain), a tertiary-care teaching hospital with 1177 beds (including 72 intensive care unit [ICU] beds), and active solid-organ and hematopoietic stem-cell transplantation programs. No data from pediatric patients (134 beds, settled in a different building) were recorded for this study. StudyPeriod The study period included 28 quarters between January 2009 and December 2015. PRIOAM was initiated in January 2011. Intervention The methods have been described elsewhere [14]. In brief, a multidisciplinary team of 10 counselors was set up, including infectious diseases experts from different departments of the hospital. They randomly chose 1 antibiotic prescription each week and held educational interviews (EIs) with the prescriber, reviewing the key aspects of antibiotic treatment of the case. The interview followed a structured questionnaire, and the approach was strictly educational; clinical charts were not reviewed and no changes in antibiotic treatment were required. Patient data remained anonymous. Additional educative measures included (1) update, publication, and diffusion of local guidelines for the management of most frequent infectious syndromes [15], which were also used as a reference to assess the quality of prescriptions during the interviews; (2) monthly educational meetings with the counselor team to reinforce the homogeneity of criteria and to encourage continuous learning regarding the main aspects of antibiotic use; (3) quarterly information regarding the profile of antibiotic use in every department; (4) yearly information on the incidence of bacterial resistance reported to all departments, and (5) yearly clinical sessions to analyze the specific results of the program in each unit, to outline the improvement strategies for the following year. The program received institutional support, and its objectives were included in the agreement signed annually by each department with the hospital management. In November 2012 a parallel transmission control program was started at the ICU due to a long-term endemic of carbapenem-resistant Acinetobacter baumannii. This program included active surveillance of hygienic measures in the unit and weekly screening of asymptomatic carriers of MDR gram-negative bacilli for all patients admitted to the ICU. No other interventions were performed in the center during the study period. Study Measures Data on antibiotic ATC group J01 (antibacterials for systemic use) consumption were recorded quarterly. Defined daily doses (DDDs) per 1000 occupied bed days (OBDs) were calculated according to the Anatomical Therapeutical Chemical classification system [16]. We a l s o a na ly ze d t h e i n ci de nc e d e nsi ty p er 1 00 0 O BD s of h osp ital-acquired BSIs produced by the 6 most frequent microorganisms (coagulase-negative Staphylococci excluded): Escherichia coli, Klebsiella pneumoniae, A. baumannii, Pseudomonas aeruginosa, Staphylococcus aureus and Candida spp. Every strain was classified as MDR or non-MDR according to the criteria described below. The impact on mortality rates was assessed as the all-cause crude death rate [17] (deaths per 1000 OBDs per quarter) on day +14 after the diagnosis of these episodes of BSI. Microbiological Definitions Hospital-acquired BSIs were defined as those diagnosed based on blood cultures obtained ≥48 hours after hospital admission, or <48 hours after admission in patients hospitalized during the previous 3 weeks. Recurrent isolation of the same microorganisms was considered to represent a unique episode of BSI unless the sample was obtained 1 month after the last positive blood culture. The MDR categorization was applied for extended-spectrum β-lactamases (ESBLs), derepressed AmpC β-lactamases or carbapenemase-producing Enterobacteriaceae, all isolates of methicillin-resistant S. aureus and Candida spp., and all P. aeruginosa and A. baumannii strains fulfilling the German Society for Hygiene and Microbiology criteria for MDR organisms [18, 19]. The ESBL and methicillin-resistant S. aureus criteria followed the European Committee on Antimicrobial Susceptibility Testing (EUCAST) recommendations [20, 21]. Downloaded from https://academic.oup.com/cid/article-abstract/65/12/1992/4069913 by Biblioteca Virtual del Sistema Sanitario Público de Andalucía user on 29 June 2018 ! Tk" 1994 • CID 2017:65 (15 December) • Molina etal Statistical Analysis ITS regression analysis was performed for each variable according to the Cochrane Effective Practice and Organization Care method [22], to compare time trends before and after the intervention. Two standardized effect sizes were estimated: a change in level (difference between the observed outcome at the first time point of the intervention and that predicted by the preintervention trend) and a change in trend (difference between pre- and postintervention slopes) after the intervention. Differences were considered statistically significant at P < .05 (2-tailed tests). Statistical analyses were performed using IBM SPSS Statistics software, version19.0. To assess the robustness of the findings from the ITS analysis, we also performed a joinpoint regression analysis [23] of each dependent variable as a sensitivity analysis. The aim was to identify any statistically significant change occurring in the linear slope of the trend for each variable and assess mathematically whether it occurred over the same time period as the intervention. We used the joinpoint regression program [24] to run the calculations. RESULTS Educational Interviews A total of 3176 EIs were performed with prescribers from all clinical units; 1206 EIs were held in the first year, followed by an average of 500 per year. The proportion of prescribers interviewed the first year was 66.3% of the 585 prescribing physicians, followed by 49.7% per year. The average number of EIs was 3.1 EIs per prescriber the first year, followed by 2.2 EIs per prescriber per year. The average time required for each interview was 10 minutes. In the first quarter after the program implementation up to 53% of antibiotic prescriptions evaluated were considered inappropriate, improving to 39% by the end of the study period (χ2 test; P<.01). Of 559 prescribers who completed an anonymous satisfaction survey after the EI, 97.7% evaluated it positively. Antibiotic Consumption The implementation of PRIOAM was followed by a significant decrease in antibiotic consumption, maintained during the following years. This reduction was observed for all classes of antibiotics (data not shown). The median consumption dropped from 1008 (interquartile range [IQR], 980–1078) to 774 (750– 787) DDDs per1000 OBDs from the first to the last year. Figure1 shows the time-trend analysis, with a significant change in level after the ninth trimester of −216.8 DDDs per 1000 OBDs (95% confidence interval [CI], −347.5 to −86.1; P<.01). Compared with expected antibiotic consumption according to the preintervention trend, a sustained reduction with a relative effect (difference from the preintervention trend) between −21.5% and −18.3% was observed throughout the study period. Impact on Incidence of Hospital-Acquired Candidemia, Multidrug- Resistant (MDR) Bacteria Bloodstream Infections (BSIs), and Non-MDR BSIs The incidence density of hospital-acquired candidemia and MDR BSI diminished parallel to the antibiotic pressure. The increasing trend in the preintervention period (0.018 cases per 1000 OBDs per quarter; 95% CI, −.003 to .039) reverted toward a decreasing trend with a change in slope of −0.029 cases per 1000 OBDs per quarter (−.051 to −.008; P<.05) (Figure2). Compared with the expected trend in the preintervention period, a relative reduction of −24.4% was observed soon after the implementation of the program (in the 10th quarter) and was estimated to be of up to −71.0% by the end of the study Figure 1. Changes in antibiotic consumption. ATC group J01 (antibacterials for systemic use); DDDs, defined daily doses; OBDs, occupied bed days. Downloaded from https://academic.oup.com/cid/article-abstract/65/12/1992/4069913 by Biblioteca Virtual del Sistema Sanitario Público de Andalucía user on 29 June 2018 ! Tf" " Long-Term Impact of an EducationalASP • CID 2017:65 (15 December) • 1995 period, 5years later. Incidence densities per quarter for each specific microorganism were also recorded. Conversely, the incidence density of hospital-acquired BSIs produced by non- MDR strains of the same microorganisms under study did not change during the intervention period (slope −0.004; 95% CI, −.045 to .037; P=.85) (Figure3). Impact on Mortality Rates for Hospital-Acquired Candidemia and Multidrug-Resistant Bloodstream Infections The all-cause 14-day crude death rate for hospital-acquired candidemia and MDR BSIs was reduced parallel to its incidence. Asignificant change was proved in the mortality trends between the preintervention period (increasing trend of 0.011 deaths per 1000 OBDs per quarter; 95% CI, .005 to .017; P<.001) and the postintervention period (change in slope, −0.015 deaths per 1000 OBDs per quarter; −.021 to −.008; P<.001) (Figure4). This change occurred 3months after the PRIOAM implementation, with a level reduction of −0.045 (95% CI, −.087 to −.004; P<.01) and an estimated relative effect of −27.9% compared with the expected mortality rate according to the preinterventiontrend. The all-cause 14-day crude death rate for hospital-acquired BSIs produced by any microorganism (either MDR or susceptible) also decreased after the intervention (Figure5), reversing from a preintervention increasing trend (0.019; 95% CI, −.005 to .034) to a decreasing trend after the implementation of the program (change in slope −0.025; −.040 to −.009; P<.05). Figure 3. Evolution of incidence of hospital-acquired non–multidrug-resistant (non-MDR) bacterial bloodstream infections (BSIs). OBDs, occupied bed days. Figure2. Impact on incidence of hospital-acquired candidemia and multidrug-resistant (MDR) bacterial bloodstream infections (BSIs). OBDs, occupied bed days. Downloaded from https://academic.oup.com/cid/article-abstract/65/12/1992/4069913 by Biblioteca Virtual del Sistema Sanitario Público de Andalucía user on 29 June 2018 UU" Clinical impact of ASP and IDC on cancer patients / Journal of Infection 79 (2019) 206–211 207 consumption, with scarce information on their clinical impact. 6–9 This is why the generation of good-quality evidence supporting the clinical benefits and feasibility of these initiatives has been demanded as a critical aspect to promote their application in this setting. 2 In this article, we show the long-term results achieved by an educational ASP associated with Infectious Diseases consultation (IDC) on mortality and antibiotic use of hospitalized patients with solid cancer over a 9-year period. Methods Study design and period A quasi-experimental ecologic study with a time-trend analysis was performed over 34 quarters from January 2009 to June 2017. Setting The intervention was implemented in the 20-bed Oncology ward of University Hospital Virgen del Rocío, a tertiary-care hospital in Seville (Spain). Patients with solid, non-hematological malignancies were attended in this unit. The same two senior oncologists attended hospitalized patients throughout the whole study period. Ethics The study was approved by the local Ethics Committee. Intervention A stable IDC program has been performed in the Oncology ward for the last 20 years, consisting of bedside advice on the management of complex infections and early report of all bloodstream infections (BSI). In January 2011, an educational ASP was prompted throughout the entire hospital, whose methodology and general results have already been published. 10,11 In brief, it consisted of a bundle of educative measures, designed and performed by a multidisciplinary team including Infectious Diseases physicians, Microbiologists, Pharmacists, Intensive Care physicians, Paediatricians and Preventivists. In the specific case of Oncology, the intervention included: a) development of consensual clinical guidelines for common infectious syndromes in patients with cancer 12 ; b) face-to-face structured educational interviews with Oncologists on the basis of specific antibiotic prescriptions to reinforce the principles of the correct use of antibiotics (supplementary file 1); prescriptions employed for interviews were randomly selected (not targeted toward specific classes of antibiotics), and their aim was merely pedagogic (not auditing); c) periodical clinical sessions tackling practical aspects of the management of infections in Oncology; d) incorporation of the objectives of the ASP to the annual agreement signed by the department and the hospital director; and e) quarterly reports to the Head of department with the level of attainment of annual pre-agreed objectives. The usual Infectious Diseases consultant on the Oncology ward led the implementation of these tasks in the department. The main messages tackled in educational interviews were: identification and management of sepsis, interpretation of microbiologic results, de-escalation and sequential oral treatments whenever possible, diversification of antibiotic prescriptions and training in optimal duration of antibiotic courses (supplementary file 1). No other interventions concerning antibiotic use (e.g. antibiotic policies, restrictions, etc.) were performed during the study period. The infection control program in this department consisted exclusively of the isolation of patients with resistant bacteria recovered from clinical samples. No new actions were implemented regarding the prevention of infections in these patients either. Outcomes The incidence of BSI produced by the six most relevant microorganisms was monitored (coagulase-negative Staphylococci excluded): Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Staphylococcus aureus, and Candida spp., and specifically the incidence of multidrug-resistant strains in the Oncology ward (as defined in supplementary file 2). Surveillance data were stored and analysed using WHONET 5.3. The impact of the intervention on the clinical management of serious infections was measured through the rate of early (7-day) and late (30-day) all-cause mortality among patients developing these BSI, which were recorded yearly. The magnitude of the effect on mortality was also evaluated through quarterly measures of the incidence density (ID) of early and late deaths among patients with BSI (i.e. number of deaths per 10 0 0 admissions). Patients dying in less than 24 h after blood samples collection were not considered for the mortality analysis, as previously proposed, 13,14 for a better selection of patients actually benefitting from this intervention targeting an optimised use of antibiotics. Oncologic patients admitted in such severe condition that produces death in just a few hours are frequently not candidates for intensive support, which undercuts the effectiveness of any other therapeutic measure. The potential changes in antibiotic use promoted by the intervention were evaluated through quarterly measures of the consumption of all-class antibiotics (ATC group J01 and J02), and specifically antipseudomonal betalactams. Consumption was calculated as Defined Daily Doses (DDD) per 100 occupied bed-days (OBD), according to the Anatomical Therapeutical Chemical Classification (ATC/DDD) methodology. 15 In order to evaluate the implementation of switching to oral treatments, the quarterly rate of oral antibiotic agents DDDs prescribed over the global number of DDDs was also recorded. The impact on direct costs was evaluated through the monitoring of quarterly pharmacy expenditures in antimicrobial drugs of the Oncology department. Statistical analysis Two different analyses were performed to evaluate the impact of both interventions (the IDC and the ASP). A time-trend study with a segmented-regression analysis was carried out during the whole study period (2009–2017) to assess the long-term impact of the combination of both interventions. Additionally, to evaluate the specific effect of the ASP, an interrupted time-series (ITS) regression analysis was performed to compare trends before and after the program, following Cochrane Effective Practice and Organization Care recommendations. 16 Two standardized effect sizes were estimated: changes in level (difference between the observed outcome at the first time point of the intervention and the point predicted by the pre-intervention trend), and changes in trend (difference between pre- and post-intervention slopes) following the intervention. A p value of < 0.05 was considered statistically significant. Tests were 2-tailed. Statistical analyses were performed with Joinpoint Regression Program v.4.5.0.1 and R software v.3.4.3. Results 252 episodes of BSI over 34 quarters were recorded. The ID of BSI remained stable (average incidence 4.37 episodes per 10 0 0 OBD, quarterly percentage of change −1% CI95% −2.5, 0.5, p = 0.17), as well as the ID of BSI produced by multi-drug resistant bacteria, which kept low during all the study period (average incidence 0.62 ! Ue" " 208 Clinical impact of ASP and IDC on cancer patients / Journal of Infection 79 (2019) 206–211 Fig. 1. Time trends of the early (7-day) and late (30-day) mortality of patients with bloodstream infections (BSI) throughout the study period. ∗The decreasing trend was statistically significant for all indicators, including early mortality rate ( −13.3% yearly reduction; CI95% −20.5; −5.4 p = 0.006), late mortality rate ( −8,1% yearly reduction; CI95% −15; −0.7% p = 0.03), incidence density of early deaths ( −18% annual reduction; CI95% −23.2; −12.5 p < 0.0 0 01) and incidence density of late deaths ( −13.5% annual reduction; CI95% −19.9; - 6.5, p = 0.003) among patients with BSI. 2017 data refers to the months included in the study period (January 1st to June 30th). episodes per 10 0 0 OBD, quarterly percentage of change 0,2% CI95% −0.8, 1.2, p = 0.70) (see supplementary file 2). A total number of 128 individual educational interviews (average 10 interviews per physician a year), 10 clinical sessions (1–2 per year) and 26 reports to the Head of department were delivered after the initiation of the ASP in January of 2011. A significant reduction in early and late mortality of patients with BSI was observed over the whole study period. Seven and 30- day crude mortality rate decreased a 13.3% per year (CI95% −20.5; −5.4 p < 0.01) and −8.1% per year (CI95% −15; −0.7% p = 0.03) respectively. The ID of early deaths per 10 0 0 admissions among patients with BSI was also reduced ( −18% annual reduction; CI95% −23.2; −12.5 p < 0.0 0 01), as well as the ID of late deaths ( −13.5% annual reduction; CI95% −19.9; - 6.5, p < 0.01) ( Fig. 1 ). A significant reduction in the global consumption of antibiotics was proved (quarterly reduction −0.4% CI95% −0.7; −0.1, p = 0.01), and specifically for antipseudomonal betalactams (quarterly reduction −1.23% CI95% −1.85; −0.61, p < 0.001). Direct expenditure in antimicrobials was also significantly reduced by the end of the study period (quarterly reduction −1484 €CI95% −2020 to −949 €, p < 0.01). Conversely, the rate of oral antibiotics prescribed over the total number of DDDs increased progressively (quarterly increase 0.90% CI95% 0.10; 1.72, p = 0.02). The evolution of consumption for specific antibiotics can be found in supplementary file 3. We analysed the specific impact of our ASP on these results through a before-after ITS analysis ( Table 1 ). After the implementation of the ASP, the descending trend in the ID of mortality observed in the pre-intervention period was maintained, with no significant changes in slope proved in this case ( Table 1 , Fig. 2 ). When variables assessing antibiotic use were analysed, a significant inflection point was demonstrated after the ASP initiation for all of them, except for the rate of oral antibiotic prescriptions, for which a non-significant improvement was also observed ( Table 1 and Fig. 3 ). Evaluation of the quality of the prescriptions was not systematically performed, but the educational interviews allowed describing some of the most frequent reasons for inappropriate use of antibiotics in the unit. An incorrect selection of the agent according to the clinical diagnosis (28.6%) in the case of empiric treatments, and failing to de-escalate or inappropriate duration in the case of definite therapies (19.6% for both causes) motivated most of the inadequate prescriptions (see supplementary file 4). Discussion Our results show that the association of an educational ASP with IDC was able to achieve long-term improvements in antibiotic use, and was accompanied by a reduction of the mortality of bacteraemic infections among patients with solid tumours. To our knowledge, this is the first study proving such benefits for these interventions in the setting of immunocompromised hosts. A maintained reduction in both the incidence and the mortality rate of patients with BSI ( Fig. 1 ) was observed throughout the study period. The 30-day mortality rate described at the beginning of the study (mean rate 39%) was similar to other large cohorts, 3,17 but by the end of the intervention, it had significantly decreased to a mean mortality rate of 20%. Noticeably, our results also show a significant reduction in early crude mortality throughout the study period ( Fig. 1 ), which would correlate better to an improved management of these acute infections, and should not be expected to be modified by other improvements in general care of cancer patients (e.g. chemotherapy schemes). IDC had already proved beneficial to the survival of patients with BSI produced by S. aureus 18 and Candida spp. 14 . However, other studies with a wider scope, analysing all-cause BSI, have only observed better antimicrobial use with no impact on mortality when assessing the role of the counselling. 19,20 Moreover, none of these studies have assessed the impact of IDC in the specific setting of patients with cancer. Our results provide valuable information in this regard, showing a significant improvement in survival parallel to maintained IDC in a large cohort of cancer patients with BSI, which was not limited to specific aetiologies. With this study, we aimed to evaluate the specific impact of the ASP on mortality. The pre-intervention decreasing trend in mortality was maintained after the implementation of the stewardship program, but no significant changes in the slope were established ( Fig. 2 ). These results prevent us from definitely establishing a causality relationship between the ASP itself and the reduction of mortality, but seems likely that the combined effect of both interventions (the IDC and the ASP) contributed significantly for this sustained trend. At least, these data should highlight the safety of the strategies of rational use of antibiotics promoted by the ASP, also in this population of immunosuppressed hosts. These results are consistent with that obtained by a recent clinical trial developed by our group, which demonstrated the safety of interrupting antibiotic treatment in hematologic patients with febrile neutropenia after confirming the clinical cure. 21 We believe this new information to be relevant, since most studies on ASP developed in immunosuppressed populations have limited their results to the reduction in the consumption of certain antibiotics with no information on their clinical effects or, at best, showing an absence of an increase in mortality. 6–9 To our knowledge, before ours only two ASPs developed in patients with cancer have reported a reduction in mortality. 22,23 They both based their conclusions on twogroup comparison tests which directly measured differences before and after the intervention, but this kind of analyses have been strongly discouraged in the assessment of ASPs due to their high Uk" Clinical impact of ASP and IDC on cancer patients / Journal of Infection 79 (2019) 206–211 209 Table 1 Interrupted time-series analysis of the clinical outcomes and antibiotic use changes observed after the implementation of the antimicrobial stewardship program. Change in level a (CI95%) Change in slope b (CI95%) Deaths per 1000 admissions (7 days) −0.43 ( −7.07; 6.20) −0.07 ( −1.43; 1.29) Deaths per 1000 admissions (30 days) −0.34 ( −9.71; 9.01) −0.77 ( −2.69; 1.15) DDD of all-class antimicrobials (J01 + J02) /100 OBD 0.95 ( −4.04; 5.96) −1.98 ( −3.31; −0.64) ∗ DDD of antipseudomonal betalactams /100 OBD −4.04 ( −7.6 1; −0.46) ∗ −1.08 ( −1.96; −0.21) ∗ Pharmacy expenditures in antimicrobial agents( €) −4770 ( −7360; −2180) ∗ −1484 ( −2020; −949) ∗ Rate of DDD of oral antimicrobials over all DDD (%) −2.14 ( −10.48; 6.20) 0.51 ( −1.41; 2.42) OBD: Occupied bed-days; DDD: defined daily dose. a Reduction in the first quarter after the intervention with respect to the expected value. b Average reduction per quarter after the intervention. ∗ p < 0.05 . Fig. 2. Interrupted time-series analysis of the trends in mortality among patients with bloodstream infections (BSI) observed before and after the implementation of the antimicrobial stewardship program. (a) Before-after trends in incidence density of early deaths per 10 0 0 admissions among patients developing bloodstream infections, measured at the 7th day after the BSI diagnosis. (b) Before-after trends in incidence density of late deaths per 10 0 0 admissions among patients developing bloodstream infections, measured at the 30th day after the BSI diagnosis. Solid blue lines show the observed trend during the pre-intervention period. Dashed blue lines show the expected trend after the intervention according to the preintervention values. Solid red lines show the observed trend after the intervention. Change in level : indicates the reduction in the first trimester after the intervention with respect to the expected value. Change in trend . Indicates the average reduction achieved per quarter after the intervention. IDC : Infectious Diseases Counseling; ASP : Antimicrobial Stewardship Program. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) ! Uf" " 210 Clinical impact of ASP and IDC on cancer patients / Journal of Infection 79 (2019) 206–211 Fig. 3. Interrupted time-series analysis of the trends in antibiotic use observed after the implementation of the antimicrobial stewardship program. (a) Before-after trends in global consumption of antibiotics; (b) Before-after trends in consumption of antipseudomonal betalactams; (c) Before-after trends in the rate of DDD of oral antibiotics prescribed over the total number of DDDs; (d) Beforeafter trends in the direct Pharmacy expenditures in antimicrobials. Solid blue lines show the observed trend during the pre-intervention period. Dashed blue lines show the expected trend after the intervention according to the pre-intervention values. Solid red lines show the observed trend after the intervention. Change in level : indicates the reduction in the first trimester after the intervention with respect to the expected value. Change in trend . Indicates the average reduction achieved per quarter after the intervention. IDC : Infectious Diseases Counseling; ASP : Antimicrobial Stewardship Program. risk of bias. 24 Indeed, the internal validity of both studies seems to be undercut by a limited sample size and study period, and a seemingly uneven distribution of basal characteristics and clinical presentation of the infections evaluated between groups. 22,23 ITS have been pointed out as the preferential method to assess the impact of interventions, as we did. 16,25 The ASP had a significant impact on the use of antibiotics in the unit. Our data show how the implementation of structured interventions is necessary to change the way antibiotic are used in these kinds of units, suggesting that the sole clinical counselling may be insufficient to achieve this goal. In fact, when variables regarding antimicrobial consumption were analysed, we observed stable or even worsening trends in antibiotic use during the years preceding the ASP ( Fig. 3 ). This might be explained because in traditional IDC, the intervention of the expert is limited to the patients attended by the consultant, and this may not necessarily change the use of antibiotics in the entire unit. Our ASP consisted of a bundle of educational interventions aiming to improve the knowledge of all Oncologists on the principles of a correct antimicrobial treatment, 10 and it was only after their implementation when global antibiotic use in the unit was truly improved. The study has some limitations. The possibility of an ecologic bias is inherent to the design, and causality should be cautiously considered. We analysed in detail any possible interference from potential confounding factors, and recorded no significant changes in the incidence of all-cause BSI or multi-drug resistant microorganisms, no significant modifications in the portfolio of services of the Oncology department occurred, and no other interventions affecting antibiotic policies, infection control or antibiotic prophylaxis were implemented during the study period. A more complex methodology for the statistical analyses was also chosen to prevent some of these potential biases, 24 showing consistent results throughout all the variables evaluated. Causality cannot be definitely established by this design (especially for mortality variables), but the consistency between all these data supports the feasibility of this hypothesis. Of note, the expiration of the patent of imipenem (March 2010) and meropenem (April 2011), as well as minor changes in the costs of other antimicrobials throughout the study period may have explained some part of the reduction in Pharmacy expenditure reported. The effect of this circumstance on final results should be expected secondary, since the reduction in antibiotic consumption was not limited to carbapenems, and continued throughout the whole study period, years after the patent expiration. The close interrelation between both interventions evaluated (the IDC and the ASP) made it difficult to measure the precise weight of each one on the final outcomes achieved. Nonetheless, the significance of this precise information may be less relevant, since they are usually also carried out together in real-life. Finally, the single-centre design of the study makes it necessary to confirm the reproducibility of our results in different healthcare centres; in this sense, we believe that our work may serve as a solid proof-of-concept to encourage the implementation of similar programs, and offer new arguments to avoid the reluctance of clinicians still unsure of the safety of these initiatives. To sum up, this study suggests a substantial contribution of the IDC and ASPs for improving the outcome of BSI in patients with solid cancer, and for promoting better use of antibiotics in this setting. Our results also show the safety of the strategies of rational use of antibiotics among immunocompromised hosts, and define the necessity of implementing structured ASPs beyond sole clinical counselling to achieve this goal. CRediT authorship contribution statement José Molina: Conceptualization, Formal analysis, Writing - review & editing. Manuel Noguer: ec" Clinical impact of ASP and IDC on cancer patients / Journal of Infection 79 (2019) 206–211 211 Writing - review & editing. José Antonio Lepe: Data curation, Writing - review & editing. María Antonia Pérez-Moreno: Data curation, Formal analysis, Writing - review & editing. Manuela Aguilar-Guisado: Writing - review & editing. Roberto Lasso de la Vega: Writing - review & editing. Germán Peñalva: Data curation, Formal analysis, Writing - review & editing. Juan Carlos Crespo- Rivas: Writing - review & editing. María Victoria Gil-Navarro: Data curation, Writing - review & editing. Javier Salvador: Writing - review & editing. José Miguel Cisneros: Conceptualization, Funding acquisition, Writing - review & editing. Acknowledgments The whole Oncology department of the University Hospital Virgen del Rocío, whose close commitment with the program made possible its results, deserves a special mention. We also acknowledge the invaluable contribution of all the ASP professionals. We thank the hospital manager and the Andalusian Health Service (SAS) of the Regional Ministry of Health of Andalusia (Spain) for supporting the antimicrobial stewardship program. Preliminary data of this study were reported subsequently at the 28th European Congress of Clinical Microbiology and Infectious Diseases, and XXII Congress of the Spanish Society of Infectious Diseases and Clinical Microbiology. Funding The program received public funding from the Regional Health Ministry of Andalucía [PI-0361–2010], which did not participate in the development of the program or the analysis of its results. Transparency declaration None to declare. Supplementary material Supplementary material associated with this article can be found, in the online version, at doi: 10.1016/j.jinf.2019.07.002 . References 1. Davey P, Marwick CA, Scott CL, Charani E, McNeil K, Brown E, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev 2017(2). doi: 10.10 02/14651858.CD0 03543.pub4 . 2. Robilotti E, Holubar M, Seo SK, Deresinski S. Feasibility and applicability of antimicrobial stewardship in immunocompromised patients. Curr Opin Infect Dis 2017; 30 (4):346–53. doi: 10.1097/QCO.0 0 0 0 0 0 0 0 0 0 0 0 0380 . 3. Marín M, Gudiol C, Garcia-Vidal C, Ardanuy C, Carratalà J. Bloodstream infections in patients with solid tumors: epidemiology, antibiotic therapy, and outcomes in 528 episodes in a single cancer center. Med (Baltimore) 2014; 93 (3):143–9. doi: 10.1097/MD.0 0 0 0 0 0 0 0 0 0 0 0 0 026 . 4. Alevizakos M, Gaitanidis A, Andreatos N, Arunachalam K, Flokas ME, Mylonakis E. Bloodstream infections due to extended-spectrum β -lactamase- producing enterobacteriaceae among patients with malignancy: a systematic review and meta-analysis. Int J Antimicrob Agents 2017; 50 (5):657–63. doi: 10.1016/ j.ijantimicag.2017.07.003 . 5. Seo SK, Lo K, Abbo LM. Current state of antimicrobial stewardship at solid organ and hematopoietic cell transplant centers in the uS. Infect Control Hosp Epidemiol 2016; 37 (10):1195–200. doi: 10.1017/ice.2016.149 . 6. Horikoshi Y, Kaneko T, Morikawa Y, Isogai M, Suwa J, Higuchi H, et al. The north wind and the sun: pediatric antimicrobial stewardship program combining restrictive and persuasive approaches in hematology-oncology ward and hematopoietic stem cell transplant unit. Pediatr Infect Dis J 2018; 37 (2):164–8. doi: 10.1097/INF.0 0 0 0 0 0 0 0 0 0 0 01746 . 7. Snyder M, Pasikhova Y, Baluch A. Early antimicrobial De-escalation and stewardship in adult hematopoietic stem cell transplantation recipients: retrospective review. Open Forum Infect Dis 2017; 4 (4):ofx226. doi: 10.1093/ofid/ofx226 . 8. So M, Mamdani MM, Morris AM, Lau TTY, Broady R, Deotare U, et al. Effect of an antimicrobial stewardship programme on antimicrobial utilization and costs in patients with leukaemia: a retrospective interventional controlled study. Clin Microbiol Infect Off Publ Eur Soc Clin Microbiol Infect Dis 2017. doi: 10.1016/j.cmi. 2017.11.009 . 9. Wattier Rachel L, Levy Emily R, Sabnis Amit J, Dvorak Christopher C, Auerbach Andrew D. Reducing second gram-negative antibiotic therapy on pediatric oncology and hematopoietic stem cell transplantation services. Infect Control Hosp Epidemiol 2017; 38 (9):1039–47. doi: 10.1017/ice.2017.118 . 10. Molina J, Peñalva G, Gil-Navarro María V, Praena J, Lepe JA, Pérez-Moreno MA, et al. Long-term impact of an educational antimicrobial stewardship program on hospital-acquired candidemia and multidrug-resistant bloodstream infections: a quasi-experimental study of interrupted time-series analysis. Clin Infect Dis Off Publ Infect Dis Soc Am 2017. doi: 10.1093/cid/cix692 . 11. Cisneros JM , Neth O , Gil-Navarro MV , Lepe-Jiménez JA , Jiménez-Parrilla F , Cordero E , et al. Global impact of an educational antimicrobial stewardship program on prescribing practice in a tertiary hospital center. Clin Microbiol Infect 2014; 20 (1):82–8 . 12. PRIOAM Guidelines for the diagnosis and treatment of the infectious diseases. Infectious syndromes in patients with malignancies. University Hospital Virgen del Rocío (Seville, Spain). Available at: www.guiaprioam.com . Accessed 01 April 2019. 13. López-Cortés LE, Del Toro MD, Gálvez-Acebal J, Bereciartua-Bastarrica E, Fariñas MC, Sanz-Franco M, et al. Impact of an evidence-based bundle intervention in the quality-of-care management and outcome of staphylococcus aureus bacteremia. Clin Infect Dis Off Publ Infect Dis Soc Am 2013; 57 (9):1225–33. doi: 10.1093/cid/cit499 . 14. Lee Rachael A, Joanna Z, Camins BC, Griffin RL, Rodriguez JM, McCarty TP, et al. Impact of infectious disease consultation on clinical management and mortality in patients with candidemia. Clin Infect Dis Off Publ Infect Dis Soc Am 2018. doi: 10.1093/cid/ciy849 . 15. WHO collaborating center for drug statistics methodology. Available at https: //www.whocc.no/ddd/definition _ and _ general _ considera/ . Accessed 24 December 2017, n.d. 16. Norwegian Knowledge Cent. Effective practice and organisation of care (EPOC). Interrupted time series (ITS) analyses. EPOC Resources for review authors 2013. 17. Williams MD, Braun LA, Cooper LM, Johnston J, Weiss RV, Qualy RL, et al. Hospitalized cancer patients with severe sepsis: analysis of incidence, mortality, and associated costs of care. Crit Care Lond Engl 2004; 8 (5):R291–8. doi: 10.1186/ cc2893 . 18. Vogel M, Schmitz RPH, Hagel S, Pletz MW, Gagelmann N, Scherag A, et al. Infectious disease consultation for staphylococcus aureus bacteremia - A systematic review and meta-analysis. J Infect 2016; 72 (1):19–28. doi: 10.1016/j.jinf.2015.09. 037 . 19. Kerremans JJ, Verbrugh HA, Vos MC. Frequency of microbiologically correct antibiotic therapy increased by infectious disease consultations and microbiological results. J Clin Microbiol 2012; 50 (6):2066–8. doi: 10.1128/JCM.06051-11 . 20. Fluckiger U , Zimmerli W , Sax H , Frei R , Widmer AF . Clinical impact of an infectious disease service on the management of bloodstream infection. Eur J Clin Microbiol Infect Dis Off Publ Eur Soc Clin Microbiol 20 0 0; 19 (7):493–500 . 21. Aguilar-Guisado M, Espigado I, Martín-Peña A, Gudiol C, Royo-Cebrecos C, Falantes J, et al. Optimisation of empirical antimicrobial therapy in patients with haematological malignancies and febrile neutropenia (How long study): an open-label, randomised, controlled phase 4 trial. Lancet Haematol 2017; 4 (12):e573–83. doi: 10.1016/S2352- 3026(17)30211- 9 . 22. Rosa RG, Goldani LZ, dos Santos RP. Association between adherence to an antimicrobial stewardship program and mortality among hospitalised cancer patients with febrile neutropaenia: a prospective cohort study. BMC Infect Dis 2014; 14 :286. doi: 10.1186/1471- 2334- 14- 286 . 23. Madran B, Keske ¸S , Tokça G, Dönmez E, Ferhano ˘ glu B, Çetiner M, et al. Implementation of an antimicrobial stewardship program for patients with febrile neutropenia. Am J Infect Control 2018; 46 (4):420–4. doi: 10.1016/j.ajic.2017.09.030 . 24. Shardell M, Harris AD, El-Kamary SS, Furuno JP, Miller RR, Perencevich Eli N. Statistical analysis and application of quasi experiments to antimicrobial resistance intervention studies. Clin Infect Dis Off Publ Infect Dis Soc Am 2007; 45 (7):901–7. doi: 10.1086/521255 . 25. Wagner AK , Soumerai SB , Zhang F , Ross-Degnan D . Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 2002; 27 (4):299–309 . ! ed" " Artículo 3 eb" Journal Pre-proof Seven versus 14-days course of antibiotics for the treatment of bloodstream infections by Enterobacterales. A randomized, controlled trial José Molina, M.D., Enrique Montero-Mateos, M.D., Julia Praena-Segovia, M.D., Eva León-Jiménez, M.D., Ph.D., Clara Natera, M.D., Ph.D., Luis E. López-Cortés, M.D., Ph.D., Lucía Valiente, M.D., Clara M. Rosso-Fernández, M.D., Ph.D., Marta Herrero, M.D., Ana I. Aller-García, M.D., Ph.D., Ángela Cano, M.D., Belén Gutiérrez- Gutiérrez, M.D., Ph.D., Ignacio Márquez-Gómez, M.D., Rocío Álvarez-Marín, M.D., Ph.D., Carmen Infante, M.D., Ph.D., Cristina Roca, M.D., Adoración Valiente-Méndez, M.D., Jerónimo Pachón, M.D., Ph.D., José María Reguera, M.D., Ph.D., Juan Enrique Corzo-Delgado, M.D., Ph.D., Julián Torre-Cisneros, M.D., Ph.D., Jesús Rodríguez- Baño, M.D., Ph.D., José Miguel Cisneros, M.D., Ph.D., on behalf of the SHORTEN trial team PII: S1198-743X(21)00491-2 DOI: https://doi.org/10.1016/j.cmi.2021.09.001 Reference: CMI 2678 To appear in: Clinical Microbiology and Infection Received Date: 11 July 2021 Revised Date: 31 August 2021 Accepted Date: 1 September 2021 Please cite this article as: Molina J, Montero-Mateos E, Praena-Segovia J, León-Jiménez E, Natera C, López-Cortés LE, Valiente L, Rosso-Fernández CM, Herrero M, Aller-García AI, Cano Á, Gutiérrez- Gutiérrez B, Márquez-Gómez I, Álvarez-Marín R, Infante C, Roca C, Valiente-Méndez A, Pachón J, Reguera JM, Corzo-Delgado JE, Torre-Cisneros J, Rodríguez-Baño J, Cisneros JM, on behalf of the SHORTEN trial team, Seven versus 14-days course of antibiotics for the treatment of bloodstream infections by Enterobacterales. A randomized, controlled trial, Clinical Microbiology and Infection, https:// doi.org/10.1016/j.cmi.2021.09.001. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.  2021 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved. ! e!" " eO" ! eT" " ! kb" ! k!" " ! kO" ! kT" " kU" ! ke" " ! kk" ! kf" " fc" ! fd" " fk" Includes: derivation of the urinary or biliary tract, drainage of empyema or other deep-seated abscesses, removal of a vascular catheter, etc. Definition of outcome measures: Outcome measures were monitored in all trial visits. The assessment of all outcome measures was performed at the end of follow-up. Death: The patient is deceased by any cause during the follow-up. Clinical cure: disappearance of symptoms and signs of infections, including fever and focal symptoms. A patient will be considered apyretic when he/she reaches a temperature equal to or lower than 37ºC in a sustained manner in the following days. Microbiological cure: negative control blood cultures. Relapse of the bacteremia: new isolation in blood cultures of the same microorganism responsible for the initial episode of bacteremia, in a patient in whom previous negative blood cultures had already been documented. Relapse of fever: fever of new onset of any cause (known or unknown), in a patient who had already remained apyretic as defined in the clinical cure definition. Superinfection: documented infection during the follow-up, produced by a microorganism other than the bacterium responsible for the initial episode of bacteremia (including Clostridiodes difficile). ! ff" " Supplementary file 2. Main antibiotic classes prescribed. (a) Initial empirical treatment prescribed before receiving microbiological results. Antibiotic treatment 7-day group 14-day group Amoxicillin-clavulanate 24 30 Cephalosporins 46 42 Fluorquinolones 11 17 Piperacillin-tazobactam 12 17 Carbapenems 13 11 Other 9 16 No empirical treatment 1 2 Combination therapy as empirical treatment 13 15 (b) Initial targeted treatment prescribed after receiving microbiological results*. Antibiotic treatment 7-day group 14-day group Penicillins 7 8 Amoxicillin-clavulanate 12 16 Cephalosporins 47 62 Fluorquinolones 23 18 Piperacillin-tazobactam 11 13 Carbapenems 12 11 Other 5 5 Combination therapy as targeted treatment 2 7 ! dcc" Supplementary file 3. Observed characteristics between participants with complete and incomplete data Experimental Control Analyzed (110) Missing (9) Analyzed (122) Missing (7) Sex female 55 (50) 3 (33) 57 (47) 2 (29) Age (median, IQR) 65 (53-76) 70 (56-81) 68 (53-77) 66 (62-72) Inpatient care 83 (76) 8 (89) 84 (69) 6 (86) Charlson index ≥ 3 50 (46) 4 (44.4) 53 (43) 3 (43) Comorbidities Diabetes 42 (38) 3 (33) 35 (29) 3 (43) Chronic kidney disease 16 (15) 2 (22) 30 (25) 2 (29) Haemodialysis 4 (4) 0 8 (7) 0 Colagenopathies 6 (5) 0 4 (3) 0 Hepatopathy 9 (8) 1 (11) 13 (11) 0 Malignancies 29 (26) 3 (33) 28 (23) 4 (57) Dementia 3 (3) 0 5 (4) 0 Solid organ transplantation 5 (5) 0 6 (5) 0 Mechanisms of resistance ESBL 15 (14) 1 (11) 12 (10) 0 AmpC 3 (3) 1 (11) 7 (6) 2 (29) BSI accquisition Community 46 (42) 3 (33) 52 (43) 2 (29) Healthcare-related 30 (27) 3 (33) 29 (24) 1 (14) Hospital 34 (31) 2 (22) 41 (34) 4 (57) Source of BSI Urinary 66 (60) 4 (44) 62 (51) 4 (57) Intraabdominal 15 (14) 1 (11) 17 (14) 1 (14) Vascular 14 (13) 0 16 (13) 0 Respiratory 2 (2) 1 (11) 12 (10) 0 Unknown 8 (7) 2 (22) 9 (7) 2 (29) Other 5 (5) 0 6 (5) 0 Source requiring drainage 29 (26) 1 (11) 25 (20) 1 (14) Inadequate empirical treatment 26 (24) 2 (22) 22 (18) 3 (43) Presentation sepsis/septic shock 15 (14) 1 (11) 17 (14) 0 Other relevant risk factors Immunosuppressant drugs 16 (15) 1 (11) 14 (11) 0 Previous ICU stay (30 days) 13 (12) 0 8 (7) 0 Previous surgery (30 days) 13 (12) 0 9 (7) 1 (14) Permanent indwelling urinary catheter 13 (12) 2 (22) 13 (11) 2 (29) Previous urinary obstruction 7 (6) 0 14 (11) 0 Previous biliary obstruction 6 (5) 2 (22) 7 (6) 1 (14) ! dcd" " Suplementary file 4. Observed characteristic of participants excluded from the per protocol analysis. Experimental (n=17) Control (n=14) Sex female 4 (23.5%) 4 (28.6%) Age (median, IQR) 55 (47-62) 67 (53-76) Patient care -Outpatient 0 2 -Inpatient 14 9 Charlson index ≥ 3 10 (58.8%) 5 (35.7%) Comorbidities -Diabetes 5 (29.4%) 3 (21.3%) -Chronic kidney disease 5 (29.4%) 5 (35.7%) -Malignancies 10 (58.8%) 2 (14.3%) -Solid organ transplantation 2 (11.8%) 0 Microorganism non-Enterobacterales 3 (17.6%) 1 (7.1%) Mechanisms of resistance (ESBL or AmpC) 5 (29.4%) 1 (7.1%) BSI acquisition (community) 4 (23.5%) 4 (28.5%) Source of BSI -Urinary 5 (29.4%) 5 (35.7%) -Intraabdominal 4 2 Inadequate empirical treatment 2 3 Presentation sepsis/septic shock 4 (23.5%) 0 Other relevant risk factors Immunosuppressant drugs 5 (29.4%) 3 (21.3%) -Previous ICU stay (30 days) 4 (23.5%) 1 (7.1%) -Previous surgery (30 days) 4 (23.5%) 2 (14.3%) -Permanent indwelling urinary catheter 4 (23.5%) 2 (14.3%) -Previous biliary obstruction 2 (11.8%) 0 Outcomes -Days of treatment 19 (9-20) (n=11/17) 20 (15-27) (n=11/14) -Absence of clinical cure 6/13 (46.2%) 5/13 (38.5%) -Deaths 0/17 2/14 (14.3%) ! dcb" Supplemetary file 5. Number of patients meeting criteria for treatment interruption on day +7 (experimental group) and day +14 (control group). Intention to treat cohort. Experimental (n=119) Control (n=129) Interruption criteria is met 92 (77.3%) 103 (79.8%) Interruption criteria is NOT met 15 (12.6%) 10 (7.8%) -Persistent symptoms 13 (10,9%) 9 (7%) -Other infection 2 (1.7%) 1 (0.8%) Not assessed* 12 (10.1%) 16 (12.4%) *Death before assessment, not assessed after exclusion or lost to follow-up. Per protocol cohort. Experimental (n=93) Control (n=108) Interruption criteria is met 84 (90.3%) 102 (94.4%) Interruption criteria is NOT met 9 (9.7%) 3 (2.8%) -Persistent symptoms 7 (7.5%) 2 (1.9%) -Other infection 2 (2.2%) 1 (0.9%) Not assessed* 0 3 (2.8%) *Death before assessment. ! dc!" " ! ! Supplementary file 6. Causes for relapsing fever. Intention to treat cohort. Experimental (n=119) Control (n=129) No relapse of fever* 89 (80.9%) 96 (80.7%) Relapse of fever* 21 (19.1%) 23 (19.3%) - Worsening of the infection motivating patient inclusion 7 (6.4%) 8 (6.7%) - Other infection 11 (10%) 13 (10.9%) - Non-infectous fever 3 (2.7%) 2 (1.7%) Unknown 9 10 *Percentages are calculated out of the total number of patients assessed Per protocol cohort. Experimental (n=93) Control (n=106) No relapse of fever 76 (81.7%) 87 (82.1%) Relapse of fever 17 (18.3%) 19 (17.9%) - Worsening of the infection motivating patient inclusion 6 (6.5%) 5 (4.7%) - Other infection 8 (8.6%) 12 (11.3%) - Non-infectous fever 3 (3.2%) 2 (1.9%) Unknown 0 0 ! dcO" Supplementary file 7. Observed adverse event (per 1,000 person-days). Experimental Control Difference Adverse events 23.6 19.5 3.7 (-2.7 to 10.4) Severe adverse events 5.3 6.8 -1.5 (-5.0 to 2.1) Drug-related adverse reaction* 2.6 2.7 -0.1 (-2.5 to 2.6) System Organ Class Common Terminology Criteria for Adverse Events (v 4.0) Blood and lymphatic 0,9 0,2 0.7 (-0.6 to 2.4) Cardiac disorders 0,3 1,1 -0.8 (-2.4 to 0.7) Gastrointestinal disroders 2,9 2,9 0 (-2.5 to 2.7) General disorders and administration site conditions 1,8 1,8 -0.1 (-2.1 to 2.2) Hepatobiliary disorders 0,3 0,2 0.1 (-1.0 to 1.4) Infections and infestations 7,3 6,1 1.2 (-2.4 to 5.2) Injury, poisoning and procedural complications 0,3 0,5 -0.2 (-1.4 to 1.2) Investigations 1,8 1,1 0.6 (-1.2 to 2.8) Metabolism and nutrition disorders 0,9 0,0 0.9 (-0.2 to 2.6) Musculoskeletal and conective tissue disorders 0,9 0,0 0.9 (-0.2 to 2.6) Neoplasms benign, malignant and unspecified 0,3 0,5 -0.2 (-1.4 to 1.2) Nervous system disorders 1,2 0,7 0.5 (-1.0 to 2.4) Psychiatric disorders 0,0 0,5 -0.5 (-1.7 to 0.7) Renal and urinary disorders 1,5 0,9 0.6 (-1.1 to 2.6) Respiratory, thoracic and mediastinal disorders 1,2 1,1 0.1 (-1.6 to 2.0) Skin and subcutaneous tissue 0,6 0,9 -0.3 (-1.8 to 1.3) Vascular disorders 1,2 0,9 0.3 (-1.3 to 2.2) *Adverse reactions with a definite, probable, or possible relationship with the study drug were considered for the analysis. All safety analyses were performed in the intention to treat cohort. ! dcT" " Supplementary file 8. Desirability of Outcome Ranking and Response Adjusted for Duration of Antibiotic Risk, detailed by patient. Arm Overall clinical response Days of antibiotic use No. of Control Participants With a Lower DOOR Experimental 1 6 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 ! dcU" Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 7 108 Experimental 1 8 108 Experimental 1 8 108 Experimental 1 8 108 Experimental 1 8 108 Experimental 1 8 108 Experimental 1 9 108 Experimental 1 9 108 Experimental 1 9 108 Experimental 1 9 108 Experimental 1 9 108 Experimental 1 9 108 Experimental 1 10 108 Experimental 1 10 108 Experimental 1 11 107.5 Experimental 1 12 107 Experimental 1 13 106 Experimental 1 14 75.5 Experimental 1 14 75.5 Experimental 1 17 37 Experimental 1 23 35 Experimental 2 7 31 Experimental 2 7 31 Experimental 2 14 30.5 Experimental 2 15 29 Experimental 2 20 27.5 Experimental 2 21 27 Experimental 2 21 27 Experimental 2 22 27 Experimental 2 22 27 Experimental 2 39 25 Experimental 3 7 25 Experimental 3 7 25 Experimental 3 7 25 Experimental 3 7 25 Experimental 3 9 25 Experimental 3 12 25 ! dce" " Experimental 3 13 25 Experimental 3 18 19 Experimental 3 18 19 Experimental 3 18 19 Experimental 3 20 17.5 Experimental 3 20 17.5 Experimental 4 17 7.5 Experimental 5 7 4 Control 1 11 Sum=7800 Control 1 13 Control 1 13 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 Control 1 14 ! ddO" DZfe6Tp" Rv"(" dc6dph; Z.'."()8/-$-$" 0&"$&)$-:-/-0(06" $&" ,&(/-2@" *)" ()8/-$-$" aEECiCFaFC" 8/%'!3/, "6"7*&"'.$%,@"+@'."/.$"5(+-&)%&$"($-9)(0.$"(/":,(2." 0&" %,(%('-&)%." +.,%." %*3-&,.)" *)(" 5,.:(:-/-0(0" 0&/" ee6ep" 0&" +.)$&9*-," '&L.,&$",&$*/%(0.$"7*&"/.$"5(+-&)%&$"7*&",&+-:-&,.)"%,(%('-&)%.$"0&"dO"0H($6" +.)$-0&,()0."&)"+.)L*)%."/("+*,(+-@)"+/H)-+(6"&/",-&$9."0&"&3&)%.$"(03&,$.$" 9,(3&$"="/("&`5.$-+-@)"("()%-:-@%-+.$;" " " ! ddT" " Discusión general ! ddU" " " " " " 6.DISCUSIÓN GENERAL. 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