RESEARCH ARTICLE Critically ill patients with community-onset intraabdominal infections: Influence of healthcare exposure on resistance rates and mortality Emilio Maseda ID1,2*, Sofı́a Ramı́rez1,2, Pedro Picatto3, Eva Peláez-Peláez4, Carlos Garcı́a- Bernedo5, Nazario Ojeda-Betancur6, Gerardo Aguilar7, Beatriz Forés8, Jorge Solera- Marı́n9, Marı́a Aliaño-Piña10, Eduardo Tamayo11, Fernando Ramasco12, Raquel Garcı́a- a1111111111 Álvarez13, Ada González-Lisorge14, Marı́a-José Giménez15,16, Alejandro Suárez-de-la- a1111111111 Rica1,2, for the HELP Investigators and the Perioperative Infection Research Group¶ a1111111111 a1111111111 1 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario La Paz, Madrid, Spain, 2 Universidad a1111111111 Autónoma de Madrid, Madrid, Spain, 3 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario Central de Asturias, Oviedo, Spain, 4 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario Vall d’Hebron, Barcelona, Spain, 5 Anesthesiology and Surgical Critical Care Dpt., Hospital del Mar, Barcelona, Spain, 6 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario de Gran Canaria Dr. Negrı́n, Las Palmas de Gran Canaria, Spain, 7 Anesthesiology and Surgical Critical Care Dpt., Hospital Clı́nico Universitario, Valencia, Spain, 8 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario OPEN ACCESS Basurto, Bilbao, Spain, 9 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario de Canarias, Santa Cruz de Tenerife, Spain, 10 Anesthesiology and Surgical Critical Care Dpt., Hospital Virgen de la Citation: Maseda E, Ramı́rez S, Picatto P, Peláez- Salud, Toledo, Spain, 11 Anesthesiology and Surgical Critical Care Dpt., Hospital Clı́nico Universitario, Peláez E, Garcı́a-Bernedo C, Ojeda-Betancur N, et Valladolid, Spain, 12 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario de la Princesa, al. (2019) Critically ill patients with community- Madrid, Spain, 13 Anesthesiology and Surgical Critical Care Dpt., Hospital Universitario 12 de Octubre, onset intraabdominal infections: Influence of Madrid, Spain, 14 Anesthesiology and Surgical Critical Care Dpt., Hospital Clı́nico Universitario Virgen de la healthcare exposure on resistance rates and Arrixaca, Murcia, Spain, 15 PRISM-AG, Madrid, Spain, 16 Universidad Europea, Madrid, Spain mortality. PLoS ONE 14(9): e0223092. https://doi. org/10.1371/journal.pone.0223092 ¶ Membership of the HELP study and the Perioperative Infection Research Group is provided in the Acknowledgments. Editor: Shane Patman, University of Notre Dame * emilio.maseda@gmail.com Australia, AUSTRALIA Received: September 19, 2018 Accepted: September 15, 2019 Abstract Published: September 26, 2019 The concept of healthcare-associated infections (as opposed to hospital-acquired infec- Copyright: © 2019 Maseda et al. This is an open tions) in intraabdominal infections (IAIs) is scarcely supported by data in the literature. The access article distributed under the terms of the aim of the present study was to analyse community-onset IAIs (non-postoperative/non-nos- Creative Commons Attribution License, which ocomial) in patients admitted to intensive care units (ICUs), to investigate differences in permits unrestricted use, distribution, and reproduction in any medium, provided the original resistance patterns linked to healthcare exposure and mortality-associated factors. A one- author and source are credited. year prospective observational study (17 Spanish ICUs) was performed distributing cases Data Availability Statement: The Spanish as healthcare-associated infections (HCAI), community-acquired infections (CAI) and legislation specially protects health data. Following immunocompromised patients (ICP). Bacteria producing extended-spectrum β-lactamases clinical practice, data from patients in the study (ESBL) and/or carbapenemase (CPE), high-level aminoglycoside- and/or methicillin- and/or were recorded in their corresponding medical vancomycin- resistance were considered antimicrobial resistant (AMR). Mortality-associ- records at participating hospitals. The anonymous datasets used and/or analyzed during the study are ated factors were identified by regression multivariate analysis. Of 345 patients included available from the corresponding author on (18.8% HCAI, 6.1% ICP, 75.1% CAI), 51.6% presented generalized peritonitis; 32.5% were reasonable request and with permission of the >75 years (55.4% among HCAI). Overall, 11.0% cases presented AMR (7.0% ESBL- and/or corresponding hospital director and the Ethics CPE), being significantly higher in HCAI (35.4%) vs. CAI (5.8%) (p<0.001) vs. ICP (0%) (p = Committee. Requests could be sent to the Ethics Committee of Hospital Universitario La Paz 0.003). Overall 30-day mortality was 14.5%: 23.1% for HCAI and 11.6% for CAI (p = 0.016). PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 1 / 12 Impact of resistance in community-onset severe intraabdominal infections (Madrid, Spain) which was the committee that Mortality (R2 = 0.262, p = 0.021) was positively associated with age >75 years (OR = 6.67, approved the study protocol at the following email 95%CI = 2.56–17.36,p<0.001), Candida isolation (OR = 3.05, 95%CI = 1.18–7.87,p = address: sol.gracia@salud.madrid.org. 0.022), and SAPS II (per-point, OR = 1.08, 95%CI = 1.05–1.11, p<0.001) and negatively Funding: This multicentre study was possible due with biliary infections (OR = 0.06, 95%CI = 0.01–0.48,p = 0.008). In this study, the antimicro- to the generous implication of the personnel in the 17 participating ICUs. The study did not receive bial susceptibility pattern of bacteria isolated from patients with healthcare contact was external funding. One of the authors [MJG] is shifted to resistance, suggesting the need for consideration of the healthcare category (not employee of a commercial company (PRISM-AG) including hospital-acquired infections) for severe IAIs. 30-day mortality was positively which was not funder of the present study. This related with age >75 years, severity and Candida isolation but not with AMR. company only provided support in the form of the salary for this author [MJG], but did not have any role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific role of this author is articulated in the ‘author contributions’ section. Introduction Competing interests: E.M. has served as speaker for Merck, Sharp & Dohme (MSD), Pfizer and Complicated intra-abdominal infections (IAIs) are severe infections requiring early adequate Astellas; and has received educational grants from empirical treatment in addition to control of infectious foci. Approximately 40% of all patients Astellas. F.R. has served as speaker for MSD. G.A. diagnosed with secondary peritonitis need ICU treatment [1], IAIs being the second most has served as speaker for MSD, Astellas, Gilead, common cause of sepsis [2]. Reported mortality rates of severe secondary peritonitis have only and Pfizer and received educational grants from slightly decreased over the last decades, and range from 20% to 60% [1,3], thus remaining as Astellas, Pfizer and MSD. M-JG is employee of an important field for research. The increasingly advanced age of the population (with the PRISM-AG and has received an educational grant from Fundación Micellium para el Desarrollo y associated burden of chronic diseases), and the increased diagnosis in patients with impaired Difusión del Conocimiento Cientı́fico (Valencia, host defences complicate even more outcomes and increase mortality [3,4]. Spain). The remaining authors have disclosed that Since there is general agreement on the prime importance of controlling early source to they do not have any potential conflicts of interest. reduce mortality [4–6], nowadays, the focus is on improving early empirical antimicrobial This does not alter our adherence to PLOS ONE treatments. Inadequate empirical treatments are those providing inadequate coverage of the policies on sharing data and materials. potential microorganisms involved, their resistance traits being of special importance. For complicated IAIs, the traditional binary classification (in-/out-hospital patient) may be not fully resolute for identification of patients at risk for antibiotic-resistant infections since non- hospitalized patients having contact with healthcare settings may be nonetheless at risk. Fur- thermore, resistant isolates are increasingly being isolated from patients without risk factors for healthcare/hospital- acquired infections [4,7,8], this representing a challenge for selecting initial antibiotic treatment. The AGORA initiative [9] and the 2017’s guidelines by The Surgical Infection Society [4] differentiate community-acquired IAIs and healthcare-associated IAIS, with presumed differ- ences in resistance patterns between both categories [9]. But in both documents, hospital- acquired infections are considered as part of healthcare-associated infections [4,9]. In IAIs the concept of healthcare-associated infections as opposed to hospital-acquired infections (unlike what occurs for bacteraemia and pneumonia) is scarcely supported by published data [10] and, traditionally, it is not considered a category different from nosocomial and community- acquired IAIs [11]. However, in contrast to the widely described resistance in pathogens responsible of nosocomial IAIs [12,13], there are few data from healthcare-associated and community-acquired IAIs to help in identifying risks factors for infections by resistant patho- gens [4]. In addition, if the presence of multi-drug resistant bacteria implies higher severity, as it occurs for other pathologies [14], needs also further clarification. We designed the prospective observational multicentre HELP study to describe characteris- tics of IAIs having community-onset (i.e, non-postoperative/non-nosocomial), in patients that due to their severity required ICU management, to investigate possible differences in antibiotic resistance patterns between patients with and without healthcare exposure, and factors associ- ated with mortality. PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 2 / 12 Impact of resistance in community-onset severe intraabdominal infections Material and methods The HELP study (HELP = HEaLthcare-associated intra-abdominal infections study in criti- cally ill Patients) was a prospective, observational, multicentre study conducted in 17 ICUs in Spanish Universitary hospitals. These centres included all consecutive adult patients (�18 yr), admitted in the ICU after surgical treatment for control of the infectious foci, having as diag- nosis non-postoperative/non-nosocomial IAIs. All patients must have an intraoperative microbiological sample (peritoneal fluid) collected for culture. The study included patients entering the ICUs between November 1st 2014 and October 31th 2015. IAIs following surgery (post-operative) or those diagnosed in patients admitted for �48 hours (nosocomial) were excluded. The study protocol was approved by the Ethics Committee of Hospital La Paz, Madrid, Spain. Participants were asked to sign a written consent at entry in the ICU. The study was performed in accordance with the ethical standards laid down in the Declaration of Helsinki (Edinburgh, October 2000). Patients were divided in three groups: patients with healthcare-associated infections (HCAI), patients with community-acquired infections (CAI) and immunocompromised patients (ICP). HCAI was defined as an infection in patients with at least one of the following criteria: i) Hospitalization in an acute care hospital for �48 hours within 90 days prior to the onset of infection, ii) Residence in nursing homes or extended-care facilities, iii) Home infu- sion therapy including antibiotics, iv) Chronic dialysis within 30 days prior to the onset of infection, v) Domiciliary wound care, and/or vi) Family member carrying multidrug-resistant pathogens [15]. ICP were considered patients with immunosuppressive treatment, chemother- apy, corticosteroid therapy for at least 4 weeks before onset of infection, solid organ transplant, and/or HIV-positive patients [15]. IAIs that did not fill exclusion criteria and criteria for HCAI or ICP were considered CAI. Patients presenting criteria for classification as ICP and HCAI were assigned to the HCAI group. Demographic, clinical and microbiological data, empirical antimicrobial treatment, compli- cations, length of stay, and outcome (mortality in the ICU and 30-day mortality) were recorded. Adequacy of source control was evaluated considering criteria previously described [16]. The previous functional status (Barthel index) [17], the Sequential Organ Failure Assess- ment (SOFA) [18] and the Simplified Acute Physiologic Score-II (SAPS II) [19] scores were calculated using clinical data at ICU admission. Blood and intraoperative intra-abdominal fluid samples were collected and immediately sent to the Microbiology laboratory of each cen- tre for processing following standard methods in daily practice. Isolated bacteria presenting extended-spectrum β-lactamases (ESBL) and/or carbapenemase production (for gram-nega- tives) and/or high-level aminoglycoside resistance (HLAR) and/or resistance to vancomycin and/or methicillin resistance (for gram-positives) were considered antimicrobial resistant pathogens (AMR). Differences between groups were assessed by t-test or U-Mann-Whitney non-parametric tests (continuous variables) or by Chi square/Fisher exact tests (discrete variables). For the comparisons between the three groups (HCAI, CAI and ICP), due to the multiple comparisons performed, the Bonferroni correction was applied and the resulting level of significance was rounded down and set at p � 0.01. A stepwise logistic regression multivariate analysis was con- ducted in order to determine variables associated with 30-day mortality. All variables showing differences in the two-group data (survivors/dead) analyse (p <0.05) were included. Interac- tions and linear dependence between independent variables were previously controlled. The significant model (p <0.05) showing the maximum parsimony (the lowest number of variables without significant reduction in the value of the determination coefficient) and the highest R2 was considered. All statistical calculations were computed using SPSS v.14. PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 3 / 12 Impact of resistance in community-onset severe intraabdominal infections Results A total of 360 outpatients with IAIs (non-postoperative/non-nosocomial) were considered in the 17 participating ICUs during the one-year study period. Fifteen were excluded due to miss- ing data, and 345 patients remained as evaluable for the study analysis. Of them, 18.8% (65 out of 345) were HCAI cases, 6.1% (21 out of 345) were ICP cases, and the remaining 75.1% (259 out of 345) were cases of CAI. Up to 51.6% patients presented generalized peritonitis, without difference by groups. Table 1 shows demographic data by type of infection. Source control was considered adequate in 311 (90.1%) cases, without differences by study group. Colon was the most frequent infection site in all groups: up to ~62% cases among ICPs, a percentage higher than for CAI (32.8%) (p = 0.007). Patients with HCAI presented significantly higher mean age (p<0.001) and abscess formation (p = 0.004) while patients with CAI presented higher per- centage of infections involving the appendix compared to HCAI (p<0.001). Table 2 shows comorbidities, severity scores and complications by type of infection. Signifi- cantly higher percentages of patients with congestive heart disease, chronic renal failure, and malignancies were found in the HCAI versus CAI groups; values of SAPS II and SOFA were also higher (p<0.001). Malignancies and liver disease were more frequent among ICP versus CAI cases (p<0.001). Septic shock was the most frequent complication in all groups, being sig- nificantly more frequent in HCAI (>50% cases) than in CAI. Only 10.7% patients presented positive blood culture; among them, the most frequent iso- late was E. coli (3.2%), without differences between groups. Among bacteria isolated from peri- toneal fluid, the percentage of AMR was 11.0%, being 7.0% for ESBL- and/or carbapenemase- producing enterobacteria. Overall, the percentage of AMR was significantly higher in HCAI Table 1. Demographic and clinical data. Variable HCAIa (n = 65) CAIa (n = 259) ICPa (n = 21) p vs. HCAI p vs. HCAI p vs. CAI Age (years; mean ± SD) 72.5 ± 15.2 62.3 ± 17.5 <0.001 61.0 ± 16.2 ns ns Age >75 years [n (%)] 36 (55.4) 72 (27.8) <0.001 4 (19.0) 0.003 ns Males 35 (53.8) 143 (55.2) ns 13 (61.9) ns ns Days in hospital pre-ICU admission (mean ± SD) 2.3 ± 8.4 0.6 ± 0.9 ns 1.0 ± 1.5 ns ns Adequate control of infectious foci 58 (89.2) 236 (91.1) ns 17 (81.0) ns ns Site of infection Stomach 9 (13.8) 47 (18.1) ns 0 (0.0) ns ns Small bowel 13 (20.0) 28 (10.8) ns 2 (9.5) ns ns Biliary tract 18 (27.7) 43 (16.6) ns 3 (14.3) ns ns Appendix 2 (3.1) 56 (21.6) <0.001 3 (14.3) ns ns Colon 23 (35.4) 85 (32.8) ns 13 (61.9) ns 0.007 Type of infection/process Generalized peritonitis 32 (49.2) 131 (50.6) ns 15 (71.4) ns ns Localized peritonitis 15 (23.1) 83 (32.0) ns 3 (14.3) ns ns Abscess 12 (18.5) 18 (6.9) 0.004 0 (0.0) ns ns GIb perforation 6 (9.2) 27 (10.4) ns 3 (14.3) ns ns Negative peritoneal culture 7 (10.5) 48 (18.5) ns 0 (0.0) ns ns Demographic and clinical data by type of peritonitis. Data expressed as n (%) except where indicated a HCAI: Healthcare-associated infection; CAI: Community-associated infection; ICP: Immunocompromised patients b GI: Gastro-intestinal ns: non-significant (p>0.01) https://doi.org/10.1371/journal.pone.0223092.t001 PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 4 / 12 Impact of resistance in community-onset severe intraabdominal infections Table 2. Comorbidities, severity scores and complications. Variable HCAIa (n = 65) CAIa (n = 259) ICPa (n = 21) p vs. HCAI p vs. HCAI p vs. CAI Barthel index (mean ± SD) 71.8 ± 24.9 89.3 ± 13.1 <0.001 85.2 ± 12.2 0.007 ns Comorbidities Congestive heart disease 12 (18.5) 10 (3.9) <0.001 3 (14.3) ns ns Chronic Obstructive Pulmonary Disease 8 (12.3) 31 (12.0) ns 0 (0.0) ns ns Diabetes mellitus 13 (20.0) 42 (16.2) ns 3 (14.3) ns ns Liver disease 3 (4.6) 12 (3.6) ns 6 (28.6) 0.002 <0.001 Chronic renal failure 12 (18.5) 16 (6.2) 0.001 3 (14.3) ns ns Alcoholism 11 (16.9) 26 (10.0) ns 3 (14.3) ns ns Malignancies 17 (26.2) 30 (11.6) 0.003 9 (42.9) ns <0.001 Severity (mean ± SD) SAPS IIb 46.6 ± 14.7 37.0 ± 16.0 <0.001 42.3 ± 17.4 ns ns Sequential Organ Failure Assessment (SOFA) 6.3 ± 3.1 4.2 ± 3.6 <0.001 6.3 ± 2.5 ns ns Lactate (mmol/l) 2.5 ± 2.8 2.4 ± 2.2 ns 2.4 ± 2.2 ns ns Complications Acute respiratory distress syndrome 4 (6.2) 18 (6.9) ns 0 (0.0) ns ns Mechanical ventilation >24h 20 (30.8) 54 (20.8) ns 8 (38.1) ns ns Noninvasive mechanical ventilation>24h 7 (10.8) 29 (11.2) ns 1 (4.8) ns ns Septic shock 33 (50.8) 79 (30.5) 0.002 12 (57.1) ns ns Disseminated intravascular coagulation 4 (6.2) 11 (4.2) ns 0 (0.0) ns ns Acute renal failure 24 (36.9) 70 (27.0) ns 9 (42.9) ns ns Renal replacement therapy 4 (6.2) 19 (7.3) ns 3 (14.3) ns ns Comorbidities, severity scores and complications. Data expressed as n (%) except where indicated a HCAI: Healthcare-associated infection; CAI: Community-associated infection; ICP: Immunocompromised patients b SAPS II: Simplified Acute Physiologic Score-II ns: non-significant (p>0.01) https://doi.org/10.1371/journal.pone.0223092.t002 (23/65; 35.4%) vs. CAI (15/259; 5.8%) (p<0.001) or vs. ICP (0/21; 0%) (p = 0.003), without dif- ferences between CAI and ICP (p = 0.641). Table 3 shows per species percentage of isolation of aerobic/facultative bacteria from perito- neal fluid. Isolation of ESBL-and/or carbapenemase- producing bacteria was significantly more frequent from HCAI than CAI patients (p<0.001), with significant higher percentages of ESBL-producing E. coli (p = 0.030) and Klebsiella spp. (p = 0.001). These type of isolates were not found among enterobacteria isolated from ICP patients. Isolation of enterococci was sig- nificantly more frequent from HCAI than CAI (33.8% vs. 17.8%, p = 0.004), with higher per- centage of isolates showing HLAR [9 out of 22 (40.9%) vs. 3 out of 46 (6.5%) for HCAI vs. CAI isolates]. No differences in total gram-negative anaerobic bacteria isolation were found between groups. ICP patients presented significantly higher rates of Clostridium spp. isolation com- pared with patients with CAI (23.8% vs. 4.7%; p = 0.005). Overall, isolation of Candida spp. occurred in 19.1% (66 out of 345) patients, without differences between groups (23.1% for HCAI, 17.8% for CAI and 23.8% for ICP). Table 4 shows empirical antimicrobial treatment by group. Piperacillin-tazobactam was sig- nificantly more frequent as empirical treatment in CAI than in ICP (p = 0.008), while the use of carbapenems (and among them, meropenem) was significantly more frequent in ICPs vs. HCAI or CAI (p<0.01). Treatment with tigecycline and daptomycin was significantly more PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 5 / 12 Impact of resistance in community-onset severe intraabdominal infections Table 3. Microbiological data. Bacteria HCAIa (n = 65) CAIa (n = 259) ICPa (n = 21) p vs. HCAI p vs. HCAI p vs. CAI Total Enterobacteria 48 (73.8) 169 (65.3) ns 17 (81.0) ns ns E. coli (Total) 31 (47.7) 119 (45.9) ns 13 (61.9) ns ns b E. coli (ESBL ) 5 (7.7) 5 (1.9) ns 0 (0.0) 0.009 ns E. coli (CPEc) 2 (3.1) 2 (0.8) ns 0 (0.0) ns ns Klebsiella spp (Total) 11 (16.9) 33 (12.7) ns 3 (14.3) ns ns Klebsiella spp (ESBLb) 4 (6.2) 0 (0.0) 0.001 0 (0.0) ns ns c Klebsiella spp (CPE ) 1 (1.5) 0 (0.0) ns 0 (0.0) ns ns Enterobacter spp (Total) 3 (4.6) 11 (4.2) ns 1 (4.8) ns ns Enterobacter spp (ESBLb) 1 (1.5) 4 (1.5) ns 0 (0.0) ns ns Total ESBLb enterobacteria 10 (15.4) 9 (3.5) 0.001 0 (0.0) ns ns Total CPEc 3 (4.6) 2 (0.8) ns 0 (0.0) ns ns Total ESBLb and/or CPEc 13 (20.0) 11 (4.2) <0.001 0 (0.0) ns ns Pseudomonas spp. 1 (1.5) 16 (6.2) ns 3 (14.3) ns ns Total gram-positive bacteria 39 (60.0) 112 (43.2) ns 7 (33.3) ns ns Total Enterococcus 22 (33.8) 46 (17.8) 0.004 2 (9.5) ns ns E. faecalis 5 (7.7) 17 (6.6) ns 1 (4.8) ns ns E. faecium (Total) 11 (16.9) 16 (6.2) 0.005 1 (4.8) ns ns E. faecium (HLARd) 6 (9.2) 1 (0.4) <0.001 0 (0.0) ns ns Enterococcus spp. (Total) 6 (9.2) 13 (5.0) ns 0 (0.0) ns ns Enterococcus spp. (HLARd) 3 (4.6) 2 (0.8) ns 0 (0.0) ns ns Enterococcus spp. (vancomycin-resistant) 1 (1.5) 1 (0.4) ns 0 (0.0) ns ns Total HLARd bacteria 9 (13.8) 3 (1.2) <0.001 0 (0.0) ns ns Per species, percentage of isolation of aerobe/facultative bacteria from peritoneal fluid. Data are expressed as n (%). a HCAI: Healthcare-associated infection; CAI: Community-associated infection; ICP: Immunocompromised patients b ESBL: extended spectrum β-lactamase-producing c CPE: carbapenemase-producing d HLAR: High-level aminoglycoside resistance ns: non-significant ns: non-significant (p>0.01) https://doi.org/10.1371/journal.pone.0223092.t003 frequent in HCAI and ICP than in CAI patients. Antifungals were used in a total of 13% patients, without differences between groups. Table 5 shows length of stay and outcome by type of infection. No differences in the vari- ables analysed were found between groups. In the subgroup of patients >75 years (n = 112), no significant differences (p = 0.452) in 30-day mortality were found between groups: 12/36 (33.3%) for HCAI; 19/72 (26.4%) for CAI and 0/4 for ICP. The ICP group was excluded from the multivariate analysis due to its low number of patients, remaining 324 patients (279 surviving and 45 dead patients). Variables showing dif- ferences in the two-group data analysis (those included in the multivariate analysis) are shown in Table 6. Different models were performed. The Hosmer-Lemeshow test and the perfor- mance of the models were evaluated, being always <0.01. The significant (p<0.05) model showing the maximum parsimony and the highest R2 (R2 = 0.262, p = 0.021) indicated age >75 years (OR = 6.67, 95%CI = 2.56–17.36, p<0.001), Candida isolation from peritoneal fluid (OR = 3.05, 95%CI = 1.18–7.87, p = 0.022), and SAPS II (per point, OR = 1.08, 95%CI = 1.05– 1.11, p<0.001) as variables positively associated with mortality, and biliary tract as site of PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 6 / 12 Impact of resistance in community-onset severe intraabdominal infections Table 4. Antimicrobial treatment. Antimicrobials HCAIa (n = 65) CAIa (n = 259) ICPa (n = 21) p vs. HCAI p vs. HCAI p vs. CAI Total β-lactams 62 (0.95) 266 (1.03) ns 22 (1.05) ns ns Penicillins (Total) 33 (0.51) 165 (0.64) ns 6 (0.29) ns 0.001 Amoxicillin/clavulanic acid 5 (0.08) 56 (0.22) ns 0 (0.00) ns ns Piperacillin/tazobactam 28 (0.43) 109 (0.42) ns 6 (0.29) ns 0.008 Cephalosporins (Total) 4 (0.06) 21 (0.08) ns 2 (0.10) ns ns Cefotaxime 3 (0.05) 18 (0.07) ns 1 (0.05) ns ns Ceftriaxone 1 (0.02) 2 (0.01) ns 1 (0.05) ns ns Ceftazidime 0 (0.00) 1 (0.00) ns 0 (0.00) - ns Carbapenems (Total) 23 (0.35) 79 (0.31) ns 14 (0.67) ns 0.001 Imipenem 1 (0.02) 15 (0.06) ns 1 (0.05) ns ns Meropenem 17 (0.26) 35 (0.14) ns 12 (0.57) 0.009 <0.001 Ertapenem 5 (0.08) 29 (0.11) ns 1 (0.05) ns ns Monobactams (Aztreonam) 2 (0.03) 1 (0.00) ns 0 (0.00) ns ns Total aminoglycosides 4 (0.06) 15 (0.06) ns 2 (0.10) ns ns Total quinolones 2 (0.03) 5 (0.02) ns 1 (0.05) ns ns Glycylcyclines (Tigecycline) 9 (0.14) 7 (0.03) <0.001 3 (0.14) ns 0.006 Daptomycin 4 (0.06) 2 (0.01) 0.004 2 (0.10) ns 0.001 Linezolid 4 (0.06) 16 (0.06) ns 4 (0.19) ns ns Metronidazole 7 (0.11) 27 (0.10) ns 3 (0.14) ns ns Total antifungals 10 (0.15) 29 (0.11) ns 6 (0.29) ns ns Antimicrobials used as empirical treatment. Data are expressed as n (ratio of per-patient antimicrobial use). a HCAI: Healthcare-associated infection; CAI: Community-associated infection; ICP: Immunocompromised patients ns: non-significant (p>0.01) https://doi.org/10.1371/journal.pone.0223092.t004 infection (OR = 0.06, 95%CI = 0.01–0.48, p = 0.008) as variable negatively associated with mortality. Discussion Up to 17 Spanish UCIs participated in this observational study analysing severe IAIs having community-onset. Our results confirm for this entity the difference of resistance patterns in community patients with and without healthcare exposure, since isolation of AMR from Table 5. Length of stay and outcome in the ICU. Variable HCAIa (n = 65) CAIa (n = 259) ICPa (n = 21) p vs. HCAI p vs. HCAI p vs. CAI Length of stay in the ICU [days; median (IQR)] 4.0 (1.0–7.0) 2.0 (1.0–6.0) ns 5.0 (1.0–8.5) ns ns Length of hospital stay [days; median (IQR)] 17.0 (10.5–27.0) 12.0 (8.0–24.0) ns 19.0 (13.0–46.5) ns ns Mortality in the ICU [n (%)] 3 (4.6) 21 (8.1) ns 4 (19.0) ns ns Mortality within 30 days of infection onset [n (%)] 15 (23.1) 30 (11.6) ns 5 (23.8) ns ns Length of stay and outcome by type of peritonitis a HCAI: Healthcare-associated infection; CAI: Community-associated infection; ICP: Immunocompromised patients IQR: Interquartile range ns: non-significant (p>0.01) https://doi.org/10.1371/journal.pone.0223092.t005 PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 7 / 12 Impact of resistance in community-onset severe intraabdominal infections peritoneal fluid was significantly more frequent from HCAI versus CAI. However, in the mul- tivariate analysis no association between AMR and 30-day mortality was found. On the con- trary, our 30-day mortality was positively associated with age >75 years, Candida isolation from peritoneal fluid, and values of SAPS II, and negatively associated with biliary tract as site of infection. Therapeutic recommendations are based, among others, on the severity of the infection, age, patient’s status captured by scoring systems [4,20], and the possibility of multidrug resis- tant bacteria in relation to the origin of the infection [4,21]. In the present study, the different characteristics of patients in the study groups were in line with all these criteria: patients with healthcare exposure were significantly older, presented higher severity at admission, and pre- sented more frequently AMR than CAI cases. Therefore, from the microbiological perspective (AMR), our results validate the category of healthcare-associated IAIs as opposed to commu- nity infections. This constitutes the main difference with other studies investigating risk factors for IAIs by multidrug resistant pathogens which considered hospital-acquired infections among healthcare-associated infections [22,23]. The profile of pathogens isolated from peritoneal samples was in accordance with previous studies, with similar percentages of enzymatic resistance in enterobacteria (20% for HCAI and 4.2% for CAI) [24,25], and isolation rates of enterococci significantly higher in HCAI than CAI, as in a previous study on community-onset healthcare-associated IAIs [26]. An interest- ing finding was the low rate of non-fermenters found, probably in relation to the community- onset of infections, since additional pathogenic bacteria as P. aeruginosa and yeasts must be considered in hospital-associated complicated IAIs and in immunocompromised hosts [27]. The reduced number of ICP patients limited its analysis, not allowing for drawing conclusions. Candida spp. was the third most frequent microorganism isolated after E. coli and enterococci, without differences in isolation rates between HCAI and CAI. The overall percentage of Can- dida isolation in our study was high, and similar to the percentage found in critically ill patients with secondary and tertiary abdominal sepsis [28]. Nevertheless, postoperative perito- nitis has different microbiological features than non-postoperative nosocomial IAIs and CAIs, where the similar frequency of yeast isolation has been reported [29]. Surprisingly, AMR (as defined in the present study) were not isolated from ICP patients, possibly due to the reduced number of ICP cases included. But, on the contrary, AMR were found in 5.8% of the patients not having contact with healthcare, thus, theoretically, not pre- senting risk factors for harbouring resistant bacteria. In this sense, the lack of difference in iso- lation of ESBL-producing E. coli between HCAI and CAI illustrates the extension of the risk for resistance beyond the healthcare settings to the community. The presence of resistant E. coli isolates in the community is increasing over time, as confirmed in the SMART Program, where the rate of multidrug-resistant E. coli was more than double from 2009 to 2013 among community-associated IAIs [30]. In the present study, overall mortality was similar to the one described in other studies on non-post-operative intraabdominal infections [31,32]. The multivariate analysis did not iden- tify AMR as variable associated with 30-day mortality. A previous study in ICU-acquired bloodstream infections showed similar results, the pathogen resistance pattern not impacting attributable mortality [33]. In our study, the 30-day mortality relied on other classical parame- ters as advanced age and severity, and microbiological parameters as isolation of Candida spp. Nevertheless, despite its statistical significance, interpretations of these results need caution since for age a substantial OR value was accompanied by a large confidence interval, and for SAPS II the magnitude of effect was an OR = 1.08 per point increased in the score. However, our results are well supported by the literature. In a previous study on acute secondary perito- nitis, age older than 80 years showed to be an independent risk factor of mortality regardless PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 8 / 12 Impact of resistance in community-onset severe intraabdominal infections Table 6. Significant data in two-group data analysis. Variable Survivors Dead p (n = 279) (n = 45) Age >75 years 77 (27.6) 31 (68.9) <0.001 HCAIa 50 (17.9) 15 (33.3) 0.017 Small bowel as site of infection 29 (10.4) 12 (26.7) 0.002 Biliary tract as site of infection 60 (21.5) 1 (2.2) 0.002 Appendix as site of infection 55 (19.7) 3 (6.7) 0.034 Generalized peritonitis 132 (47.3) 31 (68.9) 0.007 Localized peritonitis 93 (33.3) 5 (11.1) 0.003 Congestive heart disease 14 (5.0) 8 (17.8) 0.005 Chronic renal failure 18 (6.5) 10 (22.2) 0.002 Lactate �3 mmol/l 59 (21.1) 20 (44.4) 0.001 SAPS IIb >46 points 63 (22.6) 32 (71.1) <0.001 Isolation of CPEc from peritoneal fluid 2 (0.7) 3 (6.7) 0.021 Isolation of Enterobacter spp. from peritoneal fluid 5 (1.8) 4 (8.9) 0.024 Isolation of Candida spp. from peritoneal fluid 40 (14.3) 13 (28.9) 0.027 Variables (values at admission) introduced in the multivariate model for the HCAIa + CAIa population based on the significant (p<0.05) differences between survivors and dead patients. Data expressed as n (%). a HCAI: Healthcare-associated infection; CAI: Community-associated infection b SAPS II: Simplified Acute Physiologic Score-II c CPE: carbapenemase-producing Enterobacteria https://doi.org/10.1371/journal.pone.0223092.t006 the Mannheim Peritonitis Index score [34]. Similarly, several studies have concluded the increased mortality associated with isolation of Candida [35,36], also in patients with compli- cated non-postoperative IAIs [32]. The strength of the present prospective descriptive study was the inclusion of all patients with community-onset severe IAIs admitted in a large number of ICUs in Spain over one year. Time of source control was not available in our study, this representing a study limitation. Other inherent limitations of descriptive studies (absence of sample size calculation, variability in routine laboratory procedures, lack of standardized criteria for hospital discharge. . .) weak- ness conclusions, although, on the other hand, discloses actual bacterial isolation and thera- peutic management of this entity in clinical practice. Importantly, the analysis of the empirical treatments selected by treating physicians suggests an influence of the awareness of possible resistance in certain patients, since there was a more frequent utilization of broad-spectrum antibiotics in the HCAI and ICP groups. This could have negatively influenced the multivari- ate analysis for AMR and 30-day mortality. In this context, the lack of assessment of the ade- quacy of empirical antimicrobial treatments represents a study limitation, although without influence on epidemiological AMR results. Conclusion Despite AMR (as defined in the present study) were not isolated from ICP patients (possibly due to the reduced number of ICP cases included), the results of this study showed that the antimicrobial susceptibility pattern of bacteria isolated from patients with healthcare contact was shifted to resistance, suggesting the need for consideration of the healthcare category (not including hospital-acquired infections) for severe IAIs. According to our results, treating phy- sicians facing the management of severe IAIs should consider not only the patient’s age and PLOS ONE | https://doi.org/10.1371/journal.pone.0223092 September 26, 2019 9 / 12 Impact of resistance in community-onset severe intraabdominal infections severity at admission (risk factors for mortality) but also healthcare exposure as risk factor for multidrug resistance even in IAIs having community-onset. Acknowledgments Investigators of the HELP study and the Perioperative Infection Research Group: González-Lisorge A., Garcı́a-Palenciano C., Ercole G.A. (H. Clı́nico Universitario Virgen de la Arrixaca, Murcia, Spain), Aguilar G., Carrizo J., Serralta F., Martı́nez-Castro S., Gracia E. (H. Clı́nico Universitario, Valencia, Spain), Ojeda-Betancur N., Ramos-Álamo A., Gómez-Mar- rero J., Cabrera-Ramı́rez L. (H. Universitario de Gran Canaria Dr. Negrı́n, Las Palmas de Gran Canaria, Spain), del Castillo Blanco A., Dı́az-Antolı́n M.P. (H. Son LLátzer, Palma de Mallorca, Spain), Moreno I. (H. Universitario y Politécnico de La Fe, Valencia, Spain), Ledesma B. (H. Universitario Prı́ncipe de Asturias, Alcalá de Henares, Spain), Nuñez M. (H. Álvaro Cun- queiro, Vigo, Spain), Garcı́a-Bernedo C., Benı́tez-Cano A., Carazo-Cordobés J., Castelltort Mascó L. (H. del Mar, Barcelona, Spain), Maseda E., Ramı́rez S., Suárez-de-la-Rica A., Mon- tero-Feijoo A., Salgado P., Gilsanz F. (H. Universitario La Paz, Madrid, Spain), Tamayo E., de Vargas Martı́nez O., Flores-Crespo M. (H. Clı́nico Universitario, Valladolid, Spain), Picatto P., Castañón-Alonso E., Álvarez-Fernández R.A. (H. Universitario Central de Asturias, Oviedo, Spain), Forés B., Bengoetxea-Uriarte U.X., Freijo-Guerreo J.J., González-Garcı́a J. (H. Univer- sitario Basurto, Bilbao, Spain), Granizo J.J. (H. Universitario Infanta Cristina, Parla, Spain), Peláez-Peláez E (H. Universitario Vall d’Hebron, Barcelona, Spain), Solera-Marı́n J. (H. Uni- versitario de Canarias, Santa Cruz de Tenerife, Spain), Aliaño-Piña M. (H. Virgen de la Salud, Toledo, Spain), Ramasco F. (H. Universitario de la Princesa, Madrid, Spain), Garcı́a-Álvarez R (H. Universitario 12 de Octubre, Madrid, Spain), Giménez MJ (PRISM-AG, Madrid, Spain). Lead author for this group: Emilio Maseda, MD PhD; email: emilio.maseda@gmail.com Author Contributions Conceptualization: Emilio Maseda, Alejandro Suárez-de-la-Rica. Formal analysis: Emilio Maseda, Marı́a-José Giménez, Alejandro Suárez-de-la-Rica. Funding acquisition: Emilio Maseda. Investigation: Emilio Maseda, Sofı́a Ramı́rez, Pedro Picatto, Eva Peláez-Peláez, Carlos Garcı́a- Bernedo, Nazario Ojeda-Betancur, Gerardo Aguilar, Beatriz Forés, Jorge Solera-Marı́n, Marı́a Aliaño-Piña, Eduardo Tamayo, Fernando Ramasco, Raquel Garcı́a-Álvarez, Ada González-Lisorge, Alejandro Suárez-de-la-Rica. Project administration: Emilio Maseda. Supervision: Emilio Maseda. Writing – original draft: Emilio Maseda, Marı́a-José Giménez, Alejandro Suárez-de-la-Rica. Writing – review & editing: Emilio Maseda, Sofı́a Ramı́rez, Pedro Picatto, Eva Peláez-Peláez, Carlos Garcı́a-Bernedo, Nazario Ojeda-Betancur, Gerardo Aguilar, Beatriz Forés, Jorge Solera-Marı́n, Marı́a Aliaño-Piña, Eduardo Tamayo, Fernando Ramasco, Raquel Garcı́a- Álvarez, Ada González-Lisorge, Marı́a-José Giménez, Alejandro Suárez-de-la-Rica. 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