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. Author manuscript; available in PMC: 2023 Mar 15.
Published in final edited form as: Lancet Microbe. 2023 Feb 9;4(3):e159–e170. doi: 10.1016/S2666-5247(22)00329-9

Global epidemiology and clinical outcomes of carbapenem-resistant Pseudomonas aeruginosa and associated carbapenemases (POP): a prospective cohort study

Jinnethe Reyes 1, Lauren Komarow 1, Liang Chen 1, Lizhao Ge 1, Blake M Hanson 1, Eric Cober 1, Erica Herc 1, Thamer Alenazi 1, Keith S Kaye 1, Julia Garcia-Diaz 1, Lanjuan Li 1, Souha S Kanj 1, Zhengyin Liu 1, Jose M Oñate 1, Robert A Salata 1, Kalisvar Marimuthu 1, Hainv Gao 1, Zhiyong Zong 1, Sandra L Valderrama-Beltrán 1, Yunsong Yu 1, Paul Tambyah 1, Gregory Weston 1, Soraya Salcedo 1, Lillian M Abbo 1, Qing Xie 1, Karen Ordoñez 1, Minggui Wang 1, Martin E Stryjewski 1, Jose M Munita 1, David L Paterson 1, Scott Evans 1, Carol Hill 1, Keri Baum 1, Robert A Bonomo 1, Barry N Kreiswirth 1, Maria Virginia Villegas 1, Robin Patel 1, Cesar A Arias 1, Henry F Chambers 1, Vance G Fowler Jr 1, Yohei Doi 1, David van Duin 1, Michael J Satlin 1, on behalf of the Antibacterial Resistance Leadership Group and Multi-Drug Resistant Organism Network Investigators
PMCID: PMC10016089  NIHMSID: NIHMS1878924  PMID: 36774938

Summary

Background

Carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global threat, but the distribution and clinical significance of carbapenemases are unclear. The aim of this study was to define characteristics and outcomes of CRPA infections and the global frequency and clinical impact of carbapenemases harboured by CRPA.

Methods

We conducted an observational, prospective cohort study of CRPA isolated from bloodstream, respiratory, urine, or wound cultures of patients at 44 hospitals (10 countries) between Dec 1, 2018, and Nov 30, 2019. Clinical data were abstracted from health records and CRPA isolates were whole-genome sequenced. The primary outcome was 30-day mortality from the day the index culture was collected. We compared outcomes of patients with CRPA infections by infection type and across geographic regions and performed an inverse probability weighted analysis to assess the association between carbapenemase production and 30-day mortality.

Findings

We enrolled 972 patients (USA n=527, China n=171, south and central America n=127, Middle East n=91, Australia and Singapore n=56), of whom 581 (60%) had CRPA infections. 30-day mortality differed by infection type (bloodstream 21 [30%] of 69, respiratory 69 [19%] of 358, wound nine [14%] of 66, urine six [7%] of 88; p=0·0012) and geographical region (Middle East 15 [29%] of 52, south and central America 20 [27%] of 73, USA 60 [19%] of 308, Australia and Singapore three [11%] of 28, China seven [6%] of 120; p=0·0002). Prevalence of carbapenemase genes among CRPA isolates also varied by region (south and central America 88 [69%] of 127, Australia and Singapore 32 [57%] of 56, China 54 [32%] of 171, Middle East 27 [30%] of 91, USA ten [2%] of 527; p<0·0001). KPC-2 (n=103 [49%]) and VIM-2 (n=75 [36%]) were the most common carbapenemases in 211 carbapenemase-producing isolates. After excluding USA patients, because few US isolates had carbapenemases, patients with carbapenemase-producing CRPA infections had higher 30-day mortality than those with non-carbapenemase-producing CRPA infections in both unadjusted (26 [22%] of 120 vs 19 [12%] of 153; difference 9%, 95% CI 3–16) and adjusted (difference 7%, 95% CI 1–14) analyses.

Interpretation

The emergence of different carbapenemases among CRPA isolates in different geographical regions and the increased mortality associated with carbapenemase-producing CRPA infections highlight the therapeutic challenges posed by these organisms.

Introduction

Pseudomonas aeruginosa is a leading global pathogen.1 Infections due to P aeruginosa are common, associated with high mortality, and increasingly carbapenem resistant.2–4 For this reason, WHO designated carbapenem-resistant P aeruginosa (CRPA) as one of three Critical Priority pathogens.5 The Antibacterial Resistance Leadership Group therefore set about to characterise the clinical and molecular epidemiology of CRPA.6

Non-enzymatic carbapenem resistance mechanisms are common in P aeruginosa.1 Although the emergence of carbapenemases fuelled the expansion of carbapenem-resistant Enterobacterales,7 the extent to which carbapenemases contribute to CRPA globally is unclear. The emergence of carbapenemases in CRPA would have therapeutic implications, because many carbapenemases confer resistance not only to carbapenems, but also to other β-lactam drugs, including some novel β-lactam–β-lactamase inhibitors.8 This expanded spectrum of resistance might be associated with worse outcomes among patients with CRPA infections. Furthermore, most rapid diagnostic tests for carbapenem resistance rely on detection of carbapenemase genes,9 and thus the utility of these tests to detect CRPA depends on the prevalence and types of carbapenemases harboured by these organisms.

Previous epidemiological investigations of CRPA were geographically limited or lacked detailed clinical data or molecular characterisation of bacteria.8,10–16 To address these knowledge gaps, we aimed to identify clinical characteristics of patients with CRPA isolates and outcomes of patients infected with CRPA across geographical regions, characterise the genetic back-grounds and frequency and types of carbapenemases among CRPA isolates across geographical regions, and compare outcomes of patients infected with carbapenemase-producing CRPA with those infected with non-carbapenemase-producing CRPA.

Methods

Study design and participants

The prospective observational Pseudomonas study (POP) was a cohort study that included 44 hospitals, including 16 in the USA, ten in south and central America (Colombia n=5, Chile n=2, Argentina n=2, Nicaragua n=1), nine in China, five in Australia, two in Singapore, one in Lebanon, and one in Saudi Arabia. Hospitalised patients with CRPA isolated from a bloodstream, respiratory, urinary, or wound culture between Dec 1, 2018, and Nov 30, 2019, and for whom 30-day outcome data were available, were eligible. Only the first eligible CRPA culture episode per patient was included. Patients were initially enrolled on the basis of detection of carbapenem resistance by the local clinical laboratory, but only those whose isolates were meropenem resistant (minimum inhibitory concen tration [MIC] ≥8 μg/mL) on the basis of broth microdilution testing in a central laboratory were included.17 Patients whose isolates were not confirmed to be P aeruginosa by whole-genome sequencing were excluded. Ethical approval for the study was obtained through institutional review boards of all health systems involved and the requirement to obtain informed consent was waived.

Procedures

Clinical data were abstracted from electronic health records at study sites and reviewed until 90 days after hospital discharge. Patients were presumed to be alive unless they were known to have died. Infection and colonisation were defined by previously applied criteria,7 except for respiratory isolates, where the clinical diagnosis recorded by physicians in the electronic health records was applied with supporting analyses using standardised criteria.7 Hospital-acquired infections were defined as those where the first positive culture was collected more than 2 days after hospital admission.

CRPA isolates underwent antimicrobial susceptibility testing at each site’s local clinical microbiology laboratory as per standard of care. Isolates were then sent to a central laboratory (the Antibacterial Resistance Leadership Group Laboratory Center at the Mayo Clinic [Rochester, MN, USA] for isolates not from China and the MDRO Regional Central Laboratory at Huashan Hospital, Fudan University [Shanghai, China] for Chinese isolates) where meropenem susceptibility was assessed by reference broth microdilution.17 DNA were extracted using the Wizard Genomic DNA Purification Kit (Promega; Madison, WI, USA) or DNeasy Blood and Tissue Kit (QIAGEN; Venlo, Netherlands). We used Illumina Nextera XT DNA sample preparation kits (Illumina; San Diego, CA, USA) to prepare libraries for sequencing. Isolates underwent next-generation sequencing using an Illumina HiSeq 4000, NextSeq 2000, or MiSeq, as previously described.18 We multiplexed and sequenced samples to yield a sequence coverage of around 100x. Paired end-reads were either 150 bp or 300 bp, and the MiSeq Reagent Kit version 3 or HiSeq X Ten Reagent Kit version 2.5 were used. Raw and quality trimmed fastq files were evaluated using Raspberry version 0.3. Sequencing data were quality trimmed and Illumina Nextera indexes removed using Trimmomatic version 0.39. Draft genomes were assembled using SPAdes version 3.13.0. Pseudomonas species were determined by fastANI version 1.32, using a 95% cutoff for species identification.19,20 Ten genomes were also included that had 94–95% average nucleotide identity with P aeruginosa but less than 86% average nucleotide identity with other Pseudomonas species. Multilocus sequence typing was analysed using mlst version 2.19.0 and the PubMLST database.21 Resistance genes were identified by AMRFinderPlus version 3.10.5 and ARIBA version 2.14.6.22,23 Core genome alignment was generated by Snippy version 4.6.018 using the P aeruginosa PAO1 genome (accession number NC_002516) as the reference. A maximum likelihood phylogenetic tree was constructed in RAxML version 8.2.4.24 oprD and its promoter regions were examined by BLASTn from BLAST+ 2.11.0,25 and those with a premature stop codon, frameshift, truncation, or promoter region IS insertion were classified as oprD mutants.

Outcomes

The primary outcome was 30-day mortality from the day the index culture was collected. Secondary outcomes were length of hospital stay from the day of the index culture, disposition after hospital discharge, and the desirability of outcome ranking (DOOR) analysis at 30 days.26 The DOOR outcome was defined a priori and assessed three undesirable events (absence of clinical response, lack of discharge or hospital readmission, and renal failure or Clostridioides difficile infection) and ordered outcomes based on the number of events.7 Clinical response was defined as symptomatic response, no additional CRPA therapy after the initial treatment course, and no relapse within 30 days.

Statistical analysis

We compared characteristics of patients with CRPA isolates and outcomes of patients with CRPA infections between five geographical regions (USA, China, south and central America, the Middle East, and Australia and Singapore). We used the χ2 test, to compare categorical variables, and the Kruskal-Wallis test, to compare continuous variables, in the comparison of characteristics and outcomes of patients with carbapenemase-producing CRPA infections with those with non-carbapenemase-producing CRPA infections. We constructed 95% Wald CIs with pooled variance for differences in 30-day and 90-day mortality. US patients were excluded from this analysis, because few US isolates harboured a carbapenemase. To adjust for confounding in the association between carbapenemases and mortality, we performed an inverse probability weighted analysis with adjustments for geographical region, age-adjusted Charlson Comorbidity Index,27 patient location before hospitalisation, immunocompromised status, and anatomical source of infection. We also performed an inverse probability weighted analysis within each geographical region. We visualised 30-day mortality by geographical region and by presence of a carbapenemase with Kaplan-Meier curves with administrative censoring at 30 days. We estimated pairwise DOOR probabilities of a favourable outcome (ie, fewer undesirable events of absence of clinical response, lack of discharge or hospital readmission, and renal failure or Clostridioides difficile infection) for a randomly selected infected patient between geographical regions and between patients with carbapenemase-producing and non-carbapenemase-producing CRPA infections. To further assess the association between carbapenemases and mortality, we constructed a multivariate logistic regression model with random effects for study site and a multivariate Cox proportional hazards model, using the same covariates as the inverse probability weighted analysis. p values of 0·05 or less were designated statistically significant and all tests were two-sided. Analyses were performed using SAS version 9.4.

Role of the funding source

The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.

Results

Of 1443 patients enrolled in POP, 972 (67%) were eligible for this analysis, including 527 (59% of total) in the USA, 171 (18%) in China, 127 (13%) in south and central America, 91 (9%) in the Middle East, and 56 (6%) in Australia and Singapore (appendix p 11). Patients in south and central America (median age 56 years, IQR 32–70) and China (59 years, 46–72) were younger than patients in the USA (63 years, 49–73), Middle East (66 years, 46–74), and Australia and Singapore (68 years, 59–79; p<0·0001; table 1), and had fewer comorbidities (south and central America median Charlson Comorbidity Index 1, IQR 0–2; China 1, 1–2; USA 2, 1–4; Middle East 2, 0–4, Australia and Singapore 3, 1–4; p<0·0001). 581 (60%) patients had CRPA infections and 391 (40%) had CRPA colonisation. 358 (62%) of 581 infections were respiratory, 88 (15%) were urinary, 69 (12%) were bloodstream, and 66 (11%) were wound infections (appendix p 2). Acuity of illness was higher among infected patients in the USA compared with other regions (China median Pitt Bacteraemia Score 2, IQR 0–4; Middle East 2, 1–6; Australia and Singapore 2, 0–4; south and central America 3, 0–6; USA 4, 2–6; p<0·0001).

Table 1:

Patient characteristics

Total (n=972) USA (n=527) China (n=171) South and central America (n=127) Middle East (n=91) Australia and Singapore (n=56) p value*
Demographics
 Age, years 62 (47–73) 63 (49–73) 59 (46–72) 56 (32–70) 66 (46–74) 68 (59–79) <0·0001
 Sex ·· ·· ·· ·· ·· ·· 0·052
  Female 351 (36%) 206 (39%) 48 (28%) 42 (33%) 38 (42%) 17 (30%) ··
  Male 621 (64%) 321 (61%) 123 (72%) 85 (67%) 53 (58%) 39 (70%) ··
Comorbidities
 Charlson Comorbidity Index 2 (1–4) 2 (1–4) 1 (1–2) 1 (0–2) 2 (0–4) 3 (1–4) <0·0001
 Diabetes 330 (34%) 193 (37%) 31 (18%) 37 (29%) 39 (43%) 30 (54%) <0·0001
 Heart disease 271 (28%) 192 (36%) 27 (16%) 11 (9%) 28 (31%) 13 (23%) <0·0001
 Cerebrovascular disease 200 (21%) 100 (19%) 63 (37%) 9 (7%) 22 (24%) 6 (11%) <0·0001
 Chronic kidney disease 126 (13%) 90 (17%) 5 (3%) 11 (9%) 15 (16%) 5 (9%) <0·0001
 Chronic obstructive pulmonary disease 154 (16%) 119 (23%) 11 (6%) 8 (6%) 10 (11%) 6 (11%) <0·0001
 History of malignancy 180 (19%) 91 (17%) 27 (16%) 28 (22%) 21 (23%) 13 (23%) 0·34
 Immunocompromised 123 (13%) 77 (15%) 7 (4%) 24 (19%) 11 (12%) 4 (7%) 0·0007
Origin of patient ·· ·· ·· ·· ·· ·· <0·0001
 Home 533 (55%) 261 (50%) 83 (49%) 79 (62%) 70 (77%) 40 (71%) ··
 Long-term care facility 171 (18%) 150 (28%) 7 (4%) 2 (2%) 2 (2%) 10 (18%) ··
 Hospital transfer 261 (27%) 115 (22%) 81 (47%) 44 (35%) 16 (18%) 5 (9%) ··
 Foreign country 6 (1%) 1 (<1%) 0 1 (1%) 3 (3%) 1 (2%) ··
 Hospice 1 (<1%) 0 0 1 (1%) 0 0 ··
Previous intensive care unit admission 549 (56%) 296 (56%) 92 (54%) 73 (57%) 68 (75%) 20 (36%) 0·0001
Patient location at time of first positive culture ·· ·· ·· ·· ·· ·· <0·0001
 Emergency department 119 (12%) 93 (18%) 5 (3%) 20 (16%) 0 1 (2%) ··
 Hospital ward 418 (43%) 185 (35%) 97 (57%) 43 (34%) 47 (52%) 46 (82%) ··
 Intensive care unit 402 (41%) 233 (44%) 66 (39%) 53 (42%) 41 (45%) 9 (16%) ··
 Other 33 (3%) 16 (3%) 3 (2%) 11 (9%) 3 (3%) 0 ··
Days from admission to culture 8 (1–27) 4 (0–21) 10 (2–25) 20 (2–43) 22 (9–65) 13 (1–25) <0·0001
Hospital-acquired 609 (63%) 281 (53%) 128 (75%) 90 (71%) 74 (81%) 36 (64%) <0·0001
Infection or colonisation by source ·· ·· ·· ·· ·· ·· <0·0001
 Blood (infection only) 69 (7%) 29 (6%) 10 (6%) 15 (12%) 12 (13%) 3 (5%) ··
 Respiratory 523 (54%) 283 (54%) 126 (74%) 41 (32%) 62 (68%) 11 (20%) ··
  Infection 358 (37%) 194 (37%) 94 (55%) 30 (24%) 31 (34%) 9 (16%) ··
  Colonisation 165 (17%) 89 (17%) 32 (19%) 11 (9%) 31 (34%) 2 (4%) ··
 Urinary 214 (22%) 120 (23%) 23 (13%) 42 (33%) 8 (9%) 21 (38%) ··
  Infection 88 (9%) 47 (9%) 11 (6%) 19 (15%) 6 (7%) 5 (9%) ··
  Colonisation 126 (13%) 73 (14%) 12 (7%) 23 (18%) 2 (2%) 16 (29%) ··
 Wound 166 (17%) 95 (18%) 12 (7%) 29 (23%) 9 (10%) 21 (38%) ··
  Infection 66 (7%) 38 (7%) 5 (3%) 9 (7%) 3 (3%) 11 (20%) ··
  Colonisation 100 (10%) 57 (11%) 7 (4%) 20 (16%) 6 (7%) 10 (18%) ··
Pitt Bacteraemia Score 3 (1–6) 3 (2–6) 2 (0–4) 2 (0–6) 3 (1–6) 2 (0–4) <0·0001
Polymicrobial 345 (35%) 191 (36%) 78 (46%) 31 (24%) 19 (21%) 26 (46%) <0.0001
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Data are n (%) or median (IQR).

*

χ2 test was used for categorical variables, and Kruskal-Wallis test was used for continuous variables.

A carbapenemase gene was detected in 211 (22%) of 972 CRPA isolates, including 186 (19%) with one carbapenemase gene and 25 (3%) with two. Klebsiella pneumoniae carbapenemase gene (blaKPC-2) was most common, present as the only carbapenemase gene in 83 isolates (39% of carbapenemase-producing CRPA isolates) and combined with blaVIM-2 in 20 (9% of carbapenemase-producing CRPA isolates). blaVIM-2 was present as the only carbapenemase gene in 52 isolates (25% of carbapenemase-producing CRPA isolates). Other common carbapenemase genes were blaNDM-1 (n=14, 7% of carbapenemase-producing CRPA isolates), blaIMP-1 (n=13, 6%), and blaGES-5 (n=12, 6%). Only one isolate had a class D carbapenemase gene (blaOXA-23).

88 (69%) of 127 CRPA isolates had a carbapenemase gene in south and central America, 32 (57%) of 56 in Australia and Singapore, 54 (32%) of 171 in China, 27 (30%) of 91 in the Middle East, and 10 (2%) of 527 in the USA (p<0·0001; figure 1). In south and central America, 41 (32%) of 127 isolates harboured blaKPC-2, 22 (17%) harboured blaVIM-2, and 20 (16%) harboured both blaKPC-2 and blaVIM-2. In China, 40 (23%) of 171 isolates harboured blaKPC-2 and six (4%) harboured blaVIM-2. blaVIM-2 (16 [18%] of 91 isolates) and blaGES-5 (seven [8%]) were the most common carbapenemase genes in the Middle East. By contrast, blaNDM-1 (12 [21%] of 56 isolates) and blaIMP-1 (12 [21%]) were the most common carbapenemase genes in Australia and Singapore. oprD mutations were identified in 670 (69%) of 972 isolates and were more frequently present in non-carbapenemase-producing CRPA isolates than in carbapenemase-producing CRPA isolates (546 [72%] of 761 vs 124 [59%] of 211; p=0·0003).

Figure 1: Carbapenemase genes identified in carbapenem-resistant Pseudomonas aeruginosa infection and colonisation isolates.

Figure 1:

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Isolates carried the followed carbapenemase genes: blaVIM-2 (n=5), blaKPC-2 (n=2), blaKPC-3 (n=1), blaNDM-1 (n=1), and blaVIM-1 (n=1) in the USA; blaKPC-2 (n=40), blaVIM-2 (n=6), blaGES-5 (n=2), blaDIM (n=1), blaIMP-14 (n=1), blaIMP-45 (n=1), blaIMP-54 (n=1), blaVIM-24 (n=1), and blaAFM-1 plus blaIMP-45 (n=1) in China; blaKPC-2 (n=41), blaVIM-2 (n=22), blaKPC-2 plus blaVIM-2 (n=20), blaIMP-18 + blaVIM-2 (n=3), blaOXA-23 (n=1), and blaVIM-11 (n=1) in south and central America; blaVIM-2 (n=16), blaGES-5 (n=7), blaIMP-15 (n=2), blaIMP-1 (n=1), and blaIMP-13 (n=1) in the Middle East; and blaIMP-1 (n=12), blaNDM-1 (n=12), blaGES-5 (n=3), blaVIM-2 (n=3), blaVIM-6 (n=1), blaIMP-62 plus blaNDM-1 (n=1) in Australia and Singapore. *blaNDM was identified in one (<1%) of 527 isolates and is thus not shown in the figure.

Carbapenemase-producing CRPA isolates had higher meropenem MIC values than non-carbapenemase-producing CRPA isolates (appendix p 12). 169 (80%) of 211 carbapenemase-producing CRPA isolates had meropenem MIC values of more than 32 μg/mL, compared with 72 (9%) of 761 non-carbapenemase-producing CRPA isolates (p<0·0001). Carbapenemase-producing CRPA isolates with oprD mutations were more likely to have meropenem MIC values of more than 32 μg/mL than those without oprD mutations (110 [89%] of 124 vs 59 [68%] of 87; p=0·0002). All 13 isolates with blaNDM, 11 (92%) of 12 isolates with blaGES, 75 (89%) of 84 isolates with blaKPC, 16 (84%) of 19 isolates with blaIMP, and 32 (57%) of 56 isolates with blaVIM had meropenem MIC values of more than 32 μg/mL. Local laboratory antimicrobial susceptibility testing indicated that carbapenemase-producing CRPA isolates were less likely to be susceptible to cefepime (14 [7%] of 193 vs 289 [42%] of 694), ceftazidime (6 [3%] of 176 vs 172 [39%] of 439), piperacillin-tazobactam (eight [5%] of 146 vs 252 [36%] of 700), ciprofloxacin (12 [6%] of 202 vs 256 [35%] of 730), and amikacin (77 [37%] of 206 vs 500 [85%] of 590) than non-carbapenemase-producing CRPA isolates (p<0·0001 for all comparisons; appendix p 3).

We found diverse genetic lineages among CRPA isolates (figure 2). The most common clonal groups were CG235, representing 117 (12%) of 972 isolates (116 [99%] of 117 were ST235, and one [1%] was ST3746), and CG111, representing 79 (8%) of 972 isolates (69 [87%] of 79 were ST111, nine [11%] were ST966, and one [1%] was other; appendix p 4). No other clonal group represented more than 4% of isolates. CG235 was the most common clonal group in south and central America (34 [27%] of 127 isolates), Australia and Singapore (13 [23%] of 56), the Middle East (14 [15%] of 91), and the USA (50 [9%] of 527). CG111 was the next most common clonal group in south and central America (26 [20%] of 127) and the Middle East (12 [13%] of 91), and 37 (97%) of 38 CG111 isolates in these regions harboured blaVIM-2. 14 (54%) of 26 CG111 isolates in south and central America harboured both blaKPC-2 and blaVIM-2. In China, CG463 (all ST463) was most common (34 [20%] of 171 isolates), and 31 (91%) of 34 CG463 isolates harbored blaKPC-2. CG463 was not identified in any other region. CG308 (20 [95%] of 21 were ST308, and one [5%] was ST2126) was most common in Australia and Singapore, where all 12 CG308 isolates harboured blaNDM-1.

Figure 2:

Figure 2:

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Phylogenetic population structures of carbapenem-resistant Pseudomonas aeruginosa isolates

105 (18%, 95% CI 15–21) of 581 patients infected with CRPA died within 30 days and 148 (25%, 22–29) died within 90 days (table 2). 21 (30%, 20–41) of 69 patients with bloodstream infections died within 30 days, 69 (19%, 15–23) of 358 patients with respiratory infections, nine (14%, 5–22) of 66 patients with wound infections, and six (7%, 2–12) of 88 patients with urinary infections (p=0·0012; appendix p 13). 223 (38%, 95% CI 34–42) of 581 infected patients were discharged to their home. 15 (29%, 17–41%) of 52 patients died within 30 days in the Middle East, 20 (27%, 17–38) of 73 in south and central America, 60 (19%, 15–24) of 308 in the USA, three (11%, 0–22) of 28 in Australia and Singapore, and seven (6%, 2–10) of 120 in China (p=0·0002; figure 3A; table 2). Similar mortality was observed when applying a standardised definition of respiratory tract infection instead of a physician-adjudicated definition (appendix p 5). Probabilities of favourable DOOR outcomes were greater in China than in other geographical regions (table 2; appendix p 14).

Table 2:

Patient outcomes

Total (n=581) USA (n=308) China (n=120) South and central America (n=73) Middle East (n=52) Australia and Singapore (n=28) p value*
Mortality†
 30-day (primary outcome) 105 (18%) 60 (19%) 7 (6%) 20 (27%) 15 (29%) 3 (11%) 0·0002
 90-day 148 (25%) 87 (28%) 10 (8%) 23 (32%) 21 (40%) 7 (25%) <0·0001
Length of hospital stay from infection onset, days 13 (6–30) 10 (5–20) 15 (7–30) 18 (7–41) 28 (11–59) 39 (19–72) <0·0001
Desirability of outcomes ranking outcome at 30 days‡
 Alive without events 211 (36%) 120 (39%) 51 (43%) 22 (30%) 12 (23%) 6 (21%) ··
 Alive with 1 event 123 (21%) 73 (24%) 36 (30%) 9 (12%) 2 (4%) 3 (11%) ··
 Alive with 2 or 3 events 142 (24%) 55 (18%) 26 (22%) 22 (30%) 23 (44%) 16 (57%) ··
 Death 105 (18%) 60 (19%) 7 (6%) 20 (27%) 15 (29%) 3 (11%) ··
Disposition after discharge <0·0001
 Home 223 (38%) 94 (31%) 47 (39%) 42 (58%) 27 (52%) 13 (46%) ··
 Long-term care facility 145 (25%) 129 (42%) 4 (3%) 5 (7%) 1 (2%) 6 (18%) ··
 Transfer to another hospital or to a foreign country 57 (10%) 5 (2%) 48 (40%) 2 (3%) 1 (2%) 1 (4%) ··
 Hospice 27 (5%) 15 (5%) 11 (9%) 1 (1%) 0 0 ··
 Death 121 (21%) 63 (20%) 10 (8%) 22 (30%) 20 (38%) 6 (21%) ··
 Remained in the hospital 8 (1%) 2 (1%) 0 1 (1%) 3 (6%) 2 (7%) ··
Clinical response 283 (49%) 175 (57%) 56 (47%) 29 (40%) 14 (27%) 9 (32%) <0·0001
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Data are n (%) or median (IQR).

*

χ2 test was used for categorical variables, and Kruskal-Wallis test was used for continuous variables.

†

Patients who were discharged to hospice were not considered to have died.

‡

The three adverse events assessed by desirability of outcomes ranking were lack of clinical response, lack of discharge within 30 days or readmission within 30 days, and incident renal failure or Clostridioides difficile infection. The unadjusted probability estimates for a favourable outcome (ie, clinical response, discharge or hospital readmission, and absence of renal failure or Clostridioides difficile infection) using China as the reference region were 44% (95% CI 39–50) for the USA, 35% (27–43) for south and central America, 28% (20–37) for the Middle East, and 31% (21–42) for Australia and Singapore (appendix p 5).

Figure 3:

Figure 3:

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30-day overall survival after carbapenem-resistant Pseudomonas aeruginosa infection (A) 30-day overall survival by region. (B) 30-day overall survival by presence of carbapenemase for infections outside the USA.

120 (44%) of 273 patients with CRPA infections outside of the USA were infected by carbapenemase-producing CRPA. Patients with carbapenemase-producing CRPA infections were more likely to be in south and central America (53 [44%] of 120 with carbapenemase-producing CRPA vs 20 [13%] of 153 with non-carbapenemase-producing CRPA), immunocom promised (23 [19%] vs 11 [7%]), and have a bloodstream (25 [21%] vs 15 [10%]) or urinary infection (36 [30%] vs 5 [3%]) than patients with non-carbapenemase-producing CRPA infections, and were less likely to be in China (30 [25%] vs 90 [59%]) and have a respiratory (44 [37%] vs 120 [78%]) or polymicrobial infection (33 [28%] vs 66 [43%]; appendix p 6). Mortality was higher in patients with carbapenemase-producing CRPA infections compared with non-carbapenemase-producing CRPA infections at 30 days (26 [22%] of 120 vs 19 [12%] of 153; unadjusted difference 9%, 95% CI 3–16; figure 3B) and at 90 days (33 [28%] of 120 vs 28 [18%] of 153; unadjusted difference 9%, 2–16). Carbapenemase-producing CRPA infections were also associated with increased mortality compared with non-carbapenemase-producing CRPA in an inverse probability weighted analysis (30-day difference 8%, 1–14; 90-day difference 8%, 0–15). Increased 30-day mortality after carbapenemase-producing CRPA infection was also observed within each geographical region, except for south and central America (appendix p 7), and when performing an analysis that applied a standardised definition of CRPA pneumonia (appendix p 8). The multivariate logistic regression (adjusted odds ratio 2∙09, 95% CI 0∙93–4∙70) and Cox proportional hazards models (adjusted hazard ratio 1∙41, 95% CI 0∙71–2∙80) also suggested increased 30-day mortality with carbapenemase production (appendix pp 9–10). DOOR outcomes, clinical response rates, and hospital length of stay were not significantly different between carbapenemase-producing CRPA and non-carbapenemase-producing CRPA infections (appendix p 6).

Discussion

In this international, prospective cohort study, we found differences in the prevalence and types of carbapenemases harboured by CRPA across geographical regions. Although only 2% of CRPA isolates from the USA had a carbapenemase, 30–69% of CRPA isolates in other regions had a carbapenemase, with the highest frequency in south and central America. KPC-2 was the most common carbapenemase globally, followed by VIM-2, IMP-1, NDM-1, and GES-5, but distinct carbapenemases predominated in different regions. Carbapenemase-producing CRPA isolates were more likely to have high-level meropenem resistance and resistance to other anti-pseudomonal drugs than non-carbapenemase-producing CRPA isolates. Moreover, carbapenemase-producing CRPA infections were associated with increased mortality compared with non-carbapenemase-producing CRPA infections (22% vs 12%), with this difference persisting after adjusting for age, geographical region, comorbidities, patient location before admission, immunocompromised status, and source of infection.

This work was conducted through the Multi-drug Resistant Organism Network. It was a multinational study aimed at increasing understanding of the clinical and molecular epidemiology of carbapenem-resistant Gram-negative pathogens, and adds to previous analyses of carbapenem-resistant Enterobacterales and Acinetobacter baumannii from the Multi-drug Resistant Organism Network.7,18,28 Most previous studies of carbapenemases in P aeruginosa analysed isolates within a single country or region.8,10–15 An exception is an analysis of CRPA isolates from 12 countries by Gill and colleagues.16 They found that VIM and GES were the most common carbapenemases, which differs from our study, in which KPC was most common. We believe that differences in geographical regions between studies might explain these disparate findings. blaKPC has driven the global proliferation of carbapenem resistance in Enterobacterales,7 so the emergence of KPC in P aeruginosa poses a major public health threat, particularly because KPC-producing organisms are resistant to the anti-pseudomonal drug ceftolozane-tazobactam.29 Moreover, we found that P aeruginosa harbouring both blaKPC-2 and blaVIM-2 has emerged in south and central America. The presence of both enzymes reduces treatment options because avibactam and relebactam do not inhibit VIM carbapenemases, and thus these organisms are also resistant to ceftazidime–avibactam and imipenem-relebactam.29,30 We hypothesise that the expanded resistance of carbapenemase-producing CRPA might have contributed to the increased mortality observed among patients infected with carbapenemase-producing CRPA compared with non-carbapenemase-producing CRPA.

Our finding that carbapenem resistance in P aeruginosa is rarely due to carbapenemases in the USA corroborates work from the Centers for Disease Control and Prevention’s Antibacterial Resistance Laboratory Network. They sampled CRPA isolates submitted to USA public health laboratories, used targeted PCR or phenotypic methods to identify carbapenemases, and found that 3% of CRPA isolates possessed a carbapenemase.11 We believe that identifying a similarly low prevalence of carbapenemases in our cohort using whole-genome sequencing strengthens the conclusion that carbapenemase-producing CRPA are rare in the USA. However, surveillance is needed to detect the emergence of carbapenemase-producing CRPA in the USA, given their emergence in other regions.

We identified substantial differences in outcomes of patients with CRPA infection by geographical region. 30-day mortality was 6% in China and 11% in Australia and Singapore, but it was 19% in the USA, 27% in south and central America, and 29% in the Middle East. The reasons for these mortality differences are unclear, but mortality was also lower in China in an international study of infections caused by carbapenem-resistant Klebsiella pneumoniae.18 Patients from China had lower Pitt Bacteraemia Scores, indicating a lower severity of acute illness, and were less likely to be immunocompromised than patients from other regions. It is possible that differences in characteristics of health-care systems and supportive care contributed to these mortality differences. Ceftolozane-tazobactam and ceftazidime-avibactam were not available or not widely used during the study in south-central American countries and China, but one or both drugs were frequently used in other regions. The unavailability of these drugs in south and central America, combined with the high prevalence of carbapenemase-producing CRPA that are resistant to traditional anti-pseudomonal drugs, might have contributed to the high mortality observed in this region. These geographical differences in outcomes have implications for clinical trials of treatments for CRPA infections. A clinical trial of ceftolozane-tazobactam might show efficacy in the USA, where carbapenemase-producing CRPA is rare, but not in south and central America, where KPC-producing and VIM-producing CRPA are common.

The genetic heterogeneity of CRPA isolates in this study contrasts with the clonal dominance of ST258 and ST11 in carbapenem-resistant K pneumoniae or ST2 in carbapenem-resistant A baumannii.18,28 Although CG235 was most common, it represented only 12% of CRPA isolates in this study. Different clones within CG235 have acquired different carbapenemase genes in different geographical regions. For example, although CG235 did not harbour carbapenemases in the USA, a CG235 clone acquired blaKPC-2 in south and central America, another CG235 clone acquired blaGES-5 in the Middle East, and another acquired blaIMP-1 in Australia and Singapore. Although CG111 was observed in most regions, only CG111 strains in south and central America acquired both blaKPC-2 and blaVIM-2. Additionally, certain clonal groups that acquired carbapenemase genes have emerged within specific regions. For example, CG463 was only identified in China and almost all isolates possessed blaKPC-2. CG308 was mostly identified in Australia and Singapore, where it had acquired blaNDM-1. Although these emerging high-risk carbapenemase-producing CRPA might currently be geographically limited, vigilance is warranted to detect their emergence in new locations.

This study has limitations. Although it included hospitals from four continents, it did not include sites from Europe or Africa. Furthermore, participating hospitals might not be completely representative of their geographical region. The clinical data only included data that were available through each hospital’s electronic health records. Thus, it is possible that differences in documentation contributed to geographical variation in patient characteristics. This approach was pursued to obtain a waiver of informed consent, which permitted consecutive enrolment of patients with CRPA infections at study hospitals without selection bias. Furthermore, our primary outcome of 30-day mortality does not rely on extensive documentation in electronic health records. The in-vitro activity of non-carbapenem antibiotics against CRPA isolates was assessed using antimicrobial susceptibility testing results from local laboratories, not central laboratories. Although this testing was not standardised, it represents real-world data that were available to providers. It is a strength that whole-genome sequencing was performed on all CRPA isolates, but even whole-genome sequencing is insufficient to identify all mechanisms of carbapenem resistance in P aeruginosa, such as overexpression of efflux pumps and chromosomal β-lactamases. We encourage additional studies of CRPA that assess gene expression to garner additional insights. Although we adjusted for potential confounders using inverse probability weighting, we might have been unable to adjust for all variables that might confound the association between carbapenemase-producing CRPA and mortality. Furthermore, this association might not apply to US patients, because they were excluded from this analysis owing to a low prevalence of carbapenemases. We encourage additional investigations to confirm our findings in other cohorts. Finally, we evaluated CRPA isolated from the four most common anatomical sites, but our results might not apply to other anatomical sites.

In summary, this multinational study identified differences in the clinical characteristics and outcomes of patients infected with CRPA across geographical regions. Carbapenemases were rare in CRPA isolates in the USA but common in isolates in other regions, particularly KPC-2 and VIM-2. Carbapenemase-producing CRPA isolates exhibited higher degrees of meropenem resistance than non-carbapenemase-producing CRPA isolates and were more frequently resistant to other anti-pseudomonal drugs. Moreover, patients with carbapenemase-producing CRPA infection had a higher 30-day mortality rate, even after adjustment for confounders. These findings highlight that different strategies are needed to combat CRPA in different parts of the world.

Supplementary Material

1

Research in context.

Evidence before this study

We searched PubMed without language restrictions for articles published before May 17, 2022, using the terms “carbapenem resistant”, “Pseudomonas aeruginosa”, and “carbapenemase”. The results of this search primarily identified studies of carbapenem-resistant Pseudomonas aeruginosa (CRPA) epidemiology that were conducted in individual centres or individual countries. For example, studies conducted by the Centers for Disease Control and Prevention found that 2–3% of CRPA isolates submitted to public health laboratories in the USA possessed a carbapenemase. We identified one study that characterised CRPA isolates from 14 countries in the Asia-Pacific region and found that VIM, NDM, VEB, and IMP were the most common carbapenemases harboured by these organisms.

A second international study analysed CRPA isolates from17 medical centres in 12 countries in Europe, the Middle East, the USA, South America, and Africa, and found that 33% of isolates possessed carbapenemases, of which VIM and GES were most common. Both studies found that carbapenemase-producing CRPA isolates were less likely to test susceptible to other anti-pseudomonal drugs than non-carbapenemase-producing CRPA isolates. Neither of these studies used whole-genome sequencing to provide a comprehensive evaluation of carbapenemase genes and detailed clinical data to assess patient characteristics and outcomes were not available. We did not identify any studies that compared outcomes of patients infected with CRPA across different geographical regions or compared outcomes of patients infected with carbapenemase-producing CRPA with those infected with non-carbapenemase-producing CRPA.

Added value of this study

We used a uniform protocol to characterise the clinical and bacterial characteristics of all CRPA isolates from 972 patients hospitalised over a 1-year period at 44 medical centres in10 countries. We made several observations not made in previous studies. First, 30-day mortality after CRPA infection was highest in bloodstream infections (30%), followed by infections of the respiratory tract (19%), wounds (14%), and urinary tract (7%). Second, 30-day mortality varied across geographical regions, with the highest mortality in the Middle East (29%) and south and central America (27%), and the lowest in China (6%). Third, 30-day mortality was higher in patients with carbapenemase-producing CRPA infections compared with non-carbapenemase-producing CRPA infections (22% vs 12%) and this mortality difference persisted even after adjusting for age, comorbidities, geographical region, patient location before hospitalisation, immunocompromised status, and anatomical source of infection. These new findings highlight the differences in the role of carbapenemases and in clinical outcomes in CRPA infections across different geographical regions.

Implications of all the available evidence

The differential emergence of carbapenemases among CRPA isolates across geographical regions has diagnostic and therapeutic implications. Given that most rapid diagnostic tests for carbapenem resistance rely on detecting carbapenemase genes, the yield of these assays to detect CRPA might be lower in the USA than in regions with a high prevalence of carbapenemase-producing CRPA. Furthermore, the emergence of serine-carbapenemases and metallo-carbapenemases in multiple geographical regions reduces the clinical utility of new β-lactam–β-lactamase inhibitors for CRPA infections in these areas, because these new drugs might not be effective against organisms with these enzymes. These findings have implications for the design of clinical trials of new antibacterial drugs for CRPA infections.

Acknowledgments

This study was funded by a grant from the NIH (UM1 AI104681) to HFC and VGF.

Declaration of interests

All authors report funding support from the Antibacterial Resistance Leadership Group of the National Institutes of Health (NIH) and the National Institute of Allergy and Infectious Diseases (NIAID; UM1AI104681) during the conduct of this study. Additionally, during the conduct of this study, and outside of the submitted work, the authors report the following disclosures. KSK reports consulting fees paid directly to him by Merck, Shionogi, Qpex, and Micrux. JG-D reports grants and contracts paid to her institution from NIH, BARDA, Janssen Research & Development LLC, Pfizer, BioNTech SE, GCAR, Hoffman La-Roche, I-Mab Bioppharma, Rebiotix, Target Health, LLC OBO Lilly USA, GlaxoSmithKline, Summit Limited, Cidara Therapeutics, Merck Sharp & Dohme, Seres Therapeutics; and Infectious Diseases Society of America Research Committee participation paid to her directly. SSK reports speaker and advisory board payments from Pfizer, Astellas, Novartis, Merck, and Gilead. JMO reports speaker payments from Pfizer, MSD, and Biotoscana; and board participation on the Chair Ethics Committee. SLV-B reports personal fees from Pfizer, Biotoscana, and MSD; meeting support from MSD and Pfizer; and data safety monitoring board participation with MSD and GlaxoSmithKline. PT reports honoraria payments to his institution from Aj Biologics and bioMérieux. GW reports payment to his institution from Allergan for contracted activities. LMA reports grants and contracts paid to her institution from Rainmakers/CDC multisystem inflammatory syndrome in adults with SARS-CoV-2, and Regeneron study co-investigator; consulting and honoraria paid directly to them from Medscape for CME lectures, and Ferring Pharmaceuticals for advisory board participation; and volunteer work as the director of the IDSA Board of Directors. KO reports payments for educational events and presentations from Pfizer, MSD, AstraZeneca, and Farma de Colombia; meeting support from Pfizer, MSD, and Gilead; and expert testimony support from Pfizer, bioMérieux, and MSD. MES reports speaker fees from Pfizer (Argentina); advisory board participation for Wockhardt; consultancy for Basilea; and data safety monitoring board participation with Fulcrum Therapeutics. JMM reports grants from Pfizer, MSD, and bioMérieux, the National Fund for Scientific and Technological Development; and the Agencia Nacional de Investigation y Desarrollo Millennium Science Initiative/Millennium Initiative for Collaborative Research on Bacterial Resistance, Government of Chile. DLP reports grants and contracts paid to his institution from Merck, Pfizer, and Shionogi; consulting and honoraria payments to him by Merck, Shionogi, QPex, Spero Therapeutics, Sumitomo, Pfizer, and bioMérieux; meeting support from Shionogi; and board and committee participation with Symvivo, and AMR action fund. SE reports grants from the NIAID and the NIH and Degruter (Editor in Chief for Statistical Communications in Infectious Diseases); royalties from Taylor & Francis; consulting fees from Genentech, AstraZeneca, Takeda, Microbiotix, Johnson & Johnson, Endologix, ChemoCentryx, Becton Dickinson, Atricure, Roviant, Neovasc, Nobel Pharma, Horizon, International Drug Development Institute, SVB Leerink; payments from Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks; meeting support from the US Food and Drug Administration, the Deming Conference on Applied Statistics, the Clinical Trial Transformation Initiative, the Council for International Organizations of Medical Sciences, the International Chinese Statistical Association Applied Statistics Symposium, and the Antimicrobial Resistance and Stewardship Conference; and board member participation for the NIH, the Breast International Group, the University of Pennsylvania, Duke University, Roche, Pfizer, Takeda, Akouos, Apellis, Teva, Vir, DayOneBio, Alexion, Tracon, Rakuten, AbbVie, Nuvelution, Clover, FHI Clinical, Lung Biotech, SAB Biopharm, Advantagene, the American Statistical Association, the Society for Clinical Trials, and the Frontier Science Foundation. RAB reports grants and contracts, paid to his institution, by VenatoRx, Wockhardt, and Merck; payments made to him by Pfizer to moderate meeting sessions; patents with Case Western Reserve University on the development of boronic acid transition state inhibitors for β-lactamases (WO2022187362A1, US9949995B2, and US20170252326A1); and payment for participation on a data safety monitoring board, safety oversight committee support, and Logistics Associate for DMID-CROMS (contractor) with Technical Resources International. MVV reports contracts, consulting fees, and honoraria payments from Pfizer and MSD; consulting fees from West Quimica Colombia; and honoraria from bioMérieux. RP reports grants from BioFire Diagnostics, ContraFect, and TenNor Therapeutics; is a consultant to Curetis, Specific Technologies, Next Gen Diagnostics, PathoQuest, Selux Diagnostics, 1928 Diagnostics, PhAST, Day Zero Diagnostics, Torus Biosystems, Mammoth Biosciences, and Qvella, for which monies are paid to Mayo Clinic; is a consultant to Netflix and CARB-X; has a patent on Bordetella pertussis and parapertussis PCR issued (US8507201B2), a patent on a device and method for sonication (with royalties paid by Samsung to Mayo Clinic; US7076117B2), and a patent on an anti-biofilm substance issued (US8802414B2); receives an editor’s stipend from the Infectious Diseases Society of America; and receives honoraria from the National Board of Medical Examiners, UpToDate, and the Infectious Diseases Board Review Course. CAA reports the grants and contracts paid to his institution from NIH and NIAID, MeMed Diagnostics, Entasis Therapeutics, Merck Pharmaceuticals, and Harris County Public Health; payments to him for UpToDate royalties, reimbursement of meeting attendance, and speaking from Infectious Diseases Society of America, American Society for Microbiology, Society of Hospital Epidemiology of America, European Society for Clinical Microbiology and Infectious Diseases, bioMérieux Foundation, Sociedad Argentina de Infectologia, Sociedad Chilena de Infectologia, Sociedad Colombiana de Infectologia, Panamerican Society for Infectious Diseases, Brazilian Society for Infectious Diseases, reviewer participation as part of the NIH grant Review Study Sections, travel expenses from the Infectious Disease Society of America (IDSA) Board of Directors, and for Editor in Chief for Antimicrobial Agents and Chemotherapy; non-paid participation with WHO Antibacterial Pipeline Advisory Group; and participation on the IDSA Board of Directors. HFC reports participation on a Merck data safety monitoring board for molnupiravir paid directly to him, stock ownership in Moderna and Merck, and a position as expert witness for Lilly and Nexus Pharmaceuticals. VGF reports grants to his institution from the NIH, MedImmune, Allergan, Pfizer, Advanced Liquid Logics, Theravance, Novartis, Merck, Medical Biosurfaces, Locus, Affinergy, ContraFect, Karius, Genentech, Regeneron, Basilea, and Janssen; royalties from UpToDate; personal fees from Novartis, Debiopharm, Genentech, Achaogen, Affinium, Medicines, MedImmune, Bayer, Basilea, Affinergy, Janssen, ContraFect, Regeneron, Destiny, Amphliphi Biosciences, Integrated Biotherapeutics, C3J, Armata, Valanbio, Akagera, Aridis, and Roche; editorial stipend from Infectious Diseases of America; pending patent for a host gene expression signature diagnostic for sepsis (US9850539B2); and stock options with Valanbio and ArcBio. YD reports grants from Entasis, Asahi Kasei Pharma, Shionogi, and Kanto Chemical paid to his institution; consulting fees paid directly to him from Meiji Seika Pharma, Shionogi, Gilead, MSD, Chugai, and bioMérieux; and speaker payments from MSD, Shionogi, AstraZeneca, Teijin Healthcare, Gilead, FujiFilm Toyama Chemical, bioMerieux, HU Frontier, and Eiken Chemical paid to him. DvD reports grants and contracts from the NIH and Merck paid to his institution outside of the published work; and consultancy for Astellas, Merck, Allergan, T2Biosystems, Roche, Achaogen, Neumedicine, Shionogi, Pfizer, Entasis, QPex, Wellspring, and Karius. MJS reports contract payments to his institution from Merck, Allergan, BioFire Diagnostics, Affinity Biosensors, and SNIPRBiome; personal consulting fees from Shionogi; and data and safety monitoring board participation for Spero Therapeutics.

Funding

National Institutes of Health.

MDRO Network Investigators (listed by centre alphabetically)

American University of Beirut Medical Center, Beirut, Lebanon: Souha S Kanj; Beijing Ditan Hospital, Capital Medical University, Beijing, China: Fujie Zhang; Boston University, Boston, MA, USA: Judith J Lok; Case Western, Cleveland, OH, USA: Robert A Salata; Centro de Educación Médica e Investigaciones Clínicas, Buenos Aires, Argentina: Martin Stryjewski, Valentina Di Castelnuovo; Centro Medico Imbanaco, Cali, Colombia: Jose Millan Oñate Gutierrez; Cleveland Clinic, Cleveland, OH, USA: Eric Cober, Susan Richter; Duke University, Durham, NC, USA: Deverick J Anderson, Beth Evans, Carol Hill, Heather R Cross, Keri Baum, Rebekka Arias, Vance G Fowler Jr; ESE Hospital Universitario, San Jorge de Pereira, Pereira, Colombia: Karen Ordoñez; Emory University, Atlanta, GA, USA: Jesse T Jacob; Guangzhou Eighth People’s Hospital, Guangzhou, China: Linghua Li; Hackensack Meridian Health, Nutley, NJ, USA: Barry N Kreiswirth, Claudia Manca, Liang Chen, Samit Desai; Henry Ford Hospital, Detroit, MI, USA: Erica Herc; Hospital “Cosme Argerich” de Buenos Aires, Buenos Aires, Argentina: Ezequiel Cordova; Hospital de Puerto Montt, Puerto Montt, Chile: Maria Rioseco; Hospital Escuela Oscar Danilo Rosales Arguello, Leon, Nicaragua: Samuel Vichez; Hospital Italiano de Buenos Aires, Buenos Aires, Argentina: Marisa L Sanchez; Hospital San Ignacio, Bogotá, Colombia: Sandra Valderrama; Hospital Universitario Erasmo Meoz ESE, Cúcuta, Colombia: Jairo Figueroa; Houston Methodist, Houston, TX, USA: Cesar A Arias, An Q Dinh, Diane Panesso, Kirsten Rydell, Truc T Tran; Huashan Hospital, Fudan University, Shanghai, China: Fupin Hu, Jiachun Su, Jianping Jiang, Minggui Wang, Xiaogang Xu, Yang; Instituto de Ciencias e Innovación en Medicina, Clinica Alemana, Universidad del Desarrollo, Santiago, Chile: Jose M Munita, Maria Spencer; King Abdulaziz Medical City, Riyadh, Saudi Arabia: Thamer Alenazi; Louis Stokes Cleveland Department of Veterans Affairs Medical Center, Cleveland, OH, USA: Robert A Bonomo, Steven H Marshall, Susan D Rudin; Mayo Clinic, Rochester, MN, USA: Charles Huskins, Kerry Greenwood-Quaintance, Robin Patel, Suzannah Schmidt-Malan; Medical College of Wisconsin, Milwaukee, WI, USA: Sara Revolinski; MedStar Washington Hospital Center, Washington, DC, USA: Glenn Wortmann; MetroHealth Medical Center, Cleveland, OH, USA: Robert C Kalayjian; Montefiore Medical Center, Albert Einstein College of Medicine, New York, NY, USA: Gregory Weston; Montefiore Medical Center, Moses Campus, Bronx, NY, USA: Belinda Ostrowsky; Mount Sinai, New York, NY, USA: Gopi Patel; New York University Langone Medical Center, NY, USA: Daniel Eiras; North Shore University Hospital, Manhasset, NY, USA: Angela Kim; Ochsner Clinic Foundation, New Orleans, LA, USA: Julia Garcia-Diaz; Organizacion Clinica General del Norte, Barranquilla, Colombia: Soraya Salcedo; OSF Saint Francis Medical Center, Peoria, IL, USA: John J Farrell; Peking Union Medical College Hospital, Beijing, China: Fujie Zhang, Zhengyin Liu; Princess Alexandra Hospital, Brisbane, Queensland, Australia: Andrew Henderson; Royal Brisbane and Women’s Hospital, Brisbane, Queensland, Australia: David L Paterson; Ruijin Hospital, Shanghai, China: Qing Xie; Rutgers University, New Brunswick, NJ, USA: Keith S Kaye; Shulan Hangzhou Hospital, Shulan Health, Hangzhou, China: Hainv Gao; Sir Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China: Yunsong Yu; St Vincent’s Hospital, Melbourne, Victoria, Australia: Mary Waters; Stony Brook University, Stony Brook, NY, USA: Bettina C Fries; SUNY Downstate Medical Center, New York, NY, USA: Brandon Eilertson; Tan Tock Seng Hospital, Singapore: Kalisvar Marimuthu, Oon Tek Ng, Partha Pratim De; National University of Singapore, Singapore: Kean Lee Chew, Nares Smitasin, Paul Ananth Tambyah; Temple University Hospital, Philadelphia, PA, USA: Jason C Gallagher; The Alfred Hospital, Melbourne, Victoria, Australia: Anton Peleg; The Austin Hospital, Heidelberg West, Victoria, Australia: Marcel Leroi; The First Affiliated Hospital of Medical School of Zhejiang University, Hangzhou, China: Lanjuan Li; The George Washington University, Washington, DC, USA: Lauren Komarow, Lizhao Ge, Scott Evans; The University of Alabama, Birmingham, AL, USA: Todd McCarty; The University of California San Francisco, CA, USA: Henry F Chambers; The University of California, Los Angeles, CA, USA: Omai B Garner; The University of Miami Miller School of Medicine and Jackson Health System, Miami, FL, USA: Lilian M Abbo; The University of North Carolina, Chapel Hill, NC, USA: David van Duin; The University of Pennsylvania Health System, Philadelphia, PA, USA: Ebbing Lautenbach, Jennifer H Han; The University of Pittsburgh School of Medicine, Pittsburgh, PA, USA: Yohei Doi; The University of Southern California, Los Angeles, CA, USA: Darren Wong; The University of Texas Health Science Center at Houston, Houston, TX, USA: Blake Hanson; Universidad El Bosque, Bogotá, Colombia: Jinnethe Reyes, Maria Virginia Villegas Botero, Lorena Diaz; University Hospitals Cleveland Medical Center, Cleveland, OH, USA: Federico Perez; Vanderbilt University Medical Center, Nashville, TN, USA: Ritu Banerjee; Wayne State University, Detroit, MI, USA: Sorabh Dhar; Weill Cornell Medicine, NewYork-Presbyterian Hospital, New York, NY, USA: Michael J Satlin, Lars F Westblade; West China Hospital of Sichuan University, Chengdu, China: Zhiyong Zong.

Footnotes

For more on data sharing see https://arlg.org/request-data/

Data sharing

Individual deidentified participant data (and supporting documentation, data dictionaries, and protocol) that underlie the results in this Article can be made available to investigators following submission of a plan for data use, approval by the Antibacterial Resistance Leadership Group or designated entity, and execution of required institutional agreements. Provision might be contingent upon the availability of funding for data preparation and deidentification. More information can be found on the Antibacterial Resistance Leadership Group website. Sequences will be publicly available through the National Center for Biotechnology Information (accession number PRJNA824880).

References

  • 1.Livermore DM. Multiple mechanisms of antimicrobial resistance in Pseudomonas aeruginosa: our worst nightmare? Clin Infect Dis 2002; 34: 634–40. [DOI] [PubMed] [Google Scholar]
  • 2.Thaden JT, Park LP, Maskarinec SA, Ruffin F, Fowler VG Jr, van Duin D. Results from a 13-year prospective cohort study show increased mortality associated with bloodstream infections caused by Pseudomonas aeruginosa compared to other bacteria. Antimicrob Agents Chemother 2017; 61: e02761–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Sader HS, Castanheira M, Ryan Arends SJ, Goossens H, Flamm RK. Geographical and temporal variation in the frequency and antimicrobial susceptibility of bacteria isolated from patients hospitalized with bacterial pneumonia: results from 20 years of the SENTRY Antimicrobial Surveillance Program (1997–2016). J Antimicrob Chemother 2019; 74: 1595–606. [DOI] [PubMed] [Google Scholar]
  • 4.Cai B, Echols R, Magee G, et al. Prevalence of carbapenem-resistant Gram-negative infections in the United States predominated by Acinetobacter baumannii and Pseudomonas aeruginosa. Open Forum Infect Dis 2017; 4: ofx176. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.WHO. Media Center. WHO publishes list of bacteria for which new antibiotics are urgently needed. World Health Organization: Feb 27, 2017. https://www.who.int/news/item/27-02-2017-who-publishes-list-of-bacteria-for-which-new-antibiotics-are-urgently-needed (accessed June 30, 2022). [Google Scholar]
  • 6.Chambers HF, Evans SR, Patel R, et al. Antibacterial Resistance Leadership Group 2.0: back to business. Clin Infect Dis 2021; 73: 730–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.van Duin D, Arias CA, Komarow L, et al. Molecular and clinical epidemiology of carbapenem-resistant Enterobacterales in the USA (CRACKLE-2): a prospective cohort study. Lancet Infect Dis 2020; 20: 731–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Giani T, Arena F, Pollini S, et al. Italian nationwide survey on Pseudomonas aeruginosa from invasive infections: activity of ceftolozane/tazobactam and comparators, and molecular epidemiology of carbapenemase producers. J Antimicrob Chemother 2018; 73: 664–71. [DOI] [PubMed] [Google Scholar]
  • 9.Cortazzo V, D’Inzeo T, Giordano L, et al. Comparing BioFire FilmArray BCID2 and BCID panels for direct detection of bacterial pathogens and antimicrobial resistance genes from positive blood cultures. J Clin Microbiol 2021; 59: e03163–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Del Barrio-Tofiño E, Zamorano L, Cortes-Lara S, et al. Spanish nationwide survey on Pseudomonas aeruginosa antimicrobial resistance mechanisms and epidemiology. J Antimicrob Chemother 2019; 74: 1825–35. [DOI] [PubMed] [Google Scholar]
  • 11.Vallabhaneni S, Huang JY, Grass JE, et al. Antimicrobial susceptibility profiles to predict the presence of carbapenemase genes among carbapenem-resistant Pseudomonas aeruginosa isolates. J Clin Microbiol 2021; 59: e02874–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Hu YY, Gu DX, Cai JC, Zhou HW, Zhang R. Emergence of KPC-2-producing Pseudomonas aeruginosa sequence type 463 isolates in Hangzhou, China. Antimicrob Agents Chemother 2015; 59: 2914–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Kresken M, Körber-Irrgang B, Korte-Berwanger M, et al. Dissemination of carbapenem-resistant Pseudomonas aeruginosa isolates and their susceptibilities to ceftolozane-tazobactam in Germany. Int J Antimicrob Agents 2020; 55: 105959. [DOI] [PubMed] [Google Scholar]
  • 14.Vanegas JM, Cienfuegos AV, Ocampo AM, et al. Similar frequencies of Pseudomonas aeruginosa isolates producing KPC and VIM carbapenemases in diverse genetic clones at tertiary-care hospitals in Medellín, Colombia. J Clin Microbiol 2014; 52: 3978–86. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Lee YL, Ko WC, Hsueh PR. Geographic patterns of carbapenem-resistant Pseudomonas aeruginosa in the Asia-Pacific Region: Results from the Antimicrobial Testing Leadership and Surveillance (ATLAS) Program, 2015–2019. Antimicrob Agents Chemother 2022; 66: e0200021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Gill CM, Aktab E, Alfouzan W, et al. The ERACE-PA Global Surveillance Program: ceftolozane/tazobactam and ceftazidime/avibactam in vitro activity against a global collection of carbapenem-resistant Pseudomonas aeruginosa. Eur J Clin Microbiol Infect Dis 2021; 40: 2533–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Clinical and Laboratory Standards Institute. Performance standards for antimicrobial susceptibility testing, 31st edn. Wayne, PA, USA: Clinical and Laboratory Standards Institute, 2021. [Google Scholar]
  • 18.Wang M, Earley M, Chen L, et al. Clinical outcomes and bacterial characteristics of carbapenem-resistant Klebsiella pneumoniae complex among patients from different global regions (CRACKLE-2): a prospective cohort study. Lancet Infect Dis 2022; 22: 401–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 2018; 9: 5114. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Lalucat J, Mulet M, Gomila M, García-Valdés E. Genomics in bacterial taxonomy: impact on the genus Pseudomonas. Genes (Basel) 2020; 11: 139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Jolley KA, Maiden MCJ. BIGSdb: scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 2010; 11: 595. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Feldgarden M, Brover V, Haft DH, et al. Validating the AMRFinder Tool and Resistance Gene Database using antimicrobial resistance genotype-phenotype correlations in a collection of isolates. Antimicrob Agents Chemother 2019; 63: e00483–19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Hunt M, Mather AE, Sánchez-Busó L, et al. ARIBA: rapid antimicrobial resistance genotyping directly from sequencing reads. Microb Genom 2017; 3: e000131. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Stamatakis A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 2014; 30: 1312–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215: 403–10. [DOI] [PubMed] [Google Scholar]
  • 26.Evans SR, Rubin D, Follmann D, et al. Desirability of Outcome Ranking (DOOR) and Response Adjusted for Duration of Antibiotic Risk (RADAR). Clin Infect Dis 2015; 61: 800–06. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Charlson ME, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol 1994; 47: 1245–51. [DOI] [PubMed] [Google Scholar]
  • 28.Iovleva A, Mustapha MM, Griffith MP, et al. Carbapenem-resistant Acinetobacter baumannii in US hospitals: diversification of circulating lineages and antimicrobial resistance. mBio 2022; 13: e0275921. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Bail L, Sanches Ito CA, Stangler Arend LNV, da Silva Nogueira K, Tuon FF. Activity of imipenem-relebactam and ceftolozane-tazobactam against carbapenem-resistant Pseudomonas aeruginosa and KPC-producing Enterobacterales. Diagn Microbiol Infect Dis 2022; 102: 115568. [DOI] [PubMed] [Google Scholar]
  • 30.Livermore DM, Warner M, Mushtaq S. Activity of MK-7655 combined with imipenem against Enterobacteriaceae and Pseudomonas aeruginosa. J Antimicrob Chemother 2013; 68: 2286–90. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

1
NIHMS1878924-supplement-1.pdf (1.1MB, pdf)

Data Availability Statement

Individual deidentified participant data (and supporting documentation, data dictionaries, and protocol) that underlie the results in this Article can be made available to investigators following submission of a plan for data use, approval by the Antibacterial Resistance Leadership Group or designated entity, and execution of required institutional agreements. Provision might be contingent upon the availability of funding for data preparation and deidentification. More information can be found on the Antibacterial Resistance Leadership Group website. Sequences will be publicly available through the National Center for Biotechnology Information (accession number PRJNA824880).

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