Clinical characteristics and risk factors for septic shock in patients with pyometra: A retrospective multicenter cohort study.

BACKGROUND: Pyometra is a disease characterized by the collection of pus in the uterus. The clinical characteristics and etiology of pyometra have not been sufficiently described. In this study, we investigated the clinical characteristics, epidemiology, outcomes, and risk factors of septic shock in patients with pyometra. METHODS: Patients with pyometra admitted to one of four university-affiliated hospitals between January 2010 to August 2022 were enrolled. Pyometra cases associated with peripartum infection and surgical site infection were excluded. Clinical characteristics and outcomes of pyometra were described, and pyometra patients with or without septic shock were compared. RESULTS: A total of 192 patients was included. Twenty-eight-day all-cause mortality was 5.0%, and the 1-year recurrence rate was 6.3%. Median patient age was 77.5 years. The two most common symptoms were abdominal pain (49.0%) and vaginal discharge (47.9%). Escherichia coli (40.1%), Klebsiella pneumoniae (16.7%), and Streptococcus spp.(16.0%) were the pathogens most frequently isolated by conventional culture; those isolated from polymerase chain reaction were Mycoplasma hominis (48.0%), and Ureaplasma spp. (32.0%). In multivariable analysis, fever, uterine perforation, and dementia were associated with increased incidence of septic shock, while vaginal discharge was associated with a lower incidence of septic shock. CONCLUSIONS: Our findings suggest that pyometra is a unique gynecological infectious syndrome in post-menopausal individuals. The most common associated pathogens are similar to those involved in urinary tract infections rather than those of sexually transmitted diseases. Decreased cognitive function could delay early diagnosis of pyometra and lead to septic shock and higher mortality.

Expired Platelet Concentrate Up-Cycling: Growth Factor-Rich Bioproduct Preparation for FBS Substitute.

Due to the short storage period, large quantities of platelet concentrate (PC) are expiring. The expired PC cannot be injected into a blood vessel, but the activity of bioactive molecules, especially growth factors, is still preserved. In this paper, we organized a process to obtain a growth factor-rich bioproduct for use as a supplement in human cell culture by optimizing freezing, thawing, and sterilization conditions. Each unit of PC displayed visual differences, diverse biochemical values, and growth factor concentrations. To minimize lot-to-lot variation, we pooled a minimum of 10 PC units. The concentrations of growth factors were maximized through five freeze-thaw cycles for 12 h at -80 °C for freezing and for 5 min at 36 °C for thawing. We used a cell strainer with 40 µm pores, followed by a 0.45 µm filter and a 0.22 µm filter sequentially to sterilize the bioproduct with minimizing loss. The obtained growth factors remained stable for 4-6 h at room temperature (23 °C), 24 h at 4 °C, and 12 months at -80 °C. Cellular responses to the growth factor-rich bioproduct were tested with primary human renal proximal tubule epithelial cells. The cells exhibited a significantly increased growth rate, compared to the fetal bovine serum (FBS)-treated control group. The cells maintained their characteristic cuboidal shape, and stem cells and renal progenitor cells also preserved their genetic characteristics during culture. Therefore, the growth factor-rich bioproduct isolated from expired PC through our process can be used as a medium supplement to replace FBS in human cell culture for clinical application.

Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.

The development of new immunotherapies to treat the inflammatory mechanisms that sustain atherosclerotic cardiovascular disease (ASCVD) is urgently needed. Herein, we present a path to drug repurposing to identify immunotherapies for ASCVD. The integration of time-of-flight mass cytometry and RNA sequencing identified unique inflammatory signatures in peripheral blood mononuclear cells stimulated with ASCVD plasma. By comparing these inflammatory signatures to large-scale gene expression data from the LINCS L1000 dataset, we identified drugs that could reverse this inflammatory response. Ex vivo screens, using human samples, showed that saracatinib-a phase 2a-ready SRC and ABL inhibitor-reversed the inflammatory responses induced by ASCVD plasma. In Apoe-/- mice, saracatinib reduced atherosclerosis progression by reprogramming reparative macrophages. In a rabbit model of advanced atherosclerosis, saracatinib reduced plaque inflammation measured by [18F] fluorodeoxyglucose positron emission tomography-magnetic resonance imaging. Here we show a systems immunology-driven drug repurposing with a preclinical validation strategy to aid the development of cardiovascular immunotherapies.

Factors for mortality in patients with persistent Staphylococcus aureus bacteremia: The importance of treatment response rather than bacteremia duration.

BACKGROUND: The criteria for antibiotic failure in persistent Staphylococcus aureus bacteremia (SAB) are unclear, but treatment response and bacteremia duration are commonly used indicators of antibiotic failure. We evaluated the effects of treatment response and bacteremia duration on mortality in persistent SAB. METHODS: We retrospectively identified patients with persistent SAB in four university-affiliated hospitals between 2017 and 2021. Bacteremia duration was calculated from the first day of active antibiotic therapy, and persistent SAB was defined as bacteremia lasting for 2 or more days. Defervescence and Pitt bacteremia score (PBS) were used to evaluate treatment response at treatment day 4. The primary outcome was 30-day in-hospital mortality. Time-dependent multivariable Cox regression analysis and subgroup analysis according to methicillin resistance were performed. RESULTS: A total of 221 patients was included in the study, and the 30-day in-hospital mortality was 28.5%. There was no significant difference in bacteremia duration between survived and deceased patients. Independent factors for mortality included age, Charlson comorbidity index, initial PBS, pneumonia, and removal of the eradicable focus. PBS at treatment day 4 ≥ 3 was the strongest risk factor (adjusted hazard ratio [HR] = 4.260), but defervescence was not. Bacteremia duration was not an independent factor except for 13 days or more of methicillin-resistant SAB (adjusted HR = 1.064). CONCLUSIONS: In patients with persistent SAB, PBS at treatment day 4 was associated with 30-day in-hospital mortality rather than defervescence and bacteremia duration. The results of this study could help determine early intensified treatment strategies in persistent SAB patients.

lncHUB2: aggregated and inferred knowledge about human and mouse lncRNAs.

Long non-coding ribonucleic acids (lncRNAs) account for the largest group of non-coding RNAs. However, knowledge about their function and regulation is limited. lncHUB2 is a web server database that provides known and inferred knowledge about the function of 18 705 human and 11 274 mouse lncRNAs. lncHUB2 produces reports that contain the secondary structure fold of the lncRNA, related publications, the most correlated coding genes, the most correlated lncRNAs, a network that visualizes the most correlated genes, predicted mouse phenotypes, predicted membership in biological processes and pathways, predicted upstream transcription factor regulators, and predicted disease associations. In addition, the reports include subcellular localization information; expression across tissues, cell types, and cell lines, and predicted small molecules and CRISPR knockout (CRISPR-KO) genes prioritized based on their likelihood to up- or downregulate the expression of the lncRNA. Overall, lncHUB2 is a database with rich information about human and mouse lncRNAs and as such it can facilitate hypothesis generation for many future studies. The lncHUB2 database is available at https://maayanlab.cloud/lncHUB2. Database URL: https://maayanlab.cloud/lncHUB2.

PrismEXP: gene annotation prediction from stratified gene-gene co-expression matrices.

Background: Gene-gene co-expression correlations measured by mRNA-sequencing (RNA-seq) can be used to predict gene annotations based on the co-variance structure within these data. In our prior work, we showed that uniformly aligned RNA-seq co-expression data from thousands of diverse studies is highly predictive of both gene annotations and protein-protein interactions. However, the performance of the predictions varies depending on whether the gene annotations and interactions are cell type and tissue specific or agnostic. Tissue and cell type-specific gene-gene co-expression data can be useful for making more accurate predictions because many genes perform their functions in unique ways in different cellular contexts. However, identifying the optimal tissues and cell types to partition the global gene-gene co-expression matrix is challenging. Results: Here we introduce and validate an approach called PRediction of gene Insights from Stratified Mammalian gene co-EXPression (PrismEXP) for improved gene annotation predictions based on RNA-seq gene-gene co-expression data. Using uniformly aligned data from ARCHS4, we apply PrismEXP to predict a wide variety of gene annotations including pathway membership, Gene Ontology terms, as well as human and mouse phenotypes. Predictions made with PrismEXP outperform predictions made with the global cross-tissue co-expression correlation matrix approach on all tested domains, and training using one annotation domain can be used to predict annotations in other domains. Conclusions: By demonstrating the utility of PrismEXP predictions in multiple use cases we show how PrismEXP can be used to enhance unsupervised machine learning methods to better understand the roles of understudied genes and proteins. To make PrismEXP accessible, it is provided via a user-friendly web interface, a Python package, and an Appyter. AVAILABILITY. The PrismEXP web-based application, with pre-computed PrismEXP predictions, is available from: https://maayanlab.cloud/prismexp; PrismEXP is also available as an Appyter: https://appyters.maayanlab.cloud/PrismEXP/; and as Python package: https://github.com/maayanlab/prismexp.

The Efficacy and Safety of a Human Perirenal Adipose Tissue-Derived Stromal Vascular Fraction in an Interstitial Cystitis Rat Model.

BACKGROUND: Interstitial cystitis (IC) is a chronic and intractable disease that can severely deteriorate patients' quality of life. Recently, stem cell therapy has been introduced as a promising alternative treatment for IC in animal models. We aimed to verify the efficacy and safety of the human perirenal adipose tissue-derived stromal vascular fraction (SVF) in an IC rat model. METHODS: From eight-week-old female rats, an IC rat model was established by subcutaneous injection of 200 µg of uroplakin3A. The SVF was injected into the bladder submucosal layer of IC rats, and pain scale analysis, awakening cytometry, and histological and gene analyses of the bladder were performed. For the in vivo safety analysis, genomic DNA purification and histological analysis were also performed to check tumorigenicity and thrombus formation. RESULTS: The mean pain scores in the SVF 20 µl group were significantly lower on days 7 and 14 than those in the control group, and bladder intercontraction intervals were significantly improved in the SVF groups in a dose-dependent manner. Regeneration of the bladder epithelium, basement membrane, and lamina propria was observed in the SVF group. In the SVF groups, however, bladder fibrosis and the expression of inflammatory markers were not significantly improved compared to those in the control group. CONCLUSION: This study demonstrated that a perirenal adipose tissue-derived SVF is a promising alternative for the management of IC in terms of improving bladder pain and overactivity.

Perirenal adipose tissues as a human elastin source, and optimize the extraction process.

Elastin is very rarely repaired extracellular matrix (ECM) in physiological condition. The commercial human elastin for exogenous medical treatment is very expensive, and has a potential for disease transmission. Animal-origin elastin is relatively low price, but has concerns for xenogeneic immune responses. Considering cost and safety, we focused on the perirenal adipose tissue, donated from healthy young people via donor nephrectomy. Until now, all of the perirenal adipose tissues are discarded as a medical waste after kidney transplantation. In the present study, we applied perirenal adipose tissues as the source of human elastin, and optimized the extraction process to get high purified and quantified elastin. Through pre-processing step, the delipidated and decellularized ECM was prepared. Next, with four different elastin extraction process (acidic solvents, neutral salt, organic solvents or hot alkali method), elastin was extracted, and the concentration of amino acid between each product was compared, and bright-field/electron microscopy, Fourier transform infrared (FT-IR) spectroscopy and cytotoxicity analysis were also performed. As controls, bovine neck ligament-derived and human skin-derived elastin were used. Among the elastin extraction methods, the hot alkali insoluble product showed (1) relatively high positive area of Verhoeff's and low Masson's trichrome stain, (2) 64.24% purity, 159.29 mg/g quantity, and ∼6.37% yield in amino acid analysis, (3) ß-sheet second structure, and (4) thin fiber composed mesh-like sheet structure in SEM image. These values were higher than those of the commercial human skin elastin. When comparing hydrolyzed forms, α-elastin from hot alkali insoluble product showed enhanced cell proliferation and maintained cell properties compared to the κ-elastin. Therefore, we confirmed that the perirenal adipose tissue is an ideal source of human elastin with safety assurance, and the hot alkali process combined with pre-process seems to be the optimal method for elastin extraction with high purity and quantity.

Gpr83 Tunes Nociceptor Function, Controlling Pain.

The function of peripheral nociceptors is frequently tuned by the action of G protein-coupled receptors (GPRs) that are expressed in them, which contribute to pain alteration. Expanding new information on such GPRs and predicting their potential outcomes can help to construct new analgesic strategies based on their modulations. In this context, we attempted to present a new GPR not yet acknowledged for its pain association. Gpr83 exhibits relatively high expressions in the peripheral nervous system compared to other tissues when we mined and reconstructed Gene Expression Omnibus (GEO) metadata, which we confirmed using immunohistochemistry on murine dorsal root ganglia (DRG). When Gpr83 expression was silenced in DRG, neuronal and behavioral nociception were all downregulated. Pathologic pain in hind paw inflammation and chemotherapy-induced peripheral neuropathy were also alleviated by this Gpr83 knockdown. Dependent on exposure time, the application of a known endogenous Gpr83 ligand PEN showed differential effects on nociceptor responses in vitro. Localized PEN administration mitigated pain in vivo, probably following Gq/11-involved GPR downregulation caused by the relatively constant exposure. Collectively, this study suggests that Gpr83 action contributes to the tuning of peripheral pain sensitivity and thus indicates that Gpr83 can be among the potential GPR targets for pain modulation.

Erratum: Publisher Correction: Systems immunology-based drug repurposing framework to target inflammation in atherosclerosis.

[This corrects the article DOI: 10.1038/s44161-023-00278-y.].

Discrepancies Between Bayesian Vancomycin Models Can Affect Clinical Decisions in the Critically Ill.

Purpose: To assess the agreement in 24-hour area under the curve (AUC24) value estimates between commonly used vancomycin population pharmacokinetic models in the critically ill. Materials and Methods: Adults admitted to intensive care who received intravenous vancomycin and had a serum vancomycin concentration available were included. AUC24 values were determined using Tucuxi (revision cd7bd7a8) for dosing intervals with a vancomycin concentration using three models (Goti 2018, Colin 2019, and Thomson 2009) previously evaluated in the critically ill. AUC24 values were categorized as subtherapeutic (<400 mg·h/L), therapeutic (400-600 mg·h/L), or toxic (>600 mg·h/L), assuming a minimum inhibitory concentration of 1 mg/L. AUC24 value categorization was compared across the three models and reported as percent agreement. Results: Overall, 466 AUC24 values were estimated in 188 patients. Overall, 52%, 42%, and 47% of the AUC24 values were therapeutic for the Goti, Colin, and Thomson models, respectively. The agreement of AUC24 values between all three models was 48% (223/466), Goti-Colin 59% (193/466), Goti-Thomson 68% (318/466), and Colin-Thomson 67% (314/466). Conclusion: In critically ill patients, vancomycin AUC24 values obtained from different pharmacokinetic models are often discordant, potentially contributing to differences in dosing decisions. This highlights the importance of selecting the optimal model.

Making Common Fund data more findable: catalyzing a data ecosystem.

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs' Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs.

Anti-Metastatic Effect of Pyruvate Dehydrogenase Kinase 4 Inhibition in Bladder Cancer via the ERK, SRC, and JNK Pathways.

Bladder cancer is a common global cancer with a high percentage of metastases and high mortality rate. Thus, it is necessary to identify new biomarkers that can be helpful in diagnosis. Pyruvate dehydrogenase kinase 4 (PDK4) belongs to the PDK family and plays an important role in glucose utilization in living organisms. In the present study, we evaluated the role of PDK4 in bladder cancer and its related protein changes. First, we observed elevated PDK4 expression in high-grade bladder cancers. To screen for changes in PDK4-related proteins in bladder cancer, we performed a comparative proteomic analysis using PDK4 knockdown cells. In bladder cancer cell lines, PDK4 silencing resulted in a lower rate of cell migration and invasion. In addition, a PDK4 knockdown xenograft model showed reduced bladder cancer growth in nude mice. Based on our results, PDK4 plays a critical role in the metastasis and growth of bladder cancer cells through changes in ERK, SRC, and JNK.

Tapered catheter-based transurethral photoacoustic and ultrasonic endoscopy of the urinary system.

Early diagnosis is critical for treating bladder cancer, as this cancer is very aggressive and lethal if detected too late. To address this important clinical issue, a photoacoustic tomography (PAT)-based transabdominal imaging approach was suggested in previous reports, in which its in vivo feasibility was also demonstrated based on a small animal model. However, successful translation of this approach to real clinical settings would be challenging because the human bladder is located at a depth that far exceeds the typical penetration depth of PAT (∼3 cm for in vivo cases). In this study, we developed a tapered catheter-based, transurethral photoacoustic and ultrasonic endoscopic probe with a 2.8 mm outer diameter to investigate whether the well-known benefits of PAT can be harnessed to resolve unmet urological issues, including early diagnosis of bladder cancer. To demonstrate the in vivo imaging capability of the proposed imaging probe, we performed a rabbit model-based urinary system imaging experiment and acquired a 3D microvasculature map distributed in the wall of the urinary system, which is a first in PAT, to the best of our knowledge. We believe that the results strongly support the use of this transurethral imaging approach as a feasible strategy for addressing urological diagnosis issues.

Transforming L1000 profiles to RNA-seq-like profiles with deep learning.

The L1000 technology, a cost-effective high-throughput transcriptomics technology, has been applied to profile a collection of human cell lines for their gene expression response to > 30,000 chemical and genetic perturbations. In total, there are currently over 3 million available L1000 profiles. Such a dataset is invaluable for the discovery of drug and target candidates and for inferring mechanisms of action for small molecules. The L1000 assay only measures the mRNA expression of 978 landmark genes while 11,350 additional genes are computationally reliably inferred. The lack of full genome coverage limits knowledge discovery for half of the human protein coding genes, and the potential for integration with other transcriptomics profiling data. Here we present a Deep Learning two-step model that transforms L1000 profiles to RNA-seq-like profiles. The input to the model are the measured 978 landmark genes while the output is a vector of 23,614 RNA-seq-like gene expression profiles. The model first transforms the landmark genes into RNA-seq-like 978 gene profiles using a modified CycleGAN model applied to unpaired data. The transformed 978 RNA-seq-like landmark genes are then extrapolated into the full genome space with a fully connected neural network model. The two-step model achieves 0.914 Pearson's correlation coefficients and 1.167 root mean square errors when tested on a published paired L1000/RNA-seq dataset produced by the LINCS and GTEx programs. The processed RNA-seq-like profiles are made available for download, signature search, and gene centric reverse search with unique case studies.

Getting Started with LINCS Datasets and Tools.

The Library of Integrated Network-based Cellular Signatures (LINCS) was an NIH Common Fund program that aimed to expand our knowledge about human cellular responses to chemical, genetic, and microenvironment perturbations. Responses to perturbations were measured by transcriptomics, proteomics, cellular imaging, and other high content assays. The second phase of the LINCS program, which lasted 7 years, involved the engagement of six data and signature generation centers (DSGCs) and one data coordination and integration center (DCIC). The DSGCs and the DCIC developed several digital resources, including tools, databases, and workflows that aim to facilitate the use of the LINCS data and integrate this data with other publicly available data. The digital resources developed by the DSGCs and the DCIC can be used to gain new biological and pharmacological insights that can lead to the development of novel therapeutics. This protocol provides step-by-step instructions for processing the LINCS data into signatures, and utilizing the digital resources developed by the LINCS consortia for hypothesis generation and knowledge discovery. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Navigating L1000 tools and data in CLUE.io Basic Protocol 2: Computing signatures from the L1000 data with the CD method Basic Protocol 3: Analyzing lists of differentially expressed genes and querying them against the L1000 data with BioJupies and the Bulk RNA-seq Appyter Basic Protocol 4: Utilizing the L1000FWD resource for drug discovery Basic Protocol 5: KINOMEscan and the KINOMEscan Appyter Basic Protocol 6: LINCS P100 and GCP Proteomics Assays Basic Protocol 7: The LINCS Joint Project (LJP) Basic Protocol 8: The LINCS Data Portals and SigCom LINCS Basic Protocol 9: Creating and analyzing signatures with iLINCS.

SigCom LINCS: data and metadata search engine for a million gene expression signatures.

Millions of transcriptome samples were generated by the Library of Integrated Network-based Cellular Signatures (LINCS) program. When these data are processed into searchable signatures along with signatures extracted from Genotype-Tissue Expression (GTEx) and Gene Expression Omnibus (GEO), connections between drugs, genes, pathways and diseases can be illuminated. SigCom LINCS is a webserver that serves over a million gene expression signatures processed, analyzed, and visualized from LINCS, GTEx, and GEO. SigCom LINCS is built with Signature Commons, a cloud-agnostic skeleton Data Commons with a focus on serving searchable signatures. SigCom LINCS provides a rapid signature similarity search for mimickers and reversers given sets of up and down genes, a gene set, a single gene, or any search term. Additionally, users of SigCom LINCS can perform a metadata search to find and analyze subsets of signatures and find information about genes and drugs. SigCom LINCS is findable, accessible, interoperable, and reusable (FAIR) with metadata linked to standard ontologies and vocabularies. In addition, all the data and signatures within SigCom LINCS are available via a well-documented API. In summary, SigCom LINCS, available at https://maayanlab.cloud/sigcom-lincs, is a rich webserver resource for accelerating drug and target discovery in systems pharmacology.

Adverse Events Following Immunization Associated with the First and Second Doses of the ChAdOx1 nCoV-19 Vaccine among Healthcare Workers in Korea.

As worldwide large-scale inoculation of novel vaccines is on the way, the importance of real-world data on safety cannot be overemphasized. We aimed to investigate the adverse events following immunization (AEFIs) associated with the ChAdOx1 nCoV-19 vaccine among healthcare workers (HCWs). We investigated the systemic and local adverse events reported within seven days following the first and second doses of vaccination, using the mobile vaccine adverse events reporting system (MVAERS) developed by our hospital. The response rates were 71.8% (994/1384) and 52.9% (727/1375) after the first and second doses, respectively. The most commonly reported AEFIs were tenderness and pain at the injection site and fatigue after the first and second doses. In comparison to the first dose, the incidence and severity of AEFIs were lower following the second dose. Since the Korean government does not recommend the ChAdOx1 nCoV-19 vaccination for those under 30 years of age, with greater risk than benefit, we additionally compared the AEFIs of age groups under and above 30 years of age. The overall incidence of AEFIs was similar in both the under and over 30 age groups. In conclusion, AEFIs associated with the ChAdOx1 nCoV-19 vaccine were found to be tolerable, and AEFIs associated with the second dose were less common and severe compared to the first dose. Further safety surveillance studies on COVID-19 vaccines are required to validate our findings.

Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge.

A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ('polypharmacology'). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Difference in the Clinical Outcome of Bloodstream Infections Caused by Klebsiella aerogenes and Enterobacter cloacae Complex.

BACKGROUND: The difference in clinical outcomes between Klebsiella aerogenes (formerly Enterobacter aerogenes) bacteremia (KAB) and Enterobacter cloacae complex bacteremia (ECB) is controversial. METHODS: We compared the clinical outcomes of patients with KAB and ECB and examined the risk factors associated with mortality. We conducted a retrospective case-control study of hospitalized patients with monobacterial KAB and ECB between January 2011 and June 2020. The primary outcome measure was 30-day all-cause mortality. Multiple logistic regression and propensity-score (PS) matching were used to identify independent risk factors for mortality. The models included demographic characteristics, comorbidities, recent healthcare contact, patient status at the onset of bacteremia, and severity of infection as covariates. RESULTS: A total of 282 patients with KAB or ECB were included, among whom 194 patients were selected after PS matching. The 30-day all-cause mortality rate was higher in the ECB group than in the KAB group (24.1% vs 10.6%, P = .003). In a multivariable model, ECB was an independent risk factor for 30-day mortality in both overall and PS-matched cohorts (adjusted odds ratio, 3.528; 95% confidence interval, 1.614-7.714; P = .002). Stay in the intensive care unit at the onset of bacteremia and higher Pitt bacteremia score were found to be independent risk factors for 30-day mortality. CONCLUSIONS: In our study, mortality was significantly higher in patients with ECB than in those with KAB. Further studies are warranted to clarify the virulence mechanisms of E cloacae complex.