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BackgroundCOVID-19 has led to an unprecedented strain on health care facilities across the United States. Accurately identifying patients at an increased risk of deterioration may help hospitals manage their resources while improving the quality of patient care. Here, we present the results of an analytical model, Predicting Intensive Care Transfers and Other Unforeseen Events (PICTURE), to identify patients at high risk for imminent intensive care unit transfer, respiratory failure, or death, with the intention to improve the prediction of deterioration due to COVID-19. ObjectiveThis study aims to validate the PICTURE model’s ability to predict unexpected deterioration in general ward and COVID-19 patients, and to compare its performance with the Epic Deterioration Index (EDI), an existing model that has recently been assessed for use in patients with COVID-19. MethodsThe PICTURE model was trained and validated on a cohort of hospitalized non–COVID-19 patients using electronic health record data from 2014 to 2018. It was then applied to two holdout test sets: non–COVID-19 patients from 2019 and patients testing positive for COVID-19 in 2020. PICTURE results were aligned to EDI and NEWS scores for head-to-head comparison via area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve. We compared the models’ ability to predict an adverse event (defined as intensive care unit transfer, mechanical ventilation use, or death). Shapley values were used to provide explanations for PICTURE predictions. ResultsIn non–COVID-19 general ward patients, PICTURE achieved an AUROC of 0.819 (95% CI 0.805-0.834) per observation, compared to the EDI’s AUROC of 0.763 (95% CI 0.746-0.781; n=21,740; P

BACKGROUND: Management of localized or recurrent prostate cancer since the 1990s has been based on risk stratification using clinicopathological variables, including Gleason score, T stage (based on digital rectal exam), and prostate-specific antigen (PSA). In this study a novel prognostic test, the Decipher Prostate Genomic Classifier (GC), was used to stratify risk of prostate cancer progression in a US national database of men with prostate cancer. METHODS: Records of prostate cancer cases from participating SEER (Surveillance, Epidemiology, and End Results) program registries, diagnosed during the period from 2010 through 2018, were linked to records of testing with the GC prognostic test. Multivariable analysis was used to quantify the association between GC scores or risk groups and use of definitive local therapy after diagnosis in the GC biopsy-tested cohort and postoperative radiotherapy in the GC-tested cohort as well as adverse pathological findings after prostatectomy. RESULTS: A total of 572 545 patients were included in the analysis, of whom 8927 patients underwent GC testing. GC biopsy-tested patients were more likely to undergo active active surveillance or watchful waiting than untested patients (odds ratio [OR] =2.21, 95% confidence interval [CI] = 2.04 to 2.38, P

ObjectivesCefiderocol is a novel siderophore cephalosporin with in vitro activity against multidrug-resistant (MDR), gram-negative bacteria and intrinsic structural stability to all classes of carbapenemases. We sought to identify gene variants that could affect the mechanism of action (MOA) of cefiderocol.MethodsWe report a case of bacteremia in a liver transplant candidate with a strain of carbapenem-resistant Escherichia coli that was found to be resistant to cefiderocol despite no prior treatment with this antimicrobial agent. Using whole-genome sequencing, we characterized the genomic content of this E coli isolate and assessed for genetic variants between related strains that were found to be cefiderocol susceptible.ResultsWe identified several variants in genes with the potential to affect the mechanism of action of cefiderocol.ConclusionsThe cefiderocol resistance in the E coli isolate identified in this study is likely due to mutations in the cirA gene, an iron transporter gene.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) frequently causes hospital-acquired infections and is associated with high morbidity and mortality. CRKP can have multiple resistance mechanisms and only a few can be routinely detected by commercial molecular or phenotypic assays making surveillance for CRKP particularly challenging. In this report, we identified and characterized an unusual non-carbapenemase-producing CRKP carrying a rare plasmid-borne inducible AmpC gene, blaDHA-1 . The isolate was recovered from blood culture of a 67-year-old female presenting with sepsis post bladder surgery and ureteral stent removal. The primary isolate displayed an indeterminate susceptibility pattern for ceftriaxone by broth microdilution, but was susceptible by disk diffusion with one colony growing within the zone of inhibition. The ceftriaxone resistant colony was sub-cultured and had a minimum inhibitory concentration (MIC) of 2 ug/ml for imipenem (intermediate) and a zone size of 18 mm for ertapenem (resistant), but remained susceptible to cefepime and meropenem. Further phenotypic characterization of this sub-cultured isolate showed carbapenemase activity. Whole genome sequencing (WGS) revealed the presence of two subpopulations of a K. pneumoniae (MLST sequence type 11) from the primary blood culture isolate: one pan-susceptible to beta-lactams tested and the other resistant to the 3rd generation cephalosporins and ertapenem. WGS analysis identified the resistant K. pneumoniae harboring IncFIB(K) and IncR plasmids and the presence of plasmid-borne beta-lactam resistance genes bla OXA-1 and bla DHA-1, an inducible AmpC gene. Additional resistance genes against quinolones (aac(6')-Ib-cr, oqxA, oqB), aminoglycoside (aph(3')-Ia), sulfonamide (sul1), and tetracycline (tet(A)) were also identified. DHA-1 positive K. pneumoniae have been previously identified outside the US, particularly in Asia and Europe, but limited cases have been reported in the United States and may be underrecognized. Our study highlights the importance of using both extended phenotypic testing and WGS to identify emerging resistance mechanisms in clinical Enterobacterales isolates with unusual antimicrobial resistance patterns.

We describe a case of endogenous endophthalmitis caused by sequence type 66-K2 hypervirulent Klebsiella pneumoniae in a diabetic patient with no travel history outside the United States. Genomic analysis showed the pathogen has remained highly conserved, retaining >98% genetic similarity to the original strain described in Indonesia in 1935.

ABSTRACT Candida auris is an emerging multi-drug resistant yeast responsible for invasive infections among hospitalized patients. We described a case series of C. auris isolated in the Los Angeles area from an ongoing outbreak. Genomic analysis showed a single Clade III lineage of African origin in all 6 cases since 2019.

We describe a case of carbapenem resistant E. coli isolated from urine in an 87-year-old woman with recurrent urinary tract infections. Using whole genome sequencing (WGS), we identified the carbapenem resistance mechanism to be a combination of ompC porin loss and plasmid-mediated AmpC gene blaCMY-2 , which was not detected by routine molecular and phenotypic carbapenemase assays. Our case raises a concern for the limitation of current CRE screening tools for emerging resistance mechanisms and demonstrates the utility of WGS as a better tool for characterization of CRE in the clinical setting.

Aeromonas hydrophila resides in a variety of aquatic environments. Infections with A. hydrophila mainly occur after contact with fresh or brackish water. Nosocomial infections with A. hydrophila can also occur. A. hydrophila infections can be difficult to treat due to both intrinsic and acquired antimicrobial resistance (AMR) mechanisms. In 2018-19, we isolated multi-drug resistant (MDR) A. hyrodphila from two solid organ transplant patients with intra-abdominal infections. We aimed to characterize their AMR mechanisms and to determine their genetic relatedness to aid epidemiological investigation. We performed whole genome sequencing (WGS) using Illumina MiSeq and Nanopore MinIon on 3 A. hydrophila isolates, with one isolate from Patient A (blood) and two isolates from Patient B (abdominal and T-tube fluid, isolated 2 weeks apart). Phenotypic assays included: Broth Microdilution (BMD), Modified Hodge Test (MHT), Modified Carbapenem Inactivation Method (mCIM), and EDTA Carbapenem Inactivation Method (eCIM). Data analyses were performed using CLCbio and Geneious. AMR genomic analysis revealed that all three isolates possess chromosomally encoded genes including bla OXA-12(oxacillinase), bla cepS (AmpC), and bla cphA7(metallo-beta-lactamase). All isolates tested strongly positive by MHT and mCIM, but only Patient B's second isolate (after 2 weeks of meropenem treatment) tested positive by eCIM. More intriguingly, Patient B's first isolate (before meropenem treatment) tested falsely susceptible to carbapenems by BMD, suggesting bla cphA7 gene was not expressed constitutively. Phylogenetic analysis showed the two isolates from Patient B were highly similar with only 1 SNP difference. The isolate from Patient A only differed from Patient B's isolates by 35 and 36 SNPs, respectively, suggesting close genetic relatedness. Further epidemiological investigation is undergoing. We report the first cases of CphA-mediated carbapenem resistant A. hydrophila in the U.S. It is concerning that 1 out of 3 isolates tested falsely susceptible to carbapenems by BMD despite clear carbapenemase production shown by strongly positive MHT and mCIM. In both cases, meropenem was initially used to treat the patients. Clinicians and microbiologists in the US should be aware of the emerging MDR Aeromonas nosocomial infections and the potential false carbapenem susceptible results due to CphA-type carbapenemase, which may be induced during treatment.

PURPOSE: Patient-centered outcomes (PCOs) are pivotal in cancer treatment, as they directly reflect patients' quality of life. Although multiple studies suggest that factors affecting breast cancer–related morbidity and survival are influenced by treatment side effects and adherence to long-term treatment, such data are generally only available on a smaller scale or from a single center. The primary challenge with collecting these data is that the outcomes are captured as free text in clinical narratives written by clinicians. MATERIALS AND METHODS: Given the complexity of PCO documentation in these narratives, computerized methods are necessary to unlock the wealth of information buried in unstructured text notes that often document PCOs. Inspired by the success of large language models (LLMs), we examined the adaptability of three LLMs, GPT-2, BioGPT, and PMC-LLaMA, on PCO tasks across three institutions, Mayo Clinic, Emory University Hospital, and Stanford University. We developed an open-source framework for fine-tuning LLM that can directly extract the five different categories of PCO from the clinic notes. RESULTS: We found that these LLMs without fine-tuning (zero-shot) struggle with challenging PCO extraction tasks, displaying almost random performance, even with some task-specific examples (few-shot learning). The performance of our fine-tuned, task-specific models is notably superior compared with their non–fine-tuned LLM models. Moreover, the fine-tuned GPT-2 model has demonstrated a significantly better performance than the other two larger LLMs. CONCLUSION: Our discovery indicates that although LLMs serve as effective general-purpose models for tasks across various domains, they require fine-tuning when applied to the clinician domain. Our proposed approach has the potential to lead more efficient, adaptable models for PCO information extraction, reducing reliance on extensive computational resources while still delivering superior performance for specific tasks. New patient-centered outcome extraction pipeline for patients with breast cancer—extensive comparative analysis between LLMs, two external validations, and open-source model sharing. [ABSTRACT FROM AUTHOR]

This paper draws together elements of the academic literature on policy mobilities on the one hand, and on the 'digital turn' on the other. It argues that COVID‐19 accelerated the digitalization of everyday life asking we think through how those already existing informational infrastructures supporting the mobility of policies are continuing to evolve, as are the methods available for researching them. This has potential consequences for how cities practice policy comparison exchange, and learning and how these processes are studied. This paper sets out a three‐pronged schema to take seriously the intersection of policy mobilities and the digital. They are policy mobilities through the digital, policy mobilities produced by the digital and policy mobilities of the digital. It concludes by outlining fruitful areas for a future research agenda. [ABSTRACT FROM AUTHOR]

Relations between the US and China have deteriorated to their lowest point since their rapprochement in the 1970s. To make sense of contemporary geopolitics, our objective in this article is two-fold. First, we historically situate contemporary US-China rivalry to conceptualise the Second Cold War (SCW). We argue that in the wake of the 2008 financial crisis, both the US and China launched 'restorative' political projects that harked back to imagined pasts. These projects are mutually exclusive and animate contemporary geopolitics. Second, we conceptualise the spatial logic of great power rivalry in the Second Cold War. In contrast to the first Cold War, when great powers sought to incorporate territory into blocs, the US and China currently compete on a global scale for centrality in four interrelated networks that they anticipate will underpin hegemony in the 21st century: infrastructure (e.g. logistics and energy), digital, production and finance. We review the state of competition in each network and draw two broad conclusions: (1) this mode of competition makes it difficult for either side to conclusively 'win' the Second Cold War, and (2) many countries are likely to remain integrated with both the US and China. [ABSTRACT FROM AUTHOR]

Background/aimsThere are wide variations in colorectal cancer (CRC) incidence across the world. Historically, the highest incidence rates have been reported historically in more developed countries; however, increasing trends have been seen in developing countries. Here, we present the CRC incidence pattern in Cyprus, Israel, Jordan, and İzmir, Turkey, which are countries of the Middle East Cancer Consortium (MECC).Materials and methodsWe analyzed 2005-2010 CRC data from population-based registries and calculated crude and age standardized rates for CRC, colon and rectum subsites, and annual percent changes (APCs) for trends.ResultsThe age-adjusted incidence rates (AAIRs) for CRC were the highest in Israeli Jews (IJ) (46.7 for males and 35.5 for females), which exceeded those of the USA Surveillance, Epidemiology, and End Result (SEER) program registries. In both sexes, AAIRs in Cyprus and Israeli Arabs (IA) were close to those in SEER registries. For both sexes, AAIRs in İzmir and Jordan were substantially lower than those in other registries. Statistically significant decreasing trends over time were observed in AAIRs for both sexes in the SEER program (APCs: males, -3.24% and females, -2.54%), whereas the trends varied within the MECC registries. There were decreasing AAIR trends for males in IJ and IA and for females in Cyprus and IJ; APC for females in IJ (-4.29%) was significant. Conversely, increasing trends with the significant APCs were observed in males in İzmir (2.43%) and Jordan (7.57%).ConclusionMECC countries comprise both high- and low-risk populations for CRCs. However, increasing trends in low-risk populations have been alarming. Thus, the need for implementing tailored primary and secondary prevention programs in the region is essential.