Air dispersal of multidrug-resistant organisms including methicillin-resistant Staphylococcus aureus, carbapenem-resistant Acinetobacter baumannii, and carbapenemase-producing Enterobacterales in general wards: surveillance culture of air grilles.

BACKGROUND: The environmental surveillance of air grilles in clinical areas has not been systematically analyzed. METHODS: Samples were collected from frequently-touched items (n=529), air supply (n=295) and exhaust (n=184) grilles in six medical and eleven surgical wards for the cultures of multidrug-resistant organisms (MDROs): methicillin-resistant Staphylococcus aureus (MRSA), carbapenem-resistant Acinetobacter baumannii (CRAB), and carbapenemase-producing Enterobacterales (CPE), and isolates were selected for whole-genome analysis (WGS). The contamination rates were correlated with the colonization pressures of the respective MDROs. RESULTS: From 3-October to 21-November 2023, 9.8% (99/1008) of the samples tested positive, with MRSA (24.2%,24/99), CRAB (59.6%,59/99), and CPE (2.0%,2/99), being the only detected MDROs. The contamination rate in air exhaust grilles (26.6%,49/184) was significantly higher than in air supply grilles (5.8%,17/295;p<0.001). The contamination rate of air exhaust grilles with any MDRO in acute medical wards (73.7%,14/19) was significantly higher than in surgical wards (12.5%,4/32;p<0.001). However, there was no difference in the contamination rate of air exhaust grilles between those located inside and outside the cohort cubicles for MDROs (27.1%,13/48 vs. 28.8%,30/104;p=0.823). Nevertheless, the weekly CRAB colonization pressure showed a significant correlation with the overall environmental contamination rate (r=0.878; 95%CI:0.136-0.986;p=0.004), as well as with the contamination rate in air supply grilles (r=0.960;95%CI:0.375-0.999;p<0.001) and air exhaust grilles (r=0.850;95%CI:0.401-0.980;p=0.008). WGS demonstrated clonal relatedness of isolates collected from patients and air exhaust grilles. CONCLUSIONS: Air grilles may serve as MDRO reservoirs. Cohort nursing in open cubicles may not completely prevent MDRO transmission through air dispersal, prompting the consideration of future hospital design.

Single-cell transcriptomic analyses reveal distinct immune cell contributions to epithelial barrier dysfunction in checkpoint inhibitor colitis.

Immune checkpoint inhibitor (ICI) therapy has revolutionized oncology, but treatments are limited by immune-related adverse events, including checkpoint inhibitor colitis (irColitis). Little is understood about the pathogenic mechanisms driving irColitis, which does not readily occur in model organisms, such as mice. To define molecular drivers of irColitis, we used single-cell multi-omics to profile approximately 300,000 cells from the colon mucosa and blood of 13 patients with cancer who developed irColitis (nine on anti-PD-1 or anti-CTLA-4 monotherapy and four on dual ICI therapy; most patients had skin or lung cancer), eight controls on ICI therapy and eight healthy controls. Patients with irColitis showed expanded mucosal Tregs, ITGAEHi CD8 tissue-resident memory T cells expressing CXCL13 and Th17 gene programs and recirculating ITGB2Hi CD8 T cells. Cytotoxic GNLYHi CD4 T cells, recirculating ITGB2Hi CD8 T cells and endothelial cells expressing hypoxia gene programs were further expanded in colitis associated with anti-PD-1/CTLA-4 therapy compared to anti-PD-1 therapy. Luminal epithelial cells in patients with irColitis expressed PCSK9, PD-L1 and interferon-induced signatures associated with apoptosis, increased cell turnover and malabsorption. Together, these data suggest roles for circulating T cells and epithelial-immune crosstalk critical to PD-1/CTLA-4-dependent tolerance and barrier function and identify potential therapeutic targets for irColitis.

Gabapentin as a novel adjunct for postoperative irritability after superior cavopulmonary connection operation in children.

OBJECTIVES: Describing our institution's off-label use of gabapentin to treat irritability after superior cavopulmonary connection surgery and its impact on subsequent opiate and benzodiazepine requirements. METHODS: This is a single-center retrospective cohort study including infants who underwent superior cavopulmonary connection operation between 2011 and 2019. RESULTS: Gabapentin was administered in 74 subjects (74/323, 22.9%) during the observation period, with a median (IQR) starting dose of 5.7 (3.3, 15.0) mg/kg/day and a maximum dose of 10.7 (5.5, 23.4) mg/kg/day. Infants who underwent surgery in 2015-19 were more likely to receive gabapentin compared with those who underwent surgery in 2011-14 (p < 0.0001). Infants prescribed gabapentin were younger at surgery (137 versus 146 days, p = 0.007) and had longer chest tube durations (1.8 versus 0.9 days, p < 0.001), as well as longer postoperative intensive care (5.8 versus 3.1 days, p < 0.0001) and hospital (11.5 versus 7.0 days, p < 0.0001) lengths of stays. The year of surgery was the only predisposing factor associated with gabapentin administration in multivariate analysis. In adjusted linear regression, infants prescribed gabapentin on postoperative day 0-4 (n = 64) had reduced benzodiazepine exposure in the following 3 days (-0.29 mg/kg, 95% CI -0.52 - -0.06, p = 0.01) compared with those not prescribed gabapentin, while no difference was seen in opioid exposure (p = 0.59). CONCLUSIONS: Gabapentin was used with increasing frequency during the study period. There was a modest reduction in benzodiazepine requirements associated with gabapentin administration and no reduction in opioid requirements. A randomised controlled trial could better assess gabapentin's benefits postoperatively in children with congenital heart disease.

Updated Pseudo-seq Protocol for Transcriptome-Wide Detection of Pseudouridines.

Pseudouridine (Ψ), the most prevalent modified base in cellular RNAs, has been mapped to numerous sites not only in rRNAs, tRNAs, and snRNAs but also mRNAs. Although there have been multiple techniques to identify Ψs, due to the recent development of sequencing technologies some reagents are not compatible with the current sequencer. Here, we show the updated Pseudo-seq, a technique enabling the genome-wide identification of pseudouridylation sites with single-nucleotide precision. We provide a comprehensive description of Pseudo-seq, covering protocols for RNA isolation from human cells, library preparation, and detailed data analysis procedures. The methodology presented is easily adaptable to any cell or tissue type with high-quality mRNA isolation. It can be used for discovering novel pseudouridylation sites, thus constituting a crucial initial step toward understanding the regulation and function of this modification. Key features • Identification of Ψ sites on mRNAs. • Updated Pseudo-seq provides precise positional and quantitative information of Ψ. • Uses a more efficient library preparation with the latest, currently available materials.

Feedback Loop Failure Modes in Medical Diagnosis: How Biases Can Emerge and Be Reinforced.

BACKGROUND: Medical diagnosis in practice connects to research through continuous feedback loops: Studies of diagnosed cases shape our understanding of disease, which shapes future diagnostic practice. Without accounting for an imperfect and complex diagnostic process in which some cases are more likely to be diagnosed correctly (or diagnosed at all), the feedback loop can inadvertently exacerbate future diagnostic errors and biases. FRAMEWORK: A feedback loop failure occurs if misleading evidence about disease etiology encourages systematic errors that self-perpetuate, compromising future diagnoses and patient care. This article defines scenarios for feedback loop failure in medical diagnosis. DESIGN: Through simulated cases, we characterize how disease incidence, presentation, and risk factors can be misunderstood when observational data are summarized naive to biases arising from diagnostic error. A fourth simulation extends to a progressive disease. RESULTS: When severe cases of a disease are diagnosed more readily, less severe cases go undiagnosed, increasingly leading to underestimation of the prevalence and heterogeneity of the disease presentation. Observed differences in incidence and symptoms between demographic groups may be driven by differences in risk, presentation, the diagnostic process itself, or a combination of these. We suggested how perceptions about risk factors and representativeness may drive the likelihood of diagnosis. Differing diagnosis rates between patient groups can feed back to increasingly greater diagnostic errors and disparities in the timing of diagnosis and treatment. CONCLUSIONS: A feedback loop between past data and future medical practice may seem obviously beneficial. However, under plausible scenarios, poorly implemented feedback loops can degrade care. Direct summaries from observational data based on diagnosed individuals may be misleading, especially concerning those symptoms and risk factors that influence the diagnostic process itself. HIGHLIGHTS: Current evidence about a disease can (and should) influence the diagnostic process. A feedback loop failure may occur if biased "evidence" encourages diagnostic errors, leading to future errors in the evidence base.When diagnostic accuracy varies for mild versus severe cases or between demographic groups, incorrect conclusions about disease prevalence and presentation will result without specifically accounting for such variability.Use of demographic characteristics in the diagnostic process should be done with careful justification, in particular avoiding potential cognitive biases and overcorrection.

Increased utilization of the hybrid procedure is not associated with improved early survival for newborns with hypoplastic left heart syndrome: a single-centre experience.

OBJECTIVES: The primary objectives were to examine utilization of the Hybrid versus the Norwood procedure for patients with hypoplastic left heart syndrome or variants and the impact on hospital mortality. The Hybrid procedure was 1st used at our institution in 2004. METHODS: Review of all subjects undergoing the Norwood or Hybrid procedure between 1 January 1984 and 31 December 2022. The study period was divided into 8 eras: era 1, 1984-1988; era 2, 1989-1993; era 3, 1994-1998; era 4, 1999-2003; era 5, 2004-2008; era 6, 2009-2014; era 7, 2015-2018 and era 8, 2019-2022. The primary outcome was in-hospital mortality. Mortality rates were computed using standard binomial proportions with 95% confidence intervals. Rates across eras were compared using an ordered logistic regression model with and adjusted using the Tukey-Kramer post-hoc procedure for multiple comparisons. In the risk-modelling phase, logistic regression models were specified and tested. RESULTS: The Norwood procedure was performed in 1899 subjects, and the Hybrid procedure in 82 subjects. Use of the Hybrid procedure increased in each subsequent era, reaching 30% of subjects in era 8. After adjustment for multiple risk factors, use of the Hybrid procedure was significantly and positively associated with hospital mortality. CONCLUSIONS: Despite the increasing use of the Hybrid procedure, overall mortality for the entire cohort has plateaued. After adjustment for risk factors, use of the Hybrid procedure was significantly and positively associated with mortality compared to the Norwood procedure.

Genomic investigation of Lactococcus formosensis, Lactococcus garvieae, and Lactococcus petauri reveals differences in species distribution by human and animal sources.

Lactococcus garvieae is a fish pathogen that can cause diseases in humans and cows. Two genetically related species, Lactococcus formosensis and Lactococcus petauri, may be misidentified as L. garvieae. It is unclear if these species differ in host specificity and virulence genes. This study analyzed the genomes of 120 L. petauri, 53 L. formosensis, and 39 L. garvieae isolates from various sources. The genetic diversity and virulence gene content of these isolates were compared. The results showed that 77 isolates previously reported as L. garvieae were actually L. formosensis or L. petauri. The distribution of the three species varied across different collection sources, with L. petauri being predominant in human infections, human fecal sources, and rainbow trout, while L. formosensis was more common in bovine isolates. The genetic diversity of isolates within each species was high and similar. Using a genomic clustering method, L. petauri, L. formosensis, and L. garvieae were divided into 45, 22, and 13 clusters, respectively. Most rainbow trout and human isolates of L. petauri belonged to different clusters, while L. formosensis isolates from bovine and human sources were also segregated into separate clusters. In L. garvieae, most human isolates were grouped into three clusters that also included isolates from food or other sources. Non-metric multidimensional scaling ordination revealed the differential association of 15 virulence genes, including 14 adherence genes and a bile salt hydrolase gene, with bacterial species and certain collection sources. In conclusion, this work provides evidence of host specificity among the three species. IMPORTANCE: Lactococcus formosensis and Lactococcus petauri are two newly discovered bacteria, which are closely related to Lactococcus garvieae, a pathogen that affects farmed rainbow trout, as well as causes cow mastitis and human infections. It is unclear whether the three bacteria differ in their host preference and the presence of genes that contribute to the development of disease. This study shows that L. formosensis and L. petauri were commonly misidentified as L. garvieae. The three bacteria showed different distribution patterns across various sources. L. petauri was predominantly found in human infections and rainbow trout, while L. formosensis was more commonly detected in cow mastitis. Fifteen genes displayed a differential distribution among the three bacteria from certain sources, indicating a genetic basis for the observed host preference. This work indicates the importance of differentiating the three bacteria in diagnostic laboratories for surveillance and outbreak investigation purposes.

An outbreak of Burkholderia cepacia complex exit site infection among peritoneal dialysis patients caused by contaminated spray dressing.

Background: Wound dressing is intended to provide a physical barrier from microorganisms. Spray dressing is convenient and can be applied to wounds of various contours. In July 2020, a cluster of four Burkholderia cepacia complex (BCC) exit site infections was identified among peritoneal dialysis patients in a regional hospital in Hong Kong. In response, our hospital infection control team conducted an epidemiologic investigation. Methods: We conducted a retrospective cohort study of peritoneal dialysis patients with culture-confirmed BCC exit site infections from January 2011 to July 2020. Outbreak investigations, including case finding, molecular typing and post-outbreak surveillance, were performed. Discussion: A substantial increase in BCC exit site infections has been observed since 2013, rising from 0.23 in 2012 to 1.09 episodes per 100 patient-year in 2015, with the number of cases in the first half of 2020 already surpassing the total from 2019. The potential source had been traced to a spray dressing introduced to exit site care in December 2012. Burkholderia cepacia complex was isolated from both the unopened and in-use sprays from the same lot. Multilocus sequence typing analysis confirmed their genetic relatedness. The spray dressing was subsequently removed from exit site care. Post-outbreak surveillance over two years showed a marked and sustained decrease in BCC exit site infection. Conclusion: Water-based spray dressing can be a source of BCC causing wound infections. The use of contaminated spray dressing, especially in chronic wounds with proximity to indwelling catheters, may pose an inherent risk to patients.

The Emergence of Candida auris is Not Associated with Changes in Antifungal Prescription at Hospitals.

Purpose: This study describes the emergence of Candida auris in Hong Kong, focusing on the incidence and trends of different Candida species over time. Additionally, the study analyzes the relationship between C. auris and antifungal prescription, as well as the impact of outbreaks caused by C. auris. Patients and Methods: Data were collected from 43 public hospitals across seven healthcare networks (A to G) in Hong Kong, including Candida species culture and antifungal prescription information. Among 150,267 patients with 206,405 hospitalization episodes, 371,653 specimens tested positive for Candida species. Trends in Candida species and antifungal prescription were analyzed before (period 1: 2015 1Q to 2019 1Q) and after (period 2: 2019 2Q to 2023 2Q) the emergence of C. auris in Hong Kong. Results: Candida albicans was the most prevalent species, accounting for 57.1% (212,163/371,653) of isolations, followed by Candida glabrata (13.1%, 48,666), Candida tropicalis (9.2%, 34,261), and Candida parapsilosis (5.3%, 19,688). C. auris represented 2.0% of all Candida species isolations. Comparing period 2 to period 1, the trend of C. albicans remained stable, while C. glabrata, C. tropicalis, and C. parapsilosis demonstrated a slower increasing trend in period 2 than in period 1. Other species, including C. auris, exhibited a 1.1% faster increase in trend during period 2 compared to period 1. Network A, with the highest antifungal prescription, did not experience any outbreaks, while networks F and G had 40 hospital outbreaks due to C. auris in period 2. Throughout the study period, healthcare networks B to G had significantly lower antifungal prescription compared to network A, ranging from 54% to 78% less than that of network A. Conclusion: There is no evidence showing correlation between the emergence of C. auris and antifungal prescription in Hong Kong. Proactive infection control measures should be implemented to prevent nosocomial transmission and outbreak of C. auris.

Influence of a Large Language Model on Diagnostic Reasoning: A Randomized Clinical Vignette Study.

Importance: Diagnostic errors are common and cause significant morbidity. Large language models (LLMs) have shown promise in their performance on both multiple-choice and open-ended medical reasoning examinations, but it remains unknown whether the use of such tools improves diagnostic reasoning. Objective: To assess the impact of the GPT-4 LLM on physicians' diagnostic reasoning compared to conventional resources. Design: Multi-center, randomized clinical vignette study. Setting: The study was conducted using remote video conferencing with physicians across the country and in-person participation across multiple academic medical institutions. Participants: Resident and attending physicians with training in family medicine, internal medicine, or emergency medicine. Interventions: Participants were randomized to access GPT-4 in addition to conventional diagnostic resources or to just conventional resources. They were allocated 60 minutes to review up to six clinical vignettes adapted from established diagnostic reasoning exams. Main Outcomes and Measures: The primary outcome was diagnostic performance based on differential diagnosis accuracy, appropriateness of supporting and opposing factors, and next diagnostic evaluation steps. Secondary outcomes included time spent per case and final diagnosis. Results: 50 physicians (26 attendings, 24 residents) participated, with an average of 5.2 cases completed per participant. The median diagnostic reasoning score per case was 76.3 percent (IQR 65.8 to 86.8) for the GPT-4 group and 73.7 percent (IQR 63.2 to 84.2) for the conventional resources group, with an adjusted difference of 1.6 percentage points (95% CI -4.4 to 7.6; p=0.60). The median time spent on cases for the GPT-4 group was 519 seconds (IQR 371 to 668 seconds), compared to 565 seconds (IQR 456 to 788 seconds) for the conventional resources group, with a time difference of -82 seconds (95% CI -195 to 31; p=0.20). GPT-4 alone scored 15.5 percentage points (95% CI 1.5 to 29, p=0.03) higher than the conventional resources group. Conclusions and Relevance: In a clinical vignette-based study, the availability of GPT-4 to physicians as a diagnostic aid did not significantly improve clinical reasoning compared to conventional resources, although it may improve components of clinical reasoning such as efficiency. GPT-4 alone demonstrated higher performance than both physician groups, suggesting opportunities for further improvement in physician-AI collaboration in clinical practice.

Human lung cancer harbors spatially organized stem-immunity hubs associated with response to immunotherapy.

The organization of immune cells in human tumors is not well understood. Immunogenic tumors harbor spatially localized multicellular 'immunity hubs' defined by expression of the T cell-attracting chemokines CXCL10/CXCL11 and abundant T cells. Here, we examined immunity hubs in human pre-immunotherapy lung cancer specimens and found an association with beneficial response to PD-1 blockade. Critically, we discovered the stem-immunity hub, a subtype of immunity hub strongly associated with favorable PD-1-blockade outcome. This hub is distinct from mature tertiary lymphoid structures and is enriched for stem-like TCF7+PD-1+CD8+ T cells, activated CCR7+LAMP3+ dendritic cells and CCL19+ fibroblasts as well as chemokines that organize these cells. Within the stem-immunity hub, we find preferential interactions between CXCL10+ macrophages and TCF7-CD8+ T cells as well as between mature regulatory dendritic cells and TCF7+CD4+ and regulatory T cells. These results provide a picture of the spatial organization of the human intratumoral immune response and its relevance to patient immunotherapy outcomes.

Telemedicine for Multidisciplinary Urologic Cancer Care: A Prospective Single Institution Study.

BACKGROUND: We rapidly implemented a telemedicine Multidisciplinary Urologic Cancer Clinic (MDUCC) at the University of Washington/Seattle Cancer Care Alliance during the peak of the COVID-19 Public Health Emergency to maintain our ability to provide multidisciplinary cancer care. We report our experiences though assessment of patient-reported outcomes from our telemedicine MDUCC. METHODS: Video visits with a urologic oncologist, medical oncologist, and radiation oncologist were conducted in the same format as our in-person MDUCC. We prospectively collected patient demographic and clinical data. Patients were invited to complete a post-visit survey that assessed satisfaction, provider trust, travel time, and costs of the telemedicine visit. We estimated travel distances and times from each patient's home to our clinic. RESULTS: Among invited patients, twenty-four patients completed a survey after their telemedicine MDUCC visit. Twenty patients (83%) were at home during the visit. Most (85%) were men, Caucasian (79%), and were being seen in our Bladder Cancer MDUCC (83%). All twenty-four patients responded that they would be willing to have future appointments via telemedicine; eighteen patients (75%) strongly agreed that the encounter was high quality; 19 patients strongly agreed that they were satisfied with their visit. Patients saved an estimated average one-way travel distance of 145 miles and one-way travel time of 179 minutes to convene a telemedicine visit. CONCLUSIONS: Telemedicine MDUCCs are feasible and effective in providing access to multidisciplinary urologic cancer care. Patient satisfaction was high, and many patients were spared a substantial travel burden. Telemedicine may continue to be leveraged to improve access to multidisciplinary urologic cancer care.

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes.

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin's role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

Policy Interventions to Enhance Medical Care for People With Obesity in the United States-Challenges, Opportunities, and Future Directions.

Policy Points Health policymakers have insufficiently addressed care for people with obesity (body mass index ≥ 30 kg/m2 ) in the United States. Current federal policies targeting obesity medications reflect this unfortunate reality. We argue for a novel policy framework to increase access to effective obesity therapeutics and care, recognizing that, though prevention is critical, the epidemic proportions of obesity in the United States warrant immediate interventions to augment care. Reducing barriers to and improving the quality of existing anti-obesity medications, intensive behavioral therapy, weight management nutrition and dietary counseling, and bariatric surgery are critical. Moreover, to ensure continuity of care and patient-clinician trust, combating physician and broader weight stigma must represent a central component of any viable obesity care agenda.

Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine.

One of the major barriers to using large language models (LLMs) in medicine is the perception they use uninterpretable methods to make clinical decisions that are inherently different from the cognitive processes of clinicians. In this manuscript we develop diagnostic reasoning prompts to study whether LLMs can imitate clinical reasoning while accurately forming a diagnosis. We find that GPT-4 can be prompted to mimic the common clinical reasoning processes of clinicians without sacrificing diagnostic accuracy. This is significant because an LLM that can imitate clinical reasoning to provide an interpretable rationale offers physicians a means to evaluate whether an LLMs response is likely correct and can be trusted for patient care. Prompting methods that use diagnostic reasoning have the potential to mitigate the "black box" limitations of LLMs, bringing them one step closer to safe and effective use in medicine.

Pseudouridylation-mediated gene expression modulation.

RNA-guided pseudouridylation, a widespread post-transcriptional RNA modification, has recently gained recognition for its role in cellular processes such as pre-mRNA splicing and the modulation of premature termination codon (PTC) readthrough. This review provides insights into its mechanisms, functions, and potential therapeutic applications. It examines the mechanisms governing RNA-guided pseudouridylation, emphasizing the roles of guide RNAs and pseudouridine synthases in catalyzing uridine-to-pseudouridine conversion. A key focus is the impact of RNA-guided pseudouridylation of U2 small nuclear RNA on pre-mRNA splicing, encompassing its influence on branch site recognition and spliceosome assembly. Additionally, the review discusses the emerging role of RNA-guided pseudouridylation in regulating PTC readthrough, impacting translation termination and genetic disorders. Finally, it explores the therapeutic potential of pseudouridine modifications, offering insights into potential treatments for genetic diseases and cancer and the development of mRNA vaccine.

Single-cell atlas of the liver myeloid compartment before and after cure of chronic viral hepatitis.

BACKGROUND & AIMS: Chronic viral infections present serious public health challenges; however, direct-acting antivirals (DAAs) are now able to cure nearly all patients infected with hepatitis C virus (HCV), representing the only cure of a human chronic viral infection to date. DAAs provide a valuable opportunity to study immune pathways in the reversal of chronic immune failures in an in vivo human system. METHODS: To leverage this opportunity, we used plate-based single-cell RNA-seq to deeply profile myeloid cells from liver fine needle aspirates in patients with HCV before and after DAA treatment. We comprehensively characterised liver neutrophils, eosinophils, mast cells, conventional dendritic cells, plasmacytoid dendritic cells, classical monocytes, non-classical monocytes, and macrophages, and defined fine-grained subpopulations of several cell types. RESULTS: We discovered cell type-specific changes post-cure, including an increase in MCM7+STMN1+ proliferating CD1C+ conventional dendritic cells, which may support restoration from chronic exhaustion. We observed an expected downregulation of interferon-stimulated genes (ISGs) post-cure as well as an unexpected inverse relationship between pre-treatment viral load and post-cure ISG expression in each cell type, revealing a link between viral loads and sustained modifications of the host's immune system. We found an upregulation of PD-L1/L2 gene expression in ISG-high neutrophils and IDO1 expression in eosinophils, pinpointing cell subpopulations crucial for immune regulation. We identified three recurring gene programmes shared by multiple cell types, distilling core functions of the myeloid compartment. CONCLUSIONS: This comprehensive single-cell RNA-seq atlas of human liver myeloid cells in response to cure of chronic viral infections reveals principles of liver immunity and provides immunotherapeutic insights. CLINICAL TRIAL REGISTRATION: This study is registered at ClinicalTrials.gov (NCT02476617). IMPACT AND IMPLICATIONS: Chronic viral liver infections continue to be a major public health problem. Single-cell characterisation of liver immune cells during hepatitis C and post-cure provides unique insights into the architecture of liver immunity contributing to the resolution of the first curable chronic viral infection of humans. Multiple layers of innate immune regulation during chronic infections and persistent immune modifications after cure are revealed. Researchers and clinicians may leverage these findings to develop methods to optimise the post-cure environment for HCV and develop novel therapeutic approaches for other chronic viral infections.

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study.

BACKGROUND: Preoperative risk assessments used in clinical practice are insufficient in their ability to identify risk for postoperative mortality. Deep-learning analysis of electrocardiography can identify hidden risk markers that can help to prognosticate postoperative mortality. We aimed to develop a prognostic model that accurately predicts postoperative mortality in patients undergoing medical procedures and who had received preoperative electrocardiographic diagnostic testing. METHODS: In a derivation cohort of preoperative patients with available electrocardiograms (ECGs) from Cedars-Sinai Medical Center (Los Angeles, CA, USA) between Jan 1, 2015 and Dec 31, 2019, a deep-learning algorithm was developed to leverage waveform signals to discriminate postoperative mortality. We randomly split patients (8:1:1) into subsets for training, internal validation, and final algorithm test analyses. Model performance was assessed using area under the receiver operating characteristic curve (AUC) values in the hold-out test dataset and in two external hospital cohorts and compared with the established Revised Cardiac Risk Index (RCRI) score. The primary outcome was post-procedural mortality across three health-care systems. FINDINGS: 45 969 patients had a complete ECG waveform image available for at least one 12-lead ECG performed within the 30 days before the procedure date (59 975 inpatient procedures and 112 794 ECGs): 36 839 patients in the training dataset, 4549 in the internal validation dataset, and 4581 in the internal test dataset. In the held-out internal test cohort, the algorithm discriminates mortality with an AUC value of 0·83 (95% CI 0·79-0·87), surpassing the discrimination of the RCRI score with an AUC of 0·67 (0·61-0·72). The algorithm similarly discriminated risk for mortality in two independent US health-care systems, with AUCs of 0·79 (0·75-0·83) and 0·75 (0·74-0·76), respectively. Patients determined to be high risk by the deep-learning model had an unadjusted odds ratio (OR) of 8·83 (5·57-13·20) for postoperative mortality compared with an unadjusted OR of 2·08 (0·77-3·50) for postoperative mortality for RCRI scores of more than 2. The deep-learning algorithm performed similarly for patients undergoing cardiac surgery (AUC 0·85 [0·77-0·92]), non-cardiac surgery (AUC 0·83 [0·79-0·88]), and catheterisation or endoscopy suite procedures (AUC 0·76 [0·72-0·81]). INTERPRETATION: A deep-learning algorithm interpreting preoperative ECGs can improve discrimination of postoperative mortality. The deep-learning algorithm worked equally well for risk stratification of cardiac surgeries, non-cardiac surgeries, and catheterisation laboratory procedures, and was validated in three independent health-care systems. This algorithm can provide additional information to clinicians making the decision to perform medical procedures and stratify the risk of future complications. FUNDING: National Heart, Lung, and Blood Institute.