MultiToxPred 1.0: a novel comprehensive tool for predicting 27 classes of protein toxins using an ensemble machine learning approach.

Protein toxins are defense mechanisms and adaptations found in various organisms and microorganisms, and their use in scientific research as therapeutic candidates is gaining relevance due to their effectiveness and specificity against cellular targets. However, discovering these toxins is time-consuming and expensive. In silico tools, particularly those based on machine learning and deep learning, have emerged as valuable resources to address this challenge. Existing tools primarily focus on binary classification, determining whether a protein is a toxin or not, and occasionally identifying specific types of toxins. For the first time, we propose a novel approach capable of classifying protein toxins into 27 distinct categories based on their mode of action within cells. To accomplish this, we assessed multiple machine learning techniques and found that an ensemble model incorporating the Light Gradient Boosting Machine and Quadratic Discriminant Analysis algorithms exhibited the best performance. During the tenfold cross-validation on the training dataset, our model exhibited notable metrics: 0.840 accuracy, 0.827 F1 score, 0.836 precision, 0.840 sensitivity, and 0.989 AUC. In the testing stage, using an independent dataset, the model achieved 0.846 accuracy, 0.838 F1 score, 0.847 precision, 0.849 sensitivity, and 0.991 AUC. These results present a powerful next-generation tool called MultiToxPred 1.0, accessible through a web application. We believe that MultiToxPred 1.0 has the potential to become an indispensable resource for researchers, facilitating the efficient identification of protein toxins. By leveraging this tool, scientists can accelerate their search for these toxins and advance their understanding of their therapeutic potential.

CDKN2A-p16 Deletion and Activated KRASG12D Drive Barrett's-Like Gland Hyperplasia-Metaplasia and Synergize in the Development of Dysplasia Precancer Lesions.

BACKGROUND & AIMS: Barrett's esophagus is the precursor of esophageal dysplasia and esophageal adenocarcinoma. CDKN2A-p16 deletions were reported in 34%-74% of patients with Barrett's esophagus who progressed to dysplasia and esophageal adenocarcinoma, suggesting that p16 loss may drive neoplastic progression. KRAS activation frequently occurs in esophageal adenocarcinoma and precancer lesions. LGR5+ stem cells in the squamocolumnar-junction (SCJ) of mouse stomach contribute as Barrett's esophagus progenitors. We aimed to determine the functional effects of p16 loss and KRAS activation in Barrett's-like metaplasia and dysplasia development. METHODS: We established mouse models with conditional knockout of CDKN2A-p16 (p16KO) and/or activated KRASG12D expression targeting SCJ LGR5+ cells in interleukin 1b transgenic mice and characterized histologic alterations (mucous-gland hyperplasia/metaplasia, inflammation, and dysplasia) in mouse SCJ. Gene expression was determined by microarray, RNA sequencing, and immunohistochemistry of SCJ tissues and cultured 3-dimensional organoids. RESULTS: p16KO mice exhibited increased mucous-gland hyperplasia/metaplasia versus control mice (P = .0051). Combined p16KO+KRASG12D resulted in more frequent dysplasia and higher dysplasia scores (P = .0036), with 82% of p16KO+KRASG12D mice developing high-grade dysplasia. SCJ transcriptome analysis showed several activated pathways in p16KO versus control mice (apoptosis, tumor necrosis factor-α/nuclear factor-kB, proteasome degradation, p53 signaling, MAPK, KRAS, and G1-to-S transition). CONCLUSIONS: p16 deletion in LGR5+ cell precursors triggers increased SCJ mucous-gland hyperplasia/metaplasia. KRASG12D synergizes with p16 deletion resulting in higher grades of SCJ glandular dysplasia, mimicking Barrett's high-grade dysplasia. These genetically modified mouse models establish a functional role of p16 and activated KRAS in the progression of Barrett's-like lesions to dysplasia in mice, representing an in vivo model of esophageal adenocarcinoma precancer. Derived 3-dimensional organoid models further provide in vitro modeling opportunities of esophageal precancer stages.

Normoblastemia in COVID-19 patients is associated with more severe disease and adverse outcome.

OBJECTIVES: The clinical, pathological, and laboratory correlates of normoblastemia in COVID-19 patients have not been adequately explored. We sought to assess the frequency of normoblastemia in COVID-19, its association with other markers of disease, as well as other clinical outcomes. METHODS: All COVID-19 patients seen at our institution with at least one automated complete blood count (aCBC) evaluation from March to May 2020 were included in this retrospective cohort analysis. Results of aCBC and tests for markers of the acute phase response performed within 5 days before the first COVID-19 positive test and 14 days after the last positive test were reviewed. We also evaluated histologic features of the reticuloendothelial system of COVID-19 decedents. RESULTS: Among a total of 2501 COVID-19 patients, 715 (28.6%) were found to have normoblastemia. Patients with this abnormality had significantly higher (median, (1st quartile, 3rd quartile) WBC (15.7 (11.2, 23.1) u/L vs. 8.3 (6.2, 11.5) u/L), absolute neutrophil count (7.0 (5.1, 10.1) u/L vs. 5.1 (3.7, 7.3) u/L), immature granulocyte percentage (0.8 (0.5, 1.3)% vs. 0.5 (0.3, 0.8)%), ESR (76.0 (60.5, 100.0) mm/hr vs. 66.0 (45.0, 87.0) mm/hr), ferritin (1404.5 (645.0, 2871.0) ng/mL vs. 672.7 (313.4, 1348.0) ng/mL), INR (1.4 (1.2, 1.7) vs. 1.2 (1.1, 1.3)), D-dimer (8.2 (2.8, 20.0) ug/mL FEU vs. 1.5 (0.8, 3.7) µg/mL FEU), and IL-6 (216.6 (77.7, 315.0) pg/mL vs. 54.3 (23.2, 127.8) pg/mL) levels, and lower hemoglobin (12.5 (10.7, 14.2) g/dL vs. 13.2 (11.8, 14.6) g/dL) and absolute lymphocyte count (1.0 (0.7, 1.3) u/L vs. 1.1 (0.8, 1.5) u/L). The incidence of intubation and ventilation support (61.3% (65/106) vs. 10.5% (31/263)) and mortality rates (37.9%, 271/715 vs. 11.8%, 210/1786), were higher in normoblastemic patients. Multivariable logistic regression revealed normoblastemia to be an independent predictive biomarker of short-term mortality in COVID-19. CONCLUSION: Normoblastemia in COVID-19 is associated with markers of severe disease, extramedullary erythropoiesis, and adverse clinical outcome.

Current Status of Omics in Biological Quality Elements for Freshwater Biomonitoring.

Freshwater ecosystems have been experiencing various forms of threats, mainly since the last century. The severity of this adverse scenario presents unprecedented challenges to human health, water supply, agriculture, forestry, ecological systems, and biodiversity, among other areas. Despite the progress made in various biomonitoring techniques tailored to specific countries and biotic communities, significant constraints exist, particularly in assessing and quantifying biodiversity and its interplay with detrimental factors. Incorporating modern techniques into biomonitoring methodologies presents a challenging topic with multiple perspectives and assertions. This review aims to present a comprehensive overview of the contemporary advancements in freshwater biomonitoring, specifically by utilizing omics methodologies such as genomics, metagenomics, transcriptomics, proteomics, metabolomics, and multi-omics. The present study aims to elucidate the rationale behind the imperative need for modernization in this field. This will be achieved by presenting case studies, examining the diverse range of organisms that have been studied, and evaluating the potential benefits and drawbacks associated with the utilization of these methodologies. The utilization of advanced high-throughput bioinformatics techniques represents a sophisticated approach that necessitates a significant departure from the conventional practices of contemporary freshwater biomonitoring. The significant contributions of omics techniques in the context of biological quality elements (BQEs) and their interpretations in ecological problems are crucial for biomonitoring programs. Such contributions are primarily attributed to the previously overlooked identification of interactions between different levels of biological organization and their responses, isolated and combined, to specific critical conditions.

Biopolitics and speculative objects in Chilean health projects.

'Biopolitics' is a much-used concept in recent academic literature. One of its main fields of application is in the analysis of public health projects. This article analyses the national Explicit Health Guarantees project in Chile from that perspective. However, we criticize the standard invocation of 'biopolitics' by observing that such public health projects require technoscientific operations that establish truths and regimes of obligation for the groups involved -understanding regime both as a set of imposed orders and a set of regulated processes. Specifically, the Explicit Health Guarantees project defines what we call 'speculative objects'. These have two characteristics: (a) They relate highly diverse entities into integrated wholes that are and involve objects of knowledge and uncertainty, and (b) this integration creates regimes of obligation considered as scientific truths on many different groups. We conclude by proposing new questions about the notion of biopolitics and its relationship with uncertainty and speculation.

Development of an Accessible and Scalable Quantitative Polymerase Chain Reaction Assay for Monkeypox Virus Detection.

During the 2022 monkeypox (MPX) outbreak, testing has been limited and results delayed, allowing ongoing transmission. Gold-standard quantitative polymerase chain reaction (qPCR) diagnostics are difficult to obtain. This research adapted the June 2022 CDC MPX qPCR assay for broad implementation. Validated using MPX stocks in a matrix with multiple sample types, MPX was detected with cycle threshold (Ct) values 17.46-35.59 and titer equivalents 8.01 × 106 to 2.45 × 100 plaque-forming unit (PFU)/mL. The detection limit was 3.59 PFU/mL. Sensitivity and specificity were both 100%. This qPCR assay can be quickly and broadly implemented in research and public health laboratories to increase diagnostic capacity amid the growing MPX outbreak.

Building the Model.

CONTEXT.­: Machine learning (ML) allows for the analysis of massive quantities of high-dimensional clinical laboratory data, thereby revealing complex patterns and trends. Thus, ML can potentially improve the efficiency of clinical data interpretation and the practice of laboratory medicine. However, the risks of generating biased or unrepresentative models, which can lead to misleading clinical conclusions or overestimation of the model performance, should be recognized. OBJECTIVES.­: To discuss the major components for creating ML models, including data collection, data preprocessing, model development, and model evaluation. We also highlight many of the challenges and pitfalls in developing ML models, which could result in misleading clinical impressions or inaccurate model performance, and provide suggestions and guidance on how to circumvent these challenges. DATA SOURCES.­: The references for this review were identified through searches of the PubMed database, US Food and Drug Administration white papers and guidelines, conference abstracts, and online preprints. CONCLUSIONS.­: With the growing interest in developing and implementing ML models in clinical practice, laboratorians and clinicians need to be educated in order to collect sufficiently large and high-quality data, properly report the data set characteristics, and combine data from multiple institutions with proper normalization. They will also need to assess the reasons for missing values, determine the inclusion or exclusion of outliers, and evaluate the completeness of a data set. In addition, they require the necessary knowledge to select a suitable ML model for a specific clinical question and accurately evaluate the performance of the ML model, based on objective criteria. Domain-specific knowledge is critical in the entire workflow of developing ML models.

Sobre la producción de certidumbre en salud pública: biopolítica y objetos especulativos / On the production of certainty in public health: biopolitics and speculative objects

Resumen En este trabajo, analizamos la producción de certidumbre en una política en salud configurada desde el esquema epistémico de la medicina basada en la evidencia: el régimen de Garantías Explícitas en Salud en Chile. Con base en los estudios de ciencia y tecnología, el análisis de material producido mediante etnografías focalizadas en escenarios ministeriales, y considerando entrevistas a expertos y profesionales, exponemos cómo en estos escenarios los objetos vinculados con la evidencia llegan a servir para tres propósitos: reducir la complejidad de procesos globales, conectar lo local con lo global y, fundamentalmente, generar un nuevo continuo que vincula la verdad con la incertidumbre. Caracterizamos a estas entidades como "objetos especulativos", destacando su importante papel en la articulación de retóricas que permiten la configuración local de la biopolítica.

Abstract This article analyzes the production of certainty in a health policy shaped by the epistemic scheme of evidence-based medicine: the Regime of Explicit Health Guarantees in Chile. Based on studies on science and technology, the analysis of material produced through focused ethnographies in ministry settings, and interviews with experts and professionals, this study exposes how objects linked to the evidence serve for three purposes in these scenarios: to reduce the complexity of global processes, to connect the local with the global, and to generate a new continuum that links truth with uncertainty. These objects are characterized here as "speculative objects," highlighting their important role in the articulation of rhetoric that allows the local configuration of biopolitics.

Changes in SARS-CoV-2 viral load and mortality during the initial wave of the pandemic in New York City.

Public health interventions such as social distancing and mask wearing decrease the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it is unclear whether they decrease the viral load of infected patients and whether changes in viral load impact mortality from coronavirus disease 2019 (COVID-19). We evaluated 6923 patients with COVID-19 at six New York City hospitals from March 15-May 14, 2020, corresponding with the implementation of public health interventions in March. We assessed changes in cycle threshold (CT) values from reverse transcription-polymerase chain reaction tests and in-hospital mortality and modeled the impact of viral load on mortality. Mean CT values increased between March and May, with the proportion of patients with high viral load decreasing from 47.7% to 7.8%. In-hospital mortality increased from 14.9% in March to 28.4% in early April, and then decreased to 8.7% by May. Patients with high viral loads had increased mortality compared to those with low viral loads (adjusted odds ratio 2.34). If viral load had not declined, an estimated 69 additional deaths would have occurred (5.8% higher mortality). SARS-CoV-2 viral load steadily declined among hospitalized patients in the setting of public health interventions, and this correlated with decreases in mortality.

Pretest Symptom Duration and Cycle Threshold Values for Severe Acute Respiratory Syndrome Coronavirus 2 Reverse-Transcription Polymerase Chain Reaction Predict Coronavirus Disease 2019 Mortality.

BACKGROUND: The relationship between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and patient symptom duration in both in- and outpatients, and the impact of these factors on patient outcomes, are currently unknown. Understanding these associations is important to clinicians caring for patients with coronavirus disease 2019 (COVID-19). METHODS: We conducted an observational study between March 10 and May 30, 2020 at a large quaternary academic medical center in New York City. Patient characteristics, laboratory values, and clinical outcomes were abstracted from the electronic medical records. Of all patients tested for SARS-CoV-2 during this time (N = 16 384), there were 5467 patients with positive tests, 4254 of which had available cycle threshold (Ct) values and were included in further analysis. Univariable and multivariable logistic regression models were used to test associations between Ct values, duration of symptoms before testing, patient characteristics, and mortality. The primary outcome is defined as death or discharge to hospice. RESULTS: Lower Ct values at diagnosis (ie, higher viral load) were associated with significantly higher mortality among both in- and outpatients. It is interesting to note that patients with a shorter time since the onset of symptoms to testing had a worse prognosis, with those presenting less than 3 days from symptom onset having 2-fold increased odds of death. After adjusting for time since symptom onset and other clinical covariates, Ct values remained a strong predictor of mortality. CONCLUSIONS: Severe acute respiratory syndrome coronavirus 2 reverse-transcription polymerase chain reaction Ct value and duration of symptoms are strongly associated with mortality. These 2 factors add useful information for clinicians to risk stratify patients presenting with COVID-19.

Sociospatial ties and postdisaster reconstruction: An analysis of the assemblage in the mega-fire of Valparaíso.

Disasters affect sociospatial links in a dynamic and unstable meshwork of aspects that are reconfigured. In this sense, accounting for this complexity is central to analyze the transformation of the sociospatial linkage of the affected people and communities. Addressing from community environmental psychology, we propose the concept of assemblage to guide a situated reading of subjective, material, and community aspects present in a reconstruction process after a disaster. Following a qualitative methodology, using spatially referenced narrative interviews (n = 16) and thematic analysis, it is described how these links are presented in a community that lived the mega-fire of a part of the city of Valparaíso in Chile. The results describe that the experience of being a community is a variable flow within a process defined by an ever-emerging configuration of spatial, technological, personal, social, and sensory characteristics. We conclude by pointing out the qualities of the communities when considered from an assemblage perspective.

Machine Learning Highlights Downtrending of COVID-19 Patients with a Distinct Laboratory Profile.

Background: New York City (NYC) experienced an initial surge and gradual decline in the number of SARS-CoV-2-confirmed cases in 2020. A change in the pattern of laboratory test results in COVID-19 patients over this time has not been reported or correlated with patient outcome. Methods: We performed a retrospective study of routine laboratory and SARS-CoV-2 RT-PCR test results from 5,785 patients evaluated in a NYC hospital emergency department from March to June employing machine learning analysis. Results: A COVID-19 high-risk laboratory test result profile (COVID19-HRP), consisting of 21 routine blood tests, was identified to characterize the SARS-CoV-2 patients. Approximately half of the SARS-CoV-2 positive patients had the distinct COVID19-HRP that separated them from SARS-CoV-2 negative patients. SARS-CoV-2 patients with the COVID19-HRP had higher SARS-CoV-2 viral loads, determined by cycle threshold values from the RT-PCR, and poorer clinical outcome compared to other positive patients without the COVID12-HRP. Furthermore, the percentage of SARS-CoV-2 patients with the COVID19-HRP has significantly decreased from March/April to May/June. Notably, viral load in the SARS-CoV-2 patients declined, and their laboratory profile became less distinguishable from SARS-CoV-2 negative patients in the later phase. Conclusions: Our longitudinal analysis illustrates the temporal change of laboratory test result profile in SARS-CoV-2 patients and the COVID-19 evolvement in a US epicenter. This analysis could become an important tool in COVID-19 population disease severity tracking and prediction. In addition, this analysis may play an important role in prioritizing high-risk patients, assisting in patient triaging and optimizing the usage of resources.

Blood component utilization in COVID-19 patients in New York City: Transfusions do not follow the curve.

BACKGROUND: Blood suppliers and transfusion services have worked diligently to maintain an adequate blood supply during the COVID-19 pandemic. Our experience has shown that some COVID-19 inpatients require transfusion support; understanding this need is critical to blood product inventory management. STUDY DESIGN AND METHODS: Hospital-wide and COVID-19 specific inpatient blood product utilization data were collected retrospectively for our network's two tertiary academic medical centers over a 9-week period (March 1, 2020-May 2, 2020), when most inpatients had COVID-19. Utilization data were merged with a COVID-19 patient database to investigate clinical demographic characteristics of transfused COVID-19 inpatients relative to non-transfused ones. RESULTS: Overall, 11 041 COVID-19 patients were admitted and 364 received blood product transfusions for an overall transfusion rate of 3.3%. COVID-19 patients received 1746 blood components in total, the majority of which were red blood cells. COVID-19 patients' weekly transfusion rate increased as the pandemic progressed, possibly reflecting their increased severity of illness. Transfusion was significantly associated with several indicators of severe disease, including mortality, intubation, thrombosis, longer hospital admission, lower hemoglobin and platelet nadirs, and longer prothrombin and activated partial thromboplastin times. As the pandemic progressed, institutional adherence to transfusion guidelines improved for RBC transfusions compared to prior year trends but did not improve for platelets or plasma. CONCLUSION: There is a need to closely monitor the blood product inventory and demand throughout the COVID-19 pandemic as patients' transfusion needs may increase over time. Daily or weekly trending of patients' clinical status and laboratory values may assist blood banks in inventory management.

Interferon activation status underlies higher antibody response to viral antigens in patients with systemic lupus erythematosus receiving no or light treatment.

OBJECTIVES: Infections have been proposed as an environmental risk factor for autoimmune disease. Responses to microbial antigens may be studied in vivo during vaccination. We therefore followed patients with SLE and controls during split-virion influenza vaccination to quantify antibody responses against viral antigens and associated cellular and proteome parameters. METHODS: Blood samples and clinical data were collected from female patients with SLE with no or HCQ and/or low-dose prednisolone treatment (n = 29) and age- and sex-matched healthy controls (n = 17). Vaccine-specific antibody titres were measured by ELISA and IFN-induced gene expression in monocytes by quantitative PCR. Serum proteins were measured by proximity extension assay and disease-associated symptoms were followed by questionnaires. RESULTS: The vaccine-specific antibody response was significantly higher in patients compared with controls and titres of IgG targeting the viral proteins were higher in patients than controls at both 1 and 3 months after immunization. Clinical disease symptoms and autoantibody titres remained unchanged throughout the study. Notably, a positive pre-vaccination mRNA-based IFN score was associated with a significantly higher vaccine-specific antibody response and with a broader profile of autoantibody specificities. Screening of serum protein biomarkers revealed higher levels of IFN-regulated proteins in patients compared with controls and that levels of such proteins correlated with the vaccine-specific IgG response, with C-C motif chemokine ligand 3 exhibiting the strongest association. CONCLUSION: Augmented antibody responses to viral antigens develop in patients with SLE on no or light treatment and associate with markers of type I IFN system activation at the RNA and protein levels.

Objetos proposicionales: una política organizacional mediada por documentos / Propositional objects: an organizational policy mediated by documents

Los documentos han formado parte importante de los procesos de formalización y transforma-ción organizacional. Esto ha sido particularmente evidente en el campo de la medicina. En este trabajo analizamos las acciones que promueven documentos como las guías de práctica clínica. Realizamos etnografías focalizadas, entrevistas y análisis documental en espacios de diseño, así como también en centros de atención. Para el análisis, adoptamos la perspectiva de la teoría del actor-red. Esta aproximación nos ha permitido señalar cómo las guías inscriben relaciones que son interpretadas localmente, entablan vínculos de co-afección en tanto modifican y son modificadas por los escenarios clínicos, y participan de arreglos pragmáticos para formular de-terminados efectos. Finalmente, y adoptando elementos de la filosofía procesual de Whi-tehead, consideramos que estas pueden ser concebidas como objetos proposicionales. Estos ob-jetos recogen las potencialidades normativas de un escenario, ofrecen ocasiones para ser in-troducidos en relaciones y, asimismo, orientar su curso. (AU)

Documents have been an important part of organisational formalization and transformation. This has been particularly evident in the medical field. In this work we analyze the actions promoted by documents such as clinical practice guidelines. We carried out focused ethnogra-phies, interviews, and documentary analysis in design spaces, as well as in care centres. For the analysis, we adopted actor-network theory perspective. This approach has allowed us to point out how the guides inscribe relationships that are interpreted locally, establish co-affection links as they modify and are modified by the clinical scenarios, and participate in pragmatic arrangements to formulate clinical effects. Finally, and adopting elements of Whitehead's process philosophy, we consider that these can be conceived as propositional ob-jects. These objects collect the normative potential of a scenario, offer opportunities to be introduced into relationships and, likewise, guide its course. (AU)

SARS-CoV-2 Viral Load Predicts Mortality in Patients with and without Cancer Who Are Hospitalized with COVID-19.

Patients with cancer may be at increased risk of severe coronavirus disease 2019 (COVID-19), but the role of viral load on this risk is unknown. We measured SARS-CoV-2 viral load using cycle threshold (CT) values from reverse-transcription polymerase chain reaction assays applied to nasopharyngeal swab specimens in 100 patients with cancer and 2,914 without cancer who were admitted to three New York City hospitals. Overall, the in-hospital mortality rate was 38.8% among patients with a high viral load, 24.1% among patients with a medium viral load, and 15.3% among patients with a low viral load (p < 0.001). Similar findings were observed in patients with cancer (high, 45.2% mortality; medium, 28.0%; low, 12.1%; p = 0.008). Patients with hematologic malignancies had higher median viral loads (CT = 25.0) than patients without cancer (CT = 29.2; p = 0.0039). SARS-CoV-2 viral load results may offer vital prognostic information for patients with and without cancer who are hospitalized with COVID-19.

Clinical Performance of SARS-CoV-2 Molecular Tests.

Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the clinical performance of these tests is still poorly understood, particularly with regard to disease course, patient-specific factors, and viral shedding. From 10 March to 1 May 2020, NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed for 3,432 patients, of which 2,413 had initial negative and 802 had initial positive results. Repeat-tested patients were more likely to have severe disease and low viral loads. The negative predictive value of the first-day result among repeat-tested patients was 81.3% The clinical sensitivity of SARS-CoV-2 molecular assays was estimated between 58% and 96%, depending on the unknown number of false-negative results in single-tested patients. Conversion to negative was unlikely to occur before 15 to 20 days after initial testing or 20 to 30 days after the onset of symptoms, with 50% conversion occurring at 28 days after initial testing. Conversion from first-day negative to positive results increased linearly with each day of testing, reaching 25% probability in 20 days. Sixty patients fluctuated between positive and negative results over several weeks, suggesting that caution is needed when single-test results are acted upon. In summary, our study provides estimates of the clinical performance of SARS-CoV-2 molecular assays and suggests time frames for appropriate repeat testing, namely, 15 to 20 days after a positive test and the same day or next 2 days after a negative test for patients with high suspicion for COVID-19.

Bacteremia and Blood Culture Utilization during COVID-19 Surge in New York City.

A surge of patients with coronavirus disease 2019 (COVID-19) presenting to New York City hospitals in March 2020 led to a sharp increase in blood culture utilization, which overwhelmed the capacity of automated blood culture instruments. We sought to evaluate the utilization and diagnostic yield of blood cultures during the COVID-19 pandemic to determine prevalence and common etiologies of bacteremia and to inform a diagnostic approach to relieve blood culture overutilization. We performed a retrospective cohort analysis of 88,201 blood cultures from 28,011 patients at a multicenter network of hospitals within New York City to evaluate order volume, positivity rate, time to positivity, and etiologies of positive cultures in COVID-19. Ordering volume increased by 34.8% in the second half of March 2020 compared to the level in the first half of the month. The rate of bacteremia was significantly lower among COVID-19 patients (3.8%) than among COVID-19-negative patients (8.0%) and those not tested (7.1%) (P < 0.001). COVID-19 patients had a high proportion of organisms reflective of commensal skin microbiota, which, when excluded, reduced the bacteremia rate to 1.6%. More than 98% of all positive cultures were detected within 4 days of incubation. Bloodstream infections are very rare for COVID-19 patients, which supports the judicious use of blood cultures in the absence of compelling evidence for bacterial coinfection. Clear communication with ordering providers is necessary to prevent overutilization of blood cultures during patient surges, and laboratories should consider shortening the incubation period from 5 days to 4 days, if necessary, to free additional capacity.