bluuebunny/crossref_metadata_2025_split huggingface dataset:
1216. Benchmarking Published Gene Signatures for Robust Infection Classification
Authors: Bodkin Nicholas , Ross Melissa H , Henao Ricardo , Tsalik Ephraim L 
Published: January 2021

Abstract

Background
Host gene expression has emerged as a promising diagnostic strategy to discriminate bacterial and viral infection. Multiple gene signatures of varying size and complexity have been developed in various clinical populations. However, there has been no systematic comparison of these signatures. It is also unclear how these signatures apply to different clinical populations. This meta-analysis examined 19 published signatures, validated in 49 publicly available datasets for a total of 4750 patients. The objectives were to understand how the signatures compared to each other with respect to composition and performance, and to evaluate their performance in different patient subgroups.

Methods
Signatures were characterized with respect to size, platform, and discovery population. For each of the 19 signatures, we ran leave-one-out cross-validation to generate AUCs for bacterial classification and viral classification. We then applied dataset-specific thresholds to generate accuracies, pooling patients across datasets.

Results
Signature performance varied significantly with a median AUC across all validation datasets ranging from 0.55 to 0.94 for bacterial classification and 0.79 to 0.96 for viral classification. Signature size varied (1- 341 genes) with smaller signatures generally performing more poorly for both bacterial classification (P &lt; .001) and for viral classification (P = 0.02). Viral infection was easier to diagnose than bacterial infection (85% vs. 80% overall accuracy, respectively; P &lt; .001). Host gene expression classifiers performed more poorly in children &lt; 12-years compared to those older than 12-years for both bacterial infection (77% vs. 83%, respectively; P &lt; .001) and for viral infection (82% vs. 89%, respectively; P &lt; .001). We did not observe differences based on illness severity as defined by ICU care for either bacterial or viral infections.

Conclusion
We observed significant differences among gene expression signatures for bacterial/viral discrimination, though these were not due to variations in the discovery methods or populations. Signature size directly correlated with test performance, which was generally better for the diagnosis of viral infection and in populations &gt;12-years.

Disclosures
Ephraim L. Tsalik, MD, MHS, PhD, Predigen (Shareholder, Other Financial or Material Support, Founder)
1218. Comparing the Diagnostic Accuracy of Clinician Judgement to a Novel Host Response Diagnostic for Acute Respiratory Illness
Authors: Jaffe Ian S , Jaehne Anja K , Quackenbush Eugenia , McClain Micah T , Ginsburg Geoffrey S , Woods Christopher W , Rivers Emanuel , Tsalik Ephraim L 
Published: January 2021

Abstract

Background
Discriminating bacterial and viral infections remains clinically challenging. The resulting antibacterial misuse contributes to antimicrobial resistance. Host gene expression-based tests are a promising strategy to discriminate of bacterial and viral infections, but their potential clinical utility has not yet been evaluated.

Methods
A host gene expression biosignature was measured using either qRT-PCR or microarray in 683 ED subjects with suspected infection. Based on chart reviews, we recorded clinical diagnosis as defined both by the provider assessment and by the provider treatment plan. The biosignature, diagnosis, treatment plan, and procalcitonin were compared to clinical adjudication as the reference standard. With this as a baseline, we then calculated average weighted accuracy (AWA) and change in overall net benefit (∆NB), weighting bacterial false negatives four times more seriously than false positives.

Results
Gene expression correctly classified the three possible disease etiologies (bacterial, viral, or non-infectious) 76.1% of the time, outperforming provider diagnosis, provider treatment, and procalcitonin (Table 1). Overall accuracy was higher in subjects with bacterial infections (n=278, 83.8% accurate) compared to those with viral (n=234, 76.5%) and non-infectious (n=171, 63.2%) etiologies. Due to a strong sensitivity bias to treat bacterial infections at the expense of diagnostic accuracy and specificity, the provider diagnosis was overall more accurate than the corresponding treatment plan (71.4% accuracy vs. 68.1%), resulting in inappropriate antibiotic use in 41.0% of cases where antibiotics were prescribed. The gene expression test had significantly higher AWA for the diagnosis of bacterial infection than both procalcitonin and provider treatment (82.4% vs. 70.3% and 74.4%, respectively; p &lt; 0.0001). Consequently, the host gene expression test had greater net benefit than provider treatment (∆NBbact = 9.9%), provider diagnosis (∆NBbact = 4.4%), and procalcitonin (∆NBbact = 27.1%).
Table 1: Summary of provider, procalcitonin, and host gene expression test performance in a cohort of 683 subjects.

Conclusion
Host gene expression-based tests to distinguish bacterial and viral infection can facilitate more appropriate treatment, leading to improved patient outcomes and mitigating the antibiotic resistance crisis.

Disclosures
Geoffrey S. Ginsburg, MD PhD, Predigen, Inc (Shareholder, Other Financial or Material Support) Ephraim L. Tsalik, MD, MHS, PhD, Predigen (Shareholder, Other Financial or Material Support, Founder)
1220. Disruption of the Body Temperature Circadian Rhythm in Hospitalized Patients
Authors: Geneva Ivayla I , Javaid Waleed 
Published: January 2021

Abstract

Background
The circadian rhythm is believed to offer survival advantage with dysregulation being linked to immune response deficiencies and metabolic derangements. Diurnal temperature variation exists in humans, yet its preservation during illness is not well understood. Herein we present an analysis of diurnal body temperatures among hospitalized patients, with a focus on infectious versus non-infectious diagnoses.

Methods
Temperatures measured within 1/2 hour of 8am, 12pm, 4pm, 8pm, 12 am, and 4am from 16,245 hospitalized patients were analyzed using descriptive statistics and t-tests.

Results
Although we found a diurnal pattern when analyzing the ensemble of temperatures from all patients (Figure 1), stratified by measurement site (oral, axillary, temporal, and tympanic), the through-to-peak difference was only 0.2F (0.1C), while previously reported diurnal difference in healthy volunteers was 1.9 °F (1.06 °C). Data from the core body temperature sites monotherm and rectal did not show any diurnal pattern. The peaks in body temperature occurred at 8 pm for all patients, regardless of age, which is similar to healthy people. However, the minimum body temperature was shifted to later times compared with healthy people (6am or 2 hours before rising in health) – for young patients (age 20-30 years, N=1285) the through was at 8am and for elderly patients (age 70-80 years, N=1736), it was at 12pm (Figure 2). Analysis of body temperature of individual patients showed that less than 20% of patients exhibited diurnal variation and among those showing variation, the trend was present only on the minority of hospitalization days (Table 1). Interestingly, the presence or absence of an infectious process did not influence the proportion of patients showing diurnal variation.
Figure 1

Figure 2

Table 1

Conclusion
Hospitalization is associated with disruption in the circadian rhythm as reflected by patients’ body temperature, with shifting of the diurnal variation curve and blunting of the temperature range both in the ensemble and on the individual level. The trend is not influenced by having an infection. However, since core body temperatures tend to be the measurement site of choice in the ICU setting, we suspect that further obliteration of the diurnal rhythm occurs with more severe disease.

Disclosures
All Authors: No reported disclosures
1223. Impact of Helicobacter pylori Infection on Duodenal Microbial Community Structures and Microbial Metabolic Pathways
Authors: Maeda Tadashi , zai hiroaki , Fukui Yuto , katou yoshihumi , kumade eri , watanabe toshiyasu , Furushou Norihiro , Nakajima Hitoshi , arai kazuho , Ishii Yoshikazu , tateda kazuhiro , Urita Yoshihisa 
Published: January 2021

Abstract

Background
Recent reports suggest that Helicobacter pylori infection causes extragastric diseases. However, the onset mechanisms of these diseases have not been fully elucidated, and the factors involved in the onset of these extragastric diseases remain obscure.

Methods
Forty-seven (20 male, 27 female) subjects who underwent gastric cancer screening were enrolled. Aspirated duodenal fluid samples were collected from the descending duodenum. Samples were analyzed by 16S rRNA gene amplicon sequencing to investigate whether the duodenal microbiota and microbial biofunctions were affected by H. pylori infection.

Results
Thirteen subjects were H. pylori positive while 34 were negative. We observed 1404 bacterial operational taxonomic units from 23 phyla and 253 genera. In the H. pylori positive group, we observed higher abundance of Proteobacteria and lower abundance of Actinobacteria and TM7 than in the H. pylori negative group. The abundance of 10 genera differed significantly between the H. pylori positive and negative groups. Aspects of microbiota in the H. pylori positive group were significantly influenced by 12 taxa primarily belonging to Gammaproteobacteria, compared with those in the H. pylori negative group. Microbial functional annotation collated using the Kyoto Encyclopedia of Genes and Genomes Orthology database showed that 12 microbial metabolic pathways were significantly affected by H. pylori infection.

Conclusion
1. pylori infection disrupted the normal bacterial communities in the duodenum and changed aspects of the commensal microbial functions primarily by upregulating the metabolic pathways. This may be one of the principal factors in the development of extragastric diseases.

Disclosures
All Authors: No reported disclosures
1224. Investigation of Infectious Etiologies in the Lower Respiratory Tract from Pediatric Patients with Unexpected Cardiopulmonary Deterioration using Next-Generation Sequencing
Authors: Takeuchi Suguru , Kawada Jun-ichi , Horiba Kazuhiro , yamaguchi Makoto , Okumura Toshihiko , Suzuki Takako , Torii Yuka , Kawabe Shinji , Wada Sho , Ikeyama Takanari , Ito Yoshinori 
Published: January 2021

Abstract

Background
In pediatric patients, unexpected cardiopulmonary deterioration with or without following cardiopulmonary arrest (CPA) are rare events, but can be caused by any of several etiologies, including infectious diseases. The most common cause of out-of-hospital CPA in children ≤12 years old was sudden infant death syndrome (SIDS), whereas infectious diseases were responsible for approximately 10% of the CPA cases. However, the role of infection may have been underestimated as triggers of SIDS or CPA. This study aimed to investigate the infectious etiologies in pediatric patients with unexpected cardiopulmonary deterioration using next-generation sequencing (NGS).

Methods
A total of 16 pediatric patients who were admitted to the pediatric intensive care unit with unexpected cardiopulmonary deterioration with or without following CPA were enrolled. Ten bronchoalveolar fluid (BALF) and six transtracheal aspirates (TTA) samples obtained in the acute phase were used to prepare NGS libraries. The libraries were sequenced on HiSeq and analyzed using metagenome analysis tools.

Results
In ten of 16 patients, one or more bacterial/viral pathogens were detected in the BALF or TTA specimens using NGS. Compared to the conventional culture and viral antigen test results, an additional 6 bacterial (e.g., Chlamydia trachomatis) and 4 viral pathogens (e.g., coxsackievirus A6 and human coronavirus NL63) were identified by NGS in four of ten patients in whom no causative pathogen had been identified by conventional culture and viral antigen tests. A summary of the detected pathogens is listed in Table 1. Notably, sequencing results allowed us to define genotypes for all of the detected viruses in a single NGS assay per patient. Furthermore, based on phylogenetic analysis of the VP1 region, the coxsackievirus A6 strain detected in this study belongs to lineage E2 and harbors an amino acid change (T283A), a substitution that has potential to cause severe illness.
Table 1

Conclusion
Our results suggest that viral and bacterial infection are common triggers in unexpected cardiopulmonary deterioration in pediatric patients. NGS has the potential to contribute to the clarification of the etiology of pediatric critical illness.

Disclosures
All Authors: No reported disclosures
1226. Performance of a Host Response Test for Bacterial/Viral Discrimination in Immunocompromised Patients
Authors: Mahle Rachael E , Suchindran Sunil , Henao Ricardo , Steinbrink Julie M , Burke Thomas W , McClain Micah T , Ginsburg Geoffrey S , Woods Christopher W , Tsalik Ephraim L 
Published: January 2021

Abstract

Background
Difficulty distinguishing bacterial and viral infections contributes to excess antibiotic use. A host response strategy overcomes many limitations of pathogen-based tests, but depends on a functional immune system. This approach may therefore be limited in immunocompromised (IC) hosts. Here, we evaluated a host response test in IC subjects, which has not been extensively studied in this manner.

Methods
An 81-gene signature was measured using qRT-PCR in previously enrolled IC subjects (chemotherapy, solid organ transplant, immunomodulatory agents, AIDS) with confirmed bacterial infection, viral infection, or non-infectious illness (NI). A regularized logistic regression model estimated the likelihood of bacterial, viral, and noninfectious classes. Clinical adjudication was the reference standard.

Results
A host gene expression model trained in a cohort of 136 immunocompetent subjects (43 bacterial, 41 viral, and 52 NI) had an overall accuracy of 84.6% for the diagnosis of bacterial vs. non-bacterial infection and 80.8% for viral vs. non-viral infection. The model was validated in an independent cohort of 134 IC subjects (64 bacterial, 28 viral, 42 NI). The overall accuracy was 73.9% for bacterial infection (p=0.03 vs. training cohort) and 75.4% for viral infection (p=0.27). Test utility could be improved by reporting probability ranges. For example, results divided into probability quartiles would allow the highest quartile to be used to rule in infection and the lowest to rule out infection. For IC subjects in the lowest quartile, the test had 90.1% and 96.4% sensitivity for bacterial and viral infection, respectively. For the highest quartile, the test had 91.4% and 84.0% specificity for bacterial and viral infection, respectively. The type or number of immunocompromising conditions did not impact performance.
Illness Etiology Probabilities

Conclusion
A host gene expression test discriminated bacterial, viral, and non-infectious etiologies at a lower overall accuracy in IC patients compared to immunocompetent patients, though this difference was only significant for bacterial vs non-bacterial disease. With modified interpretive criteria, a host response strategy may offer clinically useful and complementary diagnostic information for IC patients.

Disclosures
Thomas W. Burke, PhD, Predigen, Inc (Consultant) Geoffrey S. Ginsburg, MD PhD, Predigen, Inc (Shareholder, Other Financial or Material Support) Christopher W. Woods, MD, MPH, FIDSA, Predigen, Inc (Shareholder, Other Financial or Material Support) Ephraim L. Tsalik, MD, MHS, PhD, FIDSA, Predigen, Inc (Scientific Research Study Investigator, Shareholder, Other Financial or Material Support)
1228. The Role of Procalcitonin (PCT) and Lactic Acid in Febrile Neutropenic Cancer Patients in an Oncological Emergency Center
Authors: Chaftari Patrick , Chaftari Anne-Marie , Hachem Ray Y , Yeung Sai-ching , dagher Hiba , Jiang Ying , Malek Alexandre , Mulonovich Victor , Raad Issam I , Raad Issam I 
Published: January 2021

Abstract

Background
Procalcitonin (PCT) and lactic acid have emerged as biomarkers that increase in bacterial infections/sepsis and have been used in conjunction with clinical judgment to guide antibiotic administration. The Multinational Association for Supportive Care in Cancer (MASCC) risk index has been used to classify the risk for patients with neutropenic fever. However this index includes subjective elements and complex metrics that make it difficult to use in an oncological emergency center (EC). The purpose of this study is to evaluate the role of serum PCT alone and in combination with lactate to predict bloodstream infections (BSI), hospitalization and 14 days mortality in febrile neutropenic cancer patients presenting to the EC.

Methods
We conducted a retrospective study of all febrile neutropenic cancer patients who presented to our EC between April 1, 2018 and April 30, 2019 and had a serum PCT and lactic acid levels done. Fever was defined either as a documented temperature of ≥100.4 °F or a chief complaint of fever reported at home. Neutropenia was defined as an absolute neutrophil count ≤500 cells/mL.

Results
We included 550 cancer patients of which 385 (70%) had hematologic malignancies and 165 (30%) had solid tumors. A BSI was documented in 116 (21%) patients due to gram negative organisms in 66%, gram positive organisms in 30%, and both in 4%. A higher rate of mortality within 14 days of EC presentation was seen in patients whose PCT ≥ 0.25 compared to those with PCT &lt; 0.25 (5.2% vs 0.7%; p=0.002). Similarly a higher rate of BSI and a longer hospital stay was seen in patients whose PCT ≥ 0.25 compared to those with PCT &lt; 0.25. A PCT ≥ 0.25 or a lactate level &gt;2.2 had a sensitivity of 93% and a negative predictive value of 100% for a 14 day mortality. A logistic regression analysis showed an association between BSI and hematological malignancy, PCT ≥ 0.25, and lacate level &gt;2.2 mmole/L.

Conclusion
A PCT ≥ 0.25 was associated with BSI, LOS and 14 day mortality. The combination of PCT / serum lactate have a good sensitivity and high negative predictive value for BSI and mortality. Because this combination could be useful in identifying the high risk febrile patients requiring hospital admission, it will be compared to the standard but more labor intensive MASCC score index.

Disclosures
Issam I. Raad, MD, Citius (Other Financial or Material Support, Ownership interest)Cook Medical (Grant/Research Support)Inventive Protocol (Other Financial or Material Support, Ownership interest)Novel Anti-Infective Technologies (Shareholder, Other Financial or Material Support, Ownership interest)
1229. Volatile Biomarkers of Influenza Infection in the Breath
Authors: Danaher Patrick , Phillips Michael , Schmitt Peter , Richard Stephanie , Millar Gene , White Brian , Okulicz Jason , Coles Christian L , Burgess Timothy 
Published: January 2021

Abstract

Background
Annual influenza epidemics cause significant morbidity and mortality. New, emerging strains threaten to cause catastrophic pandemics. Assay of exhaled breath for volatile organic compounds (VOCs) via gas chromatography-mass spectroscopy (GC-MS) is an emerging diagnostic modality ideally suited to fill the gap in influenza diagnostics.

Methods
Patients with influenza like illness (ILI) presenting to the Troop Medical Clinic on JBSA Fort Sam Houston, TX, from 3/2017 to 3/2019 submitted a 2-minute breath sample in addition to a nasopharyngeal swab collected for polymerase chain reaction (PCR) assay for influenza virus. ILI was defined as temperature &gt; 100.40F AND respiratory symptoms like cough, sputum production, chest pain and/or sore throat. Breath VOCs were assayed with GC-MS and data were analyzed in order to identify the significant breath VOC biomarkers that discriminated between ILI patients with and without a PCR assay positive for influenza with greater than random accuracy.

Results
Demographic, clinical, PCR and breath data were available for 237 episodes of ILI. PCR was positive for influenza for 32 episodes (30 influenza A and 2 B). The median age of participants was 21 (IQR 19, 23) and 69% were male. There were no differences in age, gender, education, race, or smoking, between the influenza positive and negative groups. Likewise, there was no difference in days of limited activity or missed work, or symptoms at presentation between the groups. The algorithm achieved near maximal predictive accuracy of 78% with four biomarkers (74% sensitivity and 70% specificity). Based on their mass spectra, these biomarker VOCs were tentatively identified as 2-amino-1-propanol, 2-butanamine, n-nitro, 3-methyl-hexanal, and heptane, which are consistent with products of oxidative stress.
Figure. Accuracy, Sensitivity, and Specificity of Influenza Breath Test. Receiver operating characteristic (ROC) of the breath test (sensitivity versus 1-specificity). The accuracy of the breath test was 78%. With a cutoff point at the “shoulder” of the ROC curve, the test had 74% sensitivity and 70% specificity.

Conclusion
Our findings bolster available benchtop and clinical data suggesting that breath testing may be a useful diagnostic modality for influenza infection. The next step will be to study the predictive algorithm developed in this protocol in a blinded validation cohort. If the predictive algorithm performs well in a validation study, adaptation for its use in a portable, tabletop GC would be warranted to allow for a rapid, accurate, universal point-of-care influenza diagnostic test.

Disclosures
Michael Phillips, MD, Menssana Research, Inc (Grant/Research Support)