COVID-19 Hospitalization in Hawai'i and Patterns of Insurance Coverage, Race and Ethnicity, and Vaccination.

Importance: The people of Hawai'i have both high rates of health insurance and high levels of racial and ethnic diversity, but the degree to which insurance status and race and ethnicity contribute to health outcomes in COVID-19 remains unknown. Objective: To evaluate the associations of insurance coverage, race and ethnicity (using disaggregated race and ethnicity data), and vaccination with outcomes for COVID-19 hospitalization. Design, Setting, and Participants: This retrospective cohort study included hospitalized patients at a tertiary care medical center between March 2020 and March 2022. All patients hospitalized for acute COVID-19, identified based on diagnosis code or positive results on polymerase chain reaction-based assay for SARS-CoV-2, were included in analysis. Data were analyzed from May 2022 to May 2023. Exposure: COVID-19 requiring hospitalization. Main Outcome and Measures: Electronic medical record data were collected for all patients. Associations among race and ethnicity, insurance coverage, receipt of at least 1 COVID-19 vaccine, intensive care unit (ICU) transfer, in-hospital mortality, and COVID-19 variant wave (pre-Delta vs Delta and Omicron) were assessed using adjusted multivariable logistic regression. Results: A total of 1176 patients (median [IQR] age of 58 [41-71] years; 630 [54%] male) were hospitalized with COVID-19, with a median (IQR) body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) of 30 (25-36) and Sequential Organ Failure Assessment score of 1 (0-2). The sample included 16 American Indian or Alaska Native patients, 439 Asian (not otherwise specified) patients, 15 Black patients, 66 Chinese patients, 246 Filipino patients, 76 Hispanic patients, 107 Japanese patients, 10 Korean patients, 299 Native Hawaiian patients, 523 Pacific Islander (not otherwise specified) patients, 156 Samoan patients, 5 Vietnamese patients, and 311 White patients (patients were able to identify as >1 race or ethnicity). When adjusting for age, BMI, sex, medical comorbidities, and socioeconomic neighborhood status, there were no differences in either ICU transfer (eg, Medicare vs commercial insurance: odds ratio [OR], 0.84; 95% CI, 0.43-1.64) or in-hospital mortality (eg, Medicare vs commercial insurance: OR, 0.85; 95% CI, 0.36-2.03) as a function of insurance type. Disaggregation of race and ethnicity revealed that Filipino patients were more likely to die in the hospital (OR, 1.79; 95% CI, 1.04-3.03; P = .03). When considering variant waves, mortality among Filipino patients was highest during the pre-Delta time period (OR, 2.72; 95% CI, 1.02-7.14; P = .04), when mortality among Japanese patients was lowest (OR, 0.19; 95% CI, 0.03-0.78; P = .04); mortality among Native Hawaiian patients was lowest during the Delta and Omicron period (OR, 0.35; 95% CI, 0.13-0.79; P = .02). Patients with Medicare, compared with those with commercial insurance, were more likely to have received at least 1 COVID-19 vaccine (OR, 1.85; 95% CI, 1.07-3.21; P = .03), but all patients, regardless of insurance type, who received at least 1 COVID-19 vaccine had reduced ICU admission (OR, 0.40; 95% CI, 0.21-0.70; P = .002) and in-hospital mortality (OR, 0.42; 95% CI, 0.21-0.79; P = .01). Conclusions and Relevance: In this cohort study of hospitalized patients with COVID-19, those with government-funded insurance coverage (Medicare or Medicaid) had similar outcomes compared with patients with commercial insurance, regardless of race or ethnicity. Disaggregation of race and ethnicity analysis revealed substantial outcome disparities and suggests opportunities for further study of the drivers underlying such disparities. Additionally, these findings illustrate that vaccination remains a critical tool to protect patients from COVID-19 mortality.

Using Trajectories of Bedside Vital Signs to Identify COVID-19 Subphenotypes.

BACKGROUND: Trajectories of bedside vital signs have been used to identify sepsis subphenotypes with distinct outcomes and treatment responses. The objective of this study was to validate the vitals trajectory model in a multicenter cohort of patients hospitalized with COVID-19 and to evaluate the clinical characteristics and outcomes of the resulting subphenotypes. RESEARCH QUESTION: Can the trajectory of routine bedside vital signs identify COVID-19 subphenotypes with distinct clinical characteristics and outcomes? STUDY DESIGN AND METHODS: The study included adult patients admitted with COVID-19 to four academic hospitals in the Emory Healthcare system between March 1, 2020, and May 31, 2022. Using a validated group-based trajectory model, we classified patients into previously defined vital sign trajectories using oral temperature, heart rate, respiratory rate, and systolic and diastolic BP measured in the first 8 h of hospitalization. Clinical characteristics, biomarkers, and outcomes were compared between subphenotypes. Heterogeneity of treatment effect to tocilizumab was evaluated. RESULTS: The 7,065 patients with hospitalized COVID-19 were classified into four subphenotypes: group A (n = 1,429, 20%)-high temperature, heart rate, respiratory rate, and hypotensive; group B (1,454, 21%)-high temperature, heart rate, respiratory rate, and hypertensive; group C (2,996, 42%)-low temperature, heart rate, respiratory rate, and normotensive; and group D (1,186, 17%)-low temperature, heart rate, respiratory rate, and hypotensive. Groups A and D had higher ORs of mechanical ventilation, vasopressors, and 30-day inpatient mortality (P < .001). On comparing patients receiving tocilizumab (n = 55) with those who met criteria for tocilizumab but were admitted before its use (n = 461), there was significant heterogeneity of treatment effect across subphenotypes in the association of tocilizumab with 30-day mortality (P = .001). INTERPRETATION: By using bedside vital signs available in even low-resource settings, we found novel subphenotypes associated with distinct manifestations of COVID-19, which could lead to preemptive and targeted treatments.

Identification of Clinically Significant Cytokine Signature Clusters in Patients With Septic Shock.

OBJECTIVES: To identify cytokine signature clusters in patients with septic shock. DESIGN: Prospective observational cohort study. SETTING: Single academic center in the United States. PATIENTS: Adult (≥ 18 yr old) patients admitted to the medical ICU with septic shock requiring vasoactive medication support. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: One hundred fourteen patients with septic shock completed cytokine measurement at time of enrollment (t 1 ) and 24 hours later (t 2 ). Unsupervised random forest analysis of the change in cytokines over time, defined as delta (t 2 -t 1 ), identified three clusters with distinct cytokine profiles. Patients in cluster 1 had the lowest initial levels of circulating cytokines that decreased over time. Patients in cluster 2 and cluster 3 had higher initial levels that decreased over time in cluster 2 and increased in cluster 3. Patients in clusters 2 and 3 had higher mortality compared with cluster 1 (clusters 1-3: 11% vs 31%; odds ratio [OR], 3.56 [1.10-14.23] vs 54% OR, 9.23 [2.89-37.22]). Cluster 3 was independently associated with in-hospital mortality (hazard ratio, 5.24; p = 0.005) in multivariable analysis. There were no significant differences in initial clinical severity scoring or steroid use between the clusters. Analysis of either t 1 or t 2 cytokine measurements alone or in combination did not reveal clusters with clear clinical significance. CONCLUSIONS: Longitudinal measurement of cytokine profiles at initiation of vasoactive medications and 24 hours later revealed three distinct cytokine signature clusters that correlated with clinical outcomes.

Analysis of Protein Biomarkers From Hospitalized COVID-19 Patients Reveals Severity-Specific Signatures and Two Distinct Latent Profiles With Differential Responses to Corticosteroids.

OBJECTIVES: To identify and validate novel COVID-19 subphenotypes with potential heterogenous treatment effects (HTEs) using electronic health record (EHR) data and 33 unique biomarkers. DESIGN: Retrospective cohort study of adults presenting for acute care, with analysis of biomarkers from residual blood collected during routine clinical care. Latent profile analysis (LPA) of biomarker and EHR data identified subphenotypes of COVID-19 inpatients, which were validated using a separate cohort of patients. HTE for glucocorticoid use among subphenotypes was evaluated using both an adjusted logistic regression model and propensity matching analysis for in-hospital mortality. SETTING: Emergency departments from four medical centers. PATIENTS: Patients diagnosed with COVID-19 based on International Classification of Diseases , 10th Revision codes and laboratory test results. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Biomarker levels generally paralleled illness severity, with higher levels among more severely ill patients. LPA of 522 COVID-19 inpatients from three sites identified two profiles: profile 1 ( n = 332), with higher levels of albumin and bicarbonate, and profile 2 ( n = 190), with higher inflammatory markers. Profile 2 patients had higher median length of stay (7.4 vs 4.1 d; p < 0.001) and in-hospital mortality compared with profile 1 patients (25.8% vs 4.8%; p < 0.001). These were validated in a separate, single-site cohort ( n = 192), which demonstrated similar outcome differences. HTE was observed ( p = 0.03), with glucocorticoid treatment associated with increased mortality for profile 1 patients (odds ratio = 4.54). CONCLUSIONS: In this multicenter study combining EHR data with research biomarker analysis of patients with COVID-19, we identified novel profiles with divergent clinical outcomes and differential treatment responses.

Comparison of time series clustering methods for identifying novel subphenotypes of patients with infection.

OBJECTIVE: Severe infection can lead to organ dysfunction and sepsis. Identifying subphenotypes of infected patients is essential for personalized management. It is unknown how different time series clustering algorithms compare in identifying these subphenotypes. MATERIALS AND METHODS: Patients with suspected infection admitted between 2014 and 2019 to 4 hospitals in Emory healthcare were included, split into separate training and validation cohorts. Dynamic time warping (DTW) was applied to vital signs from the first 8 h of hospitalization, and hierarchical clustering (DTW-HC) and partition around medoids (DTW-PAM) were used to cluster patients into subphenotypes. DTW-HC, DTW-PAM, and a previously published group-based trajectory model (GBTM) were evaluated for agreement in subphenotype clusters, trajectory patterns, and subphenotype associations with clinical outcomes and treatment responses. RESULTS: There were 12 473 patients in training and 8256 patients in validation cohorts. DTW-HC, DTW-PAM, and GBTM models resulted in 4 consistent vitals trajectory patterns with significant agreement in clustering (71-80% agreement, P < .001): group A was hyperthermic, tachycardic, tachypneic, and hypotensive. Group B was hyperthermic, tachycardic, tachypneic, and hypertensive. Groups C and D had lower temperatures, heart rates, and respiratory rates, with group C normotensive and group D hypotensive. Group A had higher odds ratio of 30-day inpatient mortality (P < .01) and group D had significant mortality benefit from balanced crystalloids compared to saline (P < .01) in all 3 models. DISCUSSION: DTW- and GBTM-based clustering algorithms applied to vital signs in infected patients identified consistent subphenotypes with distinct clinical outcomes and treatment responses. CONCLUSION: Time series clustering with distinct computational approaches demonstrate similar performance and significant agreement in the resulting subphenotypes.

Development and validation of novel sepsis subphenotypes using trajectories of vital signs.

PURPOSE: Sepsis is a heterogeneous syndrome and identification of sub-phenotypes is essential. This study used trajectories of vital signs to develop and validate sub-phenotypes and investigated the interaction of sub-phenotypes with treatment using randomized controlled trial data. METHODS: All patients with suspected infection admitted to four academic hospitals in Emory Healthcare between 2014-2017 (training cohort) and 2018-2019 (validation cohort) were included. Group-based trajectory modeling was applied to vital signs from the first 8 h of hospitalization to develop and validate vitals trajectory sub-phenotypes. The associations between sub-phenotypes and outcomes were evaluated in patients with sepsis. The interaction between sub-phenotype and treatment with balanced crystalloids versus saline was tested in a secondary analysis of SMART (Isotonic Solutions and Major Adverse Renal Events Trial). RESULTS: There were 12,473 patients with suspected infection in training and 8256 patients in validation cohorts, and 4 vitals trajectory sub-phenotypes were found. Group A (N = 3483, 28%) were hyperthermic, tachycardic, tachypneic, and hypotensive. Group B (N = 1578, 13%) were hyperthermic, tachycardic, tachypneic (not as pronounced as Group A) and hypertensive. Groups C (N = 4044, 32%) and D (N = 3368, 27%) had lower temperatures, heart rates, and respiratory rates, with Group C normotensive and Group D hypotensive. In the 6,919 patients with sepsis, Groups A and B were younger while Groups C and D were older. Group A had the lowest prevalence of congestive heart failure, hypertension, diabetes mellitus, and chronic kidney disease, while Group B had the highest prevalence. Groups A and D had the highest vasopressor use (p < 0.001 for all analyses above). In logistic regression, 30-day mortality was significantly higher in Groups A and D (p < 0.001 and p = 0.03, respectively). In the SMART trial, sub-phenotype significantly modified treatment effect (p = 0.03). Group D had significantly lower odds of mortality with balanced crystalloids compared to saline (odds ratio (OR) 0.39, 95% confidence interval (CI) 0.23-0.67, p < 0.001). CONCLUSION: Sepsis sub-phenotypes based on vital sign trajectory were consistent across cohorts, had distinct outcomes, and different responses to treatment with balanced crystalloids versus saline.

Chronic Lymphocytic Leukemia With Leptomeningeal Involvement Presenting as an Acute Encephalopathy.

Introduction Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in Western countries. Extramedullary involvement in the central nervous system (CNS) is a rare complication of the disease, and less than 200 cases have been reported. We report a case of leptomeningeal involvement of CLL that presented as an acute encephalopathy. Case presentation A 76-year-old man with treatment-naïve, Rai stage 0 CLL presented with altered mental status. Cerebrospinal-fluid studies, including flow cytometry, confirmed the leptomeningeal involvement of the previously diagnosed CLL. Surveillance imaging and lab studies showed no evidence of disease progression or Richter's transformation. One-time intrathecal methotrexate resulted in transient improvement of his mental status. Conclusion CLL patients with new-onset neurologic manifestations should be evaluated for the CNS involvement of the neoplasm via brain imaging and cerebrospinal-fluid flow cytometry. This CNS involvement of CLL is associated with poor clinical outcomes. Intrathecal treatment with methotrexate, cytarabine, and steroid may improve neurologic symptoms.

Coronavirus Disease 2019 Temperature Trajectories Correlate With Hyperinflammatory and Hypercoagulable Subphenotypes.

OBJECTIVES: Body temperature trajectories of infected patients are associated with specific immune profiles and survival. We determined the association between temperature trajectories and distinct manifestations of coronavirus disease 2019. DESIGN: Retrospective observational study. SETTING: Four hospitals within an academic healthcare system from March 2020 to February 2021. PATIENTS: All adult patients hospitalized with coronavirus disease 2019. INTERVENTIONS: Using a validated group-based trajectory model, we classified patients into four previously defined temperature trajectory subphenotypes using oral temperature measurements from the first 72 hours of hospitalization. Clinical characteristics, biomarkers, and outcomes were compared between subphenotypes. MEASUREMENTS AND MAIN RESULTS: The 5,903 hospitalized coronavirus disease 2019 patients were classified into four subphenotypes: hyperthermic slow resolvers (n = 1,452, 25%), hyperthermic fast resolvers (1,469, 25%), normothermics (2,126, 36%), and hypothermics (856, 15%). Hypothermics had abnormal coagulation markers, with the highest d-dimer and fibrin monomers (p < 0.001) and the highest prevalence of cerebrovascular accidents (10%, p = 0.001). The prevalence of venous thromboembolism was significantly different between subphenotypes (p = 0.005), with the highest rate in hypothermics (8.5%) and lowest in hyperthermic slow resolvers (5.1%). Hyperthermic slow resolvers had abnormal inflammatory markers, with the highest C-reactive protein, ferritin, and interleukin-6 (p < 0.001). Hyperthermic slow resolvers had increased odds of mechanical ventilation, vasopressors, and 30-day inpatient mortality (odds ratio, 1.58; 95% CI, 1.13-2.19) compared with hyperthermic fast resolvers. Over the course of the pandemic, we observed a drastic decrease in the prevalence of hyperthermic slow resolvers, from representing 53% of admissions in March 2020 to less than 15% by 2021. We found that dexamethasone use was associated with significant reduction in probability of hyperthermic slow resolvers membership (27% reduction; 95% CI, 23-31%; p < 0.001). CONCLUSIONS: Hypothermics had abnormal coagulation markers, suggesting a hypercoagulable subphenotype. Hyperthermic slow resolvers had elevated inflammatory markers and the highest odds of mortality, suggesting a hyperinflammatory subphenotype. Future work should investigate whether temperature subphenotypes benefit from targeted antithrombotic and anti-inflammatory strategies.

Preventing Home Medication Administration Errors.

Medication administration errors that take place in the home are common, especially when liquid preparations are used and complex medication schedules with multiple medications are involved; children with chronic conditions are disproportionately affected. Parents and other caregivers with low health literacy and/or limited English proficiency are at higher risk for making errors in administering medications to children in their care. Recommended strategies to reduce home medication errors relate to provider prescribing practices; health literacy-informed verbal counseling strategies (eg, teachback and showback) and written patient education materials (eg, pictographic information) for patients and/or caregivers across settings (inpatient, outpatient, emergency care, pharmacy); dosing-tool provision for liquid medication measurement; review of medication lists with patients and/or caregivers (medication reconciliation) that includes prescription and over-the-counter medications, as well as vitamins and supplements; leveraging the medical home; engaging adolescents and their adult caregivers; training of providers; safe disposal of medications; regulations related to medication dosing tools, labeling, packaging, and informational materials; use of electronic health records and other technologies; and research to identify novel ways to support safe home medication administration.

Severe Acute Respiratory Syndrome-Associated Coronavirus 2 Infection and Organ Dysfunction in the ICU: Opportunities for Translational Research.

OBJECTIVES: Since the beginning of the coronavirus disease 2019 pandemic, hundreds of thousands of patients have been treated in ICUs across the globe. The severe acute respiratory syndrome-associated coronavirus 2 virus enters cells via the angiotensin-converting enzyme 2 receptor and activates several distinct inflammatory pathways, resulting in hematologic abnormalities and dysfunction in respiratory, cardiac, gastrointestinal renal, endocrine, dermatologic, and neurologic systems. This review summarizes the current state of research in coronavirus disease 2019 pathophysiology within the context of potential organ-based disease mechanisms and opportunities for translational research. DATA SOURCES: Investigators from the Research Section of the Society of Critical Care Medicine were selected based on expertise in specific organ systems and research focus. Data were obtained from searches conducted in Medline via the PubMed portal, Directory of Open Access Journals, Excerpta Medica database, Latin American and Caribbean Health Sciences Literature, and Web of Science from an initial search from December 2019 to October 15, 2020, with a revised search to February 3, 2021. The medRxiv, Research Square, and clinical trial registries preprint servers also were searched to limit publication bias. STUDY SELECTION: Content experts selected studies that included mechanism-based relevance to the severe acute respiratory syndrome-associated coronavirus 2 virus or coronavirus disease 2019 disease. DATA EXTRACTION: Not applicable. DATA SYNTHESIS: Not applicable. CONCLUSIONS: Efforts to improve the care of critically ill coronavirus disease 2019 patients should be centered on understanding how severe acute respiratory syndrome-associated coronavirus 2 infection affects organ function. This review articulates specific targets for further research.

IL-33-mediated Eosinophilia Protects against Acute Lung Injury.

Pneumonia-induced lung injury and acute respiratory distress syndrome can develop because of an inappropriate inflammatory response to acute infections, leading to a compromised alveolar barrier. Recent work suggests that hospitalized patients with allergies/asthma are less likely to die of pulmonary infections and that there is a correlation between survival from acute respiratory distress syndrome and higher eosinophil counts; thus, we hypothesized that eosinophils associated with a type 2 immune response may protect against pneumonia-induced acute lung injury. To test this hypothesis, mice were treated with the type 2-initiating cytokine IL-33 intratracheally 3 days before induction of pneumonia with airway administration of a lethal dose of Staphylococcus aureus. Interestingly, IL-33 pretreatment promoted survival by inhibiting acute lung injury: amount of BAL fluid proinflammatory cytokines and pulmonary edema were both reduced, with an associated increase in oxygen saturation. Pulmonary neutrophilia was also reduced, whereas eosinophilia was strongly increased. This eosinophilia was key to protection; eosinophil reduction eliminated both IL-33-mediated protection against mortality and inhibition of neutrophilia and pulmonary edema. Together, these data reveal a novel role for eosinophils in protection against lung injury and suggest that modulation of pulmonary type 2 immunity may represent a novel therapeutic strategy.

Temperature Trajectory Subphenotypes Correlate With Immune Responses in Patients With Sepsis.

OBJECTIVES: We recently found that distinct body temperature trajectories of infected patients correlated with survival. Understanding the relationship between the temperature trajectories and the host immune response to infection could allow us to immunophenotype patients at the bedside using temperature. The objective was to identify whether temperature trajectories have consistent associations with specific cytokine responses in two distinct cohorts of infected patients. DESIGN: Prospective observational study. SETTING: Large academic medical center between 2013 and 2019. SUBJECTS: Two cohorts of infected patients: 1) patients in the ICU with septic shock and 2) hospitalized patients with Staphylococcus aureus bacteremia. INTERVENTIONS: Clinical data (including body temperature) and plasma cytokine concentrations were measured. Patients were classified into four temperature trajectory subphenotypes using their temperature measurements in the first 72 hours from the onset of infection. Log-transformed cytokine levels were standardized to the mean and compared with the subphenotypes in both cohorts. MEASUREMENTS AND MAIN RESULTS: The cohorts consisted of 120 patients with septic shock (cohort 1) and 88 patients with S. aureus bacteremia (cohort 2). Patients from both cohorts were classified into one of four previously validated temperature subphenotypes: "hyperthermic, slow resolvers" (n = 19 cohort 1; n = 13 cohort 2), "hyperthermic, fast resolvers" (n = 18 C1; n = 24 C2), "normothermic" (n = 54 C1; n = 31 C2), and "hypothermic" (n = 29 C1; n = 20 C2). Both "hyperthermic, slow resolvers" and "hyperthermic, fast resolvers" had high levels of G-CSF, CCL2, and interleukin-10 compared with the "hypothermic" group when controlling for cohort and timing of cytokine measurement (p < 0.05). In contrast to the "hyperthermic, slow resolvers," the "hyperthermic, fast resolvers" showed significant decreases in the levels of several cytokines over a 24-hour period, including interleukin-1RA, interleukin-6, interleukin-8, G-CSF, and M-CSF (p < 0.001). CONCLUSIONS: Temperature trajectory subphenotypes are associated with consistent cytokine profiles in two distinct cohorts of infected patients. These subphenotypes could play a role in the bedside identification of cytokine profiles in patients with sepsis.

Caring for Critically Ill Adults With Coronavirus Disease 2019 in a PICU: Recommendations by Dual Trained Intensivists.

OBJECTIVE: In the midst of the severe acute respiratory syndrome coronavirus 2 pandemic, which causes coronavirus disease 2019, there is a recognized need to expand critical care services and beds beyond the traditional boundaries. There is considerable concern that widespread infection will result in a surge of critically ill patients that will overwhelm our present adult ICU capacity. In this setting, one proposal to add "surge capacity" has been the use of PICU beds and physicians to care for these critically ill adults. DESIGN: Narrative review/perspective. SETTING: Not applicable. PATIENTS: Not applicable. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The virus's high infectivity and prolonged asymptomatic shedding have resulted in an exponential growth in the number of cases in the United States within the past weeks with many (up to 6%) developing acute respiratory distress syndrome mandating critical care services. Coronavirus disease 2019 critical illness appears to be primarily occurring in adults. Although pediatric intensivists are well versed in the care of acute respiratory distress syndrome from viral pneumonia, the care of differing aged adult populations presents some unique challenges. In this statement, a team of adult and pediatric-trained critical care physicians provides guidance on common "adult" issues that may be encountered in the care of these patients and how they can best be managed in a PICU. CONCLUSIONS: This concise scientific statement includes references to the most recent and relevant guidelines and clinical trials that shape management decisions. The intention is to assist PICUs and intensivists in rapidly preparing for care of adult coronavirus disease 2019 patients should the need arise.

Ultrasensitive digital quantification of cytokines and bacteria predicts septic shock outcomes.

Quantification of pathogen and host biomarkers is essential for the diagnosis, monitoring, and treatment of infectious diseases. Here, we demonstrate sensitive and rapid quantification of bacterial load and cytokines from human biological samples to generate actionable hypotheses. Our digital assay measures IL-6 and TNF-α proteins, gram-negative (GN) and gram-positive (GP) bacterial DNA, and the antibiotic-resistance gene blaTEM with femtomolar sensitivity. We use our method to characterize bronchoalveolar lavage fluid from patients with asthma, and find elevated GN bacteria and IL-6 levels compared to healthy subjects. We then analyze plasma from patients with septic shock and find that increasing levels of IL-6 and blaTEM are associated with mortality, while decreasing IL-6 levels are associated with recovery. Surprisingly, lower GN bacteria levels are associated with higher probability of death. Applying decision-tree analysis to our measurements, we are able to predict mortality and rate of recovery from septic shock with over 90% accuracy.

Allergic Immune Diseases and the Risk of Mortality Among Patients Hospitalized for Acute Infection.

OBJECTIVES: The immune response during sepsis remains poorly understood and is likely influenced by the host's preexisting immunologic comorbidities. Although more than 20% of the U.S. population has an allergic-atopic disease, the type 2 immune response that is overactive in these diseases can also mediate beneficial pro-resolving, tissue-repair functions. Thus, the presence of allergic immunologic comorbidities may be advantageous for patients suffering from sepsis. The objective of this study was to test the hypothesis that comorbid type 2 immune diseases confer protection against morbidity and mortality due to acute infection. DESIGN: Retrospective cohort study of patients hospitalized with an acute infection between November 2008 and January 2016 using electronic health record data. SETTING: Single tertiary-care academic medical center. PATIENTS: Admissions to the hospital through the emergency department with likely infection at the time of admission who may or may not have had a type 2 immune-mediated disease, defined as asthma, allergic rhinitis, atopic dermatitis, or food allergy, as determined by International Classification of Diseases, 9th Revision, Clinical Modification codes. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 10,789 admissions for infection, 2,578 (24%) had a type 2 disease; these patients were more likely to be female, black, and younger than patients without type 2 diseases. In unadjusted analyses, type 2 patients had decreased odds of dying during the hospitalization (0.47; 95% CI, 0.38-0.59, p < 0.001), while having more than one type 2 disease conferred a dose-dependent reduction in the risk of mortality (p < 0.001). When adjusting for demographics, medications, types of infection, and illness severity, the presence of a type 2 disease remained protective (odds ratio, 0.55; 95% CI, 0.43-0.70; p < 0.001). Similar results were found using a propensity score analysis (odds ratio, 0.57; 95% CI, 0.45-0.71; p < 0.001). CONCLUSIONS: Patients with type 2 diseases admitted with acute infections have reduced mortality, implying that the type 2 immune response is protective in sepsis.