Onset Of Severe Sepsis Research Articles

Utilizing a Pediatric Early Warning Tool for Sepsis Screening in a Pediatric Oncology Hospital.

Background: Yearly, 75,000 children develop severe sepsis and 7000 die. Immunocompromising conditions and treatment of patients with malignancy put them at higher risk for sepsis. To reduce mortality, morbidity, and onset of severe sepsis in patients at St. Jude Children’s Research Hospital, our team joined the Children’s Hospital Association Improving Pediatric Sepsis Outcomes collaborative. Objectives: Build on an existing Pediatric Early Warning Score scoring tool for clinical deterioration to enhance real-time recognition of septic patients to intervene quickly with appropriate tests and treatment. Methods: A multiprofessional team of over 50 staff and family representatives developed St. Jude specific Sepsis Recognition and Treatment Guidelines. Implemented in the inpatient units in January 2019 and outpatient units in January 2020, the guidelines include sepsis screening, team huddles, intervention algorithms, and order sets. Monthly, sepsis screening, huddles, and interventions are reviewed. Evaluated data include number of sepsis huddles, classification of sepsis huddles, use of order sets, nurse and provider documentation and disposition of patients. Based on data review, SBARs, education, reminders for staff, and numerous PDSA cycles have been implemented. Results: The number of sepsis huddles has steadily increased from 2019 to 2021 (Fig. 1). Order set usage has increased from 14% in first quarter of 2019 to 62% in second quarter of 2021. The number of sepsis-attributable mortalities decreased from 4 in 2017 before sepsis guideline implementation to 0 in 2019 and 2020 (a decrease of 100%). Number of hospital days to treat sepsis declined, patients had fewer days on a ventilator, fewer days on vasoactive medications, and fewer days in the ICU. Identification and treatment of severe sepsis or septic shock cases increased from four in 2018 before implementation to 18 in 2020 (Fig. 2). For sepsis STAT cases in 2019 and 2020, respectively, the sepsis screening tool utilization increased from 93% to 100% (goal, 85%), sepsis huddles were activated in 93% and 100% (goal, 85%), order set utilization increased from 0 to 38% (goal, 85%), time to first IV fluid bolus was 34 and 47 minutes (goal, 20 minutes), and time to first IV antibiotic administration improved from 62 minutes to 44 minutes (goal, 60 minutes). Conclusions: Improving pediatric sepsis outcomes is an on-going quality and patient safety priority for our hospital. We demonstrated that Pediatric Early Warning Score plus screening tool can be successfully utilized in a high-volume pediatric oncology hospital to quickly identify patients with potential sepsis. Early identification and prompt management of sepsis have proven to decrease morbidity and mortality in pediatric hematology, oncology, and transplant patients. Disclosure The authors have no financial interest to declare in relation to the content of this article.Figure 1.: Quarterly number of sepsis huddles, sepsis algorithm category, and percent of huddles where order sets were used.Figure 2.: Number of sepsis cases and sepsis-attributable mortalities in 2017 - 2020.

Evaluating the impact of severe sepsis 3-hour bundle compliance on 28-day in-hospital mortality: A propensity adjusted, nested case-control study.

The Centers for Medicare and Medicaid Services Severe Sepsis and Septic Shock Management Bundle (SEP-1) assesses antibiotic administration, lactate measurement, and blood culture collection within 3h of severe sepsis onset. The impact of the SEP-1 3-hour bundle among patients with severe sepsis is not extensively described. This investigation aimed to describe the impact of 3-hour bundle compliance on 28-day in-hospital mortality in patients with severe sepsis. This was a retrospective, propensity adjusted, nested case-control study assessing the impact of compliance with a 3-hour sepsis bundle among patients with severe sepsis. This study was conducted at a large, academic, tertiary care medical center in Detroit, Michigan from July 1, 2017 to December 31, 2019. Cases were defined as those suffering 28-day in-hospital mortality. Controls were defined as those surviving at or discharged by 28 days. Patients were separated based on 3-hour bundle compliance or noncompliance. Nested and overall cohorts were assessed. Severe sepsis time zero was manually validated. Patients with shock, requiring vasopressors within 8 h of time zero, or those not meeting SEP-1 inclusion criteria were excluded. The primary outcome was the propensity adjusted odds of 28-day in-hospital mortality among 3-hour bundle compliant versus noncompliant patients. Secondary outcomes included mortality for individual bundle element compliance, progression to septic shock, and predictors of mortality according to logistic regression. A total of 325 compliant and 325 noncompliant patients were included. The median Sequential Organ Failure Assessment (SOFA) score was three in each group. There was no difference in propensity adjusted odds of mortality among those compliant versus noncompliant with the 3-hour bundle (odds-ratio [OR] 1.039; 95% CI: 0.721-1.497; p=0.838) or with individual bundle elements. SOFA score and female sex were predictors of mortality. Three-hour bundle compliance did not impact 28-day in-hospital mortality in patients with severe sepsis. Further research is needed to understand the impact of 3-hour bundle compliance on mortality in severe sepsis.

Change in Score for Neonatal Acute Physiology-II Measurements for Prediction of Mortality in Severely Septic Preterm Neonates.

To study the discriminatory ability of the change (delta) in the Score for Neonatal Acute Physiology-II (SNAP-II) for 14-d mortality in preterm neonates with severe sepsis. Consecutively born neonates of < 34-wk gestation during the 1-y study period in a tertiary care neonatal unit were included. SNAP-II was recorded at the onset of severe sepsis (T0) and serially at 24 (T1), 48 (T2), and 72 (T3) h. Delta scores (Δ SNAP-II) were derived from the difference between the SNAP-II at baseline and each one of the subsequent time points. Seventy-one preterm neonates were enrolled. Baseline characteristics were similar in survivors (n = 53) and nonsurvivors (n = 18). Median SNAP-II at all the four time points were significantly higher in nonsurvivors (p < 0.001). Delta SNAP-II (T0-T2) was significantly different between nonsurvivors and survivors (mean difference: -14.7; 95% CI: -29, -0.9; p = 0.02), while the difference was not significant between T0-T1 and T0-T3. Initial SNAP-II had a significantly better discriminating ability than Δ SNAP-II at various time points (AUC, 95% CI: 0.59, 0.41-0.75 for T0-T1; 0.70, 0.50-0.87 for T0-T2; and 0.64; 0.38-0.89 for T0-T3). Delta SNAP-II does not have a better discriminatory ability for mortality by 14 d in preterm neonates with severe sepsis.

Prediction of sepsis onset in hospital admissions using survival analysis.

To determine the efficacy of modern survival analysis methods for predicting sepsis onset in ICU, emergency, medical/surgical, and TCU departments. We performed a retrospective analysis on ICU, med/surg, ED, and TCU cases from multiple Mercy Health hospitals from August 2018 to March 2020. Patients in these departments were monitored by the Mercy Virtual vSepsis team and sepsis cases were determined and documented in the Mercy EHR via a rule-based engine utilizing clinical data. We used survival-based modeling methods to predict sepsis onset in these cases. The three survival methods that were used to predict the onset of severe sepsis and septic shock produced AUC values > 0.85 and each provided a median lead time of > 20h prior to disease onset. This methodology improves upon previous work by demonstrating excellent model performance when generalizing survival-based prediction methods to both severe sepsis and septic shock as well as non-ICU departments.IRB InformationTrial Registration ID: 1,532,327-1.Trial Effective Date: 12/02/2019.

Predicting sepsis severity at first clinical presentation: The role of endotypes and mechanistic signatures.

SummaryBackgroundInter-individual variability during sepsis limits appropriate triage of patients. Identifying, at first clinical presentation, gene expression signatures that predict subsequent severity will allow clinicians to identify the most at-risk groups of patients and enable appropriate antibiotic use.MethodsBlood RNA-Seq and clinical data were collected from 348 patients in four emergency rooms (ER) and one intensive-care-unit (ICU), and 44 healthy controls. Gene expression profiles were analyzed using machine learning and data mining to identify clinically relevant gene signatures reflecting disease severity, organ dysfunction, mortality, and specific endotypes/mechanisms.FindingsGene expression signatures were obtained that predicted severity/organ dysfunction and mortality in both ER and ICU patients with accuracy/AUC of 77–80%. Network analysis revealed these signatures formed a coherent biological program, with specific but overlapping mechanisms/pathways. Given the heterogeneity of sepsis, we asked if patients could be assorted into discrete groups with distinct mechanisms (endotypes) and varying severity. Patients with early sepsis could be stratified into five distinct and novel mechanistic endotypes, named Neutrophilic-Suppressive/NPS, Inflammatory/INF, Innate-Host-Defense/IHD, Interferon/IFN, and Adaptive/ADA, each based on ∼200 unique gene expression differences, and distinct pathways/mechanisms (e.g., IL6/STAT3 in NPS). Endotypes had varying overall severity with two severe (NPS/INF) and one relatively benign (ADA) groupings, consistent with reanalysis of previous endotype studies. A 40 gene-classification tool (accuracy=96%) and several gene-pairs (accuracy=89–97%) accurately predicted endotype status in both ER and ICU validation cohorts.InterpretationThe severity and endotype signatures indicate that distinct immune signatures precede the onset of severe sepsis and lethality, providing a method to triage early sepsis patients.

Targeting G\u03b113-integrin interaction ameliorates systemic inflammation

Systemic inflammation as manifested in sepsis is an excessive, life-threatening inflammatory response to severe bacterial or viral infection or extensive injury. It is also a thrombo-inflammatory condition associated with vascular leakage/hemorrhage and thrombosis that is not effectively treated by current anti-inflammatory or anti-thrombotic drugs. Here, we show that MB2mP6 peptide nanoparticles, targeting the Gα13-mediated integrin “outside-in” signaling in leukocytes and platelets, inhibited both inflammation and thrombosis without causing hemorrhage/vascular leakage. MB2mP6 improved mouse survival when infused immediately or hours after onset of severe sepsis. Furthermore, platelet Gα13 knockout inhibited septic thrombosis whereas leukocyte Gα13 knockout diminished septic inflammation, each moderately improving survival. Dual platelet/leukocyte Gα13 knockout inhibited septic thrombosis and inflammation, further improving survival similar to MB2mP6. These results demonstrate that inflammation and thrombosis independently contribute to poor outcomes and exacerbate each other in systemic inflammation, and reveal a concept of dual anti-inflammatory/anti-thrombotic therapy without exacerbating vascular leakage.

Predictors of severe sepsis-related in-hospital mortality based on a multicenter cohort study: The Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study.

This study aimed to identify prognostic factors for severe sepsis-related in-hospital mortality using the structural equation model (SEM) analysis with statistical causality. Sepsis data from the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma study (FORECAST), a multicenter cohort study, was used. Forty seven observed variables from the database were used to construct 4 latent variables. SEM analysis was performed on these latent variables to analyze the statistical causality among these data. This study evaluated whether the variables had an effect on in-hospital mortality. Overall, 1148 patients were enrolled. The SEM analysis showed that the 72-hour physical condition was the strongest latent variable affecting mortality, followed by physical condition before treatment. Furthermore, the 72-hour physical condition and the physical condition before treatment strongly influenced the Sequential Organ Failure Assessment (SOFA) score with path coefficients of 0.954 and 0.845, respectively. The SOFA score was the strongest variable that affected mortality after the onset of severe sepsis. The score remains the most robust prognostic factor and can facilitate appropriate policy development on care.

Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48\xa0h in advance using a diverse dataset from 461 US hospitals

BackgroundSevere sepsis and septic shock are among the leading causes of death in the United States and sepsis remains one of the most expensive conditions to diagnose and treat. Accurate early diagnosis and treatment can reduce the risk of adverse patient outcomes, but the efficacy of traditional rule-based screening methods is limited. The purpose of this study was to develop and validate a machine learning algorithm (MLA) for severe sepsis prediction up to 48 h before onset using a diverse patient dataset.MethodsRetrospective analysis was performed on datasets composed of de-identified electronic health records collected between 2001 and 2017, including 510,497 inpatient and emergency encounters from 461 health centers collected between 2001 and 2015, and 20,647 inpatient and emergency encounters collected in 2017 from a community hospital. MLA performance was compared to commonly used disease severity scoring systems and was evaluated at 0, 4, 6, 12, 24, and 48 h prior to severe sepsis onset.Results270,438 patients were included in analysis. At time of onset, the MLA demonstrated an AUROC of 0.931 (95% CI 0.914, 0.948) and a diagnostic odds ratio (DOR) of 53.105 on a testing dataset, exceeding MEWS (0.725, P < .001; DOR 4.358), SOFA (0.716; P < .001; DOR 3.720), and SIRS (0.655; P < .001; DOR 3.290). For prediction 48 h prior to onset, the MLA achieved an AUROC of 0.827 (95% CI 0.806, 0.848) on a testing dataset. On an external validation dataset, the MLA achieved an AUROC of 0.948 (95% CI 0.942, 0.954) at the time of onset, and 0.752 at 48 h prior to onset.ConclusionsThe MLA accurately predicts severe sepsis onset up to 48 h in advance using only readily available vital signs extracted from the existing patient electronic health records. Relevant implications for clinical practice include improved patient outcomes from early severe sepsis detection and treatment.

Plan-Do-Study-Act Methodology: Refining an Inpatient Pediatric Sepsis Screening Process.

Introduction:Pediatric sepsis remains a leading cause of death of children in the United States. Timely recognition and treatment are critical to prevent the onset of severe sepsis and septic shock. Electronic screening tools aid providers in identifying patients at risk for sepsis. Our overall project goal was to decrease the number of sepsis-related emergent transfers to the pediatric intensive care unit by optimizing sepsis screening tools, interruptive alerts, and a new paper tool and huddle process using Plan-Do-Study-Act (PDSA) methodology.Methods:Our team utilized historical data to develop inpatient electronic sepsis screening tools to identify pediatric patients at risk for sepsis. Using PDSA iterative cycles over 3 months, we tested the design of an interruptive alert, paper tool, and a new sepsis huddle process.Results:During the PDSA, the clinical teams conducted huddles on all patients who received an interruptive alert (n = 35). Eighty percent of huddles had a 5.7 minute average response time and an average duration of 5.3 minutes. Completion of the huddle outcome notes occurred 83% of the time, and 70% had feedback related to the alert, paper form, and huddle process. The number of days between sepsis-related emergent transfers to the pediatric intensive care unit increased from a median of 17.5 to 57.5 days, with a single point as high as 195 days between events.Conclusions:The inpatient sepsis team learned valuable lessons using PDSA methodology. The results of the iterative cycles allowed the team to optimize and refine the tests of change. System-wide implementation benefited from the application of this quality improvement tool.

Comparative study between spontaneous fungal peritonitis (SFP) and spontaneous bacterial peritonitis (SBP) in patients with end stage liver disease (ESLD)

Background: Bacterial infections in end stage liver disease are common and associated with increased mortality. Although extensive research has elucidated the impact of bacterial infections as the major precipitating event leads to increased frequency of liver-related complications and mortality in these patients. Objective: Evaluating the clinical and laboratory characters, risk factors, and outcome of fungal and bacterial peritonitis in cirrhotic patients with end stage liver disease (ESLD). Patients and Methods: This cross sctional study enrolled 60 patients with liver cirrhosis and ascites. Fifty patients were culture-positive spontaneous peritonitis, including 12 with spontaneous fungal peritonitis (SFP), and 38 culture-positive spontaneous bacterial peritonitis (SBP), and 10 patients without clinical or laboratory evidence of peritonitis as a control group, during the study period, between 1st February 2018 and 30th May 2019. We compared the clinical, laboratory findings, Child–Pugh scores, model for end stage liver disease (MELD) score, risk factors, and mortality rates between patients with spontaneous peritonitis associated with fungal culture-positive ascites, and those with spontaneous peritonitis associated with bacterial culture-positive ascites. Results: Patients of the current study were critically ill. The mean duration of ESLD in the studied patients was 4.75 ± 1.8 year, 57 patients (95.0%) were Child score C, and 3 patients (5%) were Child score B. The mean MELD score was 23.32 ± 5.49. All patients with evidence of peritonitis were Child C, and mean MELD scores were 22.6 ±5.7 and 26.1±4.5 in SBP and SFP groups respectively. Jaundice, GI bleeding and hepatic encephalopathy were significantly for clinical presentation and predictors of mortality in SFP group compared to SBP and control group. Lower levels of hemoglobin (Hb), S. albumin and platelets count and increased level of total leukocytic count (TLC), international normalized ratio (INR), and bilirubin were significantly higher in SFP group compared to SBP and control group. Duration of ESLD and hospital admission was significant in SFP compared to SBP and control group. HCC was evident in SFP group (66.7%) that was highly significant in comparison to SBP (28.9%), and control group (20%). Overall mortality rate among the studied groups was 45%, the mortality rate was significantly increased in SFP group (75%) compared to SBP (42.1%), and control group (20%).The mean MELD score significantly increased in non-survival group compared to survival group . The duration of ESLD significantly increased in non-survival group compared to survival group. Conclusion: Prolonged and severe underlying liver disease with a high Child- Pugh or MELD score, renal impairment, HCC, and onset of severe sepsis have been reported as risk factors in increased mortality in patients with SFP than in SBP. In SFP, mortality was associated not only with the severity of the underlying liver disease, but also with delay in diagnosis and initiation of antifungal therapy.

Comparative study between spontaneous fungal peritonitis (SFP) and spontaneous bacterial peritonitis (SBP) in patients with end stage liver disease (ESLD)

Background: Bacterial infections in end stage liver disease are common and associated with increased mortality. Although extensive research has elucidated the impact of bacterial infections as the major precipitating event leads to increased frequency of liver-related complications and mortality in these patients. Objective: Evaluating the clinical and laboratory characters, risk factors, and outcome of fungal and bacterial peritonitis in cirrhotic patients with end stage liver disease (ESLD). Patients and Methods: This cross sctional study enrolled 60 patients with liver cirrhosis and ascites. Fifty patients were culture-positive spontaneous peritonitis, including 12 with spontaneous fungal peritonitis (SFP), and 38 culture-positive spontaneous bacterial peritonitis (SBP), and 10 patients without clinical or laboratory evidence of peritonitis as a control group, during the study period, between 1st February 2018 and 30th May 2019. We compared the clinical, laboratory findings, Child–Pugh scores, model for end stage liver disease (MELD) score, risk factors, and mortality rates between patients with spontaneous peritonitis associated with fungal culture-positive ascites, and those with spontaneous peritonitis associated with bacterial culture-positive ascites. Results: Patients of the current study were critically ill. The mean duration of ESLD in the studied patients was 4.75 ± 1.8 year, 57 patients (95.0%) were Child score C, and 3 patients (5%) were Child score B. The mean MELD score was 23.32 ± 5.49. All patients with evidence of peritonitis were Child C, and mean MELD scores were 22.6 ±5.7 and 26.1±4.5 in SBP and SFP groups respectively. Jaundice, GI bleeding and hepatic encephalopathy were significantly for clinical presentation and predictors of mortality in SFP group compared to SBP and control group. Lower levels of hemoglobin (Hb), S. albumin and platelets count and increased level of total leukocytic count (TLC), international normalized ratio (INR), and bilirubin were significantly higher in SFP group compared to SBP and control group. Duration of ESLD and hospital admission was significant in SFP compared to SBP and control group. HCC was evident in SFP group (66.7%) that was highly significant in comparison to SBP (28.9%), and control group (20%). Overall mortality rate among the studied groups was 45%, the mortality rate was significantly increased in SFP group (75%) compared to SBP (42.1%), and control group (20%).The mean MELD score significantly increased in non-survival group compared to survival group . The duration of ESLD significantly increased in non-survival group compared to survival group. Conclusion: Prolonged and severe underlying liver disease with a high Child- Pugh or MELD score, renal impairment, HCC, and onset of severe sepsis have been reported as risk factors in increased mortality in patients with SFP than in SBP. In SFP, mortality was associated not only with the severity of the underlying liver disease, but also with delay in diagnosis and initiation of antifungal therapy.

1130. Vancomycin Use in Pediatric Severe Sepsis at a Freestanding Children’s Hospital

BackgroundSurviving Sepsis Campaign guidelines recommend antibiotics be administered within 1 hour of severe sepsis (SS) onset, but do not suggest which agents to give. Vancomycin (VAN) is often chosen as empiric therapy for severe sepsis (SS) in children without evidence of the prevalence or risk factors for infections requiring VAN. As VAN is associated with significant nephrotoxicity, this study was performed to measure the risk-benefit ratio of empiric VAN use in pediatric sepsis.MethodsThis was a retrospective study of children with SS between 1/1/2015 to 6/30/2018 at the Women and Children’s Hospital of Buffalo, as captured by billing data and sent to state Department of Health for mandated reporting. SS cases were assessed for risk factors for Gram-positive infections, including presence of a central venous line (CVL) or other invasive device; history of MRSA infection or nasal colonization within the last 2 years; skilled nursing facility (SNF) residence; and prolonged hospitalization of >1 month. Invasive infections for which vancomycin is an optimal agent, specifically culture-proven methicillin-resistant Staphylococcus aureus (MRSA), coagulase-negative Staphylococcus (CoNS), and ampicillin-resistant Enterococcus infections, were defined as vancomycin requiring (VAN-req). Acute kidney injury (AKI) was defined as having a serum Creatinine of twice normal per age-related reference values.ResultsOf 304 identified SS cases, 8.9% had VAN-req infections. VAN was empirically given to 58.2% of cases (177); 86.4% ultimately did not have VAN-req infections. 9.2% of all SS cases had AKI at SS onset; this included 15.8% of patients (28) receiving VAN, of which only 1 (3.6%) had a VAN-req infection. History of a past MRSA infection, prolonged hospitalization, SNF residence, and CVL presence were found to be independent risk factors for a VAN-req infection (Table 1). VAN-req infections in patients lacking these four risk factors was 3.1% (4/130).ConclusionVAN was given empirically in the majority of pediatric SS cases, but culture-proven infections requiring the drug were infrequent, especially in patients without specific risk factors. The use of empiric VAN for SS should be guided by well-defined criteria, as the drug’s potential risks are likely to outweigh any benefit in most patients. Disclosures All authors: No reported disclosures.

Pediatric Severe Sepsis Prediction Using Machine Learning.

Background: Early detection of pediatric severe sepsis is necessary in order to optimize effective treatment, and new methods are needed to facilitate this early detection.Objective: Can a machine-learning based prediction algorithm using electronic healthcare record (EHR) data predict severe sepsis onset in pediatric populations?Methods: EHR data were collected from a retrospective set of de-identified pediatric inpatient and emergency encounters for patients between 2–17 years of age, drawn from the University of California San Francisco (UCSF) Medical Center, with encounter dates between June 2011 and March 2016.Results: Pediatric patients (n = 9,486) were identified and 101 (1.06%) were labeled with severe sepsis following the pediatric severe sepsis definition of Goldstein et al. (1). In 4-fold cross-validation evaluations, the machine learning algorithm achieved an AUROC of 0.916 for discrimination between severe sepsis and control pediatric patients at the time of onset and AUROC of 0.718 at 4 h before onset. The prediction algorithm significantly outperformed the Pediatric Logistic Organ Dysfunction score (PELOD-2) (p < 0.05) and pediatric Systemic Inflammatory Response Syndrome (SIRS) (p < 0.05) in the prediction of severe sepsis 4 h before onset using cross-validation and pairwise t-tests.Conclusion: This machine learning algorithm has the potential to deliver high-performance severe sepsis detection and prediction through automated monitoring of EHR data for pediatric inpatients, which may enable earlier sepsis recognition and treatment initiation.

Early and dynamic alterations of Th2/Th1 in previously immunocompetent patients with community-acquired severe sepsis: a prospective observational study

BackgroundT helper (Th) cells regulate sepsis processes, including primary pathogen clear and secondary pathogen defence. The objectives of this study were to determine the early and dynamic alterations of Th1 and Th2 populations to community-acquired severe sepsis upon onset among previously immunocompetent patients and whether it was related to clinical outcomes.MethodsThis prospective observational cohort study was conducted at a general intensive care unit (ICU) of a tertiary teaching hospital in China. Immunocompetent patients with community-acquired severe sepsis within 24 h upon onset were included as septic group. Healthy volunteers and critically ill patients without severe sepsis were recruited as controls. Whole blood was collected on D0, 3rd day (D3) and 7th day (D7) for septic group and once upon enrollment for controls. Th1 and Th2 populations were measured by flow cytometry and assessed for associations with 28-day mortality using cox proportional hazard models. Associations of dynamic alterations of Th cell subpopulations with clinical outcomes were investigated.ResultsThis study demonstrated that community-acquired severe sepsis patients (n = 71) had increased Th2/Th1 and Th2 populations, compared to healthy controls (n = 7) and critically ill patients without severe sepsis (n = 7) at admission. Among the septic cohort, values of Th2/Th1 were significantly higher in non-survivors than survivors on D0 (p = 0.04), D3 (p < 0.001) and D7 (p < 0.001). Patients with persistently increasing Th2/Th1 demonstrated the highest mortality (47.1%) and incidence of ICU-acquired infections (64.7%).ConclusionsTh2/Th1 was markedly up-regulated with Th2 dominance upon community-acquired severe sepsis onset among previously immunocompetent patients and its persistently dynamic increase was associated with ICU-acquired infections and 28-day death.Trial registration Institutional Ethics Committee of Zhongda Hospital, 2014ZDSYLL086, registered in June 2014-prospectively registered; ClinicalTrials.gov, NCT02883218, registered on 25 Aug 2016-retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT02883218?cond=NCT02883218&rank=1

Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.

We used artificial intelligence to develop a novel algorithm using physiomarkers to predict the onset of severe sepsis in critically ill children. Observational cohort study. PICU. Children age between 6 and 18 years old. None. Continuous minute-by-minute physiologic data were available for a total of 493 critically ill children admitted to a tertiary care PICU over an 8-month period, 20 of whom developed severe sepsis. Using an alert time stamp generated by an electronic screening algorithm as a reference point, we studied up to 24 prior hours of continuous physiologic data. We identified physiomarkers, including SD of heart rate, systolic and diastolic blood pressure, and symbolic transitions probabilities of those variables that discriminated severe sepsis patients from controls (all other patients admitted to the PICU who did not meet severe sepsis criteria). We used logistic regression, random forests, and deep Convolutional Neural Network methods to derive our models. Analysis was performed using data generated in two windows prior to the firing of the electronic screening algorithm, namely, 2-8 and 8-24 hours. When analyzing the physiomarkers present in the 2-8 hours analysis window, logistic regression performed with specificity of 87.4% and sensitivity of 55.0%, random forest performed with 79.6% specificity and 80.0% sensitivity, and the Convolutional Neural Network performed with 83.0% specificity and 75.0% sensitivity. When analyzing physiomarkers from the 8-24 hours window, logistic regression resulted in 77.1% specificity and 39.3% sensitivity, random forest performed with 82.3% specificity and 61.1% sensitivity, whereas the Convolutional Neural Network method achieved 81% specificity and 76% sensitivity. Artificial intelligence can be used to predict the onset of severe sepsis using physiomarkers in critically ill children. Further, it may detect severe sepsis as early as 8 hours prior to a real-time electronic severe sepsis screening algorithm.

Predictive Value of Serum Albumin Level for the Prognosis of Severe Sepsis Without Exogenous Human Albumin Administration: A Prospective Cohort Study.

The prognostic significance of serum albumin levels in patients with sepsis has previously been reported; however, these studies have not excluded the potential confounding effect of exogenous albumin administration. In this study, we investigate the predictive value of serum albumin for the prognosis of severe sepsis without the interference of exogenous albumin administration. A prospective cohort study was conducted from April to November 2014 in the internal and surgical intensive care units of a tertiary care hospital. During the study period, due to a supply shortage, patients were not treated with human albumin. Serum albumin levels were measured, and laboratory and clinical data were collected at the onset of severe sepsis. Prognostic factors were analyzed using receiver operating characteristic curve and multivariate Cox proportional hazard regression analysis. Survival was assessed by Kaplan-Meier method. One hundred sixteen patients were included in the study. The overall 28-day mortality was 26.7%. The most common infection sources were lower respiratory tract, abdomen/pelvis, and bloodstream. Compared to patients who survived, those who died had lower serum albumin levels and higher Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores. Receiver operating characteristic curves demonstrate that albumin level is a strong predictor of 28-day mortality, and the optimal cutoff value maximizing sensitivity and specificity is 29.2 g/L. Through multivariate Cox regression analysis, low serum albumin levels (<29.2 g/L) and APACHE II scores are identified as independent risk factors for mortality. Patients with lower serum albumin levels more often had abdominal/pelvic sources of infection, acute kidney or liver injury, septic shock, and higher APACHE II and SOFA scores. The 28-day survival rate was lower for patients with serum albumin below 29.2 g/L than for patients with serum albumin at or above this level. Having excluded potential confounding effect of exogenous albumin administration, low serum albumin levels are associated with an increased risk of death in patients with severe sepsis.

Ischemia-modified albumin is a predictor of short-term mortality in patients with severe sepsis

PurposeOne of the most important events leading to morbidity and mortality in patients with severe sepsis is the development of global tissue hypoperfusion and oxidative damage. Ischemia-modified albumin (IMA), an albumin generated under ischemic and oxidative conditions, is a marker of oxidative stress and hypoperfusion. Here, we investigated whether IMA level could predict short-term mortality with severe sepsis. MethodsA prospective cohort study was conducted from April 2014 to October 2014 in intensive care units in a tertiary hospital. At the onset of severe sepsis, serum IMA level was measured, and baseline and laboratory data, infection sources, and underlying diseases were recorded; Sequential Organ Failure Assessment and Acute Physiology and Chronic Health Evaluation II scores were calculated. Multivariate logistic regression and receiver operating characteristic curve analyses were used to evaluate predictors of mortality. Kaplan-Meier analysis was used to compare survival at day 28. ResultsA total of 117 patients with severe sepsis were included (overall 28-day mortality, 24.8%). The IMA level was higher in nonsurvivors than in survivors (P < .05). It was a strong predictor of 28-day mortality (area under the receiver operating characteristic curve, 0.742; P < .001), and the optimal cutoff for IMA level maximizing sensitivity and specificity was 110 U/mL. On multivariate logistic regression, Acute Physiology and Chronic Health Evaluation II score and IMA level were independent risk factors for death. Survival rate was reduced with very high IMA level (≥110 U/mL; P < .05). ConclusionsThe IMA level, especially at least 110 U/mL, may be a useful predictor of death for patients with severe sepsis.

The prognostic value of serum albumin level in early stage of severe sepsis

Objective To investigate the predictive value of serum albumin level in patients with severe sepsis. Methods One hundred and twenty cases of patients with severe sepsis admitted to Qilu Hospital, Shandong University from April 2014 to October 2014 were prospectively enrolled. The serum albumin levels were measured and the laboratory and clinical data were collected at the onset of severe sepsis. Acute Physiology and Chronic Health Evaluation (APACHE) Ⅱ score and Sequential Organ Failure Assessment (SOFA) score were calculated. Patients were grouped according to the prognosis by day 28 or stratified by albumin level. Prognostic factors were analyzed by multivariable Logistic regression. Results A total of 120 patients were enrolled with mean age of (57.6±18.3) years, among which 75 were male. The mean duration of hospitalization was (20.1±17.8) days. The 28-day mortality was 25.8% (31/120). The most common infection sources were respiratory tract (56.7%), abdominal/pelvis (19.2%) and bloodstream (9.2%). Serum albumin level in survival group was significantly higher than that in death group ([32.1±6.4] g/L vs [27.5±5.5] g/L, t=3.562, P=0.001). Compared with survival group, the patients in death group had higher APACHE Ⅱ and SOFA scores (22.0±9.1 vs 13.4±7.2; 7.1±3.7 vs 4.3±3.5; t= —5.372 and —3.690, both P<0.05). Along with the decrease of serum albumin level, the incidence of bloodstream infection, solid tumor, septic shock, acute kidney injury and liver injury significantly increased. Patients with lower albumin level had significantly higher SOFA scores and 28-day mortality (all P<0.05). Multivariable regression analysis showed that albumin level lower than 28 g/L and higher APACHE Ⅱ score were independent risk factors for mortality (OR=4.156, 95%CI: 1.198—14.415; OR=1.121, 95%CI: 1.039—1.210; both P<0.05). Conclusions A significantly lowered serum albumin level would increase the risk of mortality in patients with severe sepsis. The combination of albumin level and APAHCE Ⅱ score might be beneficial to evaluate the prognosis. Key words: Serum albumin; Severe sepsis; Prognosis; Risk factors

Design of an electronic medical record (EMR)-based clinical decision support system to alert clinicians to the onset of severe sepsis

Design of an electronic medical record (EMR)-based clinical decision support system to alert clinicians to the onset of severe sepsis

Clinical Articularities of Drug-induced Agranulocytosis or Severe Neutropenia in Elderly Patients

Agranulocytosis is a life-threatening disorder in any age and also in the elderly subjects who are receiving on the average a larger number of drugs than younger subjects. This disorder frequently occurs as an adverse reaction to drugs, particularly to antibiotics, antiplatelet agents, anti-thyroid drugs, neuroleptics or anti-epileptic agents and nonsteroidal anti-inflammatory agents. Although patients experiencing drug-induced agranulocytosis may initially be asymptomatic, the severity of the neutropenia usually translates into the onset of severe sepsis that requires intravenous broad-spectrum anti-biotherapy. In this setting, hematopoietic growth factors have been shown to shorten the duration of neutropenia. Thus with appropriate management, the mortality rate of idiosyncratic druginduced agranulocytosis is now of 5% to 10%. Today, drug-induced agranulocytosis still remains a rare event with an annual incidence from 3 to 12 cases per million of people. However, given the increased life expectancy and subsequent longer exposure to drugs, as well as the development of new agents, physicians should be aware of this complication and its management.