Pediatric sepsis screening in US hospitals

Barriers and facilitators to effective electronic health record-based sepsis screening in the pediatric intensive care unit

Introduction

The Pediatric Surviving Sepsis Campaign supports the implementation of automated tools for early sepsis recognition. In 2019 the C.S. Mott Children's Hospital Pediatric Intensive Care Unit deployed an electronic medical record (EMR)-based screening for early recognition and treatment of sepsis.

Materials and Methods

We analyzed all automated primary sepsis alerts, secondary screens, and bedside huddles from November 2019 to January 2020 (Cohort 1) and from November 2020 to January 2021 (Cohort 2) to identify barriers and facilitators for the use of this tool. We distributed surveys to frontline providers to gather feedback on end-user experience.

Results

In Cohort 1, 895 primary alerts were triggered, yielding 503 completed secondary screens and 40 bedside huddles. In Cohort 2, 925 primary alerts were triggered, yielding 532 completed secondary screens and 12 bedside huddles. Surveys assessing end-user experience identified the following facilitators: (1) 73% of nurses endorsed the bedside huddle as value added; (2) 74% of medical providers agreed the bedside huddle increased the likelihood of interventions. The greatest barriers to successful implementation included the (1) overall large number of primary alerts from the automated tool and (2) rate of false alerts, many due to routine respiratory therapy interventions.

Discussion

Our data suggests that the successful implementation of EMR-based sepsis screening tools requires countermeasures focusing on 3 key drivers for change: education, technology, and patient safety.

Conclusion

While both medical providers and bedside nurses found merit in our EMR-based sepsis early recognition system, continued refinement is necessary to avoid sepsis alert fatigue.

Emergency Department Sepsis Triage Scoring Tool Elements Associated With Hypotension Within 24 Hours in Children With Fever and Tachycardia

OBJECTIVE

Pediatric sepsis screening is becoming the standard of care for children presenting to the emergency department (ED) and has been shown to improve recognition of severe sepsis, but it is unknown if these screening tools can predict progression of disease. The objective of this study was to determine if any elements of a sepsis triage trigger tool were predictive of progression to hypotensive shock in children presenting to the ED with fever and tachycardia.

METHODS

This study is a retrospective case-control study of children ≤18 years presenting to an ED with fever and tachycardia, comparing those who went on to develop hypotensive shock in the subsequent 24 hours (case) to those who did not (control). Primary outcome was the proportion of encounters where the patient had specific abnormal vital signs or clinical signs as components of the sepsis triage score. The secondary outcomes were the proportion of encounters where the patient had a sepsis risk factor.

RESULTS

During the study period, there were 94 patients who met case criteria and 186 controls selected. In the adjusted multivariable model, the 2 components of the sepsis triage score that were more common in case patients were the presence of severe cerebral palsy (adjusted odds ratio, 9.4 [3.7, 23.9]) and abnormal capillary refill at triage (adjusted odds ratio, 3.1 [1.4, 6.9]).

CONCLUSIONS

Among children who present to a pediatric ED with fever and tachycardia, those with prolonged capillary refill at triage or severe cerebral palsy were more likely to progress to decompensated septic shock, despite routine ED care.

Digital solutions in paediatric sepsis: current state, challenges, and opportunities to improve care around the world

The digitisation of health care is offering the promise of transforming the management of paediatric sepsis, which is a major source of morbidity and mortality in children worldwide. Digital technology is already making an impact in paediatric sepsis, but is almost exclusively benefiting patients in high-resource health-care settings. However, digital tools can be highly scalable and cost-effective, and-with the right planning-have the potential to reduce global health disparities. Novel digital solutions, from wearable devices and mobile apps, to electronic health record-embedded decision support tools, have an unprecedented opportunity to transform paediatric sepsis research and care. In this Series paper, we describe the current state of digital solutions in paediatric sepsis around the world, the advances in digital technology that are enabling the development of novel applications, and the potential effect of advances in artificial intelligence in paediatric sepsis research and clinical care.

Development of a New Screening Tool for Pediatric Septic Shock

STUDY OBJECTIVE

Existing screening tools for sepsis in children are limited by suboptimal sensitivity. Our objective was to develop a new, more sensitive screening tool for pediatric septic shock by enhancing 2 aspects of the 4-point Liverpool quick Sequential Organ Failure Assessment (LqSOFA) tool.

METHODS

We performed a secondary analysis of a cohort of children (1 month to 18 years) who presented to a pediatric emergency department (ED) with suspected infection over a 10-year period. Septic shock was defined as intravenous vasoactive infusion within 24-hours of arrival for children with suspected infection and intravenous antibiotics administered. We developed the 4-point quick Pediatric Septic Shock Screening Score (qPS4) by making 2 changes to the 4-point LqSOFA: (1) the pulse rate parameter was replaced with the recently derived Temperature and Age-adjusted Mean Shock Index and (2) standard respiratory rate cutoffs for tachypnea were replaced by cutoffs derived empirically from the study cohort. The other 2 LqSOFA criteria were unchanged (abnormal mentation and capillary refill ≥3 seconds). We defined a positive qPS4 as ≥2 criteria (consistent with LqSOFA). We used the training cohort from the parent study to derive cutoffs for respiratory rate and the validation cohort to compare the qPS4 with LqSOFA and qSOFA.

RESULTS

Among the 47,231 encounters in the validation cohort from the parent study, with median age of 4.5 years, qPS4 had an area under the receiver operating characteristic curve for septic shock of 0.94 (95% confidence interval [CI] 0.92 to 0.96). qPS4 ≥2 had a sensitivity of 89.7% (95% CI 84.9% to 94.5%), and a specificity of 92.2% (95% CI 92.0% to 92.5%) for septic shock. In comparison, the LqSOFA achieved an area under the receiver operating characteristic curve of 0.86 (95% CI 0.82 to 0.89), a sensitivity of 56.1% (95% CI 48.3% to 63.9%), and a specificity of 96.8% (95% CI 96.6% to 96.9%). The median time from first positive qPS4 to initiation of an intravenous vasoactive infusion was 2.5 hours (IQR 0.9 to 6.1) compared to 0.7 hours (IQR 0.0 to 4.5) for LqSOFA.

CONCLUSION

The qPS4, with 2 enhancements to the LqSOFA, demonstrated overall improved sensitivity and specificity for pediatric septic shock.

Improved pediatric ICU mortality prediction for respiratory diseases: machine learning and data subdivision insights

The growing concern of pediatric mortality demands heightened preparedness in clinical settings, especially within intensive care units (ICUs). As respiratory-related admissions account for a substantial portion of pediatric illnesses, there is a pressing need to predict ICU mortality in these cases. This study based on data from 1188 patients, addresses this imperative using machine learning techniques and investigating different class balancing methods for pediatric ICU mortality prediction. This study employs the publicly accessible "Paediatric Intensive Care database" to train, validate, and test a machine learning model for predicting pediatric patient mortality. Features were ranked using three machine learning feature selection techniques, namely Random Forest, Extra Trees, and XGBoost, resulting in the selection of 16 critical features from a total of 105 features. Ten machine learning models and ensemble techniques are used to make accurate mortality predictions. To tackle the inherent class imbalance in the dataset, we applied a unique data partitioning technique to enhance the model's alignment with the data distribution. The CatBoost machine learning model achieved an area under the curve (AUC) of 72.22%, while the stacking ensemble model yielded an AUC of 60.59% for mortality prediction. The proposed subdivision technique, on the other hand, provides a significant improvement in performance metrics, with an AUC of 85.2% and an accuracy of 89.32%. These findings emphasize the potential of machine learning in enhancing pediatric mortality prediction and inform strategies for improved ICU readiness.

Predictive Value of a Diagnostic Five-Gene Biomarker for Pediatric Sepsis

Background

Pediatric sepsis has a very high morbidity and mortality rate. The purpose of this study was to evaluate diagnostic biomarkers and immune cell infiltration in pediatric sepsis.

Methods

Three datasets (GSE13904, GSE26378, and GSE26440) were downloaded from the gene expression omnibus (GEO) database. After identifying overlapping genes in differentially expressed genes (DEGs) and modular sepsis genes selected via a weighted gene co-expression network (WGCNA) in the GSE26378 dataset, pivotal genes were further identified by using LASSO regression and random forest analysis to construct a diagnostic model. Receiver operating characteristic curve (ROC) analysis was used to validate the efficacy of the diagnostic model for pediatric sepsis. Furthermore, we used qRT-PCR to detect the expression levels of pivotal genes and validate the diagnostic model's ability to diagnose pediatric sepsis in 65 actual clinical samples.

Results

Among 294 overlapping genes of DEGs and modular sepsis genes, five pivotal genes (STOM, MS4A4A, CD177, MMP8, and MCEMP1) were screened to construct a diagnostic model of pediatric sepsis. The expression of the five pivotal genes was higher in the sepsis group than in the normal group. The diagnostic model showed good diagnostic ability with AUCs of 1, 0.986, and 0.968. More importantly, the diagnostic model showed good diagnostic ability with AUCs of 0.937 in the 65 clinical samples and showed better efficacy compared to conventional inflammatory indicators such as procalcitonin (PCT), white blood cell (WBC) count, C-reactive protein (CRP), and neutrophil percentage (NEU%).

Conclusion

We developed and tested a five-gene diagnostic model that can reliably identify pediatric sepsis and also suggest prospective candidate genes for peripheral blood diagnostic testing in pediatric sepsis patients.

Pediatric Sepsis Diagnosis, Management, and Sub-phenotypes

Sepsis and septic shock are major causes of morbidity, mortality, and health care costs for children worldwide, including >3 million deaths annually and, among survivors, risk for new or worsening functional impairments, including reduced quality of life, new respiratory, nutritional, or technological assistance, and recurrent severe infections. Advances in understanding sepsis pathophysiology highlight a need to update the definition and diagnostic criteria for pediatric sepsis and septic shock, whereas new data support an increasing role for automated screening algorithms and biomarker combinations to assist earlier recognition. Once sepsis or septic shock is suspected, attention to prompt initiation of broad-spectrum empiric antimicrobial therapy, fluid resuscitation, and vasoactive medications remain key components to initial management with several new and ongoing studies offering new insights into how to optimize this approach. Ultimately, a key goal is for screening to encompass as many children as possible at risk for sepsis and trigger early treatment without increasing unnecessary broad-spectrum antibiotics and preventable hospitalizations. Although the role for adjunctive treatment with corticosteroids and other metabolic therapies remains incompletely defined, ongoing studies will soon offer updated guidance for optimal use. Finally, we are increasingly moving toward an era in which precision therapeutics will bring novel strategies to improve outcomes, especially for the subset of children with sepsis-induced multiple organ dysfunction syndrome and sepsis subphenotypes for whom antibiotics, fluid, vasoactive medications, and supportive care remain insufficient.

Prevalence and Characteristics of Diagnostic Error in Pediatric Critical Care: A Multicenter Study

OBJECTIVES

Effective interventions to prevent diagnostic error among critically ill children should be informed by diagnostic error prevalence and etiologies. We aimed to determine the prevalence and characteristics of diagnostic errors and identify factors associated with error in patients admitted to the PICU.

DESIGN

Multicenter retrospective cohort study using structured medical record review by trained clinicians using the Revised Safer Dx instrument to identify diagnostic error (defined as missed opportunities in diagnosis). Cases with potential errors were further reviewed by four pediatric intensivists who made final consensus determinations of diagnostic error occurrence. Demographic, clinical, clinician, and encounter data were also collected.

SETTING

Four academic tertiary-referral PICUs.

PATIENTS

Eight hundred eighty-two randomly selected patients 0-18 years old who were nonelectively admitted to participating PICUs.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Of 882 patient admissions, 13 (1.5%) had a diagnostic error up to 7 days after PICU admission. Infections (46%) and respiratory conditions (23%) were the most common missed diagnoses. One diagnostic error caused harm with a prolonged hospital stay. Common missed diagnostic opportunities included failure to consider the diagnosis despite a suggestive history (69%) and failure to broaden diagnostic testing (69%). Unadjusted analysis identified more diagnostic errors in patients with atypical presentations (23.1% vs 3.6%, p = 0.011), neurologic chief complaints (46.2% vs 18.8%, p = 0.024), admitting intensivists greater than or equal to 45 years old (92.3% vs 65.1%, p = 0.042), admitting intensivists with more service weeks/year (mean 12.8 vs 10.9 wk, p = 0.031), and diagnostic uncertainty on admission (77% vs 25.1%, p < 0.001). Generalized linear mixed models determined that atypical presentation (odds ratio [OR] 4.58; 95% CI, 0.94-17.1) and diagnostic uncertainty on admission (OR 9.67; 95% CI, 2.86-44.0) were significantly associated with diagnostic error.

CONCLUSIONS

Among critically ill children, 1.5% had a diagnostic error up to 7 days after PICU admission. Diagnostic errors were associated with atypical presentations and diagnostic uncertainty on admission, suggesting possible targets for intervention.

[Time to Antibiotics (TTA) - Reassessment from the German Working Group for Fever and Neutropenia in Children and Adolescents (DGPI/GPOH)]

BACKGROUND

The current German guidance from 2016 recommends a Time to Antibiotics (TTA) of<60 min in children and adolescents with febrile neutropenia (FN).

METHODS

Critical analysis of available studies and recent meta-analyses, and discussion of the practical consequences in the FN working group of the German Societies for Paediatric Oncology and Haematology and Paediatric Infectious Diseases.

RESULTS

The available evidence does not support a clinically significant outcome benefit of a TTA<60 min in all paediatric patients with FN. Studies suggesting such a benefit are biased (mainly triage bias), use different TTA definitions and display further methodical limitations. In any case, a TTA<60 min remains an essential component of the 1st hour-bundle in paediatric cancer patients with septic shock or sepsis with organ dysfunction.

CONCLUSION

Provided that all paediatric FN patients receive a structured medical history and physical examination (including vital signs) by experienced and trained medical personnel in a timely fashion, and provided that a sepsis triage and management bundle is established and implemented, a TTA lower than 3 hours is sufficient and reasonable in stable paediatric cancer patients with FN.

A Temperature- and Age-Adjusted Shock Index for Emergency Department Identification of Pediatric Sepsis

OBJECTIVE

To empirically derive a novel temperature- and age-adjusted mean shock index (TAMSI) for early identification of sepsis and septic shock in children with suspected infection.

METHODS

We performed a retrospective cohort study of children aged 1 month to <18 years presenting to a single emergency department with suspected infection over a 10-year period. TAMSI was defined as (pulse rate - 10 × [temperature - 37])/(mean arterial pressure). The primary outcome was sepsis, and the secondary outcome was septic shock. In the two-thirds training set, we determined TAMSI cutoffs for each age group using a minimum sensitivity of 85% and Youden Index. In the one-third validation data set, we calculated test characteristics for the TAMSI cutoffs and compared them with those for the Pediatric Advanced Life Support (PALS) tachycardia or systolic hypotension cutoffs.

RESULTS

In the sepsis validation data set, the sensitivity-targeting TAMSI cutoff yielded a sensitivity of 83.5% (95% confidence interval [CI] 81.7% to 85.4%) and specificity of 42.8% (95% CI 42.4% to 43.3%) versus a sensitivity of 77.7% (95% CI 75.7% to 79.8%) and specificity of 60.0% (95% CI 59.5% to 60.4%) for PALS. For septic shock, the sensitivity-targeting TAMSI cutoff achieved a sensitivity of 81.3% (95% CI 75.2% to 87.4%) and a specificity of 83.5% (95% CI 83.2% to 83.8%) versus a sensitivity of 91.0% (95% CI 86.5% to 95.5%) and a specificity of 58.8% (95% CI 58.4% to 59.3%) for PALS. TAMSI yielded an increased positive likelihood ratio and similar negative likelihood ratio versus PALS.

CONCLUSIONS

TAMSI achieved a similar negative likelihood ratio and improved positive likelihood ratio compared with PALS vital sign cutoffs for the prediction of septic shock, but it did not improve on PALS for sepsis prediction, among children with suspected infection.

Pediatric Cardiac Arrest and Resuscitation

Pediatric cardiac arrest in the emergency department is rare. We emphasize the importance of preparedness for pediatric cardiac arrest and offer strategies for the optimal recognition and care of patients in cardiac arrest and peri-arrest. This article focuses on both prevention of arrest and the key elements of pediatric resuscitation that have been shown to improve outcomes for children in cardiac arrest. Finally, we review changes to the American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care that were published in 2020.

A sepsis trigger tool reduces time to antibiotic administration in the NICU

OBJECTIVE

Prolonged time to antibiotic administration is associated with increased morbidity and mortality. Interventions to decrease the time to antibiotic administration may improve mortality and morbidity.

STUDY DESIGN

We identified possible change concepts for reducing time to antibiotic usage in the NICU. For the initial intervention, we developed a sepsis screening tool based on NICU-specific parameters. The main goal of the project was to reduce time to antibiotic administration by 10%.

RESULTS

The project was conducted from April 2017 until April 2019. There were no missed cases of sepsis in the project period. Time to antibiotic administration for patients who were started on antibiotics decreased during the project, with the mean shifting from 126 to 102 min, a reduction of 19%.

CONCLUSIONS

We successfully reduced time to antibiotic delivery in our NICU using a trigger tool to identifying potential cases of sepsis in the NICU environment. The trigger tool requires broader validation.

Reduction of Very Rapid Emergency Transfers to the Pediatric Intensive Care Unit

Introduction

Emergency transfers are associated with increased inpatient pediatric mortality. Therefore, interventions to improve system-level situational awareness were utilized to decrease a subset of emergency transfers that occurred within four hours of admission to an inpatient medical-surgical unit called very rapid emergency transfers (VRET). Specifically, we aimed to increase the days between VRET from non-ICU inpatient units from every 10 days to every 25 days over 1 year.

Methods

Using the Model for Improvement, we developed an interdisciplinary team to reduce VRET. The key drivers targeted were the admission process from the emergency department and ambulatory clinics, sepsis recognition and communication, and expansion of our situational awareness framework. Days between VRET defined the primary outcome metric for this improvement project.

Results

After six months of interventions, our baseline improved from a VRET every 10 days to every 79 days, followed by another shift to 177 days, which we sustained for 3 years peaking at 468 days between events.

Conclusion

Interventions targeting multiple admission sources to improve early recognition and communication of potential clinical deterioration effectively reduced and nearly eliminated VRET at our organization.

Utilizing big data from electronic health records in pediatric clinical care

Big data has the capacity to transform both pediatric healthcare delivery and research, but its potential has yet to be fully realized. Curation of large multi-institutional datasets of high-quality data has allowed for significant advances in the timeliness of quality improvement efforts. Improved access to large datasets and computational power have also paved the way for the development of high-performing, data-driven decision support tools and precision medicine approaches. However, implementation of these approaches and tools into pediatric practice has been hindered by challenges in our ability to adequately capture the heterogeneity of the pediatric population as well as the nuanced complexities of pediatric diseases such as sepsis. Moreover, there are large gaps in knowledge and definitive evidence demonstrating the utility, usability, and effectiveness of these types of tools in pediatric practice, which presents significant challenges to provider willingness to leverage these solutions. The next wave of transformation for pediatric healthcare delivery and research through big data and sophisticated analytics will require focusing efforts on strategies to overcome cultural barriers to adoption and acceptance. IMPACT: Big data from EHRs can be used to drive improvement in pediatric clinical care. Clinical decision support, artificial intelligence, machine learning, and precision medicine can transform pediatric care using big data from the EHR. This article provides a review of barriers and enablers for the effective use of data analytics in pediatric clinical care using pediatric sepsis as a use case. The impact of this review is that it will inform influencers of pediatric care about the importance of current trends in data analytics and its use in improving outcomes of care through EHR-based strategies.

Characteristics and Outcomes of Sepsis Presenting in Inpatient Pediatric Settings

OBJECTIVE

The pediatric sepsis literature lacks studies examining the inpatient setting, yet sepsis remains a leading cause of death in children's hospitals. More information is needed about sepsis arising in patients already hospitalized to improve morbidity and mortality outcomes. This study describes the clinical characteristics, process measures, and outcomes of inpatient sepsis cases compared with emergency department (ED) sepsis cases within the Improving Pediatric Sepsis Outcomes data registry from 46 hospitals that care for children.

METHODS

This retrospective cohort study included Improving Pediatric Sepsis Outcomes sepsis cases from January 2017 to December 2019 with onset in inpatient or ED. We used descriptive statistics to compare inpatient and ED sepsis metrics and describe inpatient sepsis outcomes.

RESULTS

The cohort included 26 855 cases; 8.4% were inpatient and 91.6% were ED. Inpatient cases had higher sepsis-attributable mortality (2.0% vs 1.4%, P = .025), longer length of stay after sepsis recognition (9 vs 5 days, P <.001), more intensive care admissions (57.6% vs 54.1%, P = .002), and greater average vasopressor use (18.0% vs 13.6%, P <.001) compared with ED. In the inpatient cohort, >40% of cases had a time from arrival to recognition within 12 hours. In 21% of cases, this time was >96 hours. Improved adherence to sepsis treatment bundles over time was associated with improved 30-day sepsis-attributable mortality for inpatients with sepsis.

CONCLUSIONS

Inpatient sepsis cases had longer lengths of stay, more need for intensive care, and higher vasopressor use. Sepsis-attributable mortality was significantly higher in inpatient cases compared with ED cases and improved with improved sepsis bundle adherence.

Automated digital technologies for supporting sepsis prediction in children: a scoping review protocol

INTRODUCTION

While there have been several literature reviews on the performance of digital sepsis prediction technologies and clinical decision-support algorithms for adults, there remains a knowledge gap in examining the development of automated technologies for sepsis prediction in children. This scoping review will critically analyse the current evidence on the design and performance of automated digital technologies to predict paediatric sepsis, to advance their development and integration within clinical settings.

METHODS AND ANALYSIS

This scoping review will follow Arksey and O'Malley's framework, conducted between February and December 2022. We will further develop the protocol using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. We plan to search the following databases: Association of Computing Machinery (ACM) Digital Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Embase, Google Scholar, Institute of Electric and Electronic Engineers (IEEE), PubMed, Scopus and Web of Science. Studies will be included on children >90 days postnatal to <21 years old, predicted to have or be at risk of developing sepsis by a digitalised model or algorithm designed for a clinical setting. Two independent reviewers will complete the abstract and full-text screening and the data extraction. Thematic analysis will be used to develop overarching concepts and present the narrative findings with quantitative results and descriptive statistics displayed in data tables.

ETHICS AND DISSEMINATION

Ethics approval for this scoping review study of the available literature is not required. We anticipate that the scoping review will identify the current evidence and design characteristics of digital prediction technologies for the timely and accurate prediction of paediatric sepsis and factors influencing clinical integration. We plan to disseminate the preliminary findings from this review at national and international research conferences in global and digital health, gathering critical feedback from multidisciplinary stakeholders. SCOPING REVIEW REGISTRATION: https://osf.io/veqha/?view_only=f560d4892d7c459ea4cff6dcdfacb086.

Novel biosynthesis of tellurium nanoparticles and investigation of their activity against common pathogenic bacteria

Objectives

Tellurium has received substantial attention for its remarkable properties. This study performed in vitro and in vivo testing of the antibacterial action of tellurium nanoparticles biosynthesized in actinomycetes against methicillin-resistant Staphylococcus aureus (MRSA), a common blood bacterial pathogen.

Methods

Nine actinomycete isolates were tested for their potential to reduce potassium tellurite (K₂TeO₃) and form tellurium nanoparticles (TeNPs). The most efficient actinomycete isolate in producing Tellerium nanoparticles was identified through molecular protocols. The generated TeNPs were characterized using UV, TEM, EDX, XRD and FTIR. The bacterial species implicated in bloodstream infections were detected at El Hussein Hospital. Bacterial identification and antibiotic susceptibility testing were performed using Vitek 2. An animal infection model was used to test the efficacy of the produced TeNPs against the most commonly isolated methicillin-resistant S. aureus using survival assays, colony counting, cytokine assessment and biochemical testing.

Results

The most efficient actinomycete isolate was identified as Streptomyces graminisoli and given the accession number (OL773539). The mean particle size of the produced TeNPs was 21.4 nm, and rods and rosette forms were observed. Methicillin-resistant S. aureus (MRSA) was the main bacterium (60%) causing blood stream infections, and was followed by Escherichia coli (25%) and Klebsiella pneumoniae (15%). The produced TeNPs were tested against MRSA, the bacterium most frequently isolated from blood, and showed a promising action inhibition zone of 24 ± 0.7 mm and an MIC of 50 μg/ml. An animal infection model indicated the promise of TeNPs alone or in combination with standard drugs to combat MRSA in a rat intravenous infection model.

Conclusion

TeNPs combined with vancomycin have successive impact to combat bacteremia for further verification of results.

Proteomics Combined with RNA Sequencing to Screen Biomarkers of Sepsis

Purpose

To screen biomarkers in the serum of patients with sepsis by proteomics combined with RNA sequencing technology, and to find new diagnostic and therapeutic targets for sepsis.

Patients and Methods

Blood samples of 22 sepsis patients (sepsis group) and 10 healthy volunteers (normal group) were collected from January 2019 to December 2020. Data-independent acquisition (DIA) method was employed for protein profiling, RNA sequencing was employed for gene sequencing. Subsequently, quality control and differential analysis (FC≥2; FDR<0.05) of DIA data and RNA sequencing data were performed. Then we identified expression trend-consistent divergence factors by nine-quadrant analysis; subsequent protein-protein interaction (PPI) and gene ontology (GO) functional enrichment analysis of intersection factors was performed, and meta-analysis of targets at transcriptome level was implemented using public datasets. Finally, five Peripheral blood mononuclear cell (PBMC) samples (NC=2; SIRS=1; SEPSIS =2) were collected, and cell localization analysis of core genes was performed by 10× single-cell RNA sequencing (scRNA-seq).

Results

Compared with the normal group, there were 4681 differentially expressed genes and 202 differentially expressed proteins in the sepsis group. Among them, 25 factors were expressed in both proteome and transcriptome, and the analysis of PPI and GO found that they were mainly involved in biological processes such as white blood cell and neutrophil response, inflammatory and immune response. Four core genes GSTO1, C1QA, RETN, and GRN were screened by meta-analysis, all of which were highly expressed in the sepsis group compared with the normal group (P<0.05); scRNA-seq showed the core genes were mainly localized in macrophage cell lines.

Conclusion

The core genes GSTO1, C1QA, RETN and GRN are mainly expressed in macrophages, widely involved in inflammation and immune responses, and are highly expressed in plasma in the sepsis, suggesting that they may become potential research targets for sepsis.

Impact of an electronic alert system for pediatric sepsis screening a tertiary hospital experience

This study aimed to assess the potential impact of implementing an electronic alert system (EAS) for systemic inflammatory syndrome (SIRS) and sepsis in pediatric patients mortality. This retrospective study had a pre and post design. We enrolled patients aged ≤ 14 years who were diagnosed with sepsis/severe sepsis upon admission to the pediatric intensive care unit (PICU) of our tertiary hospital from January 2014 to December 2018. We implemented an EAS for the patients with SIRS/sepsis. The patients who met the inclusion criteria pre-EAS implementation comprised the control group, and the group post-EAS implementation was the experimental group. Mortality was the primary outcome, while length of stay (LOS) and mechanical ventilation in the first hour were the secondary outcomes. Of the 308 enrolled patients, 147 were in the pre-EAS group and 161 in the post-EAS group. In terms of mortality, 44 patients in the pre-EAS group and 28 in the post-EAS group died (p 0.011). The average LOS in the PICU was 7.9 days for the pre-EAS group and 6.8 days for the post-EAS group (p 0.442). Considering the EAS initiation time as the "zero time", early recognition of SIRS and sepsis via the EAS led to faster treatment interventions in post-EAS group, which included fluid boluses with median (25th, 75th percentile) time of 107 (37, 218) min vs. 30 (11,112) min, p < 0.001) and time to initiate antimicrobial therapy median (25th, 75th percentile) of 170.5 (66,320) min vs. 131 (53,279) min, p 0.042). The difference in mechanical ventilation in the first hour of admission was not significant between the groups (25.17% vs. 24.22%, p 0.895). The implementation of the EAS resulted in a statistically significant reduction in the mortality rate among the patients admitted to the PICU in our study. An EAS can play an important role in saving lives and subsequent reduction in healthcare costs. Further enhancement of systematic screening is therefore highly recommended to improve the prognosis of pediatric SIRS and sepsis. The implementation of the EAS, warrants further validation in multicenter or national studies.