The Surviving Sepsis Campaign: research priorities for the administration, epidemiology, scoring and identification of sepsis

Blood calprotectin as a biomarker for infection and sepsis - the prospective CASCADE trial

BACKGROUND

Early in the host-response to infection, neutrophils release calprotectin, triggering several immune signalling cascades. In acute infection management, identifying infected patients and stratifying these by risk of deterioration into sepsis, are crucial tasks. Recruiting a heterogenous population of patients with suspected infections from the emergency department, early in the care-path, the CASCADE trial aimed to evaluate the accuracy of blood calprotectin for detecting bacterial infections, estimating disease severity, and predicting clinical deterioration.

METHODS

In a prospective, observational trial from February 2021 to August 2022, 395 patients (n = 194 clinically suspected infection; n = 201 controls) were enrolled. Blood samples were collected at enrolment. The accuracy of calprotectin to identify bacterial infections, and to predict and identify sepsis and mortality was analysed. These endpoints were determined by a panel of experts.

RESULTS

The Area Under the Receiver Operating Characteristic (AUROC) of calprotectin for detecting bacterial infections was 0.90. For sepsis within 72 h, calprotectin's AUROC was 0.83. For 30-day mortality it was 0.78. In patients with diabetes, calprotectin had an AUROC of 0.94 for identifying bacterial infection.

CONCLUSIONS

Calprotectin showed notable accuracy for all endpoints. Using calprotectin in the emergency department could improve diagnosis and management of severe infections, in combination with current biomarkers.

CLINICAL TRIAL REGISTRATION NUMBER

DRKS00020521.

Biomarkers in Sepsis: A Current Review of New Technologies

Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.

The relationship between lactate dehydrogenase to albumin ratio and all-cause mortality during ICU stays in patients with sepsis: A retrospective cohort study with propensity score matching

Background

Sepsis is a prevalent and severe medical condition which is frequently observed in the intensive care unit (ICU). Although numerous biomarkers have been identified to predict the prognosis of sepsis, the lactate dehydrogenase to albumin ratio (LDH/ALB ratio) has not been extensively investigated. The principal objective of this study is to assess the relationship between LDH/ALB ratio and all-cause mortality in patients with sepsis.

Methods

This study included all adult critically ill patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.0) database. Propensity score matching (PSM) analysis was conducted to mitigate bias, and Kaplan-Meier curves were performed to evaluate the cumulative survival across different groups. The association between the LDH/ALB ratio and mortality was examined through restricted cubic spline (RCS) analysis and Cox regression analysis. The robustness of the findings was confirmed through subgroup analyses. Additionally, the prognostic capability of the LDH/ALB ratio was further evaluated using receiver operating characteristic (ROC) curve analysis.

Results

There were 6059 adult patients with sepsis enrolled in the final analysis. RCS revealed a non-linear relationship between the LDH/ALB ratio and an increased risk of ICU all-cause mortality (χ2 = 46.900, P < 0.001). Following PSM analysis, 1553 matched pairs were obtained. As comparison to the low LDH/ALB ratio group, the mortality rate in the high LDH/ALB ratio group was significantly higher (P < 0.001). Kaplan-Meier curves, both before and after PSM, revealed that the ICU cumulative survival rate for patients with sepsis was significantly lower in the high LDH/ALB ratio group compared to the low LDH/ALB ratio group (χ2 = 93.360, P < 0.001; χ2 = 14.400, P < 0.001). Even after adjusting for a range of potential confounders, multivariate Cox regression analysis indicated that an elevated LDH/ALB ratio was a significant predictor of all-cause mortality in these patients. ROC curve analysis demonstrated that the LDH/ALB ratio had an area under the ROC curve (AUC) of 0.688 for predicting ICU mortality, with a sensitivity of 69.2% and a specificity of 58.6%.

Conclusions

An elevated LDH/ALB ratio (≥10.57) was associated with all-cause mortality in critically ill patients with sepsis, and it might serve as a prognostic marker. Clinicians should pay closer attention to sepsis patients presenting with an LDH/ALB ratio of 10.57 or higher.

Continuous monitoring of physiological data using the patient vital status fusion score in septic critical care patients

Accurate and standardized methods for assessing the vital status of patients are crucial for patient care and scientific research. This study introduces the Patient Vital Status (PVS), which quantifies and contextualizes a patient's physical status based on continuous variables such as vital signs and deviations from age-dependent normative values. The vital signs, heart rate, oxygen saturation, respiratory rate, mean arterial blood pressure, and temperature were selected as input to the PVS pipeline. The method was applied to 70 pediatric patients in the intensive care unit (ICU), and its efficacy was evaluated by matching high values with septic events at different time points in patient care. Septic events included systemic inflammatory response syndrome (SIRS) and suspected or proven sepsis. The comparison of maximum PVS values between the presence and absence of a septic event showed significant differences (SIRS/No SIRS: p < 0.0001, η2 = 0.54; Suspected Sepsis/No Suspected Sepsis: p = 0.00047, η2 = 0.43; Proven Sepsis/No Proven Sepsis: p = 0.0055, η2 = 0.34). A further comparison between the most severe PVS in septic patients with the PVS at ICU discharge showed even higher effect sizes (SIRS: p < 0.0001, η2 = 0.8; Suspected Sepsis: p < 0.0001, η2 = 0.8; Proven Sepsis: p = 0.002, η2 = 0.84). The PVS is emerging as a data-driven tool with the potential to assess a patient's vital status in the ICU objectively. Despite real-world data challenges and potential annotation biases, it shows promise for monitoring disease progression and treatment responses. Its adaptability to different disease markers and reliance on age-dependent reference values further broaden its application possibilities. Real-time implementation of PVS in personalized patient monitoring may be a promising way to improve critical care. However, PVS requires further research and external validation to realize its true potential.

Applying Machine Learning to Blood Count Data Predicts Sepsis with ICU Admission

BACKGROUND

Timely diagnosis is crucial for sepsis treatment. Current machine learning (ML) models suffer from high complexity and limited applicability. We therefore created an ML model using only complete blood count (CBC) diagnostics.

METHODS

We collected non-intensive care unit (non-ICU) data from a German tertiary care centre (January 2014 to December 2021). Using patient age, sex, and CBC parameters (haemoglobin, platelets, mean corpuscular volume, white and red blood cells), we trained a boosted random forest, which predicts sepsis with ICU admission. Two external validations were conducted using data from another German tertiary care centre and the Medical Information Mart for Intensive Care IV database (MIMIC-IV). Using the subset of laboratory orders also including procalcitonin (PCT), an analogous model was trained with PCT as an additional feature.

RESULTS

After exclusion, 1 381 358 laboratory requests (2016 from sepsis cases) were available. The CBC model shows an area under the receiver operating characteristic (AUROC) of 0.872 (95% CI, 0.857-0.887). External validations show AUROCs of 0.805 (95% CI, 0.787-0.824) for University Medicine Greifswald and 0.845 (95% CI, 0.837-0.852) for MIMIC-IV. The model including PCT revealed a significantly higher AUROC (0.857; 95% CI, 0.836-0.877) than PCT alone (0.790; 95% CI, 0.759-0.821; P < 0.001).

CONCLUSIONS

Our results demonstrate that routine CBC results could significantly improve diagnosis of sepsis when combined with ML. The CBC model can facilitate early sepsis prediction in non-ICU patients with high robustness in external validations. Its implementation in clinical decision support systems has strong potential to provide an essential time advantage and increase patient safety.

The Predictors of Perceived Barriers and Facilitators of Applying Sepsis Six Guidelines Among Critical Care Nurses

BACKGROUND

Sepsis is a life-threatening condition that demands quick and cautious interventions from nurses, as they are the frontline caregivers, so they are essential in recognizing early signs of sepsis, initiating prompt healthcare interventions, and providing comprehensive care to improve patient outcomes. This study aimed to examine the predictors of perceived barriers and facilitators of applying evidence-based sepsis guidelines among critical care nurses.

METHODS

This cross-sectional descriptive study was conducted on a convenience sample of 180 nurses working in critical care settings (ICU, critical care unit, ED, burning unit, dialysis unit) at a university hospital. A valid and reliable questionnaire was used to examine the predictors of perceived barriers and facilitators of applying evidence-based sepsis guidelines among critical care nurses.

RESULTS

This study revealed that the main barriers faced by critical care nurses are lack of sepsis recognition during observational rounds and delay in sepsis diagnosis by medical staff. For the most common facilitators of applying Sepsis Six guidelines, the participating nurses reported the presence of a written tool/protocol for sepsis identification and management.

CONCLUSIONS

The study emphasized the importance of the presence of evidence-based protocols for sepsis assessment and management and nurses' compliance with guidelines. Ongoing education training for nurses and providing step-by-step written checklists are a cornerstone to improving nurses' knowledge and the practical skills of early identification and management of sepsis.

Surviving Sepsis Campaign Research Priorities 2023

OBJECTIVES

To identify research priorities in the management, epidemiology, outcome, and pathophysiology of sepsis and septic shock.

DESIGN

Shortly after publication of the most recent Surviving Sepsis Campaign Guidelines, the Surviving Sepsis Research Committee, a multiprofessional group of 16 international experts representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine, convened virtually and iteratively developed the article and recommendations, which represents an update from the 2018 Surviving Sepsis Campaign Research Priorities.

METHODS

Each task force member submitted five research questions on any sepsis-related subject. Committee members then independently ranked their top three priorities from the list generated. The highest rated clinical and basic science questions were developed into the current article.

RESULTS

A total of 81 questions were submitted. After merging similar questions, there were 34 clinical and ten basic science research questions submitted for voting. The five top clinical priorities were as follows: 1) what is the best strategy for screening and identification of patients with sepsis, and can predictive modeling assist in real-time recognition of sepsis? 2) what causes organ injury and dysfunction in sepsis, how should it be defined, and how can it be detected? 3) how should fluid resuscitation be individualized initially and beyond? 4) what is the best vasopressor approach for treating the different phases of septic shock? and 5) can a personalized/precision medicine approach identify optimal therapies to improve patient outcomes? The five top basic science priorities were as follows: 1) How can we improve animal models so that they more closely resemble sepsis in humans? 2) What outcome variables maximize correlations between human sepsis and animal models and are therefore most appropriate to use in both? 3) How does sepsis affect the brain, and how do sepsis-induced brain alterations contribute to organ dysfunction? How does sepsis affect interactions between neural, endocrine, and immune systems? 4) How does the microbiome affect sepsis pathobiology? 5) How do genetics and epigenetics influence the development of sepsis, the course of sepsis and the response to treatments for sepsis?

CONCLUSIONS

Knowledge advances in multiple clinical domains have been incorporated in progressive iterations of the Surviving Sepsis Campaign guidelines, allowing for evidence-based recommendations for short- and long-term management of sepsis. However, the strength of existing evidence is modest with significant knowledge gaps and mortality from sepsis remains high. The priorities identified represent a roadmap for research in sepsis and septic shock.

Decrease in Mortality after the Implementation of a Hospital Model to Improve Performance in Sepsis Care: Princess Sepsis Code

Sepsis is a time-dependent disease whose prognosis is influenced by early diagnosis and therapeutic measures. Mortality from sepsis remains high, and for this reason, the guidelines of the Surviving Sepsis Campaign recommend establishing specific care programs aimed at patients with sepsis. We present the results of the application of a hospital model to improve performance in sepsis care, called Princess Sepsis Code, with the aim of reducing mortality. A retrospective study was conducted using clinical, epidemiological, and outcome variables in patients diagnosed with sepsis from 2015 to 2022. A total of 2676 patients were included, 32% of whom required admission to the intensive care unit, with the most frequent focus of the sepsis being abdominal. Mortality in 2015, at the beginning of the sepsis code program, was 24%, with a declining rate noted over the study period, with mortality reaching 17% in 2022. In the multivariate analysis, age > 70 years, respiratory rate > 22 rpm, deterioration in the level of consciousness, serum lactate > 2 mmol/L, creatinine > 1.6 mg/dL, and the focus of the sepsis were identified as variables independently related to mortality. The implementation of the Princess Sepsis Code care model reduces the mortality of patients exhibiting sepsis and septic shock.

Molecular antimicrobial susceptibility testing in sepsis

Rapidly detecting and identifying pathogens is crucial for appropriate antimicrobial therapy in patients with sepsis. Conventional diagnostic methods have been a great asset to medicine, though they are time consuming and labor intensive. This work will enable healthcare professionals to understand the bacterial community better and enhance their diagnostic capacity by using novel molecular methods that make obtaining quicker, more precise results possible. The authors discuss and critically assess the merits and drawbacks of molecular testing and the added value of these tests, including the shift turnaround time, the implication for clinicians' decisions, gaps in knowledge, future research directions and novel insights or innovations. The field of antimicrobial molecular testing has seen several novel insights and innovations to improve the diagnosis and management of infectious diseases.

Artificial intelligence in emergency medicine. A systematic literature review

Motivation and objective: Emergency medicine is becoming a popular application area for artificial intelligence methods but remains less investigated than other healthcare branches. The need for time-sensitive decision-making on the basis of high data volumes makes the use of quantitative technologies inevitable. However, the specifics of healthcare regulations impose strict requirements for such applications. Published contributions cover separate parts of emergency medicine and use disparate data and algorithms. This study aims to systematize the relevant contributions, investigate the main obstacles to artificial intelligence applications in emergency medicine, and propose directions for further studies.

METHODS

The contributions selection process was conducted with systematic electronic databases querying and filtering with respect to established exclusion criteria. Among the 380 papers gathered from IEEE Xplore, ACM Digital Library, Springer Library, ScienceDirect, and Nature databases 116 were considered to be a part of the survey. The main features of the selected papers are the focus on emergency medicine and the use of machine learning or deep learning algorithms.

FINDINGS AND DISCUSSION

The selected papers were classified into two branches: diagnostics-specific and triage-specific. The former ones are focused on either diagnosis prediction or decision support. The latter covers such applications as mortality, outcome, admission prediction, condition severity estimation, and urgent care prediction. The observed contributions are highly specialized within a single disease or medical operation and often use privately collected retrospective data, making them incomparable. These and other issues can be addressed by creating an end-to-end solution based on human-machine interaction.

CONCLUSION

Artificial intelligence applications are finding their place in emergency medicine, while most of the corresponding studies remain isolated and lack higher generalization and more sophisticated methodology, which can be a matter of forthcoming improvements.

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.

SEPSIS UNIT IN THE EMERGENCY DEPARTMENT: IMPACT ON MANAGEMENT AND OUTCOME OF SEPTIC PATIENTS

ABSTRACT

Study hypothesis : Implementation of a new pathway dedicated to septic patients within the emergency department (ED) would improve early management, organ dysfunction, and outcome. Methods: During phase 1, all consecutive adult patients with infection and qualifying quick Sequential Organ Failure Assessment (qSOFA) score upon ED admission were managed according to standards of care. A multifaceted intervention was then performed (implementation phase): educational program, creation of a sepsis alert upon ED admission incorporated in the professional software, together with severity scores and Surviving Sepsis Campaign (SSC) bundle reminders, and dedication of two rooms to the management of septic patients (sepsis unit). During phase 2, patients were managed according to this new organization. Results: Of the 89,040 patients admitted to the ED over the two phases, 2,643 patients (3.2%) had sepsis including 277 with a qualifying qSOFA score on admission (phase 1, 141 patients; phase 2, 136 patients). Recommendations of SSC 3-h bundle significantly improved between the two periods regarding lactate measurement (87% vs. 96%, P = 0.006), initiation of fluid resuscitation (36% vs. 65%, P < 0.001), blood cultures sampling (83% vs. 93%, P = 0.014), and administration of antibiotics (18% vs. 46%, P < 0.001). The Sequential Organ Failure Assessment score between H0 and H12 varied significantly more during phase 2 (1.9 ± 1.9 vs. 0.8 ± 2.6, P < 0.001). Mortality significantly decreased during the second phase, on day 3 (28% vs. 15%, P = 0.008) and on day 28 (40% vs. 28%, P = 0.013). Conclusion: Systematic detection, education, and per protocol organization with a sepsis unit dedicated to the early management of septic patients appear to improve compliance with SSC bundles, organ dysfunction, and short-term mortality. These results warrant to be confirmed by prospective studies.

Development of a mobile application for health education about sepsis

OBJECTIVE

To develop and validate a mobile application for health education about sepsis.

METHOD

Methodological study composed of two stages. Firstly, information from the Latin American Sepsis Institute and Global Sepsis Alliance was used, followed by putting together, design and layout of the application, according to the agile development model proposed by Sommerville. In the second stage, content validation occurred with 20 health professionals with expertise in the areas of intensive care and sepsis, from the use of the Instrument for Validation of Educational Content in Health through analyzing objectives, structure and relevance; and it was considered valid the item with a minimum agreement of 80%, by binomial test.

RESULTS

The app presents 15 screens that encompass prevention measures, recognition and early identification of sepsis, illustrated by interactive images. Out of the 18 items evaluated in the validation process, the minimum agreement obtained was 0.95 and the average validation index was 0.99.

CONCLUSION

The application was developed and considered valid by the referees regarding contents. Thus, it is an important technological resource for health education in prevention and early identification of sepsis.

Direct and indirect effects of socioeconomic status on sepsis risk and mortality: a mediation analysis of the HUNT Study

BACKGROUND

Socioeconomic status (SES) may influence risk of sepsis and sepsis-related mortality, but to what extent lifestyle and health-related factors mediate this effect is not known.

METHODS

The study included 65 227 participants of the population-based HUNT Study in Norway linked with hospital records to identify incident sepsis and sepsis-related deaths. Cox regression estimated HRs of sepsis risk and mortality associated with different indicators of SES, whereas mediation analyses were based on an inverse odds weighting approach.

RESULTS

During ~23 years of follow-up (1.3 million person-years), 4200 sepsis cases and 1277 sepsis-related deaths occurred. Overall, participants with low SES had a consistently increased sepsis risk and sepsis-related mortality using education, occupational class and financial difficulties as indicators of SES. Smoking and alcohol consumption explained 57% of the sepsis risk related to low education, whereas adding risk factors of cardiovascular disease and chronic diseases to the model increased the explained proportion to 78% and 82%, respectively.

CONCLUSION

This study shows that SES is inversely associated with sepsis risk and mortality. Approximately 80% of the effect of education on sepsis risk was explained by modifiable lifestyle and health-related factors that could be targets for prevention.

Albumin versus balanced crystalloid for resuscitation in the treatment of sepsis: A protocol for a randomised controlled feasibility study, "ABC-Sepsis"

Background

Patients presenting with suspected sepsis to secondary care often require fluid resuscitation to correct hypovolaemia and/or septic shock. Existing evidence signals, but does not demonstrate, a benefit for regimes including albumin over balanced crystalloid alone. However, interventions may be started too late, missing a critical resuscitation window.

Methods

ABC Sepsis is a currently recruiting randomised controlled feasibility trial comparing 5% human albumin solution (HAS) with balanced crystalloid for fluid resuscitation in patients with suspected sepsis. This multicentre trial is recruiting adult patients within 12 hours of presentation to secondary care with suspected community acquired sepsis, with a National Early Warning Score ≥5, who require intravenous fluid resuscitation. Participants are randomised to 5% HAS or balanced crystalloid as the sole resuscitation fluid for the first 6 hours.

Objectives

Primary objectives are feasibility of recruitment to the study and 30-day mortality between groups. Secondary objectives include in-hospital and 90-day mortality, adherence to trial protocol, quality of life measurement and secondary care costs.

Discussion

This trial aims to determine the feasibility of conducting a trial to address the current uncertainty around optimal fluid resuscitation of patients with suspected sepsis. Understanding the feasibility of delivering a definitive study will be dependent on how the study team are able to negotiate clinician choice, Emergency Department pressures and participant acceptability, as well as whether any clinical signal of benefit is detected.

NAMPT-associated gene signature in the prediction of severe sepsis

OBJECTIVE

Sepsis is a life-threatening condition of severe organ dysfunction induced by uncontrolled infection and dysregulated host response. However, standardized clinical biomarkers for sepsis are needed to improve patient care, especially in intensive care units (ICUs). Nicotinamide phosphoribosyltransferase (NAMPT) regulates the activity of nicotinamide adenine dinucleotide (NAD)-dependent enzymes and modulates multiple metabolic pathways. Elevated NAMPT gene expression is a risk factor in the pathogenesis and development of sepsis, which is strongly linked to patient morbidity and ICU mortality. At present, there is no identified NAMPT gene signature for prognosis of sepsis patients.

METHODS

By analyzing gene expression profiles in peripheral blood mononuclear cells, this study was designed to establish a NAMPT-associated biomarker that effectively predicts survival in sepsis patients.

RESULTS

We obtained 19 common genes by intersecting NAMPT-associated genes and sepsis survival-related genes, and this 19-gene signature is significantly enriched in metabolic pathways and NF-κB pathways related to sepsis development. Notably, this 19-gene NAMPT signature was able to discriminate high-risk sepsis from low-risk sepsis in both discovery and validation cohorts. Furthermore, we confirmed that this 19-gene NAMPT signature performed significantly better for sepsis prognosis than random gene sets with 19 genes.

CONCLUSIONS

We identified a novel NAMPT gene signature with effective prognostic power for sepsis. Further studies focusing on these biomarkers may also provide an early intervention system for sepsis treatment.

Genetic Variants of Matrix Metalloproteinase and Sepsis: The Need Speed Study

Many causal mechanisms in sepsis susceptibility are largely unknown and the functional genetic polymorphisms (GP) of matrix metalloproteinases (MMPs) and their natural tissue inhibitor of MMPs (TIMP1) could play a role in its development. GPs of MMPs and TIMP (namely MMP-1 rs1799750, MMP-3 rs3025058, MMP-8 rs11225395, MMP-9 rs2234681, and TIMP-1 rs4898) have been compared in 1058 patients with suspected sepsis to assess the association with susceptibility and etiology of sepsis. Prevalence of MMP8 rs11225395 G/G genotype was higher in sepsis patients than in those with non-infective Systemic Inflammatory Reaction Syndrome (35.6 vs. 26%, hazard ratio, HR 1.56, 95% C.I. 1.04–2.42, p = 0.032). G/G patients developed less hyperthermia (p = 0.041), even after stratification for disease severity (p = 0.003). Patients carrying the 6A allele in MMP3 rs3025058 had a higher probability of microbiologically-proven sepsis (HR 1.4. 95%C.I. 1.01–1.94, p = 0.044), particularly when due to virus (H.R. 2.14, 95% C.I. 1.06–4.31, p = 0.046), while MMP-1 G/G genotype patients carried a higher risk for intracellular bacteria (Chlamydia, Mycoplasma, and Legionella, H.R. 6.46, 95% C.I. 1.58–26.41, p = 0.003). Neither severity of sepsis at presentation, nor 30-day mortality were influenced by the investigated variants or their haplotype. MMP8 rs11225395 G/G carriers have lower temperature at presentation and a more than 50% increased susceptibility to sepsis. Among patients with sepsis, carriers of MMP1 rs1799750 G/G have an increased susceptibility for intracellular pathogen infections, while virus serology is more often positive in those with the MMP3 rs3025058 A/A genotype.

Micro- and nanosensors for detecting blood pathogens and biomarkers at different points of sepsis care

Severe infections can cause a dysregulated response leading to organ dysfunction known as sepsis. Sepsis can be lethal if not identified and treated right away. This requires measuring biomarkers and pathogens rapidly at the different points where sepsis care is provided. Current commercial approaches for sepsis diagnosis are not fast, sensitive, and/or specific enough for meeting this medical challenge. In this article, we review recent advances in the development of diagnostic tools for sepsis management based on micro- and nanostructured materials. We start with a brief introduction to the most popular biomarkers for sepsis diagnosis (lactate, procalcitonin, cytokines, C-reactive protein, and other emerging protein and non-protein biomarkers including miRNAs and cell-based assays) and methods for detecting bacteremia. We then highlight the role of nano- and microstructured materials in developing biosensors for detecting them taking into consideration the particular needs of every point of sepsis care (e.g., ultrafast detection of multiple protein biomarkers for diagnosing in triage, emergency room, ward, and intensive care unit; quantitative detection to de-escalate treatment; ultrasensitive and culture-independent detection of blood pathogens for personalized antimicrobial therapies; robust, portable, and web-connected biomarker tests outside the hospital). We conclude with an overview of the most utilized nano- and microstructured materials used thus far for solving issues related to sepsis diagnosis and point to new challenges for future development.

Critical Care Database Comprising Patients With Infection

Patients treated in the intensive care unit (ICU) are closely monitored and receive intensive treatment. Such aggressive monitoring and treatment will generate high-granularity data from both electronic healthcare records and nursing charts. These data not only provide infrastructure for daily clinical practice but also can help to inform clinical studies. It is technically challenging to integrate and cleanse medical data from a variety of sources. Although there are several open-access critical care databases from western countries, there is a lack of this kind of database for Chinese adult patients. We established a critical care database involving patients with infection. A large proportion of these patients have sepsis and/or septic shock. High-granularity data comprising laboratory findings, baseline characteristics, medications, international statistical classification of diseases (ICD) code, nursing charts, and follow-up results were integrated to generate a comprehensive database. The database can be utilized for a variety of clinical studies. The dataset is fully accessible at PhysioNet(https://physionet.org/content/icu-infection-zigong-fourth/1.0/).

Surviving Sepsis Campaign: Research Opportunities for Infection and Blood Purification Therapies

Patients with infection can develop sepsis, and their mortality can be high. An important aspect in the treatment of sepsis is adequate management of the infection.