Sepsis patients in the emergency department: stratification using the Clinical Impression Score, Predisposition, Infection, Response and Organ dysfunction score or quick Sequential Organ Failure Assessment score?

IMPLICATIONS OF YWHAH GENE EXPRESSION IN THE EARLY DETECTION OF SEPSIS

ABSTRACT

Sepsis, a complex and multifaceted condition, is a common occurrence with serious implications for critically ill patients in the intensive care unit (ICU). The YWHAH gene encodes the 14-3-3n protein, a member of the 14-3-3 protein family. While existing research primarily focuses on the role of 14-3-3n in conditions such as schizophrenia and various cancers, our study revealed that the expression of the YWHAH gene remained relatively stable in both infected individuals and healthy controls. Through Venn plot analysis following weighted gene correlation network analysis, we observed a potential association between elevated YWHAH expression and the transition from infection to sepsis. In a comprehensive analysis of public single-cell transcriptome databases, the expression of YWHAH was found to be distinctive in cases of sepsis and infection. These findings were corroborated through an in vitro analysis utilizing real-time polymerase chain reaction. This study represents the initial identification of variations in YWHAH gene expression between patients with infection and sepsis, potentially offering insights for the development of early detection and treatment strategies for sepsis.

Exploiting the Features of Clinical Judgment to Improve Assessment of Disease Severity in the Emergency Department: An Acutelines Study

BACKGROUND

Clinical judgment, also known as gestalt or gut feeling, can predict deterioration and can be easily and rapidly obtained. To date, it is unknown what clinical judgement precisely entails. The aim of this study was to elucidate which features define the clinical impression of health care professionals in the ED.

METHOD

A nominal group technique (NGT) was used to develop a consensus-based instrument to measure the clinical impression score (CIS, scale 1-10) and to identify features associated with either a more severe or less severe estimated disease severity. This single-center observational cohort study included 517 medical patients visiting the ED. The instrument was prospectively validated.. The predictive value of each feature for the clinical impression was assessed using multivariate linear regression analyses to adjust for potential confounders and validated in the infection group.

RESULTS

The CIS at the ED was associated with ICU admission (OR 1.67 [1.37-2.03], p < 0.001), in-hospital mortality (OR 2.25 [1.33-3.81], p < 0.001), and 28-day mortality (OR 1.33 [1.07-1.65], <0.001). Dry mucous membranes, eye glance, red flags during physical examination, results of arterial blood gas analysis, heart and respiratory rate, oxygen modality, triage urgency, and increased age were associated with a higher estimated disease severity (CIS). On the other hand, behavior of family, self-estimation of the patient, systolic blood pressure, and Glascow Coma Scale were associated with a lower estimated disease severity (CIS).

CONCLUSION

We identified several features that were associated with the clinical impression of health care professionals in the ED. Translating the subjective features and objective measurements into quantifiable parameters may aid the development of a novel triage tool to identify patients at risk of deterioration in the ED.

Comparing In-Hospital Mortality Prediction by Senior Emergency Resident's Judgment and Prognostic Models in the Emergency Department

Background

A comparison of emergency residents' judgments and two derivatives of the Sequential Organ Failure Assessment (SOFA), namely, the mSOFA and the qSOFA, was conducted to determine the accuracy of predicting in-hospital mortality among critically ill patients in the emergency department (ED).

Methods

A prospective cohort research was performed on patients over 18 years of age presented to the ED. We used logistic regression to develop a model for predicting in-hospital mortality by using qSOFA, mSOFA, and residents' judgment scores. We compared the accuracy of prognostic models and residents' judgment in terms of the overall accuracy of the predicted probabilities (Brier score), discrimination (area under the ROC curve), and calibration (calibration graph). Analyses were carried out using R software version R-4.2.0.

Results

In the study, 2,205 patients with median age of 64 (IQR: 50-77) years were included. There were no significant differences between the qSOFA (AUC 0.70; 95% CI: 0.67-0.73) and physician's judgment (AUC 0.68; 0.65-0.71). Despite this, the discrimination of mSOFA (AUC 0.74; 0.71-0.77) was significantly higher than that of the qSOFA and residents' judgments. Additionally, the AUC-PR of mSOFA, qSOFA, and emergency resident's judgments was 0.45 (0.43-0.47), 0.38 (0.36-0.40), and 0.35 (0.33-0.37), respectively. The mSOFA appears stronger in terms of overall performance: 0.13 vs. 0.14 and 0.15. All three models showed good calibration.

Conclusion

The performance of emergency residents' judgment and the qSOFA was the same in predicting in-hospital mortality. However, the mSOFA predicted better-calibrated mortality risk. Large-scale studies should be conducted to determine the utility of these models.

Predicting deterioration of patients with early sepsis at the emergency department using continuous heart rate variability analysis: a model-based approach

BACKGROUND

Sepsis is a life-threatening disease with an in-hospital mortality rate of approximately 20%. Physicians at the emergency department (ED) have to estimate the risk of deterioration in the coming hours or days and decide whether the patient should be admitted to the general ward, ICU or can be discharged. Current risk stratification tools are based on measurements of vital parameters at a single timepoint. Here, we performed a time, frequency, and trend analysis on continuous electrocardiograms (ECG) at the ED to try and predict deterioration of septic patients.

METHODS

Patients were connected to a mobile bedside monitor that continuously recorded ECG waveforms from triage at the ED up to 48 h. Patients were post-hoc stratified into three groups depending on the development of organ dysfunction: no organ dysfunction, stable organ dysfunction or progressive organ dysfunction (i.e., deterioration). Patients with de novo organ dysfunction and those admitted to the ICU or died were also stratified to the group of progressive organ dysfunction. Heart rate variability (HRV) features over time were compared between the three groups.

RESULTS

In total 171 unique ED visits with suspected sepsis were included between January 2017 and December 2018. HRV features were calculated over 5-min time windows and summarized into 3-h intervals for analysis. For each interval, the mean and slope of each feature was calculated. Of all analyzed features, the average of the NN-interval, ultra-low frequency, very low frequency, low frequency and total power were different between the groups at multiple points in time.

CONCLUSIONS

We showed that continuous ECG recordings can be automatically analyzed and used to extract HRV features associated with clinical deterioration in sepsis. The predictive accuracy of our current model based on HRV features derived from the ECG only shows the potential of HRV measurements at the ED. Unlike other risk stratification tools employing multiple vital parameters this does not require manual calculation of the score and can be used on continuous data over time. Trial registration The protocol of this study is published by Quinten et al., 2017.

Recognition of Critically Ill Patients by Acute Health Care Providers: A Multicenter Observational Study

OBJECTIVES

Although the Modified Early Warning Score (MEWS) is increasingly being used in the acute care chain to recognize disease severity, its superiority compared with clinical gestalt remains unproven. Therefore, the aim of this study was to compare the accuracy of medical caregivers and MEWS in predicting the development of critical illness.

DESIGN

This was a multicenter observational prospective study.

SETTING

It was performed in a level-1 trauma center with two different sites and emergency departments (EDs) with a combined capacity of about 50.000 patients annually.

PATIENTS

It included all adult patients presented to the ED by Emergency Medical Services (EMS).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

For all patients, the acute caregivers were asked several standardized questions regarding clinical predicted outcome (clinical gestalt), and the MEWS was calculated. The primary outcome was the occurrence of critical illness, defined as ICU admission, serious adverse events, and mortality within 72 hours. The sensitivity, specificity, and discriminative power of both clinical gestalt and MEWS for the occurrence of critical illness were calculated as the area under the receiver operating characteristic curve (AUROC). Among the total of 800 included patients, 113 patients (14.1%) suffered from critical illness. The specificity for predicting three-day critical illness for all caregivers (for EMS nurses, ED nurses, and physicians) was 93.2%; 97.3%, and 96.8%, respectively, and was significantly (p < 0.01) better than an MEWS score of 3 or higher (70.4%). The sensitivity was significantly lower for EMS and ED nurses, but not significantly different for physicians compared with MEWS. The AUROCs for prediction of 3-day critical illness by both the ED nurses (AUROC = 0.809) and the physicians (AUROC = 0.848) were significantly higher (p = 0.032 and p = 0.010, respectively) compared with MEWS (AUROC = 0.731).

CONCLUSIONS

For patients admitted to the ED by EMS, medical professionals can predict the development of critical illness within 3 days significantly better than the MEWS. Although MEWS is able to correctly predict those patients that become critically ill, its use leads to overestimation due to a substantial number of false positives.

The Value of the First Clinical Impression as Assessed by 18 Observations in Patients Presenting to the Emergency Department

The first clinical impression of emergency patients conveys a myriad of information that has been incompletely elucidated. In this prospective, observational study, the value of the first clinical impression, assessed by 18 observations, to predict the need for timely medical attention, the need for hospital admission, and in-hospital mortality in 1506 adult patients presenting to the triage desk of an emergency department was determined. Machine learning models were used for statistical analysis. The first clinical impression could predict the need for timely medical attention [area under the receiver operating characteristic curve (AUC ROC), 0.73; p = 0.01] and hospital admission (AUC ROC, 0.8; p = 0.004), but not in-hospital mortality (AUC ROC, 0.72; p = 0.13). The five most important features informing the prediction models were age, ability to walk, admission by emergency medical services, lying on a stretcher, breathing pattern, and bringing a suitcase. The inability to walk at triage presentation was highly predictive of both the need for timely medical attention (p < 0.001) and the need for hospital admission (p < 0.001). In conclusion, the first clinical impression of emergency patients presenting to the triage desk can predict the need for timely medical attention and hospital admission. Important components of the first clinical impression were identified.

Sepsis biomarkers and diagnostic tools with a focus on machine learning

Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers.

Performance of early warning and risk stratification scores versus clinical judgement in the acute setting: a systematic review

OBJECTIVE

Risk stratification is increasingly based on Early Warning Score (EWS)-based models, instead of clinical judgement. However, it is unknown how risk-stratification models and EWS perform as compared with the clinical judgement of treating acute healthcare providers. Therefore, we performed a systematic review of all available literature evaluating clinical judgement of healthcare providers to the use of risk-stratification models in predicting patients' clinical outcome.

METHODS

Studies comparing clinical judgement and risk-stratification models in predicting outcomes in adult patients presenting at the ED were eligible for inclusion. Outcomes included the need for intensive care unit (ICU) admission; severe adverse events; clinical deterioration and mortality. Risk of bias among the included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool.

RESULTS

Six studies (6419 participants) were included of which 4 studies were judged to be at high risk of bias. Only descriptive analysis was performed as a meta-analysis was not possible due to few included studies and high clinical heterogeneity. The performance of clinical judgement and risk-stratification models were both moderate in predicting mortality, deterioration and need for ICU admission with area under the curves between 0.70 and 0.89. The performance of clinical judgement did not significantly differ from risk-stratification models in predicting mortality (n=2 studies) or deterioration (n=1 study). However, clinical judgement of healthcare providers was significantly better in predicting the need for ICU admission (n=2) and severe adverse events (n=1 study) as compared with risk-stratification models.

CONCLUSION

Based on limited existing data, clinical judgement has greater accuracy in predicting the need for ICU admission and the occurrence of severe adverse events compared with risk-stratification models in ED patients. However, performance is similar in predicting mortality and deterioration.

PROSPERO REGISTRATION NUMBER

CRD42020218893.

Prehospital administration of broad-spectrum antibiotics for sepsis patients: A systematic review and meta-analysis

Background and Aims

Some studies have suggested that earlier initiation of antibiotics has shown positive outcomes in sepsis patients. We aimed to do a systematic review and meta-analysis to evaluate the effect of prehospital administration of antibiotics on 28 days mortality and length of stay in hospital and intensive care unit for sepsis patients.

Methods

We formulated a search strategy and used it on search databases PubMed, Scopus, Web of Science, and Embase. We then screened the records for eligibility and included controlled studies, either clinical trials or cohort studies reporting prehospital antibiotic administration for sepsis patients. We excluded duplicates, books, conferences' abstracts, case reports, editorials, letters, author responses, not English studies, and studies with nonavailable full text. Animal and lab studies were also excluded.

Results

The total number of studies identified is 1811, 19 were eligible for systematic review and 4 for meta-analysis (three cohort and one clinical trial). The total number of sepsis patients in the four included studies in the 28 days mortality outcome was 3523 (1779 took prehospital antibiotics and 1744 did not take prehospital antibiotics). Of 1779 who took the antibiotics, 190 died, and of 1744 who did not take antibiotics, 292 died (95% confidence interval 0.68-0.97, p = 0.02).

Conclusion

This meta-analysis reveals that receiving prehospital antibiotics can significantly lower mortality in sepsis patients compared to patients who do not receive prehospital antibiotics. However, more clinical trials and multicenter prospective studies with high sample sizes are needed to get strong evidence supporting our findings.

Prospective international validation of the predisposition, infection, response and organ dysfunction (PIRO) clinical staging system among intensive care and general ward patients

Background

Stratifying patients with sepsis was the basis of the predisposition, infection, response and organ dysfunction (PIRO) concept, an attempt to resolve the heterogeneity in treatment response. The purpose of this study is to perform an independent validation of the PIRO staging system in an international cohort and explore its utility in the identification of patients in whom time to antibiotic treatment is particularly important.

Methods

Prospective international cohort study, conducted over a 6-month period in five Portuguese hospitals and one Australian institution. All consecutive adult patients admitted to selected wards or the intensive care, with infections that met the CDC criteria for lower respiratory tract, urinary, intra-abdominal and bloodstream infections were included.

Results

There were 1638 patients included in the study. Patients who died in hospital presented with a higher PIRO score (10 ± 3 vs 8 ± 4, p < 0.001). The observed mortality was 3%, 15%, 24% and 34% in stage I, II, III and IV, respectively, which was within the predicted intervals of the original model, except for stage IV patients that presented a lower mortality. The hospital survival rate was 84%. The application of the PIRO staging system to the validation cohort resulted in a positive predictive value of 97% for stage I, 91% for stage II, 85% for stage III and 66% for stage IV. The area under the receiver operating characteristics curve (AUROC) was 0.75 for the all cohort and 0.70 if only patients with bacteremia were considered. Patients in stage III and IV who did not have antibiotic therapy administered within the desired time frame had higher mortality rate than those who have timely administration of antibiotic.

Conclusions

To our knowledge, this is the first external validation of this PIRO staging system and it performed well on different patient wards within the hospital and in different types of hospitals. Future studies could apply the PIRO system to decision-making about specific therapeutic interventions and enrollment in clinical trials based on disease stage.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13613-021-00966-7.

The timing of use of risk stratification tools affects their ability to predict mortality from sepsis. A meta-regression analysis

Background: Risk stratification tools (RSTs) are used in healthcare settings to identify patients at risk of sepsis and subsequent adverse outcomes. In practice RSTs are used on admission and thereafter as ‘trigger’ tools prompting sepsis management. However, studies investigating their performance report scores at a single timepoint which varies in relation to admission. The aim of this meta-analysis was to determine if the predictive performance of RSTs is altered by the timing of their use. Methods: We conducted a systematic review and meta-regression analysis of studies published from inception to 31 October 2018, using EMBASE and PubMed databases. Any cohort studies investigating the ability of an RST to predict mortality in adult sepsis patients admitted to hospital, from which a 2x2 table was available or could be constructed, were included. The diagnostic performance of RSTs in predicting mortality was the primary outcome. Sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver-operating curve (AUROC) were the primary measures, enabling further meta-regression analysis. Results: 47 studies were included, comprising 430,427 patients. Results of bivariate meta-regression analysis found tools using a first-recorded score were less sensitive than those using worst-recorded score (REML regression coefficient 0.57, 95% CI 0.07-1.08). Using worst-recorded score led to a large increase in sensitivity (summary sensitivity 0.76, 95% CI 0.67-0.83, for worst-recorded scores vs. 0.64 (0.57-0.71) for first-recorded scores). Scoring system type did not have a significant relationship with studies’ predictive ability. The most analysed RSTs were qSOFA (n=37) and EWS (n=14). Further analysis of these RSTs also found timing of their use to be associated with predictive performance. Conclusion: The timing of any RST is paramount to their predictive performance. This must be reflected in their use in practice, and lead to prospective studies in future.

Beyond the bundle: Clinical controversies in the management of sepsis in emergency medicine patients

Sepsis is a condition characterized by life-threatening organ dysfunction caused by a dysregulated host response to infection. The emergency department (ED) serves as a crucial entry point for patients presenting with sepsis. Given the heterogeneous presentation and high mortality rate associated with sepsis and septic shock, several clinical controversies have emerged in the management of sepsis. These include the use of novel therapeutic agents like angiotensin II, hydrocortisone, ascorbic acid, thiamine ("HAT") therapy, and levosimendan, Additionally, controversies with current treatments in vasopressor dosing, and the use of and balanced or unbalanced crystalloid are crucial to consider. The purpose of this review is to discuss clinical controversies in the management of septic patients, including the use of novel medications and dosing strategies, to assist providers in appropriately determining what treatment strategy is best suited for patients.

Validation of the Predisposition Infection Response Organ (PIRO) dysfunction score for the prognostic stratification of patients with sepsis in the Emergency Department

OBJECTIVE

There are many different methods for computing the Predisposition Infection Response Organ (PIRO) dysfunction score. We compared three PIRO methods (PIRO1 (Howell), PIRO2 (Rubulotta) and PIRO3 (Rathour)) for the stratification of mortality and high level of care admission in septic patients arriving at the Emergency Department (ED) of an Italian Hospital.

DESIGN, SETTING AND PARTICIPANTS

We prospectively collected clinical data of 470 patients admitted due to infection in the ED to compute PIRO according to three different methods. We tested PIRO variables for the prediction of mortality in the univariate analysis. Calculation and comparison were made of the area under the receiver operating curve (AUC) for the three PIRO methods, SOFA and qSOFA.

RESULTS

Most of the variables included in PIRO were related to mortality in the univariate analysis. Increased PIRO scores were related to higher mortality. In relation to mortality, PIRO 1 performed better than PIRO2 at 30 d ((AUC 0.77 (0.716-0.824) vs. AUC 0.699 (0.64-0.758) (p=0.03) and similarly at 60 d (AUC 0.767 (0.715-0.819) vs AUC 0.709 (0.656-0.763)(p=0.55)); PIRO1 performed similarly to PIRO3 (AUC 0.765 (0.71-0.82) at 30 d, AUC 0.754 (0.701-0.806) at 60 d, p=ns). Both PIRO1 and PIRO3 were as good as SOFA referred to mortality (AUC 0.758 (0.699, 0.816) at 30 d vs. AUC 0.738 (0.681, 0.795) at 60 d; p=ns). For high level of care admission, PIRO proved inferior to SOFA.

CONCLUSIONS

We support the use of PIRO1, which combines ease of use and the best performance referred to mortality over the short term. PIRO2 proved to be less accurate and more complex to use, suffering from missing microbiological data in the ED setting.

Reverse Engineering of the Pediatric Sepsis Regulatory Network and Identification of Master Regulators

Sepsis remains a leading cause of death in ICUs all over the world, with pediatric sepsis accounting for a high percentage of mortality in pediatric ICUs. Its complexity makes it difficult to establish a consensus on genetic biomarkers and therapeutic targets. A promising strategy is to investigate the regulatory mechanisms involved in sepsis progression, but there are few studies regarding gene regulation in sepsis. This work aimed to reconstruct the sepsis regulatory network and identify transcription factors (TFs) driving transcriptional states, which we refer to here as master regulators. We used public gene expression datasets to infer the co-expression network associated with sepsis in a retrospective study. We identified a set of 15 TFs as potential master regulators of pediatric sepsis, which were divided into two main clusters. The first cluster corresponded to TFs with decreased activity in pediatric sepsis, and GATA3 and RORA, as well as other TFs previously implicated in the context of inflammatory response. The second cluster corresponded to TFs with increased activity in pediatric sepsis and was composed of TRIM25, RFX2, and MEF2A, genes not previously described as acting in a coordinated way in pediatric sepsis. Altogether, these results show how a subset of master regulators TF can drive pathological transcriptional states, with implications for sepsis biology and treatment.

Cohort profile of Acutelines: a large data/biobank of acute and emergency medicine

PURPOSE

Research in acute care faces many challenges, including enrolment challenges, legal limitations in data sharing, limited funding and lack of singular ownership of the domain of acute care. To overcome these challenges, the Center of Acute Care of the University Medical Center Groningen in the Netherlands, has established a de novo data, image and biobank named 'Acutelines'.

PARTICIPANTS

Clinical data, imaging data and biomaterials (ie, blood, urine, faeces, hair) are collected from patients presenting to the emergency department (ED) with a broad range of acute disease presentations. A deferred consent procedure (by proxy) is in place to allow collecting data and biomaterials prior to obtaining written consent. The digital infrastructure used ensures automated capturing of all bed-side monitoring data (ie, vital parameters, electrophysiological waveforms) and securely importing data from other sources, such as the electronic health records of the hospital, ambulance and general practitioner, municipal registration and pharmacy. Data are collected from all included participants during the first 72 hours of their hospitalisation, while follow-up data are collected at 3 months, 1 year, 2 years and 5 years after their ED visit.

FINDINGS TO DATE

Enrolment of the first participant occurred on 1 September 2020. During the first month, 653 participants were screened for eligibility, of which 180 were approached as potential participants. In total, 151 (84%) provided consent for participation of which 89 participants fulfilled criteria for collection of biomaterials.

FUTURE PLANS

The main aim of Acutelines is to facilitate research in acute medicine by providing the framework for novel studies and issuing data, images and biomaterials for future research. The protocol will be extended by connecting with central registries to obtain long-term follow-up data, for which we already request permission from the participant.

TRIAL REGISTRATION NUMBER

NCT04615065.

Comparison of SIRS criteria and qSOFA score for identifying culture-positive sepsis in the emergency department: a prospective cross-sectional multicentre study

OBJECTIVE

To compare the daily practice of two emergency departments (ED) in the Netherlands, where systemic inflammatory response syndrome (SIRS) criteria and quick Sequential Organ Failure Assessment (qSOFA) score are used differently as screening tools for culture-positive sepsis.

DESIGN

A prospective cross-sectional multicentre study.

SETTING

Two EDs at two European clinical teaching hospitals in the Netherlands.

PARTICIPANTS

760 patients with suspected infection who met SIRS criteria or had a qualifying qSOFA score who were treated at two EDs in the Netherlands from 1 January to 1 March 2018 were included.

METHODS

SIRS criteria and qSOFA score were calculated for each patient. The first hospital treated the patients who met SIRS criteria following the worldwide Surviving Sepsis Campaign protocol. At the second hospital, only patients who met the qualifying qSOFA score received this treatment. Therefore, patients could be divided into five groups: (1) SIRS+, qSOFA-, not treated according to protocol (reference group); (2) SIRS+, qSOFA-, treated according to protocol; (3) SIRS+, qSOFA+, treated according to protocol; (4) SIRS-, qSOFA+, not treated according to protocol; (5) SIRS-, qSOFA+, treated according to protocol.

PRIMARY AND SECONDARY OUTCOME MEASURES

To prove culture-positive sepsis was present, cultures were used as the primary outcome. Secondary outcomes were in-hospital mortality and intensive care unit (ICU) admission.

RESULTS

98.9% met SIRS criteria and 11.7% met qSOFA score. Positive predictive values of SIRS criteria and qSOFA score were 41.2% (95% CI 37.4% to 45.2%) and 48.1% (95% CI 37.4% to 58.9%), respectively. HRs were 0.79 (95% CI 0.40 to 1.56, p=0.500), 3.42 (95% CI 1.82 to 6.44, p<0.001), 18.94 (95% CI 2.48 to 144.89, p=0.005) and 4.97 (95% CI 1.44 to 17.16, p=0.011) for groups 2-5, respectively.

CONCLUSION

qSOFA score performed as well as SIRS criteria for identifying culture-positive sepsis and performed significantly better for predicting in-hospital mortality and ICU admission. This study shows that SIRS criteria are no longer necessary and recommends qSOFA score as the standard for identifying culture-positive sepsis in the ED.

TRIAL REGISTRATION NUMBER

NL8315.

Prognostic tools for elderly patients with sepsis: in search of new predictive models

As a tool to support clinical decision-making, Mortality Prediction Models (MPM) can help clinicians stratify and predict patient risk. There are numerous scoring systems for patients with sepsis that predict sepsis-related mortality and the severity of sepsis. But there are currently no MPMs for adults with sepsis who meet the criteria of "good." Clinicians are unlikely to use complex MPMs that require extensive or expensive data collection to impede workflow. Machine learning applied to minimal medical records of patients diagnosed with sepsis can be a useful tool. Progress is needed in the development and validation of clinical decision support tools that can assist in patient risk stratification, prognosis, discussion of patient outcomes, and shared decision making.

Differentiating sepsis from similar groups of symptoms at triage level in emergency care

OBJECTIVES

Conditions that have similar initial presentations as sepsis may make early recognition of sepsis in an emergency room (ER) difficult. We investigated whether selected physiologic and metabolic parameters can be reliably used in the emergency department to differentiate sepsis from other disease states that mimic it, such as dehydration and stroke.

METHODS

Loess regression on retrospective follow-up chart data of patients with sepsis-like symptoms (N = 664) aged 18+ in a large ER in Hungary was used to visualize/identify cutoff points for sepsis risk. A multivariate logistic regression model based on standard triage data was constructed with its corresponding receiver operating characteristic (ROC) curve and compared with another model constructed based on current sepsis guidelines.

RESULTS

Age, bicarbonate, HR, lactate, pH, and body temperature had U, V, W, or reverse U-shaped associations with identifiable inflexion points, but the cutoff values we identified were slightly different from guideline cutoff values. In contrast to the guidelines, no inflexion points could be observed for the association of sepsis with SBP, DPB, MAP, and RR and therefore were treated as continuous variables. Compared to the guidelines-based model, the triage data-driven final model contained additional variables (age, pH, bicarbonate) and did not include lactate. The data-driven model identified about 85% of sepsis cases correctly, while the guidelines-based model identified only about 70% of sepsis cases correctly.

CONCLUSION

Our findings contribute to the growing body of evidence for the necessity of finding improved tools to identify sepsis at early time points, such as in the ER.

Managing adult patients with infectious diseases in emergency departments: international ID-IRI study

We aimed to explore factors for optimizing antimicrobial treatment in emergency departments. A single-day point prevalence survey was conducted on January 18, 2020, in 53 referral/tertiary hospitals in 22 countries. 1957 (17%) of 11557 patients presenting to EDs had infections. The mean qSOFA score was 0.37 ± 0.74. Sepsis (qSOFA ≥ 2) was recorded in 218 (11.1%) patients. The mean qSOFA score was significantly higher in low-middle (1.48 ± 0.963) compared to upper-middle (0.17 ± 0.482) and high-income (0.36 ± 0.714) countries (P < 0.001). Eight (3.7%) patients with sepsis were treated as outpatients. The most common diagnoses were upper-respiratory (n = 877, 43.3%), lower-respiratory (n = 316, 16.1%), and lower-urinary (n = 201, 10.3%) infections. 1085 (55.4%) patients received antibiotics. The most-commonly used antibiotics were beta-lactam (BL) and BL inhibitors (n = 307, 15.7%), third-generation cephalosporins (n = 251, 12.8%), and quinolones (n = 204, 10.5%). Irrational antibiotic use and inappropriate hospitalization decisions seemed possible. Patients were more septic in countries with limited resources. Hence, a better organizational scheme is required.

Integrating infection and sepsis management through holistic early warning systems and heuristic approaches: a concept proposal

This is a first attempt to integrate the three pillars of infection management: the infection prevention and control (IPC), and surveillance (IPCS), antimicrobial stewardship (AMS), and rapid identification and management of sepsis (RIMS). The new 'Sepsis-3' definition extrapolates the diagnosis of sepsis from our previously slightly naïve concept of a stepwise evolving pattern. In doing so, however, we have placed the transition from infection toward sepsis in the domain of uncertainty and time-dependency. This now demands that clinical judgment be used in the risk stratification of patients with infection, and that pragmatic local solutions be used to prompt clinicians to evaluate formally for sepsis. We feel it is necessary to stimulate the development of a new generation of concepts and models aiming at embracing uncertainty. We see the opportunity for a heuristic approach focusing on the relevant clinical predictors at hand allowing to navigate the uncertainty of infection diagnosis under time constraints. The diverse and situated clinical approaches eventually emerging need to focus on the understanding of infection as the unbalanced interactions of host, pathogen, and environment. In order extend such approach throughout the patient journey we propose a holistic early warning system underpinned by the risk-based categories of hazards and vulnerabilities iteratively fostered by the information gathered by the infection prevention control and surveillance, clinical microbiology, and clinical chemistry services.

Haemogram-Derived Indices for Screening and Prognostication in Critically Ill Septic Shock Patients: A Case-Control Study

This study aimed (1) to assess the diagnostic accuracy of neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), monocyte-to-lymphocyte (MLR) and platelet count-to-mean platelet volume (PLT/MPV) ratios in predicting septic shock in patients on admission to the intensive care unit (ICU) and (2) to compare it with the role of C-reactive protein (CRP), procalcitonin (PCT) and lactate level. We also sought (3) to verify whether the indices could be useful in ICU mortality prediction and (4) to compare them with Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II) and Sequential Organ Failure Assessment (SOFA) scores. This retrospective study covered 138 patients, including 61 subjects with multi-organ failure due to septic shock (study group) and 77 sex- and age-matched controls. Septic patients had significantly higher NLR (p < 0.01) and NLR predicted septic shock occurrence (area under the ROC curve, AUROC = 0.66; 95% CI 0.58-0.74). PLR, MLR and PLT/MPV were impractical in sepsis prediction. Combination of CRP with NLR improved septic shock prediction (AUROC = 0.88; 95% CI 0.81-0.93). All indices failed to predict ICU mortality. APACHE II and SAPS II predicted mortality with AUROC = 0.68; 95% CI 0.54-0.78 and AUROC = 0.7; 95% CI 0.57-0.81, respectively. High NLR may be useful to identify patients with multi-organ failure due to septic shock but should be interpreted along with CRP or PCT. The investigated indices are not related with mortality in this specific clinical setting.

Validation of the Predisposition Infection Response Organ (PIRO) dysfunction score for the prognostic stratification of patients with sepsis in the Emergency Department

OBJECTIVE

There are many different methods for computing the Predisposition Infection Response Organ (PIRO) dysfunction score. We compared three PIRO methods (PIRO1 (Howell), PIRO2 (Rubulotta) and PIRO3 (Rathour)) for the stratification of mortality and high level of care admission in septic patients arriving at the Emergency Department (ED) of an Italian Hospital.

DESIGN, SETTING AND PARTICIPANTS

We prospectively collected clinical data of 470 patients admitted due to infection in the ED to compute PIRO according to three different methods. We tested PIRO variables for the prediction of mortality in the univariate analysis. Calculation and comparison were made of the area under the receiver operating curve (AUC) for the three PIRO methods, SOFA and qSOFA.

RESULTS

Most of the variables included in PIRO were related to mortality in the univariate analysis. Increased PIRO scores were related to higher mortality. In relation to mortality, PIRO 1 performed better than PIRO2 at 30 d ((AUC 0.77 (0.716-0.824) vs. AUC 0.699 (0.64-0.758) (p=0.03) and similarly at 60 d (AUC 0.767 (0.715-0.819) vs AUC 0.709 (0.656-0.763)(p=0.55)); PIRO1 performed similarly to PIRO3 (AUC 0.765 (0.71-0.82) at 30 d, AUC 0.754 (0.701-0.806) at 60 d, p=ns). Both PIRO1 and PIRO3 were as good as SOFA referred to mortality (AUC 0.758 (0.699, 0.816) at 30 d vs. AUC 0.738 (0.681, 0.795) at 60 d; p=ns). For high level of care admission, PIRO proved inferior to SOFA.

CONCLUSIONS

We support the use of PIRO1, which combines ease of use and the best performance referred to mortality over the short term. PIRO2 proved to be less accurate and more complex to use, suffering from missing microbiological data in the ED setting.

Interventions for rapid recognition and treatment of sepsis in the emergency department: a narrative review

BACKGROUND

Sepsis is a major cause of morbidity and mortality worldwide. Early recognition and treatment of sepsis is associated with improved outcome. The emergency department (ED) is the department where patients with sepsis seek care. However, recognition of sepsis in the ED remains difficult. Different alert and triage systems, screening scores and intervention strategies have been developed to assist clinicians in early recognition of sepsis and to optimize management.

OBJECTIVES

This narrative review describes currently applied interventions or interventions we can start using today, such as screening scores, (automated) triage systems, sepsis teams and clinical pathways in sepsis care; and it summarizes evidence for the effect of implementation of these interventions in the ED on patient management and outcomes.

SOURCES

A systematic literature search was conducted in PubMed, resulting in 39 eligible studies.

CONTENT

The main sepsis interventions in the ED are (automated) triage systems, sepsis teams and clinical pathways, the most integrative being a clinical pathway. Implementation of any of these interventions in sepsis care will generally lead to increased protocol adherence. Presumably increased adherence to sepsis guidelines and bundles will lead to better patient outcomes, but the level of evidence to support this improvement is low, whereas implementation of interventions is often complex and costly. No studies comparing different interventions were identified. Two essential factors for success of interventions in the ED are obtaining the support from all professionals and providing ongoing education. The vulnerability of these interventions lies in the lack of accurate tools to identify sepsis; diagnosing sepsis ultimately still relies on clinical assessments. A lack of specificity or sepsis alerts may lead to alert fatigue and/or overtreatment.

IMPLICATIONS

The severity and poor outcome of sepsis as well as the frequency of its presentation in EDs make a structured, protocol-based approach towards these patients essential, preferably as part of a clinical pathway.

Prognostic value of prehospital quick sequential organ failure assessment score among patients with suspected infection

OBJECTIVE

After the third international consensus on sepsis released its new definitions, the prognostic value of quick sequential organ failure assessment (qSOFA) score has been confirmed in the emergency department. However, its validity in the prehospital setting remains unknown. The objective of the study was to assess its accuracy for prehospital patients cared by emergency physician-staffed ambulances (services mobiles d'urgence et de réanimation SMUR).

PATIENTS AND METHODS

This was a prospective observational multicenter cohort study (N = 6). All consecutive patients with prehospital clinical suspicion of infection by the emergency physician of the SMUR emergency medical service were included. Components of qSOFA were collected, and the patients were followed until hospital discharge. The primary end point was in-hospital mortality, censored at 28 days. Secondary end points included ICU admission longer than 72 h and a composite of 'death or ICU stay more than 72 h'.

RESULTS

We screened 342 patients and included 332 in the analysis. Their mean age was 73 years, 159 (48%) were women, and the most common site of infection was respiratory (73% of cases). qSOFA was at least 2 in 133 (40%) patients. The overall in-hospital mortality was 27%: 41% in patients with qSOFA of at least 2 versus 18% for qSOFA less than 2 (absolute difference 23%; 95% confidence interval: 13-33%, P < 0.001). The overall discrimination for qSOFA was poor, with an area under the receiver operating characteristic curve of 0.69 (95% confidence interval: 0.62-0.74).

CONCLUSION

In this large multicenter study, prehospital qSOFA presents a strong association with mortality in infected patient, though with poor prognostic performances in our severely ill sample.

Prognosis of β-adrenergic blockade therapy on septic shock and sepsis: A systematic review and meta-analysis of randomized controlled studies

PURPOSE

β-adrenoceptor antagonist (β-blocker) may have potential in the treatment of septic shock and sepsis. However, the relevant research findings are still controversial.

METHODS

We conducted a systematic review and meta-analysis to explore the efficacy of β-blocker in patients with septic shock and sepsis. The primary sources of the reviewed studies through August 2018, with restriction on the language of English, were Pubmed and Embase. Randomized controlled trials (RCT) were included to evaluate the efficacy of β-blocker in the treatment of septic shock and sepsis. Meta analysis was performed using a random effect model. Two researchers independently searched articles, extracted data, and assessed the quality of the included studies.

RESULTS

A total of 6 studies related to 5 original RCTs were qualified for inclusion in this systematic review and meta-analysis with a total of 363 patients with sepsis and/or septic shock. β-blocker was associated with a significantly decreased 28-day mortality compared to usual treatment group as the control (RR = 0.59, 95%CI: 0.48, 0.74; P < 0.00001). Heart rate in β-blocker was significantly lower than that in the standard care group (SMD = -2.01, 95%CI: -3.03, -0.98; P = 0001).

CONCLUSION

β-blocker of esmolol is safe and effective in improving 28-day mortality and controlling ventricular rate in patients with sepsis after fluid resuscitation, and has no significant adverse effect on tissue perfusion.

The impact of the Sepsis-3 definition on ICU admission of patients with infection

Background

Sepsis is defined as a life-threatening organ dysfunction due to a dysregulated inflammation following an infection. However, the impact of this definition on patient care is not fully clear. This study investigated the impact of the current definition on ICU admission of patients with infection.

Methods

We performed a prospective observational study over twelve months on consecutive patients presented to our emergency department and admitted for infection. We analyzed the predictive values of the quick sequential organ failure assessment (qSOFA) score, the SOFA score and blood lactate regarding ICU admission.

Results

We included 916 patients with the diagnosis of infection. Median age was 74 years (IQR 62–82 years), and 56.3% were males. There were 219 direct ICU admissions and 697 general ward admissions. A qSOFA score of ≥2 points had 52.9% sensitivity and 98.3% specificity regarding sepsis diagnosis. A qSOFA score of ≥2 points had 87.2% specificity but only 39.9% sensitivity to predict ICU admission. A SOFA score of ≥2 points had 97.4% sensitivity, but only 17.1% specificity to predict ICU admission, while a SOFA score of ≥4 points predicted ICU admission with 82.6% sensitivity and 71.7% specificity. The area under the receiver operating curve regarding ICU admission was 0.81 (95 CI, 0.77–0.86) for SOFA score, 0.55 (95% CI, 0.48–0.61) for blood lactate, and only 0.34 (95% CI, 0.28–0.40) for qSOFA on emergency department presentation.

Conclusions

While a positive qSOFA score had a high specificity regarding ICU admission, the low sensitivity of the score among septic patients as well as among ICU admissions considerably limited its value in routine patient management. The SOFA score was the better predictor of ICU admission, while the predictive value of blood lactate was equivocal.

Prevalence of organ failure and mortality among patients in the emergency department: a population-based cohort study

OBJECTIVES

The aim was to describe population-based incidence and emergency department-based prevalence and 1-year all-cause mortality of patients with new organ failure present at arrival.

DESIGN

This was a population-based cohort study of all citizens in four municipalities (population of 230 000 adults).

SETTING

Emergency department at Odense University Hospital, Denmark.

PARTICIPANTS

We included all adult patients who arrived from 1 April 2012 to 31 March 2015.

PRIMARY AND SECONDARY OUTCOME MEASURES

Organ failure was defined as a modified Sequential Organ Failure Assessment score≥2 within six possible organ systems: cerebral, circulatory, renal, respiratory, hepatic and coagulation.The primary outcome was prevalence of organ failure, and secondary outcomes were 0-7 days, 8-30 days and 31-365 days all-cause mortality.

RESULTS

We identified in total 175 278 contacts, of which 70 399 contacts were further evaluated for organ failure. Fifty-two per cent of these were women, median age 62 (IQR 42-77) years. The incidence of new organ failure was 1342/100 000 person-years, corresponding to 5.2% of all emergency department contacts.The 0-7-day, 8-30-day and 31-365-day mortality was 11.0% (95% CI: 10.2% to 11.8%), 5.6% (95% CI: 5.1% to 6.2%) and 13.2% (95% CI: 12.3% to 14.1%), respectively, if the patient had one or more new organ failures at first contact in the observation period, compared with 1.4% (95% CI: 1.3% to 1.6%), 1.2% (95% CI: 1.1% to 1.3%) and 5.2% (95% CI: 5.0% to 5.4%) for patients without. Seven-day mortality ranged from hepatic failure, 6.5% (95% CI: 4.9% to 8.6%), to cerebral failure, 33.8% (95% CI: 31.0% to 36.8%), the 8-30-day mortality ranged from cerebral failure, 3.9% (95% CI: 2.8% to 5.3%), to hepatic failure, 8.6% (95% CI: 6.6% to 10.8%) and 31-365-day mortality ranged from cerebral failure, 9.3% (95% CI: 7.6% to 11.2%), to renal failure, 18.2% (95% CI: 15.5% to 21.1%).

CONCLUSIONS

The study revealed an incidence of new organ failure at 1342/100 000 person-years and a prevalence of 5.2% of all emergency department contacts. One-year all-cause mortality was 29.8% among organ failure patients.

Clinical applications of artificial intelligence in sepsis: A narrative review

Many studies have been published on a variety of clinical applications of artificial intelligence (AI) for sepsis, while there is no overview of the literature. The aim of this review is to give an overview of the literature and thereby identify knowledge gaps and prioritize areas with high priority for further research. A literature search was conducted in PubMed from inception to February 2019. Search terms related to AI were combined with terms regarding sepsis. Articles were included when they reported an area under the receiver operator characteristics curve (AUROC) as outcome measure. Fifteen articles on diagnosis of sepsis with AI models were included. The best performing model reached an AUROC of 0.97. There were also seven articles on prognosis, predicting mortality over time with an AUROC of up to 0.895. Finally, there were three articles on assistance of treatment of sepsis, where the use of AI was associated with the lowest mortality rates. Of the articles, twenty-two were judged to be at high risk of bias or had major concerns regarding applicability. This was mostly because predictor variables in these models, such as blood pressure, were also part of the definition of sepsis, which led to overestimation of the performance. We conclude that AI models have great potential for improving early identification of patients who may benefit from administration of antibiotics. Current AI prediction models to diagnose sepsis are at major risks of bias when the diagnosis criteria are part of the predictor variables in the model. Furthermore, generalizability of these models is poor due to overfitting and a lack of standardized protocols for the construction and validation of the models. Until these problems have been resolved, a large gap remains between the creation of an AI algorithm and its implementation in clinical practice.

Downregulation of JKAP is correlated with elevated disease risk, advanced disease severity, higher inflammation, and poor survival in sepsis

OBJECTIVE

This study aimed to explore the association of JKAP with sepsis risk and investigate its correlation with disease severity, inflammatory cytokines, and survival in sepsis patients.

METHODS

A hundred and one sepsis patients along with 100 healthy controls were enrolled, and their blood serum samples were collected for JKAP and inflammatory cytokines measurement by enzyme-linked immunoassay. The difference in serum JKAP between sepsis patients and healthy controls was determined. Among sepsis patients, the correlation of JKAP with disease severity, laboratory indexes, inflammatory cytokines, 28-day mortality, and accumulating survival was analyzed.

RESULTS

JNK pathway-associated phosphatase level was decreased in sepsis patients compared with healthy controls and presented with good value in predicting decreased sepsis risk (AUC = 0.896 [95% CI: 0.851-0.941]). And its low expression was associated with advanced disease severity (APACHE II score and SOFA score) and systemic inflammation (CRP, PCT, TNF-α, IL-1β, IL-6, and IL-17) in sepsis patients. Additionally, JKAP level was decreased in deaths compared with survivors and had good value in distinguishing deaths from survivors (AUC = 0.742 [95% CI: 0.636-0.849]). Further, Kaplan-Meier curve analysis disclosed that JKAP high expression predicted more prolonged accumulating survival in sepsis patients.

CONCLUSION

JNK pathway-associated phosphatase is of good value in predicting lower sepsis risk, and its downregulation correlates with advanced disease severity, higher level of systemic inflammation, and poor survival in sepsis patients.

Prognostic Accuracy of Quick SOFA is different according to the severity of illness in infectious patients

BACKGROUND

Sepsis-3 proposed the quick Sequential Organ Failure Assessment (qSOFA) to identify sepsis patients likely to have poor outcome. The clinical utility of qSOFA still remains controversial because its predictive accuracy for mortality is quite different across the validation studies. We hypothesized that one of the major causes for these controversial findings was the heterogeneity in severity across the studies, and evaluated the association between severity of illness and the prognostic accuracy of qSOFA.

MATERIALS AND METHODS

This was a post hoc analysis of a prospective nationwide cohort of consecutive adult patients with sepsis in 59 intensive care units in Japan. Regression trees analysis for survival was used to classify patients according to severity of illness as determined by SOFA score on registration. We conducted receiver operating characteristic (ROC) analyses and evaluated the differences in the area under the ROC curve (AUROC). As a subgroup analysis, we conducted the above evaluations in emergency department (ED) and non-ED patients separately.

RESULTS

We included 1114 patients fulfilling the criteria and classified them into three subsets according to severity. The AUROC for mortality was significantly different according to the severity of illness (p = 0.007), with the highest AUROC being in the low-severity subset (patients with SOFA score ≤ 7). Interestingly, our subgroup analysis revealed that a significant difference in the AUROC of qSOFA was observed only in ED patients.

CONCLUSION

This study suggested that lower severity of illness was associated with the relatively higher prognostic accuracy of qSOFA, especially in ED patients.

Quick Sequential Organ Failure Assessment as a prognostic factor for infected patients outside the intensive care unit: a systematic review and meta-analysis

Quick Sequential Organ Failure Assessment (qSOFA) was proposed to replace SIRS as a new screening tool for the identification of septic patients at high mortality. However, researches from infected patients outside of ICU especially in Emergency Department (ED) drew contradictory conclusions on the prognostic value of qSOFA. This systematic review evaluated qSOFA as a prognostic marker of infected patients outside of ICU. The primary outcome was hospital mortality or 28- or 30-day mortality. Data were pooled based on sensitivity and specificity. Twenty-four trials with 121,237 participants were included. qSOFA had a poor sensitivity (0.58 [95% CI 0.47-0.67], 0.54 [95% CI 0.43-0.65]) and moderate specificity (0.69 [95% CI 0.48-0.84], 0.77 [95% CI 0.66-0.86]) for prediction of mortality in patients outside of ICU and ED patients only. Studies that used in-hospital mortality showed a higher sensitivity (0.61 [95% CI 0.50-0.71] vs 0.32 [95% CI 0.15-0.49]) and lower specificity (0.70 [95% CI 0.59-0.82] vs 0.92 [95% CI 0.85-0.99]) than studies that used 28 or 30-day mortality. Studies with overall mortality < 10% showed higher specificity (0.89 [95% CI 0.82-0.95] vs 0.62 [95% CI 0.48-0.76]) than studies with overall mortality ≥ 10%. There is no difference in the accuracy of diagnosis of sepsis between positive qSOFA scores and SIRS criteria. qSOFA was poor sensitivity and moderate specificity in predicting mortality of infected patients outside of ICU especially in ED. Combining qSOFA and SIRS may be helpful in predicting mortality.

qSOFA is a Poor Predictor of Short-Term Mortality in All Patients: A Systematic Review of 410,000 Patients

BACKGROUND

To determine the validity of the Quick Sepsis-Related Organ Failure Assessment (qSOFA) in the prediction of outcome (in-hospital and 1-month mortality, intensive care unit (ICU) admission, and hospital and ICU length of stay) in adult patients with or without suspected infections where qSOFA was calculated and reported; Methods: Cochrane Central of Controlled trials, EMBASE, BIOSIS, OVID MEDLINE, OVID Nursing Database, and the Joanna Briggs Institute EBP Database were the main databases searched. All studies published until 12 April 2018 were considered. All studies except case series, case reports, and conference abstracts were considered. Studies that included patients with neutropenic fever exclusively were excluded.

RESULTS

The median AUROC for in-hospital mortality (27 studies with 380,920 patients) was 0.68 (a range of 0.55 to 0.82). A meta-analysis of 377,623 subjects showed a polled AUROC of 0.68 (0.65 to 0.71); however, it also confirmed high heterogeneity among studies (I² = 98.8%, 95%CI 98.6 to 99.0). The median sensitivity and specificity for in-hospital mortality (24 studies with 118,051 patients) was 0.52 (range 0.16 to 0.98) and 0.81 (0.19 to 0.97), respectively. Median positive and negative predictive values were 0.2 (range 0.07 to 0.38) and 0.94 (0.85 to 0.99), respectively.

Short-term mortality in older medical emergency patients can be predicted using clinical intuition: A prospective study

Background

Older emergency department (ED) patients are at risk for adverse outcomes, however, it is hard to predict these. We aimed to assess the discriminatory value of clinical intuition, operationalized as disease perception, self-rated health and first clinical impression, including the 30-day surprise question (SQ: “Would I be surprised if this patient died in the next 30 days” of patients, nurses and physicians. Endpoints used to evaluate the discriminatory value of clinical intuition were short-term (30-day) mortality and other adverse outcomes (intensive/medium care admission, prolonged length of hospital stay, loss of independent living or 30-day readmission).

Methods

In this prospective, multicentre cohort study, older medical patients (≥65 years), nurses and physicians filled in scores regarding severity of illness and their concerns (i.e. disease perception and clinical impression scores) immediately after arrival of the patient in the ED. In addition, patients filled in a self-rated health score and nurses and physicians answered the SQ. Area under the curves (AUCs) of receiver operating characteristics (ROCs) were calculated.

Results

The median age of the 602 included patients was 79 years and 86.7% were community dwelling. Within 30 days, 66 (11.0%) patients died and 263 (43.7%) patients met the composite endpoint. The severity of concern score of both nurses and physicians yielded the highest AUCs for 30-day mortality (for both 0.75; 95%CI 0.68–0.81). AUCs for the severity of illness score and SQ of nurses and physicians ranged from 0.71 to 0.74 while those for the disease perception and self-rated health of patients ranged from 0.64 to 0.69. The discriminatory value of the scores for the composite endpoint was lower (AUCs ranging from 0.60 to 0.67). We used scores that have not been previously validated which could influence their generalisability.

Conclusion

Clinical intuition,—disease perception, self-rated health and first clinical impression—documented at an early stage after arrival in the ED, is a useful clinical tool to predict mortality and other adverse outcomes in older ED patients. Highest discriminatory values were found for the nurses’ and physicians’ severity of concern score. Intuition may be helpful for the implementation of personalised medical care in the future.

Comparison of Prognostic Accuracy of the quick Sepsis-Related Organ Failure Assessment between Short- & Long-term Mortality in Patients Presenting Outside of the Intensive Care Unit - A Systematic Review & Meta-analysis

The purpose of this meta-analysis was to compare the ability of the qSOFA in predicting short- (≤30 days or in-hospital mortality) and long-term (>30 days) mortality among patients outside the intensive care unit setting. Studies reporting on the qSOFA and mortality were searched using MEDLINE and SCOPUS. Studies were included if they involved patients presenting to the ED with suspected infection and usage of qSOFA score for mortality prognostication. Data on qSOFA scores and mortality rates were extracted from 36 studies. The overall pooled sensitivity and specificity for the qSOFA were 48% and 86% for short-term mortality and 32% and 92% for long-term mortality, respectively. Studies reporting on short-term mortality were heterogeneous (Odd ratio, OR = 5.6; 95% CI = 4.6-6.8; Higgins's I2 = 94%), while long-term mortality studies were homogenous (OR = 4.7; 95% CI = 3.5-6.1; Higgins's I2 = 0%). There was no publication bias for short-term mortality analysis. The qSOFA score showed poor sensitivity but moderate specificity for both short and long-term mortality, with similar performance in predicting both short- and long- term mortality. Geographical region was shown to have nominal significant (p = 0.05) influence on qSOFA short-term mortality prediction.

Prevalence and prognosis of acutely ill patients with organ failure at arrival to hospital: A systematic review

Introduction

Patients in an emergency department are diverse. Some are more seriously ill than others and some even arrive in multi-organ failure. Knowledge of the prevalence of organ failure and its prognosis in unselected patients is important from a diagnostic, hospital planning, and from a quality evaluation point of view, but is not reported systematically.

Objectives

To analyse the prevalence and prognosis of new onset organ failure in unselected acute patients at arrival to hospital.

Methods

A systematic review of studies of prevalence and prognosis of acutely ill patients with organ failure at arrival to hospital. We searched PubMed, Cochrane Library, Embase and Cinahl, and read references in included studies. Two authors decided independently on study eligibility and extracted data. Results were summarised qualitatively.

Results

Four studies were included with a total of 678,960 patients. The number of different organ failures reported in the studies ranged from one to six, and the settings were emergency departments and wards. The definitions of organ failure varied between studies. The prevalence of organ failure was 7%, 14%, 14%, and 23%, and in-hospital mortality was 5%, 11% and 15% respectively. The relative risk of in-hospital mortality for patients with organ failure compared to patients without organ failure varied from 2.58 to 8.65. Numbers of organ failures per 1,000 visits varied from 71 to 256.

Conclusion

The results of this review indicate that clinicians have good reasons to be alert when a patient arrives to the emergency department; as a state of organ failure seems both frequent and highly severe.

However, most studies identified were performed in patients after a diagnosis was established, and only very few studies were performed in unselected patients.

Systematic review registration number

PROSPERO: CRD42017060871.

qSOFA score not predictive of in-hospital mortality in emergency patients with decompensated liver cirrhosis

BACKGROUND

Quick sequential organ failure assessement (qSOFA) has been validated for patients with presumed sepsis and the general emergency department (ED) population. However, it has not been validated in specific subgroups of ED patients with a high mortality. We aimed to investigate the prognostic performance of qSOFA with respect to in-hospital mortality, intensive care unit (ICU) admission, and length of hospitalisation in patients with decompensated liver cirrhosis. Furthermore, we compared qSOFA to systemic inflammatory response syndrome (SIRS), model of end stage liver disease score (MELD), and Child-Pugh criteria and evaluated whether addition of sodium (Na⁺) levels to qSOFA increases its prognostic performance.

METHODS

This observational study included patients admitted with the diagnosis of decompensated liver cirrhosis. All patients with a complete set of vital parameters were included in this study.

RESULTS

A total of 186 patients were included. A positive qSOFA score was not associated with in-hospital mortality, ICU admission, or length of hospitalisation (all p > 0.15). MELD scores reliably predicted need for ICU admission and in-hospital mortality (both p < 0.01), but not the length of hospitalisation. qSOFA-Na+ only moderately increased the diagnostic performance of qSOFA with regard to need for ICU admission (AUC_ICU[qSOFA] = 0.504 vs. AUC_ICU[qSOFA-Na+] = 0.609, p = 0.03), but not for in-hospital mortality (AUC_death[qSOFA] = 0.513 vs. AUC_death[qSOFA-Na+] = 0.592, p = 0.054).

CONCLUSION

qSOFA does not predict in-hospital mortality, ICU admission or length of hospitalisation in patients with decompensated liver cirrhosis. Extension of qSOFA with a disease-specific component, the qSOFA-Na+, moderately increased the diagnostic ability of qSOFA.

Performance of the quick Sequential (sepsis-related) Organ Failure Assessment score as a prognostic tool in infected patients outside the intensive care unit: a systematic review and meta-analysis

Background

The usefulness of the quick Sequential (Sepsis-related) Organ Failure Assessment (qSOFA) score in providing bedside criteria for early prediction of poor outcomes in patients with suspected infection remains controversial. We investigated the prognostic performance of a positive qSOFA score outside the intensive care unit (ICU) compared with positive systemic inflammatory response syndrome (SIRS) criteria.

Methods

A systematic literature search was performed using MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. Data were pooled on the basis of sensitivity, specificity, and diagnostic OR. Overall test performance was summarized using a hierarchical summary ROC and the AUC. Meta-regression analysis was used to identify potential sources of bias.

Results

We identified 23 studies with a total of 146,551 patients. When predicting in-hospital mortality in our meta-analysis, we identified pooled sensitivities of 0.51 for a positive qSOFA score and 0.86 for positive SIRS criteria, as well as pooled specificities of 0.83 for a positive qSOFA score and 0.29 for positive SIRS criteria. Discrimination for in-hospital mortality had similar AUCs between the two tools (0.74 vs. 0.71; P = 0.816). Using meta-regression analysis, an overall mortality rate ≥ 10% and timing of qSOFA score measurement could be significant sources of heterogeneity. For predicting acute organ dysfunction, although the AUC for a positive qSOFA score was higher than that for positive SIRS criteria (0.87 vs. 0.76; P < 0.001), the pooled sensitivity of positive qSOFA score was very low (0.47). In addition, a positive qSOFA score tended to be inferior to positive SIRS criteria in predicting ICU admission (0.63 vs. 0.78; P = 0.121).

Conclusions

A positive qSOFA score had high specificity outside the ICU in early detection of in-hospital mortality, acute organ dysfunction, and ICU admission, but low sensitivity may have limitations as a predictive tool for adverse outcomes. Because between-study heterogeneity was highly represented among the studies, our results should be interpreted with caution.

Electronic supplementary material

The online version of this article (10.1186/s13054-018-1952-x) contains supplementary material, which is available to authorized users.

Utility of quick sepsis-related organ failure assessment (qSOFA) to predict outcome in patients with pneumonia

Background

Despite on-going advances in medical treatment, the burden of disease of pneumonia remains high. We aimed to determine the association of the qSOFA score with in-hospital mortality, length of hospitalisation, and admission to the intensive care unit (ICU) in patients with pneumonia. Further, in a subgroup analysis, the outcomes were compared for qSOFA in comparison to other risk scores, including the CURB-65 and SIRS scores.

Methods

In a retrospective analysis, admission data from the ED of the Bern University Hospital, Switzerland, were screened to identify patients admitted for pneumonia. In addition to clinical characteristics, qSOFA and CURB-65 scores and SIRS criteria were assessed and evaluated with respect to the defined study outcomes.

Results

527 patients (median age 66 IQR 50–76) were included in this study. The overall in-hospital mortality was 13.3% (n = 70); 22.0% (n = 116) were transferred to the ICU. The median length of hospitalisation was 7 days (IQR 4–12). In comparison to qSOFA-negative patients, qSOFA-positive patients had increased odds ratios for in-hospital mortality (OR 2.6, 95%:1.4, 4.7, p<0.001) and ICU admission (3.5, 95% CI: 2.0. 5.8, p<0.001) and an increased length of stay (p<0.001). For ICU admission, the specificity of qSOPA-positivity (≥2) was 82.1% and sensitivity 43.0%. For in-hospital mortality, the specificity of qSOPA-positivity (≤2) was 88.9% and sensitivity 24.4%.

In the subgroup analysis (n = 366). The area under the receiver operating curve for ICU admission was higher for qSOFA than for the CURB-65 score (p = 0.013). The evaluated scores did not differ significantly in their prognostication of in-hospital mortality (p>0.05).

Conclusions

The qSOFA score is associated with in-hospital mortality, ICU admission and length of hospitalisation in ED patients with pneumonia. Subgroup analysis revealed that qSOFA is superior to CURB-65 in respect to prognostication of ICU admission.

Protocol of the sepsivit study: a prospective observational study to determine whether continuous heart rate variability measurement during the first 48 hours of hospitalisation provides an early warning for deterioration in patients presenting with infection or sepsis to the emergency department of a Dutch academic teaching hospital

INTRODUCTION

One in five patients with sepsis deteriorates within 48 hours after hospital admission. Regrettably, a clear tool for the early detection of deterioration is still lacking. The SepsiVit study aims to determine whether continuous heart rate variability (HRV) measurement can provide an early warning for deterioration in patients presenting with suspected infection or sepsis to the emergency department (ED).

METHODS AND ANALYSIS

The protocol of a prospective observational study in the ED. We will include 171 adult medical patients presenting with suspected infection or sepsis and at least two systemic inflammatory response syndrome criteria. Patients with known pregnancy, cardiac transplantation or not admitted to our hospital are excluded.High sample frequency ECG signals (500 Hz), respiratory rate, blood pressure and peripheral oxygen saturation will be recorded continuously during the first 48 hours of hospitalisation using a bedside patient monitor (Philips IntelliVue MP70). Primary endpoint is patient deterioration, defined as the development of organ dysfunction, unplanned intensive care unit admission or in-hospital mortality. The ECG data will be used for offline HRV analysis. We will compare the HRV between two groups (deterioration/no deterioration) and analyse whether HRV provides an early warning for deterioration. Furthermore, we will create a multivariate predictive model for deterioration based on heart rate, respiratory rate and HRV. As planned secondary analyses, we (1) perform a subgroup analysis for patients with pneumosepsis and urosepsis and (2) determine whether HRV using lower sample frequencies (1 Hz or less) suffices to predict deterioration.

ETHICS AND DISSEMINATION

The Institutional Review Board of the University Medical Center Groningen granted a waiver for the study (METc 2015/164). Results will be disseminated through international peer-reviewed publications and conference presentations. A lay summary of the results will be provided to the study participants.

TRIAL REGISTRATION NUMBER

NTR6168; Pre-results.