Evaluation of the modified MEDS, MEWS score and Charlson comorbidity index in patients with community acquired sepsis in the emergency department

Prognostic accuracy of SOFA, MEWS, and SIRS criteria in predicting the mortality rate of patients with sepsis: A meta-analysis

BACKGROUND

In recent years, some studies classified patients with sepsis and predicted their mortality by using some evaluation scales. Several studies reported significant differences in the predictive values of several tools, and the non-uniformity of the cut-off value.

OBJECTIVE

To determine and compare the prognostic accuracy of Sequential Organ Failure Assessment (SOFA) score, Modified Early Warning Score (MEWS), and Systemic Inflammatory Response Syndrome (SIRS) criteria in predicting the mortality of patients with sepsis.

METHODS

This study comprised of systematic literature review and meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. We searched PubMed, Embase, Web of Science and Cochrane Library databases from their establishment to July 31, 2022. The research articles published in the index journals provide sufficient data (true positive, false positive, true negative, and false negative results) for patients with sepsis. The combined sensitivity and specificity of the 95% confidence interval (CI) were calculated using the bivariate random effect model (BRM). The hierarchical overall subject working characteristics (HSROC) curve was drawn to evaluate the accuracy of the overall prognosis.

RESULTS

Data of 55 088 patients from 32 studies were included in this meta-analysis. SOFA had an intermediate sensitivity of 0.73 (95% CI: 0.67-0.78) and a specificity of 0.70 (0.63-0.76). SIRS criteria had the highest sensitivity of 0.75 (0.66-0.82) and the lowest specificity of 0.40 (0.29-0.52). MEWS had the lowest sensitivity of 0.49 (0.40-0.59) and the highest specificity of 0.82 (0.78-0.86).

CONCLUSIONS

Among SOFA, MEWS, and SIRS criteria, SOFA showed moderate sensitivity and specificity for predicting mortality in patients with sepsis, the highest sensitivity of SIRS and the strongest specificity of MEWS for predicting mortality in patients with sepsis. The future research direction is to combine the relevant indicators of MEWS and SIRS to develop a measurement tool with high reliability and validity.

RELEVANCE TO CLINICAL PRACTICE

The review provides useful insights into the prognostic accuracy of different assessment tools in predicting mortality in sepsis patients, which will help clinicians choose the most appropriate tool for early identification and treatment of sepsis. The findings may also contribute to the development of more accurate and reliable prognostic models for sepsis.

Predictive performance of comorbidity for 30-day and 1-year mortality in patients with bloodstream infection visiting the emergency department: a retrospective cohort study

OBJECTIVES

To investigate whether the Charlson Comorbidity Index (CCI) predicted short-term and long-term mortality in patients with a bloodstream infection visiting the emergency department (ED) and compare it to the often-validated National Early Warning Score (NEWS).

DESIGN

A retrospective cohort study.

SETTING

A tertiary hospital in the Netherlands.

PARTICIPANTS

Adult patients attending the ED with a blood culture-proven infection between 2012 and 2017 were included. We collected the comorbidities from the CCI and the vital signs from the NEWS.

MAIN OUTCOMES

Short-term mortality (30-day) and long-term mortality (1 year). We assessed the predictive performance by discrimination, expressed as the area under the curve (AUC).

RESULTS

We included 1039 patients with a blood culture-proven infection. Mortality was 10.4% within 30 days and 27.8% within 1 year. On average patients had two comorbidities (ranging from 0 to 6). Highly prevalent comorbidities were malignancy (30.2%) and diabetes mellitus (20.5%). The predictive performance of the CCI was highest for 1-year mortality (AUC 0.696 (95%CI) (0.660 to 0.732)) and better compared with the NEWS (AUC (95% CI) 0.594 (0.555 to 0.632)). For prediction of 30-day mortality, the NEWS was superior (AUC (95% CI) 0.706 (0.656 to 0.756)) to the comorbidities of the CCI (AUC (95% CI) 0.568 (0.507 to 0.628)).

CONCLUSIONS

We found that presenting comorbidity (ie, the CCI) is most useful to prognosticate long-term outcome in patients with bloodstream infection in the ED. Short-term mortality is more accurately predicted by deviating vital signs (ie, the NEWS).

Profile of Sepsis Patients Treated in Intensive Care Unit of Sanglah Hospital Denpasar

BACKGROUND: Primary data regarding sepsis patients in Indonesia, especially in Denpasar, are still limited in number in reporting. The lack of information about sepsis made the authors interested in conducting this study. AIM: The aim of the study was to obtain more in-depth information about the profile of sepsis patients treated in Sanglah Hospital, Denpasar. MATERIALS AND METHODS: This was a cross-sectional descriptive research. Target population in this study are data on patient registers that are included in the inclusion criteria from June 1, 2019 to June 30, 2021, at intensive care unit Sanglah Hospital, Denpasar. The variables in this study included: Demographic conditions such as age, gender, and address, qSOFA score, comorbidities, ventilator, and patient’s outcome (survival or non-survival). RESULTS: A total samples were 173 patients. The average age of patients in this study was 54 years old with 56.6% male and 32.9% lived in Denpasar. Patients suspected of having early sepsis had a qSOFA 0 score of 35.3%, qSOFA 1 was 33.5%, qSOFA 2 was 23.7%, and qSOFA 3 was 7.5%. Patients with sepsis and suspected sepsis with comorbidities were 96% and 79.8% of patients were on a ventilator. The mortality rate in this study was 67.1%. CONCLUSION: These primary data hopefully become references for the future research.

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.

A comparison of different scores for diagnosis and mortality prediction of adults with sepsis in Low-and-Middlencome Countries: a systematic review and meta-analysis

BACKGROUND

Clinical scores for sepsis have been primarily developed for, and applied in High-Income Countries. This systematic review and meta-analysis examined the performance of the quick Sequential Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SIRS), Modified Early Warning Score (MEWS), and Universal Vital Assessment (UVA) scores for diagnosis and prediction of mortality in patients with suspected infection in Low-and-Middle-Income Countries.

METHODS

PubMed, Science Direct, Web of Science, and the Cochrane Central Register of Controlled Trials databases were searched until May 18, 2021. Studies reporting the performance of at least one of the above-mentioned scores for predicting mortality in patients of 15 years of age and older with suspected infection or sepsis were eligible. The Quality Assessment of Diagnostic Accuracy Studies tool was used for risk-of-bias assessment. PRISMA guidelines were followed (PROSPERO registration: CRD42020153906). The bivariate random-effects regression model was used to pool the individual sensitivities, specificities and areas-under-the-curve (AUC).

FINDINGS

Twenty-four articles (of 5669 identified) with 27,237 patients were eligible for inclusion. qSOFA pooled sensitivity was 0·70 (95% confidence interval [CI] 0·60-0·78), specificity 0·73 (95% CI 0·67-0·79), and AUC 0·77 (95% CI 0·72-0·82). SIRS pooled sensitivity, specificity and AUC were 0·88 (95% CI 0·79 -0·93), 0·34 (95% CI 0·25-0·44), and 0·69 (95% CI 0·50-0·83), respectively. MEWS pooled sensitivity, specificity and AUC were 0·70 (95% CI 0·57 -0·81), 0·61 (95% CI 0·42-0·77), and 0·72 (95% CI 0·64-0·77), respectively. UVA pooled sensitivity, specificity and AUC were 0·49 (95% CI 0·33 -0·65), 0·91(95% CI 0·84-0·96), and 0·76 (95% CI 0·44-0·93), respectively. Significant heterogeneity was observed in the pooled analysis.

INTERPRETATION

Individual score performances ranged from poor to acceptable. Future studies should combine selected or modified elements of different scores.

FUNDING

Partially funded by the UK National Institute for Health Research (NIHR) (17/63/42).

Geriatric emergency department revisits after discharge with Potentially Inappropriate Medications: A retrospective cohort study

OBJECTIVE

To determine whether Potentially Inappropriate Medications (PIMs) prescribed in an academic emergency department (ED) are associated with increased ED revisits in older adults.

METHODS

A retrospective chart review of Medicare beneficiaries 65 years and older, discharged from an academic ED (January 2012 - November 2015) with any PIMs versus no PIMs. PIMs were defined using Category 1 of the 2015 Updated Beers criteria. Primary outcomes, obtained from a Medicare database linked to hospital ED subjects, were ED revisits 3 and 30 days from index ED discharge. Adjusted multiple logistic regression was used with entropy balance weighted covariates: Age in years, Gender, Race, Number of discharge medications, Charlson Comorbidity Index (CCI) score, Emergency Severity Index scores (ESI), Chief Complaint, Medicaid status, and prior 90 Day ED visits.

RESULTS

Over the study period, there were a total of 7,591 Medicare beneficiaries 65+ discharged from the ED with a prescription; 1,383 (18%) received one or more PIMs. ED revisits in 30 days were fewer for the PIMs cohort (12% PIMs vs 16% no PIMs, OR 0.79, 95% CI 0.65 - 0.95, P value <0.005). Hospital admissions in 30 days were fewer for the PIMs cohort (4 PIMs vs 7% no PIMs, OR 0.75, 95% CI 0.56 - 1.00, P value <0.005). In addition to PIMs, covariate risk factors associated with ED revisits in 30 days included comorbidity severity, history of prior ED revisits, chief complaint, and Medicaid status. Risk factors associated with hospitalization in 30 days included those plus age and emergency severity index, but not race nor ethnicity.

CONCLUSIONS

Patients discharged from the ED receiving potentially inappropriate medications as defined by Category 1 of the 2015 updated Beers criteria had lower odds of revisiting the ED within 30 days of index visit. Sociodemographic factors such as gender and race did not predict ED revisits or hospital admissions. Clinical characteristics predicted ED revisits and hospital admissions, the strongest risk being increasing Charlson Comorbidity Index score followed by triage acuity and chief complaint. Future studies are needed to delineate the implications of our findings.

Performance of universal early warning scores in different patient subgroups and clinical settings: a systematic review

OBJECTIVE

To assess predictive performance of universal early warning scores (EWS) in disease subgroups and clinical settings.

DESIGN

Systematic review.

DATA SOURCES

Medline, CINAHL, Embase and Cochrane database of systematic reviews from 1997 to 2019.

INCLUSION CRITERIA

Randomised trials and observational studies of internal or external validation of EWS to predict deterioration (mortality, intensive care unit (ICU) transfer and cardiac arrest) in disease subgroups or clinical settings.

RESULTS

We identified 770 studies, of which 103 were included. Study designs and methods were inconsistent, with significant risk of bias (high: n=16 and unclear: n=64 and low risk: n=28). There were only two randomised trials. There was a high degree of heterogeneity in all subgroups and in national early warning score (I2=72%-99%). Predictive accuracy (mean area under the curve; 95% CI) was highest in medical (0.74; 0.74 to 0.75) and surgical (0.77; 0.75 to 0.80) settings and respiratory diseases (0.77; 0.75 to 0.80). Few studies evaluated EWS in specific diseases, for example, cardiology (n=1) and respiratory (n=7). Mortality and ICU transfer were most frequently studied outcomes, and cardiac arrest was least examined (n=8). Integration with electronic health records was uncommon (n=9).

CONCLUSION

Methodology and quality of validation studies of EWS are insufficient to recommend their use in all diseases and all clinical settings despite good performance of EWS in some subgroups. There is urgent need for consistency in methods and study design, following consensus guidelines for predictive risk scores. Further research should consider specific diseases and settings, using electronic health record data, prior to large-scale implementation.

PROSPERO REGISTRATION NUMBER

PROSPERO CRD42019143141.

Prediction of Mortality in Surgical Intensive Care Unit Patients Using Machine Learning Algorithms

Objective: Predicting prognosis of in-hospital patients is critical. However, it is challenging to accurately predict the life and death of certain patients at certain period. To determine whether machine learning algorithms could predict in-hospital death of critically ill patients with considerable accuracy and identify factors contributing to the prediction power.

Materials and Methods: Using medical data of 1,384 patients admitted to the Surgical Intensive Care Unit (SICU) of our institution, we investigated whether machine learning algorithms could predict in-hospital death using demographic, laboratory, and other disease-related variables, and compared predictions using three different algorithmic methods. The outcome measurement was the incidence of unexpected postoperative mortality which was defined as mortality without pre-existing not-for-resuscitation order that occurred within 30 days of the surgery or within the same hospital stay as the surgery.

Results: Machine learning algorithms trained with 43 variables successfully classified dead and live patients with very high accuracy. Most notably, the decision tree showed the higher classification results (Area Under the Receiver Operating Curve, AUC = 0.96) than the neural network classifier (AUC = 0.80). Further analysis provided the insight that serum albumin concentration, total prenatal nutritional intake, and peak dose of dopamine drug played an important role in predicting the mortality of SICU patients.

Conclusion: Our results suggest that machine learning algorithms, especially the decision tree method, can provide information on structured and explainable decision flow and accurately predict hospital mortality in SICU hospitalized patients.

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

BACKGROUND

Severe sepsis and septic shock are among the leading causes of death in the United States and sepsis remains one of the most expensive conditions to diagnose and treat. Accurate early diagnosis and treatment can reduce the risk of adverse patient outcomes, but the efficacy of traditional rule-based screening methods is limited. The purpose of this study was to develop and validate a machine learning algorithm (MLA) for severe sepsis prediction up to 48 h before onset using a diverse patient dataset.

METHODS

Retrospective analysis was performed on datasets composed of de-identified electronic health records collected between 2001 and 2017, including 510,497 inpatient and emergency encounters from 461 health centers collected between 2001 and 2015, and 20,647 inpatient and emergency encounters collected in 2017 from a community hospital. MLA performance was compared to commonly used disease severity scoring systems and was evaluated at 0, 4, 6, 12, 24, and 48 h prior to severe sepsis onset.

RESULTS

270,438 patients were included in analysis. At time of onset, the MLA demonstrated an AUROC of 0.931 (95% CI 0.914, 0.948) and a diagnostic odds ratio (DOR) of 53.105 on a testing dataset, exceeding MEWS (0.725, P < .001; DOR 4.358), SOFA (0.716; P < .001; DOR 3.720), and SIRS (0.655; P < .001; DOR 3.290). For prediction 48 h prior to onset, the MLA achieved an AUROC of 0.827 (95% CI 0.806, 0.848) on a testing dataset. On an external validation dataset, the MLA achieved an AUROC of 0.948 (95% CI 0.942, 0.954) at the time of onset, and 0.752 at 48 h prior to onset.

CONCLUSIONS

The MLA accurately predicts severe sepsis onset up to 48 h in advance using only readily available vital signs extracted from the existing patient electronic health records. Relevant implications for clinical practice include improved patient outcomes from early severe sepsis detection and treatment.

Evaluation of prognostic value of MEDS, MEWS, and CURB-65 criteria and sepsis I and sepsis III criteria in patients with community-acquired infection in emergency department

Background:

Early and effective treatment of patients with sepsis requires early recognition in emergency department and understanding the severity of the disease. Many studies have been conducted for this purpose, and many of scoring systems have been developed that provide early recognition of these patients and show their severity.

Objectives:

The aim of this study is to evaluate the efficacy of the scoring systems used to determine the mortality of patients with infections admitted in emergency department.

Methods:

In all, 400 patients who admitted to Uludağ University Hospital Emergency Department were prospectively included in this study. In addition to Systemic Inflammatory Response Syndrome score, Quick SOFA score, Mortality in Emergency Department Sepsis score, Modified Early Warning Score, and Charlson Comorbidity Index score in all patients, CURB-65 score was calculated in the patients diagnosed with pneumonia. It has been aimed to determine the power of these scores’ predictive mortality rates and their superiority to each other.

Results:

It was found that Mortality in Emergency Department Sepsis score and Quick SOFA score could be used with similar efficacy (respectively p = 0.761 and p = 0.073) in determining early mortality in emergency department (5th and 14th days) and that MEDS score was more effective (p < 0.001) in predicting the 28th-day mortality. While these recommendations were valid in patients diagnosed with pneumonia, it was determined that CURB-65 score could also be used to estimate 5th-, 14th-, and 28th-day mortalities (respectively, for the 5th day, p = 0.894 and p = 0.256; for the 14th day, p = 0.425 and p = 0.098; and for the 28th day, p = 0.095 and p = 0.158). The power of Systemic Inflammatory Response Syndrome score, previously used to identify sepsis, in predicting mortality was detected to be lower.

Conclusion:

Mortality in Emergency Department Sepsis score and Quick SOFA score could be used with similar efficacy in determining early mortality in emergency department. However, if you want to predict 28th-day mortality rate, it can be better to use Mortality in Emergency Department Sepsis score or CURB-65 (in patients diagnosed with pneumonia).

Development and Validation of a Quick Sepsis-Related Organ Failure Assessment-Based Machine-Learning Model for Mortality Prediction in Patients with Suspected Infection in the Emergency Department

The quick sepsis-related organ failure assessment (qSOFA) score has been introduced to predict the likelihood of organ dysfunction in patients with suspected infection. We hypothesized that machine-learning models using qSOFA variables for predicting three-day mortality would provide better accuracy than the qSOFA score in the emergency department (ED). Between January 2016 and December 2018, the medical records of patients aged over 18 years with suspected infection were retrospectively obtained from four EDs in Korea. Data from three hospitals (n = 19,353) were used as training-validation datasets and data from one (n = 4234) as the test dataset. Machine-learning algorithms including extreme gradient boosting, light gradient boosting machine, and random forest were used. We assessed the prediction ability of machine-learning models using the area under the receiver operating characteristic (AUROC) curve, and DeLong's test was used to compare AUROCs between the qSOFA scores and qSOFA-based machine-learning models. A total of 447,926 patients visited EDs during the study period. We analyzed 23,587 patients with suspected infection who were admitted to the EDs. The median age of the patients was 63 years (interquartile range: 43-78 years) and in-hospital mortality was 4.0% (n = 941). For predicting three-day mortality among patients with suspected infection in the ED, the AUROC of the qSOFA-based machine-learning model (0.86 [95% CI 0.85-0.87]) for three -day mortality was higher than that of the qSOFA scores (0.78 [95% CI 0.77-0.79], p < 0.001). For predicting three-day mortality in patients with suspected infection in the ED, the qSOFA-based machine-learning model was found to be superior to the conventional qSOFA scores.

Admittances characteristics by sepsis in the Spanish internal medicine services between 2005 and 2015: mortality pattern

BACKGROUND

Studies in recent years suggest an increase in the incidence of sepsis but a decrease in mortality. The aim of this study is to describe the characteristics of patients discharged after a sepsis episode from Spanish internal medicine services between 2005 and 2015.

RESULTS

Since 2005, in which there were a total of 4,319 cases, sepsis hospitalizations has been consistently increasing yearly reaching a total of 25,820 cases in 2015. We observed that septic patients are older and with higher comorbidity than the general population admitted in Internal Medicine. On the other hand, we found a decreasing trend in the mortality rates of patients with sepsis in our series going from 35.7% in 2005 to 30.1% in 2015 (p < 0.005).

DISCUSSION

In our study, a higher comorbidity at admission and developing complications during admittance, conditioned a higher probability of death due to sepsis. The variables that were associated with increased mortality risk were age, acute renal failure, acute respiratory failure, lactic acidosis, septic shock and chronic heart failure.

CONCLUSION

As in other similar studies, we observed an increase in the hospitalizations by sepsis as a diagnosis at discharge during the study period in Internal Medicine services with a simultaneous decrease in mortality. Comorbidity at admission and complications during admittance condition mortality.

Performance Assessment of the Mortality in Emergency Department Sepsis Score, Modified Early Warning Score, Rapid Emergency Medicine Score, and Rapid Acute Physiology Score in Predicting Survival Outcomes of Adult Renal Abscess Patients in the Emergency Department

Background

Renal abscess is a relatively uncommon yet debilitating and potentially fatal disease. There is no clearly defined, objective risk stratification tool available for emergency physicians' and surgeons' use in the emergency department (ED) to quickly determine the appropriate management strategy for these patients, despite early intervention having a beneficial impact on survival outcomes.

Objective

This case control study evaluates the performance of Mortality in Emergency Department Sepsis Score (MEDS), Modified Early Warning Score (MEWS), Rapid Emergency Medicine Score (REMS), and Rapid Acute Physiology Score (RAPS) in predicting risk of mortality in ED adult patients with renal abscess. This will help emergency physicians, surgeons, and intensivists expedite the time-sensitive decision-making process.

Methods

Data from 152 adult patients admitted to the EDs of two training and research hospitals who had undergone a contrast-enhanced computed tomography scan of the abdomen and was diagnosed with renal abscess from January 2011 to December 2015 were analyzed, with the corresponding MEDS, MEWS, REMS, RAPS, and mortality risks calculated. Ability to predict patient mortality was assessed via receiver operating curve analysis and calibration analysis.

Results

MEDS was found to be the best performing physiologic scoring system, with sensitivity, specificity, and accuracy of 87.50%, 88.89%, and 88.82%, respectively. Area under receiver operating characteristic curve (AUROC) value was 0.9440, and negative predictive value was 99.22% with a cutoff of 9 points.

Conclusion

Our study is the largest of its kind in examining ED patients with renal abscess. MEDS has been demonstrated to be superior to MEWS, REMS, and RAPS in predicting mortality for this patient population. We recommend its use for evaluation of disease severity and risk stratification in these patients, to expedite identification of critically ill patients requiring urgent intervention.

Early Warning Scores do not accurately predict mortality in sepsis: A meta-analysis and systematic review of the literature

OBJECTIVES

Early Warning Scores are used to evaluate patients in many hospital settings. It is not clear if these are accurate in predicting mortality in sepsis. We performed a systematic review and meta-analysis of multiple studies in sepsis. Our aim was to estimate the accuracy of EWS for mortality in this setting.

METHODS

PubMED, CINAHL, Cochrane, Web of Science and EMBASE were searched to October 2016. Studies of adults with sepsis who had EWS calculated using any appropriate tool (e.g. NEWS, MEWS) were eligible for inclusion. Study quality was assessed using QUADAS-2. Summary estimates were derived using HSROC analysis.

RESULTS

Six studies (4298 participants) were included. Results suggest that EWS cannot be used to predict which patients with sepsis will (positive likelihood ratio 1.79, 95% CI 1.53 to 2.11) or will not die (negative likelihood ratio 0.59, 95% CI 0.45 to 0.78). Two studies were rated as low risk of bias and one as unclear risk of bias on all domains. The other three studies were judged at high risk of bias in one domain.

CONCLUSION

Early Warning Scores are not sufficiently accurate to rule in or rule out mortality in patients with sepsis, based on the evidence available, which is generally poor quality.

The effectiveness of physiologically based early warning or track and trigger systems after triage in adult patients presenting to emergency departments: a systematic review

BACKGROUND

Changes to physiological parameters precede deterioration of ill patients. Early warning and track and trigger systems (TTS) use routine physiological measurements with pre-specified thresholds to identify deteriorating patients and trigger appropriate and timely escalation of care. Patients presenting to the emergency department (ED) are undiagnosed, undifferentiated and of varying acuity, yet the effectiveness and cost-effectiveness of using early warning systems and TTS in this setting is unclear. We aimed to systematically review the evidence on the use, development/validation, clinical effectiveness and cost-effectiveness of physiologically based early warning systems and TTS for the detection of deterioration in adult patients presenting to EDs.

METHODS

We searched for any study design in scientific databases and grey literature resources up to March 2016. Two reviewers independently screened results and conducted quality assessment. One reviewer extracted data with independent verification of 50% by a second reviewer. Only information available in English was included. Due to the heterogeneity of reporting across studies, results were synthesised narratively and in evidence tables.

RESULTS

We identified 6397 citations of which 47 studies and 1 clinical trial registration were included. Although early warning systems are increasingly used in EDs, compliance varies. One non-randomised controlled trial found that using an early warning system in the ED may lead to a change in patient management but may not reduce adverse events; however, this is uncertain, considering the very low quality of evidence. Twenty-eight different early warning systems were developed/validated in 36 studies. There is relatively good evidence on the predictive ability of certain early warning systems on mortality and ICU/hospital admission. No health economic data were identified.

CONCLUSIONS

Early warning systems seem to predict adverse outcomes in adult patients of varying acuity presenting to the ED but there is a lack of high quality comparative studies to examine the effect of using early warning systems on patient outcomes. Such studies should include health economics assessments.

Prognostic value of early warning scores in the emergency department (ED) and acute medical unit (AMU): A narrative review

BACKGROUND

A wide array of early warning scores (EWS) have been developed and are used in different settings to detect which patients are at risk of deterioration. The aim of this review is to provide an overview of studies conducted on the value of EWS on predicting intensive care (ICU) admission and mortality in the emergency department (ED) and acute medical unit (AMU).

METHODS

A literature search was conducted in the bibliographic databases PubMed and EMBASE, from inception to April 2017. Two reviewers independently screened all potentially relevant titles and abstracts for eligibility.

RESULTS

42 studies were included. 36 studies reported on mortality as an endpoint, 13 reported ICU admission and 9 reported the composite outcome of mortality and ICU admission. For mortality prediction National Early Warning Score (NEWS) was the most accurate score in the general ED population and in those with respiratory distress, Mortality in Emergency Department Sepsis score (MEDS) had the best accuracy in patients with an infection or sepsis. ICU admission was best predicted with NEWS, however in patients with an infection or sepsis Modified Early Warning Score (MEWS) yielded better results for this outcome.

CONCLUSION

MEWS and NEWS generally had favourable results in the ED and AMU for all endpoints. Many studies have been performed on ED and AMU populations using heterogeneous prognostic scores. However, future studies should concentrate on a simple and easy to use prognostic score such as NEWS with the aim of introducing this throughout the (pre-hospital and hospital) acute care chain.

Ambulance patients with nondocumented sepsis have a high mortality risk: a retrospective study

OBJECTIVE

Sepsis is a serious disease leading to high mortality. Early recognition is important because treatment is most effective when started quickly.The primary aim of this retrospective cohort study was to assess how many sepsis patients are documented as septic by ambulance staff. The secondary aims were to investigate how many sepsis patients are transported by ambulance, to compare them with patients transported otherwise, to investigate which factors influence documentation of sepsis and to assess whether documentation influences mortality.

METHODS

We retrieved all data from ambulance and emergency department charts of patients who visited the internist in the emergency department from March 2011 to July 2012.

RESULTS

In total, 47.4% (n=363) sepsis patients were transported by ambulance. These patients were older (71.5 vs. 55.7 years, P<0.0001), admitted more frequently (97.2 vs. 85.4%, P<0.001), significantly more frequently had severe sepsis (47.4 vs. 25.8%, P<0.0001) or septic shock (12.4 vs. 4.0%, P<0.0001), and died more frequently within 28 days (17.9 vs. 7.2%, P<0.0001) than those who were transported otherwise.In 41.9% of ambulance patients, sepsis was not documented by ambulance staff. Measurement of temperature was important for documentation of sepsis (odds ratio 11.2, 95% confidence interval 5.2-24.4). In 32.1% of ambulance patients, sepsis could have been identified by assessing vital signs. Mortality in these nondocumented patients was higher than that in documented patients (25.7 vs. 12.9%, P=0.003).

CONCLUSION

Ambulance patients are seriously ill, but sepsis is often not documented by ambulance staff. Nondocumentation is associated with high mortality and could be resolved by assessing vital signs, particularly the temperature.

Diagnostic accuracy of lipopolysaccharide-binding protein for sepsis in patients with suspected infection in the emergency department

Background Biomarkers can facilitate the diagnosis of sepsis, enabling early management and improving outcomes. Lipopolysaccharide-binding protein (LBP) has been reported as a biomarker for the detection of infection, but its diagnostic value is controversial. In this study, we assessed the diagnostic accuracy of LBP for sepsis in the emergency department (ED) patients, comparing it with more established biomarkers of sepsis, including procalcitonin (PCT) and C-reactive protein (CRP). Methods LBP and other sepsis biomarkers, including PCT and CRP, were measured on admission in 102 adult patients presenting with suspected infection . Classification of patients was performed using the recently updated definition for sepsis (Sepsis-3). The diagnostic accuracy of LBP, CRP and PCT for sepsis was evaluated by using receiver operating characteristic curve (ROC) analysis. Results A total of 49 patients were classified as having sepsis. In these patients, median (interquartile range) LBP (41.8 [41.1] µg/dL vs. 26.2 [25] µg/dL), CRP (240 [205] mg/L vs. 160 [148] mg/dL) and PCT (5.19 [13.68] µg/L vs. 0.39 [1.09] µg/L) were significantly higher than in patients classified as not having sepsis ( P < 0.001 for all three biomarkers). ROC curve analysis and area under curve (AUC) revealed a value of 0.701 for LBP, similar to CRP (0.707) and lower than that for PCT (0.844) ( P = 0.012). Conclusion In adult ED patients with suspected infection, the diagnostic accuracy for sepsis of LBP is similar to that of CRP but lower than that of PCT.

Sepsis recognition in the emergency department - impact on quality of care and outcome?

Background

Appropriate and timely recognition of sepsis is a prerequisite for starting goal-directed therapy bundles. We analyzed the appropriateness of sepsis recognition and documentation with regard to adequacy of therapy and outcome in an internal medicine emergency department (ED).

Methods

This study included 487 consecutive patients ≥18 years of age who presented to a university hospital ED during a 4-week period. Clinical, laboratory, and follow-up data were acquired independently from documentation by ED physicians. The study team independently rated quality of sepsis classification (American College of Chest Physicians/Society of Critical Care Medicine definitions), diagnostic workup, and guideline-adherent therapy in the ED.

Results

Of 487 included patients, 110 presented because of infection. Of those, 54 patients matched sepsis criteria, including 20 with organ damage and thus severe sepsis, as rated by the study team. Sepsis was not recognized in 32 of these 54 cases (59%). Multivariate binary logistic regression analysis revealed that higher systolic blood pressure (p <0.05), the ability to stand (p <0.01) and a low number of documented vital signs in the ED discharge letter (p < 0.05) were independent predictors of missed sepsis. Surprisingly, adequate detection of the septic focus (81 vs. 93%, p = 0.17), appropriate fluid administration (86 vs. 87%, p = 0.39), and guideline-adherent antibiotic regimen (95 vs. 100%, p = 0.42) did not differ between cases of recognized and unrecognized sepsis, respectively. Non-recognition affected neither death-censored length of hospital stay (median 7.63 d vs. 7.13 d, p = 0.42) nor a combined endpoint of death or ICU admission to (9 vs. 12%, p = 0.55).

Conclusions

Non-recognition of sepsis in ED patients with serious infections who formally meet organizational sepsis definitions seems to have no deleterious impact on initial therapy adequacy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12873-017-0122-9) contains supplementary material, which is available to authorized users.

Scoping review: The use of early warning systems for the identification of in-hospital patients at risk of deterioration

INTRODUCTION

Early warning systems (EWS) were developed as a means of alerting medical staff to patient clinical decline. Since 85% of severe adverse events are preceded by abnormal physiological signs, the patient bed-side vital signs observation chart has emerged as an EWS tool to help staff identify and quantify deteriorating patients. There are three broad categories of patient observation chart EWS: single or multiple parameter systems; aggregated weighted scoring systems; or combinations of single or multiple parameter and aggregated weighted scoring systems.

OBJECTIVE

This scoping review is an overview of quantitative studies and systematic reviews examining the efficiency of the adult EWS charts in the recognition of in-hospital patient deterioration.

METHOD

A broad search was undertaken of peer-reviewed publications, official government websites and databases housing research theses, using combinations of keywords and phrases.

DATA SOURCES

CINAHL with full text; MedLine, PsycINFO, MasterFILE Premier, GreenFILE and ScienceDirect. Also, the Cochrane Library database, Department of Health government websites and Ethos, ProQuest and Trove databases were searched.

EXCLUSIONS

Paediatric, obstetric and intensive care studies, studies undertaken at the point of hospital admission or pre-admission, non-English publications and editorials.

RESULTS

Five hundred and sixty five publications, government documents, reports and theses were located of which 91 were considered and 21 were included in the scoping review. Of the 21 publications eight studies compared the efficacy of various EWS and 13 publications validated specific EWS.

CONCLUSIONS

There is low level quantitative evidence that EWS improve patient outcomes and strong anecdotal evidence that they augment the ability of the clinical staff to recognise and respond to patient decline, thus reducing the incidence of severe adverse events. Although aggregated weighted scoring systems are most frequently used, the efficiency of the specific EWS appears to be dependent on the patient cohort, facilities available and staff training and attitude. While the review demonstrates support for EWS, researchers caution that given the contribution of human factors to the EWS decision-making process, patient EWS charts alone cannot replace good clinical judgment.

Dyschloremia Is a Risk Factor for the Development of Acute Kidney Injury in Critically Ill Patients

Introduction

Dyschloremia is common in critically ill patients, although its impact has not been well studied. We investigated the epidemiology of dyschloremia and its associations with the incidence of acute kidney injury and other intensive care unit outcomes.

Material and Methods

This is a single-center, retrospective cohort study at Mayo Clinic Hospital—Rochester. All adult patients admitted to intensive care units from January 1^st, 2006, through December 30^th, 2012 were included. Patients with known acute kidney injury and chronic kidney disease stage 5 before intensive care unit admission were excluded. We evaluated the association of dyschloremia with ICU outcomes, after adjustments for the effect of age, gender, Charlson comorbidity index and severity of illness score.

Results

A total of 6,025 patients were enrolled in the final analysis following the implementation of eligibility criteria. From the cohort, 1,970 patients (33%) developed acute kidney injury. Of the total patients enrolled, 4,174 had a baseline serum chloride. In this group, 1,530 (37%) had hypochloremia, and 257 (6%) were hyperchloremic. The incidence of acute kidney injury was higher in hypochloremic and hyperchloremic patients compared to those with a normal serum chloride level (43% vs.30% and 34% vs. 30%, respectively; P < .001). Baseline serum chloride was lower in the acute kidney injury group vs. the non-acute kidney injury group [100 mmol/L (96–104) vs. 102 mmol/L (98–105), P < .0001]. In a multivariable logistic regression model, baseline serum chloride of ≤94 mmol/L found to be independently associated with the risk of acute kidney injury (OR 1.7, 95% CI 1.1–2.6; P = .01).

Discussion

Dyschloremia is common in critically ill patients, and severe hypochloremia is independently associated with an increased risk of development of acute kidney injury.

Severity Scores in Emergency Department Patients With Presumed Infection: A Prospective Validation Study

OBJECTIVES

The objectives of this study were to 1) validate a number of severity of illness scores in a large cohort of emergency department patients admitted with presumed infection and 2) compare the performance of scores in patient subgroups with increasing mortality: infection without systemic inflammatory response syndrome, sepsis, severe sepsis, and septic shock.

DESIGN

Prospective, observational study.

SETTING

Adult emergency department in a metropolitan tertiary, university-affiliated hospital.

PATIENTS

Emergency department patients admitted with presumed infection.

INTERVENTIONS

None.

METHODS

Consecutive emergency department patients admitted with presumed infection were identified over 160 weeks in two periods between 2007 and 2011. Clinical and laboratory data sufficient to calculate Mortality in Emergency Department Sepsis score, Acute Physiology and Chronic Health Evaluation II, Simplified Acute Physiology Score II, Sequential Organ Failure Assessment, and the Severe Sepsis Score were entered into a database. Model discrimination was quantified using area under the receiver operating curve. Calibration was assessed using visual plots, Hosmer-Lemeshow statistics, and linear regressions of observed and predicted values.

MEASUREMENTS AND MAIN RESULTS

A total of 8,871 patients were enrolled with 30-day mortality of 3.7%. Area under the receiver operating curve values for the entire cohort were: Mortality in Emergency Department Sepsis score of 0.92, Simplified Acute Physiology Score II and Acute Physiology and Chronic Health Evaluation II scores of 0.90, Sequential Organ Failure Assessment score of 0.86, and Severe Sepsis Score of 0.82. Discrimination decreased in subgroups with greater mortality for each score. All scores overestimated mortality, but closest concordance between predicted and observed mortality was seen with Mortality in Emergency Department Sepsis score.

CONCLUSIONS

The decrease in area under the receiver operating curve seen in subgroups with increasing mortality may explain some variation in results seen in previous validation studies. Scores developed in intensive care settings overestimated mortality in the emergency department. Our results underscore the importance of employing predictive models developed in similar patient populations. The Mortality in Emergency Department Sepsis score outperformed more complex predictive models and would be the most appropriate scoring system for use in similar emergency department populations with a wide spectrum of mortality risk.

Severe sepsis and septic shock in pre-hospital emergency medicine: survey results of medical directors of emergency medical services concerning antibiotics, blood cultures and algorithms

Delayed antibiotic treatment for patients in severe sepsis and septic shock decreases the probability of survival. In this survey, medical directors of different emergency medical services (EMS) in Germany were asked if they are prepared for pre-hospital sepsis therapy with antibiotics or special algorithms to evaluate the individual preparations of the different rescue areas for the treatment of patients with this infectious disease. The objective of the survey was to obtain a general picture of the current status of the EMS with respect to rapid antibiotic treatment for sepsis. A total of 166 medical directors were invited to complete a short survey on behalf of the different rescue service districts in Germany via an electronic cover letter. Of the rescue districts, 25.6 % (n = 20) stated that they keep antibiotics on EMS vehicles. In addition, 2.6 % carry blood cultures on the vehicles. The most common antibiotic is ceftriaxone (third generation cephalosporin). In total, 8 (10.3 %) rescue districts use an algorithm for patients with sepsis, severe sepsis or septic shock. Although the German EMS is an emergency physician-based rescue system, special opportunities in the form of antibiotics on emergency physician vehicles are missing. Simultaneously, only 10.3 % of the rescue districts use a special algorithm for sepsis therapy. Sepsis, severe sepsis and septic shock do not appear to be prioritized as highly as these deadly diseases should be in the pre-hospital setting.

Cardiac Troponin Is a Predictor of Septic Shock Mortality in Cancer Patients in an Emergency Department: A Retrospective Cohort Study

Background

Septic shock may be associated with myocardial damage; however, the prognostic value of cardiac enzymes in cancer patients with septic shock is unknown. In this study, we evaluated the prognostic significance of cardiac enzymes in combination with established prognostic factors in predicting the 7-day mortality rate of patients with septic shock, and we constructed a new scoring system, Septic Oncologic Patients in Emergency Department (SOPED), which includes cardiac enzymes, to predict 7-day mortality rates.

Methods and Findings

We performed a retrospective cohort study of 375 adult cancer patients with septic shock who visited the emergency department of a comprehensive cancer center between 01/01/2004 and 12/31/2013. The 7-day and 28-day mortality rates were 19.7% and 37.6%, respectively. The creatine kinase myocardial band fraction and troponin-I were significantly higher in patients who died in ≤7 days and ≤28 days than in those who did not. In Cox regression models, troponin-I >0.05 ng/mL plus Predisposition, Infection, Response, and Organ Failure (PIRO2011) or Mortality in Emergency Department Sepsis (MEDS) score was a significant predictor of survival for ≤7 days. With our new SOPED scoring system, the receiver operating characteristic area under the curve was 0.836, higher than those for PIRO2011 and MEDS.

Conclusions

Troponin-I >0.05 ng/mL was an important predictor of short-term mortality (≤7 days). The SOPED scoring system, which incorporated troponin-I, was more prognostically accurate than were other scores for 7-day mortality. Large multicenter studies are needed to verify our results and prospectively validate the prognostic performance of the SOPED score.

Early warning score: a dynamic marker of severity and prognosis in patients with Gram-negative bacteraemia and sepsis

Background

Early Warning Score (EWS) is a physiological composite score of six bedside vital parameters, routinely used in UK hospitals. We evaluated the prognostic ability of EWS in Gram-negative bacteraemia causing sepsis.

Methods

We prospectively evaluated EWS as a marker of severity and prognosis in adult patients with Gram-negative bacteraemia. All adult patients with Gram-negative bacteraemia admitted to our tertiary Teaching hospital of the National Health Service in England were enrolled over 1 year period. The highest daily EWS score was recorded from 7 days before to 14 days after the date of onset of bacteraemia. The primary outcome was 28-day mortality.

Main results

A total of 245 consecutive adult patients with Gram-negative bacteraemia with sepsis were enrolled. On multivariate analysis, following variables were associated with death for every single unit change (odds ratio in the brackets): higher age (1.05), lower mean arterial pressure (1.03), lower serum bicarbonate (1.08), higher EWS (1.27), higher SOFA score (1.36), hospital-onset of infection (5.43) and need for vasopressor agents (16.4). EWS on day 0, 1, 2, and average 14-day score were significantly higher in patients who died by 28 days from the onset of bacteraemia [95 % CI 0.4–0.6] p < 0.001. A stepwise rise in EWS and failure of improvement in EWS by 2 points 48 h after the onset of bacteraemia were associated with poor outcome.

Conclusion

EWS is a simple and cost-effective bedside tool for the assessment of severity and prognosis of sepsis caused by Gram-negative bacteraemia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12941-016-0139-z) contains supplementary material, which is available to authorized users.

Value of plasma neutrophil gelatinase-associated lipocalin in predicting the mortality of patients with sepsis at the emergency department

BACKGROUND

Sepsis is a major cause of morbidity and mortality in the emergency department. This study aimed to evaluate the assessment of severity of sepsis by and prognostic value of plasma neutrophil gelatinase-associated lipocalin (NGAL) compared with other widely used biological markers of inflammation in patients with sepsis.

METHODS

NGAL, procalcitonin, and C-reactive protein values were measured in 470 patients with suspected sepsis, and the Mortality in Emergency Department Sepsis (MEDS) score was obtained for all enrolled subjects, who were followed for up to 28days.

RESULTS

The median plasma NGAL value was increased with sepsis severity according to the MEDS score. The plasma NGAL value was higher in nonsurvivors than in survivors. The area under the receiver operating characteristic curve of NGAL (0.797) was greater than that of procalcitonin (0.599) and MEDS score (0.774) in predicting 28-day hospital mortality. Multivariable logistic regression found that the plasma NGAL value was an independent predictor for hospital mortality in patients with sepsis. The plasma NGAL values were positively correlated with C-reactive protein and procalcitonin levels, and MEDS scores.

CONCLUSIONS

Plasma NGAL is a valuable biological marker in the assessment of severity and prediction of prognosis of patients with sepsis in the emergency department.

National early warning score at Emergency Department triage may allow earlier identification of patients with severe sepsis and septic shock: a retrospective observational study

INTRODUCTION

Severe sepsis and septic shock (SS) are time-critical medical emergencies that affect millions of people in the world. Earlier administration of antibiotics has been shown to reduce mortality from SS; however, the initiation of early resuscitation requires recognition that a patient may have sepsis. Early warning scores (EWS) are broadly used to detect patient deterioration, but to date have not been evaluated to detect patients at risk for SS. The purpose of our study was to look at the relationship between the initial national EWS (NEWS) in the emergency department (ED) and the diagnosis of SS.

METHODS

We performed a retrospective, single-centre, observational study in the ED of an urban university hospital with an annual attendance of 140,000 patients. We aimed to include 500 consecutive non-trauma adult patients presenting to the ED with Manchester Triage System (MTS) category 1-3. The final diagnosis was taken from either the ED medical records or the hospital discharge summary. For all NEWS, the sensitivity and specificity to detect patients with SS was calculated.

RESULTS

A total of 500 patients were included, 27 patients (5.4%) met the criteria for SS. The area under the curve (AUC) for NEWS to identify patient at risk for SS is 0.89 (95% CI 0.84 to 0.94). A NEWS of 3 or more at ED triage has a sensitivity of 92.6% (95% CI 74.2% to 98.7%) and a specificity of 77% (95% CI 72.8% to 80.6%) to detect patients at risk for SS at ED triage.

CONCLUSIONS

A NEWS of 3 or more at ED triage may be the trigger to systematically screen the patient for SS, which may ultimately lead to early recognition and treatment.

Higher serum chloride concentrations are associated with acute kidney injury in unselected critically ill patients

BACKGROUND

Chloride administration has been found to be harmful to the kidney in critically ill patients. However the association between plasma chloride concentration and renal function has never been investigated.

METHODS

This was a retrospective study conducted in a tertiary 24-bed intensive care unit from September 2010 to November 2012. Data on serum chloride for each patient during their ICU stay were abstracted from electronic database. Cl0 referred to the initial chloride on ICU entry, Cl(max), Cl(min) and Cl(mean) referred to the maximum, minimum and mean chloride values before the onset of AKI, respectively. AKI was defined according to the conventional AKIN criteria. Univariate and multivariable analysis were performed to examine the association of chloride and AKI development.

RESULTS

A total of 1221 patients were included into analysis during study period. Three hundred and fifty-seven patients (29.2%) developed AKI. Cl(max) was significantly higher in AKI than in non-AKI group (111.8 ± 8.1 vs 107.9 ± 5.4 mmol/l; p < 0.001); Cl0 was not significantly different between AKI and non-AKI patients; Cl(mean) was significantly higher in AKI than non-AKI (104.3 ± 5.8 vs 103.4 ± 4.5;  = 0.0047) patients. Cl(max) remained to be associated with AKI in multivariable analysis (OR: 1.10, 95% CI: 1.08-1.13).

CONCLUSION

Chloride overload as represented by Cl(mean) and Cl(max) is significantly associated with the development of AKI.