Performance of NEWS2, RETTS, clinical judgment and the Predict Sepsis screening tools with respect to identification of sepsis among ambulance patients with suspected infection: a prospective cohort study

Sepsis incidence, suspicion, prediction and mortality in emergency medical services: a cohort study related to the current international sepsis guideline

PURPOSE

Sepsis suspicion by Emergency Medical Services (EMS) is associated with improved patient outcomes. This study assessed sepsis incidence and recognition by EMS and analyzed which of the screening tools recommended by the Surviving Sepsis Campaign best facilitates sepsis prediction.

METHODS

Retrospective cohort study of claims data from health insurances (n = 221,429 EMS cases), and paramedics' and emergency physicians' EMS documentation (n = 110,419); analyzed outcomes were: sepsis incidence and case fatality compared to stroke and myocardial infarction, the extent of documentation for screening-relevant variables and sepsis suspicion, tools' intersections for screening positive in identical EMS cases and their predictive ability for an inpatient sepsis diagnosis.

RESULTS

Incidence of sepsis (1.6%) was similar to myocardial infarction (2.6%) and stroke (2.7%); however, 30-day case fatality rate was almost threefold higher (31.7% vs. 13.4%; 11.8%). Complete vital sign documentation was achieved in 8.2% of all cases. Paramedics never, emergency physicians rarely (0.1%) documented a sepsis suspicion, respectively septic shock. NEWS2 had the highest sensitivity (73.1%; Specificity:81.6%) compared to qSOFA (23.1%; Sp:96.6%), SIRS (28.2%; Sp:94.3%) and MEWS (48.7%; Sp:88.1%). Depending on the tool, 3.7% to 19.4% of all cases screened positive; only 0.8% in all tools simultaneously.

CONCLUSION

Incidence and mortality underline the need for better sepsis awareness, documentation of vital signs and use of screening tools. Guidelines may omit MEWS and SIRS as recommendations for prehospital providers since they were inferior in all accuracy measures. Though no tool performed ideally, NEWS2 qualifies as the best tool to predict the highest proportion of septic patients and to rule out cases that are likely non-septic.

Evidence for Use of Validated Sepsis Screening Tools in the Prehospital Population: A Scoping Review

INTRODUCTION

Early detection and treatment of sepsis improves chances of survival; however, sepsis is often difficult to diagnose initially. This is especially true in the prehospital setting, where resources are scarce, yet time is of great significance. Early warning scores (EWS) based on vital signs were originally developed to guide medical practitioners in determining the degree of illness of a patient in the in-patient setting. These EWS were adapted for use in the prehospital setting to predict critical illness and sepsis. We performed a scoping review to evaluate the existing evidence for use of validated EWS to identify prehospital sepsis.

METHODS

We performed a systematic search using the CINAHL, Embase, Ovid-MEDLINE, and PubMed databases on September 1, 2022. Articles that examined the use of EWS to identify prehospital sepsis were included and assessed.

RESULTS

Twenty-three studies were included in this review: one validation study, two prospective studies, two systematic reviews, and 18 retrospective studies. Study characteristics, classification statistics, and primary conclusions of each article were extracted and tabulated. Classification statistics varied markedly for prehospital sepsis identification across all included EWS: sensitivities ranged from 0.02-1.00, specificities from 0.07-1.00, and PPV and NPV from 0.19-0.98 and 0.32-1.00, respectively.

CONCLUSIONS

All studies demonstrated inconsistency for the identification of prehospital sepsis. The variety of available EWS and study design heterogeneity suggest it is unlikely that new research can identify a single gold standard score. Based on our findings in this scoping review, we recommend future efforts focus on combining standardized prehospital care with clinical judgment to provide timely interventions for unstable patients where infection is considered a likely etiology, in addition to improving sepsis education for prehospital clinicians. At most, EWS can be used as an adjunct to these efforts, but they should not be relied on alone for prehospital sepsis identification.

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.