Incidence and risk factors associated with early death in patients with emergency department septic shock

Comparison of Early and Late Norepinephrine Administration in Patients With Septic Shock: A Systematic Review and Meta-analysis

BACKGROUND

Vasopressor administration at an appropriate time is crucial, but the optimal timing remains controversial.

RESEARCH QUESTION

Does early vs late norepinephrine administration impact the prognosis of septic shock?

STUDY DESIGN AND METHODS

Searches were conducted in PubMed, EMBASE, the Cochrane Library, and KMbase databases. We included studies of adults with sepsis and categorized patients into an early and late norepinephrine group according to specific time points or differences in norepinephrine use protocols. The primary outcome was overall mortality. The secondary outcomes included length of stay in the ICU, days free from ventilator use, days free from renal replacement therapy, days free from vasopressor use, adverse events, and total fluid volume.

RESULTS

Twelve studies (four randomized controlled trials [RCTs] and eight observational studies) comprising 7,281 patients were analyzed. For overall mortality, no significant difference was found between the early norepinephrine group and late norepinephrine group in RCTs (OR, 0.70; 95% CI, 0.41-1.19) or observational studies (OR, 0.83; 95% CI, 0.54-1.29). In the two RCTs without a restrictive fluid strategy that prioritized vasopressors and lower IV fluid volumes, the early norepinephrine group showed significantly lower mortality than the late norepinephrine group (OR, 0.49; 95%, CI, 0.25-0.96). The early norepinephrine group demonstrated more mechanical ventilator-free days in observational studies (mean difference, 4.06; 95% CI, 2.82-5.30). The incidence of pulmonary edema was lower in the early norepinephrine group in the three RCTs that reported this outcome (OR, 0.43; 95% CI, 0.25-0.74). No differences were found in the other secondary outcomes.

INTERPRETATION

Overall mortality did not differ significantly between early and late norepinephrine administration for septic shock. However, early norepinephrine administration seemed to reduce pulmonary edema incidence, and mortality improvement was observed in studies without fluid restriction interventions, favoring early norepinephrine use.

Predicting sepsis at emergency department triage: Implementing clinical and laboratory markers within the first nursing assessment to enhance diagnostic accuracy

BACKGROUND

Early identification of sepsis in the emergency department (ED) triage is both valuable and challenging. Numerous studies have endeavored to pinpoint clinical and biochemical criteria to assist clinicians in the prompt diagnosis of sepsis, but few studies have assessed the efficacy of these criteria in the ED triage setting. The aim of the study was to explore the accuracy of clinical and laboratory markers evaluated at the triage level in identifying patients with sepsis.

METHODS

A prospective study was conducted in a large academic urban hospital, implementing a triage protocol aimed at early identification of septic patients based on clinical and laboratory markers. A multidisciplinary panel of experts reviewed cases to ensure accurate identification of septic patients. Variables analyzed included: Charlson comorbidity index, mean arterial pressure (MAP), partial pressure of carbon dioxide (PetCO2), white cell count, eosinophil count, C-reactive protein to albumin ratio, procalcitonin, and lactate.

RESULTS

A total of 235 patients were included. Multivariable analysis identified procalcitonin ≥1 ng/mL (OR 5.2; p < 0.001); CRP-to-albumin ratio ≥32 (OR 6.6; p < 0.001); PetCO2 ≤ 28 mmHg (OR 2.7; p = 0.031), and MAP <85 mmHg (OR 7.5; p < 0.001) as independent predictors for sepsis. MAP ≥85 mmHg, CRP/albumin ratio <32, and procalcitonin <1 ng/mL demonstrated negative predictive values for sepsis of 90%, 89%, and 88%, respectively.

CONCLUSIONS

Our study underscores the significance of procalcitonin and mean arterial pressure, while introducing CRP/albumin ratio and PetCO2 as important variables to consider in the very initial assessment of patients with suspected sepsis in the ED.

CLINICAL RELEVANCE

Early identification of sepsis since the emergency department (ED) triage is challenging Implementing the ED triage protocol with simple clinical and laboratory markers allows to recognize patients with sepsis with a very good discriminatory power (AUC 0.88).

Early Prediction of Mortality for Septic Patients Visiting Emergency Room Based on Explainable Machine Learning: A Real-World Multicenter Study

BACKGROUND

Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department.

METHODS

This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO2/FIO2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine). The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley's additive explanations (SHAP).

RESULTS

Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756-0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626-0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results.

CONCLUSION

Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Red cell distribution width and in-hospital mortality in septic shock: A public database research

OBJECTIVE

This study aimed to explore the relationship between red cell distribution width (RDW) and in-hospital mortality in septic shock based on a large-scale public database.

METHODS

All patients with septic shock in MIMIC-IV were enrolled. Based on RDW values, the general characteristics of different groups were compared. Different models were constructed for exploring the association of RDW and in-hospital mortality. To assess the predictive value of RDW, receiver operator characteristic (ROC) curve analysis was applied.

RESULTS

A total of 3006 patients with septic shock were included and in-hospital mortality was 32.27% (n = 970). The results of the fully adjusted model demonstrated that RDW was positively associated with in-hospital mortality in septic shock patients after adjusting all confounders (OR = 1.12, 95% CI:1.08-1.17, p < .001). A linear relationship between RDW and in-hospital mortality was found. For predicting in-hospital mortality, the area under the ROC curve (AUC) of RDW was .602 and the best threshold of RDW was 17.25%.

CONCLUSION

RDW was associated with in-hospital mortality in septic shock. It could be a useful marker for predicting clinical outcomes in septic shock.