Predictive Validity of the qSOFA Score for Sepsis in Adults with Community-Onset Staphylococcal Infection in Thailand

Sepsis death risk factor score based on systemic inflammatory response syndrome, quick sequential organ failure assessment, and comorbidities

OBJECTIVE

In this study, we aimed to evaluate the death risk factors of patients included in the sepsis protocol bundle, using clinical data from qSOFA, SIRS, and comorbidities, as well as development of a mortality risk score.

DESIGN

This retrospective cohort study was conducted between 2016 and 2021.

SETTING

Two university hospitals in Brazil.

PARTICIPANTS

Patients with sepsis.

INTERVENTIONS

Several clinical and laboratory data were collected focused on SIRS, qSOFA, and comorbidities.

MAIN VARIABLE OF INTEREST

In-hospital mortality was the primary outcome variable. A mortality risk score was developed after logistic regression analysis.

RESULTS

A total of 1,808 patients were included with a death rate of 36%. Ten variables remained independent factors related to death in multivariate analysis: temperature ≥38 °C (odds ratio [OR] = 0.65), previous sepsis (OR = 1.42), qSOFA ≥ 2 (OR = 1.43), leukocytes >12,000 or <4,000 cells/mm3 (OR = 1.61), encephalic vascular accident (OR = 1.88), age >60 years (OR = 1.93), cancer (OR = 2.2), length of hospital stay before sepsis >7 days (OR = 2.22,), dialysis (OR = 2.51), and cirrhosis (OR = 3.97). Considering the equation of the binary regression logistic analysis, the score presented an area under curve of 0.668, is not a potential model for death prediction.

CONCLUSIONS

Several risk factors are independently associated with mortality, allowing the development of a prediction score based on qSOFA, SIRS, and comorbidities data, however, the performance of this score is low.

Performance of the Simple Clinical Score (SCS) and the Rapid Emergency Medicine Score (REMS) to predict severity level and mortality rate among patients with sepsis in the emergency department

Nurses play a key role as the first line of service for patients with medical conditions and injuries in the emergency department (ED), which includes assessing patients for sepsis. The researchers evaluated tools to examine the performance of the Simple Clinical Score (SCS) and the Rapid Emergency Medicine Score (REMS) to predict sepsis severity and mortality among sepsis patients in the ED. A retrospective survey was performed, selecting participants by using a purposive sampling method, and including the medical records of all patients diagnosed with sepsis admitted to the ED at Singburi Hospital, Thailand. Data were analysed using the ROC curve and the Area Under Curve (AUC) to calculate the accuracy of each patient's mortality prediction. A total of 225 patients diagnosed with sepsis was identified, with a mortality rate of 59.11% after admission to the medical service and intensive care unit. The AUC analysis showed that the accuracy of the model generated from the REMS (88.6%) was higher than that of the SCS (76.7%). The authors also recommend that key variables identified in this research should be used to develop screening and assessment tools for sepsis in the context of the ED.

Kigali Surgical Sepsis (KiSS) Score: A New Tool to Predict Outcomes in Surgical Patients with Sepsis in Low- and Middle-Income Settings

BACKGROUND

Sepsis is common in surgical patients, and its presence influences the outcomes in those to undergo surgery. Factors such as advanced age, presence of comorbidities and many other conditions increase mortality in surgical patients with sepsis. The sequential organ failure assessment (SOFA) score simplified into qSOFA helps to define sepsis and to identify patients who are likely to die from it. Sepsis in surgery is under investigated in low- and middle-income countries and so are the factors for mortality in that specific surgical population. Our aim was to develop a prognostic tool accurate in predicting outcomes in surgical patients with sepsis who present at University Teaching Hospitals of Kigali (CHUK) and Butare (CHUB) and in other centers with limited resources METHODS: This was a prospective cohort study conducted over a period of 1 year from February 2018 to January 2019. The surgical patients with sepsis recruited in the first 6 months at CHUK served as the derivation cohort and those recruited in the next 6 months from both CHUK and CHUB served as the validation cohort. The Kigali surgical sepsis (KiSS) score was derived, and to determine its accuracy in predicting mortality, we measured sensitivity, specificity and area under receiver operator characteristic (AUROC) curve. We then compared this with qSOFA score.

RESULTS

A total of 288 patients were recruited with 144 in each cohort. The mean age was 36.5, and median age was 32.6. The mean length of hospital stay (LoHS) was 22.9 days. The overall intensive care unit (ICU) admission rate was 51.4%, and the surgical sepsis-related hospital mortality rate was 21.7%. Factors associated with surgical sepsis-related hospital mortality were age above 55 years (p = 0.034), presence of comorbidities (p = 0.069), hypotension (p = 0.014), tachycardia (p = 0.061), tachypnea (p = 0.028), decreased level of consciousness (p = 0.021), presence of GIT perforation (p = 0.026) and number of impaired organ function (p = 0.035). A predictive score (KiSS score) consisting of six parameters was derived from these factors and compared to qSOFA score. The sensitivity of KiSS score in predicting mortality was 73% (vs 52% for qSOFA), and the specificity was 97% (vs 87% for qSOFA). The predictive validity for hospital mortality was assessed by AUROC curve, and it was 0.939 (95% CI, p < 0.001) for KiSS and 0.684 (95% CI, p < 0.001) for qSOFA.

CONCLUSION

The KiSS score was effective in predicting surgical sepsis-related hospital mortality in low-resource setting. The KiSS score showed an added advantage of stratifying septic surgical patients to be operated on into those with good, variable and poor prognosis.