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

Predicting mortality in febrile adults: comparative performance of the MEWS, qSOFA, and UVA scores using prospectively collected data among patients in four health-care sites in sub-Saharan Africa and South-Eastern Asia

Background

Clinical severity scores can identify patients at risk of severe disease and death, and improve patient management. The modified early warning score (MEWS), the quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA), and the Universal Vital Assessment (UVA) were developed as risk-stratification tools, but they have not been fully validated in low-resource settings where fever and infectious diseases are frequent reasons for health care seeking. We assessed the performance of MEWS, qSOFA, and UVA in predicting mortality among febrile patients in the Lao PDR, Malawi, Mozambique, and Zimbabwe.

Methods

We prospectively enrolled in- and outpatients aged ≥ 15 years who presented with fever (≥37.5 °C) from June 2018-March 2021. We collected clinical data to calculate each severity score. The primary outcome was mortality 28 days after enrolment. The predictive performance of each score was determined using area under the receiver operating curve (AUC).

Findings

A total of 2797 participants were included in this analysis. The median (IQR) age was 32 (24-43) years, 38% were inpatients, and 60% (1684/2797) were female. By the time of follow-up, 7% (185/2797) had died. The AUC (95% CI) for MEWS, qSOFA and UVA were 0.67 (0.63-0.71), 0.68 (0.64-0.72), and 0.82 (0.79-0.85), respectively. The AUC comparison found UVA outperformed both MEWS (p < 0.001) and qSOFA (p < 0.001).

Interpretation

We showed that the UVA score performed best in predicting mortality among febrile participants by the time follow-up compared with MEWS and qSOFA, across all four study sites. The UVA score could be a valuable tool for early identification, triage, and initial treatment guidance of high-risk patients in resource-limited clinical settings.

Funding

FCDO.

Early sclerostin assessment in frail elderly patients with sepsis: insights on short- and long-term mortality prediction

Unmet needs challenge clinical management of sepsis especially concerning patient profiling, enhancing recovery, and long-term sequelae. Here, we preliminarily focused on sclerostin (SOST) as a candidate biomarker to encompass such a broad range of clinical needs related to sepsis. Seventy-three septic patients were enrolled at internal medicine wards between January 2017 and December 2019 in this pilot study. Clinical examination and blood sample analyses were collected at enrollment and after 7 and 14 days. SOST levels were assessed on serum by ELISA. Thirty-day mortality was set as primary outcome. In-hospital and long-term mortality (2.5 years of median follow-up) were assessed as secondary outcomes. Patients were frail, elderly, and heterogeneous in terms of comorbidity burden. SOST levels were associated with age, cardiovascular comorbidities, and time to early death (30 days). When regression models were built, SOST displayed a high predictive value toward 30-day mortality (OR 13.459 with 95% CI 1.226-148.017) with ever better performance than validated scoring scales for critical ill patients. Such a predictive value of SOST was further confirmed for in-hospital (HR 10.089 with 95% CI 1.375-74.013) and long-term mortality (HR 5.061 with 95% CI 1.379-18.570). SOST levels generally decreased over 7 to 14 days after enrollment (p for trend < 0.001). The degree of this variation further predicted long-term mortality (HR for Δ SOST T0-day 14: 1.006 with 95% CI 1.001-1.011). Our results suggest a role for SOST in both short- and long-time prediction of worse outcome in septic elderly admitted to internal medicine wards.

Classifying sepsis from photoplethysmography

Sepsis is a life-threatening organ dysfunction. It is caused by a dysregulated immune response to an infection and is one of the leading causes of death in the intensive care unit (ICU). Early detection and treatment of sepsis can increase the survival rate of patients. The use of devices such as the photoplethysmograph could allow the early evaluation in addition to continuous monitoring of septic patients. The aim of this study was to verify the possibility of detecting sepsis in patients from whom the photoplethysmographic signal was acquired via a pulse oximeter. In this work, we developed a deep learning-based model for sepsis identification. The model takes a single input, the photoplethysmographic signal acquired by pulse oximeter, and performs a binary classification between septic and nonseptic samples. To develop the method, we used MIMIC-III database, which contains data from ICU patients. Specifically, the selected dataset includes 85 septic subjects and 101 control subjects. The PPG signals acquired from these patients were segmented, processed and used as input for the developed model with the aim of identifying sepsis. The proposed method achieved an accuracy of 76.37% with a sensitivity of 70.95% and a specificity of 81.04% on the test set. As regards the ROC curve, the Area Under Curve reached a value of 0.842. The results of this study indicate how the plethysmographic signal can be used as a warning sign for the early detection of sepsis with the aim of reducing the time for diagnosis and therapeutic intervention. Furthermore, the proposed method is suitable for integration in continuous patient monitoring.

Predictive Value of Systemic Immune-inflammation Index in Determining Mortality in COVID-19 Patients

Aim

The aim of this study was to evaluate whether systemic immune-inflammation index (SII) could predict mortality in patients with novel coronavirus 2019 (COVID-19) disease.

Methods

This two-center, retrospective study included a total of 191 patients with confirmed diagnosis of COVID-19 via nucleic acid test (NAT). The SII was calculated based on the complete blood parameters (neutrophil × platelet/lymphocyte) during hospitalization. The relationship between the SII and other inflammatory markers and mortality was investigated.

Results

The mortality rate was 18.3%. The mean age was 54.32±17.95 years. The most common symptoms were fever (70.7%) and dry cough (61.3%), while 8 patients (4.2%) were asymptomatic. The most common comorbidities were hypertension (37.7%), diabetes (23.0%), chronic renal failure (14.7%), and heart failure (7.9%) which all significantly increased the mortality rate (p<0.001). There was a highly positive correlation between the SII and polymorphonuclear leukocyte (PNL), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) (r=0.754, p<0.001; r=0.812, p<0.001; r=0.841, p<0.001, respectively), while a moderate, positive correlation was found between the SII and C-reactive protein (CRP) (r=0.439, p<0.001). There was a significant correlation between the SII and mortality (U=1,357, p<0.001). The cut-off value of SII was 618.8 (area under the curve=0.751, p<0.001) with 80.0% sensitivity and 61.5% specificity. A cut-off value of >618.8 was associated with a 4.68-fold higher mortality.

Conclusion

Similar to NLR and PLR, the SII is a proinflammatory marker of systemic inflammation and can be effectively used in independent predicting COVID-19 mortality.

Retrospective Analysis of the Risk Factors and Drug Resistance of Pathogenic Bacteria in Systemic Inflammatory Response Syndrome After Ureteroscopic Holmium Laser Lithotripsy for Impacted Ureteral Calculi

Objective

To investigate the risk factors, pathogen distribution, and drug resistance of systemic inflammatory response syndrome (SIRS) after holmium laser ureteroscopic lithotripsy for impacted ureteral calculi (HLULIUC).

Patients and Methods

The clinical data of 293 patients with HLULIUC in our hospital from October 2017 to February 2021 were retrospectively collected, including age, BMI, stone size, operation time, urine routine, urine culture, basic illness, complete blood count, liver and kidney function, etc. Patients were divided into SIRS and non-SIRS groups according to whether they had SIRS or not. Then the differences in clinical data, blood and urine bacterial culture results, and drug resistance between the two groups were analyzed.

Results

The incidence of SIRS after HLULIUC was 17.75%. Logistic regression analysis showed that the risk factors of SIRS after HLULIUC include ureteral calculi≥1cm (OR=2.839, 95% CI=1.341–5.647, P=0.021), long operation time (OR=4.534, 95% CI=2.597–12.751, P=0.017), diabetes mellitus (OR=3.137, 95% CI=1.142–7.319, P=0.012), increased preoperative C-reactive protein (OR=1.864, 95% CI=1.05–4.347, P=0.032), and positive urine leukocytes (OR=3.514, 95% CI=1.7237–9.734, P=0.007) and culture (OR=6.034, 95% CI=3.097–15.751, P<0.001) before operation. The main pathogens causing SIRS after HLULIUC were Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Enterococcus faecalis, and Pseudomonas aeruginosa. The pathogenic bacteria are sensitive to drugs including piperacillin/tazobactam, meropenem, tigecycline, teicoplanin, vancomycin, and imipenem. The resistance rates to quinolones (such as levofloxacin) and to the second- and third-generations of cephalosporins were as high as 52.94%–90.19%.

Conclusion

Ureteral calculi≥1cm, long operation time, diabetes, increased C-reactive protein, and preoperative positive urine leukocytes and culture are independent risk factors of SIRS after HLULIUC. Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Enterococcus faecalis, and Pseudomonas aeruginosa are the main pathogenic bacteria for SIRS after HLULIUC. The pathogenic bacteria are sensitive to drugs, including piperacillin/tazobactam, meropenem, tigecycline, teicoplanin, vancomycin, and imipenem.

Comparison of QSOFA and sirs scores for the prediction of adverse outcomes of secondary peritonitis among patients admitted on the adult surgical ward in a tertiary teaching hospital in Uganda: a prospective cohort study

BACKGROUND

SIRS and qSOFA are two ancillary scoring tools that have been used globally, inside and outside of ICU to predict adverse outcomes of infections such as secondary peritonitis. A tertiary teaching hospital in Uganda uses SIRS outside the ICU to identify patients with secondary peritonitis, who are at risk of adverse outcomes. However, there are associated delays in decision making given SIRS partial reliance on laboratory parameters which are often not quickly available in a resource limited emergency setting. In response to the practical limitations of SIRS, the sepsis-3 task force recommends qSOFA as a better tool. However, its performance in patients with secondary peritonitis in comparison to that of SIRS has not been evaluated in a resource limited setting of a tertiary teaching hospital in a low and middle income country like Uganda.

OBJECTIVE

To compare the performance of qSOFA and SIRS scores in predicting adverse outcomes of secondary peritonitis among patients on the adult surgical wards in a tertiary teaching hospital in Uganda.

METHODS

This was a prospective cohort study of patients with clinically confirmed secondary peritonitis, from March 2018 to January 2019 at the Accident and Emergency unit and the adult surgical wards of a tertiary teaching hospital in Uganda. QSOFA and SIRS scores were generated for each patient, with a score of ≥2 recorded as high risk, while a score of < 2 recorded as low risk for the adverse outcome respectively. After surgery, patients were followed up until discharge or death. In-hospital mortality and prolonged hospital stay were the primary and secondary adverse outcomes, respectively. Sensitivity, specificity, PPV, NPV and accuracy at 95% confidence interval were calculated for each of the scores using STATA v.13.

RESULTS

A total of 153 patients were enrolled. Of these, 151(M: F, 2.4:1) completed follow up and were analysed, 2 were excluded. Mortality rate was 11.9%. Fourty (26.5%) patients had a prolonged hospital stay. QSOFA predicted in-hospital mortality with AUROC of 0.52 versus 0.62, for SIRS. Similarly, qSOFA predicted prolonged hospital stay with AUROC of 0.54 versus 0.57, for SIRS.

CONCLUSION

SIRS is superior to qSOFA in predicting both mortality and prolonged hospital stay among patients with secondary peritonitis. However, overall, both scores showed a poor discrimination for both adverse outcomes and therefore not ideal tools.