Red-flag sepsis and SOFA identifies different patient population at risk of sepsis-related deaths on the general ward

Survival prediction for heart failure complicated by sepsis: based on machine learning methods

Background

Heart failure is a cardiovascular disorder, while sepsis is a common non-cardiac cause of mortality. Patients with combined heart failure and sepsis have a significantly higher mortality rate and poor prognosis, making early identification of high-risk patients and appropriate allocation of medical resources critically important.

Methods

We constructed a survival prediction model for patients with heart failure and sepsis using the eICU-CRD database and externally validated it using the MIMIC-IV database. Our primary outcome is the 28-day all-cause mortality rate. The Boruta method is used for initial feature selection, followed by feature ranking using the XGBoost algorithm. Four machine learning models were compared, including Logistic Regression (LR), eXtreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), and Gaussian Naive Bayes (GNB). Model performance was assessed using metrics such as area under the curve (AUC), accuracy, sensitivity, and specificity, and the SHAP method was utilized to visualize feature importance and interpret model results. Additionally, we conducted external validation using the MIMIC-IV database.

Results

We developed a survival prediction model for heart failure complicated by sepsis using data from 3891 patients in the eICU-CRD and validated it externally with 2928 patients from the MIMIC-IV database. The LR model outperformed all other machine learning algorithms with a validation set AUC of 0.746 (XGBoost: 0.726, AdaBoost: 0.744, GNB: 0.722), alongside accuracy (0.685), sensitivity (0.666), and specificity (0.712). The final model incorporates 10 features: age, ventilation, norepinephrine, white blood cell count, total bilirubin, temperature, phenylephrine, respiratory rate, neutrophil count, and systolic blood pressure. We employed the SHAP method to enhance the interpretability of the model based on the LR algorithm. Additionally, external validation was conducted using the MIMIC-IV database, with an external validation AUC of 0.699.

Conclusion

Based on the LR algorithm, a model was constructed to effectively predict the 28-day all-cause mortality rate in patients with heart failure complicated by sepsis. Utilizing our model predictions, clinicians can promptly identify high-risk patients and receive guidance for clinical practice.

Predictive value of white blood cell to hemoglobin ratio for 30-day mortality in patients with severe intracerebral hemorrhage

Aim

To explore the predictive value of white blood cell to hemoglobin ratio (WHR) for 30-day mortality in patients with intracerebral hemorrhage (ICH).

Methods

In this cohort study, 2,848 patients with ICH were identified in the Medical Information Mart for Intensive Care (MIMIC)-III and MIMIC-IV. Least absolute shrinkage and selection operator (LASSO) regression screened covariates of 30-day mortality of ICH patients. COX regression analysis was used to study the association of different levels of WHR, white blood cell (WBC), and hemoglobin (Hb) with 30-day mortality. The median follow-up time was 30 (20.28, 30.00) days.

Results

In total, 2,068 participants survived at the end of the follow-up. WHR was negatively correlated with the Glasgow Coma Score (GCS) (spearman correlation coefficient = -0.143, p < 0.001), and positively associated with the Sepsis-related Organ Failure Assessment (SOFA) score (spearman correlation coefficient = 0.156, p < 0.001), quick SOFA (qSOFA) score (spearman correlation coefficient = 0.156, p < 0.001), and Simplified Acute Physiology Score II (SAPS-II) (spearman correlation coefficient = 0.213, p < 0.001). After adjusting for confounders, WHR >0.833 (HR = 1.64, 95%CI: 1.39-1.92) and WBC >10.9 K/uL (HR = 1.49, 95%CI: 1.28-1.73) were associated with increased risk of 30-day mortality of patients with ICH. The area under the curve (AUC) value of the prediction model based on WHR and other predictors was 0.78 (95%CI: 0.77-0.79), which was higher than SAPSII (AUC = 0.75, 95%CI: 0.74-0.76), SOFA score (AUC = 0.69, 95%CI: 0.68-0.70) and GCS (AUC = 0.59, 95%CI: 0.57-0.60).

Conclusion

The level of WHR was associated with 30-day mortality in patients with severe ICH, and the WHR-based prediction model might provide a tool to quickly predict 30-day mortality in patients with ICH.

SIRS, SOFA, qSOFA, and NEWS in the diagnosis of sepsis and prediction of adverse outcomes: a systematic review and meta-analysis

BACKGROUND

We compared Systemic Inflammatory Response Syndrome (SIRS), Sequential Organ Failure Assessment (SOFA), Quick Sepsis-related Organ Failure Assessment (qSOFA), and National Early Warning Score (NEWS) for sepsis diagnosis and adverse outcomes prediction.

METHODS

Clinical studies that used SIRS, SOFA, qSOFA, and NEWS for sepsis diagnosis and prognosis assessment were included. Data were extracted, and meta-analysis was performed for outcome measures, including sepsis diagnosis, in-hospital mortality, 7/10/14-day mortality, 28/30-day mortality, and ICU admission.

RESULTS

Fifty-seven included studies showed good overall quality. Regarding sepsis prediction, SIRS demonstrated high sensitivity (0.85) but low specificity (0.41), qSOFA showed low sensitivity (0.42) but high specificity (0.98), and NEWS exhibited high sensitivity (0.71) and specificity (0.85). For predicting in-hospital mortality, SOFA demonstrated the highest sensitivity (0.89) and specificity (0.69). In terms of predicting 7/10/14-day mortality, SIRS exhibited high sensitivity (0.87), while qSOFA had high specificity (0.75). For predicting 28/30-day mortality, SOFA showed high sensitivity (0.97) but low specificity (0.14), whereas qSOFA displayed low sensitivity (0.41) but high specificity (0.88).

CONCLUSIONS

NEWS independently demonstrates good diagnostic capability for sepsis, especially in high-income countries. SOFA emerges as the optimal choice for predicting in-hospital mortality and can be employed as a screening tool for 28/30-day mortality in low-income countries.

The Value of Neutrophil/Lymphocyte Ratio Combined with Red Blood Cell Distribution Width in Evaluating the Prognosis of Emergency Patients with Sepsis

Sepsis is a dysfunction of various organs caused by a dysfunctional host response induced by infection. In recent years, the mortality rate of sepsis patients, especially the mortality rate of septic shock patients still remains high. Due to the complexity and heterogeneity of sepsis, there is currently a lack of clinical biomarkers that can be widely used for the early assessment of sepsis. In order to find more concise and accurate biomarkers for timely and adequate intervention in sepsis, we explored the value of neutrophil/lymphocyte ratio (NLR) combined with red blood cell distribution width (RDW) in assessing the prognosis of emergency sepsis patients. The results showed that NLR and RDW were closely related to the prognosis of emergency sepsis patients. The combination of the two can evaluate the prognosis of patients with emergency sepsis, which deserves close attention from clinicians.

NEWS2 and improving outcomes from sepsis

The cause of deterioration is often unclear, so it is vitally important that we spot the sick and deteriorating patient from all causes. As a result, warning scores must cater for all conditions, and - where possible - be standardised across all healthcare settings. This article summarises the importance of an 'unblinkered' approach to acute illness assessment, comparing and examining the evidence for different historical scoring systems and looking at the early impact of national alignment to NEWS2 in patients admitted to hospital with suspected bacterial infections.

Association between Mortality and Sequential Organ Failure Assessment Score during a Short Stay in the Intensive Care Unit after Non-Cardiac Surgery

Background: The sequential organ failure assessment (SOFA) score has been validated in various clinical situations. However, it has not been investigated during a short stay in the intensive care unit (ICU). This study aimed to evaluate the association between the SOFA score and outcomes in patients who were monitored for less than one day after non-cardiac surgery. Methods: From a total of 203,787 consecutive adult patients who underwent non-cardiac surgery between January 2011 and June 2019, we selected 17,714 who were transferred to the ICU immediately after surgery and stayed for less than 24 h. Patients were divided according to quartile value and change between the initial and follow-up levels of SOFA score. Results: Three-year mortality tended to increase with a higher initial SOFA score (11.7%, 11.8%, 15.1%, and 17.8%, respectively). The patients were divided according to changes in the SOFA score at the midnight postoperative follow-up check: 16,176 (91.3%) in the stable group and 1538 (8.7%) in the worsened group. The worsened group showed significantly higher three-year mortality and complications (13.2% vs. 18.6%; HR [hazard ratio]: 1.236; 95% CI [confidence interval]: 1.108−1.402; p ≤ 0.0021 for three-year mortality and 3.8% vs. 9.1%; HR: 2.13; 95% CI: 1.73−2.60; p < 0.001 for acute kidney injury). Conclusions: The SOFA score during a short stay in the ICU after non-cardiac surgery showed an association with mortality. The change in SOFA score may need to be considered at discharge from the ICU.

Septic patients without obvious signs of infection at baseline are more likely to die in the ICU

Objective

Early identification of sepsis is mandatory. However, clinical presentation is sometimes misleading given the lack of infection signs. The objective of the study was to evaluate the impact on the 28-day mortality of the so-called “vague” presentation of sepsis.

Design

Single centre retrospective observational study.

Setting

One teaching hospital Intensive Care Unit.

Subjects

All the patients who presented at the Emergency Department (ED) and were thereafter admitted to the Intensive Care Unit (ICU) with a final diagnosis of sepsis were included in this retrospective observational three-year study. They were classified as having exhibited either “vague” or explicit presentation at the ED according to previously suggested criteria. Baseline characteristics, infection main features and sepsis management were compared. The impact of a vague presentation on 28-day mortality was then evaluated.

Interventions

None.

Measurements and main results

Among the 348 included patients, 103 (29.6%) had a vague sepsis presentation. Underlying chronic diseases were more likely in those patients [e.g., peripheral arterial occlusive disease: adjusted odd ratio (aOR) = 2.01, (1.08–3.77) 95% confidence interval (CI); p = 0.028], but organ failure was less likely at the ED [SOFA score value: 4.7 (3.2) vs. 5.2 (3.1), p = 0.09]. In contrast, 28-day mortality was higher in the vague presentation group (40.8% vs. 26.9%, p = 0.011), along with longer time-to-diagnosis [18 (31) vs. 4 (11) h, p < 0.001], time-to-antibiotics [20 (32) vs. 7 (12) h, p < 0.001] and time to ICU admission [71 (159) vs. 24 (69) h, p < 0.001]. Whatever, such a vague presentation independently predicted 28-day mortality [aOR = 2.14 (1.24–3.68) 95% CI; p = 0.006].

Conclusions

Almost one third of septic patient requiring ICU had a vague presentation at the ED. Despite an apparent lower level of severity when initially assessed, those patients had an increased risk of mortality that could not be fully explained by delayed diagnosis and management of sepsis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07210-y.

Prediction of prognosis in elderly patients with sepsis based on machine learning (random survival forest)

Background

Elderly patients with sepsis have many comorbidities, and the clinical reaction is not obvious. Thus, clinical treatment is difficult. We planned to use the laboratory test results and comorbidities of elderly patients with sepsis from a large-scale public database Medical Information Mart for Intensive Care (MIMIC) IV to build a random survival forest (RSF) model and to evaluate the model’s predictive value for these patients.

Methods

Clinical information of elderly patients with sepsis in MIMIC IV database was collected retrospectively. Machine learning (RSF) was used to select the top 30 variables in the training cohort to build the final RSF model. The model was compared with the traditional scoring systems SOFA, SAPSII, and APSIII. The performance of the model was evaluated by C index and calibration curve.

Results

A total of 6,503 patients were enrolled in the study. The top 30 important variables screened by RSF were used to construct the final RSF model. The new model provided a better C-index (0.731 in the validation cohort). The calibration curve described the agreement between the predicted probability of RSF model and the observed 30-day survival.

Conclusions

We constructed a prognostic model to predict a 30-day mortality risk in elderly patients with sepsis based on machine learning (RSF algorithm), and it proved superior to the traditional scoring systems. The risk factors affecting the patients were also ranked. In addition to the common risk factors of vasopressors, ventilator use, and urine output. Newly added factors such as RDW, type of ICU unit, malignant cancer, and metastatic solid tumor also significantly influence prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12873-022-00582-z.

Improving sepsis recognition through use of the Sepsis Trust's community screening tool

Sepsis is associated with high levels of morbidity and mortality. All healthcare professionals have a responsibility to ensure they have sufficient knowledge to effectively screen patients for signs and symptoms of sepsis. In the community setting, screening for sepsis can be challenging, due to the complexity within the patient population and difficulties associated with observation for changes in the patient's condition. The Sepsis Trust community nursing sepsis screening tool provides decision-making support to community healthcare professionals, enabling them to make a rapid assessment for risk factors for sepsis, ensuring a proportionate, consistent and appropriate response. Through implementation of a decision-support tool within the clinical setting, it is likely that patients at risk of sepsis will be identified earlier, and patients will be escalated in a more consistent manner. This process of improving consistency in practice can improve patient outcomes, including mortality, morbidity and overall patient experience.

The Use of Different Sepsis Risk Stratification Tools on the Wards and in Emergency Departments Uncovers Different Mortality Risks: Results of the Three Welsh National Multicenter Point-Prevalence Studies

Supplemental Digital Content is available in the text.

To compare the performance of Sequential Organ Failure Assessment, systemic inflammatory response syndrome, Red Flag Sepsis, and National Institute of Clinical Excellence sepsis risk stratification tools in the identification of patients at greatest risk of mortality from sepsis in nonintensive care environments.

Comparison of qSOFA and Hospital Early Warning Scores for prognosis in suspected sepsis in emergency department patients: a systematic review

BACKGROUND

Sepsis is a major cause of morbidity and mortality and many tools exist to facilitate early recognition. This review compares two tools: the quick Sequential Organ Failure Assessment (qSOFA) and Early Warning Scores (National/Modified Early Warning Scores (NEWS/MEWS)) for predicting intensive care unit (ICU) admission and mortality when applied in the emergency department.

METHODS

A literature search was conducted using Medline, CINAHL, Embase and Cochrane Library, handsearching of references and a grey literature search with no language or date restrictions. Two authors selected studies and quality assessment completed using QUADAS-2. Area under the receiver operating characteristic curve (AUROC), sensitivities and specificities were compared.

RESULTS

13 studies were included, totalling 403 865 patients. All reported mortality and six reported ICU admission.The ranges for AUROC estimates varied from little better than chance to good prediction of mortality (NEWS: 0.59-0.88; qSOFA: 0.57-0.79; MEWS 0.56-0.75), however, individual papers generally reported higher AUROC values for NEWS than qSOFA. NEWS values demonstrated a tendency towards better sensitivity for ICU admission (NEWS ≥5, 46%-91%; qSOFA ≥2, 12%-53%) and mortality (NEWS ≥5, 51%-97%; qSOFA ≥2, 14%-71%) but lower specificity (ICU: NEWS ≥5, 25%-91%; qSOFA ≥2, 67%-99%; mortality: NEWS ≥5, 22%-91%; qSOFA ≥2, 58%-99%).

CONCLUSION

The wide range of AUROC estimates and high heterogeneity limit our conclusions. Allowing for this, the NEWS AUROC was consistently higher than qSOFA within individual papers. Both scores allow threshold setting, determined by the preferred compromise between sensitivity and specificity. At established thresholds NEWS tended to higher sensitivity while qSOFA tended to a higher specificity.

PROSPERO REGISTRATION NUMBER

CRD42019131414.

Four consecutive yearly point-prevalence studies in Wales indicate lack of improvement in sepsis care on the wards

The ‘Sepsis Six’ bundle was promoted as a deliverable tool outside of the critical care settings, but there is very little data available on the progress and change of sepsis care outside the critical care environment in the UK. Our aim was to compare the yearly prevalence, outcome and the Sepsis Six bundle compliance in patients at risk of mortality from sepsis in non-intensive care environments. Patients with a National Early Warning Score (NEWS) of 3 or above and suspected or proven infection were enrolled into four yearly 24-h point prevalence studies, carried out in fourteen hospitals across Wales from 2016 to 2019. We followed up patients to 30 days between 2016–2019 and to 90 days between 2017 and 2019. Out of the 26,947 patients screened 1651 fulfilled inclusion criteria and were recruited. The full ‘Sepsis Six’ care bundle was completed on 223 (14.0%) occasions, with no significant difference between the years. On 190 (11.5%) occasions none of the bundle elements were completed. There was no significant correlation between bundle element compliance, NEWS or year of study. One hundred and seventy (10.7%) patients were seen by critical care outreach; the ‘Sepsis Six’ bundle was completed significantly more often in this group (54/170, 32.0%) than for patients who were not reviewed by critical care outreach (168/1385, 11.6%; p < 0.0001). Overall survival to 30 days was 81.7% (1349/1651), with a mean survival time of 26.5 days (95% CI 26.1–26.9) with no difference between each year of study. 90-day survival for years 2017–2019 was 74.7% (949/1271), with no difference between the years. In multivariate regression we identified older age, heart failure, recent chemotherapy, higher frailty score and do not attempt cardiopulmonary resuscitation orders as significantly associated with increased 30-day mortality. Our data suggests that despite efforts to increase sepsis awareness within the NHS, there is poor compliance with the sepsis care bundles and no change in the high mortality over the study period. Further research is needed to determine which time-sensitive ward-based interventions can reduce mortality in patients with sepsis and how can these results be embedded to routine clinical practice.

Trial registration Defining Sepsis on the Wards ISRCTN 86502304 https://doi.org/10.1186/ISRCTN86502304 prospectively registered 09/05/2016.

Diagnostic Accuracy and Prognostic Value of Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios in Septic Patients outside the Intensive Care Unit

Background and Objectives: The aim of this study was to evaluate the diagnostic accuracy and prognostic value of neutrophil-to-lymphocyte (NLR) and platelet-to-lymphocyte (PLR) ratios and to compare them with other biomarkers and clinical scores of sepsis outside the intensive care unit. Materials and methods: In this retrospective study, 251 patients with sepsis and 126 patients with infection other than sepsis were enrolled. NLR and PLR were calculated as the ratio between absolute values of neutrophils, lymphocytes, and platelets by complete blood counts performed on whole blood by Sysmex XE-9000 (Dasit, Italy) following the manufacturer’s instruction. Results: The best NLR value in diagnosis of sepsis was 7.97 with sensibility, specificity, AUC, PPV, and NPV of 64.26%, 80.16%, 0.74 (p < 0.001), 86.49%, and 53.18%, respectively. The diagnostic role of NLR significantly increases when PLR, C-reactive protein (PCR), procalcitonin (PCT), and mid-regional pro-adrenomedullin (MR-proADM) values, as well as systemic inflammatory re-sponse syndrome (SIRS), sequential organ failure assessment (SOFA), and quick-sequential organ failure assessment (qSOFA) scores, were added to the model. The best value of NLR in predicting 90-day mortality was 9.05 with sensibility, specificity, AUC, PPV, and NPV of 69.57%, 61.44%, 0.66 (p < 0.0001), 28.9%, and 89.9%, respectively. Sensibility, specificity, AUC, PPV, and NPV of NLR increase if PLR, PCR, PCT, MR-proADM, SIRS, qSOFA, and SOFA scores are added to NLR. Conclusions: NLR and PLR represent a widely useful and cheap tool in diagnosis and in predict-ing 90-day mortality in patients with sepsis.

SOFA score is superior to APACHE-II score in predicting the prognosis of critically ill patients with acute kidney injury undergoing continuous renal replacement therapy

Background

Acute kidney injury (AKI) is the most common cause of organ failure in multiple organ dysfunction syndrome (MODS) and is associated with increased mortality. This study aimed at determining the efficacy of sequential organ failure assessment (SOFA), and acute physiology and chronic health evaluation II (APACHE-II) scoring systems in assessing the prognosis of critically ill patients with AKI undergoing continuous renal replacement therapy (CRRT). At present, APACHE-II score and SOFA score were also used to evaluate and predict the prognosis of critically ill patients with AKI.

Methods

The predictive value of SOFA and APACHE-II scores for 28- and 90-d mortality in patients with AKI undergoing CRRT were determined by multivariate analysis, sensitivity analysis, and curve-fitting analysis.

Results

A total of 836 cases were included in this study. Multivariate Cox logistic regression analysis showed that SOFA scores were associated with 28- and 90-d mortality in patients with AKI undergoing CRRT. The adjusted HR of SOFA for 28-d mortality were 1.18 (1.14, 1.21), 1.24 (1.18, 1.31), and 1.19 (1.13, 1.24) in the three models, respectively, and the adjusted HR of SOFA for 90-d mortality was 1.12 (1.09, 1.16), 1.15 (1.10, 1.19), and 1.15 (1.10, 1.19), respectively. The subgroup analysis showed that the SOFA score was associated with 28-d and 90-d mortality in patients with AKI undergoing CRRT. APACHE-II score was not associated with 28- and 90-d mortality patients with AKI undergoing CRRT. Curve fitting analysis showed that SOFA scores increased had a higher prediction accuracy for 28- and 90-d than APACHE-II.

Conclusions

The SOFA score showed a higher accuracy of mortality prediction in critically ill patients with AKI undergoing CRRT than the APACHE-II score.

Skin and sepsis: contribution of dermatology to a rapid diagnosis

In patients who develop sepsis, whether due to primary, secondary or metastatic lesions, the skin is frequently affected. However, there are unresolved aspects regarding the general clinical manifestations in the skin or the prognosis and/or therapeutic implications. The main challenge in the approach to sepsis is its early diagnosis and management. In this review, we address the sepsis-skin relationship and the potential impact of early dermatological intervention on the septic patient through ten basic questions. We found little evidence of the participation of the dermatologist in sepsis alert programs. There are early skin changes that may alert clinicians on a possible sepsis, such as skin mottling or variations in acral skin temperature. In addition, the skin is an accessible and highly cost-effective tissue for etiological studies of some forms of sepsis (e.g., meningococcal purpura) and its involvement defines the prognosis of certain patients (e.g., infective endocarditis).

The Clinical Need for New Diagnostics in the Identification and Management of Patients with Suspected Sepsis in UK NHS Hospitals: A Survey of Healthcare Professionals

Development of a new diagnostic is ideally driven by an understanding of the clinical need that the test addresses and the optimal role the test will have within a care pathway. This survey aimed to understand the clinical need for new sepsis diagnostics and to identify specific clinical scenarios that could be improved by testing. An electronic, cross-sectional survey was circulated to UK National Health Service (NHS) doctors and nurses who care for patients with suspected sepsis in hospitals. Two hundred and sixty-five participants completed the survey, representing 64 NHS Trusts in England. Sixty-seven percent of respondents suggested that the major cause of delay was during the initial identification of sepsis and the subsequent recognition of patients who were deteriorating. Existing blood tests did not enhance the confidence of consultants making their diagnoses. Those surveyed identified a role for a near-patient test to "rule out" suspected sepsis and, thereby, stop or postpone use of antibiotics. Current diagnostic tests are slow, non-specific, and do not reliably identify patients with a high suspicion of sepsis. As a result, they have a limited use in patient management and antibiotic stewardship. Future development of sepsis diagnostics should focus on overcoming these limitations.

Best diagnostic accuracy of sepsis combining SIRS criteria or qSOFA score with Procalcitonin and Mid-Regional pro-Adrenomedullin outside ICU

Early diagnosis and treatment significantly reduce sepsis mortality. Currently, no gold standard has been yet established to diagnose sepsis outside the ICU. The aim of the study was to evaluate the diagnostic accuracy of sepsis defined by SIRS Criteria of 1991, Second Consensus Conference Criteria of 2001, modified Second Consensus Conference Criteria of 2001 (obtaining SIRS Criteria and SOFA score), Third Consensus Conference of 2016, in addition to the dosage of Procalcitonin (PCT) and MR-pro-Adrenomedullin (MR-proADM). In this prospective study, 209 consecutive patients with clinical diagnosis of sepsis were enrolled (May 2014-June 2018) outside intensive care unit (ICU) setting. A diagnostic protocol could include SIRS criteria or qSOFA score evaluation, rapid testing of PCT and MR-proADM, and SOFA score calculation for organ failure definition. Using this approach outside the ICU, a rapid diagnostic and prognostic evaluation could be achieved, also in the case of negative SIRS, qSOFA or SOFA scores with high post-test probability to reduce mortality and improve outcomes.

Accuracy of a Modified qSOFA Score for Predicting Critical Care Admission in Febrile Children

BACKGROUND AND OBJECTIVES

The identification of life-threatening infection in febrile children presenting to the emergency department (ED) remains difficult. The quick Sequential Organ Failure Assessment (qSOFA) was only derived for adult populations, implying an urgent need for pediatric scores. We developed and validated a novel, adapted qSOFA score (Liverpool quick Sequential Organ Failure Assessment [LqSOFA]) and compared its performance with qSOFA, Pediatric Early Warning Score (PEWS), and National Institute for Health and Care Excellence (NICE) high-risk criteria in predicting critical care (CC) admission in febrile children presenting to the ED.

METHODS

The LqSOFA (range, 0-4) incorporates age-adjusted heart rate, respiratory rate, capillary refill, and consciousness level on the Alert, Voice, Pain, Unresponsive scale. The primary outcome was CC admission within 48 hours of ED presentation, and the secondary outcome was sepsis-related mortality. LqSOFA, qSOFA, PEWS, and NICE high-risk criteria scores were calculated, and performance characteristics, including area under the receiver operating characteristic curve, were calculated for each score.

RESULTS

In the initial (n = 1121) cohort, 47 CC admissions (4.2%) occurred, and in the validation (n = 12 241) cohort, 135 CC admissions (1.1%) occurred, and there were 5 sepsis-related deaths. In the validation cohort, LqSOFA predicted CC admission with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval [CI], 0.76 to 0.86), versus qSOFA (0.66; 95% CI, 0.60 to 0.71), PEWS (0.93; 95% CI, 0.90 to 0.95), and NICE high-risk criteria (0.81; 95% CI, 0.78 to 0.85). For predicting CC admission, the LqSOFA outperformed the qSOFA, with a net reclassification index of 10.4% (95% CI, 1.0% to 19.9%).

CONCLUSIONS

In this large study, we demonstrate improved performance of the LqSOFA over qSOFA in identifying febrile children at risk for CC admission and sepsis-related mortality. Further validation is required in other settings.

Real World Patterns of Antimicrobial Use and Microbiology Investigations in Patients with Sepsis outside the Critical Care Unit: Secondary Analysis of Three Nation-Wide Point Prevalence Studies

Recent description of the microbiology of sepsis on the wards or information on the real-life antibiotic choices used in sepsis is lacking. There is growing concern of the indiscriminate use of antibiotics and omission of microbiological investigations in the management of septic patients. We performed a secondary analysis of three annual 24-h point-prevalence studies on the general wards across all Welsh acute hospitals in years 2016–2018. Data were collected on patient demographics, as well as radiological, laboratory and microbiological data within 48-h of the study. We screened 19,453 patients over the three 24 h study periods and recruited 1252 patients who fulfilled the entry criteria. 775 (64.9%) patients were treated with intravenous antibiotics. Only in 33.65% (421/1252) of all recruited patients did healthcare providers obtain blood cultures; in 25.64% (321/1252) urine cultures; in 8.63% (108/1252) sputum cultures; in 6.79% (85/1252) wound cultures; in 15.25% (191/1252) other cultures. Out of the recruited patients, 59.1% (740/1252) fulfilled SEPSIS-3 criteria. Patients with SEPSIS-3 criteria were significantly more likely to receive antibiotics than the non-septic cohort (p < 0.0001). In a multivariable regression analysis increase in SOFA score, increased number of SIRS criteria and the use of the official sepsis screening tool were associated with antibiotic administration, however obtaining microbiology cultures was not. Our study shows that antibiotics prescription practice is not accompanied by microbiological investigations. A significant proportion of sepsis patients are still at risk of not receiving appropriate antibiotics treatment and microbiological investigations; this may be improved by a more thorough implementation of sepsis screening tools.

A Snapshot of Compliance with the Sepsis Six Care Bundle in Two Acute Hospitals in the West Midlands, UK

BACKGROUND

The sepsis six care bundle has been adopted by hospitals in England and Wales for the management of patients with sepsis, with the aim of increasing survival when all elements of the bundle are achieved.

AIM

To assess compliance with the Sepsis Six Care Bundle in two acute NHS hospitals in the West Midlands.

MATERIALS AND METHODS

Adults admitted to hospital over a 24-hour period were screened for sepsis. Sepsis was identified using the Systemic Inflammatory Response (SIRS) criteria and the quick sequential organ failure assessment (qSOFA) score. Adherence to the Sepsis Six Care Bundle was assessed.

RESULTS

249 patients were screened and 24 patients were identified as having sepsis (9.6%). One patient received all six elements of the bundle. Compliance was highest for giving intravenous fluids (58.3%) and antibiotics (58.3%), and lowest for measuring urine output (16.7%).

CONCLUSIONS

Further research is needed to establish the reasons for low compliance.

HOW TO CITE THIS ARTICLE

Frankling C, Patel J, Sharif B, Melody T, Yeung J, Gao F, et al. A Snapshot of Compliance with the Sepsis Six Care Bundle in Two Acute Hospitals in the West Midlands, UK. Indian J Crit Care Med 2019;23(7):310-315.

Application of The Sepsis-3 Consensus Criteria in a Geriatric Acute Care Unit: A Prospective Study

The prognostic value of quick Sepsis-related Organ Failure Assessment (qSOFA) score in geriatric patients is uncertain. We aimed to compare qSOFA vs. Systemic Inflammatory Response Syndrome (SIRS) criteria for mortality prediction in older multimorbid subjects, admitted for suspected sepsis in a geriatric ward. We prospectively enrolled 272 patients (aged 83.7 ± 7.4). At admission, qSOFA and SIRS scores were calculated. Mortality was assessed during hospital stay and three months after discharge. The predictive capacity of qSOFA and SIRS was assessed by calculating the Area Under the Receiver Operating Characteristic Curve (AUROC), through pairwise AUROC comparison, and multivariable logistic regression analysis. Both qSOFA and SIRS exhibited a poor prognostic performance (AUROCs 0.676, 95% CI 0.609⁻0.738, and 0.626, 95% CI 0.558⁻0.691 for in-hospital mortality; 0.684, 95% CI 0.614⁻0.748, and 0.596, 95% CI 0.558⁻0.691 for pooled three-month mortality, respectively). The predictive capacity of qSOFA showed no difference to that of SIRS for in-hospital mortality (difference between AUROCs 0.05, 95% CI -0.05 to 0.14, p = 0.31), but was superior for pooled three-month mortality (difference between AUROCs 0.09, 95% CI 0.01⁻0.17, p = 0.029). Multivariable logistic regression analysis, accounting for possible confounders, including frailty, showed that both scores were not associated with in-hospital mortality, although qSOFA, unlike SIRS, was associated with pooled three-month mortality. In conclusion, neither qSOFA nor SIRS at admission were strong predictors of mortality in a geriatric acute-care setting. Traditional geriatric measures of frailty may be more useful for predicting adverse outcomes in this setting.