Accuracy of Quick Sequential Organ Failure Assessment Score to Predict Sepsis Mortality in 121 Studies Including 1,716,017 Individuals: A Systematic Review and Meta-Analysis

Review: sepsis guidelines and core measure bundles

Sepsis is a major cause of mortality worldwide and is the third-leading cause of death in the United States. Sepsis is resource-intensive and requires prompt recognition and treatment to reduce mortality. The impact of sepsis is not only on in-hospital survival but extends into post-discharge quality of life and risk of re-admission. As the understanding of sepsis physiology evolved, so have the recommended screening tools and treatment protocol which challenge prior standards of care. There have been noteworthy efforts by the Surviving Sepsis Campaign, the Third International Consensus Definitions for Sepsis and the Centers for Medicare and Medicaid Services to establish core measure bundles. This review highlights both the 2021 SSC International Guidelines and the 2015 CMS Severe Sepsis/Septic Shock Core Measure Bundle, or SEP-1. Notably, the SEP-1 bundle was implemented as a value-based purchasing program, linking care of sepsis patients to financial incentives. The objective is to explore the most current evidence-based data to inform clinical practice while utilizing the available guidelines as a roadmap.

Are Deep Odontogenic Infections Associated With an Increased Risk for Sepsis?

BACKGROUND

Quick Sequential Organ Failure Assessment (qSOFA) is recommended to identify sepsis. Odontogenic infection (OI) can progress to sepsis, causing systematic inflammatory complications or organ failure.

PURPOSE

The purpose of the study was to measure the association between OI location and risk for sepsis at admission.

STUDY DESIGN, SETTING, AND SAMPLE

This retrospective cohort study included subjects treated for OI at Baylor University Medical Center in Dallas, TX, from January 9, 2019 to July 30, 2022. Subjects > 18 years old who were treated under general anesthesia were included. OI limited to periapical, vestibular, buccal, and/or canine spaces were excluded from the sample.

PREDICTOR VARIABLE

The primary predictor variable was OI anatomic location (superficial or deep). Superficial OI infection includes submental, submandibular, sublingual, submasseteric, and/or superficial temporal spaces. Deep OI includes pterygomandibular, deep temporal, lateral pharyngeal, retropharyngeal, pretracheal, and/or prevertebral.

MAIN OUTCOME VARIABLES

The primary outcome variable was risk for sepsis measured using a qSOFA score (0 to 3). A higher score (>0) indicates the patient has a high risk for sepsis.

COVARIATES

Covariates were demographics, clinical, laboratory, and radiological findings, antibiotic route, postoperative endotracheal intubation, tracheostomy, intensive care unit, admission, and length of stay.

ANALYSES

Descriptive and bivariate analyses were performed. A χ2 test was used for categorical variables. The Mann-Whitney U test was used for continuous variables. Statistical significance was P < .05.

RESULTS

The sample was composed of 168 subjects with a mean age of 42.8 ± 21.5 and 69 (48.6%) subjects were male. There were 11 (6.5%) subjects with a qSOFA score > 0. The relative risk of a qSOFA > 0 for a deep OI is 5.4 times greater than for a superficial OI (136 (95.8) versus 21 (80.8%): RR (95% confidence interval): 5.4 (1.51 to 19.27), P = .004). After adjusting for age, sex, American Society of Anesthesiologists score, and involved anatomical spaces, there was a significant correlation between laterality and the number of involved anatomical spaces and qSOFA score (odd ratio = 9.13, 95% confidence interval: 2.48 to 33.55, adjusted P = <.001).

CONCLUSION AND RELEVANCE

The study findings suggest that the OI location is associated with the qSOFA score >0.

Early Diagnosis of Sepsis: The Role of Biomarkers and Rapid Microbiological Tests

Sepsis is a medical emergency resulting from a dysregulated response to an infection, causing preventable deaths and a high burden of morbidity. Protocolized and accurate interventions in sepsis are time-critical. Therefore, earlier recognition of cases allows for preventive interventions, early treatment, and improved outcomes. Clinical diagnosis of sepsis by clinical scores cannot be considered an early diagnosis, given that underlying molecular pathophysiological mechanisms have been activated in the preceding hour or days. There is a lack of a widely available tool enhancing preclinical diagnosis of sepsis. Sophisticated technologies for sepsis prediction have several limitations, including high costs. Novel technologies for fast molecular and microbiological diagnosis are focusing on bedside point-of-care combined testing to reach most settings where sepsis represents a challenge.

Heart/breathing rate ratio (HBR) as a predictor of mortality in critically ill patients

Objectives

The early prediction of death is a challenge for medical staff. We evaluated the ability of the heart/breathing rate ratio (HBR) to predict mortality.

Methods

This was a single-center retrospective observational study of adult patients who had fever with or without respiratory symptoms, who survived at least 2 h after visiting the hospital, and whose lactate levels and vital signs were tested. We evaluated the distribution of mortality at different HBR levels and compared HBR with lactate.

Results

A total of 18,872 fever clinic visits were screened, and 183 patients whose lactate levels were tested were recruited. Patients who had HBR values lower than 4·5 or higher than 5·5 had greater mortality than patients who had HBR values between 4·5 and 5·5 (21·3 % vs. 3·4 %, p = 0·003; 28·9 % vs. 3·4 %, p < 0·001, respectively). In patients whose HBR was <5, the AUROC for HBR for mortality was 0·762 (95 % CI: 0.643-0·880), and that for lactate was 0·701 (95 % CI: 0·564-0·837). In patients whose HBR was ≥5, the AUROC for HBR for mortality was 0·721 (95 % CI: 0·584-0·857), and that for lactate was 0·742 (95 % CI: 0·607-0·848).

Conclusions

HBR is helpful for stratifying mortality risk among critically ill patients in acute care clinics for infectious diseases.

A new hematological parameter model for the diagnosis and prognosis of sepsis in emergency department: A single-center retrospective study

INTRODUCTION

Sepsis, a syndrome of organ dysfunction caused by an unregulated host response to infection. This study aimed to develop a novel sepsis diagnostic model of hematological parameters and evaluate its effectiveness in the early identification and prognosis of sepsis in emergency departments.

METHODS

A retrospective study was conducted in Emergency Department. Cell population data parameters related to monocytes and neutrophils were obtained using the Mindary BC-6800 plus hematology analyzer. Receiver operating characteristic (ROC) curve analysis, logistic regression analysis was performed to assess the performance of the parameters and establish a diagnostic and prognostic model of sepsis, which was then verified with a validation cohort.

RESULTS

Mon_XW exhibited the best diagnostic performance (area under the ROC curve [AUC] = 0.848, 95% confidence interval [CI]: 0.810-0.885, p < 0.001), followed by Neu_Y and Neu_YW (AUC = 0.777 95% CI: 0.730-0.824, p < 0.001). Logistic regression analysis identified Mon_XW and Neu_Y as independent predictors, which were used to establish a diagnostic model named hematological parameter for sepsis (HPS). HPS demonstrated the best diagnostic performance with an AUC of 0.862 (95% CI: 0.826-0.898, p < 0.001), sensitivity of 70.0%, and specificity of 87.1%, compared to C-reactive protein (CRP) and procalcitonin (PCT). The validation cohort also found that the positive predictive value of HPS was 70.4% and the negative predictive value was 92.2%.

CONCLUSION

The developed HPS model showed promising diagnostic efficacy for sepsis in the emergency department, which outperformed CRP and PCT in terms of sensitivity and specificity. By enabling early identification and prognosis of sepsis, that contributes to reducing sepsis-related mortality.

Applying artificial neural network in predicting sepsis mortality in the emergency department based on clinical features and complete blood count parameters

A complete blood count (CBC) is routinely ordered for emergency department (ED) patients with infections. Certain parameters, such as the neutrophil-to-lymphocyte ratio (NLR), might have prognostic value. We aimed to evaluate the prognostic value of the presenting CBC parameters combined with clinical variables in predicting 30-day mortality in adult ED patients with infections using an artificial neural network (ANN). We conducted a retrospective study of ED patients with infections between 17 December 2021 and 16 February 2022. Clinical variables and CBC parameters were collected from patient records, with NLR, monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) calculated. We determined the discriminatory performance using the area under the receiver operating characteristic curve (AUROC) and performed a 70/30 random data split and supervised ANN machine learning. We analyzed 558 patients, of whom 144 (25.8%) had sepsis and 60 (10.8%) died at 30 days. The AUROCs of NLR, MLR, PLR, and their sum were 0.644 (95% CI 0.573-0.716), 0.555 (95% CI 0.482-0.628), 0.606 (95% CI 0.529-0.682), and 0.610 (95% CI 0.534-0.686), respectively. The ANN model based on twelve variables including clinical variables, hemoglobin, red cell distribution width, NLR, and PLR achieved an AUROC of 0.811 in the testing dataset.

Management of Sepsis and Septic Shock: What Have We Learned in the Last Two Decades?

Sepsis is a clinical syndrome encompassing physiologic and biological abnormalities caused by a dysregulated host response to infection. Sepsis progression into septic shock is associated with a dramatic increase in mortality, hence the importance of early identification and treatment. Over the last two decades, the definition of sepsis has evolved to improve early sepsis recognition and screening, standardize the terms used to describe sepsis and highlight its association with organ dysfunction and higher mortality. The early 2000s witnessed the birth of early goal-directed therapy (EGDT), which showed a dramatic reduction in mortality leading to its wide adoption, and the surviving sepsis campaign (SSC), which has been instrumental in developing and updating sepsis guidelines over the last 20 years. Outside of early fluid resuscitation and antibiotic therapy, sepsis management has transitioned to a less aggressive approach over the last few years, shying away from routine mixed venous oxygen saturation and central venous pressure monitoring and excessive fluids resuscitation, inotropes use, and red blood cell transfusions. Peripheral vasopressor use was deemed safe and is rising, and resuscitation with balanced crystalloids and a restrictive fluid strategy was explored. This review will address some of sepsis management's most important yet controversial components and summarize the available evidence from the last two decades.

[Preclinical early detection and diagnosis of sepsis - step by step]

Because of very unspecific sepsis symptoms, early recognition of the emergency sepsis is difficult. If the disease is recognized in time it is possible to initiate diagnosis and treatment quickly. Rapid treatment of sepsis leads to lower mortality and less severe long-term consequences. Early detection is therefore of central importance in the diagnostic and therapeutic process, also in the outpatient setting.

Society for Maternal-Fetal Medicine Consult Series #67: Maternal sepsis

Maternal sepsis is a significant cause of maternal morbidity and mortality, and is a potentially preventable cause of maternal death. This Consult aims to summarize what is known about sepsis and provide guidance for the management of sepsis during pregnancy and the postpartum period. Most studies cited are from the nonpregnant population, but where available, pregnancy data are included. The following are the Society for Maternal-Fetal Medicine recommendations: (1) we recommend that clinicians consider the diagnosis of sepsis in pregnant or postpartum patients with otherwise unexplained end-organ damage in the presence of a suspected or confirmed infectious process, regardless of the presence of fever (GRADE 1C); (2) we recommend that sepsis and septic shock in pregnancy be considered medical emergencies and that treatment and resuscitation begin immediately (Best Practice); (3) we recommend that hospitals and health systems use a performance improvement program for sepsis in pregnancy with sepsis screening tools and metrics (GRADE 1B); (4) we recommend that institutions develop their own procedures and protocols for the detection of maternal sepsis, avoiding the use of a single screening tool alone (GRADE 1B); (5) we recommend obtaining tests to evaluate for infectious and noninfectious causes of life-threatening organ dysfunction in pregnant and postpartum patients with possible sepsis (Best Practice); (6) we recommend that an evaluation for infectious causes in pregnant or postpartum patients in whom sepsis is suspected or identified includes appropriate microbiologic cultures, including blood, before starting antimicrobial therapy, as long as there are no substantial delays in timely administration of antibiotics (Best Practice); (7) we recommend obtaining a serum lactate level in pregnant or postpartum patients in whom sepsis is suspected or identified (GRADE 1B); (8) in pregnant or postpartum patients with septic shock or a high likelihood of sepsis, we recommend administration of empiric broad-spectrum antimicrobial therapy, ideally within 1 hour of recognition (GRADE 1C); (9) after a diagnosis of sepsis in pregnancy is made, we recommend rapid identification or exclusion of an anatomic source of infection and emergency source control when indicated (Best Practice); (10) we recommend early intravenous administration (within the first 3 hours) of 1 to 2 L of balanced crystalloid solutions in sepsis complicated by hypotension or suspected organ hypoperfusion (GRADE 1C); (11) we recommend the use of a balanced crystalloid solution as a first-line fluid for resuscitation in pregnant and postpartum patients with sepsis or septic shock (GRADE 1B); (12) we recommend against the use of starches or gelatin for resuscitation in pregnant and postpartum patients with sepsis or septic shock (GRADE 1A); (13) we recommend ongoing, detailed evaluation of the patient's response to fluid resuscitation guided by dynamic measures of preload (GRADE 1B); (14) we recommend the use of norepinephrine as the first-line vasopressor during pregnancy and the postpartum period with septic shock (GRADE 1C); (15) we suggest using intravenous corticosteroids in pregnant or postpartum patients with septic shock who continue to require vasopressor therapy (GRADE 2B); (16) because of an increased risk of venous thromboembolism in sepsis and septic shock, we recommend the use of pharmacologic venous thromboembolism prophylaxis in pregnant and postpartum patients in septic shock (GRADE 1B); (17) we suggest initiating insulin therapy at a glucose level >180 mg/dL in critically ill pregnant patients with sepsis (GRADE 2C); (18) if a uterine source for sepsis is suspected or confirmed, we recommend prompt delivery or evacuation of uterine contents to achieve source control, regardless of gestational age (GRADE 1C); and (19) because of an increased risk of physical, cognitive, and emotional problems in survivors of sepsis and septic shock, we recommend ongoing comprehensive support for pregnant and postpartum sepsis survivors and their families (Best Practice).

The prognostic utility of prehospital qSOFA in addition to emergency department qSOFA for sepsis in patients with suspected infection: A retrospective cohort study

BACKGROUND

The quick sequential organ failure assessment (qSOFA) was widely used to estimate the risks of sepsis in patients with suspected infection in the prehospital and emergency department (ED) settings. Due to the insufficient sensitivity of qSOFA on arrival at the ED (ED qSOFA), the Surviving Sepsis Campaign 2021 recommended against using qSOFA as a single screening tool for sepsis. However, it remains unclear whether the combined use of prehospital and ED qSOFA improves its sensitivity for identifying patients at a higher risk of sepsis at the ED.

METHODS

We retrospectively analyzed the data from the ED of a tertiary medical center in Japan from April 2018 through March 2021. Among all adult patients (aged ≥18 years) transported by ambulance to the ED with suspected infection, we identified patients who were subsequently diagnosed with sepsis based on the Sepsis-3 criteria. We compared the predictive abilities of prehospital qSOFA, ED qSOFA, and the sum of prehospital and ED qSOFA (combined qSOFA) for sepsis in patients with suspected infection at the ED.

RESULTS

Among 2,407 patients with suspected infection transported to the ED by ambulance, 369 (15%) patients were subsequently diagnosed with sepsis, and 217 (9%) died during hospitalization. The sensitivity of prehospital qSOFA ≥2 and ED qSOFA ≥2 were comparable (c-statistics for sepsis [95%CI], 0.57 [0.52-0.62] vs. 0.55 [0.50-0.60]). However, combined qSOFA (cutoff, ≥3 [max 6]) was more sensitive than ED qSOFA (cutoff, ≥2) for identifying sepsis (0.67 [95%CI, 0.62-0.72] vs. 0.55 [95%CI, 0.50-0.60]). Using combined qSOFA, we identified 44 (12%) out of 369 patients who were subsequently diagnosed with sepsis, which would have been missed using ED qSOFA alone.

CONCLUSIONS

Using both prehospital and ED qSOFA could improve the screening ability of sepsis among patients with suspected infection at the ED.

Screening auf Sepsis in der Notfallmedizin – qSOFA ist uns nicht genug

Hintergrund

Die Sepsis ist eine häufige und lebensbedrohliche Komplikation einer akuten Infektion. In der Notfallmedizin hat sich zum Screening auf Sepsis der Quick Sequential-Organ-Failure-Assessment(qSOFA)-Score etabliert. Bereits mit der Einführung des Scores wurde dessen schwache Sensitivität kritisiert. Nun fordern aktuelle Leitlinien, den qSOFA-Score nicht mehr zum Screening auf Sepsis einzusetzen. Als eine Alternative wird der National Early Warning Score 2 (NEWS2) vorgeschlagen.

Ziel der Arbeit

In einer Subanalyse einer Kohorte von notfallmedizinischen Patient*innen soll die diagnostische Aussagekraft des qSOFA-Scores und des NEWS2 zur Erkennung einer Sepsis verglichen werden. Zusätzlich soll gezeigt werden, inwieweit mithilfe von abweichenden Vitalparametern bereits eine Risikoerhöhung für eine Sepsis ableitbar ist.

Methodik

Mittels AUROC (Area Under Receiver Operating Characteristics) und Odds Ratios wurden die Scores bzw. die Vitalparameter auf ihre Fähigkeit untersucht, septische Patient*innen zu erkennen.

Ergebnisse

Von 312 eingeschlossenen Patient*innen wurde bei 17,9 % eine Sepsis diagnostiziert. Der qSOFA-Score erkannte eine Sepsis mit einer AUROC von 0,77 (NEWS2 0,81). Für qSOFA fand sich eine Sensitivität von 57 % (Spezifität 83 %), für NEWS2 96 % (Spezifität 45 %). Die Analyse der einzelnen Vitalparameter zeigte, dass unter Patient*innen mit einer akuten Infektion eine Vigilanzminderung als deutliches Warnsignal für eine Sepsis zu werten ist.

Diskussion

In der Notfallmedizin sollte qSOFA nicht als alleiniges Tool für das Screening auf Sepsis verwendet werden. Bei Verdacht auf eine akute Infektion sollten grundsätzlich sämtliche Vitalparameter erfasst werden, um das Vorliegen einer akuten Organschädigung und somit einen septischen Krankheitsverlauf frühzeitig zu erkennen.

Graphic abstract

Performance of qSOFA Score as a Screening Tool for Sepsis in the Emergency Department

Introduction

Sepsis is the leading cause of mortality, and various scoring systems have been developed for its early identification and treatment. The objective was to test the ability of quick sequential organ failure assessment (qSOFA) score to identify sepsis and predict sepsis-related mortality in the emergency department (ED).

Methods

We conducted a prospective study from July 2018 to April 2020. Consecutive patients with age ≥18 years who presented to the ED with a clinical suspicion of infection were included. Sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV), and odds ratio (OR) for sepsis related mortality on day 7 and 28 were measured.

Results

A total of 1200 patients were recruited; of which 48 patients were excluded and 17 patients were lost to follow-up. 54 (45.4%) of 119 patients with positive qSOFA (qSOFA >2) died at 7 days and 76 (63.9%) died at 28 days. A total of 103 (10.1%) of 1016 patients with negative qSOFA (qSOFA score <2) died at 7 days and 207 (20.4%) died at 28 days. Patients with positive qSOFA score were at higher odds of dying at 7 days (OR: 3.9, 95% confidence interval [CI]: 3.1-5.2, P < 0.001) and 28 days (OR: 6.9, 95% CI: 4.6-10.3, P < 0.001). The PPV and NPV with positive qSOFA score to predict 7- and 28-day mortality were 45.4%, 89.9% and 63.9%, 79.6%, respectively.

Conclusion

The qSOFA score can be used as a risk stratification tool in a resource-limited setting to identify infected patients at an increased risk of death.

Patients with Bacterial Sepsis Are Heterogeneous with Regard to Their Systemic Lipidomic Profiles

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. In the present study, we investigated the systemic/serum lipidomic profile at the time of hospital admission for patients with bacterial sepsis. The study included 60 patients; 35 patients fulfilled the most recent 2016 Sepsis-3 criteria (referred to as Sepsis-3) whereas the remaining 25 patients had sepsis only according to the previous Sepsis-2 definition and could be classified as having Systemic Inflammatory Response Syndrome (SIRS). A total of 966 lipid metabolites were identified. Patients fulfilling the Sepsis-3 criteria differed from the Sepsis-2 patients with regard to only 15 lipid metabolites, and especially sphingolipids metabolism differed between these patient subsets. A total of only 43 metabolites differed between patients with and without bacteremia, including 12 lysophosphatidylcholines and 18 triacylglycerols (15 C18/C20 fatty acid metabolites decreased and three C14 myristate acid metabolites that were increased in bacteremia). Unsupervised hierarchical clustering analyses based on the identified sphingolipids, phosphatidylcholine and triacylglycerols showed that (i) the majority of Sepsis-3 patients differed from SIRS patients especially with regard to lysophosphatidylcholine levels; (ii) the minority of Sepsis-3 patients that clustered together with the majority of SIRS patients showed lower Sequential Organ Failure Assessment (SOFA) scores than the other Sepsis-3 patients; and (iii) the variation between the patients in the identified/altered sphingolipid and triacylglycerol metabolites further increased the heterogeneity of Sepsis-3 patients with regard to their systemic lipidomic profile at the time of diagnosis. To conclude, patients fulfilling the Sepsis-3 criteria differ with regard to their metabolic profile, and this variation depends on disease severity.

The prognostic value of sepsis scores and dichotomized triage score in patients presenting to the emergency department with fever: A prospective, observational study

BACKGROUND

The performance of the Quick Sequential Organ Failure Assessment (qSOFA) score needs to be explored further in the emergency triage room. This study aims to explore the performance of triage (tqSOFA) versus the dichotomized triage score (DTS) in patients admitted to the emergency room triage with fever.

METHODS

This research was designed as a prospective, observational study within a six-month period, including patients who presented to the emergency room triage with infrared fever ≥ 37.5 °C.

RESULTS

771 patients were analyzed.The highest sensitivity for predicting overall hospitalization and intensive care admission was seen for DTS (95.4 %, 100 %; p < 0.0001, p < 0.0001, respectively) (AUC:0.697, 95 % CI 0.663 to 0.730; AUC:0.684, 95 % CI 0.650 to 0.717, respectively). The highest sensitivity for predicting 1st week and 1st month mortality was found for DTS (100 %, 96.3 %; p < 0.0001, p < 0.0001, respectively). However, the highest specificity for predicting 1st week and 1st month mortality was observed in tqSOFA (94.1 %, 95.16; p = 0.0845, p < 0.0001, respectively) (AUC:0.658, 95 % CI 0.623 to 0.691; AUC:0.698, 95 % CI 0.664 to 0.730, respectively).

CONCLUSION

We found DTS to be as effective as tqSOFA and SIRS in determining all hospitalization times and mortality.

Is Prehospital Assessment of qSOFA Parameters Associated with Earlier Targeted Sepsis Therapy? A Retrospective Cohort Study

BACKGROUND

This study aimed to determine whether prehospital qSOFA (quick sequential organ failure assessment) assessment was associated with a shortened 'time to antibiotics' and 'time to intravenous fluid resuscitation' compared with standard assessment.

METHODS

This retrospective study included patients who were referred to our Emergency Department between 2014 and 2018 by emergency medical services, in whom sepsis was diagnosed during hospitalization. Two multivariable regression models were fitted, with and without qSOFA parameters, for 'time to antibiotics' (primary endpoint) and 'time to intravenous fluid resuscitation'.

RESULTS

In total, 702 patients were included. Multiple linear regression analysis showed that antibiotics and intravenous fluids were initiated earlier if infections were suspected and emergency medical services involved emergency physicians. A heart rate above 90/min was associated with a shortened time to antibiotics. If qSOFA parameters were added to the models, a respiratory rate ≥ 22/min and altered mentation were independent predictors for earlier antibiotics. A systolic blood pressure ≤ 100 mmHg and altered mentation were independent predictors for earlier fluids. When qSOFA parameters were added, the explained variability of the model increased by 24% and 38%, respectively (adjusted R² 0.106 versus 0.131 for antibiotics and 0.117 versus 0.162 for fluids).

CONCLUSION

Prehospital assessment of qSOFA parameters was associated with a shortened time to a targeted sepsis therapy.

Association of platelet count with all-cause mortality from acute respiratory distress syndrome: A cohort study

Background

The purpose of this study was to investigate whether platelet count was associated with mortality in acute respiratory distress syndrome (ARDS) patients.

Methods

We analyzed patients with ARDS from Multi‐parameter Intelligent Monitoring in Intensive Care Database III (MIMIC‐III). Platelet count was measured at the time of intensive care unit (ICU) admission. The cox proportional hazard model and subgroup analysis were used to determine the relationship between the platelet count and mortality of ARDS, as well as the consistency of its association. The primary outcome of this study was 365‐day mortality from the date of ICU admission.

Result

This study enrolled a total of 395 critically ill patients with ARDS. After adjustment for age, gender and ethnicity, the multivariate cox regression model showed that the hazard ratios (HRs) (95% confidence intervals [CIs]) of platelet count <192 × 10⁹/L and >296 × 10⁹/L were 2.08 (1.43, 3.04) and 1.35 (0.91, 2.01), respectively, compared with the reference (192–296 ×10⁹/L). After adjusting for confounding factors, lower platelet count (<192 × 10⁹/L) was associated with increased mortality (adjusted HR, 1.71; 95% CI 1.06–2.76, p = 0.0284). However, there was no similar trend in the 30‐day (adjusted HR,1.02; 95% CI 0.54–1.94) or 90‐day (adjusted HR, 1.65; 95% CI 0.94–2.89) mortality. In the subgroup analysis, lower platelet count showed significant interactions with specific populations (p interaction = 0.0413), especially in patients with atrial fibrillation.

Conclusion

Taken together, our analysis showed that platelet count is an independent predictor of mortality in critically ill patients with ARDS.

Prognostic nutrition index is associated with the all‐cause mortality in sepsis patients: A retrospective cohort study

Background

The study aimed at evaluating the prognostic utility of the prognostic nutritional index (PNI) for patients with sepsis.

Methods

Data in the present study were obtained from the Multiparameter Intelligent Monitoring in Intensive Care Database III. The calculation for PNI was as follows: serum albumin concentration (g/L) +0.005 × total lymphocyte count. 30‐day mortality was considered as the primary outcome, while 90‐day mortality and one‐year mortality were the secondary outcomes. Cox proportional risk models and propensity score matching (PSM) analyses were used to analyze the association between PNI and clinical outcomes in patients with sepsis. To assess the predictive value of PNI for 30‐day mortality, receiver operator characteristic (ROC) curve analysis was performed.

Results

A total of 2669 patients were in the study. After the confounding factors were adjusted, PNI ≥ 29.3 was identified as an independent predictive prognostic factor for the 30‐day all‐cause mortality (hazard ratio [HR]: 0.65; 95% confidence interval [CI]: 0.56–0.76; p < 0.00001). Moreover, PSM analysis further validated the prognostic predictive value of PNI for patients with sepsis. The AUC of the PNI was 0.6436 (95% CI: 0.6204–0.6625) which was significantly high than the AUC of NLR (0.5962, 95% CI: 0.5717–0.6206) (p = 0.0031), the RDW (0.5878, 95% CI: 0.5629–0.6127) (p < 0.0001), and PLR (0.4979, 95% CI: 0.4722–0.5235) (p < 0.0001).

Conclusion

The findings suggested that PNI was also a significant risk factor for sepsis.

A comparison of scoring systems for predicting mortality and sepsis in the emergency department patients with a suspected infection

OBJECTIVE

We aimed to compare the modified National Early Warning Score (mNEWS), quick Sequential Organ Failure Assessment (qSOFA) score, modified Systemic Inflammatory Response Syndrome (mSIRS) score, and modified Search Out Severity (mSOS) score in predicting mortality and sepsis among patients suspected of first observed infections in the emergency department. The modified scores were created by removing variables for simplicity.

METHODS

This was a prospective cohort study that enrolled adult patients presenting at the emergency department with signs and symptoms suggesting infection. The mNEWS, qSOFA score, mSIRS score, and mSOS score were calculated using triage data. The SOFA score was a reference standard for sepsis diagnosis. All patients were monitored for up to 30 days after the initial visit to measure each scoring system's ability to predict 30-day mortality and sepsis.

RESULTS

There were 260 patients included in the study. The 30-day mortality prediction with mNEWS ≥5 had the highest sensitivity (91.18%). The highest area under the receiver operating characteristic curve (AUC) for the 30-day mortality prediction was mNEWS (0.607), followed by qSOFA (0.605), mSOS (0.550), and mSIRS (0.423). The sepsis prediction with mNEWS ≥5 had the highest sensitivity (96.48%). The highest AUC for the sepsis prediction was also mNEWS (0.685), followed by qSOFA (0.605), mSOS (0.480), and mSIRS (0.477).

CONCLUSION

mNEWS was an acceptable scoring system screening tool for predicting mortality and sepsis in patients with a suspected infection.

Early Elevation of Thioredoxin-1 Serum Levels Predicts 28-Day Mortality in Patients with Sepsis

Background

Sepsis is the leading cause of death in critically ill patients, and the prevention of which requires precise outcome prediction and early intervention. We evaluated the prognostic prediction value of serum thioredoxin-1 (Trx-1) as an anti-inflammatory factor in patients with sepsis.

Methods

As a prospective study, patients with sepsis admitted to the intensive care unit (ICU) of our hospital during 2020 were recruited. Medical history collection, sequential organ failure assessment (ΔSOFA), and laboratory tests were performed within 24 h of admission. Serum levels of Trx-1 and other inflammatory biomarkers were detected with samples dynamically collected before, during, and after septic shock. Patients were categorized as survivors and non-survivors according to survival status on day 28. Correlation between Trx-1 and other sepsis-associated parameters as well as the correlation of Trx-1 and other sepsis-associated parameters with 28-day mortality were evaluated. Prognostic factors were identified by Cox regression analyses.

Results

A total of 187 patients were recruited. Serum Trx-1 level was positively correlated with inflammatory factors (interleukin-6, C-reactive protein, procalcitonin) and index of sepsis severity (ΔSOFA score, partial pressure of oxygen/fraction of inspired oxygen), all of which were significantly higher in non-survivors than survivors. While Trx-1 level at different timepoints and its evolution over time significantly differed between survivors and non-survivors, the initial Trx-1 level outperformed the other parameters in predicting 28-day survival. With 38.27 ng/mL as the cutoff value, serum Trx-1 predicted 28-day survival with optimal sensitivity and specificity.

Conclusion

Early increases in serum levels of Trx-1 can predict 28-day mortality in sepsis patients in the ICU.

Evaluation of an augmented emergency department electronic medical record-based sepsis alert

OBJECTIVE

Electronic medical records-based alerts have shown mixed results in identifying ED sepsis. Augmenting clinical patient-flagging with automated alert systems may improve sepsis screening. We evaluate the performance of a hybrid alert to identify patients in ED with sepsis or in-hospital secondary outcomes from infection.

METHODS

We extracted a dataset of all patients with sepsis during the study period at five participating Western Sydney EDs. We evaluated the hybrid alert's performance for identifying patients with a discharge diagnosis related to infection and modified sequential sepsis-related organ functional assessment (mSOFA) score ≥2 in ED and also compared the alert to rapid bedside screening tools to identify patients with infection for secondary outcomes of all-cause in-hospital death and/or intensive care unit admission.

RESULTS

A total of 118 178 adult patients presented to participating EDs during study period with 1546 patients meeting ED sepsis criteria. The hybrid alert had a sensitivity - 71.2% (95% confidence interval 68.8-73.4), specificity - 96.4% (95% confidence interval 96.3-96.5) for identifying ED sepsis. Clinician flagging identified additional alert-negative 232 ED sepsis and 63 patients with secondary outcomes and 112 alert-positive patients with infection and ED mSOFA score <2 went on to die in hospital.

CONCLUSION

The hybrid alert performed modestly in identifying ED sepsis and secondary outcomes from infection. Not all infected patients with a secondary outcome were identified by the alert or mSOFA score ≥2 threshold. Augmenting clinical practice with auto-alerts rather than pure automation should be considered as a potential for sepsis alerting until more reliable algorithms are available for safe use in clinical practice.

A statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit

BACKGROUND

Trauma patients admitted to critical care are at high risk of mortality because of their injuries. Our aim was to develop a machine learning-based model to predict mortality using Fahad-Liaqat-Ahmad Intensive Machine (FLAIM) framework. We hypothesized machine learning could be applied to critically ill patients and would outperform currently used mortality scores.

METHODS

The current Deep-FLAIM model evaluates the statistically significant risk factors and then supply these risk factors to deep neural network to predict mortality in trauma patients admitted to the intensive care unit (ICU). We analyzed adult patients (≥18 years) admitted to the trauma ICU in the publicly available database Medical Information Mart for Intensive Care III version 1.4. The first phase selection of risk factor was done using Cox-regression univariate and multivariate analyses. In the second phase, we applied deep neural network and other traditional machine learning models like Linear Discriminant Analysis, Gaussian Naïve Bayes, Decision Tree Model, and k-nearest neighbor models.

RESULTS

We identified a total of 3,041 trauma patients admitted to the trauma surgery ICU. We observed that several clinical and laboratory-based variables were statistically significant for both univariate and multivariate analyses while others were not. With most significant being serum anion gap (hazard ratio [HR], 2.46; 95% confidence interval [CI], 1.94-3.11), sodium (HR, 2.11; 95% CI, 1.61-2.77), and chloride (HR, 2.11; 95% CI, 1.69-2.64) abnormalities on laboratories, while clinical variables included the diagnosis of sepsis (HR, 2.03; 95% CI, 1.23-3.37), Quick Sequential Organ Failure Assessment score (HR, 1.52; 95% CI, 1.32-3.76). And Systemic Inflammatory Response Syndrome criteria (HR. 1.41; 95% CI, 1.24-1.26). After we used these clinically significant variables and applied various machine learning models to the data, we found out that our proposed DNN outperformed all the other methods with test set accuracy of 92.25%, sensitivity of 79.13%, and specificity of 94.16%; positive predictive value, 66.42%; negative predictive value, 96.87%; and area under the curve of the receiver-operator curve of 0.91 (1.45-1.29).

CONCLUSION

Our novel Deep-FLAIM model outperformed all other machine learning models. The model is easy to implement, user friendly and with high accuracy.

LEVEL OF EVIDENCE

Prognostic study, level II.

The SIRS criteria have better performance for predicting infection than qSOFA scores in the emergency department

Systemic inflammatory response syndrome (SIRS) reportedly has a low performance for distinguishing infection from non-infection. We explored the distribution of the patients diagnosed by SIRS (SIRS patients) or a quick sequential organ failure assessment (qSOFA) (qSOFA patients) and confirmed the performance of the both for predicting ultimate infection after hospital admission. We retrospectively analyzed the data from a multicenter prospective study. When emergency physicians suspected infection, SIRS or the qSOFA were applied. The area under the receiver operating characteristic curves (AUC) was used to assess the performance of the SIRS and qSOFA for predicting established infection. A total of 1,045 patients were eligible for this study. The SIRS patients accounted for 91.6% of qSOFA patients and they showed a higher rate of final infection than that of non-SIRS patients irrespective of the qSOFA diagnosis. The AUCs for predicting infection with SIRS and a qSOFA were 0.647 and 0.582, respectively. The SIRS significantly predicted an ultimate infection (AUC, 0.675; p = 0.018) in patients who met the SIRS and qSOFA simultaneously. In conclusion, the SIRS patients included almost all qSOFA patients. SIRS showed a better performance for predicting infection for qSOFA in those who met both definitions.