Ground truth labels challenge the validity of sepsis consensus definitions in critical illness

Sepsis Prediction Models are Trained on Labels that Diverge from Clinician-Recommended Treatment Times

Many sepsis prediction models use the Sepsis-3 definition or its variants as a training label. However, among the few sepsis models ever deployed in practice, there is scant evidence that they offer clinically meaningful decision support at the bedside. As a potential mechanism to explain this limitation, we hypothesized that clinician-recommended treatment times for sepsis would diverge from onset time defined by Sepsis-3. We conducted an electronic survey that was completed by 153 clinicians at three large and geographically diverse medical centers using vignettes derived from eight real cases of sepsis. After reviewing these vignettes, participants suggested antibiotic treatment to start an average of 7.0 hours (95% confidence interval 5.3 to 8.8) before the Sepsis-3 definition onset. Thus, predicting Sepsis-3 onset as a treatment prompt could lead to inappropriate and delayed treatment recommendations. Building predictive decision support systems that identify outcomes aligned with bedside decisions would increase their clinical utility.

Machine Learning Tools for Acute Respiratory Distress Syndrome Detection and Prediction

Machine learning (ML) tools for acute respiratory distress syndrome (ARDS) detection and prediction are increasingly used. Therefore, understanding risks and benefits of such algorithms is relevant at the bedside. ARDS is a complex and severe lung condition that can be challenging to define precisely due to its multifactorial nature. It often arises as a response to various underlying medical conditions, such as pneumonia, sepsis, or trauma, leading to widespread inflammation in the lungs. ML has shown promising potential in supporting the recognition of ARDS in ICU patients. By analyzing a variety of clinical data, including vital signs, laboratory results, and imaging findings, ML models can identify patterns and risk factors associated with the development of ARDS. This detection and prediction could be crucial for timely interventions, diagnosis and treatment. In summary, leveraging ML for the early prediction and detection of ARDS in ICU patients holds great potential to enhance patient care, improve outcomes, and contribute to the evolving landscape of precision medicine in critical care settings. This article is a concise definitive review on artificial intelligence and ML tools for the prediction and detection of ARDS in critically ill patients.

Transcriptional pathways of terminal differentiation in high- and low-density blood granulocytes in sepsis

BACKGROUND

Trauma and infection induce emergency granulopoiesis. Counts of immature granulocytes and transcriptional pathways of terminal granulocytic differentiation in blood are elevated in sepsis but correlate with disease severity. This limits their performance as sepsis biomarkers in critically ill patients. We hypothesized that activation of these pathways in sepsis is attributable to immature low-density (LD) rather than mature high-density (HD) granulocytes.

METHODS

We included patients with sepsis and systemic inflammatory response syndrome (SIRS) of comparable disease severity, and additionally septic shock, on intensive or intermediate care unit admission. Blood granulocyte isolation by CD15 MicroBeads was followed by density-gradient centrifugation. Flow cytometry was used to determine counts of developmental stages (precursors) and their relative abundancies in total, HD, and LD granulocytes. Five degranulation markers were quantified in plasma by multiplex immunoassays. A set of 135 genes mapping granulocyte differentiation was assayed by QuantiGene™ Plex. CEACAM4, PLAC8, and CD63 were analyzed by qRT-PCR. Nonparametric statistical tests were applied.

RESULTS

Precursor counts appeared higher in sepsis than SIRS but did not correlate with disease severity for early immature and mature granulocytes. Precursor subpopulations were enriched at least ten-fold in LD over HD granulocytes without sepsis-SIRS differences. Degranulation markers in blood were comparable in sepsis and SIRS. Higher expression of early developmental genes in sepsis than SIRS was more pronounced in LD and less in HD than total granulocytes. Only the cell membrane protein encoding genes CXCR2 and CEACAM4 were more highly expressed in SIRS than sepsis. By qRT-PCR, the azurophilic granule genes CD63 and PLAC8 showed higher sepsis than SIRS levels in LD granulocytes and PLAC8 also in total granulocytes where its discriminatory performance resembled C-reactive protein (CRP).

CONCLUSIONS

Transcriptional programs of early terminal granulocytic differentiation distinguish sepsis from SIRS due to both higher counts of immature granulocytes and elevated expression of early developmental genes in sepsis. The sustained expression of PLAC8 in mature granulocytes likely accounts for its selection in the whole blood SeptiCyte™ LAB test. Total granulocyte PLAC8 rivals CRP as sepsis biomarker. However, infection-specific transcriptional pathways, that differentiate sepsis from sterile stress-induced granulocytosis more reliably than CRP, remain to be identified.

Pneumonia in the first week after polytrauma is associated with reduced blood levels of soluble herpes virus entry mediator

Background

Pneumonia develops frequently after major surgery and polytrauma and thus in the presence of systemic inflammatory response syndrome (SIRS) and organ dysfunction. Immune checkpoints balance self-tolerance and immune activation. Altered checkpoint blood levels were reported for sepsis. We analyzed associations of pneumonia incidence in the presence of SIRS during the first week of critical illness and trends in checkpoint blood levels.

Materials and methods

Patients were studied from day two to six after admission to a surgical intensive care unit (ICU). Blood was sampled and physician experts retrospectively adjudicated upon the presence of SIRS and Sepsis-1/2 every eight hours. We measured the daily levels of immune checkpoints and inflammatory markers by bead arrays for polytrauma patients developing pneumonia. Immune checkpoint time series were additionally determined for clinically highly similar polytrauma controls remaining infection-free during follow-up. We performed cluster analyses. Immune checkpoint time trends in cases and controls were compared with hierarchical linear models. For patients with surgical trauma and with and without sepsis, selected immune checkpoints were determined in study baseline samples.

Results

In polytrauma patients with post-injury pneumonia, eleven immune checkpoints dominated subcluster 3 that separated subclusters 1 and 2 of myeloid markers from subcluster 4 of endothelial activation, tissue inflammation, and adaptive immunity markers. Immune checkpoint blood levels were more stable in polytrauma cases than controls, where they trended towards an increase in subcluster A and a decrease in subcluster B. Herpes virus entry mediator (HVEM) levels (subcluster A) were lower in cases throughout. In unselected surgical patients, sepsis was not associated with altered HVEM levels at the study baseline.

Conclusion

Pneumonia development after polytrauma until ICU-day six was associated with decreased blood levels of HVEM. HVEM signaling may reduce pneumonia risk by strengthening myeloid antimicrobial defense and dampening lymphoid-mediated tissue damage. Future investigations into the role of HVEM in pneumonia and sepsis development and as a predictive biomarker should consider the etiology of critical illness and the site of infection.

S-Adenosylhomocysteine Is a Useful Metabolic Factor in the Early Prediction of Septic Disease Progression and Death in Critically Ill Patients: A Prospective Cohort Study

A common final pathway of pathogenetic mechanisms in septic organ dysfunction and death is a lack or non-utilization of oxygen. Plasma concentrations of lactate serve as surrogates for the oxygen-deficiency-induced imbalance between energy supply and demand. As S-adenosylhomocysteine (SAH) was shown to reflect tissue hypoxia, we compared the ability of SAH versus lactate to predict the progression of inflammatory and septic disease to septic organ dysfunction and death. Using univariate and multiple logistic regression, we found that SAH but not lactate, taken upon patients' inclusion in the study close to ICU admission, significantly and independently contributed to the prediction of disease progression and death. Due to the stronger increase in SAH in relation to S-adenosylmethionine (SAM), the ratio of SAM to SAH, representing methylation potential, was significantly decreased in patients with septic organ dysfunction and non-survivors compared with SIRS/sepsis patients (2.8 (IQR 2.3-3.9) vs. 8.8 (4.9-13.8); p = 0.003) or survivors (4.9 (2.8-9.5) vs. 8.9 (5.1-14.3); p = 0.026), respectively. Thus, SAH appears to be a better contributor to the prediction of septic organ dysfunction and death than lactate in critically ill patients. As SAH is a potent inhibitor of SAM-dependent methyltransferases involved in numerous vital biochemical processes, the impairment of the SAM-to-SAH ratio in severely critically ill septic patients and non-survivors warrants further studies on the pathogenetic role of SAH in septic multiple organ failure.

Bundled Care to Reduce Sepsis Mortality: The Improving Pediatric Sepsis Outcomes (IPSO) Collaborative

OBJECTIVES

We sought to improve utilization of a sepsis care bundle and decrease 3- and 30- day sepsis-attributable mortality, as well as determine which care elements of a sepsis bundle are associated with improved outcomes.

METHODS

Children's Hospital Association formed a QI collaborative to Improve Pediatric Sepsis Outcomes (IPSO) (January 2017-March 2020 analyzed here). IPSO Suspected Sepsis (ISS) patients were those without organ dysfunction where the provider "intended to treat" sepsis. IPSO Critical Sepsis (ICS) patients approximated those with septic shock. Process (bundle adherence), outcome (mortality), and balancing measures were quantified over time using statistical process control. An original bundle (recognition method, fluid bolus < 20 min, antibiotics < 60 min) was retrospectively compared with varying bundle time-points, including a modified evidence-based care bundle, (recognition method, fluid bolus < 60 min, antibiotics < 180 min). We compared outcomes using Pearson χ-square and Kruskal Wallis tests and adjusted analysis.

RESULTS

Reported are 24 518 ISS and 12 821 ICS cases from 40 children's hospitals (January 2017-March 2020). Modified bundle compliance demonstrated special cause variation (40.1% to 45.8% in ISS; 52.3% to 57.4% in ICS). The ISS cohort's 30-day, sepsis-attributable mortality dropped from 1.4% to 0.9%, a 35.7% relative reduction over time (P < .001). In the ICS cohort, compliance with the original bundle was not associated with a decrease in 30-day sepsis-attributable mortality, whereas compliance with the modified bundle decreased mortality from 4.75% to 2.4% (P < .01).

CONCLUSIONS

Timely treatment of pediatric sepsis is associated with reduced mortality. A time-liberalized care bundle was associated with greater mortality reductions.

Dissecting contributions of individual systemic inflammatory response syndrome criteria from a prospective algorithm to the prediction and diagnosis of sepsis in a polytrauma cohort

Background

Sepsis is the leading cause of death in intensive care units (ICUs), and its timely detection and treatment improve clinical outcome and survival. Systemic inflammatory response syndrome (SIRS) refers to the concurrent fulfillment of at least two out of the following four clinical criteria: tachycardia, tachypnea, abnormal body temperature, and abnormal leukocyte count. While SIRS was controversially abandoned from the current sepsis definition, a dynamic SIRS representation still has potential for sepsis prediction and diagnosis.

Objective

We retrospectively elucidate the individual contributions of the SIRS criteria in a polytrauma cohort from the post-surgical ICU of University Medical Center Mannheim (Germany).

Methods

We used a dynamic and prospective SIRS algorithm tailored to the ICU setting by accounting for catecholamine therapy and mechanical ventilation. Two clinically relevant tasks are considered: (i) sepsis prediction using the first 24 h after admission to our ICU, and (ii) sepsis diagnosis using the last 24 h before sepsis onset and a time point of comparable ICU treatment duration for controls, respectively. We determine the importance of individual SIRS criteria by systematically varying criteria weights when summarizing the SIRS algorithm output with SIRS descriptors and assessing the classification performance of the resulting logistic regression models using a specifically developed ranking score.

Results

Our models perform better for the diagnosis than the prediction task (maximum AUROC 0.816 vs. 0.693). Risk models containing only the SIRS level average mostly show reasonable performance across criteria weights, with prediction and diagnosis AUROCs ranging from 0.455 (weight on leukocyte criterion only) to 0.693 and 0.619 to 0.800, respectively. For sepsis prediction, temperature and tachypnea are the most important SIRS criteria, whereas the leukocytes criterion is least important and potentially even counterproductive. For sepsis diagnosis, all SIRS criteria are relevant, with the temperature criterion being most influential.

Conclusion

SIRS is relevant for sepsis prediction and diagnosis in polytrauma, and no criterion should a priori be omitted. Hence, the original expert-defined SIRS criteria are valid, capturing important sepsis risk determinants. Our prospective SIRS algorithm provides dynamic determination of SIRS criteria and descriptors, allowing their integration in sepsis risk models also in other settings.

Comparative Analyses of the Impact of Different Criteria for Sepsis Diagnosis on Outcome in Patients with Spontaneous Subarachnoid Hemorrhage

Data on sepsis in patients with a subarachnoid hemorrhage (SAH) are scarce. We assessed the impact of different sepsis criteria on the outcome in an SAH cohort. Adult patients admitted to our ICU with a spontaneous SAH between 11/2014 and 11/2018 were retrospectively included. In patients developing an infection, different criteria for sepsis diagnosis (Sepsis-1, Sepsis-3_original, Sepsis-3_modified accounting for SAH-specific therapy, alternative sepsis criteria compiled of consensus conferences) were applied and their impact on functional outcome using the modified Rankin Scale (mRS) on hospital discharge and in-hospital mortality was evaluated. Of 270 SAH patients, 129 (48%) developed an infection. Depending on the underlying criteria, the incidence of sepsis and septic shock ranged between 21–46% and 9–39%. In multivariate logistic regression, the Sepsis-1 criteria were not associated with the outcome. The Sepsis-3 criteria were not associated with the functional outcome, but in shock with mortality. Alternative sepsis criteria were associated with mortality for sepsis and in shock with mortality and the functional outcome. While Sepsis-1 criteria were irrelevant for the outcome in SAH patients, septic shock, according to the Sepsis-3 criteria, adversely impacted survival. This impact was higher for the modified Sepsis-3 criteria, accounting for SAH-specific treatment. Modified Sepsis-3 and alternative sepsis criteria diagnosed septic conditions of a higher relevance for outcomes in patients with an SAH.