Hypothermia, Poorly Recognized by clinicians, is associated with Higher Mortality Among Critically Ill Patients with infections: A Retrospective Observational Study

Surviving Sepsis Campaign Research Priorities 2023

OBJECTIVES

To identify research priorities in the management, epidemiology, outcome, and pathophysiology of sepsis and septic shock.

DESIGN

Shortly after publication of the most recent Surviving Sepsis Campaign Guidelines, the Surviving Sepsis Research Committee, a multiprofessional group of 16 international experts representing the European Society of Intensive Care Medicine and the Society of Critical Care Medicine, convened virtually and iteratively developed the article and recommendations, which represents an update from the 2018 Surviving Sepsis Campaign Research Priorities.

METHODS

Each task force member submitted five research questions on any sepsis-related subject. Committee members then independently ranked their top three priorities from the list generated. The highest rated clinical and basic science questions were developed into the current article.

RESULTS

A total of 81 questions were submitted. After merging similar questions, there were 34 clinical and ten basic science research questions submitted for voting. The five top clinical priorities were as follows: 1) what is the best strategy for screening and identification of patients with sepsis, and can predictive modeling assist in real-time recognition of sepsis? 2) what causes organ injury and dysfunction in sepsis, how should it be defined, and how can it be detected? 3) how should fluid resuscitation be individualized initially and beyond? 4) what is the best vasopressor approach for treating the different phases of septic shock? and 5) can a personalized/precision medicine approach identify optimal therapies to improve patient outcomes? The five top basic science priorities were as follows: 1) How can we improve animal models so that they more closely resemble sepsis in humans? 2) What outcome variables maximize correlations between human sepsis and animal models and are therefore most appropriate to use in both? 3) How does sepsis affect the brain, and how do sepsis-induced brain alterations contribute to organ dysfunction? How does sepsis affect interactions between neural, endocrine, and immune systems? 4) How does the microbiome affect sepsis pathobiology? 5) How do genetics and epigenetics influence the development of sepsis, the course of sepsis and the response to treatments for sepsis?

CONCLUSIONS

Knowledge advances in multiple clinical domains have been incorporated in progressive iterations of the Surviving Sepsis Campaign guidelines, allowing for evidence-based recommendations for short- and long-term management of sepsis. However, the strength of existing evidence is modest with significant knowledge gaps and mortality from sepsis remains high. The priorities identified represent a roadmap for research in sepsis and septic shock.

Unexplained hypothermia is associated with bacterial infection in the Emergency Department

BACKGROUND

Early recognition and antibiotic therapy improve the prognosis of bacterial infections. Triage temperature in the Emergency department (ED) constitutes a diagnostic and prognostic marker of infection. The objective of this study was to assess the prevalence of community-acquired bacterial infections and the diagnostic ability of conventional biological markers in patients presenting to the ED with hypothermia.

METHODS

We conducted a retrospective single-center study over a 1-year period before the COVID-19 pandemic. Consecutive adult patients admitted to the ED with hypothermia (body temperature < 36.0 °C) were eligible. Patients with evident cause of hypothermia and patients with viral infections were excluded. Diagnosis of infection was based on the presence of at least two among the three following pre-defined criteria: (i) the presence of a potential source of infection, (ii) microbiology data, and (iii) patient outcome under antibiotic therapy. The association between traditional biomarkers (white blood cells, lymphocytes, C-reactive protein [CRP], Neutrophil to Lymphocyte Count Ratio [NLCR]) and underlying bacterial infections was evaluated using a univariate and a multivariate (logistic regression) analysis. Receiver operating characteristic curves were built to determine threshold values yielding the best sensitivity and specificity for each biomarker.

RESULTS

Of 490 patients admitted to the ED with hypothermia during the study period, 281 were excluded for circumstantial or viral origin, and 209 were finally studied (108 men; mean age: 73 ± 17 years). A bacterial infection was diagnosed in 59 patients (28%) and was mostly related to Gram-negative microorganisms (68%). The area under the curve (AUC) for the CRP level was 0.82 with a confidence interval (CI) ranging from 0.75 to 0.89. The AUC for the leukocyte, neutrophil and lymphocyte counts were 0.54 (CI: 0.45-0.64), 0.58 (CI: 0.48-0.68) and 0.74 (CI: 0.66-0.82), respectively. The AUC of NLCR and quick Sequential Organ Failure Assessment (qSOFA) reached 0.70 (CI: 0.61-0.79) and 0.61 (CI: 0.52-0.70), respectively. In the multivariate analysis, CRP ≥ 50 mg/L (OR: 9.39; 95% CI: 3.91-24.14; p < 0.01) and a NLCR ≥10 (OR: 2.73; 95% CI: 1.20-6.12; p = 0.02) were identified as independent variables associated with the diagnosis of underlying bacterial infection.

CONCLUSION

Community-acquired bacterial infections represent one third of diagnoses in an unselected population presenting to the ED with unexplained hypothermia. CRP level and NLCR appear useful for the diagnosis of causative bacterial infection.

Failure mode and effect analysis (FMEA) to identify and mitigate failures in a hospital rapid response system (RRS)

We performed FMEA on the existing RRS with the help of routine users of the RRS who acted as subject matter experts and evaluated the failures for their criticality using the Risk Priority Number approach based on their experience of the RRS. The FMEA found 35 potential failure modes and 101 failure mode effects across 13 process steps of the RRS. The afferent limb of RRS was found to be more prone to these failures (62, 61.4%) than the efferent limb of the RRS (39, 38.6%). Modification of calling criteria (12, 11.9%) and calculation of New Zealand Early Warning Scores (NZEWS) calculation (11, 10.9%) steps were found to potentially give rise to the highest number of these failures. Causes of these failures include human error and related factors (35, 34.7%), staff workload/staffing levels (30, 29.7%) and limitations due to paper-based charts and organisational factors (n = 30, 29.7%). The demonstrated electronic system was found to potentially eliminate or reduce the likelihood of 71 (70.2%) failures. The failures not eliminated by the electronic RRS require targeted corrective measures including scenario-based training and education, and revised calling criteria to include triggers for hypothermia and high systolic blood pressure.