Purpose: Our study investigates how healthcare professionals in the Intensive Care Unit make decisions under highly ambiguous conditions, where the patient’s presentation triggers initial protocolized treatment but subsequently fails to respond to medical treatment. We hypothesize that providers with a low tolerance for ambiguity and specific risk-taking preferences are likely to rapidly engage in adequate evidence-based strategies when dealing with high-risk illnesses such as sepsis. Patients and Methods: This is a single-center cohort mixed method study of healthcare providers (attendings, fellows, residents, and advanced care providers) (n=138) using clinical vignettes (Vignette#1 representing the case of sepsis, Vignette#2 representing an ambiguous case). Participants were recruited using an internal Email distribution list (response rate 13.63%). Providers were asked to choose any number of specific therapies while being assessed for tolerance of ambiguity, denial mechanism, anxiety, prevalence of risk-taking behavior, optimism, and decision-making style. Results: Providers sparsely used antibiotics in vignette #2, while fluids were rarely given in vignette #1 during the first 48 hours. By day three, providers had implemented mechanical ventilation and renal replacement therapies. Bicarbonate and corticosteroids were used significantly as collateral therapies. Study participants were not very tolerant of ambiguity, used defensive mechanisms, and more often used rational decision-making rather than intuitive decision-making. Healthcare experience correlated negatively with the stress of uncertainty, defensiveness, and rational thinking. Optimism correlated positively with years of healthcare experience. The percentage of intensive care unit responsibilities correlated with risk-taking behaviors and defensiveness. There was no difference between implementers of the bundle and never implementers in their demographic, professional, and psychological characteristics. A similar lack of correlation was seen between different levels of tolerance of ambiguity among providers. Conclusion: Providers’ experience working in the intensive care unit, combined with their level of optimism, seemed to influence the relatively low implementation of the sepsis bundle across two vignettes.

Purpose: Characterization of immune system heterogeneity in COVID‐19 patients by comparing the inflammatory markers heparin‐binding protein (HBP), serum amyloid A protein (SAA), IL‐6, and C‐reactive protein (CRP) in relation to viral burden, immune response, and tissue damage. Also, determine if prolonged elevations in these markers are associated with long‐term symptoms of COVID‐19. Methods: This study enrolled 106 hospitalized patients with PCR‐confirmed diagnoses of COVID‐19. Blood samples were collected within 24 h of admission ( t _24h ), at 48 h ( t _48h ), 7 days ( t _7d ), and long‐term, greater than 1 month, post discharge ( t _LongTerm ). Serum levels of HBP, SAA, IL‐6, and CRP were measured using a commercial point‐of‐care device. Viral burden was assessed via serum viral spike S‐protein serum levels and specific immunoglobulins G, M, and D against S&N proteins, and SARS‐CoV‐2 proteins were quantified. Tissue injury was evaluated by measuring HMGB‐1 levels. Clinical data were reviewed retrospectively. Healthy individual samples served as controls. Results: COVID‐19 patients exhibited significantly elevated serum HBP and SAA compared to healthy controls. SAA levels normalized over 1 month, whereas HBP, CRP, and IL‐6 remained persistently elevated. Patients requiring intensive care unit (ICU) admission, endotracheal intubation, or extracorporeal membrane oxygen (ECMO) demonstrated higher CRP, IL‐6, and HBP at initial assessment. However, after 48 h, only IL‐6 was elevated in patients who subsequently expired. No significant correlations emerged between serum HBP levels and HMGB‐1, viral spike protein levels, or antibodies against SARS‐CoV‐2 proteins. Pre‐existing or acquired comorbidities did not significantly influence HBP or SAA concentrations. An analysis of biomarker profiles identified four distinct patient clusters, each characterized by unique inflammatory patterns that remained stable over time. Specifically, Cluster 1 exhibited low IL‐6 with high SAA and CRP. Cluster 2 had low HBP with the highest IL‐6. Cluster 3 demonstrated low SAA and CRP levels, and Cluster 4 exhibited robust inflammatory responses across all markers except IL‐6. Conclusions: The persistence of inflammatory markers suggests ongoing inflammatory responses post‐COVID‐19 infection. Significant heterogeneity observed in inflammatory responses upon admission indicates multiple distinct inflammatory phenotypes, which may have implications for clinical outcomes and management strategies.

The immune system’s response to an invading pathogen is the critical determinant in recovery from illness. Here, we hypothesize that the immune response will swiftly follow classical activation and a resolution trajectory in patients with the rapid evolution of symptoms if challenged by a viral pathogen for the first time. Alternatively, a dysregulated response will be signified by a protracted clinical trajectory. Consequently, we enrolled 106 patients during the first wave of COVID-19 and collected their blood within 24 h, 48 h, 7 days, and over 28 days from symptoms onset. The pathogenic burden was measured via serum levels of the S-spike protein and specific immunoglobulin titers against the S and N proteins of SARS-CoV-2. The nonspecific immunological response was gauged using interleukin 6, leukocytosis, and C-reactive protein. Coagulation status was assessed. Several serum biomarkers were used as surrogates of clinical outcomes. We identified four clusters depending on the onset of symptoms (immediate [A], 6 days [B], 12 days [C], and over 21 days [D]). High variability in the S-spike protein in cluster A was present. The corresponding immunoglobulin titer was random. Only procalcitonin differentiated clusters in terms of markers of nonspecific inflammation. Coagulation markers were not significantly different between clusters. Serum surrogates on cardiomyopathy and neuronal pathology exhibited significant variability. Implementation of ECMO or noninvasive ventilation was more prominent in cluster C and D. Interestingly, SOFA or APACHE II scores were not different between nominal (A and B) versus dysregulated clusters (C and D).

Background/Objectives: Treating critically ill patients is complex and often subjective. This study investigates adherence to clinical guidelines for sepsis among different providers. Considering the strengths of the recommendations, we hypothesize that heterogeneity in the decision-making process will be low and independent of provider background and psychological makeup. Methods: This cohort study used two clinical vignettes of sepsis. Providers were given standardized treatment plans for 7 days, and their responses were recorded. Demographical, professional, and psychological (ambiguity tolerance, defensiveness, anxiety due to uncertainty, risk-taking behavior, decision styles, and optimism) variables were acquired. Results: Crystalloids were commonly used in both vignettes. Pressor engagement, especially norepinephrine, increased significantly after the third day. Providers recommended antibiotics and no provider stopped antibiotic therapy. Cluster analysis revealed no differences in therapy implementation among provider types, but some differences existed between the two vignettes. Cluster #1 was characterized by the implementation of early light bundle therapy combined with the use of pressors and a notable enhancement in therapies by the fifth day (Early Cluster). Cluster #2 (Minimalists) involved consistent engagement only in light bundle therapy throughout the treatment period. Cluster #3 (Escalation) comprised providers who rapidly escalated treatment using multiple different modalities. Cluster #3 stood out as most providers were female, non-MD, with significant ICU duties, and enhanced rational thinking. Conclusions: Providers differ in implementation styles of the sepsis treatment standard based on types of therapies selected not studied psychological variables.

Variability in novel inflammatory markers (HBP and SAA) post-surgery could indicate ongoing perioperative inflammation. This pilot cohort study collected blood from 99 patients undergoing elective cardiac surgery at baseline, 24 hours, 7 days, and 3 months post-surgery. Inflammatory markers (HBP, SAA, PCT, CRP, IL-6) were measured with a point-of-care device. Demographic and clinical data were extracted from health records. Serum SAA increased significantly in the acute postoperative phase (M _e [IQR];SAA _baseline =81.1[87] vs SAA _24hr= 232.65[88.02];U[72]=2343,p<0.0001), remained elevated at 7 days (Me _7d =252.6[88.56];U[57]=1484,p<0.0001) and were still more pronounced than baseline at t _3m (Me _3m =118.44[101.52];U[38]=448,p=0.0008). HBP showed a significant rise at seven days (HBP _baseline =45[26;89] vs HBP _7d =121[69.75;224.5]; U[56]=805,p<0.0001) then returned to near baseline by t _3m (Me _3m =32.5[15.75;98.5]). Traditional inflammatory markers PCT, CRP, and IL-6 demonstrated a rapid increase at t _24h and plateaued at t _7d . None of the biomarkers showed variability at baseline or postoperatively with preoperative status or postoperative complications. Cluster analysis of the inflammatory markers at 24 hours (t _24h ) identified distinct subgroups. Cluster #1-patients with a modest increase in all markers; Cluster#2 characterized with a robust increase in IL-6; Cluster #3 showed increase in CRP and decline in HBP; Cluster #4 showed a modest increase in IL-6 and decline in HBP; Cluster #5 represented a decline in both CRP and SAA. Patients in these clusters differ with respect to age, pre-existing peripheral artery disease, and borderline differences in perioperative acetaminophen use. SAA and HBP remain elevated longer than IL-6, CRP, and PCT after surgery, suggesting that inflammation may persist beyond 3 months.

The insulin-like growth factor binding protein, acid-labile subunit (IGFALS), plays a crucial role in glucose metabolism and immune regulation, key processes in recovery from surgery. Here, we studied the perioperative serum IGFALS dynamics and explored potential clinical implications. A total of 79 patients undergoing elective cardiac surgery with implementation of cardiopulmonary bypass had their serum isolated at baseline, 24 h, seven days, and three months postoperatively to assess serum concentrations of IGFALS and insulin growth factor 1 (IGF-1). Markers of perioperative injury included troponin I (TnI), high-mobility group box 1 (HMGB-1), and heat shock protein 60 (Hsp-60). Inflammatory status was assessed via interleukin-6 (IL-6) and interleukin-8 (IL-8). Additionally, we measured in vitro cytokine production to viral stimulation of whole blood and monocytes. Surrogates of neuronal distress included neurofilament light chain (NF-L), total tau (τ), phosphorylated tau at threonine 181 (τp181), and amyloid β40 and β42. Renal impairment was defined by RIFLE criteria. Cardiac dysfunction was denoted by serum N-terminal pro-brain natriuretic peptide (NT-proBNP) levels. Serum IGFALS levels declined significantly after surgery and remained depressed even at 3 months. Administration of acetaminophen and acetylsalicylic acid differentiated IGFALS levels at the 24 h postoperatively. Serum IGFALS 24 h post-operatively correlated with production of cytokines by leukocytes after in vitro viral stimulation. Serum amyloid-β1-42 was significantly associated with IGFALS at baseline and 24 h post-surgery Patients discharged home had higher IGFALS levels at 28 days and 3 months than those discharged to healthcare facilities or who died. These findings suggest that IGFALS may serve as a prognostic biomarker for recovery trajectory and postoperative outcomes in cardiac surgery patients.