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Introduction Sepsis is a global health priority with nearly 50 million cases annually. Cardiovascular dysfunction is common, frequently manifesting as hypotension that persists despite fluid resuscitation. Most affected patients require the use of intravenous (IV) vasoactive agents, typically necessitating intensive care unit (ICU)-level monitoring, invasive interventions and contributing substantially to healthcare costs. Midodrine, an oral alpha-1 agonist approved for orthostatic hypotension, has increasingly been used off-label as a vasopressor-sparing (reducing IV vasopressor use) strategy in sepsis, despite limited and inconsistent evidence. This pragmatic, randomised, open-label trial evaluates the efficacy and safety of midodrine in patients with sepsis-associated hypotension. We hypothesise that, compared with standard care, midodrine administration will reduce the duration of IV vasopressor use. Methods and analysis A total of 308 adult patients with sepsis-associated hypotension will be enrolled (154 per arm). The intervention group will, in addition to standard of care, receive enteral midodrine 10 mg three times daily. Outcomes will be ascertained pragmatically via electronic health record-based data retrieval and adjudicated by research coordinators blinded to treatment assignment. The primary outcome is time alive and off IV vasopressors in the first 28 days (in hours) after randomisation. Secondary outcomes include cumulative vasopressor exposure; use and duration of central venous access; cumulative fluid balance over the first 48 hours and up to 7 days of ICU stay; ICU and hospital length of stay; and ICU-, hospital-, and organ support-free days through day 28. Safety outcomes include adverse events potentially attributable to midodrine during hospitalisation including acute kidney injury. Primary analyses will follow an intention-to-treat framework, including all randomised participants according to their assigned treatment groups. Primary and secondary outcomes will be compared using a van Elteren test stratified by randomisation factors. A predefined secondary Bayesian analysis of the primary outcome will provide complementary estimates of treatment effect. Safety outcomes will be summarised descriptively without formal between-arm hypothesis testing. Ethics and dissemination The Mayo Clinic Institutional Review Board approved this protocol and required written informed consent from all participants (IRB# 24–0 00 121). Findings will be disseminated through peer-reviewed publications and international conference presentations. Trial registration number NCT06319248 .

Introduction: Life-support limits (i.e., code status), the first step in the continuum of palliation and end-of-life (EoL) care, stem from decisions made by patients and their providers to align care near the EoL with patients’ wishes. The pandemic created health care strain that may have influenced life-support limitation practices among patients with serious COVID-19. In this study, we examine variations in life-support limitations (do-not-resuscitate, DNR; do-not-intubate, DNI) depending on the hospital and period of hospitalization. Methods: We included all adults admitted to a hospital in the United States with COVID-19 from January 2020 to December 2021 using the VIRUS registry. Our outcome was any life-support limitation on admission (DNR, DNI, or both) using regression modeling. Main exposures were hospital and period of hospitalization (early vs. late pandemic). Covariates included age, sex, race/ethnicity, comorbidities, and hospitalization diagnoses. Results: There were 42,383 patients from 75 hospitals in the US. The median age was 63 (interquartile range: 50–75), 46.5% were female, and 37.5% were non-Hispanic White. The life-support limitation rate was 7.9%, and the palliative care consultation rate was 2.3%. The odds of life-support limitation were 1.86 (95% CI: 1.6–2.1) depending on the hospital, but the period of hospitalization was not associated with odds of life-support limitation. Older age was associated with the greatest increased odds (4.1 per standard deviation ∼ 17.9 years, 95% CI: 3.9–4.4), followed by comorbidities including paralysis (2.4, 95% CI: 1.8–3.0) and dementia (2.3, 95% CI: 2.0–2.6). Conclusions: After adjusting for patient-level factors, we report significant inter-hospital but no temporal variation in life-support limitation upon admission with COVID-19. Future studies should investigate specific practices that led to health care resilience to temporal practice variations in life-support limitation during the pandemic.

Introduction: This study evaluated the impact of parallel-level patient transfers on bed utilization efficiency within the Mayo Clinic Health System in Southern Minnesota, focusing on optimizing resources across tertiary and critical access hospitals. Methods: A retrospective analysis of 179,066 Emergency Department visits (2018–2022) was conducted, with ~2% involving parallel-level transfers for observation or admission. Machine learning was utilized to identify patients suitable for parallel transfers based on demographics, comorbidities, and clinical factors. A Random Forest model with an AUROC of 0.87 guided transfer decisions. Saved patient days were calculated as the difference between the actual LOS and the benchmark LOS based on Diagnosis-Related Groups (DRGs). Generalized estimating equations analyzed length of stay (LOS) differences, adjusted for confounders, with 95% confidence intervals (CI). Statistical analyses were conducted using SPSS (v.26). Results: The mean patient age was 56 years (SD = 17.2), with 51.4% being female. Saved patient days increased from ~600 to 5200 days over the study period. Transferred patients had a 5.7% longer unadjusted LOS compared to non-transferred patients (95% CI: 2.9–8.6%, p < 0.001). After adjustment for demographics and comorbidities, the LOS difference was not significant (adjusted mean difference: 0.4%, 95% CI: −1.7–2.5%, p = 0.51). Conclusions: Parallel-level transfers increased saved patient days, reflecting enhanced resource utilization. However, the adjusted LOS differences were not significant, highlighting the need for robust transfer protocols and controlled studies to confirm these findings.

Background: Procalcitonin (PCT) is recognized as an inflammatory biomarker, often elevated in COVID-19 pneumonia alongside other biomarkers. Understanding its association with severe outcomes and comparing its predictive ability with other biomarkers is crucial for clinical management. Objectives: This retrospective multicenter observational study aimed to investigate the association between PCT levels and adverse outcomes in hospitalized COVID-19 patients. Additionally, it sought to compare the predictive performance of various biomarkers. Design: The study analyzed data from the Society of Critical Care Medicine (SCCM) Viral Infection and Respiratory Illness Universal Study (VIRUS) registry, comprising COVID-19 patients hospitalized across multiple Mayo Clinic sites between March 2020 and June 2022. Methods: A total of 7851 adult COVID-19 patients were included. Patients were categorized into 6 groups based on the worst WHO ordinal scale. Multivariate models were constructed using peak biomarker levels within 72 hours of admission, adjusted for confounders. Results: Elevated PCT levels were independently associated with increased odds of adverse outcomes, including ICU admission (adjusted odds ratio [aOR] 1.32, 95%CI 1.27-1.38), IMV requirement (aOR 1.35, 95%CI: 1.28-1.42), and in-hospital mortality (aOR 1.30, 95%CI: 1.22-1.37). A 3.48-fold increase in IMV requirement and 3.55 times increase in in-hospital mortality were noted with peak PCT ⩾ 0.25 ng/ml. Similar associations were observed with other biomarkers like NLR (AUC 0.730), CRP, IL-6, LDH (AUC 0.800), and D-dimer (AUC 0.719). Models incorporating NLR, LDH, D-dimer, and PCT demonstrated the highest predictive accuracy, with a combined model exhibiting an area under the curve (AUC) of 0.826 (95%CI 0.803-0.849). Conclusions: Higher PCT levels were significantly linked to worse outcomes in COVID-19 patients, emphasizing its potential as a prognostic marker. Biomarker-based predictive models, particularly those including PCT, showed promising utility for risk assessment and clinical decision-making. Further prospective studies are warranted to validate these findings on a larger scale.

Introduction/Background: Patients admitted with sepsis are at risk of developing septic cardiomyopathy (SCM), which may elevate their risk of short-term mortality. However, the effect of SCM on long-term outcomes after sepsis is poorly understood. This study explores whether patients with sepsis and SCM have worse long-term outcomes compared to those without SCM. Research Questions/Hypothesis: What are the long-term major adverse cardiovascular events, including death, stroke, and myocardial infarction (MACE) 36 months after ICU discharge for septic patients with abnormal global left ventricular strain (LV GLS)? Methods: We conducted a retrospective study of 396 sepsis patients from August 2018 to September 2022, approved by the Mayo Clinic IRB. Patient demographics, comorbidities, echo parameters, and outcomes were collected. Due to the expected non-linear relation between LV GLS and Hazard Ratio (HR) of MACE we employed Cox regression analysis with Restricted Cubic Splines. Secondly, we divided the population into 2 groups, patients with and without normal LV GLS (between -23 and -16). The effect of non-normal LV GLS on MACE was evaluated using Cox regression weight by inverse probability weighting (IPWT) analysis after propensity score assessment, adjusting for diabetes, hypertension, BMI, history of stroke or myocardial infarction, chronic kidney disease, age, and sex. Results: Demographic variables did not differ significantly based on normal versus abnormal LV GLS. In the restricted cox regression with cubic spline models, we observed that patients with normal values had HR lower than one compared with patients without normal values (Figure 1). Secondly, we found that the HR of MACE in patients with normal LV GLS was significantly lower in the crude analysis (HR 0.66 [CI 95% 0.5, 0.86]; p<0.01) and in the analysis adjusted by IPWT (HR 0.7 [CI 95% 0.53, 0.92]; p=0.01). Conclusion: Sepsis patients with abnormal global left ventricular strain (LV GLS) have a higher risk of major adverse cardiovascular events (MACE) within 36 months post-ICU discharge compared to those with normal strain. LV GLS values outside the range of -23 to -16 are associated with increased risk. Monitoring LV GLS in sepsis patients is important for identifying those at elevated risk for long-term cardiovascular complications.

Key Clinical MessageStone heart syndrome has a complex interaction with digoxin toxicity, where, theoretically, the administration of intravenous calcium can worsen a patient's condition. Research on this subject is conflicting, so it is imperative to approach it cautiously.

Blood transfusion is a common therapeutic intervention in hospitalized patients. There are numerous indications for transfusion, including anemia and coagulopathy with deficiency of single or multiple coagulation components such as platelets or coagulation factors. Nevertheless, the practice of transfusion in critically ill patients has been controversial mainly due to a lack of evidence and the need to consider the appropriate clinical context for transfusion. Further, transfusion carries many risk factors that must be balanced with benefits. Therefore, transfusion practice in ICU patients has constantly evolved, and we endeavor to present a contemporary review of transfusion practices in this population guided by clinical trials and expert guidelines.