Citations

Background: Sepsis survivors experience substantial long-term cardiovascular (CV) morbidity and mortality. The pooled-cohort atherosclerotic cardiovascular disease (ASCVD) score estimates 10-year risk in the general population, but its accuracy soon after sepsis is unknown. Objectives: (1) Describe the absolute five-year incidence of major adverse cardiovascular events (MACE) after sepsis hospitalization. (2) Evaluate the discrimination and calibration of the 10-year ASCVD score for predicting five-year MACE in this setting. Research Questions: The ASCVD score would underpredict five-year MACE in sepsis survivors, reflecting their heightened risk. Methods: We performed a retrospective closed-cohort study using electronic health records from Mayo Clinic hospitals (USA). Adults aged 40–75 years hospitalized for sepsis between 2018 and 2020 were eligible if follow-up was ≥5 years; the age criterion matched the derivation range of the ASCVD score. The primary outcome was five-year MACE—myocardial infarction (MI), ischemic or hemorrhagic stroke, or CV death. Secondly we evaluated the predictive performance of ASCVD score for five-year MACE. Discrimination was assessed with the area under the receiver-operating curve (AUROC); calibration with Calibration-in-the-Large (CITL, ideal = 0) and slope (ideal = 1). Performance metrics were calculated in patients with complete ASCVD variables. Results: A total of 6306 sepsis admissions were screened. 2424 patients were excluded for age outside 40–75 years and 879 for <5 year follow-up, leaving 2718 patients for incidence analyses. Median age was 65 years (IQR 56–70); 55 % were male, 38 % required ICU care, and 91 % were White. Median body-mass index was 28.2 kg/m2 (IQR 23.7-34.7). During follow-up, 125 patients (4.6 %) had MI, 219 (8.1 %) experienced stroke, and 303 (11.1 %) died of CV causes; overall, 1573 patients (57.9 %) met the composite MACE outcome. Complete ASCVD data were available for 409 patients. In this subset, discrimination was moderate (AUROC 0.65; 95 % CI 0.59–0.71). Calibration showed CITL +0.34 (95 % CI 0.09–0.59) and slope 0.50 (95 % CI 0.28–0.72), indicating systematic infra-prediction and over-fitting, respectively. Conclusion: Five-year MACE incidence after sepsis is high. The 10-year ASCVD score moderately discriminates but underestimates five-year CV risk in this population, highlighting the need for sepsis-specific predictive models or recalibration to guide targeted post-sepsis cardiovascular prevention.

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.

The evidence on indications, outcomes, and complications with the use of extracorporeal membrane oxygenation (ECMO) in the setting of interstitial lung disease (ILD) is limited in the existing literature. We performed a systematic review and meta-analysis for the use of ECMO in the setting of ILD to study the prognostic factors associated with in-hospital mortality. Eighteen unique studies with a total of 1,356 patients on ECMO for ILD were identified out of which 76.5% were on ECMO as a bridge to transplant (BTT) and the rest as a bridge to recovery (BTR). The overall in-hospital mortality was 45.76%, with 71.3% and 37.8% for BTR and BTT, respectively. Among the various prognostic factors, mortality was lower with younger age (mean difference = 3.15, 95% confidence interval [CI] = 0.82–5.49), use of awake veno-arterial (VA)-ECMO compared to veno-venous (VV)-ECMO (unadjusted odds ratio [OR] = 0.22, 95% CI = 0.13–0.37) in the overall cohort. In the setting of BTT, the use of VA-ECMO had a decreased hazard ratio (HR) compared to VV-ECMO (adjusted HR = 0.34, 95% CI = 0.15–0.81, p = 0.015). The findings of our meta-analysis are critical but are derived from retrospective studies with small sample sizes and thus are of low to very low-GRADE certainty.

Abstract Aims The viability of cardiac resynchronization therapy (CRT) in inotrope-dependent heart failure (HF) has been a matter of debate. Methods and results We searched Medline, EMBASE, Scopus, and the Cochrane Library until 31 December 2022. Studies were included if (i) HF patients required inotropic support at CRT implantation; (ii) patients were ≥18 years old; and (iii) they provided a clear definition of ‘inotrope dependence’ or ‘inability to wean’. A meta-analysis was performed in R (Version 3.5.1). Nineteen studies comprising 386 inotrope-dependent HF patients who received CRT (mean age 64.4 years, 76.9% male) were included. A large majority survived until discharge at 91.1% [95% confidence interval (CI): 81.2% to 97.6%], 89.3% were weaned off inotropes (95% CI: 77.6% to 97.0%), and mean discharge time post-CRT was 7.8 days (95% CI: 3.9 to 11.7). After 1 year of follow-up, 69.7% survived (95% CI: 58.4% to 79.8%). During follow-up, the mean number of HF hospitalizations was reduced by 1.87 (95% CI: 1.04 to 2.70, P &lt; 0.00001). Post-CRT mean QRS duration was reduced by 29.0 ms (95% CI: −41.3 to 16.7, P &lt; 0.00001), and mean left ventricular ejection fraction increased by 4.8% (95% CI: 3.1% to 6.6%, P &lt; 0.00001). The mean New York Heart Association (NYHA) class post-CRT was 2.7 (95% CI: 2.5 to 3.0), with a pronounced reduction of individuals in NYHA IV (risk ratio = 0.27, 95% CI: 0.18 to 0.41, P &lt; 0.00001). On univariate analysis, there was a higher prevalence of males (85.7% vs. 40%), a history of left bundle branch block (71.4% vs. 30%), and more pronounced left ventricular end-diastolic dilation (274.3 ± 7.2 vs. 225.9 ± 6.1 mL). Conclusions CRT appears to be a viable option for inotrope-dependent HF, with some of these patients seeming more likely to respond.

Introduction: Sepsis and its associated systemic inflammatory response syndrome in the heart can lead to septic cardiomyopathy. We aim to explore new onset cardiac dysfunction in septic shock patients and its association of right heart dysfunction with hospital outcomes. Hypothesis: Early development of correct ventricular abnormalities due to septic shock may lead to worse hospital outcomes. Methods: We conducted a retrospective study of 102 patients who were hospitalized at the Mayo Clinic between August 2018 and September 2022 with septic shock and had at least one pre-sepsis echo (within one year before admission) and one post-sepsis echo (within seven days of access). Information on patient demographics, comorbidities, echo parameters, and outcomes was collected from our sepsis database and retrospective chart review. Categorical variables were described as percentages and compared by Chi-square test, and continuous variables as medians and compared using an independent sample t-test. Statistical analysis was performed using BlueSky Statistics v10.3.1. Results: Our study included 102 patients with a median age of 68 (55, 78) years, the majority being men (68%) and Caucasians (80%). Between pre- and post-sepsis echos, there was a noticeable decrease in LVEF (60% vs 50.5 %; p=0.002). Moreover, there was an increase in reduced RV function (31.6% vs. 62.6%, p<0.001), reduced LV function (56.5% vs. 85.2%, p=0.048), and RV dilatation (35.8% vs. 51.5%, p=0.03). There was also a noticeable decrease in IVC collapsibility of more than 50% (65.9% vs 22.9%, p<0.001). There was no significance in terms of demographics, comorbidities, and baseline vitals and labs among patients with RV dysfunction and without RV dysfunction except for a lower LVEF (49% vs 62 %, p= 0.004) and decreased >50 % IVC collapsibility (14.5% vs 48%, p=0.005) in RV dysfunction group. We found no differences in hospital mortality, ICU and hospital LOS, or mechanical ventilation requirements amongst patients with RV abnormalities in function and size. Conclusions: Our retrospective study shows that abnormalities in RV function and RV size are commonly observed in the initial week of septic shock. However, such RV abnormalities did not translate into worse hospital outcomes.

BACKGROUND AND OBJECTIVE: As incidence of operative spinal pathology continues to grow, so do the rates of lumbar spinal fusion procedures. Comorbidity indices can be used preoperatively to predict potential complications. However, there is a paucity of research defining the optimal comorbidity indices in patients undergoing spinal fusion surgery. We aimed to use modeling strategies to evaluate the predictive validity of various comorbidity indices and combinations thereof. METHODS: Patients who underwent spinal fusion were queried using data from the Nationwide Readmissions Database for the years 2016 through 2019. Using comorbidity indices as predictor variables, receiver operating characteristic curves were developed for pertinent complications such as mortality, nonroutine discharge, top-quartile cost, top-quartile length of stay, and 30-day readmission. RESULTS: A total of 750 183 patients were included. Nonroutine discharges occurred in 161 077 (21.5%) patients. The adjusted all-payer cost for the procedure was $37 616.97 ± $27 408.86 (top quartile: $45 409.20), and the length of stay was 4.1 ± 4.4 days (top quartile: 8.1 days). By comparing receiver operating characteristics of various models, it was found that models using Frailty + Elixhauser Comorbidity Index (ECI) as the primary predictor performed better than other models with statistically significant P -values on post hoc testing. However, for prediction of mortality, the model using Frailty + ECI was not better than the model using ECI alone ( P = .23), and for prediction of all-payer cost, the ECI model outperformed the models using frailty alone ( P < .0001) and the model using Frailty + ECI ( P < .0001). CONCLUSION: This investigation is the first to use big data and modeling strategies to delineate the relative predictive utility of the ECI and Johns Hopkins Adjusted Clinical Groups comorbidity indices for the prognostication of patients undergoing lumbar fusion surgery. With the knowledge gained from our models, spine surgeons, payers, and hospitals may be able to identify vulnerable patients more effectively within their practice who may require a higher degree of resource utilization.