Endovascular renal sympathetic denervation to improve heart failure with reduced ejection fraction: the IMPROVE-HF-I study.

INTRODUCTION: The aim of the present study was to assess the safety and efficacy of renal sympathetic denervation (RDN) in patients with heart failure with reduced ejection fraction (HFrEF). METHODS: We randomly assigned 50 patients with a left ventricular ejection fraction (LVEF) ≤ 35% and NYHA class ≥ II, in a 1:1 ratio, to either RDN and optimal medical therapy (OMT) or OMT alone. The primary safety endpoint was the occurrence of a combined endpoint of cardiovascular death, rehospitalisation for heart failure, and acute kidney injury at 6 months. The primary efficacy endpoint was the change in iodine-123 meta-iodobenzylguanidine (123I­MIBG) heart-to-mediastinum ratio (HMR) at 6 months. RESULTS: Mean age was 60 ± 9 years, 86% was male and mean LVEF was 33 ± 8%. At 6 months, the primary safety endpoint occurred in 8.3% vs 8.0% in the RDN and OMT groups, respectively (p = 0.97). At 6 months, the mean change in late HMR was -0.02 (95% CI: -0.08 to 0.12) in the RDN group, versus -0.02 (95% CI: -0.09 to 0.12) in the OMT group (p = 0.95) whereas the mean change in washout rate was 2.34 (95% CI: -6.35 to 1.67) in the RDN group versus -2.59 (95% CI: -1.61 to 6.79) in the OMT group (p-value 0.09). CONCLUSION: RDN with the Vessix system in patients with HFrEF was safe, but did not result in significant changes in cardiac sympathetic nerve activity at 6 months as measured using 123I­MIBG.

The Value of Artificial Intelligence in Laboratory Medicine.

OBJECTIVES: As laboratory medicine continues to undergo digitalization and automation, clinical laboratorians will likely be confronted with the challenges associated with artificial intelligence (AI). Understanding what AI is good for, how to evaluate it, what are its limitations, and how it can be implemented are not well understood. With a survey, we aimed to evaluate the thoughts of stakeholders in laboratory medicine on the value of AI in the diagnostics space and identify anticipated challenges and solutions to introducing AI. METHODS: We conducted a web-based survey on the use of AI with participants from Roche's Strategic Advisory Network that included key stakeholders in laboratory medicine. RESULTS: In total, 128 of 302 stakeholders responded to the survey. Most of the participants were medical practitioners (26%) or laboratory managers (22%). AI is currently used in the organizations of 15.6%, while 66.4% felt they might use it in the future. Most had an unsure attitude on what they would need to adopt AI in the diagnostics space. High investment costs, lack of proven clinical benefits, number of decision makers, and privacy concerns were identified as barriers to adoption. Education in the value of AI, streamlined implementation and integration into existing workflows, and research to prove clinical utility were identified as solutions needed to mainstream AI in laboratory medicine. CONCLUSIONS: This survey demonstrates that specific knowledge of AI in the medical community is poor and that AI education is much needed. One strategy could be to implement new AI tools alongside existing tools.

Septic patients with cancer: Do prehospital antibiotics improve survival? A sub-analysis of the PHANTASi trial.

BACKGROUND: Sepsis in patients with cancer is increasingly common and associated with high mortality. To date, no studies have examined the effectiveness of prehospital antibiotics in septic patients with cancer. This study aimed without and to evaluate the effect of prehospital antibiotics in septic patients with cancer. METHODS: We conducted a post-hoc sub-analysis of the PHANTASi (PreHospital ANTibioitcs Against Sepsis) trial database: a randomised controlled trial which enrolled patients with suspected sepsis who were transported to the emergency department by ambulance. Patients in the intervention group were administered prehospital intravenous antibiotics while those in the control group received usual care. We compared patients who had cancer to those who did not. Primary outcome was 28-day mortality; among the secondary outcomes, we included in-hospital mortality and 90-day mortality. RESULTS: 357(13.4%) of the 2658 included patients had cancer in the past five years, of which, 209 (58.5%) were included in the intervention and 148 (41.5%) usual care groups; 28-day mortality was significantly higher in patients who were diagnosed with cancer in the past five years than those without cancer in the past five years: 15.2% vs. 7.1%, respectively (p < 0.001). Prehospital antibiotics in the group of patients with cancer in the last five years yielded no significant effect on survival. There were however, significantly fewer 30-day readmissions (p = 0.031) in the intervention group of cancer patients (12.2% vs 5.7%). CONCLUSION: Prehospital antibiotics did not improve overall survival. However, there was a significant reduction in 30-day readmissions.

Health related quality of life in sepsis survivors from the Prehospital Antibiotics Against Sepsis (PHANTASi) trial.

BACKGROUND: Due to the rise in incidence, the long term effect of sepsis are becoming more evident. There is increasing evidence that sepsis may result in an impaired health related quality of life. The aim of this study was to investigate whether health related quality of life is impaired in sepsis survivors and which clinical parameters are associated with the affected health related quality of life. METHODS: We analyzed 880 Short Form 36 (SF-36) questionnaires that were sent to sepsis survivors who participated in the Prehospital Antibiotics Against Sepsis (PHANTASi) trial. These questionnaires were sent by email, 28 days after discharge. Data entry and statistical analyses were performed in SPSS. The data from the general Dutch population, was obtained from the Netherlands Cancer Institute (NKI-AVL) and served as a control group. Subsequently, 567 sepsis survivors were matched to 567 controls. Non-parametric Wilcoxon signed-rank test was performed to compare these two groups. Within the group, we sought to explain the diminished health related quality of life by factor analysis. RESULTS: We found that sepsis survivors have a worse health related quality of life compared to the general Dutch population. This negative effect was more evident for the physical component than the mental component of health related quality of life. We found that health related quality of life was significantly altered by advancing age and female sex. We also found that the total length of stay (in the hospital) and (previous) comorbidity negatively affect the physical component of health related quality of life. CONCLUSION: In our study we found that health related quality of life in sepsis survivors, 28 days after discharge, is severely diminished in comparison with the general Dutch population. The physical domain is severely affected, whereas the mental domain is less influenced. The length of stay, comorbidity, advancing age and female sex all have a negative effect on the Physical Component Scale of the health related quality of life.

Clinical applications of artificial intelligence in sepsis: A narrative review.

Many studies have been published on a variety of clinical applications of artificial intelligence (AI) for sepsis, while there is no overview of the literature. The aim of this review is to give an overview of the literature and thereby identify knowledge gaps and prioritize areas with high priority for further research. A literature search was conducted in PubMed from inception to February 2019. Search terms related to AI were combined with terms regarding sepsis. Articles were included when they reported an area under the receiver operator characteristics curve (AUROC) as outcome measure. Fifteen articles on diagnosis of sepsis with AI models were included. The best performing model reached an AUROC of 0.97. There were also seven articles on prognosis, predicting mortality over time with an AUROC of up to 0.895. Finally, there were three articles on assistance of treatment of sepsis, where the use of AI was associated with the lowest mortality rates. Of the articles, twenty-two were judged to be at high risk of bias or had major concerns regarding applicability. This was mostly because predictor variables in these models, such as blood pressure, were also part of the definition of sepsis, which led to overestimation of the performance. We conclude that AI models have great potential for improving early identification of patients who may benefit from administration of antibiotics. Current AI prediction models to diagnose sepsis are at major risks of bias when the diagnosis criteria are part of the predictor variables in the model. Furthermore, generalizability of these models is poor due to overfitting and a lack of standardized protocols for the construction and validation of the models. Until these problems have been resolved, a large gap remains between the creation of an AI algorithm and its implementation in clinical practice.

Evaluation of blood culture epidemiology and efficiency in a large European teaching hospital.

BACKGROUND: Blood cultures remain the gold standard for detecting bacteremia despite their limitations. The current practice of blood culture collection is still inefficient with low yields. Limited focus has been given to the association between timing of specimen collection at different time points during admission and their yield. METHODS: We carried out a retrospective observational study by analyzing all 3,890 sets of cultures collected from the 1,962 admitted patients over the seven-month period of this study. We compared the blood culture yield between the early group (≤24 hours after admission) and the late group (> 24 hours of admission). We also investigated the effect of prehospital oral antibiotics and pre-analytical time on the first cultures in the emergency department. Epidemiology and efficiency of blood cultures were studied for each medical specialty. RESULTS: In total, 3,349(86.1%) blood cultures were negative and 541(13.9%) were positive for one or more microorganisms. After correcting for contamination, the overall yield was 290 (7.5%). The early group (n = 1,490) yielded significantly more true-positive cultures (10.1% versus 5.8%, P<0.001) than the late group (n = 2,400). The emergency department had a significantly higher yield than general wards, 11.2% versus 5.7% (p<0.001). Prehospital oral antibiotic use and pre-analytical time did not affect the yield of first cultures at the emergency department (p = 0.735 and 0.816 respectively). The number of tests needed to obtain one true-positive culture varied between departments, ranging from 7 to 45. CONCLUSION: This study showed that blood cultures are inefficient in detecting bacteremia. Cultures collected during 24 hours after admission yielded more positive results than those collected later. Significant variations in blood culture epidemiology and efficiency per specialty suggest that guidelines should be reevaluated. Future studies should aim at improving blood culture yield, implementing educational programs to reduce contamination and cost-effective application of modern molecular diagnostic technologies.

Changes in vital signs post discharge as a potential target for intervention to avoid readmission.

Readmissions are treated as adverse events in many healthcare systems. Causes can be physiological deterioration or breakdown of social support systems. We investigated data from a European multi-centre study of readmissions for changes in vital signs between index admission and readmission. Data sets were graded according to the National Early Warning Score (NEWS). Of 487 patients in whom NEWS could be calculated on discharge and again on re-admission, 39.6% had worse vital signs with a NEWS score difference ≥ 2 points while only 7.6% had improved by ≤ 2 points. Changes in individual vital signs of 20% or more were most common in respiratory rate and heart rate. Monitoring of respiratory rate and pulse rate post-discharge might predict some deteriorations.

Prognostic value of early warning scores in the emergency department (ED) and acute medical unit (AMU): A narrative review.

BACKGROUND: A wide array of early warning scores (EWS) have been developed and are used in different settings to detect which patients are at risk of deterioration. The aim of this review is to provide an overview of studies conducted on the value of EWS on predicting intensive care (ICU) admission and mortality in the emergency department (ED) and acute medical unit (AMU). METHODS: A literature search was conducted in the bibliographic databases PubMed and EMBASE, from inception to April 2017. Two reviewers independently screened all potentially relevant titles and abstracts for eligibility. RESULTS: 42 studies were included. 36 studies reported on mortality as an endpoint, 13 reported ICU admission and 9 reported the composite outcome of mortality and ICU admission. For mortality prediction National Early Warning Score (NEWS) was the most accurate score in the general ED population and in those with respiratory distress, Mortality in Emergency Department Sepsis score (MEDS) had the best accuracy in patients with an infection or sepsis. ICU admission was best predicted with NEWS, however in patients with an infection or sepsis Modified Early Warning Score (MEWS) yielded better results for this outcome. CONCLUSION: MEWS and NEWS generally had favourable results in the ED and AMU for all endpoints. Many studies have been performed on ED and AMU populations using heterogeneous prognostic scores. However, future studies should concentrate on a simple and easy to use prognostic score such as NEWS with the aim of introducing this throughout the (pre-hospital and hospital) acute care chain.

Long-term health related quality of life in patients with sepsis after intensive care stay: A systematic review.

Sepsis is a major health care issue and sepsis survivors are often confronted with long-term complications after admission to the intensive care unit (ICU) which may negatively influence their health related quality of life (HRQOL). This study aimed to systematically evaluate the outcome in terms of HRQOL in patients with sepsis after ICU discharge. A literature search was conducted in the bibliographic databases PubMed, EMBASE, and CINAHL, including reference lists of published guidelines, reviews and associated articles. Sixteen studies were included, thirteen (81.3%) reported that sepsis survivors suffer from impaired HRQOL in physical and mental domains which persist from months to years after a sepsis episode. More focus on improving long-term outcomes for patients surviving sepsis and the ICU is needed.