Profiling endogenous adrenal function during veno-venous ECMO support in COVID-19 ARDS: a descriptive analysis

BackgroundProlonged critical illness is often accompanied by an impairment of adrenal function, which has been frequently related to conditions complicating patient management. The presumed connection between hypoxia and the pathogenesis of this critical- illness- related corticosteroid insufficiency (CIRCI) might play an important role in patients with severe acute respiratory distress syndrome (ARDS). Since extracorporeal membrane oxygenation (ECMO) is frequently used in ARDS, but data on CIRCI during this condition are scarce, this study reports the behaviour of adrenal function parameters during oxygenation support with veno-venous (vv)ECMO in coronavirus disease 2019 (COVID-19) ARDS.MethodsA total of 11 patients undergoing vvECMO due to COVID-19 ARDS at the Medical University of Vienna, who received no concurrent corticosteroid therapy, were retrospectively included in this study. We analysed the concentrations of cortisol, aldosterone, and angiotensin (Ang) metabolites (Ang I–IV, Ang 1–7, and Ang 1–5) in serum via liquid chromatography/tandem mass spectrometry before, after 1 day, 1 week, and 2 weeks during vvECMO support and conducted correlation analyses between cortisol and parameters of disease severity.ResultsCortisol concentrations appeared to be lowest after initiation of ECMO and progressively increased throughout the study period. Higher concentrations were related to disease severity and correlated markedly with interleukin-6, procalcitonin, pH, base excess, and albumin during the first day of ECMO. Fair correlations during the first day could be observed with calcium, duration of critical illness, and ECMO gas flow. Angiotensin metabolite concentrations were available in a subset of patients and indicated a more homogenous aldosterone response to plasma renin activity after 1 week of ECMO support.ConclusionOxygenation support through vvECMO may lead to a partial recovery of adrenal function over time. In homogenous patient collectives, this novel approach might help to further determine the importance of adrenal stress response in ECMO and the influence of oxygenation support on CIRCI

Duration of invasive mechanical ventilation prior to extracorporeal membrane oxygenation is not associated with survival in acute respiratory distress syndrome caused by coronavirus disease 2019

BACKGROUND: Duration of invasive mechanical ventilation (IMV) prior to extracorporeal membrane oxygenation (ECMO) affects outcome in acute respiratory distress syndrome (ARDS). In coronavirus disease 2019 (COVID-19) related ARDS, the role of pre-ECMO IMV duration is unclear. This single-centre, retrospective study included critically ill adults treated with ECMO due to severe COVID-19-related ARDS between 01/2020 and 05/2021. The primary objective was to determine whether duration of IMV prior to ECMO cannulation influenced ICU mortality. RESULTS: During the study period, 101 patients (mean age 56 [SD ± 10] years; 70 [69%] men; median RESP score 2 [IQR 1–4]) were treated with ECMO for COVID-19. Sixty patients (59%) survived to ICU discharge. Median ICU length of stay was 31 [IQR 20.7–51] days, median ECMO duration was 16.4 [IQR 8.7–27.7] days, and median time from intubation to ECMO start was 7.7 [IQR 3.6–12.5] days. Fifty-three (52%) patients had a pre-ECMO IMV duration of > 7 days. Pre-ECMO IMV duration had no effect on survival (p = 0.95). No significant difference in survival was found when patients with a pre-ECMO IMV duration of < 7 days (< 10 days) were compared to ≥ 7 days (≥ 10 days) (p = 0.59 and p = 1.0). CONCLUSIONS: The role of prolonged pre-ECMO IMV duration as a contraindication for ECMO in patients with COVID-19-related ARDS should be scrutinised. Evaluation for ECMO should be assessed on an individual and patient-centred basis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13613-022-00980-3

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

Abstract Background During the COVID-19 pandemic, a variety of clinical decision support systems (CDSS) were developed to aid patient triage. However, research focusing on the interaction between decision support systems and human experts is lacking. Methods Thirty-two physicians were recruited to rate the survival probability of 59 critically ill patients by means of chart review. Subsequently, one of two artificial intelligence systems advised the physician of a computed survival probability. However, only one of these systems explained the reasons behind its decision-making. In the third step, physicians reviewed the chart once again to determine the final survival probability rating. We hypothesized that an explaining system would exhibit a higher impact on the physicians’ second rating (i.e., higher weight-on-advice). Results The survival probability rating given by the physician after receiving advice from the clinical decision support system was a median of 4 percentage points closer to the advice than the initial rating. Weight-on-advice was not significantly different (p = 0.115) between the two systems (with vs without explanation for its decision). Additionally, weight-on-advice showed no difference according to time of day or between board-qualified and not yet board-qualified physicians. Self-reported post-experiment overall trust was awarded a median of 4 out of 10 points. When asked after the conclusion of the experiment, overall trust was 5.5/10 (non-explaining median 4 (IQR 3.5–5.5), explaining median 7 (IQR 5.5–7.5), p = 0.007). Conclusions Although overall trust in the models was low, the median (IQR) weight-on-advice was high (0.33 (0.0–0.56)) and in line with published literature on expert advice. In contrast to the hypothesis, weight-on-advice was comparable between the explaining and non-explaining systems. In 30% of cases, weight-on-advice was 0, meaning the physician did not change their rating. The median of the remaining weight-on-advice values was 50%, suggesting that physicians either dismissed the recommendation or employed a “meeting halfway” approach. Newer technologies, such as clinical reasoning systems, may be able to augment the decision process rather than simply presenting unexplained bias

A retrospective analysis of the need for on-site emergency physician presence and mission characteristics of a rural ground-based emergency medical service

Abstract Background This study aimed to address the challenges faced by rural emergency medical services in Europe, due to an increasing number of missions and limited human resources. The primary objective was to determine the necessity of having an on-site emergency physician (EP), while the secondary objectives included analyzing the characteristics of rural EP missions. Methods A retrospective study was conducted, examining rural EP missions carried out between January 1st, 2017, and December 2nd, 2021 in Burgenland, Austria. The need for physical presence of an EP was classified based on the National Advisory Committee for Aeronautics (NACA) score into three categories; category A: no need for an EP (NACA 1–3); category B: need for an EP (NACA 1–3 along with additional medical interventions beyond the capabilities of emergency medical technicians); and category C: definite need for an EP (NACA 4–7). Descriptive statistics were used for analysis. Results Out of 16,971 recorded missions, 15,591 were included in the study. Approximately 32.3% of missions fell into category A, indicating that an EP’s physical presence was unnecessary. The diagnoses made by telecommunicators matched those of the EPs in only 52.8% of cases. Conclusion The study suggests that about a third of EP missions carried out in rural areas might not have a solid medical rationale. This underscores the importance of developing an alternative care approach for these missions. Failing to address this could put additional pressure on already stretched EMS systems, risking their collapse

Virtual and Augmented Reality Applications in Medicine: Analysis of the Scientific Literature.

BACKGROUND Virtual reality (VR) and augmented reality (AR) have recently become popular research themes. However, there are no published bibliometric reports that have analyzed the corresponding scientific literature in relation to the application of these technologies in medicine. OBJECTIVE We used a bibliometric approach to identify and analyze the scientific literature on VR and AR research in medicine, revealing the popular research topics, key authors, scientific institutions, countries, and journals. We further aimed to capture and describe the themes and medical conditions most commonly investigated by VR and AR research. METHODS The Web of Science electronic database was searched to identify relevant papers on VR research in medicine. Basic publication and citation data were acquired using the "Analyze" and "Create Citation Report" functions of the database. Complete bibliographic data were exported to VOSviewer and Bibliometrix, dedicated bibliometric software packages, for further analyses. Visualization maps were generated to illustrate the recurring keywords and words mentioned in the titles and abstracts. RESULTS The analysis was based on data from 8399 papers. Major research themes were diagnostic and surgical procedures, as well as rehabilitation. Commonly studied medical conditions were pain, stroke, anxiety, depression, fear, cancer, and neurodegenerative disorders. Overall, contributions to the literature were globally distributed with heaviest contributions from the United States and United Kingdom. Studies from more clinically related research areas such as surgery, psychology, neurosciences, and rehabilitation had higher average numbers of citations than studies from computer sciences and engineering. CONCLUSIONS The conducted bibliometric analysis unequivocally reveals the versatile emerging applications of VR and AR in medicine. With the further maturation of the technology and improved accessibility in countries where VR and AR research is strong, we expect it to have a marked impact on clinical practice and in the life of patients

Inadequate Energy Delivery Is Frequent among COVID-19 Patients Requiring ECMO Support and Associated with Increased ICU Mortality

Background: Patients receiving extracorporeal membrane oxygenation (ECMO) support are at high risk for malnutrition. There are currently no general nutrition guidelines for coronavirus disease 2019 (COVID-19) patients during ECMO therapy. Methods: We conducted a retrospective analysis of COVID-19 patients requiring venovenous ECMO support at a large tertiary hospital center. Nutrition goals were calculated using 25 kcal/kg body weight (BW)/day. Associations between nutrition support and outcome were evaluated using Kaplan–Meier and multivariable Cox regression analyses. Results: Overall, 102 patients accounted for a total of 2344 nutrition support days during ECMO therapy. On 40.6% of these days, nutrition goals were met. Undernutrition was found in 40.8%. Mean daily calorie delivery was 73.7% of calculated requirements, mean daily protein delivery was 0.7 g/kg BW/d. Mean energy intake of ≥70% of calculated targets was associated with significantly lower ICU mortality independently of age, disease severity at ECMO start and body mass index (adjusted hazard ratio: 0.372, p = 0.007). Conclusions: Patients with a mean energy delivery of ≥70% of calculated targets during ECMO therapy had a better ICU survival compared to patients with unmet energy goals. These results indicate that adequate nutritional support needs to be a major priority in the treatment of COVID-19 patients requiring ECMO support

Development of a Reinforcement Learning Algorithm to Optimize Corticosteroid Therapy in Critically Ill Patients with Sepsis.

BACKGROUND: The optimal indication, dose, and timing of corticosteroids in sepsis is controversial. Here, we used reinforcement learning to derive the optimal steroid policy in septic patients based on data on 3051 ICU admissions from the AmsterdamUMCdb intensive care database. METHODS: We identified septic patients according to the 2016 consensus definition. An actor-critic RL algorithm using ICU mortality as a reward signal was developed to determine the optimal treatment policy from time-series data on 277 clinical parameters. We performed off-policy evaluation and testing in independent subsets to assess the algorithm's performance. RESULTS: Agreement between the RL agent's policy and the actual documented treatment reached 59%. Our RL agent's treatment policy was more restrictive compared to the actual clinician behavior: our algorithm suggested withholding corticosteroids in 62% of the patient states, versus 52% according to the physicians' policy. The 95% lower bound of the expected reward was higher for the RL agent than clinicians' historical decisions. ICU mortality after concordant action in the testing dataset was lower both when corticosteroids had been withheld and when corticosteroids had been prescribed by the virtual agent. The most relevant variables were vital parameters and laboratory values, such as blood pressure, heart rate, leucocyte count, and glycemia. CONCLUSIONS: Individualized use of corticosteroids in sepsis may result in a mortality benefit, but optimal treatment policy may be more restrictive than the routine clinical practice. Whilst external validation is needed, our study motivates a 'precision-medicine' approach to future prospective controlled trials and practice