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.

Multiple risk factors for postoperative nausea and vomiting (PONV)—a very distressing and outcome-related complication—have been identified, including female sex, absence of a history of smoking, history of PONV, and postoperative opioid use. Evidence of association of intraoperative hypotension with PONV is contradictory. A retrospective analysis of the perioperative documentation of 38,577 surgeries was conducted. The associations between different characterizations of intraoperative hypotension and PONV in the postoperative care unit (PACU) were investigated. First, the relationship between different characterizations of intraoperative hypotension with regard to PONV in the PACU was investigated. Secondly, the performance of the optimal characterization was assessed in an independent dataset derived via random split. The vast majority of characterizations showed an association of hypotension with the incidence of PONV in the PACU. In a multivariable regression, time with a MAP under 50 mmHg showed the strongest association with PONV in terms of the cross-validated Brier score. The adjusted odds for PONV in the PACU were estimated to be 1.34 times higher (95% CI: 1.33–1.35) when a MAP was under 50 mmHg for at least 1.8 min than when a MAP remained above 50 mmHg. The finding indicates that intraoperative hypotension may yet be another risk factor for PONV and therefore emphasizes the importance of intraoperative blood pressure management not only in patients at risk for cardiovascular complications but also in young and healthy patients at risk of PONV.

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.

Background: Associations between intraoperative hypotension (IOH) and various postoperative outcomes were shown in retrospective trials using a variety of different definitions of IOH. This complicates the comparability of these trials and makes clinical application difficult. Information about the best performing definitions of IOH regarding 30-day mortality, hospital length of stay (hLOS), and postanesthesia care unit length of stay (PACU-LOS) is missing. Methods: A retrospective cohort trial was conducted using data from patients undergoing noncardiothoracic surgery. We split the obtained dataset into two subsets. First, we used one subset to choose the best fitting definitions of IOH for the outcomes 30-day mortality, hLOS, and PACU-LOS. The other subset was used to independently assess the performance of the chosen definitions of IOH. Results: The final cohort consisted of 65,454 patients. In the shaping subset, nearly all tested definitions of IOH showed associations with the three outcomes, where the risk of adverse outcomes often increased continuously with decreasing MAP. The best fitting definitions were relative time with a MAP (mean arterial pressure) of <80 mmHg for 30-day mortality, lowest MAP for one minute for hLOS, and lowest MAP for one cumulative minute for PACU-LOS. Testing these three definitions of IOH in the independent second subset confirmed the associations of IOH with 30-day mortality, hLOS, and PACU-LOS. Conclusions: Using a data-driven approach, we identified the best fitting definitions of IOH for 30-day mortality, hLOS, and PACU-LOS. Our results demonstrate the need for careful selection of IOH definitions. Clinical trial number: n/a, EC #2245/2020

Accurate temperature measurement is crucial for the perioperative management of pediatric patients, and non-invasive thermometry is necessary when invasive methods are infeasible. A prospective observational study was conducted on 57 patients undergoing elective surgery. Temperatures were measured using a dual-sensor heat-flux (DHF) thermometer (Tcore™) and a rectal temperature probe (TRec), and the agreement between the two measurements was assessed. The DHF measurements showed a bias of +0.413 °C compared with those of the TRec. The limits of agreement were broader than the pre-defined ±0.5 °C range (−0.741 °C and +1.567 °C). Although the DHF sensors tended to overestimate the core temperature compared to the rectal measurements, an error grid analysis demonstrated that 95.81% of the DHF measurements would not have led to a wrong clinical decision, e.g., warming or cooling when not necessary. In conclusion, the low number of measurements that would have led to incorrect decisions suggests that the DHF sensor can be considered an option for continuous temperature measurement when more invasive methods are infeasible.

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.