A model relating C(e)pro and C(e)remi to AAI/2, BIS, and IoC has been developed and prospectively validated. Based on these models, the (C(e)pro, C(e)remi) concentration pairs that provide an RSS score of 4 range from (1.8 μg·mL(-1), 1.5 ng·mL(-1)) to (2.7 μg·mL(-1), 0 ng·mL(-1)). These concentrations are associated with AAI/2 values of 25 to 30, BIS of 71 to 75, and IoC of 72 to 76. The presence of noxious stimulation increases the requirements of C(e)pro and C(e)remi to achieve the same degree of sedative effects.

Background:The presence of the A118G single nucleotide polymorphism in the OPRM1 gene as well as noxious stimulation might affect the requirements of remifentanil for patients undergoing ultrasonographic endoscopy under sedation-analgesia with propofol and remifentanil. Bispectral index (BIS) was used as a surrogate measure of effect. Methods:A total of 207 patients were screened for A118G and randomly received different combinations of propofol and remifentanil, changed depending on the nausea response to endoscopy tube introduction. Nonlinear mixed effects modelling was used to establish the relation between propofol and remifentanil with respect to BIS and to investigate the influence of A118G or noxious stimulation. The value of k e0 for propofol and remifentanil was estimated to avoid the hysteresis between predicted effect site concentration (Ce) and BIS. Results: Data from 176 patients were analysed. Eleven were recessive homozygous for A118G (OPRM = 1). A total of 165 patients were either dominant homozygous or heterozygous and considered normal (OPRM = 0). The estimated values of k e0 for propofol and remifentanil were 0.122 and 0.148 min −1 . Propofol and remifentanil were synergistic with respect to the BIS (α = 1.85). EC 50 estimate for propofol was 3.86 µg/ml and for remifentanil 19.6 ng/ml in normal patients and 326 ng/ml in OPRM = 1 patients. BIS increases around 4% for the same effect site concentrations with noxious stimulation. Conclusions: Predicted effect site concentration of remifentanil ranging 1-5 ng/ml synergistically potentiates the effects

The availability of large, deidentified health datasets has enabled significant innovation in using machine learning (ML) to better understand patients and their diseases. However, questions remain regarding the true privacy of this data, patient control over their data, and how we regulate data sharing in a way that that does not encumber progress or further potentiate biases for underrepresented populations. After reviewing the literature on potential reidentifications of patients in publicly available datasets, we argue that the cost—measured in terms of access to future medical innovations and clinical software—of slowing ML progress is too great to limit sharing data through large publicly available databases for concerns of imperfect data anonymization. This cost is especially great for developing countries where the barriers preventing inclusion in such databases will continue to rise, further excluding these populations and increasing existing biases that favor high-income countries. Preventing artificial intelligence’s progress towards precision medicine and sliding back to clinical practice dogma may pose a larger threat than concerns of potential patient reidentification within publicly available datasets. While the risk to patient privacy should be minimized, we believe this risk will never be zero, and society has to determine an acceptable risk threshold below which data sharing can occur—for the benefit of a global medical knowledge system.

Abstract-Monitoring the levels of sedation-analgesia may be helpful for managing patient stress on minimally invasive medical procedures. Monitors based on EEG analysis and designed to assess general anesthesia cannot distinguish reliably between a light and deep sedation. In this work, the Poincaré plot is used as a nonlinear technique applied to EEG signals in order to characterize the levels of sedation-analgesia, according to observed categorical responses that were evaluated by means of Ramsay Sedation Scale (RSS). To study the effect of high frequencies due to EMG activity, three different frequency ranges (FR1=0.5-110 Hz, FR2=0.5-30 Hz and FR3=30-110 Hz) were considered. Indexes from power spectral analysis and plasma concentration of propofol and remifentanil were also compared with the bispectral index BIS. An adaptive Neurofuzzy Inference System was applied to model the interaction of the best indexes with respect to RSS score for each analysis, and leave-one-out cross validation method was used. The ability of the indexes to describe the level of sedation-analgesia, according with the RSS score, was evaluated using the prediction probability (Pk). The results showed that the ratio SD1/SD2FR3 contains useful information about the sedation level, and SD1FR2 and SD2FR2 had the best performance classifying response to noxious stimuli. Models including parameters from Poincaré plot emerge as a good estimator of sedation-analgesia levels.