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Background: Radical cystectomy has high complication rates and, consequently, a high socioeconomic burden. The association between preoperative electrolyte levels and postoperative outcomes after radical cystectomy has not been investigated. Therefore, we aimed to investigate the association between preoperative potassium level and clinical (30-day morbidity) and economical (length of hospital stay) postoperative outcomes of patients undergoing radical cystectomy. Materials and Methods: We retrospectively evaluated clinical data of 317 patients who had undergone radical cystectomy for bladder cancer. Univariate and multivariate logistic regression analyses were performed to determine whether preoperative patient clinical factors influence clinical (30-day morbidity according to the Clavien-Dindo classification) and economical (length of hospital stay) postoperative outcomes. Results: In univariate analysis, low Charlson comorbidity score (p = 0.011), low ASA score (p = 0.015), no aspirin intake (p = 0.048) and high-normal preoperative potassium level (p = 0.034) were associated with reduced 30-day morbidity. In multivariate analysis, only high preoperative potassium remained an independent predictive factor for a reduced risk of postoperative complications (odds ratio 0.67, 95% confidence interval (0.48, 0.92), p = 0.014). Furthermore, high-normal preoperative potassium was the only preoperative factor associated with a shorter hospital stay ≤21 days (p = 0.007). Conclusions: High-normal preoperative potassium level was associated with better clinical (lower 30-day morbidity) and economical (shorter hospital stay) outcomes in patients undergoing radical cystectomy. We recommend that a randomized controlled trial be performed to investigate whether there is a causal relationship between preoperative potassium supplementation and postoperative complications and length of hospital stay.

Haptic search is a common everyday task, usually consisting of two processes: target search and target analysis. During target search we need to know where our fingers are in space, remember the already completed path and the outline of the remaining space. During target analysis we need to understand whether the detected potential target is the desired one. Here we characterized dynamics of exploratory movements in these two processes. In our experiments participants searched for a particular configuration of symbols on a rectangular tactile display. We observed that participants preferentially moved the hand parallel to the edges of the tactile display during target search, which possibly eased orientation within the search space. After a potential target was detected by any of the fingers, there was higher probability that subsequent exploration was performed by the index or the middle finger. At the same time, these fingers dramatically slowed down. Being in contact with the potential target, the index and the middle finger moved within a smaller area than the other fingers, which rather seemed to move away to leave them space. These results suggest that the middle and the index finger are specialized for fine analysis in haptic search.

Background As the coronavirus disease 2019 (COVID-19) vaccination campaign unfolds, it is important to continuously assess the real-world safety of Food and Drug Administration (FDA)-authorized vaccines. Curation of large-scale electronic health records (EHRs) enables near-real-time safety evaluations that were not previously possible. Methods In this retrospective study, we deployed deep neural networks over a large EHR system to automatically curate the adverse effects mentioned by physicians in over 1.2 million clinical notes between December 1, 2020 and April 20, 2021. We compared notes from 68,266 individuals who received at least one dose of BNT162b2 (n = 51,795) or mRNA-1273 (n = 16,471) to notes from 68,266 unvaccinated individuals who were matched by demographic, geographic, and clinical features. Findings Individuals vaccinated with BNT162b2 or mRNA-1273 had a higher rate of return to the clinic, but not the emergency department, after both doses compared to unvaccinated controls. The most frequently documented adverse effects within 7 days of each vaccine dose included myalgia, headache, and fatigue, but the rates of EHR documentation for each side effect were remarkably low compared to those derived from active solicitation during clinical trials. Severe events, including anaphylaxis, facial paralysis, and cerebral venous sinus thrombosis, were rare and occurred at similar frequencies in vaccinated and unvaccinated individuals. Conclusions This analysis of vaccine-related adverse effects from over 1.2 million EHR notes of more than 130,000 individuals reaffirms the safety and tolerability of the FDA-authorized mRNA COVID-19 vaccines in practice. Funding This study was funded by nference., Graphical abstract, Context and significance This is a study of the mRNA COVID-19 vaccines developed by Pfizer/BioNTech and Moderna. Although these vaccines have been shown to be safe and tolerated in clinical trials, it is important to confirm their safety profiles in practice. The results from this study show that individuals receiving these vaccines are likely to experience muscle and joint soreness, but they are not more likely to seek out emergent clinical care or experience severe medical events than unvaccinated individuals. As one of the largest real-world safety studies of COVID-19 vaccines to date, these data reinforce that we should continue expanding efforts to deliver more vaccines with high confidence in their safety., McMurry et al. assess the real-world safety of the BNT162b2 and mRNA-1273 COVID-19 vaccines. Using natural language processing, they compare the rates of specified adverse effects between 68,266 vaccinated individuals and 68,266 matched unvaccinated individuals. They find that both vaccines are safe and tolerated in clinical practice.

As the COVID-19 vaccination campaign unfolds as one of the most rapid and widespread in history, it is important to continuously assess the real-world safety of the FDA-authorized vaccines. Curation from large-scale electronic health records (EHRs) allows for near real-time safety evaluations that were not previously possible. Here, we advance context- and sentiment-aware deep neural networks over the multi-state Mayo Clinic enterprise (Minnesota, Arizona, Florida, Wisconsin) for automatically curating the adverse effects mentioned by healthcare providers in over 108,000 EHR clinical notes between December 1st2020 and February 8th2021. We retrospectively compared the clinical notes of 31,029 individuals who received at least one dose of the Pfizer/BioNTech or Moderna mRNA vaccine to those of 30,933 unvaccinated individuals who were propensity matched by demographics, residential location, and history of prior SARS-CoV-2 testing. We find that vaccinated and unvaccinated individuals were seen in the clinic at similar rates within 21 days of the first or second actual or assigned vaccination date (first dose Odds Ratio = 1.14, 95% CI: 1.10-1.18; second dose Odds Ratio = 0.91, 95% CI: 0.86-0.96). Further, the incidence rates of all surveyed adverse effects were similar or lower in vaccinated individuals compared to unvaccinated individuals after either vaccine dose, although myalgia was modestly increased within 7 days of the second dose when considering only pairs of matched individuals who each had at least one clinical note in this time window (Incidence Rate Ratio = 2.5, 95% CI: 1.1-6.7). Finally, the most frequently documented adverse effects within 7 days of each vaccine dose were fatigue (Dose 1: 1.75%, Dose 2: 1.18%), nausea (Dose 1: 1.03%, Dose 2: 0.84%), myalgia (Dose 1: 0.41%; Dose 2: 0.43%), diarrhea (Dose 1: 0.65%; Dose 2: 0.45%), arthralgia (Dose 1: 0.64%; Dose 2: 0.57%), erythema (Dose 1: 0.56%; Dose 2: 0.44%), vomiting (Dose 1: 0.44%, Dose 2: 0.29%) and fever (Dose 1: 0.21%; Dose 2: 0.18%). These frequencies of adverse event documentation in EHR notes are 2.1 times (95% CI: [1.5, 3.0]) to 1500 times (95% CI: [670, 2800]) lower than the frequencies of adverse events recorded via active solicitation during clinical trials or post-marketing surveillance, with headache after second vaccination showing the highest ratio of trial reporting to EHR documentation. This rapid and timely analysis of EHR notes from 31,029 vaccinated individuals highlights the rarity of vaccine-associated adverse effects requiring clinical attention and reaffirms the tolerability of the FDA-authorized COVID-19 vaccines in practice.

BACKGROUND In the face of hospital capacity strain, hospitals have developed multifaceted plans to try to improve patient flow. Many of these initiatives have focused on the timing of discharges and on lowering lengths of stay, and they have met with variable success. We deployed a novel tool in the electronic health record to enhance discharge communication. OBJECTIVE The aim of this study is to evaluate the effectiveness of a discharge communication tool. METHODS This was a prospective, single-center, pre-post study. Hospitalist physicians and advanced practice providers (APPs) used the Discharge Today Tool to update patient discharge readiness every morning and at any time the patient status changed throughout the day. Primary outcomes were tool use, time of day the clinician entered the discharge order, time of day the patient left the hospital, and hospital length of stay. We used linear mixed modeling and generalized linear mixed modeling, with team and discharging provider included in all the models to account for patients cared for by the same team and the same provider. RESULTS During the pilot implementation period from March 5, 2019, to July 31, 2019, a total of 4707 patients were discharged (compared with 4558 patients discharged during the preimplementation period). A total of 352 clinical staff had used the tool, and 84.85% (3994/4707) of the patients during the pilot period had a discharge status assigned at least once. In a survey, most respondents reported that the tool was helpful (32/34, 94% of clinical staff) and either saved time or did not add additional time to their workflow (21/24, 88% of providers, and 34/34, 100% of clinical staff). Although improvements were not observed in either unadjusted or adjusted analyses, after including starting morning census per team as an effect modifier, there was a reduction in the time of day the discharge order was entered into the electronic health record by the discharging physician and in the time of day the patient left the hospital (decrease of 2.9 minutes per additional patient, P=.07, and 3 minutes per additional patient, P=.07, respectively). As an effect modifier, for teams that included an APP, there was a significant reduction in the time of day the patient left the hospital beyond the reduction seen for teams without an APP (decrease of 19.1 minutes per patient, P=.04). Finally, in the adjusted analysis, hospital length of stay decreased by an average of 3.7% (P=.06). CONCLUSIONS The Discharge Today tool allows for real time documentation and sharing of discharge status. Our results suggest an overall positive response by care team members and that the tool may be useful for improving discharge time and length of stay if a team is staffed with an APP or in higher-census situations.

When touching the surface of an object, its spatial structure translates into a vibration on the skin. The perceptual system evolved to translate this pattern into a representation that allows to distinguish between different materials. Here, we show that perceptual haptic representation of materials emerges from efficient encoding of vibratory patterns elicited by the interaction with materials. We trained a deep neural network with unsupervised learning (Autoencoder) to reconstruct vibratory patterns elicited by human haptic exploration of different materials. The learned compressed representation (i.e., latent space) allows for classification of material categories (i.e., plastic, stone, wood, fabric, leather/wool, paper, and metal). More importantly, classification performance is higher with perceptual category labels as compared to ground truth ones, and distances between categories in the latent space resemble perceptual distances, suggesting a similar coding. Crucially, the classification performance and the similarity between the perceptual and the latent space decrease with decreasing compression level. We could further show that the temporal tuning of the emergent latent dimensions is similar to properties of human tactile receptors.

Haptic perception involves active exploration usually consisting of repeated stereotypical movements. The choice of such exploratory movements and their parameters are tuned to achieve high perceptual precision. Information obtained from repeated exploratory movements (e.g. repeated indentations of an object to perceive its softness) is integrated but improvement of discrimination performance is limited by memory if the two objects are explored one after the other in order to compare them. In natural haptic exploration humans tend to switch between the objects multiple times when comparing them. Using the example of softness perception here we test the hypothesis that given the same amount of information, discrimination improves if memory demands are lower. In our experiment participants explored two softness stimuli by indenting each of the stimuli four times. They were allowed to switch between the stimuli after every single indentation (7 switches), after every second indentation (3 switches) or only once after four indentations (1 switch). We found better discrimination performance with seven switches as compared to one switch, indicating that humans naturally apply an exploratory strategy which might reduce memory demands and thus leads to improved performance.

Redundant estimates of an environmental property derived simultaneously from different senses or cues are typically integrated according to the maximum likelihood estimation model (MLE): Sensory estimates are weighted according to their reliabilities, maximizing the percept's reliability. Mechanisms underlying the integration of sequentially derived estimates from one sense are less clear. Here we investigate the integration of serially sampled redundant information in softness perception. We developed a method to manipulate haptically perceived softness of silicone rubber stimuli during bare-finger exploration. We then manipulated softness estimates derived from single movement segments (indentations) in a multisegmented exploration to assess their contributions to the overall percept. Participants explored two stimuli in sequence, using 2-5 indentations, and reported which stimulus felt softer. Estimates of the first stimulus's softness contributed to the judgments similarly, whereas for the second stimulus estimates from later compared to earlier indentations contributed less. In line with unequal weighting, the percept's reliability increased with increasing exploration length less than was predicted by the MLE model. This pattern of results is well explained by assuming that the representation of the first stimulus fades when the second stimulus is explored, which fits with a neurophysiological model of perceptual decisions (Deco, Rolls, & Romo, 2010). (PsycINFO Database Record

Background In the face of hospital capacity strain, hospitals have developed multifaceted plans to try to improve patient flow. Many of these initiatives have focused on the timing of discharges and on lowering lengths of stay, and they have met with variable success. We deployed a novel tool in the electronic health record to enhance discharge communication. Objective The aim of this study is to evaluate the effectiveness of a discharge communication tool. Methods This was a prospective, single-center, pre-post study. Hospitalist physicians and advanced practice providers (APPs) used the Discharge Today Tool to update patient discharge readiness every morning and at any time the patient status changed throughout the day. Primary outcomes were tool use, time of day the clinician entered the discharge order, time of day the patient left the hospital, and hospital length of stay. We used linear mixed modeling and generalized linear mixed modeling, with team and discharging provider included in all the models to account for patients cared for by the same team and the same provider. Results During the pilot implementation period from March 5, 2019, to July 31, 2019, a total of 4707 patients were discharged (compared with 4558 patients discharged during the preimplementation period). A total of 352 clinical staff had used the tool, and 84.85% (3994/4707) of the patients during the pilot period had a discharge status assigned at least once. In a survey, most respondents reported that the tool was helpful (32/34, 94% of clinical staff) and either saved time or did not add additional time to their workflow (21/24, 88% of providers, and 34/34, 100% of clinical staff). Although improvements were not observed in either unadjusted or adjusted analyses, after including starting morning census per team as an effect modifier, there was a reduction in the time of day the discharge order was entered into the electronic health record by the discharging physician and in the time of day the patient left the hospital (decrease of 2.9 minutes per additional patient, P=.07, and 3 minutes per additional patient, P=.07, respectively). As an effect modifier, for teams that included an APP, there was a significant reduction in the time of day the patient left the hospital beyond the reduction seen for teams without an APP (decrease of 19.1 minutes per patient, P=.04). Finally, in the adjusted analysis, hospital length of stay decreased by an average of 3.7% (P=.06). Conclusions The Discharge Today tool allows for real time documentation and sharing of discharge status. Our results suggest an overall positive response by care team members and that the tool may be useful for improving discharge time and length of stay if a team is staffed with an APP or in higher-census situations.

Exploring an object's shape by touch also renders information about its surface roughness. It has been suggested that shape and roughness are processed distinctly in the brain, a result based on comparing brain activation when exploring objects that differed in one of these features. To investigate the neural mechanisms of top‐down control on haptic perception of shape and roughness, we presented the same multidimensional objects but varied the relevance of each feature. Specifically, participants explored two objects that varied in shape (oblongness of cuboids) and surface roughness. They either had to compare the shape or the roughness in an alternative‐forced‐choice‐task. Moreover, we examined whether the activation strength of the identified brain regions as measured by functional magnetic resonance imaging (fMRI) can predict the behavioral performance in the haptic discrimination task. We observed a widespread network of activation for shape and roughness perception comprising bilateral precentral and postcentral gyrus, cerebellum, and insula. Task‐relevance of the object's shape increased activation in the right supramarginal gyrus (SMG/BA 40) and the right precentral gyrus (PreCG/BA 44) suggesting that activation in these areas does not merely reflect stimulus‐driven processes, such as exploring shape, but also entails top‐down controlled processes driven by task‐relevance. Moreover, the strength of the SMG/PreCG activation predicted individual performance in the shape but not in the roughness discrimination task. No activation was found for the reversed contrast (roughness > shape). We conclude that macrogeometric properties, such as shape, can be modulated by top‐down mechanisms whereas roughness, a microgeometric feature, seems to be processed automatically.

Haptic search is a common every day task. Here we characterize the movement dynamics in haptic search. Participants searched for a particular configuration of symbols on a tactile display. We compared the exploratory behavior of the fingers in proximity to potential targets: when any of the fingers encountered a potential target, there was higher probability that subsequent exploration was performed by the index or the middle finger. At the same time, the middle and the index fingers dramatically slowed down. Being in contact with the potential target, the index and the middle finger moved in around a smaller area than the other fingers, which rather seemed to move away to leave them space. Our results corroborate a previous hypothesis [1] that haptic search consists of two phases: a process of target search using all fingers, and a target analysis using the middle and the index finger, which might be specialized for fine analysis.

In haptic perception information is often sampled serially (e.g. a stimulus is repeatedly indented to estimate its softness), requiring that sensory information is retained and integrated over time. Hence, integration of sequential information is likely affected by memory. Particularly, when two sequentially explored stimuli are compared, integration of information on the second stimulus might be determined by the fading representation of the first stimulus. We investigated how the exploration length of the first stimulus and a temporal delay affect contributions of sequentially gathered estimates of the second stimulus in haptic softness discrimination. Participants subsequently explored two silicon rubber stimuli by indenting the first stimulus 1 or 5 times and the second stimulus always 3 times. In an additional experiment we introduced a 5s delay after the first stimulus was indented 5 times. We show that the longer the first stimulus is explored, the more estimates of the second stimulus’ softness contribute to the discrimination of the two stimuli, independent of the delay. This suggests that the exploration length of the first stimulus influences the strength of its representation, persisting at least for 5s, and determines how much information about the second stimulus is exploited for the comparison. There are zip files for every experiment (1 & 2), which contain all data relative to the publication. The data of each participant is contained in a separate folder. This folder contains a *.raw file for each session of the experiment and a "data" folder, which contains movement trajectories (*.trj files) and the staircase reversals for each condition (*.pse files) in separate folders for each session. Variables of Experiment 1 are described in the fileVARIABLE_CODES_EXP1.txt and the variables of Experiment 2 are described in the file VARIABLE_CODES_EXP2.txt.

Due to limitations in perceptual processing, information relevant to momentary task goals is selected from the vast amount of available sensory information by top-down mechanisms (e.g. attention) that can increase perceptual performance. We investigated how covert attention affects perception of 3D objects in active touch. In our experiment, participants simultaneously explored the shape and roughness of two objects in sequence, and were told afterwards to compare the two objects with regard to one of the two features. To direct the focus of covert attention to the different features we manipulated the expectation of a shape or roughness judgment by varying the frequency of trials for each task (20%, 50%, 80%), then we measured discrimination thresholds. We found higher discrimination thresholds for both shape and roughness perception when the task was unexpected, compared to the conditions in which the task was expected (or both tasks were expected equally). Our results suggest that active touch perception is modulated by expectations about the task. This implies that despite fundamental differences, active and passive touch are affected by feature selective covert attention in a similar way.

When touching an object, we focus more on some of its parts rather than touching the whole object’s surface, i.e. some parts are more salient than others. Here we investigated how different physical properties of rigid, plastic, relieved textures determine haptic exploratory behavior. We produced haptic stimuli whose textures were locally defined by random distributions of four independent features: amplitude, spatial frequency, orientation and isotropy. Participants explored two stimuli one after the other and in order to promote exploration we asked them to judge their similarity. We used a linear regression model to relate the features and their gradients to the exploratory behavior (spatial distribution of touch duration). The model predicts human behavior significantly better than chance, suggesting that exploratory movements are to some extent driven by the low level features we investigated. Remarkably, the contribution of each predictor changed as a function of the spatial scale in which it was defined, showing that haptic exploration preferences are spatially tuned, i.e. specific features are most salient at different spatial scales.