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World Journal of Otorhinolaryngology -... Mar 2018Although hundreds of thousands of patients seek medical help annually for disorders of taste and smell, relatively few medical practitioners quantitatively test their...
Although hundreds of thousands of patients seek medical help annually for disorders of taste and smell, relatively few medical practitioners quantitatively test their patients' chemosensory function, taking their complaints at face value. This is clearly not the approach paid to patients complaining of visual, hearing, or balance problems. Accurate chemosensory testing is essential to establish the nature, degree, and veracity of a patient's complaint, as well as to aid in counseling and in monitoring the effectiveness of treatment strategies and decisions. In many cases, patients perseverate on chemosensory loss that objective assessment demonstrates has resolved. In other cases, patients are malingering. Olfactory testing is critical for not only establishing the validity and degree of the chemosensory dysfunction, but for helping patients place their dysfunction into perspective relative to the function of their peer group. It is well established, for example, that olfactory dysfunction is the rule, rather than the exception, in members of the older population. Moreover, it is now apparent that such dysfunction can be an early sign of neurodegenerative diseases such as Alzheimer's and Parkinson's. Importantly, older anosmics are three times more likely to die over the course of an ensuring five-year period than their normosmic peers, a situation that may be averted in some cases by appropriate nutritional and safety counseling. This review provides the clinician, as well as the academic and industrial researcher, with an overview of the available means for accurately assessing smell and taste function, including up-to-date information and normative data for advances in this field.
PubMed: 30035257
DOI: 10.1016/j.wjorl.2018.03.001 -
International Journal of Nursing... Jan 2020
PubMed: 32099852
DOI: 10.1016/j.ijnss.2019.12.013 -
Brain and Behavior Jul 2021Behavioral and cognitive changes can be observed across all Huntington disease (HD) stages. Our multicenter and retrospective study investigated the association between...
INTRODUCTION
Behavioral and cognitive changes can be observed across all Huntington disease (HD) stages. Our multicenter and retrospective study investigated the association between cognitive and behavioral scale scores in manifest HD, at three different yearly timepoints.
METHODS
We analyzed cognitive and behavioral domains by the Unified Huntington's Disease Rating Scale (UHDRS) and by the Problem Behaviors Assessment Short Form (PBA-s), at three different yearly times of life (t0 or baseline, t1 after one year, t2 after two years), in 97 patients with manifest HD (mean age 48.62 ± 13.1), from three ENROLL-HD Centers. In order to test the disease progression, we also examined patients' motor and functional changes by the UHDRS, overtime.
RESULTS
The severity of apathy and of perseveration/obsession was associated with the severity of the cognitive decline (p < .0001), regardless of the yearly timepoint. The score of irritability significantly and positively correlated with perseveration errors in the verbal fluency test at t0 (r = .34; p = .001), while the psychosis significantly and negatively correlated with the information processing speed at t0 (r = -.21; p = .038) and significantly and positively correlated with perseveration errors in the verbal fluency test at t1 (r = .35; p < .0001). The disease progression was confirmed by the significant worsening of the UHDRS-Total Motor Score (TMS) and of the UHDRS-Total Functional Capacity (TFC) scale score after two-year follow-up (p < .0001).
CONCLUSION
Although the progression of abnormal behavioral manifestations cannot be predicted in HD, the severity of apathy and perseveration/obsessions are significantly associated with the severity of the cognitive function impairment, thus contributing, together, to the disease development and to patients' loss of independence, in addition to the neurological manifestations. This cognitive-behavior pattern determines a common underlying deficit depending on a dysexecutive syndrome.
Topics: Adult; Cognition; Cross-Sectional Studies; Humans; Huntington Disease; Middle Aged; Problem Behavior; Retrospective Studies; Severity of Illness Index
PubMed: 34110097
DOI: 10.1002/brb3.2151 -
Journal of the American College of... Mar 2018
Topics: Autopsy; Death, Sudden, Cardiac; Humans
PubMed: 29544604
DOI: 10.1016/j.jacc.2018.02.005 -
The Journal of Neuroscience : the... Mar 2021Gambling disorder (GD) is a behavioral addiction associated with impairments in value-based decision-making and behavioral flexibility and might be linked to changes in...
Gambling disorder (GD) is a behavioral addiction associated with impairments in value-based decision-making and behavioral flexibility and might be linked to changes in the dopamine system. Maximizing long-term rewards requires a flexible trade-off between the exploitation of known options and the exploration of novel options for information gain. This exploration-exploitation trade-off is thought to depend on dopamine neurotransmission. We hypothesized that human gamblers would show a reduction in directed (uncertainty-based) exploration, accompanied by changes in brain activity in a fronto-parietal exploration-related network. Twenty-three frequent, non-treatment seeking gamblers and twenty-three healthy matched controls (all male) performed a four-armed bandit task during functional magnetic resonance imaging (fMRI). Computational modeling using hierarchical Bayesian parameter estimation revealed signatures of directed exploration, random exploration, and perseveration in both groups. Gamblers showed a reduction in directed exploration, whereas random exploration and perseveration were similar between groups. Neuroimaging revealed no evidence for group differences in neural representations of basic task variables (expected value, prediction errors). Our hypothesis of reduced frontal pole (FP) recruitment in gamblers was not supported. Exploratory analyses showed that during directed exploration, gamblers showed reduced parietal cortex and substantia-nigra/ventral-tegmental-area activity. Cross-validated classification analyses revealed that connectivity in an exploration-related network was predictive of group status, suggesting that connectivity patterns might be more predictive of problem gambling than univariate effects. Findings reveal specific reductions of strategic exploration in gamblers that might be linked to altered processing in a fronto-parietal network and/or changes in dopamine neurotransmission implicated in GD. Wiehler et al. (2021) report that gamblers rely less on the strategic exploration of unknown, but potentially better rewards during reward learning. This is reflected in a related network of brain activity. Parameters of this network can be used to predict the presence of problem gambling behavior in participants.
Topics: Adult; Behavior, Addictive; Brain; Choice Behavior; Computer Simulation; Gambling; Humans; Learning; Magnetic Resonance Imaging; Male; Reinforcement, Psychology; Reward
PubMed: 33531415
DOI: 10.1523/JNEUROSCI.1607-20.2021 -
Scientific Reports Sep 2020The Wisconsin Card Sorting Test (WCST) is considered a gold standard for the assessment of cognitive flexibility. On the WCST, repeating a sorting category following...
The Wisconsin Card Sorting Test (WCST) is considered a gold standard for the assessment of cognitive flexibility. On the WCST, repeating a sorting category following negative feedback is typically treated as indicating reduced cognitive flexibility. Therefore such responses are referred to as 'perseveration' errors. Recent research suggests that the propensity for perseveration errors is modulated by response demands: They occur less frequently when their commitment repeats the previously executed response. Here, we propose parallel reinforcement-learning models of card sorting performance, which assume that card sorting performance can be conceptualized as resulting from model-free reinforcement learning at the level of responses that occurs in parallel with model-based reinforcement learning at the categorical level. We compared parallel reinforcement-learning models with purely model-based reinforcement learning, and with the state-of-the-art attentional-updating model. We analyzed data from 375 participants who completed a computerized WCST. Parallel reinforcement-learning models showed best predictive accuracies for the majority of participants. Only parallel reinforcement-learning models accounted for the modulation of perseveration propensity by response demands. In conclusion, parallel reinforcement-learning models provide a new theoretical perspective on card sorting and it offers a suitable framework for discerning individual differences in latent processes that subserve behavioral flexibility.
Topics: Adult; Attention; Female; Humans; Learning; Male; Models, Statistical; Neuropsychological Tests; Psychomotor Performance; Reinforcement, Psychology; Wisconsin Card Sorting Test; Young Adult
PubMed: 32963297
DOI: 10.1038/s41598-020-72407-7 -
Frontiers in Neurology 2022The capacity for voluntary control is seen as essential to human movements; the sense that one intended to move (willing) and those actions were self-generated... (Review)
Review
The capacity for voluntary control is seen as essential to human movements; the sense that one intended to move (willing) and those actions were self-generated (self-agency) gives the sense of voluntariness and of being in control. While the mechanisms underlying voluntary movement have long been unclear, recent neuroscientific tools have identified networks of different brain areas, namely, the prefrontal cortex, supplementary motor area, and parietal cortex, that underlie voluntary action. Dysfunction in these brain areas can result in different forms of semivoluntary movement as the borderland of voluntary and involuntary movement where a person may experience a disordered sense of will or agency, and thus the movement is experienced as unexpected and involuntary, for an otherwise voluntary-appearing movement. Tics, functional movement disorders, stereotypies, perseveration, compulsions, utilization behaviors, and motor mannerism have been described elsewhere in the context of psychoses, and are often mistaken for each other. Yet, they reflect an impairment of prefrontal cortices and related circuits rather than simple motor systems, which results in the absence of subjective recognition of the movements, in contrast to other neurological movement disorders where principal abnormalities are located within the basal ganglia and its connections. Therefore, their recognition is clinically important since they are usually associated with neurodevelopmental and neurodegenerative disorders. In this review, we first defined a conceptual framework, from both a neuroanatomical and a neurophysiological point of view, for the generation of voluntary movement. We then examined the evidence linking dysfunctions in different motor pathways to each type of movement disorder. We looked at common semivoluntary movement disorders providing an overview, where possible, of their phenomenology and brain network abnormalities for each condition. We also emphasized important clinical feature similarities and differences to increase recognition of each condition in practice.
PubMed: 35265031
DOI: 10.3389/fneur.2022.834217 -
The Journal of Thoracic and... Sep 2018
Topics: Alloys; Creativity; Sweating; Trachea
PubMed: 29934005
DOI: 10.1016/j.jtcvs.2018.05.021 -
Schizophrenia Bulletin Open Jan 2022There is an ongoing debate about the potential risks and benefits of long-term antipsychotic treatment in schizophrenia. The data for and against the chronic use of... (Review)
Review
There is an ongoing debate about the potential risks and benefits of long-term antipsychotic treatment in schizophrenia. The data for and against the chronic use of these medicines is mostly indirect, either from observational studies potentially exposed to reverse causation bias or randomized controlled studies that do not cover beyond 2-3 years. We propose that perseverating on the question of what positive or negative outcomes are causally associated with chronic antipsychotic treatment may not lead to better answers than the limited ones that we have, given the limited feasibility of more conclusive studies. Rather, we argue that addressing the research question of the risks and benefits of antipsychotic discontinuation from a perspective of personalized medicine, can be more productive and meaningful to people living with schizophrenia. To this end, research that can quantify the risk of relapse after treatment continuation for a given individual should be prioritized. We make the case that clinically feasible neuroimaging biomarkers have demonstrated promise in related paradigms, and that could be offering a way past this long debate on the risks and benefits of chronic antipsychotic use.
PubMed: 36277256
DOI: 10.1093/schizbullopen/sgac059 -
JMIR Medical Informatics Mar 2022High flow nasal cannula (HFNC) provides noninvasive respiratory support for children who are critically ill who may tolerate it more readily than other noninvasive...
Predicting High Flow Nasal Cannula Failure in an Intensive Care Unit Using a Recurrent Neural Network With Transfer Learning and Input Data Perseveration: Retrospective Analysis.
BACKGROUND
High flow nasal cannula (HFNC) provides noninvasive respiratory support for children who are critically ill who may tolerate it more readily than other noninvasive ventilation (NIV) techniques such as bilevel positive airway pressure and continuous positive airway pressure. Moreover, HFNC may preclude the need for mechanical ventilation (intubation). Nevertheless, NIV or intubation may ultimately be necessary for certain patients. Timely prediction of HFNC failure can provide an indication for increasing respiratory support.
OBJECTIVE
The aim of this study is to develop and compare machine learning (ML) models to predict HFNC failure.
METHODS
A retrospective study was conducted using the Virtual Pediatric Intensive Care Unit database of electronic medical records of patients admitted to a tertiary pediatric intensive care unit between January 2010 and February 2020. Patients aged <19 years, without apnea, and receiving HFNC treatment were included. A long short-term memory (LSTM) model using 517 variables (vital signs, laboratory data, and other clinical parameters) was trained to generate a continuous prediction of HFNC failure, defined as escalation to NIV or intubation within 24 hours of HFNC initiation. For comparison, 7 other models were trained: a logistic regression (LR) using the same 517 variables, another LR using only 14 variables, and 5 additional LSTM-based models using the same 517 variables as the first LSTM model and incorporating additional ML techniques (transfer learning, input perseveration, and ensembling). Performance was assessed using the area under the receiver operating characteristic (AUROC) curve at various times following HFNC initiation. The sensitivity, specificity, and positive and negative predictive values of predictions at 2 hours after HFNC initiation were also evaluated. These metrics were also computed for a cohort with primarily respiratory diagnoses.
RESULTS
A total of 834 HFNC trials (455 [54.6%] training, 173 [20.7%] validation, and 206 [24.7%] test) met the inclusion criteria, of which 175 (21%; training: 103/455, 22.6%; validation: 30/173, 17.3%; test: 42/206, 20.4%) escalated to NIV or intubation. The LSTM models trained with transfer learning generally performed better than the LR models, with the best LSTM model achieving an AUROC of 0.78 versus 0.66 for the 14-variable LR and 0.71 for the 517-variable LR 2 hours after initiation. All models except for the 14-variable LR achieved higher AUROCs in the respiratory cohort than in the general intensive care unit population.
CONCLUSIONS
ML models trained using electronic medical record data were able to identify children at risk of HFNC failure within 24 hours of initiation. LSTM models that incorporated transfer learning, input data perseveration, and ensembling showed improved performance compared with the LR and standard LSTM models.
PubMed: 35238792
DOI: 10.2196/31760