Long-COVID autonomic syndrome in working age and work ability impairment.

Long-COVID19 has been recently associated with long-sick leave and unemployment. The autonomic nervous system functioning may be also affected by SARS-CoV-2, leading to a chronic autonomic syndrome. This latter remains widely unrecognized in clinical practice. In the present study, we assessed the occurrence of Long-COVID19 Autonomic Syndrome in a group of active workers as well as the relationships between their autonomic dysfunction and work ability. This prospective observational study was conducted during the 2nd wave of the pandemic in Italy. Forty-five patients (53.6 ± 8.4 years; 32 M) hospitalized for COVID19, were consecutively enrolled at the time of their hospital discharge (T0) and followed-up for 6 months. Autonomic symptoms and work ability were assessed by COMPASS31 and Work Ability Index questionnaires at T0, one (T1), three and six (T6) months after hospital discharge and compared to those retrospectively collected for a period preceding SARS-CoV-2 infection. Clinical examination and standing test were also performed at T1 and T6. One in three working-age people developed a new autonomic syndrome that was still evident 6 months after the acute infection resolution. This was associated with a significant reduction in the work ability. Recognition of Long-COVID19 Autonomic Syndrome may promote early intervention to facilitate return to work and prevent unemployment.

Comparative Analysis of Antithrombotic Therapy Outcomes in Mild Traumatic Brain-Injury Patients: A Focus on Bleeding Risk and Hospital-Stay Duration.

BACKGROUND: Traumatic brain injury (TBI) in the elderly is a noteworthy pathology due to the exponential increase in population age, and the effects of antiplatelet and anticoagulation on patients' outcomes are still a matter of dispute. The aim of the present study was to evaluate the impact of various antithrombotic agents on patients with mild TBI, focusing on the risk of intracranial bleeding (ICH) and length of hospitalization (LOS). METHODS: A retrospective analysis was conducted, including patients with a diagnosis of TBI admitted to the Emergency Department between 2021 and 2022. Patients were classified according to the concurrent antithrombotic therapy as aspirin (ASA), antiplatelets, direct oral anticoagulants (DOACs), and low-molecular-weight heparin (LMWH). The primary outcome was the ICH occurrence, while the secondary outcome was the LOS. The statistical analysis was performed via logistic regression models in R and STATA 13.1 software. Fisher's exact test was used for the statistical significance. RESULTS: 267 patients with mild TBI were included; 148 were not on antithrombotic agents, 43 were on aspirin, 33 on DOACs, 5 on LMWH, 22 on antiplatelets, and 16 on VKA. Out of the total, 9 patients experienced ICH, none of which were on DOACs, LMWH, or VKA, but 4-out of 65-were on antiplatelets, and 5-out of 148-were not on antithrombotic therapies. Patients not on antithrombotic therapy had the shortest LOS at 0.46 days, while those on VKA had the longest LOS at 1.19 days; similar trends were observed for patients on DOAC and LMWH. CONCLUSIONS: The results reveal that TBI patients on anticoagulants/antiplatelets had longer hospital stays compared with those on aspirin alone. Notably, VKA was the strongest predictor for an extended LOS. Regarding ICH, patients taking only aspirin were twice as likely to experience bleeding compared with those on anticoagulants/antiplatelets. However, to achieve statistically significant evidence, further research with a larger cohort of patients is needed.

The Long-COVID autonomic syndrome in hospitalized patients: A one-year prospective cohort study.

Long-COVID syndrome is characterized by fatigue, orthostatic intolerance, tachycardia, pain, memory difficulties, and brain fog, which may be associated with autonomic nervous system abnormalities. We aimed to evaluate the short and long-term course of COVID-19 autonomic symptoms and quality of life (QoL) after SARS-CoV-2 infection through a one-year follow-up combined with validated questionnaires. Additionally, we aimed to identify patients with worsening autonomic symptoms at 6 and 12 months by dividing the patient cohort into two sub-groups: the Post-COVID healed Control sub-group (total score<16.4) and the Long-COVID autonomic syndrome sub-group (total score>16.4). This prospective cohort studied 112 SARS-CoV-2 positive patients discharged from Humanitas Research Hospital between January and March 2021. Autonomic symptoms and QoL were assessed using the composite autonomic symptom scale 31 (COMPASS-31) and Short Form Health Survey (SF-36) questionnaires at various time points: before SARS-CoV-2 infection (PRE), at hospital discharge (T0), and at 1 (T1), 3 (T3), 6 (T6), and 12 (T12) months of follow-up. COMPASS-31 total score, Orthostatic Intolerance and Gastrointestinal function indices, QoL, physical functioning, pain, and fatigue scores worsened at T0 compared to PRE but progressively improved at T1 and T3, reflecting the acute phase of COVID-19. Unexpectedly, these indices worsened at T6 and T12 compared to T3. Subgroup analysis revealed that 47% of patients experienced worsening autonomic symptoms at T6 and T12, indicating Long-COVID autonomic syndrome. Early rehabilitative and pharmacological therapy is recommended for patients at the T1 and T3 stages after SARS-CoV-2 infection to minimize the risk of developing long-term autonomic syndrome.

Soluble interleukin-1 receptor type 2 plasma levels in Parkinson's disease: relationship with cardiac autonomic profile before and after peripheral mechanical somatosensory stimulation.

Introduction: Systemic inflammation promotes neurodegeneration in Parkinson's disease (PD). Interleukin-1 receptor type 2 (sIL-1R2) plasma levels increase during inflammation. Data on sIL-1R2 in PD patients and its relationship with PD cardiac autonomic profile are limited, given the possible anti-inflammatory effect of vagal activation. Previously, automated mechanical peripheral somatosensory stimulation (AMPSS) enhanced cardiac vagal modulation. Objectives were to 1) evaluate sIL-1R2 plasma concentrations in PD patients and healthy controls and 2) investigate the correlations between sIL-1R2 and cardiac autonomic indices obtained by spectrum analysis of heart rate variability before and after AMPSS. Methods: sIL-1R2 plasma levels were assessed in 48 PD patients and 50 healthy controls. Electrocardiogram and beat-by-beat arterial pressure were recorded at baseline and after 5 AMPSS sessions in 16 PD patients. Results: PD patients had higher sIL-1R2 levels than controls. In the PD subgroup, an inverse correlation between sIL-1R2 and HFnu was found. There was a negative correlation between changes induced by AMPSS on HFnu and sIL-1R2. Discussion: Higher sIL-1R2 levels in PD patients reflect the inflammatory dysregulation associated with the disease. In PD patients, higher sIL-1R2 was associated with reduced cardiovagal tone. Increased cardiovagal modulation following AMPSS was associated with lower sIL-1R2 levels in Parkinson's disease patients, suggesting inflammatory state improvement.

Ursodeoxycholic Acid Does Not Improve COVID-19 Outcome in Hospitalized Patients.

Ursodeoxycholic acid (UDCA) was demonstrated to reduce susceptibility to SARS-CoV-2 infection in vitro and improve infection course in chronic liver diseases. However, real-life evidence is lacking. We analyzed the impact of UDCA on COVID-19 outcomes in patients hospitalized in a tertiary center. Between January 2020 and January 2023, among 3847 patients consecutively hospitalized for COVID19, 57 (=UDCA group) were taking UDCA. The UDCA and the control groups (n = 3790) did not differ concerning comorbidities including diabetes mellitus type 2 (15.8% vs. 12.8%) and neoplasia (12.3% vs. 9.4%). Liver diseases and vaccination rate were more common in the UDCA group (14.0% vs. 2.5% and 54.4% vs. 30.2%, respectively). Overall mortality and CPAP treatment were 22.8 % and 15.7% in the UDCA, and 21.3% and 25.9% in the control group. Mortality was similar (p = 0.243), whereas UDCA was associated with a lower rate of CPAP treatment (OR = 0.76, p < 0.05). Treatment with UDCA was not an independent predictor of survival in patients hospitalized for COVID-19.

Multimodal deep learning for COVID-19 prognosis prediction in the emergency department: a bi-centric study.

Predicting clinical deterioration in COVID-19 patients remains a challenging task in the Emergency Department (ED). To address this aim, we developed an artificial neural network using textual (e.g. patient history) and tabular (e.g. laboratory values) data from ED electronic medical reports. The predicted outcomes were 30-day mortality and ICU admission. We included consecutive patients from Humanitas Research Hospital and San Raffaele Hospital in the Milan area between February 20 and May 5, 2020. We included 1296 COVID-19 patients. Textual predictors consisted of patient history, physical exam, and radiological reports. Tabular predictors included age, creatinine, C-reactive protein, hemoglobin, and platelet count. TensorFlow tabular-textual model performance indices were compared to those of models implementing only tabular data. For 30-day mortality, the combined model yielded slightly better performances than the tabular fastai and XGBoost models, with AUC 0.87 ± 0.02, F1 score 0.62 ± 0.10 and an MCC 0.52 ± 0.04 (p < 0.32). As for ICU admission, the combined model MCC was superior (p < 0.024) to the tabular models. Our results suggest that a combined textual and tabular model can effectively predict COVID-19 prognosis which may assist ED physicians in their decision-making process.

Uncovering the Benefits of the Ketamine-Dexmedetomidine Combination for Procedural Sedation during the Italian COVID-19 Pandemic.

This retrospective observational study evaluated the safety and efficacy of the ketamine and dexmedetomidine combination (keta-dex) compared to ketamine or dexmedetomidine alone for sedation of patients with acute respiratory distress due to COVID-19 pneumonia who require non-invasive ventilation. The following factors were assessed: tolerance to the ventilation, sedation level on the Richmond Agitation-Sedation Scale (RASS), hemodynamic and saturation profile, adverse effects, and discontinuation or mortality during ventilation. The study included 66 patients who underwent sedation for non-invasive ventilation using keta-dex (KETA-DEX group, n = 22), ketamine (KET group, n = 22), or dexmedetomidine (DEX group, n = 22). The DEX group showed a slower sedation rate and a significant reduction in blood pressure compared to the KETA-DEX group (p < 0.05). An increase in blood pressure was recorded more frequently in the KET group. No reduction in oxygen saturation and no deaths were observed in any of the groups. None of the patients discontinued ventilation due to intolerance. The mean duration of sedation was 28.12 h. No cases of delirium were observed in any of the groups. Overall, keta-dex was associated with faster sedation rates and better hemodynamic profiles compared to dexmedetomidine alone. Keta-dex is effective and safe for sedation of uncooperative patients undergoing non-invasive ventilation.

Narrative Review: Low-Dose Ketamine for Pain Management.

Pain is the leading cause of medical consultations and occurs in 50-70% of emergency department visits. To date, several drugs have been used to manage pain. The clinical use of ketamine began in the 1960s and it immediately emerged as a manageable and safe drug for sedation and anesthesia. The analgesic properties of this drug were first reported shortly after its use; however, its psychomimetic effects have limited its use in emergency departments. Owing to the misuse and abuse of opioids in some countries worldwide, ketamine has become a versatile tool for sedation and analgesia. In this narrative review, ketamine's role as an analgesic is discussed, with both known and new applications in various contexts (acute, chronic, and neuropathic pain), along with its strengths and weaknesses, especially in terms of psychomimetic, cardiovascular, and hepatic effects. Moreover, new scientific evidence has been reviewed on the use of additional drugs with ketamine, such as magnesium infusion for improving analgesia and clonidine for treating psychomimetic symptoms. Finally, this narrative review was refined by the experience of the Pain Group of the Italian Society of Emergency Medicine (SIMEU) in treating acute and chronic pain with acute manifestations in Italian Emergency Departments.

A Hybrid Model for 30-Day Syncope Prognosis Prediction in the Emergency Department.

Syncope is a challenging problem in the emergency department (ED) as the available risk prediction tools have suboptimal predictive performances. Predictive models based on machine learning (ML) are promising tools whose application in the context of syncope remains underexplored. The aim of the present study was to develop and compare the performance of ML-based models in predicting the risk of clinically significant outcomes in patients presenting to the ED for syncope. We enrolled 266 consecutive patients (age 73, IQR 58-83; 52% males) admitted for syncope at three tertiary centers. We collected demographic and clinical information as well as the occurrence of clinically significant outcomes at a 30-day telephone follow-up. We implemented an XGBoost model based on the best-performing candidate predictors. Subsequently, we integrated the XGboost predictors with knowledge-based rules. The obtained hybrid model outperformed the XGboost model (AUC = 0.81 vs. 0.73, p < 0.001) with acceptable calibration. In conclusion, we developed an ML-based model characterized by a commendable capability to predict adverse events within 30 days post-syncope evaluation in the ED. This model relies solely on clinical data routinely collected during a patient's initial syncope evaluation, thus obviating the need for laboratory tests or syncope experienced clinical judgment.

Learning Analytics Applied to Clinical Diagnostic Reasoning Using a Natural Language Processing-Based Virtual Patient Simulator: Case Study.

BACKGROUND: Virtual patient simulators (VPSs) log all users' actions, thereby enabling the creation of a multidimensional representation of students' medical knowledge. This representation can be used to create metrics providing teachers with valuable learning information. OBJECTIVE: The aim of this study is to describe the metrics we developed to analyze the clinical diagnostic reasoning of medical students, provide examples of their application, and preliminarily validate these metrics on a class of undergraduate medical students. The metrics are computed from the data obtained through a novel VPS embedding natural language processing techniques. METHODS: A total of 2 clinical case simulations (tests) were created to test our metrics. During each simulation, the students' step-by-step actions were logged into the program database for offline analysis. The students' performance was divided into seven dimensions: the identification of relevant information in the given clinical scenario, history taking, physical examination, medical test ordering, diagnostic hypothesis setting, binary analysis fulfillment, and final diagnosis setting. Sensitivity (percentage of relevant information found) and precision (percentage of correct actions performed) metrics were computed for each issue and combined into a harmonic mean (F1), thereby obtaining a single score evaluating the students' performance. The 7 metrics were further grouped to reflect the students' capability to collect and to analyze information to obtain an overall performance score. A methodological score was computed based on the discordance between the diagnostic pathway followed by students and the reference one previously defined by the teacher. In total, 25 students attending the fifth year of the School of Medicine at Humanitas University underwent test 1, which simulated a patient with dyspnea. Test 2 dealt with abdominal pain and was attended by 36 students on a different day. For validation, we assessed the Spearman rank correlation between the performance on these scores and the score obtained by each student in the hematology curricular examination. RESULTS: The mean overall scores were consistent between test 1 (mean 0.59, SD 0.05) and test 2 (mean 0.54, SD 0.12). For each student, the overall performance was achieved through a different contribution in collecting and analyzing information. Methodological scores highlighted discordances between the reference diagnostic pattern previously set by the teacher and the one pursued by the student. No significant correlation was found between the VPS scores and hematology examination scores. CONCLUSIONS: Different components of the students' diagnostic process may be disentangled and quantified by appropriate metrics applied to students' actions recorded while addressing a virtual case. Such an approach may help teachers provide students with individualized feedback aimed at filling competence drawbacks and methodological inconsistencies. There was no correlation between the hematology curricular examination score and any of the proposed scores as these scores address different aspects of students' medical knowledge.

Effects of a cool classroom microclimate on cardiac autonomic control and cognitive performances in undergraduate students.

An inverted U-shape relationship between cognitive performance and indoor temperature with best performance peaking at 21.6 °C was previously described. Little is known on classroom temperature reduction effects on cognitive performances and cardiac autonomic profile, during the cold season. Fifteen students underwent electrocardiogram recording during a lecture in two days in December when classroom temperatures were set as neutral (NEUTRAL, 20-22 °C) and cool (COOL, 16-18 °C). Cognitive performance (memory, verbal ability, reasoning, overall cognitive C-score) was assessed by Cambridge Brain Science cognitive evaluation tool. Cardiac autonomic control was evaluated via the analysis of spontaneous fluctuations of heart period, as the temporal distance between two successive R-wave peaks (RR). Spectral analysis provided the power in the high frequency (HF, 0.15-0.40 Hz) and low frequency (LF, 0.04-0.15 Hz) bands of RR variability. Sympatho-vagal interaction was assessed by LF to HF ratio (LF/HF). Symbolic analysis provided the fraction of RR patterns composed by three heart periods with no variation (0 V%) and two variations (2 V%), taken as markers of cardiac sympathetic and vagal modulations, respectively. The students' thermal comfort was assessed during NEUTRAL and COOL trials. Classroom temperatures were 21.5 ± 0.8 °C and 18.4 ± 0.4 °C during NEUTRAL and COOL. Memory, verbal ability, C-Score were greater during COOL (13.01 ± 3.43, 12.32 ± 2.58, 14.29 ± 2.90) compared to NEUTRAL (9.98 ± 2.26, p = 0.002; 8.57 ± 1.07, p = 0.001 and 10.35 ± 3.20, p = 0.001). LF/HF (2.4 ± 1.7) and 0 V% (23.2 ± 11.1%) were lower during COOL compared to NEUTRAL (3.7 ± 2.8, p = 0.042; 28.1 ± 12.2.1%, p = 0.031). During COOL, 2 V% was greater (30.5 ± 10.9%) compared to NEUTRAL (26.2 ± 11.3, p = 0.047). The students' thermal comfort was slightly reduced during COOL compared to NEUTRAL trial. During cold season, a better cognitive performance was obtained in a cooler indoor setting enabling therefore energy saving too.

Transdermal auricular vagus stimulation for the treatment of postural tachycardia syndrome.

Postural Tachycardia Syndrome (POTS) is a chronic disorder characterized by symptoms of orthostatic intolerance such as fatigue, lightheadedness, dizziness, palpitations, dyspnea, chest discomfort and remarkable tachycardia upon standing. Non-invasive transdermal vagal stimulators have been applied for the treatment of epilepsy, anxiety, depression, headache, and chronic pain syndromes. Anti-inflammatory and immunomodulating effects after transdermal vagal stimulation raised interest for applications in other diseases. Patients with sympathetic overactivity, reduced cardiac vagal drive and presence of systemic inflammation like POTS may benefit from tVNS. This article will address crucial methodological aspects of tVNS and provide preliminary results of its acute and chronic use in POTS, with regards to its potential effectiveness on autonomic symptoms reduction and heart rate modulation.

Probiotic Bacterial Application in Pediatric Critical Illness as Coadjuvants of Therapy.

The use of probiotics in critically ill adult and children patients has been growing exponentially over the last 20 years. Numerous factors in pediatriac intensive care unit (PICU) patients may contribute to intestinal dysbiosis, which subsequently promotes the pathobiota's growth. Currently, lactobacillus and bifidobacterium species are mainly used to prevent the development of systemic diseases due to the subverted microbiome, followed by streptococcus, enterococcus, propionibacterium, bacillus and Escherichia coli, Lactobacillus rhamnosus GG, and Lactobacillus reuteri DSM 17938. The aim of this article is to review the scientific literature for further confirmation of the importance of the usage of probiotics in intensive care unit (ICU) patients, especially in the pediatric population. A progressive increase in nosocomial infections, especially nosocomial bloodstream infections, has been observed over the last 30 years. The World Health Organization (WHO) reported that the incidence of nosocomial infections in PICUs was still high and ranged between 5% and 10%. Petrof et al. was one of the first to demonstrate the efficacy of probiotics for preventing systemic diseases in ICU patients. Recently, however, the use of probiotics with different lactobacillus spp. has been shown to cause a decrease of pro-inflammatory cytokines and an increase in anti-inflammatory cytokines. In addition, in some studies, the use of probiotics, in particular the mix of Lactobacillus and Bifidobacterium reduces the incidence of ventilator-associated pneumonia (VAP) in PICU patients requiring mechanical ventilation. In abdominal infections, there is no doubt at all about the usefulness of using Lactobacillus spp probiotics, which help to treat ICU-acquired diarrhoea episodes as well as in positive blood culture for candida spp. Despite the importance of using probiotics being supported by various studies, their use is not yet part of the standard protocols to which all doctors must adhere. In the meantime, while waiting for protocols to be drawn up as soon as possible for use in PICUs, routine use could certainly stimulate the intestine's immune defences. Though it is still too early to say, they could be considered the drugs of the future.

Machine Learning and Syncope Management in the ED: The Future Is Coming.

In recent years, machine learning (ML) has been promisingly applied in many fields of clinical medicine, both for diagnosis and prognosis prediction. Aims of this narrative review were to summarize the basic concepts of ML applied to clinical medicine and explore its main applications in the emergency department (ED) setting, with a particular focus on syncope management. Through an extensive literature search in PubMed and Embase, we found increasing evidence suggesting that the use of ML algorithms can improve ED triage, diagnosis, and risk stratification of many diseases. However, the lacks of external validation and reliable diagnostic standards currently limit their implementation in clinical practice. Syncope represents a challenging problem for the emergency physician both because its diagnosis is not supported by specific tests and the available prognostic tools proved to be inefficient. ML algorithms have the potential to overcome these limitations and, in the future, they could support the clinician in managing syncope patients more efficiently. However, at present only few studies have addressed this issue, albeit with encouraging results.

A Natural Language Processing-Based Virtual Patient Simulator and Intelligent Tutoring System for the Clinical Diagnostic Process: Simulator Development and Case Study.

BACKGROUND: Shortage of human resources, increasing educational costs, and the need to keep social distances in response to the COVID-19 worldwide outbreak have prompted the necessity of clinical training methods designed for distance learning. Virtual patient simulators (VPSs) may partially meet these needs. Natural language processing (NLP) and intelligent tutoring systems (ITSs) may further enhance the educational impact of these simulators. OBJECTIVE: The goal of this study was to develop a VPS for clinical diagnostic reasoning that integrates interaction in natural language and an ITS. We also aimed to provide preliminary results of a short-term learning test administered on undergraduate students after use of the simulator. METHODS: We trained a Siamese long short-term memory network for anamnesis and NLP algorithms combined with Systematized Nomenclature of Medicine (SNOMED) ontology for diagnostic hypothesis generation. The ITS was structured on the concepts of knowledge, assessment, and learner models. To assess short-term learning changes, 15 undergraduate medical students underwent two identical tests, composed of multiple-choice questions, before and after performing a simulation by the virtual simulator. The test was made up of 22 questions; 11 of these were core questions that were specifically designed to evaluate clinical knowledge related to the simulated case. RESULTS: We developed a VPS called Hepius that allows students to gather clinical information from the patient's medical history, physical exam, and investigations and allows them to formulate a differential diagnosis by using natural language. Hepius is also an ITS that provides real-time step-by-step feedback to the student and suggests specific topics the student has to review to fill in potential knowledge gaps. Results from the short-term learning test showed an increase in both mean test score (P<.001) and mean score for core questions (P<.001) when comparing presimulation and postsimulation performance. CONCLUSIONS: By combining ITS and NLP technologies, Hepius may provide medical undergraduate students with a learning tool for training them in diagnostic reasoning. This may be particularly useful in a setting where students have restricted access to clinical wards, as is happening during the COVID-19 pandemic in many countries worldwide.

Relationships Between Cardiovascular Autonomic Profile and Work Ability in Patients With Pure Autonomic Failure.

Pure autonomic failure (PAF) is a rare disorder belonging to the group of synucleinopathies, characterized by autonomic nervous system degeneration. Severe orthostatic intolerance with recurrent syncope while standing are the two most disabling manifestations. Symptoms may start at middle age, thus affecting people at their working age. The aims of this study were to evaluate the autonomic and work ability impairment of a group of PAF patients and assess the relationships between cardiovascular autonomic control and work ability in these patients. Eleven PAF patients (age 57.3 ± 6.7 years), engaged in work activity, participated in the study. They completed the Composite Autonomic Symptom Score (COMPASS-31, range 0 no symptom-100 maximum symptom intensity) and Work Ability questionnaires (Work Ability Index, WAI, range 7-49; higher values indicate better work ability and lower values indicating unsatisfactory or jeopardized work ability). Electrocardiogram, blood pressure and respiratory activity were continuously recorded for 10 min while supine and during 75° head-up tilt (HUT). Autoregressive spectral analysis of cardiac cycle length approximated as the time distance between two consecutive R-wave peaks (RR) and systolic arterial pressure (SAP) variabilities provided the power in the high frequency (HF, 0.15-0.40 Hz) and low frequency (LF, 0.04-0.15 Hz) bands of RR and SAP variabilities. Cardiac sympatho-vagal interaction was assessed by LF to HF ratio (LF/HF), while the LF power of SAP (LFSAP) quantified the vascular sympathetic modulation. Changes in cardiovascular autonomic indexes induced by HUT were calculated as the delta (Δ) between HUT and supine resting positions. Spearman correlation analysis was applied. PAF patients were characterized by a moderate autonomic dysfunction (COMPASS-31 total score 47.08 ± 20.2) and by a reduction of work ability (WAI 26.88 ± 10.72). Direct significant correlations were found between WAI and ΔLFRR (r = 0.66, p = 0.03) and ΔLF/HFRR (r = 0.70, p = 0.02). Results indicate that patients who were better able to modulate heart rate, as revealed by a greater cardiac sympathetic increase and/or vagal withdrawal during the orthostatic stimulus, were those who reported higher values of WAI. This finding could be relevant to propose new strategies in the occupational environment to prevent early retirement or to extend the working life of these patients.

Psychogenic Pseudosyncope: Clinical Features, Diagnosis and Management.

Psychogenic Pseudosyncope (PPS) is the appearance of Transient Loss of Consciousness (TLOC) in which movements are absent, but there are no hemodynamic and electroencephalographic modifications as are induced by gravitational challenges which characterize syncope and true loss of consciousness. For younger and adult populations, a detailed history is crucial for the diagnosis. Clinical clues that should raise the suspicion for PPS include prolonged duration of the LOC, eye closure during the episode, unusual triggers, no recognizable prodromes and the high frequency of attacks. The presence of an established diagnosis of syncope should not deter from the concomitant diagnosis of PPS. The gold standard for a proper diagnosis of PPS is the documentation by a tilt test of normal hemodynamic and electroencephalographic parameters, when recorded during an attack. Treatment of PPS, based on the clear and empathetic communication of the diagnosis, can lead to an immediate reduction of attack frequency and lower the need to call on emergency services. Pharmacological treatment of associated psychiatric disorders and psychological interventions may be beneficial in patients with PPS. Cognitive-behavioural therapy holds the most reliable evidence of efficacy. In the present review, we aimed to address PPS with historical aspects, main clinical features and diagnostic tests, current diagnostic classification, underlying neurobiological abnormalities, management and therapy.

Work Ability Assessment and Its Relationship with Cardiovascular Autonomic Profile in Postural Orthostatic Tachycardia Syndrome.

Postural orthostatic tachycardia syndrome (POTS) negatively impacts quality of life. The excessive increase in cardiac sympathetic modulation during standing, which characterizes POTS patients, leads to many symptoms and signs of orthostatic intolerance. Little is known about the consequences of the disease on work performance and its relationship with individual autonomic profiles. Twenty-two POTS patients regularly engaged in working activity (20 females, age 36 ± 12 years) and 18 gender- and age-matched controls underwent a clinical evaluation and filled out the Work Ability Index (WAI) questionnaire. POTS patients completed the Composite Autonomic Symptom Score (COMPASS31) questionnaire, underwent continuous electrocardiogram, blood pressure and respiratory activity recordings while supine and during a 75° head-up tilt (HUT). A power spectrum analysis provided the index of cardiac sympatho-vagal balance (LF/HF). WAI scores were significantly reduced in POTS patients (29.84 ± 1.40) compared to controls (45.63 ± 0.53, p < 0.01). A significant inverse correlation was found between individual WAI and COMPASS31 scores (r = -0.46; p = 0.03), HUT increase in heart rate (r = -0.57; p = 0.01) and LF/HF (r = -0.55; p = 0.01). In POTS patients, the WAI scores were inversely correlated to the intensity of autonomic symptoms and to the excessive cardiac sympathetic activation induced by the gravitational stimulus.

Time Course of Autonomic Symptoms in Postural Orthostatic Tachycardia Syndrome (POTS) Patients: Two-Year Follow-Up Results.

Postural orthostatic tachycardia syndrome (POTS) is a multifactorial condition capable of chronically reducing the quality of life and the work ability of patients. The study aim was to assess the burden of autonomic symptoms in a cohort of POTS patients over 2 years. Patients' clinical profiles were assessed by the 31-item Composite Autonomic Symptom Score questionnaire (COMPASS 31) and a visual analog scale (VAS). One-way ANOVA for repeated measures followed by Dunnett's post-hoc test were used to compare symptoms at baseline and at 1 and 2 years. Out of 42 enrolled patients, 25 had a 1-year follow-up and 12 had a 2-year follow-up. At baseline, the reported burden of autonomic symptoms was high (overall COMPASS 31 = 49.9 ± 14.3 /100). Main complaints were related to orthostatic intolerance according to both COMPASS 31 and VAS. Fourteen patients were rendered inactive because of symptoms. At 1-year follow-up, a statistically significant improvement in pupillomotor function and overall score was detected by the COMPASS 31. These findings were confirmed at 2 years, together with a significant reduction in quality of life impairment, assessed by VAS. However, these improvements did not change patients' occupational status. Awareness of POTS diagnosis, patient monitoring, and tailored therapies can help to improve patients' condition.

Artificial Intelligence Algorithms and Natural Language Processing for the Recognition of Syncope Patients on Emergency Department Medical Records.

BACKGROUND: Enrollment of large cohorts of syncope patients from administrative data is crucial for proper risk stratification but is limited by the enormous amount of time required for manual revision of medical records. AIM: To develop a Natural Language Processing (NLP) algorithm to automatically identify syncope from Emergency Department (ED) electronic medical records (EMRs). METHODS: De-identified EMRs of all consecutive patients evaluated at Humanitas Research Hospital ED from 1 December 2013 to 31 March 2014 and from 1 December 2015 to 31 March 2016 were manually annotated to identify syncope. Records were combined in a single dataset and classified. The performance of combined multiple NLP feature selectors and classifiers was tested. Primary Outcomes: NLP algorithms' accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F3 score. RESULTS: 15,098 and 15,222 records from 2013 and 2015 datasets were analyzed. Syncope was present in 571 records. Normalized Gini Index feature selector combined with Support Vector Machines classifier obtained the best F3 value (84.0%), with 92.2% sensitivity and 47.4% positive predictive value. A 96% analysis time reduction was computed, compared with EMRs manual review. CONCLUSIONS: This artificial intelligence algorithm enabled the automatic identification of a large population of syncope patients using EMRs.