Durability of Pulmonary Vein Isolation Using Pulsed-Field Ablation: Results From the Multicenter EU-PORIA Registry.

BACKGROUND: Pulsed-field ablation (PFA) is a novel nonthermal ablation technology with high procedural safety and efficiency for pulmonary vein isolation (PVI). Premarket data showed high PVI durability during mandatory remapping studies. Data on lesion durability in real-world patients with clinically indicated redo procedures are scarce. OBJECTIVES: This study sought to report PVI durability rates in patients undergoing a clinically indicated redo procedure after an index PVI using PFA. METHODS: Patients from 7 European centers undergoing an index PVI using PFA were included the EU-PORIA (European Real-world Outcomes With Pulsed Field Ablation in Patients With Symptomatic Atrial Fibrillation) registry. In patients with subsequent left atrial redo procedures due to arrhythmia recurrence, 3-dimensional electroanatomical maps were acquired. PVI durability was assessed on a per-vein and per-patient level, and sites of reconnections and predictors of lesion durability were identified. RESULTS: Of 1,184 patients (62% paroxysmal atrial fibrillation) undergoing an index PVI using PFA, 272 (23%) had an arrhythmia recurrence. Of these, 144 (53%) underwent a left atrial redo procedure a median of 7 (Q1-Q3: 5-10) months after the first ablation. Three-dimensional electroanatomical maps identified 404 of 567 pulmonary veins (71%) with durable isolation. In 54 patients (38%), all pulmonary veins were durably isolated. Prior operator experience with cryoballoon ablation was associated with a higher PVI durability compared to operators with only point-by-point radiofrequency experience (76% vs 60%; P < 0.001). Neither the operators' cumulative experience in atrial fibrillation ablation (≤5 vs >5 years) nor the size of the PFA device used (31 mm vs 35 mm) had an impact on subsequent lesion durability (both P > 0.50). CONCLUSIONS: In 144 patients with arrhythmia recurrence after PFA PVI, durable isolation was observed in 71% of the pulmonary veins during the redo procedure, and 38% of all patients showed durable isolation of all veins.

Pulsed field ablation of the right superior pulmonary vein prevents vagal responses via anterior right ganglionated plexus modulation.

BACKGROUND: Pulsed field ablation (PFA) is selective for the myocardium. However, vagal responses and reversible effects on ganglionated plexi (GP) are observed during pulmonary vein isolation (PVI). Anterior-right GP ablation has been proven to effectively prevent vagal responses during radiofrequency-based PVI. OBJECTIVE: The purpose of this study was to test the hypothesis that PFA-induced transient anterior-right GP modulation when targeting the right superior pulmonary vein (RSPV) before any other pulmonary veins (PVs) may effectively prevent intraprocedural vagal responses. METHODS: Eighty consecutive paroxysmal atrial fibrillation patients undergoing PVI with PFA were prospectively included. In the first 40 patients, PVI was performed first targeting the left superior pulmonary vein (LSPV-first group). In the last 40 patients, RSPV was targeted first, followed by left PVs and right inferior PV (RSPV-first group). Heart rate (HR) and extracardiac vagal stimulation (ECVS) were evaluated at baseline, during PVI, and postablation to assess GP modulation. RESULTS: Vagal responses occurred in 31 patients (78%) in the LSPV-first group and 5 (13%) in the RSPV-first group (P <.001). Temporary pacing was needed in 14 patients (35%) in the LSPV-first group and 3 (8%) in the RSPV-first group (P = .003). RSPV isolation was associated with similar acute HR increase in the 2 groups (13 ± 11 bpm vs 15 ± 12 bpm; P = .3). No significant residual changes in HR or ECVS response were documented in both groups at the end of the procedure compared to baseline (all P >.05). CONCLUSION: PVI with PFA frequently induced vagal responses when initiated from the LSPV. Nevertheless, an RSPV-first approach promoted transient HR increase and reduced vagal response occurrence.

Case Report: A leadless and endovascular pacemaker teamwork.

Background: Cardiac Implantable Electronic Device infections increase short- and long-term mortality, along with healthcare costs. Leadless pacemakers (PM) were developed to overcome pocket- and minimize lead-related complications in selected high-risk patients. Recent advancements enable leadless devices to mechanically detect atrial activity, facilitating atrioventricular (AV) synchronous stimulation. Case summary: A 90-year-old woman, implanted with a dual-chamber pacemaker eight years ago due to sinus node dysfunction, presented with syncope. A diagnosis of complete AV block, in the setting of ventricular lead dysfunction was made. Due to a high risk of infection, the patient was implanted with a leadless PM capable of maintaining AV synchrony in VDD mode (MICRA™ model MC1AVR1). The transvenous PM was programmed to AAI-R mode to drive the atria, which, in turn, triggered the leadless PM to stimulate the ventricles. At six month follow-up, the AV synchrony rate was 85%. Conclusion: The combination of classic atrial pacing with leadless ventricular stimulation can be used in high-risk patients to reduce the risk of complications, in the setting of ventricular lead dysfunction. In this manner, AV synchrony can be maintained, improving hemodynamic parameters and quality of life. Low sinus rate variability at rest is essential to achieve a high AV synchrony rate in such cases.

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.

Temporal Trends in Pacemaker Implantations Over the Past Decade in France: Impact of Transcatheter Aortic Valve Implantations.

In this study, we assessed the temporal trends of permanent pacemaker implantations in France from 2008 to 2018 using data from the Échantillon Généraliste de Bénéficiaires (EGB) administrative database, a representative sample of the French population. Additionally, we evaluated the impact of transcatheter aortic valve implantations on the overall pacemaker implantation rate. Our data suggest that the incidence of permanent pacemaker implantations in France increased significantly only in patients ≥80 years old, with post-transcatheter aortic valve implantations accounting for at least 2/3 of this increase.

Artificial intelligence-assisted quantification of COVID-19 pneumonia burden from computed tomography improves prediction of adverse outcomes over visual scoring systems.

OBJECTIVE: We aimed to evaluate the effectiveness of utilizing artificial intelligence (AI) to quantify the extent of pneumonia from chest CT scans, and to determine its ability to predict clinical deterioration or mortality in patients admitted to the hospital with COVID-19 in comparison to semi-quantitative visual scoring systems. METHODS: A deep-learning algorithm was utilized to quantify the pneumonia burden, while semi-quantitative pneumonia severity scores were estimated through visual means. The primary outcome was clinical deterioration, the composite end point including admission to the intensive care unit, need for invasive mechanical ventilation, or vasopressor therapy, as well as in-hospital death. RESULTS: The final population comprised 743 patients (mean age 65  ±â€¯ 17 years, 55% men), of whom 175 (23.5%) experienced clinical deterioration or death. The area under the receiver operating characteristic curve (AUC) for predicting the primary outcome was significantly higher for AI-assisted quantitative pneumonia burden (0.739, p = 0.021) compared with the visual lobar severity score (0.711, p < 0.001) and visual segmental severity score (0.722, p = 0.042). AI-assisted pneumonia assessment exhibited lower performance when applied for calculation of the lobar severity score (AUC of 0.723, p = 0.021). Time taken for AI-assisted quantification of pneumonia burden was lower (38 ± 10 s) compared to that of visual lobar (328 ± 54 s, p < 0.001) and segmental (698 ± 147 s, p < 0.001) severity scores. CONCLUSION: Utilizing AI-assisted quantification of pneumonia burden from chest CT scans offers a more accurate prediction of clinical deterioration in patients with COVID-19 compared to semi-quantitative severity scores, while requiring only a fraction of the analysis time. ADVANCES IN KNOWLEDGE: Quantitative pneumonia burden assessed using AI demonstrated higher performance for predicting clinical deterioration compared to current semi-quantitative scoring systems. Such an AI system has the potential to be applied for image-based triage of COVID-19 patients in clinical practice.

A novel stepwise approach incorporating ethanol infusion in the vein of Marshall for the ablation of persistent atrial fibrillation.

Introduction: Apart from pulmonary vein isolation (PVI), several step-by-step procedures that aim to modify left atrial substrate have been proposed for the ablation of persistent atrial fibrillation (AF), yet the optimal strategy remains elusive. There are cumulative data suggesting an incremental benefit of adding vein of Marshall (VOM) ethanol infusion to PVI in patients with persistent AF. We sought to evaluate the feasibility and efficacy of a novel stepwise ablation approach, incorporating a VOM alcoholization step, for persistent AF. Methods: In this single-center study, we prospectively enrolled 66 consecutive patients with symptomatic persistent AF and failure of at least one antiarrhythmic drug (ADD). The ablation procedure consisted of (i) PVI, (ii) left atrial segmentation with VOM ethanol infusion and the deployment of linear radiofrequency lesions across the roof and the mitral isthmus and (iii) electrogram-based ablation of dispersion zones. The first two steps were performed in all patients, whereas the third step was carried out only in those still in AF at the end of the second step. Atrial tachycardias during the procedure were mapped and ablated. At the end of the procedure, cavotricuspid isthmus ablation was additionally performed in all patients. The primary endpoint was 12-month freedom from AF and atrial tachycardia after a single procedure and an initial three-month blanking period. Results: Total procedure time was 153 ± 38.5 min. Fluoroscopy time was 16 ± 6.5 min and the radiofrequency ablation time was 26.14 ± 0.26 min. The primary endpoint occurred in 54 patients (82%). At 12 months, 65% of patients were off any AAD. In the univariate Cox regression analysis, left ventricular ejection fraction < 40% was the only predictor of arrhythmia recurrence (HR 3.56; 95% CI, 1.04-12.19; p = 0.04). One patient developed a pericardial tamponade and another a minor groin hematoma. Conclusion: A novel stepwise approach, including a step of ethanol infusion in the VOM, is feasible, safe and provides a high rate of sinus rhythm maintenance at 12 months in patients with persistent AF.

EUropean real-world outcomes with Pulsed field ablatiOn in patients with symptomatic atRIAl fibrillation: lessons from the multi-centre EU-PORIA registry.

AIMS: Pulsed field ablation (PFA) is a new, non-thermal ablation modality for pulmonary vein (PV) isolation in patients with atrial fibrillation (AF). The multi-centre EUropean Real World Outcomes with Pulsed Field AblatiOn in Patients with Symptomatic AtRIAl Fibrillation (EU-PORIA) registry sought to determine the safety, efficacy, and learning curve characteristics for the pentaspline, multi-electrode PFA catheter. METHODS AND RESULTS: All-comer AF patients from seven high-volume centres were consecutively enrolled. Procedural and follow-up data were collected. Learning curve effects were analysed by operator ablation experience and primary ablation modality. In total, 1233 patients (61% male, mean age 66 ± 11years, 60% paroxysmal AF) were treated by 42 operators. In 169 patients (14%), additional lesions outside the PVs were performed, most commonly at the posterior wall (n = 127). Median procedure and fluoroscopy times were 58 (interquartile range: 40-87) and 14 (9-21) min, respectively, with no differences due to operator experience. Major complications occurred in 21/1233 procedures (1.7%) including pericardial tamponade (14; 1.1%) and transient ischaemic attack or stroke (n = 7; 0.6%), of which one was fatal. Prior cryoballoon users had less complication. At a median follow-up of 365 (323-386) days, the Kaplan-Meier estimate of arrhythmia-free survival was 74% (80% for paroxysmal and 66% for persistent AF). Freedom from arrhythmia was not influenced by operator experience. In 149 (12%) patients, a repeat procedure was performed due to AF recurrence and 418/584 (72%) PVs were durably isolated. CONCLUSION: The EU-PORIA registry demonstrates a high single-procedure success rate with an excellent safety profile and short procedure times in a real-world, all-comer AF patient population.

Catheter Ablation for Atrial Fibrillation in Structural Heart Disease: A Review.

Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice. Patients with structural heart disease (SHD) are at an increased risk of developing this arrhythmia and are particularly susceptible to the deleterious hemodynamic effects it carries. In the last two decades, catheter ablation (CA) has emerged as a valuable strategy for rhythm control and is currently part of the standard care for symptomatic relief in patients with AF. Growing evidence suggests that CA of AF may have potential benefits that extend beyond symptoms. In this review, we summarize the current knowledge of this intervention on SHD patients.

Outcomes after cryoballoon ablation of paroxysmal atrial fibrillation with the PolarX or the Arctic Front Advance Pro: a prospective multicentre experience.

AIMS: The aim of this study was to compare procedural efficacy and safety, including 1-year freedom from AF recurrence, between the novel cryoballoon system PolarX (Boston Scientific) and the Arctic Front Advance Pro (AFA-Pro) (Medtronic), in patients with paroxysmal AF undergoing PVI. METHODS AND RESULTS: This multicentre prospective observational study included 267 consecutive patients undergoing a first cryoablation procedure for paroxysmal AF (137 PolarX, 130 AFA-Pro). Kaplan-Meier curves with the log-rank test was used to compare the 1-year freedom from AF recurrence between both groups. Multivariate Cox model was performed to evaluate whether the type of procedure (PolarX vs. AFA-Pro) had an impact on the occurrence of AF recurrences after adjustment on potentially confounding factors. The PolarX reaches lower temperatures than the AFA-Pro (LSPV 52 ± 5, vs. 59 ± 6; LIPV 49 ± 6 vs. 56 ± 6; right superior pulmonary vein: 49 ± 6 vs. 57 ± 7; right inferior pulmonary vein: 52 ± 6 vs. 59 ± 6; P < 0.0001). A higher rate of transient phrenic nerve palsy was found in patients treated with the PolarX system (15% vs. 7%, P = 0.05). After a mean follow-up of 15 ± 5 months, 20 patients (15%) had recurrences in AFA-Pro group and 27 patients (19%) in PolarX group (P = 0.35). Based on survival analysis, no significant difference was observed between both groups with a 12-month free of recurrence survival of 91.2% (85.1-95.4%) vs. 83.7% (76.0%-89.1%) (log-rank test P = 0.11). In multivariate Cox model hazard ratio of recurrence for PolarX vs. AFA-Pro was not significant [HR = 1.6 (0.9-2.8), P = 0.12]. CONCLUSION: PolarX and AFA-Pro have comparable efficacy and safety profiles for pulmonary veins isolation in paroxysmal atrial fibrillation.

An accurate and time-efficient deep learning-based system for automated segmentation and reporting of cardiac magnetic resonance-detected ischemic scar.

BACKGROUND AND OBJECTIVES: Myocardial infarction scar (MIS) assessment by cardiac magnetic resonance provides prognostic information and guides patients' clinical management. However, MIS segmentation is time-consuming and not performed routinely. This study presents a deep-learning-based computational workflow for the segmentation of left ventricular (LV) MIS, for the first time performed on state-of-the-art dark-blood late gadolinium enhancement (DB-LGE) images, and the computation of MIS transmurality and extent. METHODS: DB-LGE short-axis images of consecutive patients with myocardial infarction were acquired at 1.5T in two centres between Jan 1, 2019, and June 1, 2021. Two convolutional neural network (CNN) models based on the U-Net architecture were trained to sequentially segment the LV and MIS, by processing an incoming series of DB-LGE images. A 5-fold cross-validation was performed to assess the performance of the models. Model outputs were compared respectively with manual (LV endo- and epicardial border) and semi-automated (MIS, 4-Standard Deviation technique) ground truth to assess the accuracy of the segmentation. An automated post-processing and reporting tool was developed, computing MIS extent (expressed as relative infarcted mass) and transmurality. RESULTS: The dataset included 1355 DB-LGE short-axis images from 144 patients (MIS in 942 images). High performance (> 0.85) as measured by the Intersection over Union metric was obtained for both the LV and MIS segmentations on the training sets. The performance for both LV and MIS segmentations was 0.83 on the test sets. Compared to the 4-Standard Deviation segmentation technique, our system was five times quicker (<1 min versus 7 ± 3 min), and required minimal user interaction. CONCLUSIONS: Our solution successfully addresses different issues related to automatic MIS segmentation, including accuracy, time-effectiveness, and the automatic generation of a clinical report.

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.

Pulsed electric field, cryoballoon, and radiofrequency for paroxysmal atrial fibrillation ablation: a propensity score-matched comparison.

AIMS: Pulsed field ablation (PFA) has emerged as a novel, non-thermal energy source to selectively ablate cardiac tissue. We describe a multicentre experience on pulmonary vein isolation (PVI) via the pentaspline Farapulse™ PFA system vs. thermal-based technologies in a propensity score-matched population of paroxysmal atrial fibrillation (PAF) patients. METHODS AND RESULTS: Propensity score matching was adopted to compare PVI-only ablation outcomes via the Farawave™ system (Group PFA), cryoballoon (Group CRYO), or focal radiofrequency (Group RF) (PFA:CRYO:RF ratio = 1:2:2). Among 1572 (mean age: 62.4 ± 11.3 years; 42.5% females) PAF patients undergoing first time PVI with either PFA (n = 174), CRYO (n = 655), or RF (n = 743), propensity score matching yielded 174 PFA, 348 CRYO, and 348 RF patients. First-pass isolation was achieved in 98.8% of pulmonary veins (PVs) with PFA, 81.5% with CRYO, and 73.1% with RF (P < 0.001). Procedural and dwell times were significantly shorter with PFA, whereas the availability of a 3D mapping system led to a significant reduction in X-ray exposure with RF. Overall complication rates were 3.4% (n = 6) with PFA, 8.6% (n = 30) with CRYO, and 5.5% (n = 19) with RF (P = 0.052). The 1-year Kaplan-Meier estimated freedom from any atrial tachyarrhythmia was 79.3% with PFA, 74.7% with CRYO, and 72.4% with RF (log-rank P-value: 0.24). Among 145 repeat ablation procedures, PV reconnection rate was 19.1% after PFA, 27.5% after CRYO, and 34.8% after RF (P = 0.01). CONCLUSION: Pulsed field ablation contributed to significantly shorter procedural times. Follow-up data showed a similar arrhythmia freedom, although a higher rate of PV reconnection was documented in post-CRYO and post-RF redo procedures.

Rapid quantification of COVID-19 pneumonia burden from computed tomography with convolutional long short-term memory networks.

Purpose: Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease 2019 (COVID-19) patients but are not part of clinical routine because the required manual segmentation of lung lesions is prohibitively time consuming. We aim to automatically segment ground-glass opacities and high opacities (comprising consolidation and pleural effusion). Approach: We propose a new fully automated deep-learning framework for fast multi-class segmentation of lung lesions in COVID-19 pneumonia from both contrast and non-contrast CT images using convolutional long short-term memory (ConvLSTM) networks. Utilizing the expert annotations, model training was performed using five-fold cross-validation to segment COVID-19 lesions. The performance of the method was evaluated on CT datasets from 197 patients with a positive reverse transcription polymerase chain reaction test result for SARS-CoV-2, 68 unseen test cases, and 695 independent controls. Results: Strong agreement between expert manual and automatic segmentation was obtained for lung lesions with a Dice score of 0.89 ± 0.07 ; excellent correlations of 0.93 and 0.98 for ground-glass opacity (GGO) and high opacity volumes, respectively, were obtained. In the external testing set of 68 patients, we observed a Dice score of 0.89 ± 0.06 as well as excellent correlations of 0.99 and 0.98 for GGO and high opacity volumes, respectively. Computations for a CT scan comprising 120 slices were performed under 3 s on a computer equipped with an NVIDIA TITAN RTX GPU. Diagnostically, the automated quantification of the lung burden % discriminate COVID-19 patients from controls with an area under the receiver operating curve of 0.96 (0.95-0.98). Conclusions: Our method allows for the rapid fully automated quantitative measurement of the pneumonia burden from CT, which can be used to rapidly assess the severity of COVID-19 pneumonia on chest CT.

When Outcomes Diverge: Age and Cardiovascular Risk as Determinants of Mortality and ICU Admission in COVID-19.

BACKGROUND: Hospital mortality and admission to the Intensive Care Unit (ICU) are markers of disease severity in COVID-19 patients. Cardiovascular co-morbidities are one of the main determinants of negative outcomes. In this study we investigated the impact of cardiovascular co-morbidities on mortality and admission to the ICU in first-wave COVID-19 patients. METHODS: A multicenter, retrospective, cohort study. A total of 1077 patients were analyzed for mortality and ICU admission. Cardiovascular risk factors were explored as determinants of the outcomes after correction for other confounders. RESULTS: In the multivariable model, after correction for age, only a history of heart failure remained independently associated (p = 0.0013) with mortality (hazard ratio 2.22, 95% confidence interval 1.37 to 3.62). Age showed a mortality risk increase of 8% per year (hazard ratio 1.08, 95% confidence interval 1.05 to 1.10, p = 0.001). The transition from ward to the ICU had, as a single determinant, the age, but in a reversed fashion (hazard ratio 0.96, 95% confidence interval 0.94 to 0.98, p = 0.0002). CONCLUSIONS: Once adjusted for the main determinant of mortality (age) heart failure only remained independently associated with mortality. Admission to the ICU was less likely for elderly patients. This may reflect the catastrophic impact of the first wave of COVID-19 pandemic in terms of ICU bed availability in Lombardy, leading to a selection process for ICU admission.

Impact of correcting the 2D PISA method on the quantification of functional tricuspid regurgitation severity.

AIMS: In functional tricuspid regurgitation (FTR) patients, tricuspid leaflet tethering and relatively low jet velocity could result in proximal flow geometry distortions that lead to underestimation of TR. Application of correction factors on two-dimensional (2D) proximal isovelocity surface area (PISA) equation may increase its reliability. This study sought to evaluate the impact of the corrected 2D PISA method in quantifying FTR severity. METHODS AND RESULTS: In 102 patients with FTR, we compared both conventional and corrected 2D PISA measurements of effective regurgitant orifice area [EROA vs. corrected (EROAc)] and regurgitant volume (RegVol vs. RegVolc) with those obtained by volumetric method (VM) using three-dimensional echocardiography (3DE), as reference. Both EROAc and RegVolc were larger than EROA (0.29 ± 0.26 vs. 0.22 ± 0.21 cm2; P < 0.001) and RegVol (24.5 ± 20 vs. 18.5 ± 14.25 mL; P < 0.001), respectively. Compared with VM, both EROAc and RegVolc resulted more accurate than EROA [bias = -0.04 cm2, limits of agreement (LOA) ± 0.02 cm2 vs. bias = -0.15 cm2, LOA ± 0.31 cm2] and RegVol (bias = -3.29 mL, LOA ± 2.19 mL vs. bias = -10.9 mL, LOA ± 13.5 mL). Using EROAc and RegVolc, 37% of patients were reclassified in higher grades of FTR severity. Corrected 2D PISA method led to a higher concordance of TR severity grade with the VM method (ĸ = 0.84 vs. ĸ = 0.33 for uncorrected PISA, P < 0.001). CONCLUSION: Compared with VM by 3DE, the conventional PISA underestimated FTR severity in about 50% of patients. Correction for TV leaflets tethering angle and lower velocity of FTR jet improved 2D PISA accuracy and reclassified more than one-third of the patients.

Changes in smell and taste perception related to COVID-19 infection: a case-control study.

The main aim of the present study was to psychophysically evaluate smell and taste functions in hospitalized COVID-19 patients and to compare those results with a group of healthy subjects. Another aim of the study was to assess the relationship of changes in patients' smell and taste functions with a number of clinical parameters, symptoms, and other physiological signs as well as with severity of disease. Olfactory and gustatory functions were tested in 61 hospitalized patients positive for SARS-CoV-2 infection and in a control group of 54 healthy individuals. Overall, we found a significant impairment of olfactory and gustatory functions in COVID-19 patients compared with the control group. Indeed, about 45% of patients self-reported complaints about or loss of either olfactory or gustatory functions. These results were confirmed by psychophysical testing, which showed a significantly reduced performance in terms of intensity perception and identification ability for both taste and smell functions in COVID-19 patients. Furthermore, gustatory and olfactory impairments tended to be more evident in male patients suffering from more severe respiratory failure (i.e., pneumonia with need of respiratory support need during hospitalization).

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.