Promises and Perils of Consumer Mobile Technologies in Cardiovascular Care: JACC Scientific Statement.

Direct-to-consumer (D2C) wearables are becoming increasingly popular in cardiovascular health management because of their affordability and capability to capture diverse health data. Wearables may enable continuous health care provider-patient partnerships and reduce the volume of episodic clinic-based care (thereby reducing health care costs). However, challenges arise from the unregulated use of these devices, including questionable data reliability, potential misinterpretation of information, unintended psychological impacts, and an influx of clinically nonactionable data that may overburden the health care system. Further, these technologies could exacerbate, rather than mitigate, health disparities. Experience with wearables in atrial fibrillation underscores these challenges. The prevalent use of D2C wearables necessitates a collaborative approach among stakeholders to ensure effective integration into cardiovascular care. Wearables are heralding innovative disease screening, diagnosis, and management paradigms, expanding therapeutic avenues, and anchoring personalized medicine.

Artificial intelligence-enabled mobile electrocardiograms for event prediction in paroxysmal atrial fibrillation.

Background: Paroxysmal atrial fibrillation (AF) often eludes early diagnosis, resulting in significant morbidity and mortality. Artificial intelligence (AI) has been used to predict AF from sinus rhythm electrocardiograms (ECGs), but AF prediction using sinus rhythm mobile electrocardiograms (mECG) remains unexplored. Objective: The purpose of this study was to investigate the utility of AI to predict AF events prospectively and retrospectively using sinus rhythm mECG data. Methods: We trained a neural network to predict AF events from sinus rhythm mECGs obtained from users of the Alivecor KardiaMobile 6L device. We tested our model on sinus rhythm mECGs within ±0-2 days, ±3-7 days, and ±8-30 days from AF events to determine the optimal screening window. Finally, we tested our model on mECGs from before an AF event to determine whether AF can be predicted prospectively. Results: We included 73,861 users with 267,614 mECGs (mean age 58.14 years; 35% women). Users with paroxysmal AF contributed 60.15% of mECGs. Model performance on the test set comprising control and study samples across all windows of interest showed an area under the curve (AUC) score of 0.760 (95% confidence interval [CI] 0.759-0.760), sensitivity of 0.703 (95% CI 0.700-0.705), specificity of 0.684 (95% CI 0.678-0.685), and accuracy of 69.4% (95% CI 0.692-0.700). Model performance was better on ±0-2 day samples (sensitivity 0.711; 95% CI 0.709-0.713) and worse on the ±8-30 day window (sensitivity 0.688; 95% CI 0.685-0.690), with performance on the ±3-7 day window falling in between (sensitivity 0.708; 95% CI 0.704-0.710). Conclusion: Neural networks can predict AF using a widely scalable and cost-effective mobile technology prospectively and retrospectively.

Elevated fibrosis burden as assessed by MRI predicts cryoballoon ablation failure.

INTRODUCTION: Late-gadolinium enhancement magnetic resonance (LGE-MRI) imaging is increasingly used in management of atrial fibrillation (AFib) patients. Here, we assess the usefulness of LGE-MRI-based fibrosis quantification to predict arrhythmia recurrence in patients undergoing cryoballoon ablation. Our secondary goal was to compare two widely used fibrosis quantification methods. METHODS: In 102 AF patients undergoing LGE-MRI and cryoballoon ablation (mean age 62 years; 64% male; 59% paroxysmal AFib), atrial fibrosis was quantified using the pixel intensity histogram (PIH) and image intensity ratio (IIR) methods. PIH segmentations were completed by a third-party provider as part of the standard of care at our hospital; Image intensity ratio (IIR) segmentations of the same scans were carried out in our lab using a commercially available software package. Fibrosis burdens and spatial distributions for the two methods were compared. Patients were followed prospectively for recurrent arrhythmia following ablation. RESULTS: Average PIH fibrosis was 15.6 ± 5.8% of the left atrial (LA) volume. Depending on threshold (IIRthr ), the average IIR fibrosis (% of LA wall surface area) ranged from 5.0 ± 7.2% (IIRthr = 1.2) to 37.4 ± 10.9% (IIRthr = 0.97). An IIRthr of 1.03 demonstrated the greatest agreement between the methods, but spatial overlap of fibrotic areas delineated by the two methods was modest (Sorenson Dice coefficient: 0.49). Fourty-two patients (41.2%) had recurrent arrhythmia. PIH fibrosis successfully predicted recurrence (HR 1.07; p = .02) over a follow-up period of 362 ± 149 days; regardless of IIRthr , IIR fibrosis did not predict recurrence. CONCLUSIONS: PIH-based volumetric assessment of atrial fibrosis was modestly predictive of arrhythmia recurrence following cryoballoon ablation in this cohort. IIR-based fibrosis was not predictive of recurrence for any of the IIRthr values tested, and the overlap in designated areas of fibrosis between the PIH and IIR methods was modest. Caution must therefore be exercised when interpreting LA fibrosis from LGE-MRI, since the values and spatial pattern are methodology-dependent.

Identifying risk of adverse outcomes in COVID-19 patients via artificial intelligence-powered analysis of 12-lead intake electrocardiogram.

BACKGROUND: Adverse events in COVID-19 are difficult to predict. Risk stratification is encumbered by the need to protect healthcare workers. We hypothesize that artificial intelligence (AI) can help identify subtle signs of myocardial involvement in the 12-lead electrocardiogram (ECG), which could help predict complications. OBJECTIVE: Use intake ECGs from COVID-19 patients to train AI models to predict risk of mortality or major adverse cardiovascular events (MACE). METHODS: We studied intake ECGs from 1448 COVID-19 patients (60.5% male, aged 63.4 ± 16.9 years). Records were labeled by mortality (death vs discharge) or MACE (no events vs arrhythmic, heart failure [HF], or thromboembolic [TE] events), then used to train AI models; these were compared to conventional regression models developed using demographic and comorbidity data. RESULTS: A total of 245 (17.7%) patients died (67.3% male, aged 74.5 ± 14.4 years); 352 (24.4%) experienced at least 1 MACE (119 arrhythmic, 107 HF, 130 TE). AI models predicted mortality and MACE with area under the curve (AUC) values of 0.60 ± 0.05 and 0.55 ± 0.07, respectively; these were comparable to AUC values for conventional models (0.73 ± 0.07 and 0.65 ± 0.10). There were no prominent temporal trends in mortality rate or MACE incidence in our cohort; holdout testing with data from after a cutoff date (June 9, 2020) did not degrade model performance. CONCLUSION: Using intake ECGs alone, our AI models had limited ability to predict hospitalized COVID-19 patients' risk of mortality or MACE. Our models' accuracy was comparable to that of conventional models built using more in-depth information, but translation to clinical use would require higher sensitivity and positive predictive value. In the future, we hope that mixed-input AI models utilizing both ECG and clinical data may be developed to enhance predictive accuracy.

Significance of electrical activity in the right superior pulmonary vein post-isolation and relationship to superior vena cava potentials.

PURPOSE: After antral pulmonary vein isolation (PVI), electrical potentials may persist deep in the right superior pulmonary vein (RSPV). Whether these potentials signify true pulmonary vein potential (PVP) (implying inadequate RSPV isolation) or are far-field potentials (FFP) from the superior vena cava (SVC) is unclear. Here, we attempt to assess the incidence of persistent potentials in RSPV post-isolation and methods to differentiate PVP from FFP. METHODS: Following PVI, we mapped the RSPV and the SVC with simultaneously placed catheters. We recorded the incidence of SVC potentials, RSPV potentials, and distance between the 2 structures. When RSPV potentials were present, we assessed (1) relationship to SVC potentials, (2) RSPV-SVC distance, and (3) responses on pacing from either site. RESULTS: Among 43 consecutive post-PVI patients, 39 (91%) patients had SVC electrical activity but only 10 had persistent RSPV potentials. Of these, 2/10 had true PVP, and 8 were FFP from SVC. Bipolar electrogram morphology did not differentiate PVP from FFP, but low-amplitude (5 mA) SVC pacing was an effective maneuver. However, high-amplitude (≥ 10 mA) pacing from SVC and/or RSPV could result in far-field capture of the other site even when RSPV was devoid of electrical activity. Average RSPV-SVC distance was 15.9 mm. CONCLUSIONS: Persistent RSPV potentials occur rarely post-PVI despite the close proximity to electrically active SVC. When present, true PVP can be differentiated from FFP by low-amplitude pacing from SVC. Bipolar EGM morphology and high-amplitude pacing are unreliable at differentiating these potentials.

Catheter ablation of atrial fibrillation results in significant QTc prolongation in the postoperative period.

BACKGROUND: The corrected QT interval (QTc) is a measure of ventricular repolarization time, and a prolonged QTc increases risk for malignant ventricular arrhythmias. Pulmonary vein isolation (PVI) may increase QTc but its effects have not been well studied. OBJECTIVE: Determine the incidence, risk factors, and outcomes of patients presenting for PVI in sinus and atrial fibrillation with postoperative QTc prolongation in a large cohort. METHODS: We performed a single-center retrospective study of consecutive atrial fibrillation ablations. QTc durations using Bazett correction were obtained from electrocardiograms at different postoperative intervals and compared to preoperative QTc. We studied clinical outcomes including clinically significant ventricular arrhythmia and death. A multivariable model was used to identify factors associated with clinically significant QTc prolongation, defined as ΔQTc ≥60 ms or new QTc duration ≥500 ms. RESULTS: A total of 352 PVIs were included in this study. We observed a statistically significant increase in mean QTc compared to baseline (446.3 ± 37.8 ms) on postoperative day (POD)0 (471.7 ± 38.2 ms, P < .001) and at POD1 (456.5 ± 35.0 ms, P < .001). There was no significant difference at 1 month (452.4 ± 33.5 ms, P = .39) and 3 months (447.3 ± 40.0 ms, P = .78). Sixty-six patients (19.2%) developed ΔQTc ≥60 ms or QTc ≥500 ms on POD0, with 4.1% persisting past 90 days. Female sex (odds ratio [OR] = 1.82, 95% confidence interval [CI] =1.01-3.29, P = .047) and history of coronary artery disease (OR = 2.16, 95% CI = 1.03-4.55, P = .042) were independently predictive of QTc prolongation ≥500 ms or ΔQTc ≥60 ms. There were no episodes of clinically significant ventricular arrhythmia or death attributable to arrhythmia. CONCLUSION: QTc duration increased significantly immediately post-PVI and returned to baseline by 1 month. PVI did not provoke significant ventricular arrhythmias in our cohort.

Rapid Exclusion of COVID Infection With the Artificial Intelligence Electrocardiogram.

OBJECTIVE: To rapidly exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using artificial intelligence applied to the electrocardiogram (ECG). METHODS: A global, volunteer consortium from 4 continents identified patients with ECGs obtained around the time of polymerase chain reaction-confirmed COVID-19 diagnosis and age- and sex-matched controls from the same sites. Clinical characteristics, polymerase chain reaction results, and raw electrocardiographic data were collected. A convolutional neural network was trained using 26,153 ECGs (33.2% COVID positive), validated with 3826 ECGs (33.3% positive), and tested on 7870 ECGs not included in other sets (32.7% positive). Performance under different prevalence values was tested by adding control ECGs from a single high-volume site. RESULTS: The area under the curve for detection of acute COVID-19 infection in the test group was 0.767 (95% CI, 0.756 to 0.778; sensitivity, 98%; specificity, 10%; positive predictive value, 37%; negative predictive value, 91%). To more accurately reflect a real-world population, 50,905 normal controls were added to adjust the COVID prevalence to approximately 5% (2657/58,555), resulting in an area under the curve of 0.780 (95% CI, 0.771 to 0.790) with a specificity of 12.1% and a negative predictive value of 99.2%. CONCLUSION: Infection with SARS-CoV-2 results in electrocardiographic changes that permit the artificial intelligence-enhanced ECG to be used as a rapid screening test with a high negative predictive value (99.2%). This may permit the development of electrocardiography-based tools to rapidly screen individuals for pandemic control.

Using smart speakers to contactlessly monitor heart rhythms.

Heart rhythm assessment is indispensable in diagnosis and management of many cardiac conditions and to study heart rate variability in healthy individuals. We present a proof-of-concept system for acquiring individual heart beats using smart speakers in a fully contact-free manner. Our algorithms transform the smart speaker into a short-range active sonar system and measure heart rate and inter-beat intervals (R-R intervals) for both regular and irregular rhythms. The smart speaker emits inaudible 18-22 kHz sound and receives echoes reflected from the human body that encode sub-mm displacements due to heart beats. We conducted a clinical study with both healthy participants and hospitalized cardiac patients with diverse structural and arrhythmic cardiac abnormalities including atrial fibrillation, flutter and congestive heart failure. Compared to electrocardiogram (ECG) data, our system computed R-R intervals for healthy participants with a median error of 28 ms over 12,280 heart beats and a correlation coefficient of 0.929. For hospitalized cardiac patients, the median error was 30 ms over 5639 heart beats with a correlation coefficient of 0.901. The increasing adoption of smart speakers in hospitals and homes may provide a means to realize the potential of our non-contact cardiac rhythm monitoring system for monitoring of contagious or quarantined patients, skin sensitive patients and in telemedicine settings.

Hydroxychloroquine with or without azithromycin for treatment of early SARS-CoV-2 infection among high-risk outpatient adults: A randomized clinical trial.

BACKGROUND: Treatment options for outpatients with COVID-19 could reduce morbidity and prevent SARS-CoV-2 transmission. METHODS: In this randomized, double-blind, three-arm (1:1:1) placebo-equivalent controlled trial conducted remotely throughout the United States, adult outpatients with laboratory-confirmed SARS-CoV-2 infection were recruited. Participants were randomly assigned to receive hydroxychloroquine (HCQ) (400 mg BID x1day, followed by 200 mg BID x9days) with or without azithromycin (AZ) (500 mg, then 250 mg daily x4days) or placebo-equivalent (ascorbic acid (HCQ) and folic acid (AZ)), stratified by risk for progression to severe COVID-19 (high-risk vs. low-risk). Self-collected nasal swabs for SARS-CoV-2 PCR, FLUPro symptom surveys, EKGs and vital signs were collected daily. Primary endpoints were: (a) 14-day progression to lower respiratory tract infection (LRTI), 28-day COVID-19 related hospitalization, or death; (b) 14-day time to viral clearance; secondary endpoints included time to symptom resolution (ClinicalTrials.gov: NCT04354428). Due to the low rate of clinical outcomes, the study was terminated for operational futility. FINDINGS: Between 15th April and 27th July 2020, 231 participants were enrolled and 219 initiated medication a median of 5.9 days after symptom onset. Among 129 high-risk participants, incident LRTI occurred in six (4.7%) participants (two control, four HCQ/AZ) and COVID-19 related hospitalization in seven (5.4%) (four control, one HCQ, two HCQ/AZ); no LRTI and two (2%) hospitalizations occurred in the 102 low-risk participants (one HCQ, one HCQ/AZ). There were no deaths. Among 152 participants with viral shedding at enrollment, median time to clearance was 5 days (95% CI=4-6) in HCQ, 6 days (95% CI=4-8) in HCQ/AZ, and 8 days (95% CI=6-10) in control. Viral clearance was faster in HCQ (HR=1.62, 95% CI=1.01-2.60, p = 0.047) but not HCQ/AZ (HR=1.25, p = 0.39) compared to control. Among 197 participants who met the COVID-19 definition at enrollment, time to symptom resolution did not differ by group (HCQ: HR=1.02, 95% CI-0.63-1.64, p = 0.95, HCQ/AZ: HR=0.91, 95% CI=0.57-1.45, p = 0.70). INTERPRETATION: Neither HCQ nor HCQ/AZ shortened the clinical course of outpatients with COVID-19, and HCQ, but not HCQ/AZ, had only a modest effect on SARS-CoV-2 viral shedding. HCQ and HCQ/AZ are not effective therapies for outpatient treatment of SARV-CoV-2 infection. FUNDING: The COVID-19 Early Treatment Study was funded by the Bill & Melinda Gates Foundation (INV-017062) through the COVID-19 Therapeutics Accelerator. University of Washington Institute of Translational Health Science (ITHS) grant support (UL1 TR002319), KL2 TR002317, and TL1 TR002318 from NCATS/NIH funded REDCap. The content is solely the responsibility of the authors and does not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated. PAN and MJA were supported by the Mayo Clinic Windland Smith Rice Comprehensive Sudden Cardiac Death Program.Trial registration ClinicalTrials.gov number NCT04354428.

Implementation of a fully remote randomized clinical trial with cardiac monitoring.

Background: The coronavirus disease 2019 (COVID-19) pandemic has challenged researchers performing clinical trials to develop innovative approaches to mitigate infectious risk while maintaining rigorous safety monitoring. Methods: In this report we describe the implementation of a novel exclusively remote randomized clinical trial (ClinicalTrials.gov NCT04354428) of hydroxychloroquine and azithromycin for the treatment of the SARS-CoV-2-mediated COVID-19 disease which included cardiovascular safety monitoring. All study activities were conducted remotely. Self-collected vital signs (temperature, respiratory rate, heart rate, and oxygen saturation) and electrocardiographic (ECG) measurements were transmitted digitally to investigators while mid-nasal swabs for SARS-CoV-2 testing were shipped. ECG collection relied on a consumer device (KardiaMobile 6L, AliveCor Inc.) that recorded and transmitted six-lead ECGs via participants' internet-enabled devices to a central core laboratory, which measured and reported QTc intervals that were then used to monitor safety. Results: Two hundred and thirty-one participants uploaded 3245 ECGs. Mean daily adherence to the ECG protocol was 85.2% and was similar to the survey and mid-nasal swab elements of the study. Adherence rates did not differ by age or sex assigned at birth and were high across all reported race and ethnicities. QTc prolongation meeting criteria for an adverse event occurred in 28 (12.1%) participants, with 2 occurring in the placebo group, 19 in the hydroxychloroquine group, and 7 in the hydroxychloroquine + azithromycin group. Conclusions: Our report demonstrates that digital health technologies can be leveraged to conduct rigorous, safe, and entirely remote clinical trials.

Dynamic voltage threshold adjusted substrate modification technique for complex atypical atrial flutters with varying circuits.

BACKGROUND: Atypical atrial flutter (AFL) is common in patients with postsurgical atrial scar, with macro- or microscopic channels in the scar acting as substrate for reentry. Heterogeneous atrial scarring can cause varying flutter circuits, which makes mapping and ablation challenging, and recurrences common. AIM: We hypothesize that dynamically adjusting voltage thresholds can identify heterogeneous atrial scarring, which can then be effectively homogenized to eliminate atypical AFLs. METHODS: We studied consecutive patients who presented to Electrophysiology laboratory for atypical AFL ablation with history of atriotomy and included the patients with multiple, varying flutter circuits during mapping in our study. We excluded patients with stable flutter circuit that was sustained and could be localized using traditional entrainment and activation mapping strategy. In the included patients, we performed detailed high-density voltage map of the atrium of interest. We adjusted voltage thresholds as needed to identify heterogeneity and channels in the scarred regions. A thorough scar homogenization was performed with irrigated smart-touch ablation catheter. Re-inducibility of tachycardia, and immediate and long-term outcomes were studied. RESULTS: Of five studied cases, one was female; age 66 ± 10 years. All five had prior surgical substrate. All the patients had multiple flutter morphologies, which varied as we mapped the AFL. After scar homogenization, tachycardia was not inducible in any patient. No recurrence of flutter was noted during a mean follow-up duration of 450 ± 27 days. CONCLUSION: High-density voltage mapping and homogenization of the scar can be an effective strategy in eliminating complex scar-mediated atypical AFL with multiple circuits.

QT interval and arrhythmic safety of hydroxychloroquine monotherapy in coronavirus disease 2019.

BACKGROUND: Observational studies have suggested increased arrhythmic and cardiovascular risk with the combination use of hydroxychloroquine (HCQ) and azithromycin in patients with coronavirus disease 2019 (COVID-19). OBJECTIVE: The arrhythmic safety profile of HCQ monotherapy, which remains under investigation as a therapeutic and prophylactic agent in COVID-19, is less established and we sought to evaluate this. METHODS: In 245 consecutive patients with COVID-19 admitted to the University of Washington hospital system between March 9, 2020, and May 10, 2020, we identified 111 treated with HCQ monotherapy. Patients treated with HCQ underwent a systematic arrhythmia and QT interval surveillance protocol including serial electrocardiograms (ECG) (baseline, following second HCQ dose). The primary endpoint was in-hospital sustained ventricular arrhythmia or arrhythmic cardiac arrest. Secondary endpoints included clinically significant QTc prolongation. RESULTS: A total of 111 patients with COVID-19 underwent treatment with HCQ monotherapy (mean age 62 ± 16 years, 44 women [39%], serum creatinine 0.9 [interquartile range 0.4] mg/dL). There were no instances of sustained ventricular arrythmia or arrhythmic cardiac arrest. In 75 patients with serial ECGs, clinically significant corrected QT (QTc) prolongation was observed in a minority (n = 5 [7%]). In patients with serial ECGs, there was no significant change in the QTc interval in prespecified subgroups of interest, including those with prevalent cardiovascular disease or baseline use of renin-angiotensin-aldosterone axis inhibitors. CONCLUSIONS: In the context of a systematic monitoring protocol, HCQ monotherapy in hospitalized COVID-19 patients was not associated with malignant ventricular arrhythmia. A minority of patients demonstrated clinically significant QTc prolongation during HCQ therapy.

Esophageal Thermal Injury Following Cryoballoon Ablation for Atrial Fibrillation.

OBJECTIVES: This study evaluated the rate and predictors of endoscopically detected esophageal thermal lesions (EDEL) in patients who underwent cryoballoon atrial fibrillation (AF) ablation (CBA). BACKGROUND: EDEL is a known complication of catheter ablation for AF and is the inciting factor for atrial esophageal fistula formation. METHODS: An observational study was conducted of patients with AF presenting for CBA. Pre-procedural magnetic resonance imaging was used to retrospectively evaluate the distance between the atrial endocardium and the esophageal lumen (AED). Intraprocedural esophageal luminal temperature and balloon temperatures were recorded. All patients underwent upper endoscopy (EGD) 24 h post-ablation. Clinical, anatomical, and ablation parameters were analyzed using logistic regression for association with thermal injury. RESULTS: A total of 95 patients (37% women; 71% paroxysmal AF) were included in the study. Esophageal thermal injury was detected on EGD in 21 patients (22%). EDEL was mostly mild (20 of 21 patients) and severe in only 1 of 21 patients. Univariate logistic regression identified gastroesophageal reflux disease to be associated with increased risk of thermal injury (odds ratio [OR]: 3.2; 95% confidence interval [CI]: 1.00 to 10.46; p = 0.04), whereas a wider AED was protective (OR: 0.16; 95% CI: 0.05 to 0.515; p = 0.002). Esophageal wall thickness was also protective (OR: 0.04; 95% CI: 0.002 to 0.864; p = 0.04). In multivariate analysis, only AED (OR: 0.22; 95% CI: 0.06 to 0.77; p = 0.018) and obesity (OR: 4.63; 95% CI: 1.13 to 18.97; p = 0.033) were associated with EDEL. Esophageal luminal temperature, number, and duration of cryoballoon applications and balloon temperature were not predictors of EDEL. CONCLUSIONS: EDEL following CBA occurred in 22% of patients and was mostly mild. Obesity and atrioesophageal distance were independently associated with increased risk.

Ablation of atrial fibrillation: Facts for the referring physician.

Radiofrequency ablation has become a safe and effective treatment for atrial fibrillation. We believe that referral to an electrophysiologist for consideration of ablation may allow for better rhythm control and outcomes by altering the natural history of atrial fibrillation progression.

Scholarship opportunities for trainees and clinician educators: learning outcomes from a case report writing workshop.

INTRODUCTION: Publishing a case report demonstrates scholarly productivity for trainees and clinician-educators. AIM: To assess the learning outcomes from a case report writing workshop. SETTING: Medical students, residents, fellows and clinician-educators attending a workshop. PROGRAM DESCRIPTION: Case report writing workshop conducted nine times at different venues. PROGRAM EVALUATION: Before and after each workshop, participants self-rated their perceived competence to write a case report, likelihood of submitting a case report to a meeting or for publication in the next 6-12 months, and perceived career benefit of writing a case report (on a five-point Likert scale). The 214 participants were from 3 countries and 27 states or provinces; most participants were trainees (64.5 %). Self-rated competence for writing a case report improved from a mean of 2.5 to 3.5 (a 0.99 increase; 95% CI, 0.88-1.12, p < 0.001). The perceived likelihood of submitting a case report, and the perceived career benefit of writing one, also showed statistically significant improvements (p = 0.002, p = 0.001; respectively). Nine of 98 participants published a case report 16-41 months after workshop completion. DISCUSSION: The workshop increased participants' perception that they could present or publish a case report.