Left atrial appendage morphology predicts the formation of left atrial appendage thrombus.

BACKGROUND: Nonchicken wing left atrial appendage (LAA) morphology is associated with higher risk for stroke in patients with atrial fibrillation (AF) than chicken wing (CW) morphology. OBJECTIVE: Assess whether LAA morphology predicts the formation of LAA thrombus independent of age, sex, presenting rhythm, left ventricular ejection fraction (LVEF), or anticoagulant use. METHODS: A cross-sectional analysis was performed on patients prospectively enrolled in the Vanderbilt LAA Registry or presenting for transesophageal echocardiogram (TEE) between January 1, 2015, and November 1, 2017 (n = 306). Two physicians independently reviewed TEEs interpreted as having LAA thrombus. Determination of LAA morphology, ejection velocity, and presence of thrombus (n = 102) were based on 0°, 45°, 90°, and 135° TEE views. The control cohort (n = 204) included consecutive AF patients undergoing TEE without LAA thrombus. RESULTS: LAA morphology in patients with LAA thrombus was: 35% windsock, 47% broccoli, and 12% CW. Windsock (odds ratio [OR], 4.0; 95% confidence interval [CI]: 1.7-9.3, p = .001) and broccoli (OR, 6.6; 95% CI: 2.6-16.6; p < .001) morphology were higher risk for thrombus compared to CW. Female sex predicted higher-odds for LAA thrombus (OR, 2.6; 95% CI: 1.4-4.8; p = .002) as did LAA-EV < 20 cm/s (OR, 11.12; 95% CI: 5.6-22.1). Anticoagulation use (OR, 0.5; 95% CI: 0.3-0.9; p = .03) and higher LVEF (OR, 0.95; 95% CI: 0.93-0.98; p < .001) were associated with lower risk. In patients with a CW morphology who had LAA thrombus, 4 of the 7 had an LAA-EV < 20 cm/s and acute systolic heart failure with LVEF < 30% or active malignancy. In multivariable linear regression analysis controlling for presenting rhythm, anticoagulant use, age, sex, and LVEF, CW morphology appears relatively protective from LAA thrombus (p = .001). CONCLUSION: CW LAA morphology appears relatively protective against the formation of LAA thrombus.

Use of a clot aspiration system during transvenous lead extraction.

INTRODUCTION: The optimal approach to the extraction of leads with large vegetations remains uncertain. METHODS: High-risk patients with lead associated vegetations undergoing device extraction at Vanderbilt Hospital with concomitant use of the Penumbra Aspiration System (Penumbra Inc, Alameda, CA) are described. An 8.5 Fr Agilis NXT (Abbott Inc, St. Paul, MN) was advanced to the right atrium, through which a Penumbra Indigo Cat-8 catheter was advanced. Using intracardiac echocardiography, the Penumbra was positioned directly on the vegetation, suction was applied until adherent, and the Indigo catheter and Agilis sheath were then removed en-bloc and aspirated debris flushed out. This was repeated until debulking was considered successful. RESULTS: Eight cases were performed. The median vegetation size was 2 cm. Pathogens were Enterococcus, Staphylococcus, Candida, Cutibacterium, and Enterobacter. In seven of eight cases, aspiration successfully reduced vegetations to less than 1 cm before successful percutaneous cardiac implantable electronic device removal. One patient underwent surgical removal via thoracotomy. There were no acute complications related to the Penumbra catheter. Three patients had CT evidence of small pulmonary emboli postprocedure. The length of stay was 3 to 27 days. One patient died on POD 1 of refractory ventricular tachycardia unrelated to the procedure. One patient died of ongoing sepsis 2 weeks postextraction. CONCLUSIONS: The Penumbra Indigo Aspiration system can be useful for vegetation debulking before transvenous lead extraction.

Catheter ablation for atrial fibrillation can be safely performed without invasive hemodynamic monitoring: A multi-center study.

BACKGROUND: Arterial invasive monitoring is the most common method in the USA for hemodynamic monitoring during atrial fibrillation (AF) ablation. Although studies have shown favorable comparison between non-invasive and invasive hemodynamic monitoring (IHM) in non-cardiac procedures under general anesthesia, limited data is available for complex cardiac procedures such as AF ablation in the USA. With progressive improvement in AF ablation procedural safety, particularly with routine use of intracardiac echocardiography (ICE) to monitor for pericardial effusion, it is unclear if invasive hemodynamic monitoring provides any advantage over non-invasive methods. Therefore, the purpose of this study is to determine whether noninvasive hemodynamic monitoring is non-inferior to invasive hemodynamic monitoring during AF ablation under general anesthesia in patients without major cardiac structural abnormality. METHODS: A multi-center retrospective data of AF ablation from July 2019 to December 2020 was extracted. A total of three hundred and sixty-two patients (362) were included, which were divided into group A (non-invasive hemodynamic monitoring) and group B (invasive hemodynamic monitoring). The primary outcome was to compare procedural safety between the two groups. RESULTS: Out of 362 patients, 184 (51%) received non-invasive and 178 (49%) received invasive hemodynamic monitoring with similar baseline characteristics. There was no significant difference between the two groups in complication rates (groin hematoma, pericardial effusion, cardiac tamponade). Mean procedure time was longer in group B with 3.35% arterial site discomfort. Urgent arterial access was required in only 1 patient in group A. CONCLUSION: This retrospective multicenter study strongly suggests that catheter ablation for atrial fibrillation under general anesthesia can be safely performed with noninvasive hemodynamic monitoring without requiring arterial access, with potential benefit in procedural duration and cost.

Natural Language Processing to Assess Documentation of Features of Critical Illness in Discharge Documents of Acute Respiratory Distress Syndrome Survivors.

RATIONALE: Transitions to outpatient care are crucial after critical illness, but the documentation practices in discharge documents after critical illness are unknown. OBJECTIVES: To characterize the rates of documentation of various features of critical illness in discharge documents of patients diagnosed with acute respiratory distress syndrome (ARDS) during their hospital stay. METHODS: We used natural language processing tools to build a keyword-based classifier that categorizes discharge documents by presence of terms from four groups of keywords related to critical illness. We used a multivariable modified Poisson regression model to infer patient- and hospital-level characteristics associated with documentation of relevant keywords. A manual chart review was used to validate the accuracy of the keyword-based classifier, and to assess for ARDS documentation during the hospital stay. MEASUREMENTS AND MAIN RESULTS: Of 815 discharge documents, ARDS was identified in only 111 (13%). Mechanical ventilation was identified in 770 (92%) and intensive care unit (ICU) admission in 693 (83%) of discharge documents. Symptoms or recommendations related to post-intensive care syndrome were included in 306 (38%) of discharge documents. Patient age (older; relative risk [RR] = 0.97/yr, 95% confidence interval [CI] = 0.96-0.98) and higher PaO2:FiO2 (decreasing illness severity; RR = 0.96/10-unit increment, 95% CI = 0.93-0.98) were associated with decreased documentation of ARDS. Being discharged from a surgical (RR = 0.33, 95% CI = 0.22-0.50) compared with a medicine service was also associated with decreased rates of ARDS documentation. The manual chart review revealed 98% concordance between ARDS documentation in the discharge summary and during the hospital stay. Accuracy of the document classifier was 100% for ARDS and mechanical ventilation, 98% for ICU admission, and 95% for symptoms of post-intensive care syndrome. CONCLUSIONS: In the discharge documents of survivors of ARDS, ARDS itself is rarely mentioned, but mechanical ventilation and ICU stay frequently are. The low rates of documentation of ARDS appear to be concordant with low rates of documentation during the hospital stay, consistent with known underrecognition in the ICU. Natural language processing tools can be used to effectively analyze large numbers of discharge documents of patients with critical illness.