To develop a natural language processing (NLP) algorithm that can accurately extract headache frequency from free-text clinical notes.
Headache frequency, defined as the number of days with any ...headache in a month (or 4 weeks), remains a key parameter in the evaluation of treatment response to migraine preventive medications. However, due to the variations and inconsistencies in documentation by clinicians, significant challenges exist to accurately extract headache frequency from the electronic health record (EHR) by traditional NLP algorithms.
This was a retrospective cross-sectional study with patients identified from two tertiary headache referral centers, Mayo Clinic Arizona and Mayo Clinic Rochester. All neurology consultation notes written by 15 specialized clinicians (11 headache specialists and 4 nurse practitioners) between 2012 and 2022 were extracted and 1915 notes were used for model fine-tuning (90%) and testing (10%). We employed four different NLP frameworks: (1) ClinicalBERT (Bidirectional Encoder Representations from Transformers) regression model, (2) Generative Pre-Trained Transformer-2 (GPT-2) Question Answering (QA) model zero-shot, (3) GPT-2 QA model few-shot training fine-tuned on clinical notes, and (4) GPT-2 generative model few-shot training fine-tuned on clinical notes to generate the answer by considering the context of included text.
The mean (standard deviation) headache frequency of our training and testing datasets were 13.4 (10.9) and 14.4 (11.2), respectively. The GPT-2 generative model was the best-performing model with an accuracy of 0.92 (0.91, 0.93, 95% confidence interval CI) and R
score of 0.89 (0.87, 0.90, 95% CI), and all GPT-2-based models outperformed the ClinicalBERT model in terms of exact matching accuracy. Although the ClinicalBERT regression model had the lowest accuracy of 0.27 (0.26, 0.28), it demonstrated a high R
score of 0.88 (0.85, 0.89), suggesting the ClinicalBERT model can reasonably predict the headache frequency within a range of ≤ ± 3 days, and the R
score was higher than the GPT-2 QA zero-shot model or GPT-2 QA model few-shot training fine-tuned model.
We developed a robust information extraction model based on a state-of-the-art large language model, a GPT-2 generative model that can extract headache frequency from EHR free-text clinical notes with high accuracy and R
score. It overcame several challenges related to different ways clinicians document headache frequency that were not easily achieved by traditional NLP models. We also showed that GPT-2-based frameworks outperformed ClinicalBERT in terms of accuracy in extracting headache frequency from clinical notes. To facilitate research in the field, we released the GPT-2 generative model and inference code with open-source license of community use in GitHub. Additional fine-tuning of the algorithm might be required when applied to different health-care systems for various clinical use cases.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Background
Aortic stenosis (AS) is associated with myocardial ischemia through different mechanisms and may impair coronary arterial flow. However, data on the impact of moderate AS in patients with ...acute myocardial infarction (MI) is limited.
Aims
This study aimed to investigate the impact of moderate AS in patients presenting with acute myocardial infarction (MI).
Methods
We conducted a retrospective analysis of all patients who presented with acute MI to all Mayo Clinic hospitals, using the Enterprise Mayo PCI Database from 2005 to 2016. Patients were stratified into two groups: moderate AS and mild/no AS. The primary outcome was all cause mortality.
Results
The moderate AS group included 183 (13.3%) patients, and the mild/no AS group included 1190 (86.7%) patients. During hospitalization, there was no difference between both groups in mortality. Patients with moderate AS had higher in‐hospital congestive heart failure (CHF) (8.2% vs. 4.4%, p = 0.025) compared with mild/no AS patients. At 1‐year follow‐up, patients with moderate AS had higher mortality (23.9% vs. 8.1%, p < 0.001) and higher CHF hospitalization (8.3% vs. 3.7%, p = 0.028). In multivariate analysis, moderate AS was associated with higher mortality at 1‐year (odds ratio 2.4, 95% confidence interval 1.4–4.1, p = 0.002). In subgroup analyses, moderate AS increased all‐cause mortality in STEMI and NSTEMI patients.
Conclusion
The presence of moderate AS in acute MI patients was associated with worse clinical outcomes during hospitalization and at 1‐year follow‐up. These unfavorable outcomes highlight the need for a close follow‐up of these patients and for timely therapeutic strategies to best manage these coexisting conditions.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Immune checkpoint inhibitors (ICIs) with nivolumab and pembrolizumab are promising agents for advanced hepatocellular carcinoma (HCC) but lack of effective biomarkers. We aimed to investigate the ...potential predictors of response and factors associated with overall survival (OS) for ICI treatment in unresectable HCC patients. Ninety-five patients who received nivolumab or pembrolizumab for unresectable HCC were enrolled for analyses. Radiologic evaluation was based on RECIST v1.1. Factors associated with outcomes were analyzed. Of 90 patients with evaluable images, the objective response rate (ORR) was 24.4%. Patients at Child-Pugh A or received combination treatment had higher ORR. Early alpha-fetoprotein (AFP) >10% reduction (within 4 weeks) was the only independent predictor of best objective response (odds ratio: 7.259,
= 0.001). For patients with baseline AFP ≥10 ng/mL, significantly higher ORR (63.6% vs. 10.2%,
< 0.001) and disease control rate (81.8% vs. 14.3%,
< 0.001) were observed in those with early AFP reduction than those without. In addition, early AFP reduction and albumin-bilirubin (ALBI) grade or Child-Pugh class were independent factors associated with OS in different models. In conclusion, a 10-10 rule of early AFP response can predict objective response and survival to ICI treatment in unresectable HCC. ALBI grade and Child-Pugh class determines survival by ICI treatment.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Right ventricular (RV) pacing is the main treatment modality for patients with advanced atrioventricular (AV) block. Chronic RV pacing can cause cardiac systolic dysfunction and heart failure (HF). ...In this review, we discuss studies that have shown deleterious effects of chronic RV pacing on systolic cardiac function causing pacing-induced cardiomyopathy (PiCM), heart failure (HF), HF hospitalization, atrial fibrillation (AF) and cardiac mortality. RV apical pacing is the most widely used and studied. Adverse effects of RV pacing appear to be directly related to pacing burden and are worse in patients with pre-existing left ventricular (LV) dysfunction. Chronic RV pacing is also associated with heart failure with preserved ejection fraction (HFpEF). Mechanisms, risk factors, clinical and echocardiographic features, and strategies to minimize RV pacing-induced cardiac dysfunction are discussed in light of the latest data. Studies on biventricular (Bi-V) pacing upgrade in patients who develop RV PiCM, use of alternate RV pacing sites, de novo Bi-V pacing, and physiologic pacing using HIS bundle pacing (HBP) and left bundle area (LBBA) pacing in patients with an anticipated high RV pacing burden are discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objective
To compare the artificial intelligence‐enabled electrocardiogram (AI‐ECG) atrial fibrillation (AF) prediction model output in patients with migraine with aura (MwA) and migraine without ...aura (MwoA).
Background
MwA is associated with an approximately twofold risk of ischemic stroke. Longitudinal cohort studies showed that patients with MwA have a higher incidence of developing AF compared to those with MwoA. The Mayo Clinic Cardiology team developed an AI‐ECG algorithm that calculates the probability of concurrent paroxysmal or impending AF in ECGs with normal sinus rhythm (NSR).
Methods
Adult patients with an MwA or MwoA diagnosis and at least one NSR ECG within the past 20 years at Mayo Clinic were identified. Patients with an ECG‐confirmed diagnosis of AF were excluded. For each patient, the ECG with the highest AF prediction model output was used as the index ECG. Comparisons between MwA and MwoA were conducted in the overall group (including men and women of all ages), women only, and men only in each age range (18 to <35, 35 to <55, 55 to <75, ≥75 years), and adjusted for age, sex, and six common vascular comorbidities that increase risk for AF.
Results
The final analysis of our cross‐sectional study included 40,002 patients (17,840 with MwA, 22,162 with MwoA). The mean (SD) age at the index ECG was 48.2 (16.0) years for MwA and 45.9 (15.0) years for MwoA (p < 0.001). The AF prediction model output was significantly higher in the MwA group compared to MwoA (mean SD 7.3% 15.0% vs. 5.6% 12.4%, mean difference 95% CI 1.7% 1.5%, 2.0%, p < 0.001). After adjusting for vascular comorbidities, the difference between MwA and MwoA remained significant in the overall group (least square means of difference 95% CI 0.7% 0.4%, 0.9%, p < 0.001), 18 to <35 (0.4% 0.1%, 0.7%, p = 0.022), and 35 to <55 (0.5% 0.2%, 0.8%, p < 0.001), women of all ages (0.6% 0.3%, 0.8%, p < 0.001), men of all ages (1.0% 0.4%, 1.6%, p = 0.002), women 35 to <55 (0.6% 0.3%, 0.9%, p < 0.001), and men 18 to <35 (1.2% 0.3%, 2.1%, p = 0.008).
Conclusions
Utilizing a novel AI‐ECG algorithm on a large group of patients, we demonstrated that patients with MwA have a significantly higher AF prediction model output, implying a higher probability of concurrent paroxysmal or impending AF, compared to MwoA in both women and men. Our results suggest that MwA is an independent risk factor for AF, especially in patients <55 years old, and that AF‐mediated cardioembolism may play a role in the migraine–stroke association for some patients.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Lipoprotein(a) (Lp(a)) is associated with an increased incidence of native aortic stenosis, which shares similar pathological mechanisms with bioprosthetic aortic valve (bAV) degeneration. However, ...evidence regarding the role of Lp(a) concentrations in bAV degeneration is lacking. This study aims to evaluate the association between Lp(a) concentrations and bAV degeneration.
In this retrospective multicentre study, patients who underwent a bAV replacement between 1 January 2010 and 31 December 2020 and had a Lp(a) measurement were included. Echocardiography follow-up was performed to determine the presence of bioprosthetic valve degeneration, which was defined as an increase >10 mm Hg in mean gradient from baseline with concomitant decrease in effective orifice area and Doppler Velocity Index, or new moderate/severe prosthetic regurgitation. Levels of Lp(a) were compared between patients with and without degeneration and Cox regression analysis was performed to investigate the association between Lp(a) levels and bioprosthetic valve degeneration.
In total, 210 cases were included (mean age 74.1±9.4 years, 72.4% males). Median time between baseline and follow-up echocardiography was 4.4 (IQR 3.7) years. Bioprostheses degeneration was observed in 33 (15.7%) patients at follow-up. Median serum levels of Lp(a) were significantly higher in patients affected by degeneration versus non-affected cases: 50.0 (IQR 72.0) vs 15.6 (IQR 48.6) mg/dL, p=0.002. In the regression analysis, high Lp(a) levels (≥30 mg/dL) were associated with degeneration both in a univariable analysis (HR 3.6, 95% CI 1.7 to 7.6, p=0.001) and multivariable analysis adjusted by other risk factors for bioprostheses degeneration (HR 4.4, 95% CI 1.9 to 10.4, p=0.001).
High serum Lp(a) is associated with bAV degeneration. Prospective studies are needed to confirm these findings and to investigate whether lowering Lp(a) levels could slow bioprostheses degradation.
Background
Quantitation of regurgitation severity using the proximal isovelocity acceleration (PISA) method to calculate effective regurgitant orifice (ERO) area has limitations. Measurement of ...three‐dimensional (3D) vena contracta area (VCA) accurately grades mitral regurgitation (MR) severity on transthoracic echocardiography (TTE).
Methods
We evaluated 3D VCA quantitation of regurgitant jet severity using 3D transesophageal echocardiography (TEE) in 110 native mitral, aortic, and tricuspid valves and six prosthetic valves in patients with at least mild valvular regurgitation. The ASE‐recommended integrative method comprising semiquantitative and quantitative assessment of valvular regurgitation was used as a reference method, including ERO area by 2D PISA for assigning severity of regurgitation grade.
Results
Mean age was 62.2±14.4 years; 3D VCA quantitation was feasible in 91% regurgitant valves compared to 78% by the PISA method. When both methods were feasible and in the presence of a single regurgitant jet, 3D VCA and 2D PISA were similar in differentiating assigned severity (ANOVAP<.001). In valves with multiple jets, however, 3D VCA had a better correlation to assigned severity (ANOVAP<.0001). The agreement of 2D PISA and 3D VCA with the integrative method was 47% and 58% for moderate and 65% and 88% for severe regurgitation, respectively.
Conclusion
Measurement of 3D VCA by TEE is superior to the 2D PISA method in determination of regurgitation severity in multiple native and prosthetic valves.
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BFBNIB, DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, SIK, UILJ, UKNU, UL, UM, UPUK, VSZLJ
Heart failure (HF) imposes a substantial burden and the prevalence of HF is high in patients with chronic kidney disease (CKD). HF results in multiple hospital admissions, but whether HF subtypes ...worsen long-term outcomes and renal function in patients with CKD remains inconclusive.
The study comprised 10 904 patients with CKD aged ≥20 years who underwent echocardiography between 1 January 2011 and 31 December 2018. The patients were stratified into four groups: non-HF, HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and HF with preserved ejection fraction (HFpEF). The primary end points were all-cause mortality, major adverse cardiovascular events (MACEs) and adverse renal outcomes.
In inverse probability of treatment weighting-adjusted method, the risk of all-cause mortality and MACEs relative to the non-HF group was greatest in the HFrEF group (HR 3.18 (95% CI 2.57 to 3.93) and HR 3.83 (95% CI 3.20 to 4.59)), followed by the HFmrEF (HR 2.75 (95% CI 2.22 to 3.42) and HR 3.08 (95% CI 2.57 to 3.69)) and HFpEF (HR 1.85 (95% CI 1.59 to 2.15) and HR 2.43 (95% CI 2.16 to 2.73) groups. In addition, the HFrEF group had the greatest risks of end-stage renal disease (HR 2.58 (95% CI 1.94 to 3.44)) compared with other groups.
HF is associated with subsequent worse clinical outcomes, which may be more pronounced in patients with HFrEF, followed by those with HFmrEF and those with HFpEF relative to non-HF group.
Abstract Background Cardiac compression in pectus excavatum (PE) deformity and effect of PE surgery on cardiac function in adults have been debated. We examined the effect of PE correction on right ...heart size and cardiac output. Methods A retrospective evaluation was performed of 168 adult patients who underwent a modified Nuss PE repair with intraoperative transesophageal echocardiography from 2011 to 2014. Seventeen patients with prior PE repair undergoing bar removal acted as controls. Results Mean age was 33.0 years (range, 18 to 71 years). There was an increase in right atrium (15.1%), tricuspid annulus (10.9%), and right ventricular outflow tract (6.1%) size after surgery (all P < .0001). Right ventricular cardiac output measured in a subset of 42 patients improved by 38%. No change in chamber size or cardiac output occurred before and after bar removal surgery in the control group. Conclusions Surgical correction of PE deformity caused a significant improvement in right heart chamber size and cardiac output.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
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