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Texas Heart Institute Journal May 2024Left main occlusion presenting as ST-segment elevation myocardial infarction is an exceedingly morbid condition. This article reports a case of cardiac arrest in a...
Left main occlusion presenting as ST-segment elevation myocardial infarction is an exceedingly morbid condition. This article reports a case of cardiac arrest in a patient after a treadmill stress test. Coronary angiography revealed 100% occlusion of the left main coronary artery. Left ventricular unloading with the Impella CP heart pump (ABIOMED/Johnson & Johnson MedTech) was used, after which epicardial blood flow was restored without angioplasty. The patient underwent surgical revascularization. Despite a prolonged revascularization time, there was no evidence of severe myocardial injury postoperatively.
Topics: Humans; Heart-Assist Devices; Coronary Angiography; ST Elevation Myocardial Infarction; Ventricular Function, Left; Male; Coronary Circulation; Middle Aged; Recovery of Function; Treatment Outcome; Pericardium; Myocardial Revascularization; Aged; Coronary Occlusion; Electrocardiography; Prosthesis Design
PubMed: 38805372
DOI: 10.14503/THIJ-23-8322 -
Hellenic Journal of Cardiology : HJC =... May 2024Estimated pulse wave velocity (ePWV), a newly established arterial stiffness (AS) parameter, predicts development of cardiovascular disease (CVD) and death in general...
AIM
Estimated pulse wave velocity (ePWV), a newly established arterial stiffness (AS) parameter, predicts development of cardiovascular disease (CVD) and death in general population or patients with CVD risk factors. However, whether ePWV is associated with adverse outcome in heart failure with preserved ejection fraction (HFpEF) patients remains unknown. Our study aimed to evaluate the prognostic value of ePWV on clinical outcomes in HFpEF.
METHODS AND RESULTS
We analyzed HFpEF participants from the Americas in the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT) trial with available baseline data (n = 1764). Cox proportional hazard model was used to explore the prognostic value of ePWV on the long-term clinical outcomes (all-cause mortality, cardiovascular mortality, all-cause hospitalization and heart failure hospitalization). Each ePWV increase by 1 m/s increased the risk for all-cause death by 16% (HR:1.16; 95% CI:1.10-1.23; P<0.001) and CVD mortality by 13% (HR:1.13; 95% CI:1.04-1.21; P=0.002) after adjusting for confounders. Patients were then grouped into 4 quartiles of ePWV. Our study indicated that the highest ePWV quartile (ePWV ≥12.806 m/s) was associated with increased risk of all-cause mortality (HR, 1.96; 95% CI, 1.43-2.69; P<0.001) and CVD mortality (HR, 1.72; 95% CI, 1.16-2.56; P=0.008) after adjusting for potential confounders.
CONCLUSION
These results suggested ePWV is independently associated with increased all-cause mortality and CVD mortality in HFpEF patients, indicating ePWV is an appropriate predictor of prognosis in patients with HFpEF.
PubMed: 38795773
DOI: 10.1016/j.hjc.2024.05.013 -
Tomography (Ann Arbor, Mich.) Apr 2024The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent....
The arterial input function (AIF) is vital for myocardial blood flow quantification in cardiac MRI to indicate the input time-concentration curve of a contrast agent. Inaccurate AIFs can significantly affect perfusion quantification. When only saturated and biased AIFs are measured, this work investigates multiple ways of leveraging tissue curve information, including using AIF + tissue curves as inputs and optimizing the loss function for deep neural network training. : Simulated data were generated using a 12-parameter AIF mathematical model for the AIF. Tissue curves were created from true AIFs combined with compartment-model parameters from a random distribution. Using Bloch simulations, a dictionary was constructed for a saturation-recovery 3D radial stack-of-stars sequence, accounting for deviations such as flip angle, T2* effects, and residual longitudinal magnetization after the saturation. A preliminary simulation study established the optimal tissue curve number using a bidirectional long short-term memory (Bi-LSTM) network with just AIF loss. Further optimization of the loss function involves comparing just AIF loss, AIF with compartment-model-based parameter loss, and AIF with compartment-model tissue loss. The optimized network was examined with both simulation and hybrid data, which included in vivo 3D stack-of-star datasets for testing. The AIF peak value accuracy and ktrans results were assessed. : Increasing the number of tissue curves can be beneficial when added tissue curves can provide extra information. Using just the AIF loss outperforms the other two proposed losses, including adding either a compartment-model-based tissue loss or a compartment-model parameter loss to the AIF loss. With the simulated data, the Bi-LSTM network reduced the AIF peak error from -23.6 ± 24.4% of the AIF using the dictionary method to 0.2 ± 7.2% (AIF input only) and 0.3 ± 2.5% (AIF + ten tissue curve inputs) of the network AIF. The corresponding ktrans error was reduced from -13.5 ± 8.8% to -0.6 ± 6.6% and 0.3 ± 2.1%. With the hybrid data (simulated data for training; in vivo data for testing), the AIF peak error was 15.0 ± 5.3% and the corresponding ktrans error was 20.7 ± 11.6% for the AIF using the dictionary method. The hybrid data revealed that using the AIF + tissue inputs reduced errors, with peak error (1.3 ± 11.1%) and ktrans error (-2.4 ± 6.7%). : Integrating tissue curves with AIF curves into network inputs improves the precision of AI-driven AIF corrections. This result was seen both with simulated data and with applying the network trained only on simulated data to a limited in vivo test dataset.
Topics: Humans; Magnetic Resonance Imaging; Contrast Media; Coronary Circulation; Computer Simulation; Neural Networks, Computer; Image Processing, Computer-Assisted
PubMed: 38787011
DOI: 10.3390/tomography10050051 -
Biosensors May 2024Real-time monitoring of physiological indicators inside the body is pivotal for contemporary diagnostics and treatments. Implantable electrodes can not only track...
Real-time monitoring of physiological indicators inside the body is pivotal for contemporary diagnostics and treatments. Implantable electrodes can not only track specific biomarkers but also facilitate therapeutic interventions. By modifying biometric components, implantable electrodes enable in situ metabolite detection in living tissues, notably beneficial in invasive glucose monitoring, which effectively alleviates the self-blood-glucose-managing burden for patients. However, the development of implantable electrochemical electrodes, especially multi-channel sensing devices, still faces challenges: (1) The complexity of direct preparation hinders functionalized or multi-parameter sensing on a small scale. (2) The fine structure of individual electrodes results in low spatial resolution for sensor functionalization. (3) There is limited conductivity due to simple device structures and weakly conductive electrode materials (such as silicon or polymers). To address these challenges, we developed multiple-channel electrochemical microneedle electrode arrays (MCEMEAs) via a separated functionalization and assembly process. Two-dimensional microneedle (2dMN)-based and one-dimensional microneedle (1dMN)-based electrodes were prepared by laser patterning, which were then modified as sensing electrodes by electrochemical deposition and glucose oxidase decoration to achieve separated functionalization and reduce mutual interference. The electrodes were then assembled into 2dMN- and 1dMN-based multi-channel electrochemical arrays (MCEAs), respectively, to avoid damaging functionalized coatings. In vitro and in vivo results demonstrated that the as-prepared MCEAs exhibit excellent transdermal capability, detection sensitivity, selectivity, and reproducibility, which was capable of real-time, in situ glucose concentration monitoring.
Topics: Biosensing Techniques; Electrodes; Electrochemical Techniques; Animals; Glucose Oxidase; Rats; Humans; Blood Glucose; Needles
PubMed: 38785717
DOI: 10.3390/bios14050243 -
BMC Medical Education May 2024As artificial intelligence (AI) increasingly integrates into medical education, its specific impact on the development of clinical skills among pediatric trainees needs... (Comparative Study)
Comparative Study Randomized Controlled Trial
BACKGROUND
As artificial intelligence (AI) increasingly integrates into medical education, its specific impact on the development of clinical skills among pediatric trainees needs detailed investigation. Pediatric training presents unique challenges which AI tools like ChatGPT may be well-suited to address.
OBJECTIVE
This study evaluates the effectiveness of ChatGPT-assisted instruction versus traditional teaching methods on pediatric trainees' clinical skills performance.
METHODS
A cohort of pediatric trainees (n = 77) was randomly assigned to two groups; one underwent ChatGPT-assisted training, while the other received conventional instruction over a period of two weeks. Performance was assessed using theoretical knowledge exams and Mini-Clinical Evaluation Exercises (Mini-CEX), with particular attention to professional conduct, clinical judgment, patient communication, and overall clinical skills. Trainees' acceptance and satisfaction with the AI-assisted method were evaluated through a structured survey.
RESULTS
Both groups performed similarly in theoretical exams, indicating no significant difference (p > 0.05). However, the ChatGPT-assisted group showed a statistically significant improvement in Mini-CEX scores (p < 0.05), particularly in patient communication and clinical judgment. The AI-teaching approach received positive feedback from the majority of trainees, highlighting the perceived benefits in interactive learning and skill acquisition.
CONCLUSION
ChatGPT-assisted instruction did not affect theoretical knowledge acquisition but did enhance practical clinical skills among pediatric trainees. The positive reception of the AI-based method suggests that it has the potential to complement and augment traditional training approaches in pediatric education. These promising results warrant further exploration into the broader applications of AI in medical education scenarios.
Topics: Humans; Pediatrics; Clinical Competence; Teaching; Educational Measurement; Artificial Intelligence; Male; Female; Internship and Residency
PubMed: 38778332
DOI: 10.1186/s12909-024-05565-1 -
BMC Palliative Care May 2024Values are broadly understood to have implications for how individuals make decisions and cope with serious illness stressors, yet it remains uncertain how patients and...
"When I do have some time, rather than spend it polishing silver, I want to spend it with my grandkids": a qualitative exploration of patient values following left ventricular assist device implantation.
BACKGROUND
Values are broadly understood to have implications for how individuals make decisions and cope with serious illness stressors, yet it remains uncertain how patients and their family and friend caregivers discuss, reflect upon, and act on their values in the post-left ventricular assist device (LVAD) implantation context. This study aimed to explore the values elicitation experiences of patients with an LVAD in the post-implantation period.
METHODS
Qualitative descriptive study of LVAD recipients. Socio-demographics and patient resource use were analyzed using descriptive statistics and semi-structured interview data using thematic analysis. Adult (> 18 years) patients with an LVAD receiving care at an outpatient clinic in the Southeastern United States.
RESULTS
Interviewed patients (n = 27) were 30-76 years, 59% male, 67% non-Hispanic Black, 70% married/living with a partner, and 70% urban-dwelling. Three broad themes of patient values elicitation experiences emerged: 1) LVAD implantation prompts deep reflection about life and what is important, 2) patient values are communicated in various circumstances to convey personal goals and priorities to caregivers and clinicians, and 3) patients leverage their values for strength and guidance in navigating life post-LVAD implantation. LVAD implantation was an impactful experience often leading to reevaluation of patients' values; these values became instrumental to making health decisions and coping with stressors during the post-LVAD implantation period. Patient values arose within broad, informal exchanges and focused, decision-making conversations with their caregiver and the healthcare team.
CONCLUSIONS
Clinicians should consider assessing the values of patients post-implantation to facilitate shared understanding of their goals/priorities and identify potential changes in their coping.
Topics: Humans; Heart-Assist Devices; Male; Middle Aged; Female; Qualitative Research; Adult; Aged; Adaptation, Psychological
PubMed: 38778297
DOI: 10.1186/s12904-024-01454-y -
Surgical Case Reports May 2024Pancreatoduodenectomy and subtotal esophagectomy are widely considered the most invasive and difficult surgical procedures in gastrointestinal surgery. Subtotal...
BACKGROUND
Pancreatoduodenectomy and subtotal esophagectomy are widely considered the most invasive and difficult surgical procedures in gastrointestinal surgery. Subtotal esophagectomy after pancreatoduodenectomy is expected to be extremely difficult due to complicated anatomical changes, and selecting an appropriate intestinal reconstruction method will also be a difficult task. Therefore, perhaps because the method is considered impossible, there have been few reports of subtotal esophagectomy after pancreatoduodenectomy.
CASE PRESENTATION
A 73-year-old man with a history of pancreatoduodenectomy was diagnosed with superficial thoracic esophageal squamous cell carcinoma. Definitive chemoradiation therapy was recommended at another hospital; however, he visited our department to undergo surgery. We performed the robot-assisted thoracoscopic subtotal esophagectomy. There were some difficulties with the reconstruction: the gastric tube could not be used, the reconstruction was long, and the organs reconstructed in the previous surgery had to be preserved. However, the concurrent reconstruction was achieved with the help of a free jejunal flap and vascular reconstruction. All reconstructions from the previous surgery, including the remnant stomach, were preserved via regional abdominal lymph node dissection. After reconstruction, intravenous indocyanine green showed that circulation in the reconstructed intestines was preserved. On postoperative day 1, no recurrent nerve paralysis was observed during laryngoscopy. The patient could start oral intake smoothly 2 weeks after surgery and did not exhibit any postoperative complications related to the reconstruction. The patient was transferred to another hospital on postoperative day 21.
CONCLUSIONS
Owing to the free jejunal flap interposition method, we safely performed one stage subtotal esophagectomy and concurrent reconstruction, preservation of the remnant stomach, and pancreaticobiliary reconstruction in patients with a history of pancreatoduodenectomy. We believe that this method is acceptable and useful for patients undergoing complicated reconstruction.
PubMed: 38775882
DOI: 10.1186/s40792-024-01919-5 -
International Journal of Medical... May 2024To evaluate the diagnostic efficacy of a developed artificial intelligence (AI) platform incorporating deep learning algorithms for the automated detection of...
PURPOSE
To evaluate the diagnostic efficacy of a developed artificial intelligence (AI) platform incorporating deep learning algorithms for the automated detection of intracranial aneurysms in time-of-flight (TOF) magnetic resonance angiography (MRA).
METHOD
This retrospective study encompassed 3D TOF MRA images acquired between January 2023 and June 2023, aiming to validate the presence of intracranial aneurysms via our developed AI platform. The manual segmentation results by experienced neuroradiologists served as the "gold standard". Following annotation of MRA images by neuroradiologists using InferScholar software, the AI platform conducted automatic segmentation of intracranial aneurysms. Various metrics including accuracy (ACC), balanced ACC, area under the curve (AUC), sensitivity (SE), specificity (SP), F1 score, Brier Score, and Net Benefit were utilized to evaluate the generalization of AI platform. Comparison of intracranial aneurysm identification performance was conducted between the AI platform and six radiologists with experience ranging from 3 to 12 years in interpreting MR images. Additionally, a comparative analysis was carried out between radiologists' detection performance based on independent visual diagnosis and AI-assisted diagnosis. Subgroup analyses were also performed based on the size and location of the aneurysms to explore factors impacting aneurysm detectability.
RESULTS
510 patients were enrolled including 215 patients (42.16 %) with intracranial aneurysms and 295 patients (57.84 %) without aneurysms. Compared with six radiologists, the AI platform showed competitive discrimination power (AUC, 0.96), acceptable calibration (Brier Score loss, 0.08), and clinical utility (Net Benefit, 86.96 %). The AI platform demonstrated superior performance in detecting aneurysms with an overall SE, SP, ACC, balanced ACC, and F1 score of 91.63 %, 92.20 %, 91.96 %, 91.92 %, and 90.57 % respectively, outperforming the detectability of the two resident radiologists. For subgroup analysis based on aneurysm size and location, we observed that the SE of the AI platform for identifying tiny (diameter<3mm), small (3 mm ≤ diameter<5mm), medium (5 mm ≤ diameter<7mm) and large aneurysms (diameter ≥ 7 mm) was 87.80 %, 93.14 %, 95.45 %, and 100 %, respectively. Furthermore, the SE for detecting aneurysms in the anterior circulation was higher than that in the posterior circulation. Utilizing the AI assistance, six radiologists (i.e., two residents, two attendings and two professors) achieved statistically significant improvements in mean SE (residents: 71.40 % vs. 88.37 %; attendings: 82.79 % vs. 93.26 %; professors: 90.07 % vs. 97.44 %; P < 0.05) and ACC (residents: 85.29 % vs. 94.12 %; attendings: 91.76 % vs. 97.06 %; professors: 95.29 % vs. 98.82 %; P < 0.05) while no statistically significant change was observed in SP. Overall, radiologists' mean SE increased by 11.40 %, mean SP increased by 1.86 %, and mean ACC increased by 5.88 %, mean balanced ACC promoted by 6.63 %, mean F1 score grew by 7.89 %, and Net Benefit rose by 12.52 %, with a concurrent decrease in mean Brier score declined by 0.06.
CONCLUSIONS
The deep learning algorithms implemented in the AI platform effectively detected intracranial aneurysms on TOF-MRA and notably enhanced the diagnostic capabilities of radiologists. This indicates that the AI-based auxiliary diagnosis model can provide dependable and precise prediction to improve the diagnostic capacity of radiologists.
PubMed: 38761459
DOI: 10.1016/j.ijmedinf.2024.105487 -
Brazilian Journal of Cardiovascular... May 2024
Topics: Humans; Intra-Aortic Balloon Pumping; Heart Transplantation; Cardiac Surgical Procedures
PubMed: 38748717
DOI: 10.21470/1678-9741-2024-0991 -
The Journal of Clinical Investigation May 2024One of the features of pathological cardiac hypertrophy is enhanced translation and protein synthesis. Translational inhibition has been shown to be an effective means...
One of the features of pathological cardiac hypertrophy is enhanced translation and protein synthesis. Translational inhibition has been shown to be an effective means of treating cardiac hypertrophy, although system-wide side effects are common. Regulators of translation, such as cardiac-specific long non-coding RNAs (lncRNAs), could provide new, more targeted, therapeutic approaches to inhibit cardiac hypertrophy. Therefore, we generated mice lacking a previously identified lncRNA named CARDINAL to examine its cardiac function. We demonstrate that CARDINAL is a cardiac-specific, ribosome associated lncRNA and show that its expression is induced in the heart upon pathological cardiac hypertrophy; its deletion in mice exacerbates stress-induced cardiac hypertrophy and augments protein translation. In contrast, overexpression of CARDINAL attenuates cardiac hypertrophy in vivo and in vitro, and suppresses hypertrophy-induced protein translation. Mechanistically, CARDINAL interacts with developmentally regulated GTP binding protein 1 (DRG1) and blocks its interaction with DRG family regulatory protein 1 (DFRP1); as a result, DRG1 is downregulated, thereby modulating the rate of protein translation in the heart in response to stress. This study provides evidence for the therapeutic potential of targeting cardiac-specific lncRNAs to suppress disease-induced translational changes and to treat cardiac hypertrophy and heart failure.
PubMed: 38743498
DOI: 10.1172/JCI169112