Journal of the Chinese Medical Association : JCMA
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Randomized Controlled Trial
Sugammadex shortens operation time and improves operation turnover efficacy in VATS.
This study compared sugammadex and neostigmine as agents for routine neuromuscular blockade reversal in video-assisted thoracoscopic surgery (VATS) to determine the optimal choice that achieves a shorter operation time and improved turnover efficiency while enhancing postoperative outcomes and ensuring patient safety during thoracic surgery. ⋯ This study's findings suggest that sugammadex may enhance total operating room occupancy time, operation turnover efficacy, and respiratory recovery outcomes in VATS, potentially improving patient care and anesthesia management.
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Patients who survive an acute myocardial infarction (AMI) have a higher risk of having a major cardiovascular event (MACE). Cardiopulmonary exercise testing (CPET) could develop prognostic stratification and prescribing exercise prescription. Patients after AMI frequently terminate CPET early with submaximal testing results. We aimed to look at the characteristics of patients' predischarge CPET variables after AMI intervention and find potential CPET variables with prognostic value. ⋯ It is critical to identify a submaximal predictor during CPET for patients who survive AMI. Our findings suggested that OUES could be a significant prognostic indicator in patients after first AMI in both the short and long term.
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The aim of this study was to examine the risk factors associated with the use of vasopressors to prevent hypotension that occurs after spinal anesthesia during cesarean section. Although the prophylactic use of vasopressors is already suggested as routine care in many parts of the world, the occurrence of spinal anesthesia-induced hypotension (SAIH) is still common in parturients. ⋯ These findings can be useful for clinicians when deciding the dose of prophylactic ephedrine or phenylephrine to prevent SAIH.
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The introduction of direct-acting antiviral agents (DAAs) has revolutionized the therapeutic landscape of chronic hepatitis C (CHC), however real-world data on the risk factors of hepatocellular carcinoma (HCC) recurrence following DAA treatment in CHC-HCC patients are limited in Taiwan. We aimed to evaluate the therapeutic efficacy of DAAs in Taiwanese patients with prior hepatitis C virus (HCV)-induced HCC and identify the posttreatment risk factors for HCC recurrence. ⋯ This investigation underscores the critical influence of factors such as prior HCC recurrence, successful attainment of SVR 12 , posttreatment AFP level, and specific tumor characteristics in determining the risk of HCC recurrence after treatment with DAAs. Our proposed innovative risk stratification system may not only contribute to enhanced personalized care but also holds the potential to optimize treatment outcomes.
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Recently, the rapid advancement in generative artificial intelligence (AI) technology, such as ChatGPT-4, has sparked discussions, particularly in image recognition. Accurate results are critical for hematological diagnosis, particularly for blood morphology identification. Despite advanced hematology analyzers, reliance on professional hematopathologists for manual identification remains in cases of abnormal or rare conditions, a process prone to human subjectivity and potential errors. Consequently, this study aimed to investigate the potential of ChatGPT-4 to assist with blood morphology identification. ⋯ This study shows that although generative AI shows the potential for blood type identification, it has not yet reached the point where it can replace the professional judgment of medical staff. The results showed that ChatGPT-4 is excellent for identifying red blood cell morphology, particularly inclusion bodies. It can be used as an auxiliary tool for clinical diagnosis. However, the overall recognition accuracy must be further improved. Our study produced innovative results in this field, establishing a foundation for future studies and highlighting the potential of generative AI in aiding blood morphology recognition. Future research should focus on enhancing the effectiveness of AI to improve overall standards of medical care.