Brit J Hosp Med
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Aims/Background Neonatal morbidity, including various diseases such as sepsis, cholestasis, and bronchopulmonary dysplasia (BPD), is a significant concern, especially in preterm infants. Selecting the appropriate lipid emulsion in parenteral nutrition (PN) is essential to improve clinical outcomes. This analysis aimed to assess the impact of a novel composite lipid emulsion, SMOFlipid, on neonates receiving PN. ⋯ The subgroup analysis indicated a decline in PDA incidence (RR: 0.88, 95% CI: 0.79-0.99, p = 0.04, I2 = 0%) among extremely premature infants receiving SMOFlipid. Conclusion SMOFlipid offers a promising option for neonatal PN, particularly for reducing cholestasis in preterm infants and PDA in extremely premature infants. Further investigations into its comprehensive benefits and long-term effects are warranted.
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Meta Analysis
Platelet Reactivity with MACE in Acute Coronary Syndrome Patients Post-PCI under Dual Antiplatelet Therapy: A Meta-Analysis.
Aim/Background Acute coronary syndrome (ACS), a condition characterized by acute cardiac ischemia, is among the major causes of death from cardiovascular diseases (CVD). However, whether there is a correlation between platelet reactivity and major adverse cardiovascular events (MACE) remains debatable, and whether platelet function tests should be tailored for ACS patients after percutaneous coronary intervention (PCI) is still under discussion. This study aims to investigate the relationship between platelet reactivity and the occurrence of MACE in ACS patients post-PCI and to discuss the implications of these findings. ⋯ On the other hand, meta-regression revealed that region (p = 0.99), type of ACS patient (p = 0.16), drug regimen (p = 0.48), testing method (p = 0.51), sampling time (p = 0.70), follow-up time (p = 0.45), and PCI protocol (p = 0.27) were not sources of heterogeneity in the study. Conclusion The meta-analysis outcomes indicate that in ACS patients receiving PCI and using dual antiplatelet therapy for 1-2 years, HPR was independently positively correlated with major adverse cardiovascular events, all-cause (or cardiac) mortality, recurrent myocardial infarction, in-stent restenosis, and stroke. This suggests that platelet reactivity testing has clinical and translational significance in predicting patients' risk of adverse cardiovascular events.
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Lesions with central hypointensity and peripheral contrast enhancement are defined as ring-enhancing lesions. The aetiologies of ring-enhancing lesions may be various, including infections, tumours, demyelinating diseases, treatment-related conditions and hematoma. The imaging findings and their distinguishing features also vary among different ring-enhancing lesions. This review examines the magnetic resonance imaging findings of different ring-enhancing lesions and their distinguishing features.
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Cervical cancer remains a leading cause of cancer-related mortality among women worldwide, particularly in underdeveloped nations. Despite advances in standard therapies, patients with recurrent metastatic cervical cancer face a poor prognosis and limited treatment options. This study aims to evaluate the efficacy and safety of emerging therapeutic approaches in managing this challenging condition, including immunotherapy, targeted medicines, and chemotherapy. ⋯ In conclusion, improvements in medical technology and the adoption of tailored treatment approaches have led to promising advancements in the management of recurrent metastatic cervical cancer. To further enhance patient care, there is an urgent need for more extensive clinical trial data and the development of more efficient personalised treatment plans. This study aims to contribute to this effort by comprehensively analysing current therapeutic strategies and identifying areas for future research.
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Review
Prediction of Cervical Cancer Lymph Node Metastasis via a Multimodal Transfer Learning Approach.
Aims/Background In the treatment of patients with cervical cancer, lymph node metastasis (LNM) is an important indicator for stratified treatment and prognosis of cervical cancer. This study aimed to develop and validate a multimodal model based on contrast-enhanced multiphase computed tomography (CT) images and clinical variables to accurately predict LNM in patients with cervical cancer. Methods This study included 233 multiphase contrast-enhanced CT images of patients with pathologically confirmed cervical malignancies treated at the Affiliated Dongyang Hospital of Wenzhou Medical University. ⋯ The area under the curve (AUC) was used to assess the predictive efficacy of the model. Results The results indicate that the deep transfer learning model exhibited high diagnostic performance within the internal validation set, with an AUC of 0.82, accuracy of 0.88, sensitivity of 0.83, and specificity of 0.89. Conclusion We constructed a comprehensive, multiparameter model based on the concept of deep transfer learning, by pre-training the model with contrast-enhanced multiphase CT images and an array of clinical variables, for predicting LNM in patients with cervical cancer, which could aid the clinical stratification of these patients via a noninvasive manner.