Brit J Hosp Med
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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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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.
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With the rapid ageing of the population, the number of older adults with two or more chronic diseases is increasing. There are individual differences in health assessment, diagnosis, treatment, health management, and medication safety for older adults with chronic conditions and multiple morbidities. ⋯ Developing effective community health management models specifically designed for older adults with multiple chronic diseases is crucial for improving their overall health. This study provides a comprehensive review of the progress in research on community health management models for older adults with multiple chronic diseases, aiming to offer valuable insights for health management in this population.
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Polypharmacy is common among older people and is associated with multiple adverse outcomes. Assessing whether it is appropriate or inappropriate for an individual is more informative than relying on a simple pill count. Modern medicine is based on single disease guidelines that promote prescribing but tend not to have deprescribing criteria. ⋯ Prescribing can be inappropriate if it is not evidence-based, harm is likely to exceed the benefit, includes hazardous medications or combinations of medicines, the patient experiences therapeutic burden, there is reduced adherence or prescribing cascades. Medicines optimisation aims to improve prescribing quality for an individual patient and may include deprescribing. It is a complex process that includes shared decision-making, careful follow-up, and communication of any resulting prescription changes.
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Renal tubular acidosis is a group of disorders characterised by metabolic acidosis, hyperchloraemia, normal anion gap, and potassium imbalance. Genetic mutations, drugs or acquired disorders disrupt the function of various transport proteins and enzymes in the renal tubules, causing diminished bicarbonate reabsorption or inability to excrete hydrogen ions, leading to proximal (type 2) and distal (type 1) renal tubular acidosis, respectively. These conditions are typically associated with hypokalaemia, which, if severe, can cause muscle paralysis and dangerous cardiac arrhythmias. ⋯ If untreated, renal tubular acidosis can lead to long-term severe complications such as growth retardation, osteoporosis, rickets, osteomalacia, and renal calculi. Moreover, renal tubular acidosis might be the initial presentation of a more severe underlying pathology, such as autoimmune disease or plasma cell dyscrasias. A better understanding of the condition can help physicians diagnose and treat it early and prevent adverse outcomes.