Brit J Hosp Med
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Aims/Background Artificial intelligence technology has attained rapid development in recent years. The integration of artificial intelligence applications into pressure reduction mattresses, giving rise to artificial intelligence-powered pressure reduction mattresses, is expected to provide personalised intelligent pressure reduction solutions, through automatic user's data-based adjustment of the patient's local pressure condition to prevent pressure injury. The purpose of this study was to investigate the effectiveness of artificial intelligence-powered smart decompression in the prevention of postoperative medium- and high-risk pressure injury in middle-aged and elderly patients. ⋯ Before treatment, there was no difference in the scores of all aspects of the Richards Campbell Sleep Questionnaire between the two groups (p > 0.05). After treatment, the scores of all aspects of Richards Campbell Sleep Questionnaire in the observation group were significantly lower than those in the control group (p < 0.05). Conclusion The artificial intelligence-powered smart decompression mattress can significantly prevent moderate- and high-risk pressure injury, effectively reducing the incidence of pressure injury and complications in postoperative long-term bedridden patients, alleviating the severity of pressure injury, relieving the pressure on various parts, and improving the sleep quality of patients.
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Observational Study
Drug exposure characteristics and related pregnancy outcomes in pregnant women: an observational cohort study.
Aims/Background The relationship between drug exposure and pregnancy outcomes is still unclear. The study was designed to characterise the overall condition of drug exposure during pregnancy and uncover related pregnancy outcomes. Methods Pregnant women were enrolled in the study from 1 October 2019 to 31 April 2022, at a tertiary hospital in Jiangsu Province, China. ⋯ Compared to the second and third trimester, unrecommended drugs are used more frequently in the first trimester. Drug exposure is associated with adverse pregnancy outcomes and these associations need to be further confirmed. It is vital to fully consider treatment benefits and potential risks before medication initiation during pregnancy.
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Meta Analysis
Efficacy and Safety of Nerve Growth Factor in Treating Neurotrophic Keratitis Patients: A Meta-Analysis.
Aims/Background Nerve growth factor has been approved for treating neurotrophic keratitis in Europe and the United States. However, its clinical efficacy and safety profile in neurotrophic keratitis patients have not been systematically evaluated. Therefore, this study systematically assessed the efficacy and safety of nerve growth factor (NGF) in treating patients with neurotrophic keratitis. ⋯ However, the incidence of ailment progression (OR = 0.44, 95% CI: 0.17-1.13) and adverse events (OR = 0.88, 95% CI: 0.50-1.56) did not show significant differences between these two groups. Conclusion In summary, for patients with neuropathic keratitis, NGF treatment can promote corneal healing efficiency, effectively improve visual correction, and reduce disease progression and incidence of adverse events to a large extent. The clinical effect and safety are high, and it is worthy of clinical promotion and application.
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The potential applications of Artificial Intelligence (AI) in anaesthesia are expansive.~However, like any technological advancement, the integration of AI in anaesthetic practice comes with both benefits and potential risks. This article seeks to set out some of the advantages and disadvantages of the use of AI technologies within the field of anaesthesia. ⋯ Whilst AI within anaesthetic practice holds immense promise, there are substantial challenges which require careful consideration and ongoing evaluation. A collaborative approach will be required from healthcare staff, developers and regulators to promote the safe, responsible, and effective application of AI in anaesthesia practice.
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Aims/Background Generally, pelvic osteosarcoma has a worse prognosis compared with limb osteosarcoma. This study aims to create and validate a new nomogram for predicting the prognosis of pelvic osteosarcoma. Methods Clinical data of 62 patients derived from the Surveillance, Epidemiology, and End Results (SEER) database and 31 Chinese patients diagnosed with pelvic osteosarcoma were gathered. ⋯ A predictive nomogram was developed based on the data from the SEER cohort and validated in the Chinese cohort. The areas under the curves (AUCs) that are used to predict 1-year, 2-year, and 3-year survival rates were 0.81 (95% CI: 0.68-0.94), 0.75 (95% CI: 0.63-0.86), and 0.80 (95% CI: 0.70-0.89) in the training cohort, and 0.67 (95% CI: 0.30-1.04), 0.66 (95% CI: 0.43-0.90) and 0.71 (95% CI: 0.50-0.93) in the validation cohort. Conclusion The predictive nomogram constructed in this study facilitates accurate and effective prediction of the overall survival of patients with pelvic osteosarcoma and helps enhance the clinical decision-making process.