The integrated medical and elderly care model provides comprehensive medical and elderly care services by establishing medical facilities in elderly care institutions or forming close cooperative relationships with surrounding medical institutions. Currently， there are 87，000 paired partnerships established nationwide between medical and health institutions and elderly care service institutions， and more than 7，800 integrated medical and elderly care institutions have obtained the qualifications of medical and health institutions and completed elderly care service registration. This model not only meets the elderly’s healthcare needs but also provides life care， psychological support， and social activities， thereby improving their quality of life. However， the integrated medical and elderly care model also faces numerous ethical dilemmas in practice. This paper aimed to explore in depth the ethical dilemmas and countermeasures optimization in the work of elderly care institutions under this model， to promote the improvement of service quality， comprehensively guarantee the rights and interests of the elderly， and promote the healthy development of this model in practice. Under this model， the elderly care institutions not only bear the responsibility of providing long-term care and life services but also need to cooperate with medical institutions to provide healthcare and health management services for the elderly. By exploring the practical paths for elderly care institutions to address the ethical dilemmas faced with this model， feasible solutions were proposed to enhance the welfare of the elderly and promote the harmonious development of society.

Delirium is a common complication after stroke. Post-stroke delirium is associated with the poor outcome and increased mortality. This article reviews the screening tools, predictive factors and predictive models of post-stroke delirium.

Objective:To construct a predictive model of post-stroke delirium (PSD) in patients with acute ischemic stroke (AIS), and to verify its predictive value.Methods:Patients with AIS admitted to the Department of Neurology, Lianyungang Hospital Affiliated to Xuzhou Medical University from February to May 2022 were enrolled prospectively. They were divided into modeling group and validation group according to the order of enrollment. Depending on whether the patients had delirium or not, the patients in the modeling group were divided into delirium group and non-delirium group. The independent risk factors for PSD were determined by multivariable logistic regression analysis, and the prediction model of PSD was constructed accordingly. The predictive value of the model was verified by the receiver operating characteristic curve. Results:Three hundred and fifty patients with AIS were included in the modeling group, of which 71 (20.28%) had PSD. The validation group included 150 patients with AIS, and 36 of them (24.00%) had PSD. Multivariate logistic regression analysis showed that age (odds ratio [ OR] 1.036, 95% confidence interval [ CI] 1.000-1.074; P=0.050], National Institutes of Health Stroke Scale (NIHSS) score ( OR 1.607, 95% CI 1.438-1.797; P<0.001), neutrophil/lymphocyte ratio (NLR) ( OR 1.135, 95% CI 1.016-1.267; P=0.025), and atrial fibrillation ( OR 5.528, 95% CI 1.315-23.245; P=0.020) were the independent risk factors for PSD. The predictive model was Z=0.036×age+0.475×NIHSS score+0.127×NLR+1.710×assignment of atrial fibrillation - 10.160. The area under the curve of the model was 0.935, and the sensitivity and specificity were 97.2% and 82.5% respectively. Conclusion:This model can effectively predict the PSD risk of patients with AIS, with higher sensitivity and specificity, and can provide a basis for PSD screening of patients with AIS.