Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros

Base de dados
Tipo de documento
Ano de publicação
Intervalo de ano de publicação
1.
Psychol Health Med ; : 1-7, 2022 Dec 28.
Artigo em Inglês | MEDLINE | ID: mdl-36578132

RESUMO

China has implemented a strict isolation system in hospitals since the COVID-19 pandemic, that adversely affected the psychology of inpatients and their caregivers. Face-to-face, semi-structured interviews with 22 stroke inpatients from two municipal hospitals were conducted to explore the psychological, emotional and related support needs of stroke inpatients and their family caregivers under this environment. Results which showed that external support for stroke inpatients and their family caregivers was insufficient highlight the necessity for developing specific nursing interventions that meet the psychological and emotional needs of inpatients and the caregivers.

2.
Front Neurol ; 14: 1254090, 2023.
Artigo em Inglês | MEDLINE | ID: mdl-37719759

RESUMO

Objective: The objective of this study is to systematically evaluate prediction models for post-thrombectomy brain edema in acute ischemic stroke (AIS) patients. This analysis aims to equip clinicians with evidence-based guidance for the selection of appropriate prediction models, thereby facilitating the early identification of patients at risk of developing brain edema post-surgery. Methods: A comprehensive literature search was conducted across multiple databases, including PubMed, Web of Science, Embase, The Cochrane Library, CNKI, Wanfang, and Vip, aiming to identify studies on prediction models for post-thrombectomy brain edema in AIS patients up to January 2023. Reference lists of relevant articles were also inspected. Two reviewers independently screened the literature and extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) and the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines were employed to assess study bias and literature quality, respectively. We then used random-effects bivariate meta-analysis models to summarize the studies. Results: The review included five articles, yielding 10 models. These models exhibited a relatively high risk of bias. Random effects model demonstrated that the AUC was 0.858 (95% CI 0.817-0.899). Conclusion: Despite the promising discriminative ability shown by studies on prediction models for post-thrombectomy brain edema in AIS patients, concerns related to a high risk of bias and limited external validation remain. Future research should prioritize the external validation and optimization of these models. There is an urgent need for large-scale, multicenter studies to develop robust, user-friendly models for real-world clinical application. Systematic review registration: https://www.crd.york.ac.uk, unique Identifier: CRD42022382790.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA