Objective: To explore the feasibility and safety of integrating the geriatric intensive care unit (GICU) into the friendly management model of the elderly critically ill patients.
Methods: A prospective controlled study was conducted. Patients with elderly critically ill admitted to the GICU and the general intensive care unit (ICU) of Jintan First People's Hospital of Changzhou from December 2021 to May 2023 were enrolled. Patients in the ICU group received the traditional intensive care and nursing mode. In addition to the ICU group basic medical care measures, the patients in the GICU group were treated with friendly management models such as flexible visitation, diagnosis and treatment environment optimization, caring diagnosis and treatment, and family participation in hospice care according to their condition assessment. The gender, age, main diagnosis, and acute physiology and chronic health evaluation II (APACHE II) at admission were recorded and compared between the two groups. During the treatment period, the incidence of nosocomial infection, unplanned extubation, falling out of bed/fall, unexpected readmission to ICU/GICU, and ICU/GICU mortality, the incidence of post-intensive care syndrome (PICS), the satisfaction rate of patients/families with medical care, and the satisfaction rate of patients/families with diagnosis and treatment environment were recorded and compared between the two groups.
Results: According to the admission criteria for ICU and GICU, as well as the willingness of the patients and/or their families, a total of 59 patients were finally included in the ICU group, and 48 patients were enrolled in the GICU group. There were no significantly differences in gender, age, main diagnosis and APACHE II score between the two groups, and there were comparability. There were no significantly differences in the incidence of adverse events such as nosocomial infection [13.6% (8/59) vs. 12.5% (6/48)], unplanned extubation [5.1% (3/59) vs. 6.2% (3/48)], falling out of bed/fall [3.4% (2/59) vs. 0% (0/48)], unexpected readmission to ICU/GICU [8.5% (5/59) vs. 10.4% (5/48)], and ICU/GICU mortality [6.8% (4/59) vs. 6.2 (3/48)] between the ICU group and GICU group (all P > 0.05). Compared with the ICU group, the incidence of PICS in GICU group was significantly lower [8.3% (4/48) vs. 25.4% (15/59), P < 0.05], the satisfaction rate of patients/families with medical care [89.6% (43/48) vs. 74.6% (44/59)] and satisfaction rate of patients/families with diagnosis and treatment environment [87.5% (42/48) vs. 67.8% (40/59)] were significantly increased (both P < 0.05).
Conclusions: The use GICU as a friendly management model for elderly critically ill patients is feasible and safe, and it is worthy of further exploration and research.
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http://dx.doi.org/10.3760/cma.j.cn121430-20240109-00024 | DOI Listing |
JAMA Netw Open
January 2025
Coronavirus and Other Respiratory Viruses Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia.
Importance: Multisystem inflammatory syndrome in children (MIS-C) is an uncommon but severe hyperinflammatory illness that occurs 2 to 6 weeks after SARS-CoV-2 infection. Presentation overlaps with other conditions, and risk factors for severity differ by patient. Characterizing patterns of MIS-C presentation can guide efforts to reduce misclassification, categorize phenotypes, and identify patients at risk for severe outcomes.
View Article and Find Full Text PDFJ Am Med Inform Assoc
January 2025
Department of Computer Science, Duke University, Durham, NC 27708, United States.
Objective: Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to bridge the gap between these 2 categories by building on modern interpretable machine learning (ML) techniques to design interpretable mortality risk scores that are as accurate as black boxes.
Material And Methods: We developed a new algorithm, GroupFasterRisk, which has several important benefits: it uses both hard and soft direct sparsity regularization, it incorporates group sparsity to allow more cohesive models, it allows for monotonicity constraint to include domain knowledge, and it produces many equally good models, which allows domain experts to choose among them.
Front Cell Infect Microbiol
January 2025
Department of Thoracic Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan.
Introduction: Invasive pulmonary aspergillosis (IPA) increases the risk of mortality of critically ill patients. Diagnostic criteria specifically targeting patients in intensive care units(ICUs) have been developed to improve diagnostic sensitivity. This study investigated health outcomes among patients in ICUs with Aspergillus isolates identified using bronchoscopy.
View Article and Find Full Text PDFJ Intensive Med
January 2025
Department of Critical Care Medicine, The First Hospital of Jilin University, Changchun, Jilin, China.
Background: The effect of the modality of hydrocortisone administration on clinical outcomes in patients with septic shock remains uncertain. This systematic review and meta-analysis evaluate the impact of intermittent bolus and continuous infusion of hydrocortisone on these outcomes.
Methods: We searched the PubMed, Embase databases, and Cochrane Library for randomized controlled trials (RCTs) and cohort studies published from inception to January 1, 2023.
J Intensive Med
January 2025
Department of Critical Care Medicine, Jiangsu Provincial Key Laboratory of Critical Care Medicine, Trauma Center, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Background: Extracorporeal membrane oxygenation (ECMO) has been proven to be a support method and technology for patients with cardiopulmonary failure. However, the transport of patients under ECMO support is challenging given the high-risk technical maneuvers and patient-care concerns involved. Herein, we examined the safety of ECMO during the transport of critically ill patients and its impact on mortality rates, to provide more secure and effective transport strategies in clinical practice.
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