Delirium During Acute Events in Nursing Home Patients

The Clinical Role of Heart Rate Variability Assessment in Cognitively Impaired Patients and Its Applicability in Community Care Settings: A Systematic Review of the Literature

Heart rate variability (HRV) correlates well with a person's overall physiological function. Clinically, HRV is successfully used in acute care to identify impending infections, but little is known about its potential in the management of chronic diseases like cognitive decline/dementia. The aim of this study was to identify the best available knowledge about HRV in cognitively impaired populations that might be applied to improve clinical practice in community settings. We conducted a systematic literature search in PubMed, Embase, and Cochrane databases published from January 2009 to August 2022. Eligible studies were selected using Covidence and each study underwent qualitative assessment using the Mixed Method Appraisal Tool. At each stage of selection, each study was reviewed independently by two members of the team, and any disputes were discussed along the way. The literature identified that the brain regions controlling HRV are also those affected by dementias of Alzheimer's type (AD) and Lewy body types (DLB). HRV was impaired in both types, with DLB showing greater impairment in all HRV parameters compared to AD. No studies explored the temporal changes of HRV or its use in the clinical management of people with cognitive impairment (CI). The current lack of standardization of HRV recording and analysis limits its use in clinical practice. HRV may emerge as a potentially useful tool to identify people with early/preclinical memory impairment and help to differentiate AD from DLB. Longitudinal HRV measurement is emerging as a useful way to monitor disease progression and treatment response, and continuous HRV measurement may prove useful in the early identification of sepsis and its complications in patients no longer able to communicate their illness experiences.

Predicting postoperative delirium after hip arthroplasty for elderly patients using machine learning

BACKGROUND

Postoperative delirium (POD) is a common and severe complication in elderly hip-arthroplasty patients.

AIM

This study aims to develop and validate a machine learning (ML) model that determines essential features related to POD and predicts POD for elderly hip-arthroplasty patients.

METHODS

The electronic record data of elderly patients who received hip-arthroplasty surgery between January 2017 and April 2021 were enrolled as the dataset. The Confusion Assessment Method (CAM) was administered to the patients during their perioperative period. The feature section method was employed as a filter to determine leading features. The classical machine learning algorithms were trained in cross-validation processing, and the model with the best performance was built in predicting the POD. Metrics of the area under the curve (AUC), accuracy (ACC), sensitivity, specificity, and F1-score were calculated to evaluate the predictive performance.

RESULTS

476 Arthroplasty elderly patients with general anesthesia were included in this study, and the final model combined feature selection method mutual information (MI) and linear binary classifier using logistic regression (LR) achieved an encouraging performance (AUC = 0.94, ACC = 0.88, sensitivity = 0.85, specificity = 0.90, F1-score = 0.87) on a balanced test dataset.

CONCLUSION

The model could predict POD with satisfying accuracy and reveal important features of suffering POD such as age, Cystatin C, GFR, CHE, CRP, LDH, monocyte count, history of mental illness or psychotropic drug use and intraoperative blood loss. Proper preoperative interventions for these factors could reduce the incidence of POD among elderly patients.

Delirium in Nursing Home Residents: A Narrative Review

Delirium is an important component of the geriatric syndromes and has been recognized to negatively influence the prognosis of older people in hospital and in a post-acute setting. About 2–5% of older people world-wide live in nursing homes and are characterized by functional impairment, cognitive decline, dementia, comorbidities, and polypharmacotherapy, all factors which influence the development of delirium. However, in this setting, delirium remains often understudied. Therefore, in this narrative review, we aimed to describe the latest evidence regarding delirium screening tools, epidemiology characteristics, outcomes, risk factors, and preventions strategies in nursing homes.