Objectives: To estimate the prevalence of probable delirium in long-term care (LTC) and complex continuing care (CCC) settings and to describe the resident characteristics associated with probable delirium.
Design: Population-based cross-sectional study using routinely collected administrative health data.
Setting And Participants: All LTC and CCC residents in Ontario, Canada, assessed with the Resident Assessment Instrument-Minimum Dataset (RAI-MDS) assessment between July 1, 2016, and December 31, 2016 (LTC n=86,454, CCC n=10,217).
Methods: Probable delirium was identified via the delirium Clinical Assessment Protocol on the RAI-MDS assessment, which is triggered when individuals display at least 1 of 6 delirium symptoms that are of recent onset and different from their usual functioning. RAI-MDS assessments were linked to demographic and health services utilization databases to ascertain resident demographics and health status. Multivariable logistic regression was used to identify characteristics associated with probable delirium, with adjusted odds ratios (ORs) and 95% confidence intervals (CIs) reported.
Results: Delirium was probable in 3.6% of LTC residents and 16.5% of CCC patients. LTC patients displayed fewer delirium symptoms than CCC patients. The most common delirium symptom in LTC was periods of lethargy (44.6% of delirium cases); in CCC, it was mental function varying over the course of the day (63.5% of delirium cases). The odds of probable delirium varied across individual demographics and health characteristics, with increased health instability having the strongest association with the outcome in both care settings (LTC: OR 30.4, 95% CI 26.2-35.3; CCC: OR 21.0, 95% CI 16.7-26.5 for high vs low instability).
Conclusions And Implications: There were differences in the presentation and burden of delirium symptoms between LTC and CCC, potentially reflecting differences in delirium severity or symptom identification. Several risk factors for probable delirium in LTC and CCC were identified that may be amenable to interventions to prevent this highly distressing condition.
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http://dx.doi.org/10.1016/j.jamda.2021.05.032 | DOI Listing |
Alzheimers Res Ther
January 2025
Department of Epidemiology and Healthcare Atlas, Central Research Institute of Ambulatory Health Care in Germany, Berlin, Germany.
Background: Many risk factors for dementia have been identified, but the timing of risk is less well understood. Here, we analyzed risk factors in a case-control study covering 10 years before an incident dementia diagnosis.
Methods: We designed a case-control study using insurance claims of outpatient consultations of patients with German statutory health insurance between January 1, 2012, and December 31, 2022.
BMC Surg
January 2025
Department of Anaesthesiology, Central People's Hospital of Zhanjiang, Zhanjiang, Guangdong, China.
Objective: The objective of this study was to develop and validate a clinically applicable nomogram for predicting the risk of delirium following hepatectomy.
Methods: We applied the LASSO regression model to identify the independent risk factors associated with POD. Subsequently, we utilized R software to develop and validate a nomogram model capable of accurately predicting the incidence of POD.
BMC Neurol
January 2025
Institute for Intensive Care Medicine, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
Background: Delirium is a common complication in patients at the intensive care unit (ICU) and is associated with prolonged ICU-stay and hospitalization and with increased morbidity. The impact of ICU-delirium on long-term survival is not clearly understood.
Methods: This retrospective single center observational study was conducted at the Institute of Intensive Care Medicine at the University Hospital Zurich, Switzerland.
Crit Care Med
December 2024
Department of Psychiatry and Human Behavior, Brown University, Alpert Medical School, Providence, RI.
Objectives: Neurocritically ill patients are at high risk for developing delirium, which can worsen the long-term outcomes of this vulnerable population. However, existing delirium assessment tools do not account for neurologic deficits that often interfere with conventional testing and are therefore unreliable in neurocritically ill patients. We aimed to determine the accuracy and predictive validity of the Fluctuating Mental Status Evaluation (FMSE), a novel delirium screening tool developed specifically for neurocritically ill patients.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Anesthesia, College of Health Sciences, Debre Tabor University, PO. Box: 272, Debre Tabor, Ethiopia.
Postoperative delirium has the potential to impact individuals of all age groups, with a significant emphasis on the elderly population. Its presence leads to an increase in surgical morbidity and mortality rates, as well as a notable prolongation of hospital stays. However, there is a lack of research regarding the prevalence, risk factors, and implications of postoperative delirium in developing nations like Ethiopia, which affects both patients and healthcare institutions.
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