scholarly journals In-hospital delirium risk assessment, diagnosis and management; medications to avoid

2013 ◽  
pp. 98-102
Author(s):  
Andrew Clegg ◽  
John Young

Background: Delirium is a common, but potentially preventable complication of acute illness that is associated with important adverse outcomes including increased length of hospital admission, risk of dementia and admission to long-term care. In-hospital risk assessment and diagnosis: Age over 65, severe illness, current hip fracture and presence of cognitive impairment or dementia are important risk factors for delirium. Assess people with any of these risk factors for recent changes or fluctuations in behaviour that might indicate delirium. If any indicators are present, complete a full cognitive assessment to confirm the diagnosis of delirium. In-hospital risk management: Multicomponent delirium prevention interventions can reduce the incidence of delirium in hospital by around one third and should be provided to people with any of the important risk factors that do not have delirium at admission. A medication review that considers both the number and type of prescribed medications is an important part of the multicomponent delirium prevention intervention. Which medications to avoid in people at risk of delirium: For people at risk of delirium, avoid new prescriptions of benzodiazepines or consider reducing or stopping these medications where possible. Opioids should be prescribed with caution in people at risk of delirium but this should be tempered by the observation that untreated severe pain can itself trigger delirium. Caution is also required when prescribing dihydropyridines and antihistamine H1 antagonists for people at risk of delirium and considered individual patient assessment is advocated. Conclusion: Delirium is common, distressing to patients, relatives and carers and is associated with important adverse outcomes. Multicomponent delirium prevention interventions can reduce the incidence of delirium by approximately one third and usually incorporate a medication review. Identification of which medications to avoid in people at risk of delirium will help guide evidence-based decision making.

2020 ◽  
Author(s):  
Kyoung Ja Moon ◽  
Chang-Sik Son ◽  
Jong-Ha Lee ◽  
Mina Park

BACKGROUND Long-term care facilities demonstrate low levels of knowledge and care for patients with delirium and are often not properly equipped with an electronic medical record system, thereby hindering systematic approaches to delirium monitoring. OBJECTIVE This study aims to develop a web-based delirium preventive application (app), with an integrated predictive model, for long-term care (LTC) facilities using artificial intelligence (AI). METHODS This methodological study was conducted to develop an app and link it with the Amazon cloud system. The app was developed based on an evidence-based literature review and the validity of the AI prediction model algorithm. Participants comprised 206 persons admitted to LTC facilities. The app was developed in 5 phases. First, through a review of evidence-based literature, risk factors for predicting delirium and non-pharmaceutical contents for preventive intervention were identified. Second, the app, consisting of several screens, was designed; this involved providing basic information, predicting the onset of delirium according to risk factors, assessing delirium, and intervening for prevention. Third, based on the existing data, predictive analysis was performed, and the algorithm developed through this was calculated at the site linked to the web through the Amazon cloud system and sent back to the app. Fourth, a pilot test using the developed app was conducted with 33 patients. Fifth, the app was finalized. RESULTS We developed the Web_DeliPREVENT_4LCF for patients of LTC facilities. This app provides information on delirium, inputs risk factors, predicts and informs the degree of delirium risk, and enables delirium measurement or delirium prevention interventions to be immediately implemented with a verified tool. CONCLUSIONS This web-based application is evidence-based and offers easy mobilization and care to patients with delirium in LTC facilities. Therefore, the use of this app improves the unrecognized of delirium and predicts the degree of delirium risk, thereby helping initiatives for delirium prevention and providing interventions. This would ultimately improve patient safety and quality of care. CLINICALTRIAL none


2021 ◽  
Vol 8 ◽  
Author(s):  
Siti Setiati ◽  
Czeresna Heriawan Soejono ◽  
Kuntjoro Harimurti ◽  
Noto Dwimartutie ◽  
I. G. P. Suka Aryana ◽  
...  

Background: National long-term care development requires updated epidemiological data related to frailty. We aimed to find the prevalence of frailty and its associated factors among Indonesian elderly.Methods: We conducted first-phase cross-sectional analysis of Indonesia Longitudinal Aging Study (INALAS) data collected from community-dwelling outpatients aged 60 years and older without acute illness in nine geriatric service care centres. Descriptive, bivariate and multivariate analyses were conducted.Results: Among 908 elderly in this study, 15.10% were robust, 66.20% were pre-frail, and 18.70% were frail. Functional dependence was associated with frailty among Indonesian elderly (OR 5.97, 95% CI 4.04–8.80). Being depressed and at risk for malnutrition were also associated with frailty with OR 2.54, 95% CI 1.56–4.12, and OR 2.56, 95% CI 1.68–3.90, respectively. Prior history of fall (OR 1.77, 95% CI 1.16–2.72) and hospitalization (OR 1.46, 95% CI 0.97–2.20) in the previous 12 months were associated with frailty. There is also significant association between poly pharmacy and frailty (OR 2.42, 95% CI 1.50–3.91).Conclusion: Approximately one in five Indonesian community-dwelling elderly was frail. Frailty is associated with functional dependence, being at risk for malnutrition or being malnourished, depression, history of fall, history of hospitalization, and poly pharmacy. There may be bidirectional relationships between the risk factors and frailty. The development of long-term care in Indonesia should be considered, without forcing the elderly who need it.


2020 ◽  
Vol 26 (9) ◽  
pp. 244-247
Author(s):  
Beverley Bostock

With evidence supporting the link between cardiovascular disease and myriad risk factors, Beverley Bostock considers how best to identify and support at-risk individuals through long-term, multidisciplinary management.


Author(s):  
Chiaki Ura ◽  
Tsuyoshi Okamura ◽  
Akinori Takase ◽  
Masaya Shimmei ◽  
Yukan Ogawa

2021 ◽  
Vol 36 (3) ◽  
pp. 287-298
Author(s):  
Jonathan Bergman ◽  
Marcel Ballin ◽  
Anna Nordström ◽  
Peter Nordström

AbstractWe conducted a nationwide, registry-based study to investigate the importance of 34 potential risk factors for coronavirus disease 2019 (COVID-19) diagnosis, hospitalization (with or without intensive care unit [ICU] admission), and subsequent all-cause mortality. The study population comprised all COVID-19 cases confirmed in Sweden by mid-September 2020 (68,575 non-hospitalized, 2494 ICU hospitalized, and 13,589 non-ICU hospitalized) and 434,081 randomly sampled general-population controls. Older age was the strongest risk factor for hospitalization, although the odds of ICU hospitalization decreased after 60–69 years and, after controlling for other risk factors, the odds of non-ICU hospitalization showed no trend after 40–49 years. Residence in a long-term care facility was associated with non-ICU hospitalization. Male sex and the presence of at least one investigated comorbidity or prescription medication were associated with both ICU and non-ICU hospitalization. Three comorbidities associated with both ICU and non-ICU hospitalization were asthma, hypertension, and Down syndrome. History of cancer was not associated with COVID-19 hospitalization, but cancer in the past year was associated with non-ICU hospitalization, after controlling for other risk factors. Cardiovascular disease was weakly associated with non-ICU hospitalization for COVID-19, but not with ICU hospitalization, after adjustment for other risk factors. Excess mortality was observed in both hospitalized and non-hospitalized COVID-19 cases. These results confirm that severe COVID-19 is related to age, sex, and comorbidity in general. The study provides new evidence that hypertension, asthma, Down syndrome, and residence in a long-term care facility are associated with severe COVID-19.


2021 ◽  
pp. 193229682199111
Author(s):  
Jacob M. Appel

The COVID-19 pandemic raised distinct challenges in the field of scarce resource allocation, a long-standing area of inquiry in the field of bioethics. Policymakers and states developed crisis guidelines for ventilator triage that incorporated such factors as immediate prognosis, long-term life expectancy, and current stage of life. Often these depend upon existing risk factors for severe illness, including diabetes. However, these algorithms generally failed to account for the underlying structural biases, including systematic racism and economic disparity, that rendered some patients more vulnerable to these conditions. This paper discusses this unique ethical challenge in resource allocation through the lens of care for patients with severe COVID-19 and diabetes.


2021 ◽  
Vol 28 (Supplement_1) ◽  
Author(s):  
V Korobkova ◽  
AL Komarov ◽  
OO Shakhmatova ◽  
MV Andreevskaya ◽  
EB Yarovaya ◽  
...  

Abstract Funding Acknowledgements Type of funding sources: None. Background Upper gastrointestinal bleeding (UGIB) is the most common hemorrhagic complication in stable CAD patients receiving antithrombotic therapy. It seems that atherosclerotic burden may increase the overall bleeding frequency. However, this factor has never been taken into account with UGIB risk assessment. We aimed to assess the predictive value of atherosclerotic burden (peripheral atherosclerosis – PAD and abdominal aortic aneurysm - AAA) for UGIB in patients with stable CAD receiving long-term antithrombotic therapy. Patients and Methods. A single center prospective Registry of Long-term AnTithrombotic TherApy (REGATTA-1 NCT04347200) included 934 pts with stable CAD (78.6% males, median age 61 [IQR 53-68] yrs). 77,3 %  of patients received dual antiplatelet therapy due to recent PCI with a switch to aspirin monotherapy after 6 months. 17,6% of patients received aspirin only, 5,1 % of patients received oral anticoagulants because of concomitant atrial fibrillation. Risk assessment of UGIB was performed according to the 2015 European Society of Cardiology guidelines (we were not able to identify only Helicobacter pylori infection). Additional ultrasound screening for PAD (lower limbs and cerebrovascular beds) and AAA was applied. The primary outcome was any overt UGIB (BARC ≥2). Results  The frequency of PAD was 18,8%, AAA – 2,4%, PAD and/or AAA -  20,5%. In a total 2335 person-years of follow-up (median follow-up - 2,5 yrs, IQR 1,1 – 5.1), UGIB occurred in 51 patients (incidence at 1 year 1,9 per 100 patients).  The median time to first occurrence of UGIB was 72 [IQR 13-214] days. Comparing the Kaplan-Meyer curves, the UGIB developed three times more often in patients with coexisted PAD and/or AAA vs isolated CAD (19.8% vs 6.5%, Log-Rank p = 0.00006). The difference remains consisted in regression model taking in account 2015 ESC panel of UGIB risk factors (OR 3.4; CI 1.7–6.9, p = 0,0005). Conclusions Atherosclerotic burden (concomitant PAD and/or AAA) is an independent predictor of UGIB in patients with stable CAD receiving long-term antithrombotic therapy.


2011 ◽  
Vol 18 (3) ◽  
pp. 572-577 ◽  
Author(s):  
Buichi Tanaka ◽  
Mio Sakuma ◽  
Masae Ohtani ◽  
Jinichi Toshiro ◽  
Tadashi Matsumura ◽  
...  

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