Delirium is not associated with anticholinergic burden or polypharmacy in older patients on admission to an acute hospital:an observational case control study

BACKGROUND: Older people are commonly prescribed multiple medications, including medications with anticholinergic effects. Polypharmacy and anticholinergic medications may be risk factors for the development of delirium. METHODS: Patients from a medical admission unit who were over 70, with DSM-IV diagnosed delirium and patients without delirium, were investigated. Number of drugs prescribed on admission and anticholinergic burden using two scales (the Anticholinergic Cognitive Burden Scale [ACB] and the Anticholinergic Drug Scale [ADS]) were recorded from electronic prescribing records. The relationship and predictive ability of these were explored. RESULTS: The sample included 125 patients with DSM-IV diagnosed delirium and 122 patients without delirium. The mean age of the sample was 84.0 years. The median number of drugs prescribed was 7: 79.8 % were prescribed ≥5 drugs and 29.0 % ≥10 drugs. The median ACB score was 1 and the median ADS score was 1.5. 73.4 % of patients had an ACB score of ≥1 and 73.0 % had a ADS score ≥1. There was no association between: number of drugs prescribed, rate of polypharmacy, rate of excessive polypharmacy, ACB score and ADS score, and a diagnosis of delirium on admission. Only acetylcholinesterase inhibitor use predicted delirium (OR 3.86, p = 0.04) and the number of drugs prescribed was negatively correlated with age (spearman rho = −0.18, p = 0.006). CONCLUSION: Neither number of drugs prescribed, polypharmacy or anticholinergic burden were associated with delirium on admission, questioning the clinical usefulness of anticholinergic drug scales. Further research is needed to unpick fully the relationship between, drugs, anticholinergic burden, age, and prevalent delirium in older patients and whether there is any role for these scales in clinical practice. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12877-016-0336-9) contains supplementary material, which is available to authorized users

Induced frailty and acute sarcopenia are overlapping consequences of hospitalisation in older adults

OBJECTIVES: To determine the effects of hospitalisation upon frailty and sarcopenia. METHODS: Prospective cohort study at single UK hospital including adults ≥70 years-old admitted for elective colorectal surgery, emergency abdominal surgery, or acute infections. Serial assessments for frailty (Fried, Frailty Index, Clinical Frailty Scale [CFS]), and sarcopenia (handgrip strength, ultrasound quadriceps and/or bioelectrical impedance analysis, and gait speed and/or Short Physical Performance Battery) were conducted at baseline, 7 days post-admission/post-operatively, and 13 weeks post-admission/post-operatively. RESULTS: Eighty participants were included (mean age 79.2, 38.8% females). Frailty prevalence by all criteria at baseline was higher among medical compared to surgical participants. Median and estimated marginal CFS values and Fried frailty prevalence increased after 7 days, with rates returning towards baseline at 13 weeks. Sarcopenia incidence amongst those who did not have sarcopenia at baseline was 20.0%. However, some participants demonstrated improvements in sarcopenia status, and overall sarcopenia prevalence did not change. There was significant overlap between diagnoses with 37.3% meeting criteria for all four diagnoses at 7 days. CONCLUSIONS: Induced frailty and acute sarcopenia are overlapping conditions affecting older adults during hospitalisation. Rates of frailty returned towards baseline at 13 weeks, suggesting that induced frailty is reversible

Baseline Nutritional Status and In-Hospital Step Count are Associated with Muscle Quantity, Quality, and Function:Results of an Exploratory Study

This exploratory study aimed to assess associations of baseline nutritional status and in-hospital step count with muscle quantity, quality, and function. Seventy-nine participants aged ≥70 years (mean age 79.1 years, 44.3% female) were recruited (elective colorectal surgery, emergency abdominal surgery, and general medical patients with infections). Baseline nutrition (Mini Nutritional Assessment) and in-hospital step count (Fitbit Inspire devices) were assessed. Ultrasound quadriceps, bioelectrical impedance analysis, and physical function were assessed at baseline and 7 (±2) days and 13 (±1) weeks post-admission/post-operatively. Baseline nutritional status was associated with baseline rectus femoris ultrasound echogenicity (normal: 58.5, at risk: 68.5, malnourished: 81.2; p = 0.025), bilateral anterior thigh thickness (normal: 5.07 cm, at risk: 4.03 cm, malnourished: 3.05 cm; p = 0.021), and skeletal muscle mass (Sergi equation) (normal: 21.6 kg, at risk: 18.2 kg, malnourished: 12.0 kg; p = 0.007). Step count was associated with baseline patient-reported physical function (&lt;900 37.1, ≥900 44.5; p = 0.010). There was a significant interaction between nutrition, step count, and time for skeletal muscle mass (Janssen equation) (p = 0.022).</p

Baseline Nutritional Status and In-Hospital Step Count are Associated with Muscle Quantity, Quality, and Function:Results of an Exploratory Study

This exploratory study aimed to assess associations of baseline nutritional status and in-hospital step count with muscle quantity, quality, and function. Seventy-nine participants aged ≥70 years (mean age 79.1 years, 44.3% female) were recruited (elective colorectal surgery, emergency abdominal surgery, and general medical patients with infections). Baseline nutrition (Mini Nutritional Assessment) and in-hospital step count (Fitbit Inspire devices) were assessed. Ultrasound quadriceps, bioelectrical impedance analysis, and physical function were assessed at baseline and 7 (±2) days and 13 (±1) weeks post-admission/post-operatively. Baseline nutritional status was associated with baseline rectus femoris ultrasound echogenicity (normal: 58.5, at risk: 68.5, malnourished: 81.2; p = 0.025), bilateral anterior thigh thickness (normal: 5.07 cm, at risk: 4.03 cm, malnourished: 3.05 cm; p = 0.021), and skeletal muscle mass (Sergi equation) (normal: 21.6 kg, at risk: 18.2 kg, malnourished: 12.0 kg; p = 0.007). Step count was associated with baseline patient-reported physical function (&lt;900 37.1, ≥900 44.5; p = 0.010). There was a significant interaction between nutrition, step count, and time for skeletal muscle mass (Janssen equation) (p = 0.022).</p

Age and frailty are independently associated with increased COVID-19 mortality and increased care needs in survivors: results of an international multi-centre study

Introduction: Increased mortality has been demonstrated in older adults with COVID-19, but the effect of frailty has been unclear. Methods: This multi-centre cohort study involved patients aged 18 years and older hospitalised with COVID-19, using routinely collected data. We used Cox regression analysis to assess the impact of age, frailty, and delirium on the risk of inpatient mortality, adjusting for sex, illness severity, inflammation, and co-morbidities. We used ordinal logistic regression analysis to assess the impact of age, Clinical Frailty Scale (CFS), and delirium on risk of increased care requirements on discharge, adjusting for the same variables. Results: Data from 5,711 patients from 55 hospitals in 12 countries were included (median age 74, IQR 54–83; 55.2% male). The risk of death increased independently with increasing age (&gt;80 vs 18–49: HR 3.57, CI 2.54–5.02), frailty (CFS 8 vs 1–3: HR 3.03, CI 2.29–4.00) inflammation, renal disease, cardiovascular disease, and cancer, but not delirium. Age, frailty (CFS 7 vs 1–3: OR 7.00, CI 5.27–9.32), delirium, dementia, and mental health diagnoses were all associated with increased risk of higher care needs on discharge. The likelihood of adverse outcomes increased across all grades of CFS from 4 to 9. Conclusions: Age and frailty are independently associated with adverse outcomes in COVID-19. Risk of increased care needs was also increased in survivors of COVID-19 with frailty or older age

Increasing frailty is associated with higher prevalence and reduced recognition of delirium in older hospitalised inpatients: results of a multi-centre study

Purpose: Delirium is a neuropsychiatric disorder delineated by an acute change in cognition, attention, and consciousness. It is common, particularly in older adults, but poorly recognised. Frailty is the accumulation of deficits conferring an increased risk of adverse outcomes. We set out to determine how severity of frailty, as measured using the CFS, affected delirium rates, and recognition in hospitalised older people in the United Kingdom. Methods: Adults over 65 years were included in an observational multi-centre audit across UK hospitals, two prospective rounds, and one retrospective note review. Clinical Frailty Scale (CFS), delirium status, and 30-day outcomes were recorded. Results: The overall prevalence of delirium was 16.3% (483). Patients with delirium were more frail than patients without delirium (median CFS 6 vs 4). The risk of delirium was greater with increasing frailty [OR 2.9 (1.8–4.6) in CFS 4 vs 1–3; OR 12.4 (6.2–24.5) in CFS 8 vs 1–3]. Higher CFS was associated with reduced recognition of delirium (OR of 0.7 (0.3–1.9) in CFS 4 compared to 0.2 (0.1–0.7) in CFS 8). These risks were both independent of age and dementia. Conclusion: We have demonstrated an incremental increase in risk of delirium with increasing frailty. This has important clinical implications, suggesting that frailty may provide a more nuanced measure of vulnerability to delirium and poor outcomes. However, the most frail patients are least likely to have their delirium diagnosed and there is a significant lack of research into the underlying pathophysiology of both of these common geriatric syndromes

Additional file 1: Figure S1. of Delirium is not associated with anticholinergic burden or polypharmacy in older patients on admission to an acute hospital: an observational case control study

Flowchart of selection of study participants. Flowchart demonstrating selection of participants to the delirium and no-delirium groups and the number of patients recruited. The number of patients excluded and not recruited are also displayed and the reason they were not included. (DOCX 30 kb