The Mini-Mental State Examination (MMSE), a brief test to assess cognitive status, is heavily influenced by age and education. It was administered to 1019 elderly subjects (aged 65-89 years) living in three different Italian cities. A statistical non-linear regression model was built up in order to obtain adjustment coefficients to reduce the influence of demographic variables on the MMSE raw scores. Age and educational level were significantly and independently associated with the MMSE score. Results of a multiple linear regression with transformation of age and education provided adjustment coefficients of the MMSE raw scores. Data from this study will ameliorate the overall reliability of MMSE as a screening test for cognitive impairment in elderly people.

The quality of life of community-dwelling elderly people is significantly linked to sensory impairment, which can be detected through simple physical examination. Mood level and social relationships are particularly affected by visual impairment, whereas self-sufficiency in daily living is more strongly related to hearing impairment.

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BackgroundTo date, delirium prevalence in adult acute hospital populations has been estimated generally from pooled findings of single-center studies and/or among specific patient populations. Furthermore, the number of participants in these studies has not exceeded a few hundred. To overcome these limitations, we have determined, in a multicenter study, the prevalence of delirium over a single day among a large population of patients admitted to acute and rehabilitation hospital wards in Italy.MethodsThis is a point prevalence study (called “Delirium Day”) including 1867 older patients (aged 65 years or more) across 108 acute and 12 rehabilitation wards in Italian hospitals. Delirium was assessed on the same day in all patients using the 4AT, a validated and briefly administered tool which does not require training. We also collected data regarding motoric subtypes of delirium, functional and nutritional status, dementia, comorbidity, medications, feeding tubes, peripheral venous and urinary catheters, and physical restraints.ResultsThe mean sample age was 82.0 ± 7.5 years (58 % female). Overall, 429 patients (22.9 %) had delirium. Hypoactive was the commonest subtype (132/344 patients, 38.5 %), followed by mixed, hyperactive, and nonmotoric delirium. The prevalence was highest in Neurology (28.5 %) and Geriatrics (24.7 %), lowest in Rehabilitation (14.0 %), and intermediate in Orthopedic (20.6 %) and Internal Medicine wards (21.4 %). In a multivariable logistic regression, age (odds ratio [OR] 1.03, 95 % confidence interval [CI] 1.01–1.05), Activities of Daily Living dependence (OR 1.19, 95 % CI 1.12–1.27), dementia (OR 3.25, 95 % CI 2.41–4.38), malnutrition (OR 2.01, 95 % CI 1.29–3.14), and use of antipsychotics (OR 2.03, 95 % CI 1.45–2.82), feeding tubes (OR 2.51, 95 % CI 1.11–5.66), peripheral venous catheters (OR 1.41, 95 % CI 1.06–1.87), urinary catheters (OR 1.73, 95 % CI 1.30–2.29), and physical restraints (OR 1.84, 95 % CI 1.40–2.40) were associated with delirium. Admission to Neurology wards was also associated with delirium (OR 2.00, 95 % CI 1.29–3.14), while admission to other settings was not.ConclusionsDelirium occurred in more than one out of five patients in acute and rehabilitation hospital wards. Prevalence was highest in Neurology and lowest in Rehabilitation divisions. The “Delirium Day” project might become a useful method to assess delirium across hospital settings and a benchmarking platform for future surveys.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0649-8) contains supplementary material, which is available to authorized users.

the Geriatric Index of Comorbidity, a measure of comorbidity assuming that both number of diseases and occurrence of very severe diseases are determinants of health, has the greatest concurrent validity with disability and is the best predictor of mortality.

Attempts towards standardization in terminology, or at least awareness of differences across languages and specialties, will help cross-talk among clinicians and researchers.

ObjectivesSeveral physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage.SettingRetrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020.ParticipantsConsecutive patients≥18 years admitted for COVID-19.Main outcome measuresSimple clinical and laboratory findings readily available after triage were compared by patients’ survival status (‘dead’ vs ‘alive’), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS).ResultsMean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0–1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO2/FiO2 (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001).ConclusionsThe COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care.

Disease-induced disability may reflect a condition of biological inability to react to acute diseases (i.e., frailty), and should be assessed as a relevant prognostic indicator.