BackgroundAlthough a number of studies have suggested that the use of Telemonitoring (TM) in patients with Chronic Obstructive Pulmonary Disease (COPD) can be useful and efficacious, its real utility in detecting Acute Exacerbation (AE) signaling the need for prompt treatment is not entirely clear. The current study aimed to investigate the benefits of a TM system in managing AE in advanced-stage COPD patients to improve their Health-Related Quality of Life (HRQL) and to reduce utilization of healthcare services.MethodsA 12-month Randomised Controlled Trial (RCT) was conducted in the Veneto region (Italy). Adult patients diagnosed with Class III-IV COPD in accordance with the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification were recruited and provided a TM system to alert the clinical staff via a trained operator whenever variations in respiratory parameters fell beyond the individual’s normal range. The study’s primary endpoint was HRQL, measured by the Italian version of the two Short Form 36-item Health Survey (SF36v2). Its secondary endpoints were: scores on the Hospital Anxiety and Depression Scale (HADS); the number and duration of hospitalizations; the number of readmissions; the number of appointments with a pulmonary specialist; the number of visits to the emergency department; and the number of deaths.ResultsThree hundred thirty-four patients were enrolled and randomized into two groups for a 1 year period. At its conclusion, changes in the SF36 Physical and Mental Component Summary scores did not significantly differ between the TM and control groups [(-2.07 (8.98) vs -1.91 (7.75); p = 0.889 and -1.08 (11.30) vs -1.92 (10.92); p = 0.5754, respectively]. Variations in HADS were not significantly different between the two groups [0.85 (3.68) vs 0.62 (3.6); p = 0.65 and 0.50 (4.3) vs 0.72 (4.5); p = 0.71]. The hospitalization rate for AECOPD and/or for any cause was not significantly different in the two groups [IRR = 0.89 (95% CI 0.79–1,04); p = 0.16 and IRR = 0.91 (95% CI 0,75 – 1.04); p = 0.16, respectively]. The readmission rate for AECOPD and/or any cause was, however, significantly lower in the TM group with respect to the control one [IRR = 0.43 (95% CI 0.19–0.98); p = 0.01 and 0.46 (95% CI 0.24–0.89); p = 0.01, respectively].ConclusionStudy results showed that in areas where medical services are well established, TM does not significantly improve HRQL in patients with COPD who develop AE. Although not effective in reducing hospitalizations, TM can nevertheless facilitate continuity of care during hospital-to-home transition by reducing the need for early readmission.Trial registrationRetrospectively registered on January 2012, ClinicalTrials.gov Identifier: NCT01513980.

Context: Both frailty and multimorbidity are strong predictors of clinical endpoints for older people. In Italy, the interventions targeting chronicity are mainly based on the treatment of diseases: sufficient epidemiological literature is available about these strategies. Less is known about the territorial distribution of the frailty status.Aims: To estimate the prevalence of frailty in older people (65+) and to evaluate the relationship between frailty and multimorbidity.Methods and material: A group of general practitioners working in Veneto (Italy) was enrolled on a voluntary basis. Older individuals were both community dwelling and institutionalized patients, that is, the older people normally followed by Italian general practitioners. A centrally randomized sample was extracted from the pool of physician-assisted elderly. Each doctor evaluated the frailty status through the CSHA Clinical Frailty Scale and the multimorbidity status through the Charlson score (Frailty = CSHA Clinical Frailty Scale’s score >4; serious multimorbidity = Charlson score ≥4). Prevalence and its confidence interval (CI) 95% were evaluated through the Agresti’s method for proportions. The relation between frailty and multimorbidity was studied through a logistic regression model adjusted for age and sex.Results: Fifty-three physicians were enrolled, whose population of elderly individuals (N = 82919) was highly representative of the population of Veneto. The prevalence of frailty in the randomized sample of 2407 older people was 23.18% (CI 95%: 21.53%–24.91%). Sex was shown to be a strong predictor of frailty (female status OR = 1.58 p < .0001) and multimorbidity was shown to be an independent predictor only for individuals <85 years of age.Conclusions: In Veneto, more than 20% of elderly people are frail. Physicians should pay close attention to frailty and multimorbidity because both are important prognostic factors toward clinical endpoints relevant to territorial care. The CSHA Clinical Frailty Scale (easy and quick) should become part of their professional routine.

Predicting the risk of cardiovascular complications, in particular heart failure hospitalisation (HHF), can improve the management of type 2 diabetes (T2D). Most predictive models proposed so far rely on clinical data not available at the higher Institutional level. Therefore, it is of interest to assess the risk of HHF in people with T2D using administrative claims data only, which are more easily obtainable and could allow public health systems to identify high-risk individuals. In this paper, the administrative claims of > 175,000 patients with T2D were used to develop a new risk score for HHF based on Cox regression. Internal validation on the administrative data cohort yielded satisfactory results in terms of discrimination (max AUROC = 0.792, C-index = 0.786) and calibration (Hosmer–Lemeshow test p value < 0.05). The risk score was then tested on data gathered from two independent centers (one diabetes outpatient clinic and one primary care network) to demonstrate its applicability to different care settings in the medium-long term. Thanks to the large size and broad demographics of the administrative dataset used for training, the proposed model was able to predict HHF without significant performance loss concerning bespoke models developed within each setting using more informative, but harder-to-acquire clinical variables.

No abstract

The non-urgent patients in the Emergency Departement (ED) are a widespread challenging problem. In the present study we investigated the relationship between the non-urgent patients in ED and the primary care services in an urban area (Mestre- Venezia). An alternative management of these patients supported by a group of family doctors in a separate laboratory, close to the ED, and using the ED triage system, has also been studied. The management of these patients in terms of waiting time, percent of patients who have left the ED without being seen and inappropriate dismissions, was sactisfactory. Otherwise 50% of the patients were sent to an urgent specialistic advisory in spite of their non-urgent problem presented. The involvement of primary care providers and a reasonable limit to an unjustified specialistic advisory are requiered to achieve a reliable alternative management for non-urgent patients in ED

Predicting the risk of cardiovascular complications, in particular heart failure hospitalisation (HHF), can improve the management of type 2 diabetes (T2D). Most predictive models proposed so far rely on clinical data not available at the higher Institutional level. Therefore, it is of interest to assess the risk of HHF in people with T2D using administrative claims data only, which are more easily obtainable and could allow public health systems to identify high-risk individuals. In this paper, the administrative claims of >175,000 patients with T2D were used to develop a new risk score for HHF based on Cox regression. Internal validation on the administrative data cohort yielded satisfactory results in terms of discrimination (max AUROC=0.792, C-index=0.786) and calibration (Hosmer-Lemeshow test p-value<0.05). The risk score was then tested on data gathered from two independent centers (one diabetes outpatient clinic and one primary care network) to demonstrate its applicability to different care settings in the medium-long term. Thanks to the large size and broad demographics of the administrative dataset used for training, the proposed model was able to predict HHF without significant performance loss concerning bespoke models developed within each setting using more informative, but harder-to-acquire clinical variables.

No abstract

Context: In Italy, little is known about the territorial distribution of the frailty status. Aims: To compare frailty- and multimorbidity-prevalence in the elderly population of two Italian regions. Methods: This study examined randomized samples of elderly (both community dwelling and institutionalized) assisted by general practitioners. Frailty was evaluated through the CSHA-Scale, multimorbidity through the Charlson-Score. The relation between frailty and multimorbidity was studied through a logistic model. Both crude and standardized prevalences were calculated. Results: One hundred and sixteen physicians assisted 176,503 patients highly representative of Italian people. In a randomized sample of 4,531 older people, the sex–age-standardized prevalence of Frailty (standard population: Italy) was 25.74% (24.63–26.85%). Age-standardized prevalence for males was 20.08% (18.46–21.71%) and 30.00% (28.54–31.57%) for females. Using the sex–age-standardization pooled sample, the prevalence of frailty was significantly higher in Sicily than Veneto (28.74% [27.03–30.46%] vs 22.30% [20.94–23.67%]. This study did not find differences in the prevalence of multimorbidity: Veneto 20.76% (19.21–22.31%); Sicily 22.05% (20.33–23.77%). Both “to be female” and “to live in Sicily” were shown to be predictors of frailty OR for being female = 1.64 (1.42–1.88); OR for living in Sicily = 1.27 (1.11–1.46). Multimorbidity was an independent frailty-predictor only for those aged < 85: OR of Charlson Index ≥ 4 for ages < 85 = 3.44 (2.88–4.11), OR for ages ≥ 85 = 1.44 (0.97–2.12). Limitations: (1) This study considered patients assisted by doctors, not a random sample of the general population. (2) The cross-sectional nature of the study limits the interpretation of the relationships between frailty and multi-morbidity. (3) Few covariates were available for our multivariate models. Conclusions: More than 1/4 of elderly persons are shown to be frail (1/5 of males and 1/3 of females). Frailty is more frequent in Sicily, while multimorbidity does not differ between the two regions. This could be due to regional differences in the organization of care networks dedicated to elderly patients.