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1. Factors affecting adherence to guidelines for antithrombotic therapy in elderly patients with atrial fibrillation admitted to internal medicine wards

Author

Marcucci, M, Iorio, A, Nobili, A, Tettamanti, M, Pasina, L, Marengoni, A, Salerno, F, Corrao, S, Mannucci, Pm, Tedeschi A, REPOSI Investigators., Rossio, R, Moreo, G, Ferrari, B, Mammarella, A, Raparelli, V, Rondinella, S, Giannico, I, Rasciti, L, Gualandi, S, Monzani, V, Savojardo, V, Fabio, G, Colombo, S, Quercioli, A, Barreca, A, Durante-Mangoni, E, Pinto, D, Incasa, E, Rizzoli, E, Vanoli, M, Casella, G, Musca, G, Cuccurullo, O, Famularo, G, Sajeva, Mr, Picardi, A, Hila, D, Rozzini, R, Giordano, A, Bonelli, A, Dentamaro, G, Gobbo, G, Cazzaniga, M, Gaudenzi, P, Giusto, L, Rizzoni, D, Castoldi, L, Mari, D, Micale, G, Altomare, E, Serviddio, G, Longhini, C, Molino, C, Deidda, S, Cuccuru, Lm, Quagliolo, M, Centenaro, Gr, Pasqui, Al, Puccetti, L, Bertolino, G, Cavallo, P, Bertolini, D, Liberato, Nl, Perciccante, A, Coralli, A, Anastasio, L, Bertucci, L, Macura, A, Matino, D, Morabito, C, Fava, R, Tuttolomondo, A, Di Sciacca, R, Semplicini, A, Magagnotti, G, Fiorentini, A, Tofi, C, Cagnoni, C, Manucra, A, Romanelli, G, Cortellaro, M, Meroni, Mr, Rossi, Dp, Vergani, C., Marcucci, M, Iorio, A, Nobili, A, Tettamanti, M, Pasina, L, Marengoni, A, Salerno, F, Corrao, S, Mannucci, PM, Tedeschi, A, Rossio, R, Moreo, G, Ferrari, B, Mammarella, A, Raparelli, V, Rondinella, S, Giannico, I, Rasciti, L, Gualandi, S, Monzani, V, Savojardo, V, Fabio, G, Colombo, S, Quercioli, A, Barreca, A, Durante-Mangoni, E, Pinto, D, Incasa, E, Rizzoli, E, Vanoli, M, Casella, G, Musca, G, Cuccurullo, O, Famularo, G, Sajeva, MR, Picardi, A, Hila, D, Rozzini, R, Giordano, A, Bonelli, A, Dentamaro, G, Gobbo, G, Cazzaniga, M, Gaudenzi, P, Giusto, L, Rizzoni, D, Castoldi, L, Mari, D, Micale, G, Altomare, E, Serviddio, G, Longhini, C, Molino, C, Deidda, S, Cuccuru, LM, Quagliolo, M, Centenaro, GR, Pasqui, AL, Puccetti, L, Bertolino, G, Cavallo, P, Bertolini, D, Liberato, NL, Perciccante, A, Coralli, A, Anastasio, L, Bertucci, L, Macura, A, Matino, D, Morabito, C, Fava, R, Tuttolomondo, A, Di Sciacca, R, Semplicini, A, Magagnotti, G, Fiorentini, A, Tofi, C, Cagnoni, C, Manucra, A, Romanelli, G, Cortellaro, M, Meroni, MR, Rossi, DP, and Vergani, C

Subjects
Male, medicine.medical_specialty, Settore MED/09 - Medicina Interna, Vitamin K, antithrombotic therapy, NO, Antithrombotic prophylaxis, Atrial fibrillation, Platelet agents, Vitamin K antagonists, Fibrinolytic Agents, Risk Factors, Internal medicine, Antithrombotic, Internal Medicine, medicine, Humans, atrial fibrillation, Registries, Medical prescription, Stroke, Aged, Retrospective Studies, Aged, 80 and over, Antithrombotic prophylaxis, Atrial fibrillation, Platelet agents, Vitamin K antagonists, guidelines, Aspirin, business.industry, antithrombotic prophylaxis, platelet agents, vitamin k antagonists, Retrospective cohort study, medicine.disease, Intracranial Embolism, Italy, Platelet aggregation inhibitor, Female, Guideline Adherence, business, guideline, Platelet Aggregation Inhibitors, Fibrinolytic agent, medicine.drug
Abstract

Introduction Current guidelines for ischemic stroke prevention in atrial fibrillation or flutter (AFF) recommend Vitamin K antagonists (VKAs) for patients at high-intermediate risk and aspirin for those at intermediate-low risk. The cost-effectiveness of these treatments was demonstrated also in elderly patients. However, there are several reports that emphasize the underuse of pharmacological prophylaxis of cardio-embolism in patients with AFF in different health care settings. Aims To evaluate the adherence to current guidelines on cardio-embolic prophylaxis in elderly (> 65 years old) patients admitted with an established diagnosis of AFF to the Italian internal medicine wards participating in REPOSI registry, a project on polypathologies/polytherapies stemming from the collaboration between the Italian Society of Internal Medicine and the Mario Negri Institute of Pharmacological Research; to investigate whether or not hospitalization had an impact on guidelines adherence; to test the role of possible modifiers of VKAs prescription. Methods We retrospectively analyzed registry data collected from January to December 2008 and assessed the prevalence of patients with AFF at admission and the prevalence of risk factors for cardio-embolism. After stratifying the patients according to their CHADS 2 score the percentage of appropriateness of antithrombotic therapy prescription was evaluated both at admission and at discharge. Univariable and multivariable logistic regression models were employed to verify whether or not socio-demographic (age > 80 years, living alone) and clinical features (previous or recent bleeding, cranio-facial trauma, cancer, dementia) modified the frequency and modalities of antithrombotic drugs prescription at admission and discharge. Results Among the 1332 REPOSI patients, 247 were admitted with AFF. At admission, CHADS 2 score was ≥ 2 in 68.4% of patients, at discharge in 75.9%. Among patients with AFF 26.5% at admission and 32.8% at discharge were not on any antithrombotic therapy, and 43.7% at admission and 40.9% at discharge were not taking an appropriate therapy according to the CHADS 2 score. The higher the level of cardio-embolic risk the higher was the percentage of antiplatelet- but not of VKAs-treated patients. At admission or at discharge, both at univariable and at multivariable logistic regression, only an age > 80 years and a diagnosis of cancer, previous or active, had a statistically significant negative effect on VKAs prescription. Moreover, only a positive history of bleeding events (past or present) was independently associated to no VKA prescription at discharge in patients who were on VKA therapy at admission. If heparin was considered as an appropriate therapy for patients with indication for VKAs, the percentage of patients admitted or discharged on appropriate therapy became respectively 43.7% and 53.4%. Conclusion Among elderly patients admitted with a diagnosis of AFF to internal medicine wards, an appropriate antithrombotic prophylaxis was taken by less than 50%, with an underuse of VKAs prescription independently of the level of cardio-embolic risk. Hospitalization did not improve the adherence to guidelines.

Published
2010

2. In-hospital death and adverse clinical events in elderly patients according to disease clustering: the REPOSI study. Marengoni A

Author

Marengoni, A, Bonometti, F, Nobili, A, Tettamanti, M, Salerno, F, Corrao, S, Iorio, A, Marcucci, M, Mannucci, PM, Tedeschi, A, Rossio, R, Moreo, G, Ferrari, B, Mammarella, A, Raparelli, V, Rondinella, S, Giannico, I, Rasciti, L, Gualandi, S, Monzani, V, Savojardo, V, Fabio, G, Colombo, S, Quercioli, A, Barreca, A, Durante Mangoni, E, Pinto, D, Incasa, E, Rizzoli, E, Vanoli, M, Casella, G, Musca, G, Cuccurullo, O, Famularo, G, Sajeva, R, Picardi, A, Hila, D, Rozzini, R, Giordano, A, Bonelli, A, Dentamaro, G, Gobbo, G, Cazzaniga, M, Gaudenzi, P, Giusto, L, Rizzoni, D, Castoldi, L, Mari, D, Micale, G, Altomare, E, Serviddio, G, Longhini, C, Molino, C, Deidda, S, Cuccuru, LM, Quagliolo, M, Centenaro, GR, Pasqui, AL, Puccetti, L, Bertolino, G, Cavallo, P, Bertolini, D, Liberato, NL, Perciccante, A, Coralli, A, Anastasio, L, Bertucci, L, Agnelli, G, Macura, A, Morabito, C, Fava, R, Di Sciacca, R, Macchini, L, Realdi, A, Fiorentini, A, Tofi, C, Cagnoni, C, Manucra, A, Romanelli, G, Cortellaro Meroni, MR, Rossi, DP, Vergani, C., TUTTOLOMONDO, Antonino, Marengoni, A, Bonometti, F, Nobili, A, Tettamanti, M, Salerno, F, Corrao, S, Iorio, A, Marcucci, M, Mannucci, PM, Tedeschi, A, Rossio, R, Moreo, G, Ferrari, B, Mammarella, A, Raparelli, V, Rondinella, S, Giannico, I, Rasciti, L, Gualandi, S, Monzani, V, Savojardo, V, Fabio, G, Colombo, S, Quercioli, A, Barreca, A, Durante Mangoni, E, Pinto, D, Incasa, E, Rizzoli, E, Vanoli, M, Casella, G, Musca, G, Cuccurullo, O, Famularo, G, Sajeva, R, Picardi, A, Hila, D, Rozzini, R, Giordano, A, Bonelli, A, Dentamaro, G, Gobbo, G, Cazzaniga, M, Gaudenzi, P, Giusto, L, Rizzoni, D, Castoldi, L, Mari, D, Micale, G, Altomare, E, Serviddio, G, Longhini, C, Molino, C, Deidda, S, Cuccuru, LM, Quagliolo, M, Centenaro, GR, Pasqui, AL, Puccetti, L, Bertolino, G, Cavallo, P, Bertolini, D, Liberato, NL, Perciccante, A, Coralli, A, Anastasio, L, Bertucci, L, Agnelli, G, Macura, A, Morabito, C, Fava, R, Tuttolomondo, A, Di Sciacca, R, Macchini, L, Realdi, A, Fiorentini, A, Tofi, C, Cagnoni, C, Manucra, A, Romanelli, G, Cortellaro Meroni, MR, Rossi, DP, and Vergani, C

Subjects
Settore MED/09 - Medicina Interna, elderly, in-hospital death
Abstract

OBJECTIVE: The aim of the study was to recognize clusters of diseases among hospitalized elderly and to identify groups of patients at risk of in-hospital death and adverse clinical events according to disease clustering. METHOD: This was a cross-sectional study conducted in 38 internal medicine and geriatric wards in Italy participating in the Registro Politerapie SIMI (REPOSI) study during 2008. The subjects were 1,332 inpatients aged 65 years or older. Clusters of diseases (i.e., two or more co-occurrent diseases) were identified using the odds ratios (OR) for the associations between pairs of conditions, followed by cluster analysis. Logistic regression models were used to evaluate the effect of disease clusters on in-hospital death and adverse clinical events. RESULTS: A total of 86.7% of the patients were discharged, 8.3% were transferred to another hospital unit, and 5.0% died during hospitalization; 36.4% of the patients had at least one adverse clinical event. Patients affected by the clusters, including heart failure (HF) and either chronic renal failure (CRF) or chronic obstructive pulmonary disease, had a significant association with in-hospital death (OR, 4.3;95% confidence interval [CI], 1.6-11.5; OR, 2.9; 95% CI, 1.1-8.3, respectively), as well as patients affected by CRF and anemia (OR, 6.1; 95% CI, 2.3-16.2). The cluster including HF and CRF was also associated with adverse clinical events (OR, 3.5; 95% CI, 1.5-7.8). The effect of both HF and CRF and anemia and CRF on in-hospital death was additive. CONCLUSION: Several groups of older patients at risk of in-hospital death and adverse clinical events were identified according to disease clustering. Knowledge of the relationship among co-occurring diseases may help developing strategies to improve clinical practice and preventative interventions.

Published
2010

3. Comparison of Disease Clusters in Two Elderly Populations Hospitalized in 2008 and 2010

Author

Marengoni, A, Nobili, A, Pirali, C, Tettamanti, M, Pasina, L, Salerno, F, Corrao, S, Iorio, A, Marcucci, M, Franchi, C, Mannucci, Pm, Reposi, Investigators, Pier Mannucci, M, Spirito, V, Noce, D, Bonazzi, J, Lombardo, R, Sparacio, E, Alborghetti, S, De Vittorio, L, Djade, Cd, Paolisso, G, Rizzo, Mr, Laieta, Mt, Roberto, T, Persico, Marcello, Salvatore, T, Sasso, Fc, Utili, R, Durante Mangoni, E, Pinto, D, Fenoglio, L, Brignone, C, Bracco, C, Gasbarrone, L, Porcari, P, Famularo, G, Sajeva, Mr, Maniscalco, G, Gunelli, M, Tirotta, D, Realdi, G, Baritussio, A, Frassoni, F, Delsignore, R, Baroni, Mc, Zardo, M, Volpato, S, Fotini, S, Manfredini, R, Longhini, C, Molino, C, Incasa, E, Guarnieri, G, Zanetti, M, Spalluti, A, Rini, G, Mansueto, P, Pepe, I, Licata, G, Calvo, L, Valenti, M, Tuttolomondo, A, Di Sciacca, R, Antonaci, S, Vella, F, Marseglia, A, Centonze, V, Modeo, Me, Palasciano, G, Pugliese, S, Capobianco, C, Murialdo, G, Bovio, M, Pasini, Fl, Capecchi, Pl, Bicchi, M, Nuti, R, Valenti, R, Capodarca, C, Auteri, A, Pasqui, Al, Puccetti, L, Olivieri, O, Stanzial, Am, Agnelli, G, Macura, A, Mannarino, E, Lupattelli, G, Rondelli, P, Serra, Mg, Musca, G, Cuccurullo, O, Cappellini, Md, Fabio, G, Motta, I, Cantoni, F, Fargion, S, Bonara, P, Bulgheroni, M, Magrini, F, Massari, F, Tonella, T, Peyvandi, F, Tedeschi, A, Rossio, R, Moreo, G, Ferrari, B, Roncari, L, Monzani, V, Savojardo, V, Folli, C, Mari, D, Rossi, Pd, Ziglioli, E, Vergani, C, Lilleri, Ms, Podda, M, Selmi, C, Meda, F, Cazzaniga, M, Monti, V, Balduini, Cl, Bertolino, G, Dezzani, L, Cavallo, P, Corazza, Gr, Miceli, E, Secchi, Mb, Wu, Sc, Balsamo, C, Anastasio, L, Sofia, L, Carbone, M, Bertucci, L, Valentia, V, Traisci, G, De Feudis, L, Bergami, E, Rizzioli, E, Cagnoni, C, Bertone, L, Manucra, A, Ronchi, E, Buratti, A, Tognin, T, Bertolini, D, Liberato, Nl, Bernasconi, G, Nardo, B, Venco, A, Guasti, L, Maroni, L, Castiglioni, L, Vanoli, M, Grignani, G, Casella, G, Mancuso, G, Tavella, R, Persico, R, Cicardi, M, Sandrone, G, Cortellaro, M, Magenta, M, Perego, F, Meroni, Mr, Rozzini, R, Falanga, L, Giordano, A, Menardo, G, Bottone, S, Sferrazzo, E, Tassara, R, Melis, D, Rebella, L, Ferri, C, Striuli, R, Scipioni, R, Salmi, R, Gaudenzi, P, Di Todaro, F, Nielsen, I, Giusto, L, Semplicini, A, Gottardo, L, Delitala, G, Carta, S, Atzori, S, Rosei, Ea, Rizzoni, D, Castoldi, L, Altomare, E, Serviddio, G, Salvatore, S, Fera, G, Di Luca ML, Renna, D, Picardi, A, Mazzarelli, C, Gentilucci, Uv, De Vincentis, A, Hila, D, Bernardi, M, Li Bassi, S, Santi, L, Masala, C, Mammarella, A, Raparelli, V, Rossi Fanelli, F, Delfino, M, Amoroso, A, Serra, P, Fontana, V, Falcone, M, Violi, F, Basili, S, Perri, L, Silveri, Ng, De Marco, G, Giupponi, B, Landolfi, R, Grieco, A, Gallo, A, Perticone, F, Sciacqua, A, Quero, M, Bagnato, C, Loria, P, Ballestri, S, Becchi, Ma, Bellettini, E, Bolondi, L, Rasciti, L, Serio, I, Gualandi, S, Romanelli, G, Bonometti, F, Carulli, N, Rondinella, S, Giannico, I, Dallegri, F, Ottonello, L, Quercioli, A, Barreca, A, Sacco, A, Bonelli, A, Dentamaro, G, Micale, G, Delitalia, G, Deidda, S, Cuccuru, Lm, Benetti, G, Quagliolo, M, Centenaro, Gr, Perciccante, A, Coralli, A, Morabito, C, Fava, R, Macchini, L, Realdi, A, Cricco, L, Fiorentini, A, Tofi, C., Marengoni A, Nobili A, Pirali, C, Tettamanti, M, Pasina, L, Salerno, F, Corrao, S, Iorio, A, Marcucci, M, Franchi, C, Mannucci, Pm, Investigators, Reposi, Zanetti, Michela, Marengoni, A., Nobili, A., Pirali, C., Tettamanti, M., Pasina, L., Salerno, F., Corrao, S., Iorio, A., Marcucci, M., Franchi, C., Mannucci, P. M, Rizzo, Mr, Marengoni A, Nobili A, Pirali C, Tettamanti M, Pasina L, Salerno F, Corrao S, Iorio A, Marcucci M, Franchi C, Mannucci PM, REPOSI Investigators [.., Bernardi M, Bolondi L, ], Mannucci, P., and Mansueto, P.

Subjects
Registrie, Male, Aging, Cirrhosis, Settore MED/09 - Medicina Interna, Time Factors, hispitalization, Gerontology, aging populations, atterns of multimorbidity, diseases in the elderly population, Health care, 80 and over, Prevalence, Chronic diseases, Cluster analysis, Hospitalized elderly, Registries, aging population, Aged, 80 and over, education.field_of_study, Settore MED/45 - Scienze Infermieristiche Generali, Cliniche E Pediatriche, Hospitalization, Italy, elderly, disease clusters, Female, hospitalized, Human, medicine.medical_specialty, Time Factor, Anemia, MULTIMORBIDITY, Population, MEDLINE, Malignancy, Diabetes mellitus, Internal medicine, medicine, Multimorbidity, Humans, education, Aged, Chronic Disease, Cluster Analysis, Geriatrics and Gerontology, Cluster Analysi, business.industry, medicine.disease, Physical therapy, disease cluster, business
Abstract

Background: As chronicity represents one of the major challenges in the healthcare of aging populations, the understanding of how chronic diseases distribute and co-occur in this part of the population is needed. Objectives: The aims of this study were to evaluate and compare patterns of diseases identified with cluster analysis in two samples of hospitalized elderly. Methods: Data were obtained from the multicenter ‘Registry Politerapie SIMI (REPOSI)' that included people aged 65 or older hospitalized in internal medicine and geriatric wards in Italy during 2008 and 2010. The study sample from the first wave included 1,411 subjects enrolled in 38 hospitals wards, whereas the second wave included 1,380 subjects in 66 wards located in different regions of Italy. To analyze patterns of multimorbidity, a cluster analysis was performed including the same diseases (19 chronic conditions with a prevalence >5%) collected at hospital discharge during the two waves of the registry. Results: Eight clusters of diseases were identified in the first wave of the REPOSI registry and six in the second wave. Several diseases were included in similar clusters in the two waves, such as malignancy and liver cirrhosis; anemia, gastric and intestinal diseases; diabetes and coronary heart disease; chronic obstructive pulmonary disease and prostate hypertrophy. Conclusion: These findings strengthened the idea of an association other than by chance of diseases in the elderly population.

Published
2013

4. In-hospital death and adverse clinical events in elderly patients according to disease clustering: The REPOSI study

Author

Marengoni, A, Bonometti, F, Nobili, A, Tettamanti, M, Salerno, F, Corrao, S, Iorio, A, Marcucci, M, Mannucci, Pm, Tedeschi A, Italian Society of Internal Medicine (SIMI) Investigators., Rossio, R, Moreo, G, Ferrari, B, Mammarella, A, Raparelli, V, Rondinella, S, Giannico, I, Rasciti, L, Gualandi, S, Monzani, V, Savojardo, V, Fabio, G, Colombo, S, Quercioli, A, Barreca, A, Durante-Mangoni, E, Pinto, D, Incasa, E, Rizzoli, E, Vanoli, M, Casella, G, Musca, G, Cuccurullo, O, Famularo, G, Sajeva, Mr, Picardi, A, Hila, D, Rozzini, R, Giordano, A, Bonelli, A, Dentamaro, G, Gobbo, G, Cazzaniga, M, Gaudenzi, P, Giusto, L, Rizzoni, D, Castoldi, L, Mari, D, Micale, G, Altomare, E, Serviddio, G, Longhini, C, Molino, C, Deidda, S, Cuccuru, Lm, Quagliolo, M, Centenaro, Gr, Pasqui, Al, Puccetti, L, Bertolino, G, Cavallo, P, Bertolini, D, Liberato, Nl, Perciccante, A, Coralli, A, Anastasio, L, Bertucci, L, Agnelli, G, Macura, A, Morabito, C, Fava, R, Tuttolomondo, A, Di Sciacca, R, Macchini, L, Realdi, A, Fiorentini, A, Tofi, C, Cagnoni, C, Manucra, A, Romanelli, G, Cortellaro, M, Meroni, Mr, Rossi, Dp, Vergani, C., Marengoni, A, Bonometti, F, Nobili, A, Tettamanti, M, Salerno, F, Corrao, S, Iorio, A, Marcucci, M, Mannucci, PM, and Italian Society of Internal Medicine (SIMI) Investigators

Subjects
Male, Aging, Disease clusters, Pediatrics, medicine.medical_specialty, Settore MED/09 - Medicina Interna, Hospital unit, Disease, Hospital mortality, disease clustering, Logistic regression, NO, 80 and over, Medicine, Cluster Analysis, Humans, Hospital Mortality, Aged, Aged, 80 and over, In hospital death, Medical Errors, business.industry, Clinical events, Female, Italy, REPOSI, In-hospital death, elderly patients, Odds ratio, Settore MED/45 - Scienze Infermieristiche Generali, Cliniche E Pediatriche, elderly patient, Geriatrics and Gerontology, business, patients at risk of in-hospital death, adverse clinical events according to disease clustering
Abstract

OBJECTIVE: The aim of the study was to recognize clusters of diseases among hospitalized elderly and to identify groups of patients at risk of in-hospital death and adverse clinical events according to disease clustering. METHOD: This was a cross-sectional study conducted in 38 internal medicine and geriatric wards in Italy participating in the Registro Politerapie SIMI (REPOSI) study during 2008. The subjects were 1,332 inpatients aged 65 years or older. Clusters of diseases (i.e., two or more co-occurrent diseases) were identified using the odds ratios (OR) for the associations between pairs of conditions, followed by cluster analysis. Logistic regression models were used to evaluate the effect of disease clusters on in-hospital death and adverse clinical events. RESULTS: A total of 86.7% of the patients were discharged, 8.3% were transferred to another hospital unit, and 5.0% died during hospitalization; 36.4% of the patients had at least one adverse clinical event. Patients affected by the clusters, including heart failure (HF) and either chronic renal failure (CRF) or chronic obstructive pulmonary disease, had a significant association with in-hospital death (OR, 4.3;95% confidence interval [CI], 1.6-11.5; OR, 2.9; 95% CI, 1.1-8.3, respectively), as well as patients affected by CRF and anemia (OR, 6.1; 95% CI, 2.3-16.2). The cluster including HF and CRF was also associated with adverse clinical events (OR, 3.5; 95% CI, 1.5-7.8). The effect of both HF and CRF and anemia and CRF on in-hospital death was additive. CONCLUSION: Several groups of older patients at risk of in-hospital death and adverse clinical events were identified according to disease clustering. Knowledge of the relationship among co-occurring diseases may help developing strategies to improve clinical practice and preventative interventions.

Published
2010

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