Multi-state modelling of heart failure care path: A population-based investigation from Italy

被引:20
作者
Gasperoni, Francesca [1 ]
Ieva, Francesca [1 ]
Barbati, Giulia [2 ,3 ]
Scagnetto, Arjuna [2 ]
Iorio, Annamaria [3 ,4 ]
Sinagra, Gianfranco [5 ]
Di Lenarda, Andrea [3 ]
机构
[1] Politecn Milan, Dept Math, MOX Modelling & Sci Comp, Milan, Italy
[2] Univ Trieste, Dept Med Sci, Trieste, Italy
[3] Cardiovasc Ctr, Trieste, Italy
[4] Papa Giovanni XXIII Hosp, Cardiol Unit, Bergamo, Italy
[5] Azienda Sanitaria Univ Integrata Trieste ASUITS, Cardiovasc Dept, Trieste, Italy
来源
PLOS ONE | 2017年 / 12卷 / 06期
关键词
LONG-TERM MORTALITY; COMPETING RISKS; PREDICTING MORTALITY; HOSPITALIZATION; SURVIVAL; REGISTRIES; COMMUNITY; PACKAGE; TRENDS; COACH;
D O I
10.1371/journal.pone.0179176
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Background How different risk profiles of heart failure (HF) patients can influence multiple readmissions and outpatient management is largely unknown. We propose the application of two multi-state models in real world setting to jointly evaluate the impact of different risk factors on multiple hospital admissions, Integrated Home Care (IHC) activations, Intermediate Care Unit (ICU) admissions and death. Methods and findings The first model (model 1) concerns only hospitalizations as possible events and aims at detecting the determinants of repeated hospitalizations. The second model (model 2) considers both hospitalizations and ICU/IHC events and aims at evaluating which profiles are associated with transitions in intermediate care with respect to repeated hospitalizations or death. Both are characterized by transition specific covariates, adjusting for risk factors. We identified 4,904 patients (4,129 de novo and 775 worsening heart failure, WHF) hospitalized for HF from 2009 to 2014. 2,714 (55%) patients died. Advanced age and higher morbidity load increased the rate of dying and of being rehospitalized (model 1), decreased the rate of being discharged from hospital (models 1 and 2) and increased the rate of inactivation of IHC (model 2). WHF was an important risk factor associated with hospital readmission. Conclusion Multi-state models enable a better identification of two patterns of HF patients. Once adjusted for age and comorbidity load, the WHF condition identifies patients who are more likely to be readmitted to hospital, but does not represent an increasing risk factor for activating ICU/IHC. This highlights different ways to manage specific patients' patterns of care. These results provide useful healthcare support to patients' management in real world context. Our study suggests that the epidemiology of the considered clinical characteristics is more nuanced than traditionally presented through a single event.
引用
收藏
页数:15
相关论文
共 37 条
[21]   Long-term trends in the incidence of and survival with heart failure [J].
Levy, D ;
Kenchaiah, S ;
Larson, MG ;
Benjamin, EJ ;
Kupka, MJ ;
Ho, KKL ;
Murabito, JM ;
Vasan, RS .
NEW ENGLAND JOURNAL OF MEDICINE, 2002, 347 (18) :1397-1402
[22]  
Lloyd-Jones D, 2010, CIRCULATION, V121, P948, DOI 10.1161/CIRCULATIONAHA.109.192666
[23]   Heart failure incidence and survival (from the atherosclerosis risk in communities study) [J].
Loehr, Laura R. ;
Rosamond, Wayne D. ;
Chang, Patricia P. ;
Folsom, Aaron R. ;
Chambless, Lloyd E. .
AMERICAN JOURNAL OF CARDIOLOGY, 2008, 101 (07) :1016-1022
[24]   Transitional care of older adults hospitalized with heart failure: A randomized, controlled trial [J].
Naylor, MD ;
Brooten, DA ;
Campbell, RL ;
Maislin, G ;
McCauley, KM ;
Schwartz, JS .
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY, 2004, 52 (05) :675-684
[25]   Acute heart failure patient profiles, management and in-hospital outcome: results of the Italian Registry on Heart Failure Outcome [J].
Oliva, Fabrizio ;
Mortara, Andrea ;
Cacciatore, Giuseppe ;
Chinaglia, Alessandra ;
Di Lenarda, Andrea ;
Gorini, Marco ;
Metra, Marco ;
Senni, Michele ;
Maggioni, Aldo P. ;
Tavazzi, Luigi .
EUROPEAN JOURNAL OF HEART FAILURE, 2012, 14 (11) :1208-1217
[26]   The COACH risk engine: a multistate model for predicting survival and hospitalization in patients with heart failure [J].
Postmus, Douwe ;
van Veldhuisen, Dirk J. ;
Jaarsma, Tiny ;
Luttik, Marie Louise ;
Lassus, Johan ;
Mebazaa, Alexandre ;
Nieminen, Markku S. ;
Harjola, Veli-Pekka ;
Lewsey, James ;
Buskens, Erik ;
Hillege, Hans L. .
EUROPEAN JOURNAL OF HEART FAILURE, 2012, 14 (02) :168-175
[27]   Tutorial in biostatistics: Competing risks and multi-state models [J].
Putter, H. ;
Fiocco, M. ;
Geskus, R. B. .
STATISTICS IN MEDICINE, 2007, 26 (11) :2389-2430
[28]   Trends in heart failure incidence and survival in a community-based population [J].
Roger, VL ;
Weston, SA ;
Redfield, MA ;
Hellermann-Homan, JP ;
Killian, J ;
Yawn, BP ;
Jacobsen, SJ .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2004, 292 (03) :344-350
[29]   Competing Risks and Multistate Models [J].
Schmoor, Claudia ;
Schumacher, Martin ;
Finke, Juergen ;
Beyersmann, Jan .
CLINICAL CANCER RESEARCH, 2013, 19 (01) :12-21
[30]   Congestive heart failure in the community -: Trends in incidence and survival in a 10-year period [J].
Senni, M ;
Tribouilloy, CM ;
Rodeheffer, RJ ;
Jacobsen, SJ ;
Evans, JM ;
Bailey, KR ;
Redfield, MM .
ARCHIVES OF INTERNAL MEDICINE, 1999, 159 (01) :29-34