scholarly journals Identifying patients at risk of rehospitalization for heart failure in administrative data: A competing risks approach

2020 ◽  
Vol 12 (1) ◽  
pp. 34
Author(s):  
P. Constantinou ◽  
N. Pelletier-Fleury ◽  
V. Olié ◽  
C. Gastaldi-Menager ◽  
Y. Juillière ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Competing Risks ◽  
Administrative Data ◽  
Patients At Risk

scholarly journals Identifying patients at risk of readmission for heart failure in the French national claim database

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
P Constantinou ◽  
N Pelletier-Fleury ◽  
V Olié ◽  
C Gastaldi-Ménager ◽  
Y Juillière ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Administrative Data ◽  
Mortality Risk ◽  
Risk Groups ◽  
Claim Database ◽  
Health State ◽  
Hazard Ratios ◽  
Patients At Risk ◽  
Competing Mortality

Abstract Background To reduce readmissions for heart failure (HF) among HF patients, most at-risk individuals could be targeted to benefit from adapted interventions. A better understanding of HF readmission predictors could help clinicians and regulators identify patients most at-risk. We focused, in particular, on distinguishing HF severity from overall health-state severity. Methods We studied predictors of HF readmission available in administrative data in a nationwide cohort of patients aged 65 years or older surviving an index hospitalization for HF in 2015 (N = 70 657). To take into account the competing mortality risk, we estimated subdistribution hazard ratios (sdHRs) of HF readmission and cause-specific hazard ratios (csHRs) for HF readmission and for death without HF readmission, over a 1-year follow-up period. We then computed cumulative incidences and daily rates of HF readmission for specific risk-groups. Results 31.8% of patients were readmitted at least once for HF, among which 27.2% (8.6% of study cohort) were readmitted 30 days after discharge. 17.6% of patients died without any HF readmission. HF severity and overall health-state severity were the strongest HF readmission predictors (sdHRs 2.66 [95% CI: 2.52-2.81] and 1.37 [1.30-1.45] respectively, when comparing extreme categories). HF severity and length of index stay were more strongly associated with the rate (csHRs) of HF readmissions, whereas overall health-state severity and age were more strongly associated with the competing rate of death without HF readmission. Risk-groups defined upon HF severity and overall health-state severity had approximately 40% of separation in HF readmission proportion (21.9% versus 60.4%). Conclusions Our results stress the importance of considering both HF severity and overall morbidity and of accounting for the competing mortality risk to identify patients at-risk of HF readmission. Such patients could benefit from targeted transitional or post-discharge HF care. Key messages Heart failure patients can be stratified into risk-groups of readmission using administrative data. Identifying at-risk patients could help clinicians and regulators to target interventions.

Left Atrial Phasic Function Predicts NT-proBNP in Asymptomatic Community Patients at Risk for Heart Failure

2021 ◽  
Vol 30 ◽  
pp. S128-S129
Author(s):  
P. Crane ◽  
M. McGrady ◽  
L. Shiel ◽  
D. Liew ◽  
S. Stewart ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Left Atrial ◽  
Patients At Risk ◽  
Community Patients

Pacemaker Induced Cardiomyopathy: An Overview of Current Literature

2021 ◽  
Vol 17 ◽  
Author(s):  
Callan Gavaghan
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Right Ventricular ◽  
Current Literature ◽  
Left Ventricular ◽  
Lv Function ◽  
Patients At Risk ◽  
Rv Pacing ◽  
Clinical Heart Failure ◽  
Potential Methods

: Pacemaker induced cardiomyopathy (PICM) is commonly defined as a reduction in left ventricular (LV) function in the setting of right ventricular (RV) pacing. This condition may be associated with the onset of clinical heart failure in those affected. Recent studies have focused on potential methods of identifying patients at risk of this condition, in addition to hypothesizing the most efficacious ways to manage these patients. Newer pacing options, such as His bundle pacing, may avoid the onset of PICM entirely.

Impaired HDL Function Predicts Subclinical Myocardial Necrosis in Patients at Risk of Developing Heart Failure

2011 ◽  
Vol 17 (8) ◽  
pp. S24
Author(s):  
Zhili Shao ◽  
Yuping Wu ◽  
Yi Lu ◽  
Stanley L. Hazen ◽  
W.H. Wilson Tang
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Myocardial Necrosis ◽  
Hdl Function ◽  
Developing Heart ◽  
Patients At Risk

scholarly journals The importance of NT proBNP in hypertensive patients management for preventing heart failure

2021 ◽  
Vol 68 (1) ◽  
pp. 71-76
Author(s):  
Irina Cuciureanu ◽  
◽  
Anamaria-Georgiana Avram ◽  
Maria Suzana Guberna ◽  
Cătălina Liliana Andrei ◽  
...  
Keyword(s):  
Heart Failure ◽  
At Risk ◽  
Diastolic Dysfunction ◽  
Medical Management ◽  
Systolic Dysfunction ◽  
Intervention Group ◽  
Control Group ◽  
Cardiovascular Pathology ◽  
Hypertensive Patients ◽  
Patients At Risk

Purpose. NT proBNP is routinely used in the diagnosis and prognosis of HF. The study aimed to determine whether the value of NT proBNP can be used in hypertensive patients to detect patients at risk of developing HF and whether in these patients medical management guided by NT proBNP can prevent the development of HF. Material and methods. We included 275 hypertensive patients who presented to the Bagdasar-Arseni Emergency Hospital for cardiological consultation for a period of 3 years. Patients diagnosed with heart failure or left ventricular systolic dysfunction and patients with symptoms of heart failure at enrollment were excluded. We divided the patients into 2 groups, a control group and an intervention group. Patients in the intervention group were managed according to the NT proBNP value, and patients in the control group received standard treatment. Results. The objectives pursued at 3 years were: diagnosis of heart failure, systolic or diastolic dysfunction of the left ventricle and hospitalization for cardiovascular pathology. After 3 years, in the control group there were 34 patients (25.4%) who developed HF, compared to 24 patients (17.0%) in the intervention group. In the control group, 51 patients (38.1%) were diagnosed with LV systolic dysfunction compared to 37 patients (26.2%) in the intervention group. Regarding diastolic LV dysfunction, in the control group there were 83 patients (61.9%), and in the intervention group there were 73 patients (51.8%). Also, the rate of hospitalizations for cardiovascular pathology was higher in the control group 47 patients (35.1%) compared to 27 patients (19.1%) in the intervention group. Discussions. Hypertensive patients in the intervention group, who were managed according to the NT proBNP value, had a lower incidence rate of heart failure, LV systolic or diastolic dysfunction, or hospitalizations for cardiovascular events than in the control group. Conclusions. The value of NT proBNP may be useful for detecting hypertensive patients at risk of developing HF, and NT proBNP-guided medical management may prevent or delay the onset of HF.

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