P3543Rehospitalization burden in heart failure with mid-range ejection fraction and morbidity burden. Is it a distinct phenotype?

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
E Santas Olmeda ◽  
R De La Espriella ◽  
G Minana ◽  
E Valero ◽  
P Palau ◽  
...  
Keyword(s):  
Heart Failure ◽  
Confidence Interval ◽  
Ejection Fraction ◽  
Recurrent Events ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Morbidity Burden ◽  
Binomial Regression ◽  
Similar Risk

Abstract Heart failure with mid-range ejection fraction (HFmrEF) has been recognized as a distinct HF phenotype, but wether patients on this category fare worse, similarly, or better than those with HF with reduced EF (HFrEF) or preserved EF (HFpEF) in terms of rehospitalization risk over time remains unclear. We therefore sought to characterize the mordibity burden of HFmrEF patients by evaluating the risk of recurrent hospitalizations following an admission for acute HF. Methods We prospectively included 2,961 consecutive patients discharged for acute HF in our institution from 2004 to 2017. Patients were categorized according to their ejection fraction (EF) obtained by an echocardiography during the index admission: HFmrEF (EF 41–49%), HFrEF (EF≤40%) and HFpEF (EF≥50%). Negative binomial regression method was used to evaluate the association between EF status and recurrent all-cause and HF-related admissions. Risk estimates were expressed as incidence ratio ratios (IRR). Results Mean age of the cohort was 73.9±11.1 years, 49% were women, and 46.0% had suffered from previous HF admissions. 472 patients (15.9%) had HFmrEF, 956 (32.3%) had HFrEF, and 1,533 (51.8%) had HFpEF. At a median (interquartile range) follow-up of 2.4 (4.4) years, 1,821 (61.5%) patients died and 6,035 all-cause readmissions were registered in 2,026 patients (68.4%), being 2,163 of them HF-related. Rates of all-cause readmission per 100 patients-years of follow-up were 43.4, 47.1 and 50.1 per HFrEF, HFmrEF and HFpEF categories, respectively. After multivariable adjustment, and compared to patients with HFrEF, HFmrEF status was not associated with a higher risk of all-cause or HF-related recurrent admissions (IRR=1.06; 95% confidence interval (CI), 0.93–1.20; p=0.89), and IRR=1.07; 95% CI, 0.91–1.26; p=0.389, respectively), whereas HFpEF status was associated with a non-significant increase in the risk of all-cause recurrent admissions but a similar risk of HF-related readmissions (IRR=1.10; 95% confidence interval (CI), 0.99–1.22; p=0.06, and IRR=1.01; 95% CI, 0.88–1.16; p=0.900, respectively) Conclusion Following an admission for acute HF, patients with HFmrEF have a similar all-cause and HF-related rehospitalization burden when compared to patients with HFrEF, by means of recurrent events analysis.

Abstract 16807: Burden and Timing of Hospitalizations in Heart Failure: A Community Study

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Alanna M Chamberlain ◽  
Yariv Gerber ◽  
Shannon M Dunlay ◽  
Sheila M Manemann ◽  
Susan A Weston ◽  
...  
Keyword(s):  
Heart Failure ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Community Study ◽  
Olmsted County ◽  
Comorbid Conditions ◽  
Binomial Regression ◽  
Time Periods ◽  
Patients Experience

Background: Heart failure (HF) patients are experiencing an epidemic of hospitalizations. Nevertheless, data on the frequency and distribution of hospitalizations over the course of the disease are lacking. Methods: We determined the rates of hospitalizations during periods of follow-up in Olmsted County, MN residents with incident HF from 2000-2010. HF was identified using ICD-9 code 428 and validated by the Framingham criteria. All hospitalizations were obtained for the 2 years following incident HF and each was categorized as due to HF, other cardiovascular (ICD-9 codes 390-427, 429-459), or non-cardiovascular causes. Follow-up was divided into discrete time periods (epochs): 0-30, 31-182, 183-365, and 366-730 days. Negative binomial regression examined associations between epochs of follow-up time and hospitalizations. Results: Among 1702 incident HF patients (mean age 76, 44% male), 1143 (67%) were hospitalized at index. Over the 2 year follow-up, 3008 hospitalizations were observed among 1136 patients, and 351 patients were hospitalized within 30 days of incident HF (median time from HF to hospitalization: 11 days). The majority of hospitalizations were due to non-cardiovascular causes (63% vs. 14% HF, 23% other cardiovascular); however, a larger proportion of HF and other cardiovascular hospitalizations were observed within the first 30 days (52% non-cardiovascular, 18% HF, 30% other cardiovascular) compared to the other time periods. The rate of hospitalization was highest within the first 30 days and was similar across sex, presentation of incident HF (inpatient, outpatient), and type of HF (preserved (≥50%), reduced (<50%) ejection fraction) (Table). Conclusions: HF patients experience high rates of hospitalizations, particularly within the first 30 days, and the majority of hospitalizations are for non-cardiovascular causes. Continued efforts to manage comorbid conditions and reduce hospitalizations in HF patients are needed.

scholarly journals The impact of frailty and aging on prognosis in patients with heart failure with preserved ejection fraction – insights from PURSUIT-HFpEF registry

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Okada ◽  
K Inoue ◽  
T Onishi ◽  
K Iwakura ◽  
T Yamada ◽  
...  
Keyword(s):  
Heart Failure ◽  
Confidence Interval ◽  
Ejection Fraction ◽  
Hazard Ratio ◽  
Adverse Outcomes ◽  
Funding Source ◽  
Preserved Ejection Fraction ◽  
Clinical Endpoint ◽  
Patients With Heart Failure

Abstract Introduction Frailty and aging are two common conditions both associated with increased vulnerability to stressful events with high risk of adverse outcomes. Purpose To evaluate the association between frailty and aging and their impacts on clinical outcome in patients with heart failure with preserved ejection fraction (HFpEF). Methods Analysis was performed from a prospective multicenter observational registry for HFpEF (PURSUIT-HFpEF Registry) conducted in the Osaka region of Japan. A total of 757 patients hospitalized for acute heart failure (diagnosed by using Framingham criteria) met the inclusion criteria: a left ventricular ejection fraction ≥50% and brain natriuretic peptide ≥100pg/ml. We included 483 patients (age, 80±9 years; men, 45%; atrial fibrillation, 35%) whose follow-up data after survival discharge were available. Patients' frailty and aging were evaluated using the clinical frailty scale (CFS) and age quartiles (Q1: &lt;76 years (n=122), Q2: 76–82 years (n=111), Q3: 82–87 years (n=127), Q4: &gt;87 years (n=123)), respectively. The primary clinical endpoint was defined as the composite of death, re-hospitalization for heart failure, and cerebrovascular accident. Results The median (interquartile range) CFS rating was 3 (2–5), and there was a little correlation between CFS rating and age (r2=0.16, p&lt;0.001). The prevalence of frailty, defined as a CFS rating &gt;4 (n=132), was positively correlated with age quartiles (Q1: 9.0%, Q2: 21.4%, Q3: 29.9%, Q4: 48.0%, p&lt;0.001). During the median follow-up period 396 days (interquartile range, 344–698) after discharge, the clinical endpoint was observed in 172 patients. The incidence was higher in patients with frailty than those without it (49.6% vs. 30.4%, log-rank p&lt;0.001). It was also correlated with age quartiles (Q1: 23.0%, Q2: 34.2%, Q3: 36.2%, Q4: 48.8%, log-rank p=0.001). Multivariate Cox regression analysis revealed that frailty (hazard ratio, 1.52; 95% confidence interval, 1.09–2.10; p=0.013) and age (hazard ratio per quartile increase, 1.24; 95% confidence interval, 1.07–1.43; p=0.004) were both associated with the clinical endpoint. Subgroup analysis in 352 patients without frailty also revealed the significant impact of age on the endpoint (1.26; 1.06–1.51; p=0.008). However, in 131 patients with frailty, there was no significant impact of age on the endpoint (1.16; 0.90–1.51; p=0.25). Conclusions Frailty was common and was associated with aging in HFpEF patients. Although they were both associated with unfavorable events, aging was no longer a significant predictor of adverse outcomes under the frailty conditions. Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Roche Diagnostics K.K. and Fuji Film Toyama Chemical Co. Ltd.

Abstract 15659: Dynamic Device Derived Heart Failure Risk Score as a Predictor of Heart Failure Hospitalisation

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Maciej Debski ◽  
Lesley Howard ◽  
Paula Black ◽  
Angelic Goode ◽  
Christopher Cassidy ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Tertiary Centre ◽  
Cardiac Devices ◽  
Failure Risk ◽  
Heart Failure Hospitalisation

Introduction: The number of people being admitted to hospital in England due to heart failure (HF) has risen by a third in the last five years. Implantable cardiac devices with integrated heart failure diagnostics are capable of combining daily measurements of multiple device-derived parameters and provide a heart failure risk score (HFRS) which might help predict HF worsening. Methods: Between 2015 and 2019 231 consecutive HF device patients were co-managed (CM) by specialist HF nurses in a tertiary centre. Follow-up was truncated at last device transmission in 2019. HF nurses’ interventions to alerts were recorded prospectively. HF-related hospitalisations were collected from hospital records. We analysed the predictive value of baseline variables on the count of days in high HFRS in a negative binomial regression model. The device settings: Optivol CareAlert switched ON vs OFF were compared. Results: 200 patients with CRT-D were followed up for 2.6 [1.0-2.8] years (Figure). Baseline characteristics and their effect on the incidence rate ratio (IRR) of days in high HFRS are presented in Table. A total of 3,486 transmissions were assessed, median 7.3 [5.9-10.0] per patient-year; 591 high HFRS episodes occurred in 115 (58%) pts. Optivol OFF increased the rate of high HFRS being transmitted >30 days after its end (45% vs 35%, P=0.018) and increased the time from episode start to transmission (36 [16-68] vs 24 [8-53] days, P<0.001). Of 21 hospitalisations for decompensated HF, 15 were predicted by high HFRS within 30 days whereas 6 were predated by medium HFRS. Conclusion: Patients who have not had a single high HFRS during follow-up did not need admission for decompensated HF.

Burden and trajectory of multimorbidity in rheumatoid arthritis: a matched cohort study from 2006 to 2015

2020 ◽  
pp. annrheumdis-2020-218282 ◽  
Author(s):  
Bryant R England ◽  
Punyasha Roul ◽  
Yangyuna Yang ◽  
Harlan Sayles ◽  
Fang Yu ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Cohort Study ◽  
Chronic Conditions ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Sensitivity Analyses ◽  
Cross Sectional ◽  
Diagnostic Codes ◽  
Binomial Regression

ObjectivesTo compare the onset and trajectory of multimorbidity between individuals with and without rheumatoid arthritis (RA).MethodsA matched, retrospective cohort study was completed in a large, US commercial insurance database (MarketScan) from 2006 to 2015. Using validated algorithms, patients with RA (overall and incident) were age-matched and sex-matched to patients without RA. Diagnostic codes for 44 preidentified chronic conditions were selected to determine the presence (≥2 conditions) and burden (count) of multimorbidity. Cross-sectional comparisons were completed using the overall RA cohort and conditional logistic and negative binomial regression models. Trajectories of multimorbidity were assessed within the incident RA subcohort using generalised estimating equations.ResultsThe overall cohort (n=277 782) and incident subcohort (n=61 124) were female predominant (76.5%, 74.1%) with a mean age of 55.6 years and 54.5 years, respectively. The cross-sectional prevalence (OR 2.29, 95% CI 2.25 to 2.34) and burden (ratio of conditions 1.68, 95% CI 1.66 to 1.70) of multimorbidity were significantly higher in RA than non-RA in the overall cohort. Within the incident RA cohort, patients with RA had more chronic conditions than non-RA (β 1.13, 95% CI 1.10 to 1.17), and the rate of accruing chronic conditions was significantly higher in RA compared with non-RA (RA × follow-up year, β 0.21, 95% CI 0.20 to 0.21, p<0.001). Results were similar when including the pre-RA period and in several sensitivity analyses.ConclusionsMultimorbidity is highly prevalent in RA and progresses more rapidly in patients with RA than in patients without RA during and immediately following RA onset. Therefore, multimorbidity should be aggressively identified and targeted early in the RA disease course.

scholarly journals A negative binomial regression model for risk estimation of 0–2 axillary lymph node metastases in breast cancer patients

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
De Zeng ◽  
Hao-Yu Lin ◽  
Yu-Ling Zhang ◽  
Jun-Dong Wu ◽  
Kun Lin ◽  
...  
Keyword(s):  
Lymph Node ◽  
Confidence Interval ◽  
Lymph Nodes ◽  
Axillary Lymph Node ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Axillary Lymph ◽  
Validation Group ◽  
Modeling Group ◽  
Binomial Regression

AbstractExtensive clinical trials indicate that patients with negative sentinel lymph node biopsy do not need axillary lymph node dissection (ALND). However, the ACOSOG Z0011 trial indicates that patients with clinically negative axillary lymph nodes (ALNs) and 1–2 positive sentinel lymph nodes having breast conserving surgery with whole breast radiotherapy do not benefit from ALND. The aim of this study is therefore to identify those patients with 0–2 positive nodes who might avoid ALND. A total of 486 patients were eligible for the study with 212 patients in the modeling group and 274 patients in the validation group, respectively. Clinical lymph node status, histologic grade, estrogen receptor status, and human epidermal growth factor receptor 2 status were found to be significantly associated with ALN metastasis. A negative binomial regression (NBR) model was developed to predict the probability of having 0–2 ALN metastases with the area under the curve of 0.881 (95% confidence interval 0.829–0.921, P < 0.001) in the modeling group and 0.758 (95% confidence interval 0.702–0.807, P < 0.001) in the validation group. Decision curve analysis demonstrated that the model was clinically useful. The NBR model demonstrated adequate discriminative ability and clinical utility for predicting 0–2 ALN metastases.

scholarly journals Impact of community piped water coverage on re-infection with urogenital schistosomiasis in rural South Africa

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Polycarp Mogeni ◽  
Alain Vandormael ◽  
Diego Cuadros ◽  
Christopher Appleton ◽  
Frank Tanser
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Primary School Children ◽  
Effective Control ◽  
Urogenital Schistosomiasis ◽  
Percentage Point Increase ◽  
Piped Water ◽  
Point Increase ◽  
Binomial Regression

Previously, we demonstrated that coverage of piped water in the seven years preceding a parasitological survey was strongly predictive of Schistosomiasis haematobium infection in a nested cohort of 1976 primary school children (Tanser, 2018). Here, we report on the prospective follow up of infected members of this nested cohort (N = 333) for two successive rounds following treatment. Using a negative binomial regression fitted to egg count data, we found that every percentage point increase in piped water coverage was associated with 4.4% decline in intensity of re-infection (incidence rate ratio = 0.96, 95% CI: 0.93–0.98, p=0.004) among the treated children. We therefore provide further compelling evidence in support of the scaleup of piped water as an effective control strategy against Schistosoma haematobium transmission.

P1759Elevated NT-pro BNP predicts Heart Failure re-hospitalizations after an acute coronary syndrome

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
E Martinez Rey-Ranal ◽  
A Cordero ◽  
M J Moreno ◽  
V Bertomeu Gonzalez ◽  
J Moreno Arribas ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Coronary Syndrome ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Predictive Capacity ◽  
Coronary Syndrome ◽  
All Cause Mortality ◽  
A Prospective Study ◽  
Grace Score

Abstract Background NT pro-BNP is a well-established biomarker of tissue congestion and has prognostic value in patients with heart failure (HF) and, also, with acute coronary syndrome (ACS). Nonetheless, there is scarce evidence on the predictive capacity of NT pro-BNP for HF re-admission after an ACS. Objective To test whether elevated values of NT pro-BNP can predict subsequent hospitalizations for HF in patients discharged after an ACS. Methods We performed a prospective study of all patients discharged after an ACS in a single center. HF re-admission was analysed by competing risk regression, taking all-cause mortality as a competing event, and results are presented as sub-Hazard Ratio (sHR); recurrent hospitalizations were tested by negative binomial regression and results are presented as incidence risk ratio (IRR). Results We included 1,679 patients, mean age 70.1 (29.7) year, 71.9% males, 41.4% STEMI and mean GRACE score 151.7 (44.4). Median NT pro-BNP was 948.2 pg/ml (IQ range 274.5–2923) and patients were divided in <300U (27.0%), 300–600 pg/ml (13.4%), 600–1000 pg/ml (10.8%) and >1000 pg/ml (46.7%) A total of 132 (5.9%) died within hospitalization and follow-up was available 98% of the patients, with a median follow-up of 33 months (IQ range 16–59). A total of 220 patients (13.1%) had at least one hospital re-admission of HF and 126 (7.5%) had more than one re-hospitalization for HF. Patients with NT pro-BNP had higher un-adjusted HF re-admissions (22.2% vs. 4.4%; p<0.01). Cardiovascular mortality increased significantly in each category of NT pro-BNP (3.8%; 8.0%; 7.7%; 18.5%) as well as all-cause mortality (0.1%; 12.4%; 11.6%; 25.3%), first HF readmission (2.7%; 7.1%; 5.5%; 23.5%); patients with NT pro-BNP had higher rates of recurrent HF readmissions: 11.6/1000 vs. 2.4/1000 patients/years (p<0.01). Multivariate analyses, adjusted by age, gender, GRACE score, left ventricle ejection fraction, revascularization and medical treatments at discharge, identified that NT pro-BNP >1000 pg/ml was associated to HF re-hospitalization (sHR: 2.60 95% CI 1.12–5.95) and recurrent hospitalizations (IRR: 1.10 95% CI 1.04–1.14). Conclusions NT pro-BNP >1000 pg/ml is an accurate risk factor for first and recurrent HF rehospitalisations after an ACS.

Abomasal nematodes of the red deer Cervus elaphus in north-eastern Italy

2007 ◽  
Vol 81 (3) ◽  
pp. 247-253 ◽  
Author(s):  
M.T. Manfredi ◽  
A.R. Di Cerbo ◽  
V. Tranquillo ◽  
C. Nassuato ◽  
L. Pedrotti ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Cervus Elaphus ◽  
Odds Ratio ◽  
Red Deer ◽  
Negative Binomial ◽  
Geographical Area ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Binomial Regression ◽  
North Eastern

AbstractThe composition of the abomasal helminth fauna and parasite diversity were studied in 298 red deer collected during 1997–2000 from three different sectors (Bolzano, Trento and Sondrio provinces) of the Stelvio National Park, one of the main protected areas of north-eastern Italy. The association between parasite burdens and geographical areas of the hosts was assessed using the negative binomial regression. A variety of abomasal helminths, both host specific and generalist, was found in all sectors. The most commonly observed parasites were the Spiculopteragia spiculoptera morph spiculoptera and Ostertagia leptospicularis morph leptospicularis, with prevalences of 79.5% and 40.9%, respectively. The minor morphs S. spiculoptera morph mathevossiani (prevalence 31.9%) and O. leptospicularis morph kolchida (18.8%) occurred at lower prevalences. Teladorsagia circumcincta morph circumcincta, Marshallagia marshalli morph marshalli and Haemonchus contortus were rarer, at prevalences of 1, 1.3 and 1.3%, respectively. Deviance analysis of the negative binomial regression model shows that the geographical area is significantly related to parasite burdens (P = 0.001). Prevalences of hosts with parasites were greater in the Sondrio (odds ratio = 1.31; 95% confidence interval: 0.16–10.85) and smaller in the Trento (odds ratio = 0.62; 95% confidence interval: 0.20–1.96) sectors with respect to Bolzano, but these differences were not statistically significant. Possible cross-infections by more generalist parasites between wild and domestic animals were also suggested, as deer and domestic ruminants (Bovinae, Caprinae and Ovinae) used the same feeding areas of the park sectors.

scholarly journals Model-based comorbidity clusters in patients with heart failure: association with clinical outcomes and healthcare utilization

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Claudia Gulea ◽  
Rosita Zakeri ◽  
Jennifer K. Quint
Keyword(s):  
Heart Failure ◽  
Latent Class ◽  
Negative Binomial ◽  
Cox Regression ◽  
Negative Binomial Regression ◽  
Administrative Claims ◽  
Healthcare Use ◽  
Binomial Regression ◽  
Patients With Heart Failure ◽  
The Usa

Abstract Background Comorbidities affect outcomes in heart failure (HF), but are not reflected in current HF classification. The aim of this study is to characterize HF groups that account for higher-order interactions between comorbidities and to investigate the association between comorbidity groups and outcomes. Methods Latent class analysis (LCA) was performed on 12 comorbidities from patients with HF identified from administrative claims data in the USA (OptumLabs Data Warehouse®) between 2008 and 2018. Associations with admission to hospital and mortality were assessed with Cox regression. Negative binomial regression was used to examine rates of healthcare use. Results In a population of 318,384 individuals, we identified five comorbidity clusters, named according to their dominant features: low-burden, metabolic-vascular, anemic, ischemic, and metabolic. Compared to the low-burden group (minimal comorbidities), patients in the metabolic-vascular group (exhibiting a pattern of diabetes, obesity, and vascular disease) had the worst prognosis for admission (HR 2.21, 95% CI 2.17–2.25) and death (HR 1.87, 95% CI 1.74–2.01), followed by the ischemic, anemic, and metabolic groups. The anemic group experienced an intermediate risk of admission (HR 1.49, 95% CI 1.44–1.54) and death (HR 1.46, 95% CI 1.30–1.64). Healthcare use also varied: the anemic group had the highest rate of outpatient visits, compared to the low-burden group (IRR 2.11, 95% CI 2.06–2.16); the metabolic-vascular and ischemic groups had the highest rate of admissions (IRR 2.11, 95% CI 2.08–2.15, and 2.11, 95% CI 2.07–2.15) and healthcare costs. Conclusions These data demonstrate the feasibility of using LCA to classify HF based on comorbidities alone and should encourage investigation of multidimensional approaches in comorbidity management to reduce admission and mortality risk among patients with HF.

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