Abstract
Objective was to examine the temporal trends in readmission and mortality of heart failure (HF) patients with history of hypertension. This study includes 51 141 patients with history of hypertension who were discharged with a first diagnosis of HF between January 1, 2000, and December 31, 2014. Data were obtained from the Myocardial Infarction Data Acquisition System (MIDAS), a statewide database of all hospitalizations for cardiovascular (CV) disease in New Jersey. The temporal trends of mortality, rates of HF‐specific readmission, and all‐cause readmissions up to 1 year after discharge were examined using multivariable logistic regression. The difference in all‐cause mortality at 3 years between patients who were readmitted compared to those who were not readmitted at 1 year was examined. The number of patients with history of hypertension and HF remained unchanged during the study period. Male gender, black race, comorbidities, and admission to non‐teaching hospitals were predictors of HF readmission and CV mortality (P < .05 for all). Readmission rate for any cause increased during the study period (P < .001) while rates of HF readmissions and mortality remained relatively unchanged. Patients that had been readmitted within a year exhibited a significantly higher 3‐year mortality (P < .001). CV mortality among HF patients with history of hypertension did not change significantly between 2000 and 2014, while the rates of all‐cause readmission increased. Patients who were readmitted had higher 3‐year mortality (P < .001) than those who were not.
Keywords: heart failure, hypertension, population‐based study, readmissions
1. INTRODUCTION
Hypertension frequently antedates the development of heart failure (HF). In the Framingham Heart Study, 91% of all newly diagnosed HF patients had a documented history of hypertension. 1 Heart failure is the most common reason for hospital admission in adults and is associated with impaired quality of life, high mortality, financial burden, and frequent readmissions. 2 , 3 The US health care expenditures on HF reached $30.7 billion between 2011 and 2014, 4 and this number is anticipated to increase to almost $70 billion by 2030. 5 Previous studies have addressed the issues of the incidence, outcomes, and time trends of HF readmissions of patients with history of hypertension. Most of these reports were either from single‐center intervention trials, were review papers and meta‐analyses, used different methodologies, and did not include follow‐up for more than 30 days. Also, these papers did not examine secular changes or did not report on the long‐term mortality of patients who were readmitted as compared to those who were not. 3 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15
The purpose of this study is to describe the incidence, time trends, and outcomes of HF readmissions in a population‐based cohort of 51 141 HF patients with history of hypertension from 2000 to 2014 using the Myocardial Infarction Data Acquisition System (MIDAS) in New Jersey. 16 , 17 , 18 We also examined differences in mortality among patients who were readmitted versus patients who were not.
2. METHODS
2.1. Data sources
The MIDAS database was used to obtain information on patients with history of hypertension who were hospitalized for HF. MIDAS captures the dates of admission and discharge, demographics, insurance type, reason for admission, and selected comorbid conditions. International Classification of Diseases‐Clinical Modification (ICD‐9‐CM) in acute care non‐federal hospitals in New Jersey from 2000 to 2014 was used for the identification of hypertension, HF, and comorbid conditions. The ICD‐9 codes used to identify the above variables are shown in Table S1. Hospital characteristics included hospital location (inner city, urban, rural, and suburban), teaching status (teaching vs non‐teaching), and availability of invasive or interventional procedures. The date and cause of death were obtained from New Jersey Death Registration files. We used “The Link King”, 19 an automated public record linkage and consolidation software that, in a report of 500 000 linked records chosen at random and referred for blinded clerical review, had a positive predictive value of 96.1% and a sensitivity of 96.7%. 20
Patients with history of hypertension who were hospitalized for HF were identified with ICD‐9‐CM primary discharge diagnosis code 428.xx (reason for admission). The cause of death was recorded using the ICD‐10‐CM codes (Table S2).
The information in MIDAS has been validated as correct in 98.8% for vital status at discharge and demographics. 21 Study patients were 18 years or older and history of hypertension who were discharged alive after a first admission for HF. Of the 51 141 patients who fulfilled the inclusion criteria, 1756 (3.4%) were excluded from the statistical analysis because of missing values. Patients with history of cancer and/or HIV were not included in this study.
2.2. Study variables
Study variables included patient demographics, comorbid conditions, hospital characteristics [teaching/non‐teaching, geographic location, facilities for percutaneous coronary intervention (PCI)], length of stay (LOS), and insurance type.
2.3. Outcomes—Statistics
Outcomes were CV and all‐cause death, readmission for HF, and all‐cause readmission at 30 days, 90 days, and 180 days and at 1 year. Multivariable logistic regression models adjusted for demographics, hospital characteristics, LOS, and the comorbid conditions listed above were developed. The time trends of the end points were examined using linear models. The effect of readmission on all‐cause death at 3 years in HF patients with history of hypertension who were readmitted as compared to those who were not readmitted was studied using logistic regression. This study was approved by the Rutgers Health Sciences Institutional Review Board.
3. RESULTS
3.1. Outcomes at 30 days, 90 days, and 180 days and at 1 year following discharge
The number of patients with history of hypertension and a first diagnosis of HF as the reason for admission who were discharged alive by year of admission ranged from 3065 to 3655 per year (Table 1). The number of patients with history of hypertension and HF remained unchanged during the study period (Figure 1). All‐cause readmissions demonstrated a statistically significant positive slope by 0.478 percent per year (95% CI: 0.317‐0.639, P < .001) while linear trends of 1‐year outcomes with respect to HF readmissions, all‐cause mortality and CV mortality there were not altered considerably (Figure 2). At 1 year, more than sixty per cent of the patients were readmitted (61.3%) and more than one‐fifth (21.4%) died. About one half of the study patients were admitted to teaching hospitals (47.8%), while 43.8% of the patients were admitted to hospitals with PCI facilities. Over one sixth (17.9%) of the patients were admitted to hospitals located in an inner city, 24.1% to hospitals in urban areas, 42.5% in suburb locations and 12.1% to hospitals in rural areas (Table 2). The baseline characteristics of the study population are described in Table 3 (Table 3).
Table 1.
Number of first heart failure admissions by year
| Year | Counts | First heart failure diagnosis |
|---|---|---|
| 2000 | 3303 | 74.4 |
| 2001 | 3300 | 74.5 |
| 2002 | 3540 | 74.2 |
| 2003 | 3566 | 74.7 |
| 2004 | 3300 | 74.5 |
| 2005 | 3276 | 75.3 |
| 2006 | 3084 | 75.2 |
| 2007 | 3065 | 75.3 |
| 2008 | 3465 | 74.9 |
| 2009 | 3510 | 75.5 |
| 2010 | 3576 | 75.1 |
| 2011 | 3474 | 74.7 |
| 2012 | 3408 | 75.2 |
| 2013 | 3623 | 74.9 |
| 2014 | 3651 | 74.9 |
| TOTAL | 51 141 |
Figure 1.
Number of first HF discharges. Total of 51 141 patients with history of hypertension, no prior HF
Figure 2.
Cardiovascular outcome trends in HF patients with history of hypertension
Table 2.
Characteristics of heart failure patients with history of hypertension
| Description | Number of Patients | Percent Patients |
|---|---|---|
| Number of Heart Failure Patients | 51 141 | |
| Mean age at first heart failure admission ± S.D | 74.9 ± 14.1 | |
| Male (%) | 22 888 | 44.8 |
| Race (%) | ||
| White | 38 262 | 74.8 |
| Black | 7992 | 15.6 |
| Other | 4887 | 9.6 |
| Ethnicity (%) | ||
| Hispanic | 4007 | 7.8 |
| Non‐Hispanic | 42 909 | 83.9 |
| Unknown | 4225 | 8.3 |
| Insurance (%) | ||
| Commercial | 12 871 | 25.2 |
| Medicare | 35 719 | 69.8 |
| Medicaid/Self‐Pay/Other | 2551 | 5 |
| Admission Hospital Type (%) | ||
| Teaching | 24 420 | 47.8 |
| Non‐Teaching | 24 965 | 48.8 |
| Unknown | 1756 | 3.4 |
| Admission to Hospital Area (%) | ||
| Urban | 12 310 | 24.1 |
| Inner city | 9168 | 17.9 |
| Rural | 6194 | 12.1 |
| Suburb | 21 713 | 42.5 |
| Unknown | 1756 | 3.4 |
| Admission Hospital Cath Lab | ||
| Cath Lab | 22 410 | 43.8 |
| No Cath Lab | 26 975 | 52.7 |
| Unknown | 1756 | 3.4 |
Table 3.
Baseline characteristics
| Description | Number of patients | Percent patients |
|---|---|---|
| Prior AF | 14 278 | 27.9 |
| Prior AMI | 6883 | 13.5 |
| History of anemia | 13 188 | 25.8 |
| History of kidney disease | 5104 | 10 |
| History of COPD | 13 086 | 25.6 |
| History of diabetes | 21 193 | 41.4 |
| History of hyperlipidemia | 22 879 | 44.7 |
| History OSA | 1028 | 2 |
| Parkinson | 900 | 1.8 |
| Prior stroke | 3924 | 7.7 |
| Prior TIA | 3610 | 7.1 |
Abbreviations: AF, Atrial fibrillation; AMI, Acute Myocardial infarction; and TIA, Transient ischemic attack; COPD, Chronic obstructive pulmonary disease; OSA, Obstructive sleep apnea.
All‐cause and HF readmissions are presented in Tables S3 and S4. All‐cause readmission rates at 30 days and 1 year were 20.7% and 61.29%, respectively (Table S3), whereas HF‐specific readmission occurred for 6.34% of the patients at 30 days and 21.43% at 1 year (Table S4). The unadjusted 30‐day readmission rates as well as all‐cause and CV death remained relatively stable (Tables S3,S5, and S6).
Predictors of higher all‐cause readmission at 1 year were LOS (odds ratio [OR]: 1.04, 95% CI: 1.02‐1.06), anemia (OR: 1.20, 95% CI: 1.15‐1.26), atrial fibrillation/flutter (OR: 1.08, 95% CI: 1.04‐1.13), CKD (OR: 1.35, 95% CI: 1.26‐1.45), COPD (OR: 1.25, 95% CI: 1.20‐1.30), diabetes (OR: 1.23, 95% CI: 1.18‐1.28), hyperlipidemia (OR: 1.14, 95% CI: 1.10‐1.19), and admission to a non‐teaching hospital (OR: 1.10, 95% CI: 1.05‐1.15) (P < .001 for all, Table 4). Patients with commercial insurance were less likely to be readmitted (OR: 0.88, 95% CI: 0.84‐0.93, P < .001), and male gender was associated with better outcomes (OR: 0.94, 95% CI: 0.90‐0.98, P < .001).
Table 4.
All‐cause readmissions
| Risk Factor | 30‐Day | 90‐Day | 180‐Day | 1‐Year |
|---|---|---|---|---|
| Chronic Kidney Disease |
1.297 (1.206, 1.394) <0.001 |
1.309 (1.228, 1.395) <0.001 |
1.326 (1.244, 1.395) <0.001 |
1.35 (1.26, 1.446) <0.001 |
| Stroke |
1.252 (0.967, 1.621) 0.088 |
1.222 (0.973, 1.535) 0084 |
1.191 (0.95, 1.493) 0.130 |
1.282 (1.007, 1.631) 0.044 |
| Parkinson |
1.199 (1.024, 1.405) 0.024 |
1.194 (1.041, 1.37) 0.011 |
1.112 (0.971, 1.273) 0.124 |
1.219 (1.059, 1.404) 0.006 |
| Anemia |
1.190 (1.132, 1.251) <0.001 |
1.198 (1.148, 1.251) <0.001 |
1.205 (1.156, 1.257) <0.001 |
1.203 (1.151, 1.257) <0.001 |
| Diabetes |
1.120 (1.07, 1.173) <0.001 |
1.16 (1.116, 1.206) <0.001 |
1.194 (1.15, 1.24) <0.001 |
1.228 (1.181, 1.277) <0.001 |
| Chronic Obstructive Pulmonary Disease |
1.132 (1.077, 1.19) <0.001 |
1.162 (1.114, 1.212) <0.001 |
1.195 (1.146, 1.245) <0.001 |
1.249 (1.196, 1.304) <0.001 |
| Length of Stay |
1.128 (1.101, 1.156) <0.001 |
1.121 (1.098, 1.144) <0.001 |
1.09 (1.069, 1.112) <0.001 |
1.038 (1.017, 1.059) <0.001 |
| Acute Myocardial Infarction |
1.098 (1.03, 1.17) 0.004 |
1.07 (1.013, 1.13) 0.0015 |
1.027 (0.974, 1.084) 0.320 |
1.001 (0.948, 1.058) 0.959 |
| Area: Inner City Area vs Urban |
1.047 (0.977, 1.122) 0.191 |
1.066 (1.006, 1.13) 0.031 |
1.039 (0.982, 1.1) 0.186 |
1.034 (0.975, 1.096) 0.263 |
| Hosp: Non‐Teaching vs Teaching |
1.064 (1.003, 1.129) 0.040 |
1.046 (0.995, 1.1) 0.076 |
1.075 (1.024, 1.128) <0.003 |
1.098 (1.045, 1.154) <0.001 |
| Discharge year |
1.022 (1.016, 1.028) <0.001 |
1.02 (1.015, 1.024) <0.001 |
1.019 (1.014, 1.024) <0.001 |
1.013 (1.008, 1.017) <0.001 |
| Area: Suburb Area vs Urban |
1.008 (0.953, 1.066) 0.782 |
1.038 (0.99, 1.088) 0.124 |
1.006 (0.961, 1.053) 0.797 |
0.983 (0.937, 1.03) 0.464 |
| Hyperlipidemia |
1.021 (0.974, 1.07) 0.388 |
1.081 (1.038, 1.125) <0.001 |
1.096 (1.054, 1.139) <0.001 |
1.141 (1.097, 1.187) <0.001 |
| Atrial Fibrillation/Atrial Flutter |
1.021 (0.971, 1.073) 0.425 |
1.045 (1.002, 1.091) 0.040 |
1.054 (1.012, 1.098) 0.0012 |
1.083 (1.038, 1.129) <0.001 |
| Insurance: Medicaid/Self‐Pay/Other vs Medicare |
1.071 (0.96, 1.194) 0.220 |
0.964 (0.878, 1.059) 0.446 |
1.013 (0.925, 1.11) 0.775 |
1.054 (0.958, 1.16) 0.282 |
| Male vs Female |
0.969 (0.925, 1.014) 0.175 |
0.975 (0.938, 1.014) 0.202 |
0.963 (0.928, 1.0) 0.050 |
0.939 (0.904, 0.976) <0.001 |
| Age (X10) |
0.966 (0.947, 0.985) <0.001 |
0.954 (0.938, 0.97) <0.001 |
0.939 (0.924, 0.955) <0.001 |
0.929 (0.914, 0.945) <0.001 |
| Hospital: No Cath Lab vs Cath Lab |
0.98 (0.924, 1.039) 0.501 |
1.01 (0.961, 1.061) 0.707 |
0.998 (0.952, 1.047) 0.944 |
1.019 (0.97, 1.07) 0.459 |
| Race: Other vs White |
0.937 (0.867, 1.014) 0.106 |
0.91 (0.852, 0.972) 0.005 |
0.95 (0.891, 1.013) 0.115 |
0.964 (0.903, 1.03) 0.278 |
| Race: Black vs White |
0.954 (0.891, 1.022) 0.179 |
1.031 (0.973, 1.092) 0.298 |
1.11 (1.05, 1.174) <0.001 |
1.129 (1.066, 1.197) <0.001 |
| Ethnicity: Non‐Hispanic vs Hispanic |
0.947 (0.868, 1.032) 0.214 |
0.841 (0.781, 0.904) <0.001 |
0.858 (0.798, 0.922) <0.001 |
0.87 (0.807, 0.937) <0.001 |
| Sleep Apnea |
0.92 (0.787, 1.075) 0.294 |
0.887 (0.776, 1.013) 0.077 |
0.946 (0.831, 1.078) 0.405 |
1.00 (0.871, 1.148) 1.000 |
| Insurance: Commercial vs Medicare |
0.899 (0.848, 0.953) <0.001 |
0.873 (0.831, 0.917) <0.001 |
0.864 (0.824, 0.906) <0.001 |
0.883 (0.841, 0.927) <0.001 |
| Ethnicity: Unknown vs Hispanic |
0.871 (0.777, 0.976) 0.018 |
0.781 (0.71, 0.859) <0.001 |
0.8 (0.729, 0.877) <0.001 |
0.809 (0.736, 0.89) <0.001 |
| Area: Rural Area vs Urban |
0.866 (0.797, 0.94) <0.001 |
0.878 (0.82, 0.941) <0.001 |
0.842 (0.789, 0.899) <0.001 |
0.822 (0.769, 0.878) <0.001 |
| Transient Ischemic Attack |
0.851 (0.65, 1.114) 0.241 |
0.891 (0.703, 1.129) 0.339 |
0.919 (0.726, 1.162) 0.480 |
0.859 (0.669, 1.103) 0.233 |
Logistic regression identified black race (OR: 1.25, 95% CI: 1.17‐1.33), stroke (OR: 1.54, 95% CI: 1.2‐1.96), history of AMI (OR: 1.12, 95% CI: 1.05‐1.19), COPD (OR: 1.09, 95% CI: 1.03‐1.14), and diabetes (OR: 1.21, 95% CI: 1.15‐1.26), as important predictors of HF readmission for HF at 1 year of follow‐up, (P < .001 for all, Table 5). A similar effect of insurance type was observed for HF readmissions (OR: 0.92, 95% CI: 0.87‐0.97, P < .001).
Table 5.
Heart failure readmissions
| Risk Factor | 30‐Day | 90‐Day | 180‐Day | 1‐Year |
|---|---|---|---|---|
| Stroke |
1.917 (1.349, 2.722) <0.001 |
1.435 (1.06, 1.942) 0.019 |
1.398 (1.064, 1.836) 0.016 |
1.535 (1.202, 1.96) <0.001 |
| Hospital: No Cath Lab vs Cath Lab |
1.175 (1.065, 1.296) 0.001 |
1.098 (1.019, 1.183) 0.014 |
1.08 (1.012, 1.153) 0.020 |
1.047 (0.987, 1.11) 0.010 |
| Acute Myocardial Infarction |
1.219 (1.1, 1.351) <0.001 |
1.195 (1.105, 1.293) <0.001 |
1.133 (1.057, 1.215) <0.001 |
1.12 (1.052, 1.193) <0.001 |
| Insurance: Medicaid/Self‐Pay/Other vs Medicare |
1.27 (1.074, 1.502) 0.005 |
1.244 (1.092, 1.417) 0.001 |
1.235 (1.101, 1.386) <0.001 |
1.19 (1.072, 1.321) 0.001 |
| Area: Suburb Area vs Urban |
1.096 (0.997, 1.204) 0.058 |
1.053 (0.98, 1.131) 0.157 |
1.051 (0.987, 1.119) 0.122 |
1.01 (0.955, 1.068) 0.719 |
| Diabetes |
1.11 (1.029, 1.198) 0.007 |
1.153 (1.088, 1.221) <0.001 |
1.172 (1.114, 1.233) <0.001 |
1.208 (1.154, 1.264) <0.001 |
| Race: Black vs White |
1.053 (0.942, 1.178) 0.360 |
1.14 (1.048, 1.24) 0.002 |
1.21 (1.125, 1.302) <0.001 |
1.248 (1.169, 1.333) <0.001 |
| Chronic Kidney Disease |
1.106 (0.978, 1.25) 0.108 |
1.1 (1.001, 1.209) 0.048 |
1.073 (0.987, 1.166) 0.098 |
1.078 (1, 1.162) 0.050 |
| Length of Stay |
1.06 (1.018, 1.103) 0.005 |
1.055 (1.023, 1.087) <0.001 |
1.058 (1.03, 1.086) <0.001 |
1.034 (1.009, 1.058) <0.001 |
| Anemia |
1.051 (0.966, 1.145) 0.249 |
1.026 (0.962, 1.095) 0.434 |
1.026 (0.969, 1.086) 0.376 |
1.037 (0.986, 1.091) 0.157 |
| Hospital: Non‐Teaching vs Teaching |
1.006 (0.912, 1.11) 0.897 |
1.032 (0.957, 1.112) 0.417 |
1.072 (1.004, 1.145) 0.037 |
1.092 (1.03, 1.159) 0.003 |
| Area: Inner City Area vs Urban |
1.036 (0.922, 1.163) 0.554 |
1.071 (0.981, 1.168) 0.124 |
1.107 (1.026, 1.194) 0.009 |
1.073 (1.003, 1.149) 0.040 |
| COPD |
1.023 (0.941, 1.112) 0.594 |
1.047 (0.983, 1.116) 0.152 |
1.059 (1.002, 1.119) 0.043 |
1.086 (1.033, 1.141) 0.001 |
| Discharge year |
1.012 (1.002, 1.021) 0.013 |
1.007 (1, 1.014) 0.047 |
1.006 (1, 1.013) 0.040 |
0.999 (0.993, 1.004) 0.707 |
| Area: Rural Area vs Urban |
0.995 (0.87, 1.137) 0.941 |
0.985 (0.89, 1.09) 0.770 |
0.941 (0.86, 1.029) 0.183 |
0.936 (0.864, 1.014) 0.105 |
| Atrial Fibrillation/Atrial Flutter |
0.994 (0.913, 1.082) 0.892 |
1.055 (0.99, 1.125) 0.098 |
1.076 (1.017, 1.137) 0.010 |
1.063 (1.011, 1.117) 0.017 |
| Hyperlipidemia |
0.956 (0.884, 1.035) 0.264 |
1.031 (0.971, 1.095) 0.314 |
1.045 (0.992, 1.101) 0.100 |
1.055 (1.007, 1.106) 0.024 |
| Race: Other vs White |
0.914 (0.802, 1.043) 0.183 |
0.899 (0.813, 0.994) 0.038 |
0.914 (0.837, 0.998) 0.046 |
0.966 (0.894, 1.044) 0.382 |
| Age (X10) |
0.962 (0.932, 0.994) 0.019 |
0.99 (0.966, 1.015) 0.429 |
0.989 (0.967, 1.01) 0.305 |
0.984 (0.964, 1.005) 0.111 |
| Insurance: Commercial vs Medicare |
0.976 (0.886, 1.074) 0.616 |
0.93 (0.864, 1.001) 0.055 |
0.914 (0.857, 0.975) 0.007 |
0.919 (0.868, 0.974) 0.004 |
| Male vs Female |
1.079 (1, 1.164) 0.051 |
1.059 (1, 1.122) 0.052 |
1.05 (0.998, 1.104) 0.061 |
1.051 (1.005, 1.1) 0.030 |
| Ethnicity: Non‐Hispanic vs Hispanic |
0.858 (0.747, 0.985) 0.030 |
0.806 (0.726, 0.895) <0.001 |
0.834 (0.76, 0.915) <0.001 |
0.833 (0.767, 0.906) <0.001 |
| Sleep Apnea |
0.803 (0.61, 1.057) 0.117 |
0.775 (0.627, 0.959) 0.019 |
0.789 (0.656, 0.949) 0.012 |
0.814 (0.693, 0.958) 0.013 |
| Ethnicity: Unknown vs Hispanic |
0.723 (0.598, 0.875) <0.001 |
0.765 (0.664, 0.88) <0.001 |
0.813 (0.719, 0.92) <0.001 |
0.781 (0.699, 0.872) <0.001 |
| Parkinson |
0.767 (0.561, 1.049) 0.097 |
0.834 (0.666, 1.045) 0.114 |
0.871 (0.718, 1.057) 0.162 |
0.921 (0.778, 1.091) 0.342 |
| Transient Ischemic Attack |
0.472 (0.324, 0.687) <0.001 |
0.65 (0.472, 0.894) 0.008 |
0.681 (0.511, 0.907) 0.009 |
0.653 (0.505, 0.843) 0.001 |
Logistic regression identified age per 10 years (OR: 1.57, 95% CI: 1.53‐1.60), male gender (OR: 1.18, 95% CI: 1.12‐1.23), LOS (OR: 1.46, 95% CI: 1.43‐1.50), anemia (OR: 1.30, 95% CI: 1.23‐1.36), history of AMI (OR: 1.23, 95% CI: 1.15‐1.31), COPD (OR: 1.23, 95% CI: 1.17‐1.29), CKD (OR: 1.37, 95% CI: 1.27‐1.48), stroke (OR: 1.53, 95% CI: 1.19‐1.96), and Parkinson's disease (OR: 1.34, 95% CI: 1.15‐1.55), as important predictors of all‐cause mortality at 1 year (P < .001 for all, Table 6). Commercial insurance was associated with lower all‐cause mortality (OR: 0.82, 95% CI: 0.78‐0.86, P < .001).
Table 6.
All‐cause death
| Risk Factor | 30‐Day | 90‐Day | 180‐Day | 1‐Year |
|---|---|---|---|---|
| Length of Stay |
1.753 (1.668, 1.842) <0.001 |
1.691 (1.632, 1.753) <0.001 |
1.58 (1.533, 1.629) <0.001 |
1.463 (1.425, 1.501) <0.001 |
| Age (X10) |
1.667 (1.589, 1.75) <0.001 |
1.62 (1.567, 1.675) <0.001 |
1.592 (1.548, 1.636) <0.001 |
1.567 (1.531, 1.604) <0.001 |
| Ethnicity: Non‐Hispanic vs Hispanic |
1.305 (1.048, 1.625) 0.017 |
1.39 (1.193, 1.618) <0.001 |
1.458 (1.285, 1.655) <0.001 |
1.442 (1.297, 1.602) <0.001 |
| Ethnicity: Unknown vs Hispanic |
1.388 (1.07, 1.801) 0.014 |
1.402 (1.168, 1.683) <0.001 |
1.393 (1.195, 1.624) <0.001 |
1.364 (1.199, 1.552) <0.001 |
| Parkinson |
1.221 (0.934, 1.596) 0.145 |
1.371 (1.136, 1.655) 0.001 |
1.335(1.132, 1.575) <0.001 |
1.335 (1.151, 1.547) <0.001 |
| Chronic Kidney Disease |
1.294 (1.123, 1.491) <0.001 |
1.327 (1.198, 1.47) <0.001 |
1.337 (1.225, 1.459) <0.001 |
1.369 (1.267, 1.478) <0.001 |
| Stroke |
1.188 (0.731, 1.933) 0.487 |
1.518 (1.1, 2.096) 0.011 |
1.588 (1.204, 2.094) 0.001 |
1.525 (1.188, 1.957) <0.001 |
| Acute Myocardial Infarction |
1.172 (1.031, 1.332) 0.015 |
1.218 (1.113, 1.334) <0.001 |
1.205 (1.116, 1.301) <0.001 |
1.229 (1.15, 1.313) <0.001 |
| Anemia |
1.136 (1.031, 1.252) 0.010 |
1.145 (1.068, 1.228) <0.001 |
1.256 (1.185, 1.333) <0.001 |
1.296 (1.231, 1.364) <0.001 |
| Area: Suburb Area vs Urban |
1.153 (1.032, 1.287) 0.012 |
1.061 (0.981, 1.147) 0.136 |
1.061 (0.993, 1.134) 0.079 |
1.054 (0.996, 1.117) 0.071 |
| Chronic Obstructive Pulmonary Disease |
1.183 (1.073, 1.305) <0.001 |
1.177 (1.097, 1.262) <0.001 |
1.185 (1.117, 1.257) <0.001 |
1.228 (1.167, 1.293) <0.001 |
| Area:Rural Area vs Urban |
1.207 (1.03, 1.413) 0.020 |
1.061 (0.948, 1.188) 0.300 |
1.037 (0.942, 1.141) 0.458 |
0.984 (0.906, 1.069) 0.707 |
| Hospital: No Cath Lab vs Cath Lab |
1.03 (0.922, 1.151) 0.602 |
1.025 (0.946, 1.11) 0.549 |
1.012 (0.946, 1.084) 0.723 |
1.036 (0.977, 1.1) 0.237 |
| Atrial Fibrillation/Atrial Flutter |
1.096 (0.999, 1.202) 0.052 |
1.055 (0.987, 1.128) 0.115 |
1.047 (0.989, 1.108) 0.113 |
1.013 (0.964, 1.064) 0.620 |
| TIA |
1.11 (0.671, 1.838) 0.685 |
0.835 (0.596, 1.17) 0.295 |
0.792 (0.593, 1.057) 0.113 |
0.819 (0.631, 1.062) 0.132 |
| Sleep Apnea |
0.962 (0.646, 1.432) 0.848 |
0.89 (0.67, 1.183) 0.422 |
0.886 (0.701, 1.119) 0.310 |
0.885 (0.728, 1.076) 0.222 |
| Discharge year |
1.028 (1.016, 1.039) <0.001 |
1.021 (1.013, 1.029) <0.001 |
1.015 (1.008, 1.022) <0.001 |
1.006 (1.001, 1.012) 0.030 |
| Area: Inner City Area vs Urban |
0.918 (0.785, 1.075) 0.288 |
0.924 (0.83, 1.029) 0.152 |
0.982 (0.898, 1.073) 0.684 |
0.97 (0.899, 1.047) 0.438 |
| Hospital: Non‐Teaching vs Teaching |
0.953 (0.853, 1.065) 0.393 |
1.006 (0.929, 1.09) 0.875 |
1.003 (0.937, 1.074) 0.924 |
1.02 (0.961, 1.082) 0.516 |
| Diabetes |
0.953 (0.6, 1.049) 0.329 |
0.969 (0.905, 1.037) 0.357 |
0.983 (0.929, 1.041) 0.566 |
1 (0.953, 1.05) 0.991 |
| Insurance: Medicaid/Self‐Pay/Other vs Medicare |
0.88 (0.612, 1.266) 0.492 |
0.905 (0.715, 1.145) 0.405 |
0.984 (0.82, 1.181) 0.863 |
1.003 (0.867, 1.161) 0.964 |
| Insurance: Commercial vs Medicare |
0.895 (0.784, 1.021) 0.100 |
0.865 (0.788, 0.948) 0.002 |
0.838 (0.776, 0.905) <0.001 |
0.803 (0.752, 0.857) <0.001 |
| Male vs Female |
1.173 (1.071, 1.285) <0.001 |
1.179 (1.105, 1.258) <0.001 |
1.183 (1.12, 1.25) <0.001 |
1.177 (1.122, 1.234) <0.001 |
| Race: Other vs White |
0.79 (0.66, 0.946) 0.010 |
0.836 (0.739, 0.945) 0.004 |
0.843 (0.761, 0.934) 0.001 |
0.83 (0.761, 0.906) <0.001 |
| Hyperlipidemia |
0.736 (0.668, 0.811) <0.001 |
0.747 (0.698, 0.8) <0.001 |
0.768 (0.725, 0.813) <0.001 |
0.769 (0.732, 0.808) <0.001 |
| Race: Black vs White |
0.731 (0.616, 0.869) <0.001 |
0.783 (0.698, 0.879) <0.001 |
0.832 (0.758, 0.914) <0.001 |
0.904 (0.837, 0.977) 0.011 |
Logistic regression identified age (OR: 1.50 per 10 years, 95% CI: 1.45‐1.55), male gender (OR: 1.17, 95% CI: 1.09‐1.24), LOS (OR: 1.30, 95% CI: 1.25‐1.34), anemia (OR: 1.14, 95% CI: 1.07‐1.23), history of AMI (OR: 1.33, 95% CI: 1.22‐1.45), COPD (OR: 1.11, 95% CI: 1.03‐1.19), stroke (OR: 1.73, 95% CI: 1.28‐2.35), and admission to a non‐teaching hospital (OR: 1.14, 95% CI: 1.05‐1.23), as important predictors of CV mortality at 1 year, (P < .001 for all, Table S7).
Table 7 describes the outcomes of interest by age group. All comparisons for these outcomes were statistically significant to the point of P < .005 except for HF Readmission of patients aged 75‐84 years old which was significant to the point of P < .05.
Table 7.
Outcomes by age group
| Outcome | Age group | OR | 95% CILB | 95% CIUB | P‐value |
|---|---|---|---|---|---|
| All‐cause readmission | 75‐84 | 0.93 | 0.89 | 0.97 | .002 |
| All‐cause readmission | >85 | 0.84 | 0.80 | 0.87 | <.001 |
| HF readmission | 75‐84 | 0.95 | 0.90 | 1.00 | .037 |
| HF readmission | >85 | 0.91 | 0.87 | 0.96 | <.001 |
| All‐cause death | 75‐84 | 2.13 | 2.01 | 2.26 | <.001 |
| All‐cause death | >85 | 4.48 | 4.24 | 4.73 | <.001 |
| CV death | 75‐84 | 2.21 | 2.03 | 2.40 | <.001 |
| CV death | >85 | 3.96 | 3.66 | 4.27 | <.001 |
Abbreviations: CV, Cardiovascular; HF, Heart failure.
The most common causes of readmission at 1 year, present in at least 1% of the patients with history of hypertension, were grouped into 13 categories and are presented in Figure 3. HF was the most common reason for readmission followed by respiratory, heart, and CKD. In the aggregate, all reasons for readmission with rates below 1% accounted for 21.7% of the total. Approximately 4 out of 10 patients (38.7%) discharged following an admission for HF were not readmitted within a year.
Figure 3.
HF patients with history of hypertension readmissions by reason for readmission
There were no significant trends for all‐cause and CV mortality. Using a logistic regression model with log2 of number of days to readmission as a predictor of 1‐year all‐cause mortality, we estimated an odds ratio of 0.816 (95% CI: 0.805‐0.827, P < 0,001).
3.2. All‐cause mortality of patients with history of hypertension who were readmitted as compared to those who were not readmitted
All‐cause 3‐year mortality among HF patients discharged alive was significantly higher in patients who were readmitted within 1 year from the index hospitalization (OR: 1.31, 95% CI: 1.26‐1.36, P < .001). The 3‐year all‐cause mortality adjusted for all covariates remained significantly higher in patients who were readmitted vs those not readmitted (OR: 1.49, 95% CI: 1.45‐1.54, P < .001). Figure 4 shows the odds ratios for all‐cause mortality at 3 years from the index HF admission comparing patients readmitted versus those who were not readmitted by reason for readmission. Readmission for AMI, CKD, acute infection, or cerebrovascular accident increased the risk of 3‐year mortality.
Figure 4.
Odds ratios of 3‐y all‐cause mortality by reason for readmission
Figure 5 presents the adjusted 3‐year mortality rates of HF patients re‐hospitalized for various reasons. Logistic regression determined history of AMI (OR: 2.2, 95% CI: 1.91‐2.55), infections (OR: 2.01, 95% CI: 1.74‐2.32), CKD (OR: 1.91, 95% CI: 1.73‐2.11), stroke (OR: 1.83, 95% CI: 1.49‐2.26), and patients with respiratory disease (OR: 1.29, 95% CI: 1.19‐1.41, P < .001 for all), as predictors of mortality within 3 years following discharge among patients with a first diagnosis of HF. The effect of these comorbid conditions on all‐cause mortality is higher than that observed in a mixed cohort of HF patients with and without history of hypertension (prior AMI OR:1.42 95% CI: 1.26‐1.60, infection‐related readmission OR:1.32 95% CI: 1.17‐1.49, history of kidney disease OR:1.20 95% CI: 1.10‐1.31, stroke OR:1.15 95% CI: 0.97‐1.35, respiratory disease was non‐significant, respectively).
Figure 5.
Odds ratios of 3‐y all‐cause mortality adjusted for all covariates
4. DISCUSSION
In this study, the number of HF readmission of patients with history of hypertension remained relatively stable. All‐cause readmissions increased significantly during the period of observation (P < .001) while all‐cause and CV mortality remained unchanged. This has been attributed to a decreased case fatality of AMI. 22
More than sixty per cent of the patients were readmitted within a year, and patients with longer LOS, anemia, CKD, and COPD were more likely to be readmitted. Patients with history of hypertension who were readmitted had higher 3‐year all‐cause mortality as compared to those who were not readmitted. Hypertension during an emergency department visit is a powerful predictor of future hospitalizations for heart failure during an 18‐month follow‐up period compared with normotension. 23 The findings of Fernandez‐Gasso et al on 30‐day HF readmissions are similar to ours. 24 Also, Bottle et al reported that HF, ischemic heart disease, cardiac dysrhythmias, and diseases of the respiratory or genitourinary system were common reasons for readmission, findings congruent with the results of this report. 25 Likewise, Davis et al, in an all‐payer analysis of HF hospitalizations, found that comorbid conditions similar to those described in this paper were associated with higher rate of readmission up to 30 days. 26 Gulea et al reported that HF patients with COPD were at significantly higher risk of readmission, a finding similar to the present study. 27
Our observation that certain comorbid conditions helped to predict mortality has been documented by previous investigators. Fonarow et al observed that patients with ischemia and those with worsening renal function had a higher mortality at follow‐up. 28 In OPTIMIZE‐HF, high systolic blood pressure was an independent predictor of morbidity and mortality, similar to the findings of the present study. Investigators from both the PRESERVE and OPTIMIZE‐HF studies highlighted that kidney disease is a strong predictor of mortality, an association also reported by Lawson et al in a UK national study. 28 , 29 , 30
Ruigomez et al, reporting on 3516 patients in The Health Improvement Network primary care database, also found higher mortality among patients readmitted for HF. 31 A publication from Alon et al among 9355 HF patients with infection‐related readmissions reported increased mortality over a 10‐year period. 32 Similarly, results from the GREAT registry indicated a higher 90‐day risk of death after a hospitalization for acute infection. 33 Similar to our findings of increased mortality with infections, are the findings of Panhwar et al of an association between influenza and increased inpatient morbidity and mortality. 34 Gerber et al reported that HF markedly increases the risk of death after MI regardless of ejection fraction. 35
In the present study, LOS was associated with higher all‐cause readmission and all‐cause mortality, similar to the results of Khan et al from the EVEREST Trial. 36 Samsky et al in their recent study on trends in readmission and LOS for hospitalized patients with HF in Canada and the United States reported similar results with respect to 30‐day readmission rates. The baseline characteristics of the US cohort are similar with respect to demographics of this study. 5 It appears that being longer inpatient did not result in lowering the chance of readmission and death by stabilizing and better treating the patients. Rather, the reason for the higher case fatality and rate of readmission was probably due to a more advanced staged of HF in these patients. Additionally, longer duration of hospitalization exposes inpatients to frequent and potentially serious complications such as line sepsis, falls after cerebrovascular accidents and pressure ulcers.
Samsky et al did not report on readmission up to 1 year and did not examine mortality. 5 This limitation of the study by Samsky et al is emphasized by Su et al who stated that the 30‐day readmission rate is not an optimal standard for HF management. 37 The effects of comorbid conditions and race observed by these authors are congruent to our results. 38 Su et al recommend that in the future, process indicators will provide additional benefits in the evaluation and treatment of HF, as also reported by Fischer et al and Barbayannis et al. 38 , 39 These studies reported findings similar to ours although they have the drawbacks outlined in introduction, for example, most were from a single‐center, were reviews or meta‐analyses, did not include follow‐up for more than 30 days, did not examine secular changes, and did not report on the long‐term mortality of patients who were readmitted.
Bradley et al and Bilchick et al reported that specific strategies employed before discharge resulted in decreased readmission rates and expense, 40 , 41 while Van Spall et al reported that implementation of a patient‐centered transitional care model did not improve clinical outcomes. 42 However, the results from a review from Delgado‐Passler indicated that a telemanagement program after hospital discharge would result in less frequent rehospitalizations and improvement of the patient's quality of life. 43 Van spall also noticed Nurse home visits and Disease management clinics reduce all‐cause mortality and all‐cause readmissions after hospitalization for HF. 44
The time range of this study did not include enough data to examine the effect of the Hospital Readmission Reduction Program (HRRP) since the data collection ended in 2014. Khera and colleagues reported that the announcement or implementation of the HRRP was not associated with an increase in in‐hospital or post‐discharge mortality. 45 This was attributed to the fact that physicians did not adopt strategies that specifically deferred admissions. 46 Conversely, Wadhera et al studying 7.9 million Medicare beneficiaries with HF, MI, and pneumonia published that the HRRP announcement and implementation was associated with an increase in post‐discharge mortality. 47
An important limitation of this study is that confounders such as clinical and laboratory data including hemodynamic status, left ventricular function, physical findings, and hospital programs designed to decrease the rate of readmissions are not included in the dataset. Also, the severity of HF and information on medications used during hospitalization or prescribed at discharge is not included in the dataset. It is possible that the use of different medication classes (eg, diuretics, β‐blockers, or calcium channel blockers) was associated with different rates of readmission and mortality. However, the present study has significant strengths, including that the data are derived from a statewide database, and an assessment of trends over a 15‐year period. Also, this New Jersey statewide database represents a population of approximately 9 million residents that has characteristics similar in ethnicity, age, household mean income, and education to the United States a whole. 48 Moreover, health insurance coverage in NJ resembles that of the United States. 49 The large size of the study that includes every patient admitted with HF in New Jersey over a 15‐year period draws from an unselected and unbiased population gives additional credence to our conclusions.
In summary, this study of 51 141 patients with history of hypertension who were discharged alive with a diagnosis of HF between 2000 and 2014 shows that the number of patients admitted for the first time for HF did not change during the 15 years of the study, that more than sixty per cent of these patients were readmitted within 1 year, and that patients who were readmitted had a significantly higher all‐cause mortality over a 3‐year period than those who were not readmitted. The take home message of this study is that attention to modifiable risk factors such as diabetes and hypercholesterolemia and discharge management to prevent a clinical deterioration after hospitalization would result in improved outcomes. Therefore, physicians treating HF patients with history of hypertension in addition to adhering to current guidelines should safeguard the management of comorbidities and the appropriate discharge planning.
CONFLICTS OF INTEREST
There are no conflicts of interest.
AUTHORS CONTRIBUTIONS
WJK and JBK conceived the idea and the design of the study, provided revisions to scientific concept of the manuscript, and had the overall supervision of the project. MG was the principal author and provided revisions to scientific concept of the manuscript. DS performed the statistical analysis and interpretation. JC provided revisions to the statistical impression of the analysis. SD helped to draft the manuscript and provided feedback. All authors have read and approved the final manuscript.
Supporting information
Supplementary Material
Giakoumis M, Sargsyan D, Kostis JB, Cabrera J, Dalwadi S, Kostis WJ; for the Myocardial Infarction Data Acquisition System (MIDAS) Study Group . Readmission and mortality among heart failure patients with history of hypertension in a statewide database. J Clin Hypertens. 2020;22:1263–1274. 10.1111/jch.13918
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