Systolic Blood Pressure and Outcome in Patients Admitted With Acute Heart Failure: An Analysis of Individual Patient Data From 4 Randomized Clinical Trials

Blood pressure and intensive treatment up-titration after acute heart failure hospitalization: Insights from the STRONG-HF trial

AIMS

A high-intensity care (HIC) strategy with rapid guideline-directed medical therapy (GDMT) up-titration and close follow-up visits improved outcomes, compared to usual care (UC), in patients recently hospitalized for acute heart failure (AHF). Hypotension is a major limitation to GDMT implementation. We aimed to assess the impact of baseline systolic blood pressure (SBP) on the effects of HIC versus UC and the role of early SBP changes in STRONG-HF.

METHODS AND RESULTS

A total of 1075 patients hospitalized for AHF with SBP ≥100 mmHg were included in STRONG-HF. For the purpose of this post-hoc analysis, patients were stratified by tertiles of baseline SBP (<118, 118-128, and ≥129 mmHg) and, in the HIC arm, by tertiles of changes in SBP from the values measured before discharge to those measured at 1 week after discharge (≥2 mmHg increase, ≤7 mmHg decrease to <2 mmHg increase, and ≥8 mmHg decrease). The primary endpoint was 180-day heart failure rehospitalization or death. The effect of HIC versus UC on the primary endpoint was independent of baseline SBP evaluated as tertiles (pinteraction = 0.77) or as a continuous variable (pinteraction = 0.91). In the HIC arm, patients with increased, stable and decreased SBP at 1 week reached 83.5%, 76.2% and 75.3% of target doses of GDMT at day 90. The risk of the primary endpoint was not significantly different between patients with different SBP changes at 1 week (adjusted p = 0.46).

CONCLUSIONS

In STRONG-HF, the benefits of HIC versus UC were independent of baseline SBP. Rapid GDMT up-titration was performed also in patients with an early SBP drop, resulting in similar 180-day outcome as compared to patients with stable or increased SBP.

Association between admission prothrombin time activity and hospital readmission in heart failure: A retrospective study

BACKGROUND

Coagulopathy is a common complication of heart failure (HF), but the prognostic significance of coagulation abnormalities for HF is still poorly understood. This investigation sought to elucidate the association between admission prothrombin time activity (PTA) and short-term readmission in HF.

METHODS

In this retrospective study, we extracted data from a publicly accessible database for hospitalized HF patients in China. The admission laboratory findings were screened by the least absolute shrinkage and selection operator (LASSO) regression. Afterward, the study population was stratified according to the admission PTA level. In univariate and multivariate analysis, we employed logistics regression model to evaluate the association of admission PTA level with short-term readmission. Subgroup analysis was preformed to examine the interaction effect between admission PTA level and covariates, including age, sex, and systolic blood pressure (SBP).

RESULTS

A total of 1505 HF patients were included, of whom 58.7% were female and 35.6% were between 70 and 79 y. In LASSO procedure, admission PTA level was included in optimized models for short-term readmission, and readmitted patients tended to have a lower admission PTA level. Multivariate analysis suggested that the low admission PTA level (admission PTA ≤ 62.3%) was associated with increased risk of 90-day readmission (odds ratio 1.63 [95% CI, 1.09 to 2.46]; P = 0.02) and 180-day readmission (odds ratio 1.65 [95% CI, 1.18 to 2.33]; P = 0.01) compared with patients with the highest admission PTA level (admission PTA ≥ 76.8%) after full adjustment. Moreover, no significant interaction effect was observed in the subgroup analysis, except for admission SBP.

CONCLUSION

Low admission PTA level is associated with an increased risk of 90-day and 180-day hospital readmission in patients with HF.

Construction of a web-based dynamic nomogram for predicting the prognosis in acute heart failure

AIMS

The early identification and appropriate management may provide clinically meaningful and substained benefits in patients with acute heart failure (AHF). This study aimed to develop an integrative nomogram with myocardial perfusion imaging (MPI) for predicting the risk of all-cause mortality in AHF patients.

METHODS AND RESULTS

Prospective study of 147 patients with AHF who received gated MPI (59.0 [47.5, 68.0] years; 78.2% males) were enrolled and followed for the primary endpoint of all-cause mortality. We analysed the demographic information, laboratory tests, electrocardiogram, and transthoracic echocardiogram by the least absolute shrinkage and selection operator (LASSO) regression for selection of key features. A multivariate stepwise Cox analysis was performed to identify independent risk factors and construct a nomogram. The predictive values of the constructed model were compared by Kaplan-Meier curve, area under the curves (AUCs), calibration plots, continuous net reclassification improvement, integrated discrimination improvement, and decision curve analysis. The 1, 3, and 5 year cumulative rates of death were 10%, 22%, and 29%, respectively. Diastolic blood pressure [hazard ratio (HR) 0.96, 95% confidence interval (CI) 0.93-0.99; P = 0.017], valvular heart disease (HR 3.05, 95% CI 1.36-6.83; P = 0.007), cardiac resynchronization therapy (HR 0.37, 95% CI 0.17-0.82; P = 0.014), N-terminal pro-B-type natriuretic peptide (per 100 pg/mL; HR 1.02, 95% CI 1.01-1.03; P < 0.001), and rest scar burden (HR 1.03, 95% CI 1.01-1.06; P = 0.008) were independent risk factors for patients with AHF. The cross-validated AUCs (95% CI) of nomogram constructed by diastolic blood pressure, valvular heart disease, cardiac resynchronization therapy, N-terminal pro-B-type natriuretic peptide, and rest scar burden were 0.88 (0.73-1.00), 0.83 (0.70-0.97), and 0.79 (0.62-0.95) at 1, 3, and 5 years, respectively. Continuous net reclassification improvement and integrated discrimination improvement were also observed, and the decision curve analysis identified the greater net benefit of the nomogram across a wide range of threshold probabilities (0-100% at 1 and 3 years; 0-61% and 62-100% at 5 years) compared with dismissing the included factors or using either factor alone.

CONCLUSIONS

A predictive nomogram for the risk of all-cause mortality in patients with AHF was developed and validated in this study. The nomogram incorporated the rest scar burden by MPI is highly predictive, and may help to better stratify clinical risk and guide treatment decisions in patients with AHF.

Effect of different blood pressure levels on short-term outcomes in hospitalized heart failure patients

Background

To investigate the influence of blood pressure (BP) level on short-term prognosis of heart failure (HF), the effect of the BP level on clinical end point events 3 months after discharge was observed.

Methods

A retrospective cohort study was performed on 1492 hospitalized HF patients. All patients were divided according to systolic blood pressure (SBP) per 20 mmHg and diastolic blood pressure (DBP) per 10 mmHg. Logistic regression analysis was used to analyze the relationship between BP level and heart failure rehospitalization, cardiac death, all-cause death and a composite end point of heart failure rehospitalization/all-cause death at 3 month follow-up after discharge.

Results

After multivariable adjustment, the relationship between SBP and DBP levels and outcomes followed an inverted J curve relationship. Compared with the reference group (110 < SBP≤130 mmHg), the risk of all end point events significantly increased in the SBP≤90 mmHg group included heart failure rehospitalization (OR 8.16, 95%CI 2.88-23.11, P < 0.001), cardiac death (OR 5.43, 95%CI 1.97-14.96, P = 0.001), all-cause death (OR 4.85, 95%CI 1.76-13.36, P = 0.002), and composite end point (OR 2.76, 95%CI 1.03-7.41, P = 0.044). SBP>150 mmHg significantly increased the risk of heart failure rehospitalization (OR 2.67, 95%CI 1.15-6.18, P = 0.022). Compared with.the reference group (65 < DBP≤75 mmHg), cardiac death (OR 2.64, 95%CI 1.15-6.05, P = 0.022) and all-cause death (OR 2.67, 95%CI 1.20-5.93, P = 0.016) was significantly increased in DBP≤55 mmHg group. There was no significant difference among subgroups according to left ventricular ejection fraction (P > 0.05).

Conclusions

There is a significant difference in the short-term prognosis 3 months after discharge in HF patients with different BP levels at discharge. There was an inverted J curve relationship between BP levels and prognosis.

Association of 48-h net fluid status with change in renal function and dyspnea among patients with decompensated heart failure: A pooled cohort analysis of three acute heart failure trials

BACKGROUND

Acute heart failure (AHF) exacerbations are a leading cause of hospitalization in the United States. Despite the frequency of AHF hospitalizations, there are inadequate data or practice guidelines on how quickly diuresis should be achieved.

OBJECTIVE

To study the association of 48-h net fluid change and (A) 72-h change in creatinine and (B) 72-h change in dyspnea among patients with acute heart failure.

DESIGNS, SETTINGS, AND PARTICIPANTS

This is a retrospective, pooled cohort analysis of patients from the DOSE, ROSE, and ATHENA-HF trials.

INTERVENTIONS

The primary exposure was 48-h net fluid status.

MAIN OUTCOMES AND MEASURES

The co-primary outcomes were 72-h change in creatinine and 72-h change in dyspnea. The secondary outcome was risk of 60-day mortality or rehospitalization.

RESULTS

Eight hundred and seven patients were included. The mean 48-h net fluid status was -2.9 L. A nonlinear association was observed with net fluid status and creatinine change, such that creatinine improved with each liter net negative up to 3.5 L (-0.03 mg/dL per liter negative [95% confidence interval [CI]: -0.06 to -0.01) and remained stable beyond 3.5 L (-0.01 [95% CI: -0.02 to 0.001], p = .17). Net fluid loss was associated with a monotonic improvement of dyspnea (1.4-point improvement per liter negative [95% CI: 0.7-2.2], p = .0002). Each liter net negative by 48 h was also associated with 12% decreased odds of 60-day rehospitalization or death (odds ratio: 0.88; 95% CI: 0.82-0.95; p = .002).

CONCLUSION

Aggressive net fluid targets within the first 48 h are associated with effective relief of patient self-reported dyspnea and improved long-term outcomes without adversely affecting renal function.

Machine learning approach identified clusters for patients with low cardiac output syndrome and outcomes after cardiac surgery

Background

Low cardiac output syndrome (LCOS) is the most serious physiological abnormality with high mortality for patients after cardiac surgery. This study aimed to explore the multidimensional data of clinical features and outcomes to provide individualized care for patients with LCOS.

Methods

The electronic medical information of the intensive care units (ICUs) was extracted from a tertiary hospital in South China. We included patients who were diagnosed with LCOS in the ICU database. We used the consensus clustering approach based on patient characteristics, laboratory data, and vital signs to identify LCOS subgroups. The consensus clustering method involves subsampling from a set of items, such as microarrays, and determines to cluster of specified cluster counts (k). The primary clinical outcome was in-hospital mortality and was compared between the clusters.

Results

A total of 1,205 patients were included and divided into three clusters. Cluster 1 (n = 443) was defined as the low-risk group [in-hospital mortality =10.1%, odds ratio (OR) = 1]. Cluster 2 (n = 396) was defined as the medium-risk group [in-hospital mortality =25.0%, OR = 2.96 (95% CI = 1.97–4.46)]. Cluster 3 (n = 366) was defined as the high-risk group [in-hospital mortality =39.2%, OR = 5.75 (95% CI = 3.9–8.5)].

Conclusion

Patients with LCOS after cardiac surgery could be divided into three clusters and had different outcomes.

Blood Pressure Drops During Hospitalization for Acute Heart Failure Treated With Serelaxin: A Patient-Level Analysis of 4 Randomized Controlled Trials

BACKGROUND

Hypotensive events and drops in systolic blood pressure (SBP-drop) are frequent in patients hospitalized with acute heart failure. We investigated whether SBP-drops are associated with outcomes in patients treated with serelaxin.

METHODS

Patient-level retrospective analyses of 4 prospective trials investigating serelaxin in acute heart failure. Main inclusion criteria were SBP 125 to 180 mm Hg, pulmonary congestion, and elevated NT-proBNP (N-terminal pro-B-type natriuretic peptide). SBP-drops were prospectively defined as SBP<100 mm Hg, or, if SBP remained >100 mm Hg, a drop from baseline of 40 mm Hg from baseline. Outcomes were a short-term composite outcome (worsening heart failure, hospital readmission for heart failure or all-cause mortality through 14 days) and 180-day mortality.

RESULTS

Overall, 2559/11 226 (23%) patients had an SBP-drop. SBP-drop, versus no SBP-drop, was associated with a worse outcome: cumulative incidence of 180-day mortality (11% versus 9%, hazard ratio [HR]. 1.21 [95% CI, 1.05-1.39]; P=0.009) and the short-term outcome (11% versus 9%, HR, 1.29 [95% CI, 1.13-1.49]; P<0.001). Of the 2 SBP-drop components, an SBP<100 mm Hg was associated with the worst outcome compared with a 40 mm Hg drop: short-term outcome (11% versus 10%) and HRs of 1.32 (95% CI, 1.13-1.55; P=0.0005) and 1.22 (95% CI, 0.97-1.56; P=0.09), for each component respectively, with a P value for interaction of 0.05. SBP-drops were associated with a worse short-term outcome in the placebo group (HR, 1.46 [95% CI, 1.19-1.79]; P=0.0003), but not in the serelaxin-group (HR, 1.18 [95% CI, 0.97-1.42]; P=0.10); P interaction=0.003.

CONCLUSIONS

SBP-drops in patients with acute heart failure and normal to high SBP at admission is associated with worse short- and long-term outcomes especially for SBP <100 mm Hg. However, in patients treated with the intravenous vasodilator serelaxin, SBP-drops seemed less harmful.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifiers: NCT02064868, NCT02007720, NCT01870778, NCT00520806.