Association of Early Blood Pressure Decrease and Renal Function With Prognosis in Acute Heart Failure

Impact of continuous and wireless monitoring of vital signs on clinical outcomes: a propensity-matched observational study of surgical ward patients

BACKGROUND

Continuous and wireless vital sign monitoring is superior to intermittent monitoring in detecting vital sign abnormalities; however, the impact on clinical outcomes has not been established.

METHODS

We performed a propensity-matched analysis of data describing patients admitted to general surgical wards between January 2018 and December 2019 at a single, tertiary medical centre in the USA. The primary outcome was a composite of in-hospital mortality or ICU transfer during hospitalisation. Secondary outcomes were the odds of individual components of the primary outcome, and heart failure, myocardial infarction, acute kidney injury, and rapid response team activations. Data are presented as odds ratios (ORs) with 95% confidence intervals (CIs) and n (%).

RESULTS

We initially screened a population of 34,636 patients (mean age 58.3 (Range 18-101) yr, 16,456 (47.5%) women. After propensity matching, intermittent monitoring (n=12 345) was associated with increased risk of a composite of mortality or ICU admission (OR 3.42, 95% CI 3.19-3.67; P<0.001), and heart failure (OR 1.48, 95% CI 1.21-1.81; P<0.001), myocardial infarction (OR 3.87, 95% CI 2.71-5.71; P<0.001), and acute kidney injury (OR 1.32, 95% CI 1.09-1.57; P<0.001) compared with continuous wireless monitoring (n=7955). The odds of rapid response team intervention were similar in both groups (OR 0.86, 95% CI 0.79-1.06; P=0.726).

CONCLUSIONS

Patients who received continuous ward monitoring were less likely to die or be admitted to ICU than those who received intermittent monitoring. These findings should be confirmed in prospective randomised 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.

Interaction effects between sleep disorders and depression on heart failure

BACKGROUND

Sleep disorders and depression were recognized as independent risk factors for heart failure, whether their interaction effects also correlated with the risk of heart failure remains elusive. This study was to explore the interaction effects between sleep disorders and depression on the risk of heart failure.

METHODS

This was a cross-sectional study that included data from 39,636 participants in the National Health and Nutritional Examination Survey (NHANES) database. Poisson regression model was applied to evaluate the associations of depression or sleep disorders with heart failure. The relative excess risk of interaction (RERI), attributable proportion of interaction (API) and synergy index (SI) were used to measure whether the interaction effects between depression and sleep disorders on heart failure was statistically significant.

RESULTS

The risk of heart failure was increased in people with sleep disorders [risk ratio (RR) = 1.92, 95% confidence interval (CI): 1.68-2.19) after adjusting for confounders including age, gender, body mass index (BMI), race, marital status, education level, annual family income, drinking history, smoking history, diabetes, hypertension and stroke. The risk of heart failure was elevated in patients with depression after adjusting for confounders (RR = 1.96, 95%CI: 1.65-2.33). Patients with depression and sleep disorders were associated with increased risk of heart failure after adjusting for confounders (RR = 2.76, 95%CI: 2.23-3.42). The CIs of interactive indexes RERI was -0.42 (95%CI: -1.23-0.39), and API was -0.15 (95%CI: -0.46-0.16), which included 0. The CI of interactive indexes SI was 0.81 (95%CI: 0.54-1.21), which contained 1.

CONCLUSION

Depression and sleep disorders were independent risk factors for heart failure but the interaction effects between depression and sleep disorders on the occurrence of heart failure were not statistically different.

Influence of systolic blood pressure trajectory on in-hospital mortality in patients with sepsis

BACKGROUND

Numerous studies have investigated the mean arterial pressure in patients with sepsis, and many meaningful results have been obtained. However, few studies have measured the systolic blood pressure (SBP) multiple times and established trajectory models for patients with sepsis with different SBP trajectories.

METHODS

Data from patients with sepsis were extracted from the Medical Information Mart for Intensive Care-III database for inclusion in a retrospective cohort study. Ten SBP values within 10 h after hospitalization were extracted, and the interval between each SBP value was 1 h. The SBP measured ten times after admission was analyzed using latent growth mixture modeling to construct a trajectory model. The outcome was in-hospital mortality. The survival probability of different trajectory groups was investigated using Kaplan-Meier (K-M) analysis, and the relationship between different SBP trajectories and in-hospital mortality risk was investigated using Cox proportional-hazards regression model.

RESULTS

This study included 3034 patients with sepsis. The median survival time was 67 years (interquartile range: 56-77 years). Seven different SBP trajectories were identified based on model-fit criteria. The in-hospital mortality rates of the patients in trajectory classes 1-7 were 25.5%, 40.5%, 11.8%, 18.3%, 23.5%, 13.8%, and 10.5%, respectively. The K-M analysis indicated that patients in class 2 had the lowest probability of survival. Univariate and multivariate Cox regression analysis indicated that, with class 1 as a reference, patients in class 2 had the highest in-hospital mortality risk (P < 0.001). Subgroup analysis indicated that a nominal interaction occurred between age group and blood pressure trajectory in the in-hospital mortality (P < 0.05).

CONCLUSION

Maintaining a systolic blood pressure of approximately 140 mmHg in patients with sepsis within 10 h of admission was associated with a lower risk of in-hospital mortality. Analyzing data from multiple measurements and identifying different categories of patient populations with sepsis will help identify the risks among these categories.

Early drop in systolic blood pressure is associated with poor diuretic response and prognosis in patients with acute heart failure

AIMS

Although an excessive drop in systolic blood pressure (SBP) during acute heart failure (AHF) negatively impacts prognosis, the association between changes in SBP and the diuretic response (DR) is unclear. We aimed to clarify the association between an early drop in SBP and DR/prognosis in patients with AHF.

METHODS AND RESULTS

This was a sub-analysis of the REALITY-AHF study, which registered patients with AHF admitted through emergency departments (EDs). An early SBP drop was defined as the difference between baseline SBP and the lowest value during the first 48 h of hospitalization. DR was defined as the urine output achieved per 40 mg of intravenous furosemide administered. SBP was measured on admission, at 90 min, and 6, 24, and 48 h after admission. Patients were divided into four groups according to their median SBP drop and DR: greater SBP drop/poor DR (n = 322), smaller SBP drop/poor DR (n = 409), greater SBP drop/good DR (n = 419), and smaller SBP drop/good DR (n = 314). The study included 1,464 patients. A greater SBP drop/poor DR was associated with higher baseline SBP and vasodilator use. Multivariable linear regression analysis showed that a greater drop in SBP was associated with poorer DR following adjustment for potential covariates. Cox proportional hazards analysis demonstrated that a greater SBP drop/poor DR was independently associated with 1-year mortality. Both SBP and DR changes were independently associated with prognosis.

CONCLUSION

An early drop in SBP during the first 48 h of hospitalization was associated with poor DR and 1-year mortality in patients with AHF.

CLINICAL TRIAL REGISTRATION

URL: http://www.umin.ac.jp/ctr/Unique identifier: UMIN000014105.