# Safety Indicators in Patients Receiving High-intensity Care After Hospital Admission for Acute Heart Failure: The STRONG-HF Trial

Daniela Tomasoni, Beth Davison, Marianna Adamo, Matteo Pagnesi, Alexandre Mebazaa, Christopher Edwards, Mattia Arrigo, Marianela Barros, Jan Biegus, Jelena Čelutkienė, et al.

► To cite this version:

Daniela Tomasoni, Beth Davison, Marianna Adamo, Matteo Pagnesi, Alexandre Mebazaa, et al. Safety Indicators in Patients Receiving High-intensity Care After Hospital Admission for Acute Heart Failure: The STRONG-HF Trial. Journal of Cardiac Failure, 2024, 30 (4), pp.525-537. 10.1016/j.cardfail.2023.09.002. inserm-05464530

HAL Id: inserm-05464530

https://inserm.hal.science/inserm-05464530v1

Submitted on 19 Jan 2026

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
<figure><img src="image_2.png" /></figure>

# Safety Indicators in Patients Receiving High-intensity Care After Hospital Admission for Acute Heart Failure: The STRONG-HF Trial

DANIELA TOMASONI, MD¹,* BETH DAVISON, PhD²,³,⁴,* MARIANNA ADAMO, MD¹

MATTEO PAGNESI, MD¹ ALEXANDRE MEBAZAA, MD, PhD²,⁵ CHRISTOPHER EDWARDS, BSc³

MATTIA ARRIGO, MD⁶ MARIANELA BARROS, MD³ JAN BIEGUS, MD, PhD⁷

JELENA ČELUTKIENĖ, MD, PhD⁸ KAMILĖ ČERLINSKAITĖ-BAJORĖ, MD⁸ OVIDIU CHIONCEL, MD, PhD⁹

ALAIN COHEN-SOLAL, MD, PhD²,¹⁰ ALBERTINO DAMASCENO, MD, PhD¹¹ RAFAEL DIAZ, MD¹²

GERASIMOS FILIPPATOS, MD¹³ ETIENNE GAYAT, MD, PhD²,⁵ ANTOINE KIMMOUN, MD, PhD¹⁴

CAROLYN S.P. LAM, MD, PhD¹⁵,¹⁶ MARIA NOVOSADOVA, MD³ PETER S. PANG, MD¹⁷

PIOTR PONIKOWSKI, MD, PhD⁷ HADIZA SAIDU, MBBS¹⁸ KAREN SLIWA, MD, PhD¹⁹ KOJI TAKAGI, MD³

JOZINE M. TER MAATEN, MD, PhD¹⁶ ADRIAAN VOORS, MD, PhD¹⁶ GAD COTTER, MD²,³,⁴ and MARCO METRA, MD¹

Brescia, Italy; Paris, France; Durham, North Carolina; Zurich, Switzerland; Wrocław, Poland; Vilnius, Lithuania; Bucharest, Romania; Maputo, Mozambique; Rosario, Argentina; Athens, Greece; Vandúuvre-lès-Nancy, France; Groningen, the Netherlands; Indianapolis, Indiana; Kano, Nigeria; and Cape Town, South Africa

## ABSTRACT

**Background:** Safety, Tolerability and Efficacy of Rapid Optimization, Helped by NT-proBNP Testing, of Heart Failure Therapies (STRONG-HF) demonstrated the safety and efficacy of rapid up-titration of guideline-directed medical therapy (GDMT) with high-intensity care (HIC) compared with usual care in patients hospitalized for acute heart failure (HF). In the HIC group, the following safety indicators were used to guide up-titration: estimated glomerular filtration rate of <30 mL/min/1.73 m², serum potassium of >5.0 mmol/L, systolic blood pressure (SBP) of <95 mmHg, heart rate of <55 bpm, and N-terminal pro-B-type natriuretic peptide concentration of >10% higher than predischarge values.

**Methods and Results:** We examined the impact of protocol-specified safety indicators on achieved dose of GDMT and clinical outcomes. Three hundred thirteen of the 542 patients in the HIC arm (57.7%) met ≥1 safety indicator at

From the ¹Depaetment of Cardiology, ASST Spedali Civili and Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy; ²Université Paris Cité, INSERM UMR-S 942(MASCOT), Paris, France; ³Momentum Research Inc, Durham, North Carolina; ⁴Heart Initiative, Durham, North Carolina; ⁵Department of Anesthesiology and Critical Care and Burn Unit, Saint-Louis and Lariboisière Hospitals, FHU PROMICE, DMU Parabol, APHP.Nord, Paris, France; ⁶Department of Internal Medicine, Stadtspital Zurich, Zurich, Switzerland; ⁷Institute of Heart Diseases, Wrocław Medical University, Wrocław, Poland; ⁸Clinic of Cardiac and Vascular Diseases, Institute of Clinical Medicine, Faculty of Medicine, Vilnius University, Vilnius, Lithuania; ⁹Emergency Institute for Cardiovascular Diseases "Prof. C.C. Iliescu", University of Medicine "Carol Davila", Bucharest, Romania; ¹⁰AP-HP Nord, Department of Cardiology, Lariboisière University Hospital, Paris, France; ¹¹Faculty of Medicine, Eduardo Mondlane University, Maputo, Mozambique; ¹²Estudios Clínicos Latinoamérica, Instituto Cardiovascular de Rosario, Rosario, Argentina; ¹³National and Kapodistrian University of Athens, School of Medicine, Attikon University Hospital, Athens, Greece; ¹⁴Université de Lorraine, Nancy; INSERM, Défaillance Circulatoire Aigue et Chronique; Service de Médecine Intensive et Réanimation Brabois,

CHRU de Nancy, Vandúuvre-lès-Nancy, France; ¹⁵National Heart Centre Singapore and Duke-National University of Singapore; ¹⁶Department of Cardiology, University of Groningen, University Medical Centre Groningen, Groningen, the Netherlands; ¹⁷Department of Emergency Medicine, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana; ¹⁸Murtala Muhammed Specialist Hospital, Bayero University Kano, Kano, Nigeria and ¹⁹Cape Heart Institute, Department of Medicine and Cardiology, Groote Schuur Hospital, University of Cape Town, Cape Town, South Africa.

Manuscript received July 25, 2023; revised manuscript received September 19, 2023; revised manuscript accepted September 19, 2023.

Reprint requests: Marco Metra, MD, Cardiology, ASST Spedali Civili di Brescia, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, University of Brescia, Brescia, Italy. Tel: +393356460581. E-mail: metramarco@libero.it

*D.T. and B.D. contributed equally to this paper.

1071-9164/$ - see front matter

© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

https://doi.org/10.1016/j.cardfail.2023.09.002
any follow-up visit 1–6 weeks after discharge. As compared with those without, patients meeting ≥1 safety indicator had more severe HF symptoms, lower SBP, and higher heart rate at baseline and achieved a lower average percentage of GDMT optimal doses (mean difference vs the HIC arm patients not reaching any safety indicator, –11.0% [95% confidence interval [CI] –13.6 to –8.4%], *P* < .001). The primary end point of 180-day all-cause death or HF readmission occurred in 15.0% of patients with any safety indicator vs 14.2% of those without (adjusted hazard ratio 0.84, 95% CI 0.48–1.46, *P* = .540). None of each of the safety indicators, considered alone, was significantly associated with the primary end point, but an SBP of <95 mm Hg was associated with a trend toward increased 180-day all-cause mortality (adjusted hazard ratio 2.68, 95% CI 0.94–7.64, *P* = .065) and estimated glomerular filtration rate decreased to <30 mL/min/1.73 m² with more HF readmissions (adjusted hazard ratio 3.60, 95% CI 1.22–10.60, *P* = .0203). The occurrence of a safety indicator was associated with a smaller 90-day improvement in the EURO-QoL 5-Dimension visual analog scale (adjusted mean difference –3.32 points, 95% CI –5.97 to –0.66, *P* = .015).

**Conclusions:** Among patients with acute HF enrolled in STRONG-HF in the HIC arm, the occurrence of any safety indicator was associated with the administration of slightly lower GDMT doses and less improvement in quality of life, but with no significant increase in the primary outcome of 180-day HF readmission or death when appropriately addressed according to the study protocol. (J Cardiac Fail 2024;30:525–537)

**Keywords:** Safety indicators, guideline-directed medical therapy, acute heart failure, hypotension, hyperkalemia, STRONG-HF.

© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

Acute heart failure (HF) is associated with a high risk of postdischarge readmissions and death.¹⁻⁵ Despite the higher risk of postdischarge events, hospitalization for HF offers the opportunity to initiate or up-titrate guideline-directed medical therapy (GDMT).⁶⁻¹² Indeed, although GDMT improves outcome and quality of life of patients with HF, it remains largely underused.¹³⁻¹⁵ Patient factors (eg, older age, comorbidities, intolerance or contraindications, instability during hospitalization) and physician factors (eg, clinical inertia) have been suggested as potential reasons for suboptimal dosing of HF therapies during hospitalization.¹⁶⁻²³

The Safety, Tolerability and Efficacy of Rapid Optimization, Helped by NT-proBNP Testing, of Heart Failure Therapies (STRONG-HF) trial demonstrated that a high-intensity care (HIC) strategy of rapid GDMT up-titration and close follow-up can decrease the risk of 180-day HF readmission or all-cause death in patients recently hospitalized for acute HF, compared with usual care (UC).²⁴,²⁵ Patients assigned to HIC were followed according to a set of prespecified specific safety indicators, which guided changes in treatment at each follow-up visit.²⁴,¹⁶

We analyzed in this study the incidence and the impact of the safety indicators on treatment and outcome of the patients assigned to the HIC arm.

## Methods

### Study Design

The design and main results of the STRONG-HF trial have been previously reported.²⁴⁻²⁶ Briefly, this multicenter, open-label, randomized trial compared a HIC strategy with early up-titration of renin angiotensin system (RAS)

inhibitors (angiotensin-converting enzyme [ACE] inhibitors, or angiotensin receptor blockers [ARBs] in patients intolerant to ACE inhibitors, or angiotensin receptor-neprilysin inhibitors [ARNIs]), β-blockers, and mineralocorticoid receptor antagonists [MRAs], vs UC, among 1078 patients admitted to hospital for acute HF and not treated with full doses of GDMT. Included patients were hemodynamically stable, had any left ventricular ejection fraction (LVEF) and high N-terminal pro-B-type natriuretic peptide (NT-proBNP) values at screening (>2500 pg/mL). Screening (visit 1) was performed within 72 hours after admission. One to 2 days before discharge, patients underwent further assessment (visit 2, before randomization). At that time, all inclusion and exclusion criteria should have been met and, in addition, to ensure that the patient was still at high risk, NT-proBNP had to be >1500 pg/mL, but with a decrease of >10% compared with screening. To ensure safety of up-titration of GDMT, all measures of systolic blood pressure (SBP), heart rate, and serum potassium within 24 h should have been ≥100 mm Hg, ≥60 bpm, and ≤5.0 mEq/L (mmol/L), respectively. Baseline parameters corresponded to those measured at randomization (visit 2).

In the HIC arm, β-blockers, ACE inhibitors/ARBs/ARNi, and MRA were rapidly up-titrated to 50% of optimal doses before discharge and to 100% of optimal doses within 2 weeks after discharge. At each of the following visits, GDMT up-titration was encouraged in the patients not on maximally tolerated doses of ACE inhibitors/ARBs/ARNi or β-blockers and without any safety criteria (as discussed elsewhere in this article). Patients were assessed by the study team at 1, 2, 3, and 6 weeks after discharge and an additional safety visit was done 1 week after any up-titration to assess safety and tolerability.²⁴ Clinical
examination and laboratory assessments including NT-proBNP, sodium and potassium plasma concentrations, and kidney function, were repeated at each visit. Patients in the UC group were followed according to local practice until a study visit performed, conducted for patients in both groups, at day 90 after randomization (visit 7).

All randomized patients were contacted at day 180 to assess the occurrence of rehospitalizations and death (visit 8). The study's primary end point was the composite of all-cause death or first HF rehospitalization at day 180. Other end points included 180-day all-cause death, 180-day HF readmission, and change in the EURO-QoL 5-Dimension (EQ-5D) visual analogue scale (VAS) score from baseline to day 90.²⁷

The study was approved by appropriate competent authorities and all sites obtained approval from ethics committees. All patients provided written informed consent. The study is registered at ClinicalTrials.gov, NCT03412201.

## Protocol Guidance According to Safety Indicators

According to study protocol, patients assigned to HIC were prescribed GDMT at ≥50% optimal doses within 2 days before anticipated hospital discharge with up-titration to full optimal doses at 2 weeks after randomization and/or in the following visits when up-titration was not completed and no safety indicator was met. GDMT up-titration was delayed according to the following prespecified safety indicators:

- No up-titration of ACE inhibitors/ARBs/ARNi and/or MRAs if SBP was <95 mm Hg and/or serum potassium was >5.0 mmol/L and/or estimated glomerular filtration rate (eGFR) was <30 mL/min/1.73 m²;

- No up-titration of β-blockers if heart rate was <55 bpm and/or SBP was <95 mm Hg; and

- Consideration of no up-titration of β-blockers and increase in diuretic dose if NT-proBNP concentrations were >10% higher than the predischarge level.²⁴

In addition, investigators were asked to increase the diuretic dose as needed if clinical signs of congestion were present and to decrease the diuretics dose if eGFR was <30 mL/min/1.73 m² without signs of congestion.

## Stratifications and Definitions

As per protocol, safety indicators were the following: eGFR of <30 mL/min/1.73 m², serum potassium of >5.0 mmol/L, SBP of <95 mm Hg, heart rate of <55 bpm, and NT-proBNP level >10% higher than the predischarge level. Because patients in the UC group were not evaluated by the study team between randomization and day 90, only patients randomized to the HIC strategy were included in the present analysis and were stratified into 2 groups based on the occurrence of any of the safety

indicators at any follow-up visit at weeks 1, 2, 3, or 6. Baseline characteristics are presented stratified by these 2 groups. Clinical outcomes as well as the average percentage of achieved GDMT doses were compared between each separate safety indicator. Although not prespecified as a safety indicator, we also explored the impact of worsening renal function (WRF), defined as a decrease in the eGFR of ≥15% from baseline.

The current analysis was not prespecified in the study protocol.

## Statistical Analysis

Continuous variables are presented as mean ± standard deviation, adjusted mean and associated standard error, or as geometric mean and 95% confidence interval (CI) for log-transformed variables; categorical variables are presented as number and percentage. Comparisons of baseline characteristics among groups were performed by analysis of variance for continuous variables, using log-transformed values for skewed continuous variables, $\chi^2$ test for categorical variables, and Cochran–Mantel–Haenszel nonzero correlation for ordinal categorical variables. Comparisons of binary variables with observed cell counts of <5 were made using Monte Carlo estimation of exact $\chi^2$ P values.

Primary and other end points through 180 days were restricted to patients enrolled at sites where the ethics committee approved the amended protocol allowing follow-up of patients through day 180, and in the cohort of patients enrolled before the primary end point was changed from 90 to 180 days, the results were down-weighted proportional to one-half its sample size. Cox proportional hazards regression models were used to evaluate the impact of safety indicators on the study end points.²⁸,²⁹ Each safety indicator, or the occurrence of any indicator, was considered as a time-dependent covariate in a separate model. The covariate took the value "no" until the visit at which the safety indicator occurred, after which the covariate took the value "yes." Baseline covariates for adjustment were selected using backward selection in the UC group from factors shown to be prognostic of the outcomes in previous studies; $P < .10$ across 10 multiple imputation datasets was the criterion for staying. Covariates finally selected for the primary end point were diastolic blood pressure, baseline NT-proBNP, ischaemic aetiology, and oedema. Results are described as hazard ratio (HR) and 95% CI.

Groups were compared with respect to the change in EQ-VAS using ANCOVA adjusted for baseline value and randomization stratification factors (LVEF of ≤40% vs LVEF of >40% and geographic region) and using observed values. Patients from Mozambique, where no linguistically validated EQ-5D was available, were excluded from the analyses. Adjusted results impute missing covariate values with results averaged across 10 multiple imputation datasets.
The dose of medication in each of the 3 medication classes (RAS inhibitors, β-blockers, and MRAs) relative to the optimal doses (see Supplemental Table 3 in the primary publication²⁴) was computed for each patient; the average of these percentages was also computed. The trajectory of the percentage optimal dose over time is presented for each medication class and for the average across the 3 medication classes by groups of patients with or without safety indicators. Differences in the percentage optimal doses between the safety indicator groups were compared using mixed models for repeated measures.

Two-sided P values of <.05 were considered statistically significant. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC).

## Results

### Incidence and Distribution of Safety Indicators

Among the 542 patients randomized to the HIC arm, 313 (57.7%) met ≥1 safety indicator at any visit, 3–6 (Fig. 1). Specifically, 28 patients (5.2%) had an eGFR of <30 mL/min/1.73 m², 51 (9.4%) had an SBP of <95 mm Hg, 46 (8.5%) had a heart rate of <55 bpm, and 149 (27.5%) had a serum potassium of >5.0 mmol/L. An increase in NT-proBNP concentration of >10% at any postdischarge follow-up visit, compared with randomization values, was observed in 223 patients (41.1%).

Table 1 shows the concomitant occurrence of multiple safety indicators in the same patients. A large proportion of patients with an eGFR of <30 mL/min/1.73 m² at any visit also had a serum potassium of >5.0 mmol/L or an increase in NT-proBNP of >10% from predischarge values (42.9% and 57.1%, respectively) at any visit. Among patients with an SBP of <95 mm Hg, 17 patients (33.3%) also had an increase in NT-proBNP of >10% at any visit.

### Decline in eGFR of ≥15%

Although not a predefined safety indicator, 181 patients (33.4%) experienced WRF with a decrease in the eGFR of ≥15% from baseline (Table 1). Approximately 90% of

patients who reached an eGFR of <30 mL/min/1.73 m² also had a decline in eGFR of ≥15% from baseline. More than one-third of patients with an SBP of <95 mm Hg as well as of those with an increase in NT-proBNP of >10% had a decrease in the eGFR of ≥15%. Patients who had an eGFR decrease of ≥15% where less up-titrated on GDMT.³⁰

### Baseline Characteristics by Safety Indicators

Baseline characteristics of patients who met ≥1 safety indicator at any visit 3–6 are shown in Table 2. The mean age, distribution of sex, race/ethnicity, and geography were similar between those with and without a safety indicator. Patients who met any safety indicator were less likely to have a history of HF but more frequently presented with acute coronary syndrome, displayed more severe HF symptoms, higher New York Heart Association functional class 1 month before hospital admission and had a lower SBP and a higher heart rate at baseline, as compared with those without safety indicators. NT-proBNP levels were similar between the 2 groups at screening, but lower at prerandomization assessment among those meeting safety indicators. Additionally, patients with safety indicators had higher hemoglobin and lower cholesterol levels. There were no differences in mean LVEF. Oral HF medications at visit 2 (before randomization) were equally administered.

<figure><img src="image_3.png" /><figcaption>Fig. 1. Distribution of safety indicators in the high-intensity care group. eGFR, estimated glomerular filtration rate; HR, heart rate; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SBP, systolic blood pressure.</figcaption></figure>

<table><caption>Table 1 Cross-tabulation of Safety Indicators at Any Visit 3–6 Week 1 through Week 6 in the High-intensity Care Group</caption><thead><tr><th></th><th>eGFR<br>&lt;30 mL/min/1.73 m²</th><th>SBP &lt;<br>95mm Hg</th><th>Heart Rate<br>&lt;55 bpm</th><th>K⁺ &gt;<br>5.0 mmol/L</th><th>NT-proBNP &gt;10%<br>Predischarge Value</th><th>eGFR<br>Decrease of<br>≥15%*</th></tr></thead><tbody><tr><td>eGFR &lt; 30 mL/min/1.73 m² (n = 28)</td><td>—</td><td>2 (7)</td><td>5 (18)</td><td>12 (43)</td><td>16 (57)</td><td>25 (29)</td></tr><tr><td>SBP &lt;95 mm Hg (n = 51)</td><td>2 (4)</td><td>—</td><td>6 (12)</td><td>10 (20)</td><td>17 (33)</td><td>18 (35)</td></tr><tr><td>Heart rate &lt;55 bpm (n = 46)</td><td>5 (11)</td><td>6 (13)</td><td>—</td><td>11 (24)</td><td>12 (26)</td><td>9 (20)</td></tr><tr><td>K⁺ &gt;5.0 mmol/L (n = 149)</td><td>12 (8)</td><td>10 (7)</td><td>11 (7)</td><td>—</td><td>72 (48)</td><td>48 (32)</td></tr><tr><td>NT-proBNP &gt;10% from before<br>discharge (n = 223)</td><td>16 (7)</td><td>17 (8)</td><td>12 (5)</td><td>72 (32)</td><td>—</td><td>87 (37)</td></tr><tr><td>Any safety indicator (n = 313)</td><td>28 (9)</td><td>51 (16)</td><td>46 (15)</td><td>149 (48)</td><td>223 (71)</td><td>181 (58)</td></tr><tr><td>eGFR decrease ≥15% (n = 181)</td><td>25 (14)</td><td>18 (10)</td><td>9 (5)</td><td>48 (27)</td><td>87 (48)</td><td>—</td></tr></tbody></table>

eGFR, estimated glomerular filtration rate; NT-proBNP, N-terminal pro-B-type natriuretic peptide; SBP, systolic blood pressure. Values are number (%).

*We explored the incidence of a decrease in eGFR of ≥15% from baseline, but it was not included among safety indicators (as per protocol).
<table><caption>**Table 2** Baseline Characteristics by Any Safety Indicator Met at Any Visit 3–6 Week 1 to Week 6 in the High Intensity Care Group</caption><thead><tr><th>Parameter</th><th>No (n=229)</th><th>Yes (n=313)</th><th>P Value</th></tr></thead><tbody><tr><td>Age, years</td><td>62.60 ± 13.78</td><td>63.20 ± 13.22</td><td>.6234</td></tr><tr><td>Sex</td><td></td><td></td><td></td></tr><tr><td>Female</td><td>92 (40.2)</td><td>124 (39.6)</td><td>.8957</td></tr><tr><td>Male</td><td>137 (59.8)</td><td>189 (60.4)</td><td></td></tr><tr><td>Self-reported race</td><td></td><td></td><td></td></tr><tr><td>Black</td><td>55 (24.0)</td><td>60 (19.2)</td><td>.2588</td></tr><tr><td>Caucasian</td><td>173 (75.5)</td><td>245 (78.3)</td><td></td></tr><tr><td>Native American</td><td>0</td><td>1 (0.3)</td><td></td></tr><tr><td>Other</td><td>1 (0.4)</td><td>6 (1.9)</td><td></td></tr><tr><td>Pacific Islander</td><td>0</td><td>1 (0.3)</td><td></td></tr><tr><td>Geographical region</td><td></td><td></td><td></td></tr><tr><td>Europe</td><td>164 (71.6)</td><td>234 (74.8)</td><td>.4129</td></tr><tr><td>Non-Europe</td><td>65 (28.4)</td><td>79 (25.2)</td><td></td></tr><tr><td>History of atrial fibrillation or atrial flutter or present at screening</td><td>92 (40.2)</td><td>137 (43.8)</td><td>.4026</td></tr><tr><td>Medical history</td><td></td><td></td><td></td></tr><tr><td>Stroke or transient ischemic attack</td><td>20 (8.7)</td><td>36 (11.5)</td><td>.2900</td></tr><tr><td>Severe liver disease</td><td>1 (0.5)</td><td>2 (0.8)</td><td>.9999</td></tr><tr><td>Psychiatric or neurological disorder</td><td>3 (1.3)</td><td>5 (1.6)</td><td>.9999</td></tr><tr><td>Malignancies</td><td>5 (2.2)</td><td>13 (4.2)</td><td>.2038</td></tr><tr><td>Diabetes</td><td>63 (27.6)</td><td>89 (28.4)</td><td>.8374</td></tr><tr><td>Diabetes control method</td><td></td><td></td><td></td></tr><tr><td>Insulin</td><td>20 (8.8)</td><td>30 (9.6)</td><td>.7472</td></tr><tr><td>Diet</td><td>37 (16.2)</td><td>65 (20.8)</td><td>.1826</td></tr><tr><td>Oral antidiabetic agents</td><td>46 (20.2)</td><td>64 (20.4)</td><td>.9382</td></tr><tr><td>Pulmonary embolism</td><td>4 (1.7)</td><td>9 (2.9)</td><td>.5751</td></tr><tr><td>Acute coronary syndrome</td><td>57 (24.9)</td><td>109 (34.8)</td><td>.0132</td></tr><tr><td>Coronary artery bypass surgery</td><td>9 (3.9)</td><td>18 (5.8)</td><td>.3359</td></tr><tr><td>Percutaneous transluminal coronary intervention</td><td>32 (14.0)</td><td>48 (15.3)</td><td>.6589</td></tr><tr><td>Angina Canadian Cardiovascular Society class 2 or higher</td><td>28 (12.2)</td><td>46 (14.7)</td><td>.4000</td></tr><tr><td>Moderate or severe chronic obstructive pulmonary disease or asthma</td><td>5 (2.2)</td><td>9 (2.9)</td><td>.6159</td></tr><tr><td>Cardiac resynchronization therapy</td><td>1 (0.4)</td><td>2 (0.6)</td><td>.9999</td></tr><tr><td>Automatic internal cardiac defibrillator</td><td>2 (0.9)</td><td>1 (0.3)</td><td>.5692</td></tr><tr><td>Heart failure history</td><td></td><td></td><td></td></tr><tr><td>History of heart failure</td><td>205 (89.5)</td><td>260 (83.1)</td><td>.0335</td></tr><tr><td>NYHA functional class 1 month before hospital admission</td><td></td><td></td><td></td></tr><tr><td>1</td><td>11 (5.0)</td><td>18 (6.2)</td><td>.0117</td></tr><tr><td>2</td><td>67 (30.7)</td><td>80 (27.6)</td><td></td></tr><tr><td>3</td><td>113 (51.8)</td><td>103 (35.5)</td><td></td></tr><tr><td>4</td><td>27 (12.4)</td><td>89 (30.7)</td><td></td></tr><tr><td>Ischemic etiology</td><td>104 (45.6)</td><td>156 (49.8)</td><td>.3313</td></tr><tr><td>LVEF, %</td><td>36.90 ± 12.78</td><td>36.50 ± 12.42</td><td>.6986</td></tr><tr><td>LVEF category</td><td></td><td></td><td></td></tr><tr><td>LVEF ≤40%</td><td>157 (68.6)</td><td>208 (66.5)</td><td>.6057</td></tr><tr><td>LVEF >40%</td><td>72 (31.4)</td><td>105 (33.5)</td><td></td></tr><tr><td>Hospitalized for heart failure in the past year</td><td>64 (27.9)</td><td>76 (24.3)</td><td>.3354</td></tr><tr><td>No. of heart failure hospitalizations in the past year</td><td>0.40 ± 0.69</td><td>0.30 ± 0.68</td><td>.4603</td></tr><tr><td>History of atrial fibrillation or atrial flutter</td><td>96 (41.9)</td><td>142 (45.4)</td><td>.4246</td></tr><tr><td>Type of atrial fibrillation or atrial flutter</td><td></td><td></td><td></td></tr><tr><td>Paroxysmal</td><td>26 (28.3)</td><td>31 (21.8)</td><td>.1873</td></tr><tr><td>Permanent</td><td>53 (57.6)</td><td>84 (59.2)</td><td></td></tr><tr><td>Persistent</td><td>13 (14.1)</td><td>27 (19.0)</td><td></td></tr><tr><td>Baseline vital signs</td><td></td><td></td><td></td></tr><tr><td>Systolic blood pressure at baseline, mm Hg</td><td>125.2 ± 14.17</td><td>122.1 ± 12.49</td><td>.0078</td></tr><tr><td>Pulse, beats/min</td><td>77.1 ± 11.16</td><td>79.5 ± 12.12</td><td>.0170</td></tr><tr><td>Respiratory rate, breaths/min</td><td>18.0 ± 2.58</td><td>18.0 ± 2.32</td><td>.9984</td></tr><tr><td>Local Laboratory</td><td></td><td></td><td></td></tr><tr><td>Hemoglobin, g/L</td><td>134.10 ± 18.52</td><td>137.9 ± 21.40</td><td>.0318</td></tr><tr><td>Lymphocytes, %</td><td>26.50 ± 10.59</td><td>27.70 ± 9.42</td><td>.1661</td></tr><tr><td>White blood cells, 10<sup>9</sup>/L</td><td>6.90 ± 1.96</td><td>6.90 ± 1.95</td><td>.6741</td></tr><tr><td>Glucose, mmol/L</td><td>6.10 ± 2.34</td><td>6.30 ± 2.56</td><td>.5166</td></tr><tr><td>Creatinine, µmol/L</td><td>105.40 ± 23.67</td><td>107.10 ± 33.76</td><td>.5163</td></tr><tr><td>Potassium, mmol/L</td><td>4.20 ± 0.43</td><td>4.30 ± 0.47</td><td>.0010</td></tr></tbody></table>

(Continued)
<table><caption>**Table 2. (Continued)**</caption><thead><tr><th>Parameter</th><th>No (n =229)</th><th>Yes (n =313)</th><th>P Value</th></tr></thead><tbody><tr><td>Sodium, mmol/L</td><td>140.00 ± 3.77</td><td>140.30 ± 4.22</td><td>.4321</td></tr><tr><td>Urea, mmol/L</td><td>7.80 ± 2.91</td><td>8.30 ± 4.01</td><td>.1185</td></tr><tr><td>ALT, U/L</td><td>32.90 ± 67.31</td><td>29.40 ± 29.52</td><td>.4286</td></tr><tr><td>Total bilirubin, µmol/L</td><td>17.30 ± 13.52</td><td>17.80 ± 10.83</td><td>.6721</td></tr><tr><td>Total cholesterol, mmol/L</td><td>4.40 ± 1.10</td><td>4.10 ± 1.07</td><td>.0024</td></tr><tr><td>NT-proBNP at screening, ng/L</td><td>6309.3 (5846.7–6808.4)</td><td>6015.8 (5643.5–6412.6)</td><td>.3443</td></tr><tr><td>NT-proBNP, ng/L</td><td>3653.6 (3360.3–3972.6)</td><td>2996.6 (2795.8–3211.8)</td><td>.0003</td></tr><tr><td>Oral heart failure medications taken at visit 2 (before randomization)</td><td></td><td></td><td></td></tr><tr><td>ACE inhibitors/ARBs/ARN inhibitors</td><td>148 (65.2)</td><td>206 (65.8)</td><td>.8817</td></tr><tr><td>β-Blockers</td><td>77 (33.9)</td><td>106 (33.9)</td><td>.9894</td></tr><tr><td>Mineralocorticoid receptor antagonists</td><td>217 (95.6)</td><td>291 (93.0)</td><td>.2025</td></tr><tr><td>Loop diuretic</td><td>219 (96.5)</td><td>301 (96.2)</td><td>.8508</td></tr></tbody></table>

Values reported are mean ± standard deviation or geometric mean (95% confidence interval) for continuous variables and number (%) for categorical variables. A patient may be classified under >1 diabetes control method.

ACE, angiotensin-converting enzyme; ALT, alanine aminotransferase; ARBs, angiotensin receptor blockers, ARNI angiotensin receptor neprilysin; LVEF, left ventricular ejection fraction; NT-proBNP, N-terminal pro-B-type natriuretic peptide; NYHA, New York Heart Association.

## Changes in HF Medication Doses According to Safety Indicators

Changes in medication doses in response to each safety indicator at each visit are reported in Fig. 2. Appropriate changes in GDMT were observed at each visit when safety indicators were met (Supplemental Table 1). The occurrence of an SBP of <95 mm Hg was significantly associated with a decrease in RAS inhibitor, MRA, or β-blocker doses at visits 3, 5, and 6 and with a lower probability of up-titration at visit 4 (when doses were to be up-titrated to 100% optimal doses). Both an eGFR of <30 mL/min/1.73 m² and a serum potassium of >5.0 mmol/L were associated with higher rates of decrease or no changes in RAS inhibitor and MRA doses at visits 3, 5, and 6 and with a lower rate of up-titration at visit 4. At each visit, patients with an increase in NT-proBNP of >10% greater than pre-discharge received higher doses of diuretics.

Fig. 3A shows the trajectory of the average percentage of GDMT optimal dose during follow-up in patients who did or did not meet any safety indicator at visits 3–6. Patients with any safety indicator, compared with those without, achieved a lower percentage of GDMT optimal doses (mean difference −11.0%, 95% CI −13.6% to −8.4%, *P* < .001). This difference was already evident at visit 4 occurring at week 2, when 100% of recommended doses should have been reached per protocol, with achieved average GDMT doses of 74.8% vs 89.0% in patients with vs without any safety indicator. The difference between the 2 groups was then more pronounced at visit 6 (73.2% vs 90.4%) and was maintained for the entire follow-up (until visit 8, day 180) (71.5% vs 84.5%) (Fig. 3A). Doses of each of the 3 classes of GDMT (RAS inhibitors, β-blockers, and MRAs) were significantly lower in patients with any safety indicator (Figs. 3B–3D).

The trajectories of the average percentage of GDMT optimal doses over time stratified by each safety indicator separately are reported in Supplemental Figs. 1.1–1.5. Patients with an eGFR of <30 mL/min/1.73 m² vs those

without, received lower doses of RAS inhibitors and MRA (Supplemental Fig. 1.1). An SBP of <95 mm Hg was associated with the greatest difference in GDMT doses (mean difference −18.5%, 95% CI −22.9% to −14.1%, *P* < .001 as compared with patients without an SBP of <95 mm Hg). The average percentage of GDMT optimal doses were significantly different also among patients with vs without heart rate of <55 bpm, serum potassium of >5.0 mmol/L, and an increase in NT-proBNP of >10% (all *P* < .001) (Supplemental Figs. 1.3–1.5).

## Clinical Outcomes by Safety Indicators

The primary end point of 180-day HF readmission or all-cause death occurred in 43 patients (15.0%) with any safety indicator vs 31 patients (14.2%) without (time-dependent covariate adjusted HR 0.84, 95% CI 0.48–1.46, *P* = .54). All-cause mortality through 180 days occurred in 16 patients (5.6%) with and 23 (10.5%) without any safety indicator and was also not significantly different (adjusted HR 0.66 95% CI 0.32–1.39, *P* = .28). HF readmission occurred in 36 patients (12.5%) with and 11 (5.0%) without a safety indicator and was also not significantly different (adjusted HR 1.63 95% CI 0.77–3.47, *P* = .20) (Table 3).

With respect to the impact of each safety indicator, considered alone, on outcomes, no single safety indicator was significantly associated with the primary end point or rates of 180-day mortality. An SBP of <95 mm Hg was associated with a trend toward increased mortality (adjusted HR 2.68, 95% CI 0.94–7.64, *P* = .065). An eGFR of <30 mL/min/1.73 m² was associated with an increased risk of 180-day HF readmission (adjusted HR 3.60, 95% CI 1.22–10.60, *P* = .020) (Table 3).

Although patients with and without a safety indicator had a mean increase in EQ-5D VAS scores from randomization to day 90, smaller improvements were observed in patients with vs without safety indicators (adjusted mean
ACEi, ARB, or ARNI

<figure><img src="image_4.png" /></figure>

β-blocker

<figure><img src="image_5.png" /></figure>

Mineralocorticoid receptor antagonists

<figure><img src="image_6.png" /></figure>

Loop diuretics

<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /><figcaption>Fig. 2. Stacked bar chart of medication changes by visit and whether safety indicator criteria met. ACEi/ARBs/ARNI, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers/angiotensin receptor-neprilysin inhibitor; other abbreviations as in Fig. 1.</figcaption></figure>

difference –3.32 points, 95% CI –5.97 to –0.66, *P* = .015)
*(Table 4).*

Discussion

The key findings of this secondary analysis from STRONG-HF are the following: (1) more than one-half of the patients randomized to HIC met ≥1 safety indicator at any follow-up visit, between 1 and 6 weeks after discharge; (2)

patients meeting any safety indicator had more severe HF
at baseline; (3) as per protocol, the average percentage of
GDMT optimal doses was 11% lower in patients with ≥1
safety indicator compared with those without, but higher
than in the UC arm; (4) the occurrence of any safety indica-
tor, when addressed by GDMT dose adjustment, was not
associated with a greater risk of the combined primary
end point of 180-day HF readmission or death despite the
more severe HF at baseline, even if the lack of statistical
power could not be excluded as a possible cause of such
<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /><figcaption>Fig. 3. Mean percentage of optimal dose of GDMT in patients with and without any safety indicator.
GDMT, guideline directed medical therapy; MRAs, mineralocorticoid receptor antagonists; other abbreviation as in Fig. 2.</figcaption></figure>

results (Graphical Abstract); and (5) despite the lack of an impact on the composite primary outcome, the occurrence of an eGFR of <30 mL/min/m² and an SBP of <95 mm Hg were associated with an increased risk of 180-days HF rehospitalizations (P = .02) and with a tendency to an increased mortality (P = .065), respectively.

Incidence of Safety Indicators and Characteristics of Patients Meeting Safety Indicators

STRONG-HF is the first study that assessed the feasibility of rapid and simultaneous up-titration of GDMT after an episode of acute HF, through frequent follow-up visits with both clinical and laboratory assessments. Frequent patient reassessment with protocol-driven changes in GDMT based on safety indicators likely contributed to the success of this treatment strategy. Thus, although more than one-half of the patients met ≥1 safety indicator at any follow-up visit, their prognosis at 180 days was similar

to that of the patients who did not meet such indicators and, overall, patients receiving HIC had better outcomes than those on UC.²⁵

Among safety indicators, an increase in NT-proBNP values of >10% and serum potassium levels of >5 mmol/L were the most frequent, whereas an SBP of <95 mm Hg, heart rate of <55 bpm, and eGFR of <30 mL/min/1.73 m² were met in <10% of patients. These findings may seem to be in contrast with data showing that hypotension, bradycardia, and kidney dysfunction are the major causes of GDMT under-prescription and under-dosing.¹³⁻¹⁵,¹⁸,²³ These differences may be ascribed to differences in the patients enrolled in previous registries, compared with those in STRONG-HF, as shown by the older age, lower SBP, LVEF, and eGFR, consistent with more advanced HF, of the patients in these registries, compared with the patients enrolled in the present trial. Second, our data also show the persistent role of clinical inertia as a major
<table><caption>**Table 3** Clinical Outcomes by Safety Indicators as Time-dependent Covariates</caption><thead><tr><th></th><th>Any Indicator</th><th>eGFR &lt;30 mL/min/ 1.73 m<sup>2</sup></th><th>SBP &lt;95 mm Hg</th><th>Heart Rate &lt;55 bpm</th><th>K<sup>+</sup> &gt;5.0 mmol/L</th><th>NT-proBNP &gt;10% Increase</th></tr></thead><tbody><tr><td colspan="7"><strong>180-Day HF readmission or death</strong></td></tr><tr><td>Unadjusted HR (95% CI), P value</td><td>0.97 (0.57–1.66), .9164</td><td>2.62 (1.00–6.86), .0508</td><td>1.13 (0.43–2.97), .8028</td><td>0.19 (0.03–1.39), .1024</td><td>0.97 (0.53–1.79), .9220</td><td>0.97 (0.56–1.67), .9047</td></tr><tr><td>Adjusted HR<sup>a</sup> (95% CI), P value</td><td>0.84 (0.48–1.46), .5396</td><td>2.06 (0.77–5.53), .1504</td><td>1.38 (0.51–3.71), .5262</td><td>0.19 (0.03–1.41), .1052</td><td>0.90 (0.49–1.66), .7322</td><td>0.83 (0.46–1.48), .5238</td></tr><tr><td colspan="7"><strong>180-Day all-cause death</strong></td></tr><tr><td>Unadjusted HR (95% CI), P value</td><td>0.57 (0.28–1.19), .1371</td><td>2.37 (0.65–8.68), .1913</td><td>2.21 (0.81–6.05), .1226</td><td>0.17 (0.01–2.91), .2211<sup>d</sup></td><td>0.59 (0.23–1.50), .2676</td><td>0.51 (0.22–1.16), .1066</td></tr><tr><td>Adjusted HR<sup>c</sup> (95% CI), P value</td><td>0.66 (0.32–1.39), .2796</td><td>1.60 (0.36–7.13), .5380</td><td>2.68 (0.94–7.64), .0653</td><td>0.21 (0.01–3.51), .2796<sup>b</sup></td><td>0.60 (0.23–1.55), .2899</td><td>0.65 (0.28–1.51), .3170</td></tr><tr><td colspan="7"><strong>180-Day HF readmission</strong></td></tr><tr><td>Unadjusted HR (95% CI), P value</td><td>1.80 (0.87–3.73), .1111</td><td>3.91 (1.38–11.1), .0105</td><td>0.58 (0.11–3.01), .5202</td><td>0.31 (0.04–2.29), .2525</td><td>1.46 (0.71–2.98), .3034</td><td>1.44 (0.73–2.82), .2893</td></tr><tr><td>Adjusted HR<sup>a</sup> (95% CI), P value</td><td>1.63 (0.77–3.47), .2005</td><td>3.60 (1.22–10.60), .0203</td><td>0.59 (0.11–3.13), .5370</td><td>0.36 (0.05–2.67), .3181</td><td>1.42 (0.69–2.91), .3377</td><td>1.35 (0.65–2.78), .4230</td></tr></tbody></table>

CI, confidence interval; HF, heart failure; HR, hazard ratio; other abbreviations as in Table 1.

HRs are relative to not having the indicator.

aAdjusted for baseline diastolic blood pressure, baseline NT-proBNP, ischemic etiology, and edema.

bFifth correction applied due to no events occurring in patients meeting the criterion causing infinite maximum likelihood estimates

cAdjusted for baseline creatinine, baseline hemoglobin, baseline urea, and baseline NT-proBNP.

dAdjusted for body mass index, baseline diastolic blood pressure, baseline cholesterol, baseline potassium, baseline NT-proBNP, baseline left ventricular ejection fraction, and edema.

cause of patients' under-treatment and the impact that a HIC program may have.¹⁴,¹⁵,¹⁷,²⁰,³¹,³²

Patients who met any safety indicator had worse HF symptoms (eg, New York Heart Association functional class), lower SBP, and higher heart rate, consistent with more severe hemodynamic impairment and HF. These patients were less likely to tolerate GDMT also in previous studies.¹⁹,³³⁻³⁶ Our results, therefore, confirm the role of HF severity as a major cause of suboptimal GDMT dosing also in patients treated with a HIC regimen. The average dose of GDMT, relative to the optimal dose, was of 71.5% in the patients who met the safety indicators, only 11% lower than in the patients who did not meet safety indicators in the HIC arm, and much larger than the 44% target dose of the UC group. Consistently, overall outcome of the patients receiving HIC was

better than in UC and safety indicators were not associated with increased mortality or HF readmissions rate.

## Prognostic Impact of Single Safety Indicators

The analysis of the prognostic impact of the single safety indicators showed that neither of them was associated with an increased rate of the combined primary end point, consistent with the efficacy of the HIC program. However, the rate of HF rehospitalizations was approximately 3-fold higher in the patients who had developed an eGFR of <30 mL/min/1.73 m² and all-cause mortality tended to be higher in patients who had developed hypotension, defined as an SBP of <95 mm Hg. Although given the large number of statistical tests performed these results could have been the play of chance,³⁷ these results are

<table><caption>**Table 4** Change in EQ-VAS from Baseline to Day 90 by Any Safety Indicator Met at Any Visit 3–6: Week 1 to Week 6 High-intensity Care Subjects Only</caption><thead><tr><th rowspan="2">EQ-VAS</th><th colspan="2">Any Safety Indicator Met</th><th rowspan="2">LS Mean Difference (95% CI)</th><th rowspan="2">P Value</th></tr><tr><th>Yes</th><th>No</th></tr></thead><tbody><tr><td>Baseline, mean (SD)</td><td>60.4 (15.83)</td><td>57.1 (13.84)</td><td></td><td></td></tr><tr><td>Day 90, mean (SD)</td><td>68.7 (15.60)</td><td>71.0 (13.45)</td><td></td><td></td></tr><tr><td colspan="5">Change from baseline to day 90</td></tr><tr><td>Partially adjusted LS mean (SE)<sup>a</sup></td><td>9.94 (1.20)</td><td>12.99 (1.24)</td><td>-3.05 (-5.60, to -0.50)</td><td>.0191</td></tr><tr><td>Fully adjusted LS mean (SE)<sup>b</sup></td><td>9.99 (1.25)</td><td>12.88 (1.27)</td><td>-2.89 (-5.55 to -0.23)</td><td>.0332</td></tr></tbody></table>

aAdjusted for baseline EQ-VAS, region, and LVEF group (≤40/>40).

bAdditionally adjusted for baseline hemoglobin, baseline creatinine, baseline cholesterol, baseline NT-proBNP, hospitalized for heart failure in prior year, edema, and New York Heart Association functional classification.EQ, EuroQoL; SD, standard deviation; LS, least squares; SE, standard error; VAS, Visual analogue scale; other abbreviation as in Table 2.
consistent with the prognostic role of these events in the patients with HF.⁶,¹⁶,³³,³⁵,³⁸ The negative impact on outcome of kidney dysfunction and hypotension is likely mediated by their untoward effects as well as by the withdrawal and/or down-titration of GDMT that often follows their occurrence in clinical practice.⁶,¹³,¹⁴,¹⁶,³³,³⁵,³⁸,³⁹,³⁴ Both these untoward consequences were likely mitigated by the HIC regimen used in STRONG-HF. However, the lack of collection of data regarding safety indicators in the UC arm precludes any conclusion regarding the efficacy of HIC on the impact of safety indicators.

Observation of a heart rate of <55 bpm in the STRONG-HF trial led to less up-titration of β-blockers. However, it could also be considered as a surrogate parameter for the achievement of adequate β-blockade, with a potential protective role.⁴⁰ Consistently, achievement of a low heart rate was not associated with poorer outcome although it hindered titration of β-blockers.

Hyperkaliemia was a frequent cause of discontinuation of GDMT, namely MRA, as repeatedly shown in the literature.¹³,¹⁸,²¹,⁴¹,⁴² However, the strategy of frequent follow-up visits used in HIC arm allowed a slower titration with the administration of lower doses, although with maintenance of MRA treatment in most of the patients with no untoward relation between these safety indicators and the risk of death or HF readmissions. Administration of new potassium lowering agent may also be considered in these patients¹,⁴³,⁴⁴ although these medications were not available in most of the cases at the time of the trial.

An increase in NT-proBNP levels of >10% than predischarge values was highly prevalent. This result is expected in the immediate postdischarge "vulnerable phase," a particularly high-risk period for clinical events, namely, worsening hemodynamics and worsening HF.¹¹ Few studies investigated the trajectories of NT-proBNP after discharge. In a post hoc analysis of the Aliskiren Trial in Acute Heart Failure Outcomes (ASTRONAUT), among patients hospitalized for worsening chronic HF, increasing NT-proBNP from baseline to the 1-month follow-up was independently predictive of increased cardiovascular mortality or HF hospitalizations.⁴⁵ Data in patients hospitalized for HF also show the negative prognostic role of an increase in NT-proBNP plasma concentrations during hospitalization.⁴⁶ When appropriately addressed as per protocol, namely, with the adjustment of diuretic dose, the increase in NT-proBNP concentrations was not associated with worse outcomes. This finding is also consistent with the beneficial effects of GDMT that was slowly but progressively titrated, even in the patients with an early NT-proBNP increase.⁴⁷

An increase in serum creatinine, traditionally defined as WRF occurred in one-third of patients in the HIC group and it was frequently associated with an increase in NT-proBNP levels. WRF may, however, occur as a transient result of better decongestion and/or initiation of RAS inhibitors and be not associated with poorer outcomes.³⁸,⁴⁸⁻⁵⁰

WRF, defined as a decrease in the eGFR of ≥15% from baseline, was not included among safety indicators and did not require GDMT doses adjustment in STRONG-HF. Despite a large body of evidence suggesting the transient nature of WRF, even up to a 30% increase in eGFR, and particular benefit of RAS inhibitors in patients with lower eGFR,⁴⁸⁻⁵⁰ many investigators chose to not up-titrate patients who had small drops in eGFR during rapid up-titration.³⁰ This issue should be emphasized when implementing the results of STRONG-HF in the postacute HF care.

Overall, these data provide important reassurance to physicians who may be reluctant to prescribe and up-titrate medications likely to cause hypotension, bradycardia, hyperkaliemia or WRF, even if they are known to be beneficial. ACE inhibitors/ARBs/ARNi and/or MRAs up-titration should be delayed when the SBP is <95 mm Hg and/or serum potassium is >5.0 mmol/L and/or eGFR is <30 mL/min/1.73 m². No up-titration of β-blockers is advised if heart rate is <55 bpm and/or SBP is <95 mm Hg. Furthermore, no up-titration of β-blockers and increase in diuretic dose should be considered if NT-proBNP concentrations are >10% higher than the predischarge level. Finally, the adjustment of diuretic doses based on the evaluation of congestion and renal function is advised.¹²,²⁴

## Limitations

There are several inherent limitations to this analysis, in addition to those already mentioned in the main STRONG-HF study. Given that we performed subgroup analyses, statistical power is limited because the study was not specifically powered for these analyses. As stated elsewhere in this article, safety indicators were assessed only in the HIC group. Thus, our data do not allow the evaluation of either the impact of HIC on the occurrence of safety indicators or the role of HIC to decrease their impact on outcomes. However, our analysis highlights the overall efficacy of HIC in the patients enrolled in STRONG-HF. By censoring deaths in the analysis of HF readmission, we assume that the deaths are "noninformative," that is, that these patients would have had the same risk of a HF readmission if they had not died as those patients that we observed. Given the multiple statistical tests performed without control of the overall error rate, caution should be exercised when interpreting statistically significant associations. Finally, we were only able to describe associations, and causality cannot be proven.

## Conclusions

Among patients with acute HF enrolled in the STRONG-HF trial and randomized to the HIC strategy, more than one-half presented safety indicators during follow-up. The occurrence of any safety indicator was associated with the
achievement of slightly lower percentage of GDMT optimal doses over time though with a similar effect on 180-day HF readmission or death. Hypotension and poor kidney function were the only safety indicators associated with a trend toward worse outcomes. The occurrence of safety indicators was associated with smaller benefits in quality of life.

## Lay Summary

More than one-half of the patients randomized to high-intensity care (HIC) arm in the Safety, Tolerability and Efficiency of Rapid Optimization, Helped by NT-proBNP Testing, of Heart Failure Therapies (STRONG-HF) trial met ≥1 safety indicator; thus, their frequent assessment during the rapid up-titration of guideline-directed medical therapy (GDMT) is strongly recommended.

Patients meeting any safety indicator had more severe HF at baseline and, as per protocol, reached a slightly lower average percentage of GDMT optimal doses, but did not experience an increase in the risk of the primary end point, compared with those without safety indicators in the HIC arm.

Rapid and simultaneous up-titration of GDMT is safe and feasible, provided that safety indicators are frequently assessed and guide the up-titration itself.

<figure><img src="image_13.png" /></figure>

## Declaration of Competing Interest

None

## Disclosures

D.T. has received speaker fees from Boehringer Ingelheim Alnylam Pharmaceuticals and from Pfizer. B.D. is an employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. B.D. is the director of the Heart Initiative, a nonprofit organization. M.A.d. has received speaker fees from Abbott Vascular and Medtronic. M.P. has received personal fees from Abbott Laboratories, AstraZeneca, Boehringer Ingelheim, and Vifor Pharma.

A.M. has received grants from Roche Diagnostics, Abbott Laboratories, 4TEEN4, and Windtree Therapeutics; honoraria for lectures from Roche Diagnostics, Bayer, and MSD; is a consultant for Corteria Pharmaceuticals, S-form Pharma, FIRE-1, Implicity, 4TEEN4, and Adrenomed; and is coinventor of a patent on combination therapy for patients having acute or persistent dyspnea. C.E. is an employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. M.B. is an employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. J.C. has received personal fees from Novartis, AstraZeneca, Boehringer Ingelheim, Roche Diagnostics, and Pfizer. O.C. received grants from Servier. A.C.-S. has received honoraria for lectures or consultancy from AstraZeneca, Novartis, Vifor, Bayer, Merck, Sanofi, Abbott, and Boehringer Ingelheim. AD works for the Faculty of Medicine, Eduardo Mondlane University (Maputo, Mozambique), which received research grants from the Heart Initiative for their participation in this study. R.D. has received supporting fees for coordination of STRONG-HF trial activities. G.F. has received lecture fees or was a committee member for trials and registries sponsored by Bayer, Vifor, Boehringer Ingelheim, Medtronic, Servier, and Amgen.

C.S.P.L. is supported by a Clinician Scientist Award from the National Medical Research Council of Singapore; has received research support from Bayer and Roche Diagnostics; has served as consultant or on the advisory board, steering committee, or executive committee for Actelion, Alleviant Medical, Allysta Pharma, Amgen, AnaCardio AB, Applied Therapeutics, AstraZeneca, Bayer, Boehringer Ingelheim, Boston Scientific, Cytokinetics, Darma Inc., EchoNous Inc, Eli Lilly, Impulse Dynamics, Intellia Therapeutics, Ionis Pharmaceutical, Janssen Research & Development LLC, Medscape/WebMD Global LLC, Merck, Novartis, Novo Nordisk, Prosciento Inc, Radcliffe Group Ltd., Redcardio Inc, ReCor Medical, Roche Diagnostics, Sanofi, Siemens Healthcare Diagnostics, and Us2.ai; and serves as co-founder and nonexecutive director of Us2.ai. M.N. is an employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics.

P.S.P. has received grants or research contracts from American Heart Association, Roche, Siemens, Ortho Diagnostics, Abbott, Beckman Coulter, and Siemens; consulting fees from Roche; honoraria from WebMD; and he has financial interest in The Heart Course. K.S. has received grants from Medtronic, Servier, and Amylam and honoraria from MSD, Novartis, and Sanofi. K.T. is an employee
of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. A.A.V. has received consultancy fees or research support from AstraZeneca, Bayer, BMS, Boehringer Ingelheim, Cytokinetics, Myocardia, Merck, Novartis, Novo Nordisk, and Roche Diagnostics. G.C. is an employee of Momentum Research, which has received grants for research from Abbott Laboratories, Amgen, Celyad, Cirius Therapeutics, Corteria Pharmaceuticals, Heart Initiative, Sanofi, Windtree Therapeutics, and XyloCor Therapeutics. GC is director of Heart Initiative, a nonprofit organization. M.M. has received personal fees from Actelion, Amgen, Livanova, and Vifor Pharma as a member of executive or data monitoring committees of sponsored clinical trials and from AstraZeneca, Bayer, Boehringer Ingelheim, Edwards Lifesciences, and Roche Diagnostics for participation to advisory boards or for speaking at sponsored meetings.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.card fail.2023.09.002.

## References

1. Authors/Task Force Members McDonagh TA, Metra M, Adamo M, Gardner RS, Baum-bach A, et al. 2021 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: developed by the Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). With the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 2022;24:4–131.

2. Kimmoun A, Takagi K, Gall E, Ishihara S, Hammoum P, El Beze N, et al. Temporal trends in mortality and readmission after acute heart failure: a systematic review and meta-regression in the past four decades. Eur J Heart Fail 2021;23:420–31.

3. Agarwal MA, Fonarow GC, Ziaeian B. National trends in heart failure hospitalizations and readmissions from 2010 to 2017. JAMA Cardiol 2021;6:952–6.

4. Hariharaputhiran S, Peng Y, Ngo L, Ali A, Hossain S, Visvanathan R, et al. Long-term survival and life expectancy following an acute heart failure hospitalization in Australia and New Zealand. Eur J Heart Fail 2022;24:1519–28.

5. Tomasoni D, Lombardi CM, Sbolli M, Cotter G, Metra M. Acute heart failure: more questions than answers. Prog Cardiovasc Dis 2020;63:599–606.

6. Greene SJ, Fonarow GC, Vaduganathan M, Khan SS, Butler J, Gheorghiade M. The vulnerable phase after hospitalization for heart failure. Nat Rev Cardiol 2015;12:220–9.

7. Arrigo M, Nijst P, Rudiger A. Optimising heart failure therapies in the acute setting. Card Fail Rev 2018;4:38–42.

8. Butler J, Yang M, Sawhney B, Chakladar S, Yang L, Djatche LM. Treatment patterns and clinical outcomes among patients <65 years with a worsening heart failure event. Eur J Heart Fail 2021;23:1334–42.

9. Rao VN, Murray E, Butler J, Cooper LB, Cox ZL, Fiuzat M, et al. In-hospital initiation of sodium-glucose cotransporter-2 inhibitors for heart failure with reduced ejection fraction. J Am Coll Cardiol 2021;78:2004–12.

10. Tomasoni D, Fonarow GC, Adamo M, Anker SD, Butler J, Coats AJS, et al. Sodium-glucose co-transporter 2 inhibitors as an early, first-line therapy in patients with heart failure and reduced ejection fraction. Eur J Heart Fail 2022;24:431–41.

11. Metra M, Tomasoni D, Adamo M, Bayes-Genis A, Filippatos G, Abdelhamid M, et al. Worsening of chronic heart failure: definition, epidemiology, management and prevention. A clinical consensus statement by the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2023;25:776–91.

12. Metra M, Adamo M, Tomasoni D, Mebazaa A, Bayes-Genis A, Abdelhamid M, et al. Pre-discharge and early post-discharge management of patients hospitalized for acute heart failure: a scientific statement by the Heart Failure Association of the ESC. Eur J Heart Fail 2023;25:1115–31.

13. Greene SJ, Butler J, Albert NM, DeVore AD, Sharma PP, Duffy CI, et al. Medical therapy for heart failure with reduced ejection fraction: the CHAMP-HF registry. J Am Coll Cardiol 2018;72:351–66.

14. Greene SJ, Fonarow GC, DeVore AD, Sharma PP, Vaduganathan M, Albert NM, et al. Titration of medical therapy for heart failure with reduced ejection fraction. J Am Coll Cardiol 2019;73:2365–83.

15. Greene SJ, Ezekowitz JA, Anstrom KJ, Demyanenko V, Givertz MM, Pina IL, et al. Medical therapy during hospitalization for heart failure with reduced ejection fraction: the VICTORIA registry. J Card Fail 2022;28:1063–77.

16. Chioncel O, Benson L, Crespo-Leiro MG, Anker SD, Coats AJS, Filippatos G, et al. Comprehensive characterization of non-cardiac comorbidities in acute heart failure: an analysis of ESC-HFA EORP heart failure long-term registry. Eur J Prev Cardiol 2023;30:1346–58.

17. Janse RJ, Fu EL, Dahlstrom U, Benson L, Lindholm B, van Diepen M, et al. Use of guideline-recommended medical therapy in patients with heart failure and chronic kidney disease: from physician's prescriptions to patient's dispensations, medication adherence and persistence. Eur J Heart Fail 2022;24:2185–95.

18. Maggioni AP, Anker SD, Dahlstrom U, Filippatos G, Ponikowski P, Zannad F, et al. Are hospitalized or ambulatory patients with heart failure treated in accordance with European Society of Cardiology guidelines? Evidence from 12,440 patients of the ESC Heart Failure Long-Term Registry. Eur J Heart Fail 2013;15:1173–84.

19. Musella F, Rosano GMC, Hage C, Benson L, Guidetti F, Moura B, et al. Patient profiles in heart failure with reduced ejection fraction: prevalence, characteristics, treatments and outcomes in a real-world heart failure population. Eur J Heart Fail 2023;25:1246–53.

20. Savarese G, Bodegard J, Norhammar A, Sartipy P, Thuresson M, Cowie MR, et al. Heart failure drug titration, discontinuation, mortality and heart failure hospitalization risk: a multinational observational study (US, UK and Sweden). Eur J Heart Fail 2021;23:1499–511.

21. Savarese G, Carrero JJ, Pitt B, Anker SD, Rosano GMC, Dahlstrom U, et al. Factors associated with underuse of mineralocorticoid receptor antagonists in heart failure with reduced ejection fraction: an analysis of 11 215 patients from the Swedish Heart Failure Registry. Eur J Heart Fail 2018;20:1326–34.

22. Stolfo D, Lund LH, Becher PM, Orsini N, Thorvoldsen T, Benson L, et al. Use of evidence-based therapy in heart failure with reduced ejection fraction across age strata. Eur J Heart Fail 2022;24:1047–62.

23. Greene SJ, Butler J, Hellkamp AS, Spertus JA, Vaduganathan M, Devore AD, et al. Comparative effectiveness of dosing of medical therapy for heart failure: from the CHAMP-HF registry. J Card Fail 2022;28:370–84.

24. Kimmoun A, Cotter G, Davison B, Takagi K, Addad F, Celutkiene J, et al. Safety, Tolerability and efficacy of Rapid Optimization, helped by NT-proBNP and GDF-15, of Heart Failure therapies (STRONG-HF): rationale and design for a multicentre, randomized, parallel-group study. Eur J Heart Fail 2019;21:1459–67.

25. Mebazaa A, Davison B, Chioncel O, Cohen-Solal A, Diaz R, Filippatos G, et al. Safety, tolerability and efficacy of up-titration of guideline-directed medical therapies for acute heart failure (STRONG-HF): a multinational, open-label, randomised, trial. Lancet 2022;400:1938–52.

26. Cotter G, Davison B, Metra M, Sliwa K, Voors AA, Addad F, et al. Amended STRONG-HF study design. Eur J Heart Fail 2021;23:1981–2.

27. Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol Group. Ann Med 2001;33:337–43.

28. Rossello X, Gonzalez-Del-Hoyo M. Survival analyses in cardiovascular research, part I: the essentials. Rev Esp Cardiol (Engl Ed) 2022;75:67–76.

29. Rossello X, Gonzalez-Del-Hoyo M. Survival analyses in cardiovascular research, part II: statistical methods in challenging situations. Rev Esp Cardiol (Engl Ed) 2022;75:77–85.

30. Ter Maaten JM MA, Davison BA, Chioncel O, Cohen Solal A, Filippatos G, Ponikowski P, et al. Early changes in renal function changes during rapid up-titration of guideline directed medical therapy following an admission for acute heart failure. Presented at the ESC Heart Failure Congress, Prague, Czech Republic, May 20–23 2023.

31. Savarese G, Kishi T, Vardeny O, Adamsson Eryd S, Bodegard J, Lund LH, et al. Heart Failure drug treatment-inertia, titration, and discontinuation: a multinational observational study (EVOLUTION HF). JACC Heart Fail 2023;11:1–14.

32. Bozkurt B. Reasons for lack of improvement in treatment with evidence-based therapies in heart failure. J Am Coll Cardiol 2019;73:2384–7.

33. Crespo-Leiro MG, Metra M, Lund LH, Milicic D, Costanzo MR, Filippatos G, et al. Advanced heart failure: a position statement of the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2018;20:1505–35.

34. Metra M, Pagnesi M, Claggett BL, Diaz R, Felker GM, McMurray JVJ, et al. Effects of omecamtiv mecarbil in heart failure with reduced ejection fraction according to blood pressure: the GALACTIC-HF trial. Eur J Heart Fail 2022;43:5006–16.

35. Vader JM, Givertz MM, Starling RC, McNulty SE, Anstrom KJ, Desvigne-Nickens P, et al. Tolerability of sacubitril/valsartan in patients with advanced heart failure: analysis of the LIFE trial run-in. JACC Heart Fail 2022;10:449–56.

36. Rosano GMC, Moura B, Metra M, Bohm M, Bauersachs J, Ben Gal T, et al. Patient profiling in heart failure for tailoring medical therapy. A consensus document of the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2021;23:872–81.

37. Pocock SJ, Rossello X, Owen R, Collier TJ, Stone GW, Rockhold FW. Primary and secondary outcome reporting in randomized trials: JACC state-of-the-art review. J Am Coll Cardiol 2021;78:827–39.

38. Emmens JE, Ter Maaten JM, Matsue Y, Figarska SM, Sama IE, Cotter G, et al. Worsening renal function in acute heart failure in the context of diuretic response. Eur J Heart Fail 2022;24:365–74.

39. Kittleson M, Hurwitz S, Shah MR, Nohria A, Lewis E, Givertz M, et al. Development of circulatory-renal limitations to angiotensin-converting enzyme inhibitors identifies patients with severe heart failure and early mortality. J Am Coll Cardiol 2003;41:2029–35.
40. Metra M, Torp-Pedersen C, Swedberg K, Cleland JG, Di Lenarda A, Komajda M, et al. Influence of heart rate, blood pressure, and beta-blocker dose on outcome and the differences in outcome between carvedilol and metoprolol tartrate in patients with chronic heart failure: results from the COMET trial. Eur Heart J 2005;26:2259–68.

41. Trevisan M, Fu EL, Xu Y, Savarese G, Dekker FW, Lund LH, et al. Stopping mineralocorticoid receptor antagonists after hyperkalaemia: trial emulation in data from routine care. Eur J Heart Fail 2021;23:1698–707.

42. Rossignol P, Lainscak M, Crespo-Leiro MG, Laroche C, Piepoli MF, Filippatos G, et al. Unravelling the interplay between hyperkalaemia, renin-angiotensin-aldosterone inhibitor use and clinical outcomes. Data from 9222 chronic heart failure patients of the ESC-HFA-EORP Heart Failure Long-Term Registry. Eur J Heart Fail 2020;22:1378–89.

43. Butler J, Anker SD, Lund LH, Coats AJS, Filippatos G, Siddiqi TJ, et al. Patiromer for the management of hyperkalemia in heart failure with reduced ejection fraction: the DIAMOND trial. Eur Heart J 2022;43:4362–73.

44. Butler J, Anker SD, Siddiqi TJ, Coats AJS, Dorigotti F, Filippatos G, et al. Patiromer for the management of hyperkalaemia in patients receiving renin-angiotensin-aldosterone system inhibitors for heart failure: design and rationale of the DIAMOND trial. Eur J Heart Fail 2022;24:230–8.

45. Greene SJ, Maggioni AP, Fonarow GC, Solomon SD, Bohm M, Kandra A, et al. Clinical profile and prognostic significance of natriuretic peptide trajectory following hospitalization for worsening chronic heart failure: findings from the ASTRONAUT trial. Eur J Heart Fail 2015;17:98–108.

46. Tsutsui H, Albert NM, Coats AJS, Anker SD, Bayes-Genis A, Butler J, et al. Natriuretic peptides: role in the diagnosis and management of heart failure: a scientific statement from the Heart Failure Association of the European Society of Cardiology, Heart Failure Society of America and Japanese Heart Failure Society. Eur J Heart Fail 2023;25:616–31.

47. Adamo M, Pagnesi M, Mebazaa A, Davison B, Edwards C, Tomasoni D, et al. NT-proBNP and high-intensity care for acute heart failure: the STRONG-HF trial. Eur Heart J 2023;44:1497–62.

48. Mullens W, Martens P, Testani JM, Tang WHW, Skouri H, Verbrugge FH, et al. Renal effects of guideline-directed medical therapies in heart failure: a consensus document from the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2022;24:603–19.

49. Mullens W, Damman K, Testani JM, Martens P, Mueller C, Lassus J, et al. Evaluation of kidney function throughout the heart failure trajectory - a position statement from the Heart Failure Association of the European Society of Cardiology. Eur J Heart Fail 2020;22:584–603.

50. Metra M, Davison B, Bettari L, Sun H, Edwards C, Lazzarini V, et al. Is worsening renal function an ominous prognostic sign in patients with acute heart failure? The role of congestion and its interaction with renal function. Circ Heart Fail 2012;5:54–62.